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Novruzov E, Peters HA, Jannusch K, Kobbe G, Dietrich S, Fischer JC, Rox J, Antoch G, Giesel FL, Antke C, Baermann BN, Mamlins E. The predictive power of baseline metabolic and volumetric [ 18F]FDG PET parameters with different thresholds for early therapy failure and mortality risk in DLBCL patients undergoing CAR-T-cell therapy. Eur J Radiol Open 2025; 14:100619. [PMID: 39803388 PMCID: PMC11719856 DOI: 10.1016/j.ejro.2024.100619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 12/03/2024] [Accepted: 12/07/2024] [Indexed: 01/16/2025] Open
Abstract
Objective [18F]FDG imaging is an integral part of patient management in CAR-T-cell therapy for recurrent or therapy-refractory DLBCL. The calculation methods of predictive power of specific imaging parameters still remains elusive. With this retrospective study, we sought to evaluate the predictive power of the baseline metabolic parameters and tumor burden calculated with automated segmentation via different thresholding methods for early therapy failure and mortality risk in DLBCL patients. Materials and methods Eighteen adult patients were enrolled, who underwent CAR-T-cell therapy accompanied by at least one pretherapeutic and two posttherapeutic [18F]FDG PET scans within 30 and 90 days between December 2018 and October 2023. We performed single-click automatic segmentation within VOIs in addition to extracting the SUV parameters to calculate the MTVs and TLGs by applying thresholds based on the concepts of a fixed absolute threshold with an SUVmax > 4.0, a relative absolute threshold with an isocontour of > 40 % of the SUVmax, a background threshold involving the addition of the liver SUV value and its 2 SD values, and only the liver SUV value. Results For early therapy failure, baseline metabolic parameters such as the SUVmax, SUVpeak and SUVmean tended to have greater predictive power than did the baseline metabolic burden. However, the baseline metabolic burden was superior in the prediction of mortality risk regardless of the thresholding method used. Conclusion This study revealed that automated delineation methods of metabolic tumor burden using different thresholds do not differ in outcome substantially. Therefore, the current clinical standard with a fixed absolute threshold value of SUV > 4.0 seems to be a feasible option.
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Affiliation(s)
- Emil Novruzov
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
| | - Helena A. Peters
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
| | - Kai Jannusch
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
| | - Guido Kobbe
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
- Department of Hematology, Oncology and Clinical Immunology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Sascha Dietrich
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
- Department of Hematology, Oncology and Clinical Immunology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Johannes C. Fischer
- Institute for Transplantation Diagnostics and Cellular Therapy, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Jutta Rox
- Institute for Transplantation Diagnostics and Cellular Therapy, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Gerald Antoch
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
| | - Frederik L. Giesel
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
- Institute for Radiation Sciences, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Christina Antke
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
| | - Ben-Niklas Baermann
- Department of Hematology, Oncology and Clinical Immunology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Eduards Mamlins
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, Düsseldorf 40225, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Germany
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Tie X, Shin M, Lee C, Perlman SB, Huemann Z, Weisman AJ, Castellino SM, Kelly KM, McCarten KM, Alazraki AL, Hu J, Cho SY, Bradshaw TJ. Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Using a Longitudinally Aware Segmentation Network. Radiol Artif Intell 2025; 7:e240229. [PMID: 39969278 DOI: 10.1148/ryai.240229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2025]
Abstract
Purpose To develop a longitudinally aware segmentation network (LAS-Net) that can quantify serial PET/CT images for pediatric patients with Hodgkin lymphoma. Materials and Methods This retrospective study included baseline (PET1) and interim (PET2) PET/CT images from 297 pediatric patients enrolled in two Children's Oncology Group clinical trials (AHOD1331 and AHOD0831). The internal dataset included 200 patients (enrolled between March 2015 and August 2019; median age, 15.4 years [range, 5.6-22.0 years]; 107 male), and the external testing dataset included 97 patients (enrolled between December 2009 and January 2012; median age, 15.8 years [range, 5.2-21.4 years]; 59 male). LAS-Net incorporates longitudinal cross-attention, allowing relevant features from PET1 to inform the analysis of PET2. The model's lesion segmentation performance on PET1 images was evaluated using Dice coefficients, and lesion detection performance on PET2 images was evaluated using F1 scores. In addition, quantitative PET metrics, including metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in PET1, as well as qPET and percentage difference between baseline and interim maximum standardized uptake value (∆SUVmax) in PET2, were extracted and compared against physician-derived measurements. Agreement between model and physician-derived measurements was quantified using Spearman correlation, and bootstrap resampling was used for statistical analysis. Results LAS-Net detected residual lymphoma on PET2 scans with an F1 score of 0.61 (precision/recall: 0.62/0.60), outperforming all comparator methods (P < .01). For baseline segmentation, LAS-Net achieved a mean Dice score of 0.77. In PET quantification, LAS-Net's measurements of qPET, ∆SUVmax, MTV, and TLG were strongly correlated with physician measurements, with Spearman ρ values of 0.78, 0.80, 0.93, and 0.96, respectively. The quantification performance remained high, with a slight decrease, in an external testing cohort. Conclusion LAS-Net demonstrated significant improvements in quantifying PET metrics across serial scans in pediatric patients with Hodgkin lymphoma, highlighting the value of longitudinal awareness in evaluating multi-time-point imaging datasets. Keywords: Pediatrics, PET/CT, Lymphoma, Segmentation, Quantification, Supervised Learning, Convolutional Neural Network (CNN), Quantitative PET, Longitudinal Analysis, Deep Learning, Image Segmentation Supplemental material is available for this article. Clinical trial registration no. NCT02166463 and NCT01026220 © RSNA, 2025 See also commentary by Khosravi and Gichoya in this issue.
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Affiliation(s)
- Xin Tie
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Muheon Shin
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
| | - Changhee Lee
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
| | - Scott B Perlman
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
- University of Wisconsin Carbone Comprehensive Cancer Center, Madison, Wis
| | - Zachary Huemann
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
| | - Amy J Weisman
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Sharon M Castellino
- Department of Pediatrics, Emory University School of Medicine, Atlanta, Ga
- Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Atlanta, Ga
| | - Kara M Kelly
- Department of Pediatric Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY
- Department of Pediatrics, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY
| | - Kathleen M McCarten
- Department of Pediatric Radiology, Imaging and Radiation Oncology, Core Rhode Island, Lincoln, RI
| | - Adina L Alazraki
- Department of Radiology, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, Ga
| | - Junjie Hu
- Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, Wis
- Department of Computer Science, School of Computer, Data and Information Sciences, University of Wisconsin, Madison, Wis
| | - Steve Y Cho
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
- University of Wisconsin Carbone Comprehensive Cancer Center, Madison, Wis
| | - Tyler J Bradshaw
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705
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Haque F, Chen A, Lay N, Carrasquillo J, Mena E, Lindenberg L, Segal JE, Eclarinal PC, Talvacchio S, Derkyi A, Choyke PL, Pacak K, Kaplan RN, Lin FI, Turkbey B, Harmon SA. Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohorts. Comput Biol Med 2025; 190:110052. [PMID: 40127518 DOI: 10.1016/j.compbiomed.2025.110052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 02/11/2025] [Accepted: 03/18/2025] [Indexed: 03/26/2025]
Abstract
BACKGROUND This study develops a deep learning-based automated lesion segmentation model for whole-body 3D18F-fluorodeoxyglucose (FDG)-Position emission tomography (PET) with computed tomography (CT) images agnostic to disease location and site. METHOD A publicly available lesion-annotated dataset of 1014 whole-body FDG-PET/CT images was used to train, validate, and test (70:10:20) eight configurations with 3D U-Net as the backbone architecture. The best-performing model on the test set was further evaluated on 3 different unseen cohorts consisting of osteosarcoma or neuroblastoma (OS cohort) (n = 13), pediatric solid tumors (ST cohort) (n = 14), and adult Pheochromocytoma/Paraganglioma (PHEO cohort) (n = 40). Both lesion-level and patient-level statistical analyses were conducted to validate the performance of the model on different cohorts. RESULTS The best performing 3D full resolution nnUNet model achieved a lesion-level sensitivity and DISC of 71.70 % and 0.40 for the test set, 97.83 % and 0.73 for ST, 40.15 % and 0.36 for OS, and 78.37 % and 0.50 for the PHEO cohort. For the test set and PHEO cohort, the model has missed small volume and lower uptake lesions (p < 0.01), whereas no statistically significant differences (p > 0.05) were found in the false positive (FP) and false negative lesions volume and uptake for the OS and ST cohort. The predicted total lesion glycolysis is slightly higher than the ground truth because of FP calls, which experts can easily check and reject. CONCLUSION The developed deep learning-based automated lesion segmentation AI model which utilizes 3D_FullRes configuration of the nnUNet framework showed promising and reliable performance for the whole-body FDG-PET/CT images.
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Affiliation(s)
- Fahmida Haque
- Artificial Intelligence Resource, National Cancer Institute, National Institute of Health, Bethesda, MD, 20814, USA
| | - Alex Chen
- Artificial Intelligence Resource, National Cancer Institute, National Institute of Health, Bethesda, MD, 20814, USA
| | - Nathan Lay
- Artificial Intelligence Resource, National Cancer Institute, National Institute of Health, Bethesda, MD, 20814, USA
| | - Jorge Carrasquillo
- Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Esther Mena
- Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Liza Lindenberg
- Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Julia E Segal
- Section on Medical Neuroendocrinology National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Philip C Eclarinal
- Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Sara Talvacchio
- Section on Medical Neuroendocrinology National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Alberta Derkyi
- Section on Medical Neuroendocrinology National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA
| | - Peter L Choyke
- Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Karel Pacak
- Section on Medical Neuroendocrinology National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, 20892, MD, USA; AKESO, Prague 5, Czech Republic
| | - Rosandra N Kaplan
- Pediatric Oncology Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Frank I Lin
- Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Baris Turkbey
- Artificial Intelligence Resource, National Cancer Institute, National Institute of Health, Bethesda, MD, 20814, USA; Molecular Imaging Branch, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA
| | - Stephanie A Harmon
- Artificial Intelligence Resource, National Cancer Institute, National Institute of Health, Bethesda, MD, 20814, USA
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Pennock M, Brodin NP, Velten C, Gjini M, Ohri N, Guha C, Kalnicki S, Tome WA, Garg MK, Kabarriti R. Pre-treatment tumour PET metrics and clinical outcomes of anal cancer in patients living with and without HIV. Acta Oncol 2025; 64:564-573. [PMID: 40275508 DOI: 10.2340/1651-226x.2025.40680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 02/19/2025] [Indexed: 04/26/2025]
Abstract
BACKGROUND/PURPOSE To investigate if pre-treatment tumour positron-emission tomography (PET) metrics' prognostic efficacy changes with HIV or viral load (VL) in anal squamous cell carcinoma (ASCC). MATERIALS AND METHODS Consecutive patients treated with definitive radiation therapy (RT) for non-metastatic ASCC from 2005 to 2021 at one institution were retrospectively identified. Patient demographic and clinical data, including HIV status and pre-treatment VL, were tabulated. Pre-treatment PET metrics were calculated with semi-automatic gradient-based segmentation algorithms. Cox-proportional-hazard and Kaplan-Meier modelling were used to investigate tumour PET metrics and outcomes: overall survival (OS), progression-free survival (PFS), and locoregional control (LRC). RESULTS A total of 175 patients were included: 110 HIV-negative and 65 patients living with HIV (PLWH). Nineteen PLWH had detectable pre-treatment VL. Median follow-up was 58 months (interquartile range [IQR]: 28-99), with 28 locoregional failures and 31 deaths. Five-year LRC, PFS, and OS was 84%, 73%, and 86%, respectively. There was no significant difference in LRC, PFS, or OS between HIV-negative patients and PLWH. 156 patients had available pre-treatment PET scans. Metabolic tumour volume and total lesion glycolysis were significantly associated with LRC and PFS on multivariate Cox analysis for the entire cohort (p ≤ 0.02), and HIV-negative patients on Cox sub-group analysis (p ≤ 0.01). No association between PET metrics and outcomes was seen for PLWH. INTERPRETATION Outcomes were comparable between HIV-negative patients and PLWH. Pre-treatment PET metrics were validated as significantly predicting outcomes for the entire cohort and HIV-negative patients, not PLWH. This may be from small numbers of PLWH patients, or non-specific uptake in patients with uncontrolled HIV reducing PET's prognostic efficacy.
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Affiliation(s)
- Michael Pennock
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - N Patrik Brodin
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Christian Velten
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Megi Gjini
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Nitin Ohri
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Chandan Guha
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Shalom Kalnicki
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Wolfgang A Tome
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Madhur K Garg
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY
| | - Rafi Kabarriti
- Departments of Radiation Oncology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY.
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Fan Y, Feigenberg SJ, Simone CB. Current and Future Applications of PET Radiomics in Radiation Oncology. PET Clin 2025; 20:185-193. [PMID: 39915189 PMCID: PMC11922665 DOI: 10.1016/j.cpet.2025.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2025]
Abstract
This review delves into the principles of PET imaging and radiomics, emphasizing their importance in detecting, staging, and monitoring various cancers. It highlights the clinical applications of PET radiomics in oncology, showcasing its impact on personalized cancer care. Additionally, the review addresses challenges such as standardizing PET radiomics, integrating multiomics data, and ethical concerns in clinical decision-making. Future directions are also discussed, including broader applications of PET radiomics in clinical trials, artificial intelligence integration for automated analysis, and incorporating multiomics data for a comprehensive understanding of tumor biology.
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Affiliation(s)
- Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3700 Hamilton Walk, Philadelphia, PA 19104-6116, USA.
| | - Steven J Feigenberg
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, 2 West, Philadelphia, PA 19104, USA
| | - Charles B Simone
- New York Proton Center; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
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Pizzuto DA, Castello A, Chiappetta M, Castellani M, Annunziata S, Campanella A, Calabrese G, Cattaneo M, Rosso L, Cusumano G, Lococo F, Mendogni P. The Role of [ 18F]F-FDG PET/CT for Predicting Histology and Prognosis in Patients with Thymic Lesions. Mol Diagn Ther 2025; 29:239-248. [PMID: 39777612 DOI: 10.1007/s40291-024-00767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/11/2024] [Indexed: 01/11/2025]
Abstract
OBJECTIVES To investigate whether 18F-fluorodeoxyglucose positron emission tomography-computed tomography ([18F]F-FDG PET/CT) metabolic parameters were associated with histology and to assess their prognostic role in patients with thymic lesions. PATIENTS AND METHODS In total, 116 patients (49/67 M/F; mean age 59.5 years) who underwent preoperative [18F]F-FDG PET/CT and thymectomy from 2012 to 2022 were retrospectively analyzed. Associations between histology and metabolic parameters (maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), peak standardized uptake value (SUVpeak), total lesion glycolysis (TLG), metabolic tumor volume (MTV), ratio between target lesion and liver SUVmax (rPET), quotient of SUVpeak in the tumor residual and SUVmean in a 20-cm3 volume of interest (qPET), and tumor-to-mediastinum (T/M) were analyzed. Freedom from recurrence (FFR) was determined and compared using the Kaplan-Meier and the log-rank test. The median follow-up was 38 months (range 14-72 months). RESULTS In total, 27 thymic hyperplasia, 41 low-risk thymomas (LRT) (types A, AB, and B1), and 48 high-risk thymomas (HRT) (B2, B3 thymoma, and carcinoma) were included. SUVmax, SUVmean, SUVpeak, rPET, qPET, and T/M were significantly higher in HRT than LRT and hyperplasia (p < 0.001). TLG and MTV were significantly higher in patients with LRT (p < 0.001). Only rPET, qPET, and T/M remained significantly higher in HRT than in LRT subgroups (p = 0.042, p = 0.049, and p = 0.028, respectively). SUVmax, SUVmean, and SUVpeak cutoffs of < 4.3, < 2.87, and 4.03, respectively, significantly distinguished patients with longer FFR (p = 0.009, p = 0.05, and p = 0.05). CONCLUSIONS Positron emission tomography (PET) metabolic parameters could help to differentiate thymic histotypes. Standardized uptake value (SUV)-based parameters appear promising to predict recurrent disease.
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Affiliation(s)
- Daniele Antonio Pizzuto
- Nuclear Medicine Unit, GSTeP Radiopharmacy-TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
| | - Angelo Castello
- Department of Nuclear Medicine, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, 20122, Milan, Italy
| | | | - Massimo Castellani
- Department of Nuclear Medicine, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, 20122, Milan, Italy
| | - Salvatore Annunziata
- Nuclear Medicine Unit, GSTeP Radiopharmacy-TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
| | - Annalisa Campanella
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
- Thoracic Surgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
| | - Giuseppe Calabrese
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
- Thoracic Surgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
| | - Margherita Cattaneo
- Thoracic Surgery and Lung Transplantation, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, 20122, Milan, Italy
| | - Lorenzo Rosso
- Thoracic Surgery and Lung Transplantation, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, 20122, Milan, Italy
| | - Giacomo Cusumano
- General Thoracic Surgery Unit, Azienda Ospedaliero Universitaria Policlinico "G. Rodolico-San Marco", 95100, Catania, Italy
- Department of Surgery and Medical-Surgical Specialties, University of Catania, 95100, Catania, Italy
| | - Filippo Lococo
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
- Thoracic Surgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
| | - Paolo Mendogni
- Thoracic Surgery and Lung Transplantation, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, 20122, Milan, Italy
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Wehrle CJ, Chávez-Villa M, Byrne M, Kusakabe J, Gross A, Mahajan P, Ruffolo L, Whitsett Linganna M, Sobotka A, Naffouje S, Khalil M, Pita A, Fujiki M, Tomiyama K, Schlegel A, Kwon DCH, Line PD, Miller C, Hashimoto K, Hernandez-Alejandro R, Aucejo F. Pretransplant metabolic tumor volume predicts recurrence following liver transplantation for colorectal metastasis: A multicenter study. Liver Transpl 2025; 31:298-310. [PMID: 39526884 DOI: 10.1097/lvt.0000000000000535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 10/14/2024] [Indexed: 11/16/2024]
Abstract
Liver transplant (LT) for colorectal cancer liver metastases (CRLM) is increasingly popular, yet the ideal selection criteria remain unknown. Pretransplant positron emission tomography (PET) metabolic tumor volume (MTV) has been described as predicting recurrence, with a proposed cutoff of MTV ≥70 cm 3 . This approach has not been validated. Patients undergoing LT for CRLM at 2 academic transplant centers (January 1, 2017, to December 1, 2023) were included. PET-MTV was calculated by a staff radiologist from the most recent PET-scan before LT using the published protocol. Twenty-six patients were included. Median follow-up was 609 days (IQR 320-1069) and from PET to LT was 1.9 months (1.3-2.6). Nearly all (n=24, 92.3%) received living donor transplantation. Absolute recurrence rate was 30.8% (n=8). Actuarial unadjusted 1- and 2-year recurrence-free survival (RFS) were 83% (n=15/18) and 62% (n=8/13); 1- and 2-year overall survival were 100% (n=18/18) and 85% (n=11/13). The incidence of recurrence-per-year follow-up was 0.35 when MTV ≥70 cm 3 versus 0.10 if MTV <70 cm 3 ( P <0.001). Median RFS using Kaplan-Meier product-estimate was 0.83 years (95% CI: 0.43-1.23) in MTV≥70 cm 3 versus 4.1 years (95% CI: 2.90-5.22) when MTV<70 cm 3 ( p <0.001); this was also associated with improved overall survival ( p =0.003). MTV>70 cm 3 demonstrated HR=2.42 (95% CI: 2.2-62.2, p =0.006) for association with RFS on univariate Cox-proportional hazards analysis, and an AUC=0.771 (95% CI: 0.560-0.981) for predicting recurrence ( p =0.030). Nineteen patients (69.2%) had histologically viable tumors, which were associated with recurrence (43% vs. 0%, p =0.039) and reduced RFS (log-rank p =0.019). PET-MTV was associated with the presence of histologically viable tumor (AUC=0.763, 95% CI: 0.583-0.944). PET-MTV ≥70 cm 3 was associated with reduced RFS and overall survival after LT for CRLM, confirming findings from the Norway group. This is likely due to its ability to identify residual viable tumors, which are independently associated with recurrence. PET-MTV should be a key selection criterion prior to LT for CRLM.
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Affiliation(s)
- Chase J Wehrle
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Mariana Chávez-Villa
- Department of Surgery, Division of Transplantation, University of Rochester Medical Center, Rochester, New York, USA
| | - Matthew Byrne
- Department of Surgery, Division of Transplantation, University of Rochester Medical Center, Rochester, New York, USA
| | - Jiro Kusakabe
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Abby Gross
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
- Department of Quantitative Health Sciences Affiliation, Cleveland Clinic, Cleveland, Ohio, USA
| | - Paresh Mahajan
- Department of Nuclear Medicine, Cleveland Clinic, Imaging Institute, Cleveland, Ohio, USA
| | - Luis Ruffolo
- Department of Surgery, Division of Transplantation, University of Rochester Medical Center, Rochester, New York, USA
| | - Maureen Whitsett Linganna
- Department of Surgery, Division of Transplantation, University of Rochester Medical Center, Rochester, New York, USA
| | - Annie Sobotka
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Samer Naffouje
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Mazhar Khalil
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Alejandro Pita
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Masato Fujiki
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Koji Tomiyama
- Department of Surgery, Division of Transplantation, University of Rochester Medical Center, Rochester, New York, USA
| | - Andrea Schlegel
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - David C H Kwon
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Pal-Dag Line
- Department of Transplantation, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Charles Miller
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Koji Hashimoto
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Roberto Hernandez-Alejandro
- Department of Gastroenterology, Hepatology & Nutrition, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
| | - Federico Aucejo
- Department of General Surgery, Cleveland Clinic, Digestive Diseases and Surgery Institute, Cleveland, Ohio, USA
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8
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Hindso TG, Martinussen T, Bjerrum CW, Keller SH, Loft A, Sjøl MB, Nissen K, Faber C, Donia M, Svane IM, Ellebaek E, Heegaard S, Kiilgaard JF, Madsen K. 18F-FDG PET/CT assessment of metabolic tumor burden predicts survival in patients with metastatic posterior uveal melanoma. Sci Rep 2025; 15:4110. [PMID: 39901052 PMCID: PMC11790917 DOI: 10.1038/s41598-025-88625-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Accepted: 01/29/2025] [Indexed: 02/05/2025] Open
Abstract
The prognostic value of metabolic tumor burden parameters obtained from 18F-FDG PET/CT imaging was evaluated in this retrospective national multicenter study of patients with metastatic posterior uveal melanoma (PUM) and compared to the largest diameter of the largest metastatic lesion (LDLM) and the American Joint Committee on Cancer (AJCC) staging system. The Maximal Standard Uptake Value (SUVmax), Metabolic Tumor Volume (MTV), and Total Lesion Glycolysis (TLG) were obtained in 106 patients. Higher values of SUVmax (p = 0.007, log-rank), MTV (p < 0.001, log-rank), and TLG (p < 0.001, long-rank) were associated with shorter survival. The three parameters were also independent predictors in the multivariate Cox model, while the AJCC staging turned insignificant. Time-dependent positive predictive value (PPV) analysis and Receiver Operating Characteristics (ROC) curves showed that MTV (Area Under the Curve (AUC) = 0.78), TLG (AUC = 0.78), and LDLM (AUC = 0.76) were good predictors of 1-year survival. For the subset of 97 patients with liver metastases, the corresponding regional measurements in the liver tended to be even better predictors. In conclusion, MTV and TLG were found to be better predictors of survival in metastatic PUM than the AJCC staging system, but when LDLM was used as a continuous variable it showed an equally good prediction of 1-year survival.
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Affiliation(s)
- Tine Gadegaard Hindso
- Department of Ophthalmology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark.
| | - Torben Martinussen
- Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, Copenhagen K, 1014, Denmark
| | - Camilla Wium Bjerrum
- Department of Radiology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Sune Høgild Keller
- Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Annika Loft
- Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Mette Bagger Sjøl
- Department of Ophthalmology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Kristoffer Nissen
- Department of Ophthalmology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Carsten Faber
- Department of Ophthalmology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Marco Donia
- Department of Oncology, National Center for Cancer Immune Therapy (CCIT-DK), Copenhagen University Hospital - Herlev and Gentofte, Borgmester Ib Juuls Vej 13, Herlev, 2730, Denmark
| | - Inge Marie Svane
- Department of Oncology, National Center for Cancer Immune Therapy (CCIT-DK), Copenhagen University Hospital - Herlev and Gentofte, Borgmester Ib Juuls Vej 13, Herlev, 2730, Denmark
| | - Eva Ellebaek
- Department of Oncology, National Center for Cancer Immune Therapy (CCIT-DK), Copenhagen University Hospital - Herlev and Gentofte, Borgmester Ib Juuls Vej 13, Herlev, 2730, Denmark
| | - Steffen Heegaard
- Department of Ophthalmology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
- Department of Pathology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Jens Folke Kiilgaard
- Department of Ophthalmology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
| | - Karine Madsen
- Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen Ø, 2100, Denmark
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9
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Hong Y, Kang YK, Park EB, Kim MS, Choi Y, Lee S, Lee CH, Kim JH, Kim M, Paeng JC, Kim CH. Incorporation of whole-body metabolic tumor burden into current prognostic models for nonsmall cell lung cancer patients with spine metastasis. Spine J 2025; 25:306-316. [PMID: 39341575 DOI: 10.1016/j.spinee.2024.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 08/05/2024] [Accepted: 09/14/2024] [Indexed: 10/01/2024]
Abstract
BACKGROUND CONTEXT Numerous prognostic models are utilized for surgical decision and prognostication in metastatic spine tumors. However, these models often fail to consider the whole-body tumor burden into account, which may be crucial for the prognosis of metastatic cancers. A potential surrogate marker for tumor burden, whole-body metabolic tumor burden (wMTB), can be calculated from total lesion glycolysis (TLG) obtained from 18F-Fludeoxyglucose positive emission tomography (18F-FDG PET) images. PURPOSE We aimed to improve prognostic power of current models by incorporating wMTB for nonsmall cell lung cancer (NSCLC) patients with spine metastases. DESIGN Retrospective analysis using a review of electrical medical records and survival data. PATIENT SAMPLE In this study, we included 74 NSCLC patients with image proven spine metastases. OUTCOME MEASURES Increase in Integrated Discrimination Improvement (IDI) index after incorporation of wMTB into prognostic scores. METHODS Enrolled patients' baseline data, cancer characteristics and survival status were retrospectively collected. Five widely used prognostic scores (Tomita, Katagiri, Tokuhashi, Global Spine Tumor Study Group [GSTSG], New England Spine Metastasis Score [NESMS]), and TLG indexes were calculated for all patients. The relationships among survival time, prognostic models and TLG values were analyzed. Improvement of prognostic power was validated by incorporating significant TLG index into significant current models. RESULTS Among current prognostic models, Tomita (EGFR wild-type), Katagiri, GSTSG and Tokuhashi were significantly related to patient survival. Among TLG indexes, LogTLG3 was significantly related to survival. Incorporation of LogTLG3 into significant prognostic models resulted in positive IDI index until 3 years in all models. CONCLUSIONS This study showed that incorporation of wMTB improved prognostic power of current prognostic models of metastatic spine tumors.
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Affiliation(s)
- Yoontae Hong
- Department of Neurosurgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yeon-Koo Kang
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eun Bi Park
- Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Min-Sung Kim
- Department of Neurosurgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yunhee Choi
- Division of Medical Statistics, Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Siyoung Lee
- Department of Orthopaedic Surgery, Derriford Hospital, University Hospitals Plymouth NHS Trust, Plymouth, United Kingdom
| | - Chang-Hyun Lee
- Department of Neurosurgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun-Hoe Kim
- Department of Neurosurgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Miso Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jin Chul Paeng
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chi Heon Kim
- Department of Neurosurgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
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10
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Dall'Olio FG, Zrafi W, Roelants V, Ambrosini V, Fourquet A, Mitea C, Passiglia F, Bauckneht M, Bonardel G, Conci N, Benitez JC, Arena V, Namour C, Naigeon M, Monnet I, Beshiri K, Hoton D, Dursun S, Danlos FX, Argalia G, Aldea M, Rovera G, Derosa L, Iebba V, Gietema HA, Gounant V, Lacroix V, Remon J, Gautheret D, Chaput N, Job B, Kannouche PL, Velasco-Nuño M, Zitvogel L, Cella E, Chícharo de Freitas JR, Vasseur D, Bettaieb MA, Tagliamento M, Hendriks L, Italiano A, Planchard D, Marabelle A, Barlesi F, Novello S, De Andreis D, Aboubakar Nana F, Ardizzoni A, Zalcman G, Garcia C, Besse B. Metabolic Tumor Volume Assessed by 18F FDG-PET CT Scan as a Predictive Biomarker for Immune Checkpoint Blockers in Advanced NSCLC and Its Biological Correlates. Clin Cancer Res 2025; 31:352-364. [PMID: 39437011 DOI: 10.1158/1078-0432.ccr-24-1993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 09/02/2024] [Accepted: 10/18/2024] [Indexed: 10/25/2024]
Abstract
PURPOSE This study aimed to explore metabolic tumor volume (MTV) as assessed by 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG-PET/CT) and understand its biological meaning in patients with non-small cell lung cancer (NSCLC) exposed to immune checkpoint blockers (ICB). EXPERIMENTAL DESIGN In this study, patients with advanced NSCLC and a positive PET scan within 42 days of first-line treatment were enrolled in 11 institutions across four countries. Total MTV (tMTV) was analyzed, with a 42% maximum standardized uptake value threshold. Survival was analyzed according to high tMTV (≥median). Plasma proteomic profile, whole exome, transcriptome, and other analyses were performed on monocentric cohorts to explore its biological correlates. RESULTS Of the 518 patients included, 167 received ICBs, 257 had chemotherapy plus ICBs, and 94 had chemotherapy. Median tMTV was 99 cm3. Median overall survival (OS) for patients with high tMTV treated with ICBs was 11.4 vs. 29.6 months (P < 0.0012) for those with low tMTV. In patients who received chemotherapy-ICB, tMTV did not correlate with OS (P = 0.099). In patients with programmed death-ligand 1 (PD-L1) ≥1% and high tMTV, chemotherapy-ICB combination was associated with longer OS compared with ICBs alone (20 vs. 11.4 months; P = 0.026), while no survival differences were observed in the low tMTV group. High tMTV correlated (and its detrimental effect seems to be driven) with a specific proteomic profile and increase in genomic instability. CONCLUSIONS Our analysis indicates high tMTV is linked to an increase in systemic inflammation, specific cytokines production, and chromosomal instability. tMTV may serve as one of the biomarkers to select the best upfront strategy in patients with PD-L1-positive advanced NSCLC.
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Affiliation(s)
- Filippo G Dall'Olio
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
- METSY Laboratory Metabolic and Systemic Aspects of Oncogenesis for New Therapeutic Approaches, UMR 9018 CNRS and Université Paris-Saclay, Villejuif, France
| | - Wael Zrafi
- Department of Biostatistics and Bioinformatics, Gustave Roussy, Villejuif, France
| | - Veronique Roelants
- Nuclear Medicine Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Valentina Ambrosini
- Nuclear Medicine, Alma Mater Studiorum University of Bologna, Bologna, Italy
- Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Aloyse Fourquet
- Department of Nuclear Medicine, Hôpital Bichat-Claude Bernard, AP-HP.Nord, Univesité Paris Cité, Paris, France
| | - Cristina Mitea
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
- GROW-School for Oncology and Reproduction, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Francesco Passiglia
- Department of Oncology, University of Turin, San Luigi Hospital, Orbassano, Italy
| | - Matteo Bauckneht
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genova, Italy
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Gerald Bonardel
- Department of Nuclear Medicine, Centre Cardiologique du Nord, Saint-Denis, France
| | - Nicole Conci
- Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Jose Carlos Benitez
- Medical Oncology Intercenter Unit, Regional and Virgen de la Victoria University Hospitals, IBIMA, Malaga, Spain
- Research Biomedical Institute of Malaga (IBIMA), Malaga, Spain
| | - Vincenzo Arena
- Nuclear Medicine Division, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Céline Namour
- Thoracic Oncology Department-Early Phases Unit CIC-1425 Inserm, Institut du Cancer AP-HP.Nord, Hôpital Bichat-Claude Bernard, Paris, France
| | - Marie Naigeon
- Laboratoire d'Immunomonitoring en Oncologie, INSERM US23, CNRS UMS 3655, Gustave Roussy, Villejuif, France
- Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
- Faculté de Pharmacie, Université Paris-Saclay, Orsay, France
| | - Isabelle Monnet
- Pneumology Department, Intercommunal Hospital of Creteil (CHI), Creteil, France
| | - Kristi Beshiri
- Département d'Innovation Thérapeutique et d'Essais Précoces (DITEP), Gustave Roussy, Université Paris Saclay, Villejui, France
| | - Delphine Hoton
- Department of Pathology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Safiye Dursun
- Department of Pulmonary Diseases, GROW-School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, the Netherlands
| | - François Xavier Danlos
- Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
- Gustave Roussy, Villejuif, France
| | - Giulia Argalia
- Nuclear Medicine, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Mihaela Aldea
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
- Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
| | - Guido Rovera
- Nuclear Medicine Division, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Lisa Derosa
- Gustave Roussy, Villejuif, France
- Institut National de la Santé Et de la Recherche Médicale (INSERM) U1015, Equipe Labellisée - Ligue Nationale Contre le Cancer, Villejuif, France
- Faculté de Médecine, Université Paris-Saclay, Kremlin-Bicetre, France
| | - Valerio Iebba
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Hester A Gietema
- GROW-School for Oncology and Reproduction, Maastricht University Medical Center, Maastricht, the Netherlands
- Maastricht University Medical Centre, Maastricht University, Maastricht, the Netherlands
| | - Valerie Gounant
- Thoracic Oncology Department-Early Phases Unit CIC-1425 Inserm, Institut du Cancer AP-HP.Nord, Hôpital Bichat-Claude Bernard, Paris, France
| | - Valérie Lacroix
- Department of Cardiovascular and Thoracic Surgery, IREC, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Jordi Remon
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
| | - Daniel Gautheret
- Department of Biostatistics and Bioinformatics, Gustave Roussy, Villejuif, France
| | - Nathalie Chaput
- Laboratoire d'Immunomonitoring en Oncologie, INSERM US23, CNRS UMS 3655, Gustave Roussy, Villejuif, France
- Faculté de Pharmacie, Université Paris-Saclay, Orsay, France
| | - Bastien Job
- Department of Biostatistics and Bioinformatics, Gustave Roussy, Villejuif, France
| | | | - Monica Velasco-Nuño
- Department of Nuclear Medicine Hospital HM Nou Delfos, HM Hospitales, Barcelona, Spain
| | - Laurence Zitvogel
- Gustave Roussy, Villejuif, France
- Institut National de la Santé Et de la Recherche Médicale (INSERM) U1015, Equipe Labellisée - Ligue Nationale Contre le Cancer, Villejuif, France
- Faculté de Médecine, Université Paris-Saclay, Kremlin-Bicetre, France
- Center of Clinical Investigations BIOTHERIS, INSERM CIC1428, Villejuif, France
| | - Eugenia Cella
- Dipartimento di Medicina Interna e Specialità Mediche (DiMI), Università degli Studi di Genova, Genoa, Italy
| | | | - Damien Vasseur
- Department of Medical Biology and Pathology, Gustave Roussy, Villejuif, France
| | | | - Marco Tagliamento
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
- Dipartimento di Medicina Interna e Specialità Mediche (DiMI), Università degli Studi di Genova, Genoa, Italy
| | - Lizza Hendriks
- Department of Pulmonary Diseases, GROW-School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, the Netherlands
| | - Antoine Italiano
- Département d'Innovation Thérapeutique et d'Essais Précoces (DITEP), Gustave Roussy, Université Paris Saclay, Villejui, France
| | - David Planchard
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
- Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
| | | | - Fabrice Barlesi
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
- Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
| | - Silvia Novello
- Department of Oncology, University of Turin, San Luigi Hospital, Orbassano, Italy
| | | | | | - Andrea Ardizzoni
- Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Gerard Zalcman
- Thoracic Oncology Department-Early Phases Unit CIC-1425 Inserm, Institut du Cancer AP-HP.Nord, Hôpital Bichat-Claude Bernard, Paris, France
| | - Camilo Garcia
- Nuclear Medicine Department, Gustave Roussy, Villejuif, France
| | - Benjamin Besse
- Cancer Medicine Department, Gustave Roussy, Villejuif, France
- Laboratoire d'Immunomonitoring en Oncologie, INSERM US23, CNRS UMS 3655, Gustave Roussy, Villejuif, France
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11
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Thunold S, Hernes E, Farooqi S, Öjlert ÅK, Francis RJ, Nowak AK, Szejniuk WM, Nielsen SS, Cedres S, Perdigo MS, Sørensen JB, Meltzer C, Mikalsen LTG, Helland Å, Malinen E, Haakensen VD. Outcome prediction based on [18F]FDG PET/CT in patients with pleural mesothelioma treated with ipilimumab and nivolumab +/- UV1 telomerase vaccine. Eur J Nucl Med Mol Imaging 2025; 52:693-707. [PMID: 39133306 PMCID: PMC11732904 DOI: 10.1007/s00259-024-06853-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 07/16/2024] [Indexed: 08/13/2024]
Abstract
PURPOSE The introduction of immunotherapy in pleural mesothelioma (PM) has highlighted the need for effective outcome predictors. This study explores the role of [18F]FDG PET/CT in predicting outcomes in PM treated with immunotherapy. METHODS Patients from the NIPU trial, receiving ipilimumab and nivolumab +/- telomerase vaccine in second-line, were included. [18F]FDG PET/CT was obtained at baseline (n = 100) and at week-5 (n = 76). Metabolic tumour volume (MTV) and peak standardised uptake value (SUVpeak) were evaluated in relation to survival outcomes. Wilcoxon rank-sum test was used to assess differences in MTV, total lesion glycolysis (TLG), maximum standardised uptake value (SUVmax) and SUVpeak between patients exhibiting an objective response, defined as either partial response or complete response according to the modified Response Criteria in Solid Tumours (mRECIST) and immune RECIST (iRECIST), and non-responders, defined as either stable disease or progressive disease as their best overall response. RESULTS Univariate Cox regression revealed significant associations of MTV with OS (HR 1.36, CI: 1.14, 1.62, p < 0.001) and PFS (HR 1.18, CI: 1.03, 1.34, p = 0.02), while multivariate analysis showed a significant association with OS only (HR 1.35, CI: 1.09, 1.68, p = 0.007). While SUVpeak was not significantly associated with OS or PFS in univariate analyses, it was significantly associated with OS in multivariate analysis (HR 0.43, CI: 0.23, 0.80, p = 0.008). Objective responders had significant reductions in TLG, SUVmax and SUVpeak at week-5. CONCLUSION MTV provides prognostic value in PM treated with immunotherapy. High SUVpeak was not associated with inferior outcomes, which could be attributed to the distinct mechanisms of immunotherapy. Early reductions in PET metrics correlated with treatment response. STUDY REGISTRATION The NIPU trial (NCT04300244) is registered at clinicaltrials.gov. https://classic. CLINICALTRIALS gov/ct2/show/NCT04300244?cond=Pleural+Mesothelioma&cntry=NO&draw=2&rank=4.
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Affiliation(s)
- Solfrid Thunold
- Dept of Oncology, Oslo University Hospital, Oslo, Norway.
- Dept of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
| | - Eivor Hernes
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Saima Farooqi
- Dept of Oncology, Oslo University Hospital, Oslo, Norway
- Dept of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Åsa Kristina Öjlert
- Dept of Oncology, Oslo University Hospital, Oslo, Norway
- Dept of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Roslyn J Francis
- Dept of Nuclear Medicine, Sir Charles Gairdner Hospital, Perth, Australia
- Medical School of The University of Western Australia, Perth, Australia
| | - Anna K Nowak
- Medical School of The University of Western Australia, Perth, Australia
- National Centre for Asbestos-Related Diseases, University of Western Australia, Perth, Australia
- Medical Oncology, Sir Charles Gairdner Hospital, Perth, Australia
| | - Weronika Maria Szejniuk
- Clinical Cancer Research Center & Department of Oncology, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Søren Steen Nielsen
- Department of Nuclear Medicine, Aalborg University Hospital, Aalborg, Denmark
| | - Susana Cedres
- Vall d'Hebron Institute of Oncology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Marc Simo Perdigo
- Dept of Nuclear Medicine, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Jens Benn Sørensen
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Carin Meltzer
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Lars Tore Gyland Mikalsen
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Department of Life Sciences and Health, Oslo Metropolitan University, Oslo, Norway
| | - Åslaug Helland
- Dept of Oncology, Oslo University Hospital, Oslo, Norway
- Dept of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Eirik Malinen
- Dept of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
| | - Vilde Drageset Haakensen
- Dept of Oncology, Oslo University Hospital, Oslo, Norway
- Dept of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
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12
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Brose A, Miederer I, König J, Gkika E, Sahlmann J, Schimek-Jasch T, Schreckenberger M, Nestle U, Kappes J, Miederer M. Prognostic value of metabolic tumor volume on [ 18F]FDG PET/CT in addition to the TNM classification system of locally advanced non-small cell lung cancer. Cancer Imaging 2024; 24:171. [PMID: 39709461 DOI: 10.1186/s40644-024-00811-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Accepted: 11/30/2024] [Indexed: 12/23/2024] Open
Abstract
PURPOSE Staging of non-small cell lung cancer (NSCLC) is commonly based on [18F]FDG PET/CT, in particular to exclude distant metastases and guide local therapy approaches like resection and radiotherapy. Although it is hoped that PET/CT will increase the value of primary staging compared to conventional imaging, it is generally limited to the characterization of TNM. The first aim of this study was to evaluate the PET parameter metabolic tumor volume (MTV) above liver background uptake as a prognostic marker in lung cancer. The second aim was to investigate the possibility of incorporating MTV into the TNM classification system for disease prognosis in locally advanced NSCLC treated with chemoradiotherapy. METHODS Retrospective evaluation of 235 patients with histologically proven, locally advanced NSCLC from the multi-centre randomized clinical PETPLAN trial and a clinical cohort from a hospital registry. The PET parameters SUVmax, SULpeak, MTV and TLG above liver background uptake were determined. Kaplan-Meier curves and stratified Cox proportional hazard regression models were used to investigate the prognostic value of PET parameters and TNM along with clinical variables. Subgroup analyses were performed to compare hazard ratios according to TNM, MTV, and the two variables combined. RESULTS In the multivariable Cox regression analysis, MTV was associated with significantly worse overall survival independent of stage and other prognostic variables. In locally advanced disease stages treated with chemoradiotherapy, higher MTV was significantly associated with worse survival (median 17 vs. 32 months). Using simple cut-off values (45 ml for stage IIIa, 48 ml for stage IIIb, and 105 ml for stage IIIc), MTV was able to further predict differences in survival for stages IIIa-c. The combination of TNM and MTV staging system showed better discrimination for overall survival in locally advanced disease stages, compared to TNM alone. CONCLUSION Higher metabolic tumor volume is significantly associated with worse overall survival and combined with TNM staging, it provides more precise information about the disease prognosis in locally advanced NSCLC treated with chemoradiotherapy compared to TNM alone. As a PET parameter with volumetric information, MTV represents a useful addition to TNM.
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Affiliation(s)
- Alexander Brose
- Department of Translational Imaging in Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstraße 74, Dresden, 01307, Germany.
- German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.
- Department of Diagnostic and Interventional Radiology, University Hospital Giessen, Justus Liebig University, Klinikstrasse 33, Giessen, 35392, Germany.
- Member of the German Center for Lung Research (DZL), Giessen, Germany.
| | - Isabelle Miederer
- Department of Nuclear Medicine, University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Jochem König
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, University Hospital Bonn, Bonn, Germany
- Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany
| | - Jörg Sahlmann
- Institute of Medical Biometry and Statistics (IMBI), Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Tanja Schimek-Jasch
- Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany
| | - Mathias Schreckenberger
- Department of Nuclear Medicine, University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany
- Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Jutta Kappes
- Department of Pulmonary Medicine, Theresienkrankenhaus, Mannheim, Germany
- Department of Internal Medicine/ Pulmonary Medicine, Catholic Hospital Koblenz-Montabaur, Koblenz, Germany
| | - Matthias Miederer
- Department of Translational Imaging in Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstraße 74, Dresden, 01307, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- Department of Nuclear Medicine, University Medical Center Mainz, Johannes Gutenberg-University Mainz, Mainz, Germany
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Yadgarov M, Berikashvili L, Rakova E, Likar Y. 18 F-FDG PET Metabolic Parameters for the Prediction of Histological Response to Induction Chemotherapy in Osteosarcoma and Ewing Sarcoma : A Systematic Review and Network Meta-analysis. Clin Nucl Med 2024; 49:e640-e649. [PMID: 39325490 DOI: 10.1097/rlu.0000000000005412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2024]
Abstract
PURPOSE This study aimed to evaluate the ability of 18 F-FDG PET/CT metabolic parameters to predict the histological response to neoadjuvant chemotherapy in patients with osteosarcoma and Ewing sarcoma. PATIENTS AND METHODS This systematic review and network meta-analysis adhered to the PRISMA-NMA and Cochrane guidelines. Electronic databases were searched from January 2008 to January 2024; this search was supplemented by snowballing methods. The risk of bias was evaluated with QUADAS-2, and evidence certainty was assessed using the GRADE approach. The prognostic value of 18 F-FDG PET/CT parameters, including pretreatment and posttreatment SUVs (SUV1, SUV2 and the SUV2/SUV1 ratio), metabolic tumor volume (MTV1, MTV2, ΔMTV), and total lesion glycolysis (TLG1, TLG2, ΔTLG), was examined. RESULTS The meta-analysis of 18 studies (714 patients) identified the ΔTLG, ΔMTV, and SUV ratio as superior predictors of histological response. The changes in metabolic activity, as indicated by these parameters, provided a robust indication of treatment effectiveness. Baseline parameters showed limited predictive value compared with posttreatment assessments. The study's robustness was confirmed through meta-regression, which revealed that the predictive value of the SUV2 and SUV ratio was consistent across various cutoff thresholds. CONCLUSIONS 18 F-FDG PET/CT metabolic parameters, particularly those measuring changes posttherapy, are effective in predicting the histological response in patients with osteosarcoma and Ewing sarcoma. These findings underscore the potential of 18 F-FDG PET/CT in guiding early treatment decisions, thereby enhancing personalized therapeutic approaches.
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Affiliation(s)
| | - Levan Berikashvili
- Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russia
| | | | - Yury Likar
- From the Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology, and Immunology, Moscow, Russia
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14
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Huang M, Zou Y, Wang W, Li Q, Tian R. The role of baseline 18F-FDG PET/CT for survival prognosis in NSCLC patients undergoing immunotherapy: a systematic review and meta-analysis. Ther Adv Med Oncol 2024; 16:17588359241293364. [PMID: 39502406 PMCID: PMC11536524 DOI: 10.1177/17588359241293364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 10/07/2024] [Indexed: 11/08/2024] Open
Abstract
Background The value of pretreatment baseline 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET)/computed tomography (CT) as a prognostic factor for survival of patients with non-small-cell lung cancer (NSCLC) receiving immunotherapy remained uncertain. Objectives To investigate the prognostic ability of baseline 18F-FDG PET/CT in patients with NSCLC receiving immunotherapy. Design A systematic review and meta-analysis. Data sources and methods We searched the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases until May 7, 2024, and extracted data related to patient characteristics, semiquantitative parameters of 18F-FDG PET/CT, and survival. We pooled hazard ratios (HRs) to evaluate the prognostic value of the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for overall survival (OS) and progression-free survival (PFS). Results A total of 22 studies (1363 patients, average age range 30-88 years) were included. Baseline 18F-FDG PET/CT-derived MTV was significantly associated with both OS (HR: 1.124, 95% confidence interval (CI) 1.058-1.195, I 2 = 81.70%) and PFS (HR: 1.069, 95% CI: 1.016-1.124, I 2 = 71.80%). Other baseline 18F-FDG PET/CT-derived parameters, including SUVmax (OS: HR: 0.930, 95% CI: 0.718-1.230; PFS: HR: 0.979, 95% CI: 0.759-1.262), SUVmean (OS: HR: 0.801, 95% CI: 0.549-1.170; PFS: HR: 0.688, 95% CI: 0.464-1.020), and TLG (OS: HR: 0.999, 95% CI: 0.980-1.018; PFS: HR: 0.995, 95% CI: 0.980-1.010), were not associated with survival. Sensitivity analyses by removing one study at a time did not significantly alter the association between MTV and PFS or between MTV and OS. There was no evidence of publication bias. Conclusion Pretreatment baseline 18F-FDG PET/CT-derived MTV might be a prognostic biomarker in NSCLC patients receiving immunotherapy. Further studies are needed to support routine use.
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Affiliation(s)
- Mingxing Huang
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yuheng Zou
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Weichen Wang
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Qianrui Li
- Department of Nuclear Medicine, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, Sichuan 610041, China
- National Medical Products Administration Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu, Sichuan, China
- Chinese Evidence-Based Medicine Center, Cochrane China Center and MAGIC China Center, West China Hospital, Sichuan University, Chengdu, China
| | - Rong Tian
- Department of Nuclear Medicine, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, Sichuan 610041, China
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15
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Fragkiadaki V, Panagiotidis E, Vlontzou E, Kalathas T, Paschali A, Kypraios C, Chatzipavlidou V, Datseris I. Correlation of PSA blood levels with standard uptake value maximum (SUV max ) and total metabolic tumor volume (TMTV) in 18F-PSMA-1007 and 18F-choline PET/CT in patients with biochemically recurrent prostate cancer. Nucl Med Commun 2024; 45:924-930. [PMID: 39082074 DOI: 10.1097/mnm.0000000000001881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
OBJECTIVES In this prospective study, we investigated the correlation between prostate-specific antigen (PSA) levels in the blood of patients with prostate cancer in biochemical recurrence after radical treatment with the semiquantitative parameters standard uptake value maximum (SUV max ) and the total metabolic tumor volume (TMTV) in the metastatic foci depicted in 18F-prostate-specific membrane antigen (PSMA)-1007 and 18F-choline PET/computed tomography (CT) imaging. METHODS We prospectively examined 104 patients with biochemical relapse of prostate cancer after primary definitive treatment. All patients underwent one 18F-PSMA-1007 and one 18F-choline PET/CT examination in randomized order within a time frame of 10 days and were followed for at least 6 months (182 ± 10 days). The semiquantitative parameters of SUV max and metabolic tumor volume (MTV) of each neoplastic lesion in PET/CT imaging were calculated, and further summation of each MTV value was done to calculate the TMTV. RESULTS According to the Spearman correlation analysis, a positive correlation was found between PSA levels and SUV max and TMTV scores in the metastatic foci of 18F-PSMA-1007 PET/CT ( r = 0.24 and 0.35, respectively; P < 0.05) and SUV max in the lesions of 18F-choline PET/CT ( r = 0.28; P < 0.0239). However, a positive but NS correlation was demonstrated between values of PSA and TMTV for each lesion in the 18F-choline PET/CT study ( r = 0.22; P = 0.0795). The detection rate of the different PSA levels with a cutoff of 1 ng/ml was higher for 18F-PSMA-1007 than 18F-choline. CONCLUSION In biochemical relapse patients there is a positive correlation between PSA levels in the blood and the semiquantitative parameters SUV max and TMTV of the metastatic foci in the 18F-PSMA-1007 and 18F-Choline PET/CT imaging.
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Affiliation(s)
| | | | - Evaggelia Vlontzou
- Department of Nuclear Medicine, Evaggelismos General Hospital, Athens and
| | | | - Anna Paschali
- Department of Nuclear Medicine, Theageneio Cancer Center, Thessaloniki,
| | | | | | - Ioannis Datseris
- Department of Nuclear Medicine, Evaggelismos General Hospital, Athens and
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16
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Schroeder C, Gatidis S, Kelemen O, Schütz L, Bonzheim I, Muyas F, Martus P, Admard J, Armeanu-Ebinger S, Gückel B, Küstner T, Garbe C, Flatz L, Pfannenberg C, Ossowski S, Forschner A. Tumour-informed liquid biopsies to monitor advanced melanoma patients under immune checkpoint inhibition. Nat Commun 2024; 15:8750. [PMID: 39384805 PMCID: PMC11464631 DOI: 10.1038/s41467-024-52923-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 09/20/2024] [Indexed: 10/11/2024] Open
Abstract
Immune checkpoint inhibitors (ICI) have significantly improved overall survival in melanoma patients. However, 60% experience severe adverse events and early response markers are lacking. Circulating tumour DNA (ctDNA) is a promising biomarker for treatment-response and recurrence detection. The prospective PET/LIT study included 104 patients with palliative combined or adjuvant ICI. Tumour-informed sequencing panels to monitor 30 patient-specific variants were designed and 321 liquid biopsies of 87 patients sequenced. Mean sequencing depth after deduplication using UMIs was 6000x and the error rate of UMI-corrected reads was 2.47×10-4. Variant allele fractions correlated with PET/CT MTV (rho=0.69), S100 (rho=0.72), and LDH (rho=0.54). A decrease of allele fractions between T1 and T2 was associated with improved PFS and OS in the palliative cohort (p = 0.008 and p < 0.001). ctDNA was detected in 76.9% of adjuvant patients with relapse (n = 10/13), while all patients without progression (n = 9) remained ctDNA negative. Tumour-informed liquid biopsies are a reliable tool for monitoring treatment response and early relapse in melanoma patients with ICI.
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Affiliation(s)
- Christopher Schroeder
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sergios Gatidis
- Department of Radiology, Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Olga Kelemen
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Leon Schütz
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Irina Bonzheim
- Institute of Pathology and Neuropathology, University Hospital Tübingen, Tübingen, Germany
| | - Francesc Muyas
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Peter Martus
- Institute for Clinical Epidemiology and Applied Biostatistics (IKEaB), Tübingen, Germany
| | - Jakob Admard
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
- NGS Competence Center Tübingen (NCCT), University of Tübingen, Tübingen, Germany
| | - Sorin Armeanu-Ebinger
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Brigitte Gückel
- Department of Radiology, Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Thomas Küstner
- Department of Radiology, Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Claus Garbe
- Department of Dermatology, University Hospital Tübingen, Tübingen, Germany
| | - Lukas Flatz
- Department of Dermatology, University Hospital Tübingen, Tübingen, Germany
| | - Christina Pfannenberg
- Department of Radiology, Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Stephan Ossowski
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, German Cancer Research Center (DKFZ), Heidelberg, Germany
- NGS Competence Center Tübingen (NCCT), University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Tübingen, Germany
| | - Andrea Forschner
- Department of Dermatology, University Hospital Tübingen, Tübingen, Germany.
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17
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Novruzov E, Dabir M, Schmitt D, Mattes-György K, Beu M, Mori Y, Antke C, Reinartz S, Lichtenberg A, Antoch G, Giesel FL, Aubin H, Mamlins E. The Predictive Role of Metabolic Volume Segmentation Compared to Semiquantitative PET Parameters in Diagnosis of LVAD Infection using [ 18F]FDG Imaging. Mol Imaging Biol 2024; 26:812-822. [PMID: 39085535 PMCID: PMC11436428 DOI: 10.1007/s11307-024-01937-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 05/20/2024] [Accepted: 07/12/2024] [Indexed: 08/02/2024]
Abstract
PURPOSE Left ventricular assisting device (LVAD) is a vital mechanical circulatory assist device for patients with end-stage heart disease, serving as either a bridge to transplantation or palliative destination therapy. Yet device infection represents a major lethal complication, warranting a multi-step, complex therapy approach including an urgent device exchange or heart transplantation. Still, timely diagnosis of site and extent of VAD-specific infection for a proper therapy planning poses challenges in regular clinical care. This single-center, retrospective study aimed to evaluate the impact of volumetric PET parameters with different thresholding compared to semiquantitative PET parameters for accurate diagnosis of VAD-specific infection. PROCEDURES Seventeen patients (1 female, 16 males; mean age 57 ± 11 years) underwent [18F]FDG imaging for suspected VAD-specific infection between April 2013 and October 2023. Various metabolic and volumetric PET parameters with different thresholding were collected for specific LVAD components including driveline entry point, subcutaneous driveline, pump pocket, inner cannula and outflow tract. Microbiology and clinical follow-up were used as the final diagnosis standard. RESULTS Nine of eleven patients with VAD-specific infection underwent urgent heart transplantation, and one had a surgical revision of LVAD. Two patients had non-VAD specific infections, and two had non-VAD related infections. Metabolic burden determination using a fixed absolute threshold provided the best outcome compared to relative thresholding or other metabolic SUV parameters. The total metabolic tumor volume (MTV) cutoff value was 9.3 cm3, and the corresponding sensitivity, specificity, accuracy, and AUC were 90.0%, 71.43%, 82.5%, and 0.814 (95% CI 0.555-0.958), respectively. The total lesion glycolysis (TLG) was 30.6, and the corresponding sensitivity, specificity, accuracy, and AUC were 90.0%, 71.4%, 82.5%, and 0.829 (95% CI 0.571-0.964), respectively. CONCLUSIONS Volumetric PET parameters with fixed absolute thresholding appear to be a valuable auxiliary tool in the evaluation of [18F]FDG imaging to enhance the diagnostic accuracy of VAD-specific infection.
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Affiliation(s)
- Emil Novruzov
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany.
| | - Mardjan Dabir
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Dominik Schmitt
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Katalin Mattes-György
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Markus Beu
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Yuriko Mori
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Christina Antke
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Sebastian Reinartz
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Artur Lichtenberg
- Department of Cardiac Surgery, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Gerald Antoch
- Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Frederik L Giesel
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Hug Aubin
- Department of Cardiac Surgery, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
| | - Eduards Mamlins
- Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany
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18
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Tie X, Shin M, Lee C, Perlman SB, Huemann Z, Weisman AJ, Castellino SM, Kelly KM, McCarten KM, Alazraki AL, Hu J, Cho SY, Bradshaw TJ. Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network. ARXIV 2024:arXiv:2404.08611v2. [PMID: 38659641 PMCID: PMC11042444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Purpose Automatic quantification of longitudinal changes in PET scans for lymphoma patients has proven challenging, as residual disease in interim-therapy scans is often subtle and difficult to detect. Our goal was to develop a longitudinally-aware segmentation network (LAS-Net) that can quantify serial PET/CT images for pediatric Hodgkin lymphoma patients. Materials and Methods This retrospective study included baseline (PET1) and interim (PET2) PET/CT images from 297 patients enrolled in two Children's Oncology Group clinical trials (AHOD1331 and AHOD0831). LAS-Net incorporates longitudinal cross-attention, allowing relevant features from PET1 to inform the analysis of PET2. Model performance was evaluated using Dice coefficients for PET1 and detection F1 scores for PET2. Additionally, we extracted and compared quantitative PET metrics, including metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in PET1, as well as qPET and ΔSUVmax in PET2, against physician measurements. We quantified their agreement using Spearman's ρ correlations and employed bootstrap resampling for statistical analysis. Results LAS-Net detected residual lymphoma in PET2 with an F1 score of 0.606 (precision/recall: 0.615/0.600), outperforming all comparator methods (P<0.01). For baseline segmentation, LAS-Net achieved a mean Dice score of 0.772. In PET quantification, LAS-Net's measurements of qPET, ΔSUVmax, MTV and TLG were strongly correlated with physician measurements, with Spearman's ρ of 0.78, 0.80, 0.93 and 0.96, respectively. The quantification performance remained high, with a slight decrease, in an external testing cohort. Conclusion LAS-Net demonstrated significant improvements in quantifying PET metrics across serial scans, highlighting the value of longitudinal awareness in evaluating multi-time-point imaging datasets.
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Affiliation(s)
- Xin Tie
- Department of Radiology, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Muheon Shin
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Changhee Lee
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Scott B Perlman
- Department of Radiology, University of Wisconsin, Madison, WI, USA
- University of Wisconsin Carbone Comprehensive Cancer Center, Madison, WI, USA
| | - Zachary Huemann
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Amy J Weisman
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Sharon M Castellino
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Kara M Kelly
- Department of Pediatric Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Department of Pediatrics, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY, USA
| | - Kathleen M McCarten
- Pediatric Radiology, Imaging and Radiation Oncology Core Rhode Island, Lincoln, RI, USA
| | - Adina L Alazraki
- Department of Radiology, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Junjie Hu
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
- Department of Computer Science, School of Computer, University of Wisconsin, Madison, WI, USA
| | - Steve Y Cho
- Department of Radiology, University of Wisconsin, Madison, WI, USA
- University of Wisconsin Carbone Comprehensive Cancer Center, Madison, WI, USA
| | - Tyler J Bradshaw
- Department of Radiology, University of Wisconsin, Madison, WI, USA
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Song JK, Lee S, Kim YJ, Kim HK, Ha JW, Choi EY, Park SW, Park SJ, Park YH, Park JH, Yang DH, Kim KH, Yang DH, Han S, Chae SY, Lee JS, Song JM, Cho GY. Effect of Evogliptin on the Progression of Aortic Valvular Calcification. J Am Coll Cardiol 2024; 84:1064-1075. [PMID: 39260927 DOI: 10.1016/j.jacc.2024.06.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 06/10/2024] [Accepted: 06/14/2024] [Indexed: 09/13/2024]
Abstract
BACKGROUND Medical therapy for aortic stenosis (AS) remains an elusive goal. OBJECTIVES This study sought to establish whether evogliptin, a dipeptidyl peptidase-4 inhibitor, could reduce AS progression. METHODS A total of 228 patients (age 67 ± 11 years; 33% women) with AS were randomly assigned to receive placebo (n = 75), evogliptin 5 mg (n = 77), or evogliptin 10 mg (n = 76). The primary endpoint was the 96-week change in aortic valve calcium volume (AVCV) on computed tomography. Secondary endpoints included the 48-week change in active calcification volume measured using 18F-sodium fluoride positron emission tomography (18F-NaF PET). RESULTS There were no significant differences in the 96-week changes in AVCV between evogliptin 5 mg and placebo (-5.27; 95% CI: -55.36 to 44.82; P = 0.84) or evogliptin 10 mg and placebo (-18.83; 95% CI: -32.43 to 70.10; P = 0.47). In the placebo group, the increase in AVCV between 48 weeks and 96 weeks was higher than that between baseline and 48 weeks (136 mm3; 95% CI: 108-163 vs 102 mm3; 95% CI: 75-129; P = 0.0485). This increasing trend in the second half of the study was suppressed in both evogliptin groups. The 48-week change in active calcification volume on 18F-NaF PET was significantly lower in both the evogliptin 5 mg (-1,325.6; 95% CI: -2,285.9 to -365.4; P = 0.008) and 10-mg groups (-1,582.2; 95% CI: -2,610.8 to -553.5; P = 0.0038) compared with the placebo group. CONCLUSIONS This exploratory study did not demonstrate the protective effect of evogliptin on AV calcification. Favorable 18F-NaF PET results and possible suppression of aortic valve calcification with longer medication use in the evogliptin groups suggest the need for larger confirmatory trials. (A Multicenter, Double-blind, Placebo-controlled, Stratified-randomized, Parallel, Therapeutic Exploratory Clinical Study to Evaluate the Efficacy and Safety of DA-1229 in Patients With Calcific Aortic Valve Disease; NCT04055883).
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Affiliation(s)
- Jae-Kwan Song
- Division of Cardiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
| | - Sahmin Lee
- Division of Cardiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Yong-Jin Kim
- Division of Cardiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyung-Kwan Kim
- Division of Cardiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jong-Won Ha
- Division of Cardiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eui-Young Choi
- Division of Cardiology, Gangnam Severance Hospital, Seoul, Republic of Korea
| | - Seung-Woo Park
- Division of Cardiology, Samsung Medical Center, Seoul, Republic of Korea
| | - Sung-Ji Park
- Division of Cardiology, Samsung Medical Center, Seoul, Republic of Korea
| | - Yong-Hyun Park
- Division of Cardiology, Pusan National University Yangsan Hospital, Busan, Republic of Korea
| | - Jae-Hyeong Park
- Chungnam National University Hospital, Daejeon, Republic of Korea
| | - Dong Heon Yang
- Division of Cardiology, Kyungpook National University Hospital, Daegu, Republic of Korea
| | - Kye Hun Kim
- Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Dong Hyun Yang
- Department of Radiology, Asan Medical Center, Seoul, Republic of Korea
| | - Sangwon Han
- Department of Nuclear Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sun Young Chae
- Department of Nuclear Medicine, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, Republic of Korea
| | - Ji Sung Lee
- Clinical Research Center, Asan Institute for Life Science, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jong-Min Song
- Division of Cardiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Goo-Yeong Cho
- Division of Cardiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
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20
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Haller SD, Essani K. Oncolytic Tanapoxvirus Variants Expressing mIL-2 and mCCL-2 Regress Human Pancreatic Cancer Xenografts in Nude Mice. Biomedicines 2024; 12:1834. [PMID: 39200298 PMCID: PMC11351728 DOI: 10.3390/biomedicines12081834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/01/2024] [Accepted: 08/06/2024] [Indexed: 09/02/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the fifth leading cause of cancer-related death and presents the lowest 5-year survival rate of any form of cancer in the US. Only 20% of PDAC patients are suitable for surgical resection and adjuvant chemotherapy, which remains the only curative treatment. Chemotherapeutic and gene therapy treatments are associated with adverse effects and lack specificity/efficacy. In this study, we assess the oncolytic potential of immuno-oncolytic tanapoxvirus (TPV) recombinants expressing mouse monocyte chemoattractant protein (mMCP-1 or mCCL2) and mouse interleukin (mIL)-2 in human pancreatic BxPc-3 cells using immunocompromised and CD-3+ T-cell-reconstituted mice. Intratumoral treatment with TPV/∆66R/mCCL2 and TPV/∆66R/mIL-2 resulted in a regression in BxPc-3 xenograft volume compared to control in immunocompromised mice; mCCL-2 expressing TPV OV resulted in a significant difference from control at p < 0.05. Histological analysis of immunocompromised mice treated with TPV/∆66R/mCCL2 or TPV/∆66R/mIL-2 demonstrated multiple biomarkers indicative of increased severity of chronic, active inflammation compared to controls. In conclusion, TPV recombinants expressing mCCL2 and mIL-2 demonstrated a therapeutic effect via regression in BxPc-3 tumor xenografts. Considering the enhanced oncolytic potency of TPV recombinants demonstrated against PDAC in this study, further investigation as an alternative or combination treatment option for human PDAC may be warranted.
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Affiliation(s)
| | - Karim Essani
- Laboratory of Virology, Department of Biological Sciences, Western Michigan University, Kalamazoo, MI 49008-5410, USA;
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21
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Szabó A, Emri M, Tóth Z, Fajtai D, Donkó T, Petneházy Ö, Kőrösi D, Repa I, Takács A, Kisiván T, Gerencsér Z, Ali O, Turbók J, Bóta B, Gömbös P, Romvári R, Kovács M. Measurement of hepatic glucose ( 18F-fluorodeoxyglucose) uptake with positron emission tomography-magnetic resonance imaging in fumonisin B intoxicated rabbit bucks. Sci Rep 2024; 14:18213. [PMID: 39107361 PMCID: PMC11303394 DOI: 10.1038/s41598-024-68210-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 07/22/2024] [Indexed: 08/10/2024] Open
Abstract
Rabbit bucks (bodyweight 5 kg) underwent dietary intoxication with fumonisin B series mycotoxins (FB1 + FB2 + FB3, 15 mg/kg diet) for 14 days to test the applicability of positron emission tomography-magnetic resonance (PET MR) hybrid imaging in characterizing experimentally induced mild hepatotoxicosis. 18F-fluorodeoxyglucose (18F-FDG) radiotracer-aided imaging was performed before and after FBs administration on identical animals, and at both time points, blood was sampled for haematology and clinical chemistry. Kinetic PET image analysis revealed time-activity curves with uptake maxima below 1 min in the liver, renal cortex, portal vein, lung and coarctatio aortae. In the frame of static PET image analysis, based on the standardized uptake value (SUV), the so-called metabolic liver volume (MLV, liver volume defined by over 0.9 × average liver SUV) and the total liver glycolysis (TLG, MLV multiplied by the SUVmean) were calculated. Mycotoxicosis increased total liver glycolysis (p < 0.04) after 14 days and liver tissue TLG inhomogeneity was minimal. Pearson correlation between TLG and alkaline phosphatase (ALP) was positive (0.515), while negative with LDH and AST (- 0.721 and - 0.491, respectively). Results indicate a slight hepatic mycotoxin effect and significantly increased glucose uptake intensity, which has been sensitively detected with molecular imaging (18F-FDG PET MRI) in the rabbit model.
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Affiliation(s)
- András Szabó
- Agribiotechnology and Precision Breeding for Food Security National Laboratory, Department of Physiology and Animal Health, Institute of Physiology and Nutrition, Hungarian University of Agriculture and Life Sciences, Kaposvár, Hungary.
- HUN-REN-MATE Mycotoxins in the Food Chain Research Group, Kaposvár, Hungary.
| | - Miklós Emri
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Zoltán Tóth
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Dániel Fajtai
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Tamás Donkó
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Örs Petneházy
- Agribiotechnology and Precision Breeding for Food Security National Laboratory, Department of Physiology and Animal Health, Institute of Physiology and Nutrition, Hungarian University of Agriculture and Life Sciences, Kaposvár, Hungary
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Dénes Kőrösi
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Imre Repa
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Alíz Takács
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Tímea Kisiván
- Medicopus Healthcare Provider and Public Nonprofit Ltd, Somogy County Moritz Kaposi Teaching Hospital, Kaposvár, Hungary
| | - Zsolt Gerencsér
- Department of Animal Breeding, Institute of Animal Sciences, Hungarian University of Agricultural and Life Sciences, Kaposvár, Hungary
| | - Omeralfaroug Ali
- Agribiotechnology and Precision Breeding for Food Security National Laboratory, Department of Physiology and Animal Health, Institute of Physiology and Nutrition, Hungarian University of Agriculture and Life Sciences, Kaposvár, Hungary
| | - Janka Turbók
- Agribiotechnology and Precision Breeding for Food Security National Laboratory, Department of Physiology and Animal Health, Institute of Physiology and Nutrition, Hungarian University of Agriculture and Life Sciences, Kaposvár, Hungary
- National Food Chain Safety Office, Animal Health Directorate, Animal Health Diagnostic Laboratory, Kaposvár, Hungary
| | - Brigitta Bóta
- HUN-REN-MATE Mycotoxins in the Food Chain Research Group, Kaposvár, Hungary
| | - Patrik Gömbös
- Agribiotechnology and Precision Breeding for Food Security National Laboratory, Department of Physiology and Animal Health, Institute of Physiology and Nutrition, Hungarian University of Agriculture and Life Sciences, Kaposvár, Hungary
| | - Róbert Romvári
- Department of Animal Breeding, Institute of Animal Sciences, Hungarian University of Agricultural and Life Sciences, Kaposvár, Hungary
| | - Melinda Kovács
- Agribiotechnology and Precision Breeding for Food Security National Laboratory, Department of Physiology and Animal Health, Institute of Physiology and Nutrition, Hungarian University of Agriculture and Life Sciences, Kaposvár, Hungary
- HUN-REN-MATE Mycotoxins in the Food Chain Research Group, Kaposvár, Hungary
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Lim CH, Um SW, Kim HK, Choi YS, Pyo HR, Ahn MJ, Choi JY. 18F-Fluorodeoxyglucose Positron Emission Tomography-Based Risk Score Model for Prediction of Five-Year Survival Outcome after Curative Resection of Non-Small-Cell Lung Cancer. Cancers (Basel) 2024; 16:2525. [PMID: 39061165 PMCID: PMC11274931 DOI: 10.3390/cancers16142525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 07/09/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
The aim of our retrospective study is to develop and assess an imaging-based model utilizing 18F-FDG PET parameters for predicting the five-year survival in non-small-cell lung cancer (NSCLC) patients after curative surgery. A total of 361 NSCLC patients who underwent curative surgery were assigned to the training set (n = 253) and the test set (n = 108). The LASSO regression model was used to construct a PET-based risk score for predicting five-year survival. A hybrid model that combined the PET-based risk score and clinical variables was developed using multivariate logistic regression analysis. The predictive performance was determined by the area under the curve (AUC). The individual features with the best predictive performances were co-occurrence_contrast (AUC = 0.675) and SUL peak (AUC = 0.671). The PET-based risk score was identified as an independent predictor after adjusting for clinical variables (OR 5.231, 95% CI 1.987-6.932; p = 0.009). The hybrid model, which integrated clinical variables, significantly outperformed the PET-based risk score alone in predictive accuracy (AUC = 0.771 vs. 0.696, p = 0.022), a finding that was consistent in the test set. The PET-based risk score, especially when integrated with clinical variables, demonstrates good predictive ability for five-year survival in NSCLC patients following curative surgery.
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Affiliation(s)
- Chae Hong Lim
- Department of Nuclear Medicine, Soonchunhyang University College of Medicine, Seoul 04401, Republic of Korea
| | - Sang-Won Um
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
| | - Hong Kwan Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
| | - Yong Soo Choi
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
| | - Hong Ryul Pyo
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
| | - Myung-Ju Ahn
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
| | - Joon Young Choi
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
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23
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Martin TW, Griffin L. Prospective pilot study utilizing changes in quantitative values obtained on serial fluorine-18 fluorodeoxyglucose ( 18F-FDG) positron emission tomography-computed tomography (PET/CT) in dogs with appendicular osteosarcoma before and after stereotactic body radiation therapy (SBRT) and carboplatin chemotherapy to assess for prediction of survival and therapeutic effectiveness. Vet Radiol Ultrasound 2024; 65:408-416. [PMID: 38655687 DOI: 10.1111/vru.13361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/24/2024] [Accepted: 03/10/2024] [Indexed: 04/26/2024] Open
Abstract
Serial fluorine 18 fluorodeoxyglucose (18F-FDG) positron emission tomography-CT (PET/CT) is commonly used in human oncology to prognosticate and evaluate for therapeutic effectiveness. In this pilot study, dogs with naturally occurring appendicular osteosarcoma were evaluated with serial 18F-FDG PET/CT in an attempt to assess for response to therapy, prognostic factors, and appropriateness of imaging intervals. Fourteen dogs were enrolled in the trial. All dogs had the initial 18F-FDG PET/CT (PET1), with nine dogs having their end-of-therapy 18F-FDG PET/CT (EoT PET) 3 months after stereotactic body radiation therapy (SBRT) to the primary tumor. The median percent change from the PET1 to the EoT PET for the standard uptake value maximum (SUVmax%) was -58% (range: -17 to -88%), metabolic tumor volume (MTV%) was -99.8% (range: -65 to -100%), and total lesion glycolysis (TLG%) was -99.8% (range: -75 to -100%), all of which were significant (P < .05, <.05, and <.05, respectively). On evaluation, it was found that volumes of GTV and CTV were significant for survival (P < .05 and <.05), MTV1, TLG1, and SUVmax on the EoT PET (SUVmaxEoT) were predictive of metastasis (P < .05), and the SUVmax% was significantly correlated to the time to first event (P < .05). Based on this data, serial 18F-FDG PET/CT performed 3 months after SBRT can show a significant reduction in avidity, and the quantitative data collected may help predict metastatic disease in canine appendicular osteosarcoma.
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Affiliation(s)
- Tiffany W Martin
- Department of Clinical Sciences, Flint Animal Cancer Center, Colorado State University, Fort Collins, Colorado, USA
| | - Lynn Griffin
- VCA Canada Central Victoria Veterinary Hospital, Victoria, British Columbia, Canada
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24
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Zarei M, Wallsten E, Grefve J, Söderkvist K, Gunnlaugsson A, Sandgren K, Jonsson J, Keeratijarut Lindberg A, Nilsson E, Bergh A, Zackrisson B, Moreau M, Thellenberg Karlsson C, Olsson LE, Widmark A, Riklund K, Blomqvist L, Berg Loegager V, Axelsson J, Strandberg SN, Nyholm T. Accuracy of gross tumour volume delineation with [68Ga]-PSMA-PET compared to histopathology for high-risk prostate cancer. Acta Oncol 2024; 63:503-510. [PMID: 38912830 PMCID: PMC11332483 DOI: 10.2340/1651-226x.2024.39041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 04/24/2024] [Indexed: 06/25/2024]
Abstract
BACKGROUND The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology. MATERIALS AND METHODS The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold. RESULTS The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm. INTERPRETATION Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.
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Affiliation(s)
- Maryam Zarei
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.
| | - Elin Wallsten
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Josefine Grefve
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Karin Söderkvist
- Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden
| | - Adalsteinn Gunnlaugsson
- Skane University Hospital, Department of Hematology, Oncology and Radiation Physics, Lund, Sweden
| | - Kristina Sandgren
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Joakim Jonsson
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Angsana Keeratijarut Lindberg
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Erik Nilsson
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Anders Bergh
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Björn Zackrisson
- Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden
| | - Mathieu Moreau
- Skane University Hospital, Department of Hematology, Oncology and Radiation Physics, Lund, Sweden
| | | | - Lars E Olsson
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden
| | - Anders Widmark
- Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden
| | - Katrine Riklund
- Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå, Sweden
| | - Lennart Blomqvist
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden; Department of Molecular Medicine and Surgery, Karolinska Institutet, Solna, Sweden
| | - Vibeke Berg Loegager
- Department of Radiology, Copenhagen University Hospital in Herlev, Herlev, Denmark
| | - Jan Axelsson
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
| | - Sara N Strandberg
- Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå, Sweden
| | - Tufve Nyholm
- Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden
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25
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Yadgarov MY, Dunaykin MM, Shestopalov GI, Kailash C, Kireeva ED, Myakova NV, Likar YN. Prognostic value of baseline and interim [ 18F]FDG PET metabolic parameters in pediatric Hodgkin's lymphoma. Eur J Nucl Med Mol Imaging 2024; 51:1955-1964. [PMID: 38351389 DOI: 10.1007/s00259-024-06643-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 02/05/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND Hodgkin lymphoma (HL) in pediatric populations has a high survival rate but poses risks for long-term morbidities. Although [18F]fluoro‑2‑deoxy‑2‑d‑glucose positron emission tomography ([18F]FDG PET) scans offer potential for improved risk stratification, the definitive prognostic value of quantitative [18F]FDG PET parameters remains unclear for pediatric HL. METHODS A single-center, retrospective study included pediatric patients diagnosed with HL between 2016 and 2023 treated according to EuroNet-PHL-C1 and DAL/GPOH-HD protocols. Patients underwent baseline and interim PET/CT scans after two chemotherapy cycles. Event-free survival (EFS) was the primary endpoint, Deauville score was the secondary endpoint. Quantitative [18F]FDG PET parameters included SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) that were evaluated using two segmentation methods (SUV 2.5, 41% SUVmax). Survival outcomes were assessed using Cox regression analysis. RESULTS A total of 115 patients (50 males, median age 14.2 years) were studied, with a median follow-up period of 35 months. During this period, 16 cases (13.9%) of relapse or progression were noted. Baseline and interim MTV 2.5, MTV 41%, TLG 2.5, and TLG 41%, along with interim SUVmax, were significantly associated with worse EFS and correlated with post-treatment Deauville scores. In multivariable analysis, interim MTV 2.5 > 0 ml (adj. hazard ratio, HR: 3.89, p = 0.009) and interim TLG 41% ≥ 30 g (adj. HR: 7.98, p = 0.006) were independent risk factors for EFS. CONCLUSION Baseline and interim [18F]FDG PET parameters can serve as significant prognostic indicators for EFS and treatment response in pediatric HL. These quantitative measures could enhance individualized, risk-adapted treatment strategies for children and adolescents with HL.
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Affiliation(s)
- Mikhail Ya Yadgarov
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.
- Department of PET and Radionuclide Diagnostics, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Samory Mashela Str. 1, 117997, Moscow, Russia.
| | - M M Dunaykin
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - G I Shestopalov
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
- Russian Children's Clinical Hospital, N.I. Pirogov Russian National Research Medical University of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - C Kailash
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - E D Kireeva
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - N V Myakova
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Yu N Likar
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
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26
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Kim BG, Lee SH, Jang Y, Kang S, Kang CM, Cho NH. Differentially expressed genes associated with high metabolic tumor volume served as diagnostic markers and potential therapeutic targets for pancreatic cancer. J Transl Med 2024; 22:453. [PMID: 38741142 PMCID: PMC11092202 DOI: 10.1186/s12967-024-05181-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 04/05/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND The lack of distinct biomarkers for pancreatic cancer is a major cause of early-stage detection difficulty. The pancreatic cancer patient group with high metabolic tumor volume (MTV), one of the values measured from positron emission tomography-a confirmatory method and standard care for pancreatic cancer, showed a poorer prognosis than those with low MTV. Therefore, MTV-associated differentially expressed genes (DEGs) may be candidates for distinctive markers for pancreatic cancer. This study aimed to evaluate the possibility of MTV-related DEGs as markers or therapeutic targets for pancreatic cancer. METHODS Tumor tissues and their normal counterparts were obtained from patients undergoing preoperative 18F-FDG PET/CT. The tissues were classified into MTV-low and MTV-high groups (7 for each) based on the MTV2.5 value of 4.5 (MTV-low: MTV2.5 < 4.5, MTV-high: MTV2.5 ≥ 4.5). Gene expression fold change was first calculated in cancer tissue compared to its normal counter and then compared between low and high MTV groups to obtain significant DEGs. To assess the suitability of the DEGs for clinical application, the correlation of the DEGs with tumor grades and clinical outcomes was analyzed in TCGA-PAAD, a large dataset without MTV information. RESULTS Total RNA-sequencing (MTV RNA-Seq) revealed that 44 genes were upregulated and 56 were downregulated in the high MTV group. We selected the 29 genes matching MTV RNA-seq patterns in the TCGA-PAAD dataset, a large clinical dataset without MTV information, as MTV-associated genes (MAGs). In the analysis with the TCGA dataset, MAGs were significantly associated with patient survival, treatment outcomes, TCGA-PAAD-suggested markers, and CEACAM family proteins. Some MAGs showed an inverse correlation with miRNAs and were confirmed to be differentially expressed between normal and cancerous pancreatic tissues. Overexpression of KIF11 and RCC1 and underexpression of ADCY1 and SDK1 were detected in ~ 60% of grade 2 pancreatic cancer patients and associated with ~ 60% mortality in stages I and II. CONCLUSIONS MAGs may serve as diagnostic markers and miRNA therapeutic targets for pancreatic cancer. Among the MAGs, KIF11, RCC1, ADCY, and SDK1 may be early diagnostic markers.
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Affiliation(s)
- Baek Gil Kim
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, South Korea
- Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea
| | - Sung Hwan Lee
- Division of Hepatobiliary and Pancreas, Department of Surgery, CHA Bundang Medical Center, CHA University, Pocheon, South Korea
| | - Yeonsue Jang
- Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea
| | - Suki Kang
- Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea
| | - Chang Moo Kang
- Department of Hepatobiliary and Pancreatic Surgery, Yonsei University College of Medicine, Seoul, South Korea.
- Pancreatobiliary Cancer Center, Yonsei Cancer Center, Severance Hospital, Seoul, South Korea.
| | - Nam Hoon Cho
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, South Korea.
- Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea.
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Lee JW, Ahn H, Yoo ID, Hong SP, Baek MJ, Kang DH, Lee SM. Relationship of FDG PET/CT imaging features with tumor immune microenvironment and prognosis in colorectal cancer: a retrospective study. Cancer Imaging 2024; 24:53. [PMID: 38627864 PMCID: PMC11020988 DOI: 10.1186/s40644-024-00698-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 04/09/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Imaging features of colorectal cancers on 2-deoxy-2-[18F]fluoro-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT) have been considered to be affected by tumor characteristics and tumor immune microenvironment. However, the relationship between PET/CT imaging features and immune reactions in tumor tissue has not yet been fully evaluated. This study investigated the association of FDG PET/CT imaging features in the tumor, bone marrow, and spleen with immunohistochemical results of cancer tissue and recurrence-free survival (RFS) in patients with colorectal cancer. METHODS A total of 119 patients with colorectal cancer who underwent FDG PET/CT for staging work-up and received curative surgical resection were retrospectively enrolled. From PET/CT images, 10 first-order imaging features of primary tumors, including intensity of FDG uptake, volumetric metabolic parameters, and metabolic heterogeneity parameters, as well as FDG uptake in the bone marrow and spleen were measured. The degrees of CD4+, CD8+, and CD163 + cell infiltration and interleukin-6 (IL-6) and matrix metalloproteinase-11 (MMP-11) expression were graded through immunohistochemical analysis of surgical specimens. The relationship between FDG PET/CT imaging features and immunohistochemical results was assessed, and prognostic significance of PET/CT imaging features in predicting RFS was evaluated. RESULTS Correlation analysis with immunohistochemistry findings showed that the degrees of CD4 + and CD163 + cell infiltration and IL-6 and MMP-11 expression were correlated with cancer imaging features on PET/CT. Patients with enhanced inflammatory response in cancer tissue demonstrated increased FDG uptake, volumetric metabolic parameters, and metabolic heterogeneity. FDG uptake in the bone marrow and spleen was positively correlated with the degree of CD163 + cell infiltration and IL-6 expression, respectively. In multivariate survival analysis, the coefficient of variation of FDG uptake in the tumor (p = 0.019; hazard ratio, 0.484 for 0.10 increase) and spleen-to-liver uptake ratio (p = 0.020; hazard ratio, 24.901 for 1.0 increase) were significant independent predictors of RFS. CONCLUSIONS The metabolic heterogeneity of tumors and FDG uptake in the spleen were correlated with tumor immune microenvironment and showed prognostic significance in predicting RFS in patients with colorectal cancer.
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Affiliation(s)
- Jeong Won Lee
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam- gu, 31151, Cheonan, Korea
| | - Hyein Ahn
- Department of Pathology, CHA Gangnam Medical Center, CHA University School of Medicine, 569 Nonhyon-ro, Gangnam-gu, 06135, Seoul, Korea
| | - Ik Dong Yoo
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam- gu, 31151, Cheonan, Korea
| | - Sun-Pyo Hong
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam- gu, 31151, Cheonan, Korea
| | - Moo-Jun Baek
- Department of Surgery, College of Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6- gil, Dongnam-gu, 31151, Cheonan, Korea
| | - Dong Hyun Kang
- Department of Colorectal surgery, College of Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam-gu, 31151, Cheonan, Korea
| | - Sang Mi Lee
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam- gu, 31151, Cheonan, Korea.
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Ebrahimi S, Lundström E, Batasin SJ, Hedlund E, Stålberg K, Ehman EC, Sheth VR, Iranpour N, Loubrie S, Schlein A, Rakow-Penner R. Application of PET/MRI in Gynecologic Malignancies. Cancers (Basel) 2024; 16:1478. [PMID: 38672560 PMCID: PMC11048306 DOI: 10.3390/cancers16081478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 03/23/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024] Open
Abstract
The diagnosis, treatment, and management of gynecologic malignancies benefit from both positron emission tomography/computed tomography (PET/CT) and MRI. PET/CT provides important information on the local extent of disease as well as diffuse metastatic involvement. MRI offers soft tissue delineation and loco-regional disease involvement. The combination of these two technologies is key in diagnosis, treatment planning, and evaluating treatment response in gynecological malignancies. This review aims to assess the performance of PET/MRI in gynecologic cancer patients and outlines the technical challenges and clinical advantages of PET/MR systems when specifically applied to gynecologic malignancies.
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Affiliation(s)
- Sheida Ebrahimi
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Elin Lundström
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Surgical Sciences, Radiology, Uppsala University, 751 85 Uppsala, Sweden
- Center for Medical Imaging, Uppsala University Hospital, 751 85 Uppsala, Sweden
| | - Summer J. Batasin
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Elisabeth Hedlund
- Department of Surgical Sciences, Radiology, Uppsala University, 751 85 Uppsala, Sweden
| | - Karin Stålberg
- Department of Women’s and Children’s Health, Uppsala University, 751 85 Uppsala, Sweden
| | - Eric C. Ehman
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Vipul R. Sheth
- Department of Radiology, Stanford University, Palo Alto, CA 94305, USA; (V.R.S.)
| | - Negaur Iranpour
- Department of Radiology, Stanford University, Palo Alto, CA 94305, USA; (V.R.S.)
| | - Stephane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Alexandra Schlein
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Rebecca Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
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Park S, Lee Y, Lee J, Min YW, Kim HK, Choi JY, Jung HA, Choi YS, Choi YL, Shim YM, Sun JM. Neoadjuvant Nivolumab Therapy for Esophageal Squamous Cell Carcinoma: A Single-Arm, Phase II Study. Cancer Res Treat 2024; 56:567-579. [PMID: 37846467 PMCID: PMC11016664 DOI: 10.4143/crt.2023.897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 10/12/2023] [Indexed: 10/18/2023] Open
Abstract
PURPOSE Programmed death-1/programmed death-ligand 1 (PD-L1) inhibitors have shown efficacy in metastatic esophageal squamous cell carcinoma (ESCC) therapy. However, data is still limited regarding neoadjuvant immunotherapy for operable ESCC. MATERIALS AND METHODS Patients with clinical stage T2 or T3 and N0 ESCC received three cycles of nivolumab therapy every two weeks before surgical resection. The primary endpoint is major pathologic responses (MPR) rate (≤ 10% of residual viable tumor [RVT]). RESULTS Total 20 patients completed the planned nivolumab therapy. Among them, 17 patients underwent surgery as protocol, showing MPR in two patients (MPR rate, 11.8%), including one pathologic complete response, on conventional pathologic response evaluation. Pathologic response was re-evaluated using the immune-related pathologic response criteria based on immune-related RVT (irRVT). Three patients were classified as immunologic major pathologic response (iMPR; ≤ 10% irRVT, iMPR rate: 17.6%), five as pathologic partial response (> 10% and < 90% irRVT), and nine as pathologic nonresponse (≥ 90% irRVT). The combined positive score (CPS) for PD-L1 in the baseline samples was predictable for iMPR, with the probability as 37.5% in CPS ≥ 10 (3/8) and 0% in CPS < 10 (0/9). CONCLUSION Although the efficacy of neoadjuvant nivolumab therapy was modest in unselected ESCC patients, further researches on neoadjuvant immunotherapy are necessary in patients with PD-L1 expressed ESCC.
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Affiliation(s)
- Sehhoon Park
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yurimi Lee
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jiyun Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yang Won Min
- Division of Gastroenterology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hong Kwan Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joon Young Choi
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyun Ae Jung
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yong Soo Choi
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yoon-La Choi
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Young Mog Shim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jong-Mu Sun
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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Salehjahromi M, Karpinets TV, Sujit SJ, Qayati M, Chen P, Aminu M, Saad MB, Bandyopadhyay R, Hong L, Sheshadri A, Lin J, Antonoff MB, Sepesi B, Ostrin EJ, Toumazis I, Huang P, Cheng C, Cascone T, Vokes NI, Behrens C, Siewerdsen JH, Hazle JD, Chang JY, Zhang J, Lu Y, Godoy MCB, Chung C, Jaffray D, Wistuba I, Lee JJ, Vaporciyan AA, Gibbons DL, Gladish G, Heymach JV, Wu CC, Zhang J, Wu J. Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept. Cell Rep Med 2024; 5:101463. [PMID: 38471502 PMCID: PMC10983039 DOI: 10.1016/j.xcrm.2024.101463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 09/07/2023] [Accepted: 02/15/2024] [Indexed: 03/14/2024]
Abstract
[18F]Fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) are indispensable components in modern medicine. Although PET can provide additional diagnostic value, it is costly and not universally accessible, particularly in low-income countries. To bridge this gap, we have developed a conditional generative adversarial network pipeline that can produce FDG-PET from diagnostic CT scans based on multi-center multi-modal lung cancer datasets (n = 1,478). Synthetic PET images are validated across imaging, biological, and clinical aspects. Radiologists confirm comparable imaging quality and tumor contrast between synthetic and actual PET scans. Radiogenomics analysis further proves that the dysregulated cancer hallmark pathways of synthetic PET are consistent with actual PET. We also demonstrate the clinical values of synthetic PET in improving lung cancer diagnosis, staging, risk prediction, and prognosis. Taken together, this proof-of-concept study testifies to the feasibility of applying deep learning to obtain high-fidelity PET translated from CT.
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Affiliation(s)
| | | | - Sheeba J Sujit
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Mohamed Qayati
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Pingjun Chen
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Muhammad Aminu
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Maliazurina B Saad
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
| | | | - Lingzhi Hong
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Ajay Sheshadri
- Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX USA
| | - Julie Lin
- Department of Pulmonary Medicine, MD Anderson Cancer Center, Houston, TX USA
| | - Mara B Antonoff
- Department of Thoracic and Cardiovascular Surgery, MD Anderson Cancer Center, Houston, TX, USA
| | - Boris Sepesi
- Department of Thoracic and Cardiovascular Surgery, MD Anderson Cancer Center, Houston, TX, USA
| | - Edwin J Ostrin
- Department of General Internal Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Iakovos Toumazis
- Department of Health Services Research, MD Anderson Cancer Center, Houston, TX, USA
| | - Peng Huang
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Chao Cheng
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Tina Cascone
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Natalie I Vokes
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Carmen Behrens
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Jeffrey H Siewerdsen
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - John D Hazle
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Joe Y Chang
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Jianhua Zhang
- Department of Genomic Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Yang Lu
- Department of Nuclear Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Myrna C B Godoy
- Department of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - David Jaffray
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Ignacio Wistuba
- Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, USA
| | - J Jack Lee
- Department of Biostatistics, MD Anderson Cancer Center, Houston, TX, USA
| | - Ara A Vaporciyan
- Department of Thoracic and Cardiovascular Surgery, MD Anderson Cancer Center, Houston, TX, USA
| | - Don L Gibbons
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Gregory Gladish
- Department of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - John V Heymach
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Carol C Wu
- Department of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Jianjun Zhang
- Department of Genomic Medicine, MD Anderson Cancer Center, Houston, TX, USA; Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA; Lung Cancer Genomics Program, MD Anderson Cancer Center, Houston, TX, USA; Lung Cancer Interception Program, MD Anderson Cancer Center, Houston, TX, USA
| | - Jia Wu
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.
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Reshtebar N, Hosseini SA, Zhuang M, Sheikhzadeh P. Estimation of kinetic parameters in dynamic FDG PET imaging based on shortened protocols: a virtual clinical study. Phys Eng Sci Med 2024; 47:199-213. [PMID: 38078995 DOI: 10.1007/s13246-023-01356-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 11/12/2023] [Indexed: 03/26/2024]
Abstract
This study investigated the estimation of kinetic parameters and production of related parametric Ki images in FDG PET imaging using the proposed shortened protocol (three 3-min/bed routine static images) by means of the simulated annealing (SA) algorithm. Six realistic heterogeneous tumors and various levels of [18F] FDG uptake were simulated by the XCAT phantom. An irreversible two-tissue compartment model (2TCM) using population-based input function was employed. By keeping two routine clinical scans fixed (60-min and 90-min post injection), the effect of the early scan time on optimizing the estimation of the pharmacokinetic parameters was investigated. The SA optimization algorithm was applied to estimate micro- and macro-parameters (K1, k2, k3, Ki). The minimum bias for most parameters was observed at a scan time of 20-min, which was < 10%. A highly significant correlation (> 0.9) as well as limited bias (< 10%) were observed between kinetic parameters generated from two methods [two-tissue compartment full dynamic scan (2TCM-full) and two-tissue compartment by SA algorithm (2TCM-SA)]. The analysis showed a strong correlation (> 0.8) between (2TCM-SA) Ki and SUV images. In addition, the tumor-to-background ratio (TBR) metric in the parametric (2TCM-SA) Ki images was significantly higher than SUV, although the SUV images provide better Contrast-to-noise ratio relative to parametric (2TCM-SA) Ki images. The proposed shortened protocol by the SA algorithm can estimate the kinetic parameters in FDG PET scan with high accuracy and robustness. It was also concluded that the parametric Ki images obtained from the 2TCM-SA as a complementary image of the SUV possess more quantification information than SUV images and can be used by the nuclear medicine specialist. This method has the potential to be an alternative to a full dynamic PET scan.
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Affiliation(s)
- Niloufar Reshtebar
- Department of Energy Engineering, Sharif University of Technology, Tehran, 8639-11365, Iran
| | - Seyed Abolfazl Hosseini
- Department of Energy Engineering, Sharif University of Technology, Tehran, 8639-11365, Iran.
| | - Mingzan Zhuang
- Department of Nuclear Medicine, Meizhou People's Hospital, Meizhou, 514011, China
| | - Peyman Sheikhzadeh
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Nuclear Medicine Department, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
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Song J, Pang W, Yi H, Ji J, Ye X, Li L. Tumor and metastatic lymph nodes metabolic activity on 18F-FDG-PET/CT to predict progression-free survival in locally advanced cervical cancer. Abdom Radiol (NY) 2024; 49:975-984. [PMID: 38302763 DOI: 10.1007/s00261-023-04158-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 12/11/2023] [Accepted: 12/16/2023] [Indexed: 02/03/2024]
Abstract
OBJECTIVE The present study investigated the predictive diseases progression value of preoperative fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with local advanced cervical cancer (LACC). METHODS In total, 267 patients [median age 58 (range: 27-85) years old] with LACC underwent 18F-FDG PET/CT prior to any treatment. The maximum standardized uptake values (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary lesion and metastatic lymph nodes were measured on PET/CT and correlated with clinicopathological features and progression-free survival (PFS). RESULTS The median follow-up was 36.52 (range: 3.09-61.29) months. During the observation period, 80 (30.0%) patients exhibited disease progression. Univariate analysis showed that FIGO stage, concurrent chemoradiotherapy (CRT), serum level of carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCC-Ag), primary tumor MTV (pMTV) and TLG (pTLG), lymph nodes SUVmax (nSUVmax) and TLG (nTLG), and total metabolic activity (sMTV, sTLG) were associated with PFS. nSUVmax ≥ 5.29, CEA ≥ 7.11 ng/ml and deficiency of concurrent CRT were independent risk factor for PFS (p = 0.006, p = 0.008, p = 0.014). The 3-year PFS for patients with high nSUVmax were 42.2% compared to 56.3% for low nSUVmax values. CONCLUSION Pretreatment cervical and lymph nodes metabolic parameters were associated with PFS in patients with LACC.
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Affiliation(s)
- Jinling Song
- Department of Nuclear Medicine, Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003), Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1, East Banshan Road, Gongshu District, Hangzhou, 310022, Zhejiang, People's Republic of China
| | - Weiqiang Pang
- Department of Nuclear Medicine, Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003), Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1, East Banshan Road, Gongshu District, Hangzhou, 310022, Zhejiang, People's Republic of China
| | - Heqing Yi
- Department of Nuclear Medicine, Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003), Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1, East Banshan Road, Gongshu District, Hangzhou, 310022, Zhejiang, People's Republic of China
| | - Jianfeng Ji
- Department of Nuclear Medicine, Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003), Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1, East Banshan Road, Gongshu District, Hangzhou, 310022, Zhejiang, People's Republic of China
| | - Xuemei Ye
- Department of Nuclear Medicine, Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003), Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1, East Banshan Road, Gongshu District, Hangzhou, 310022, Zhejiang, People's Republic of China
| | - Linfa Li
- Department of Nuclear Medicine, Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003), Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1, East Banshan Road, Gongshu District, Hangzhou, 310022, Zhejiang, People's Republic of China.
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Wang C, Wang G, Wang W, Kan Y, Zhang M, Yang J. The role of 18F-FDG PET/CT metabolic parameters in the differential diagnosis of post-transplant lymphoproliferative disorder after pediatric liver transplantation. Quant Imaging Med Surg 2024; 14:1323-1334. [PMID: 38415126 PMCID: PMC10895102 DOI: 10.21037/qims-23-1059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/17/2023] [Indexed: 02/29/2024]
Abstract
Background Post-transplant lymphoproliferative disorder (PTLD) is a significant complication after liver transplantation. Research on the diagnostic value of the Fluorine-18 fluorodeoxyglucose positron emission tomography/computerized tomography (18F-FDG PET/CT) metabolic parameters of PTLD in pediatric liver transplantation (pLT) recipients is limited. This study sought to evaluate the diagnostic efficacy of 18F-FDG PET/CT in differentiating between PTLD and non-PTLD lymphadenopathy in pLT recipients. Methods This retrospective study collected the 18F-FDG PET/CT scans with clinical and pathological information of all consecutive children who were clinically suspected of PTLD from November 2016 to September 2022 at the Beijing Friendship Hospital. The 18F-FDG PET/CT metabolic parameters of the two groups were analyzed. We then established a diagnostic model composed of the clinical characteristics and metabolic parameters. Results In total, 57 eligible patients were enrolled in this study, of whom 40 had PTLD and 17 had non-PTLD lymphadenopathy. Of the metabolic parameters examined in this study, total lesion glycolysis (TLG) had the highest area under the curve (AUC) value [0.757, 95% confidence interval (CI): 0.632-0.883, P=0.002]. The AUCs of the other metabolic parameters were all less than the AUC of TLG, including the maximum standardized uptake value (SUVmax) (AUC: 0.725, 95% CI: 0.597-0.853, P=0.008), mean standardized uptake value (SUVmean) (AUC: 0.701, 95% CI: 0.568-0.834, P=0.017), metabolic tumor volume total (MTVtotal) (AUC: 0.688, 95% CI: 0.549-0.827, P=0.040), TLG total (AUC: 0.674, 95% CI: 0.536-0.812, P=0.026). The diagnostic model, which was composed of clinical characteristics (digestive symptoms), the SUVmax, TLG, and the MTVtotal, showed excellent performance in the differential diagnosis (sensitivity: 0.675, 95% CI: 0.508-0.809; specificity: 0.941, 95% CI: 0.692-0.997; positive predictive value: 0.964, 95% CI: 0.798-0.998; and negative predictive value: 0.552, 95% CI: 0.360-0.730). Conclusions The 18F-FDG PET/CT metabolic parameters can be used to distinguishing between PTLD and non-PTLD lymphadenopathy in pLT recipients.
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Affiliation(s)
- Chaoran Wang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Guanyun Wang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Wei Wang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Ying Kan
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Mingyu Zhang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Jigang Yang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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Zirakchian Zadeh M. The role of conventional and novel PET radiotracers in assessment of myeloma bone disease. Bone 2024; 179:116957. [PMID: 37972747 DOI: 10.1016/j.bone.2023.116957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 11/19/2023]
Abstract
Over 80 % of patients with multiple myeloma (MM) experience osteolytic bone lesions, primarily due to an imbalanced interaction between osteoclasts and osteoblasts. This imbalance can lead to several adverse outcomes such as pain, fractures, limited mobility, and neurological impairments. Myeloma bone disease (MBD) raises the expense of management in addition to being a major source of disability and morbidity in myeloma patients. Whole-body x-ray radiography was the gold standard imaging modality for detecting lytic lesions. Osteolytic lesions are difficult to identify at an earlier stage on X-ray since the lesions do not manifest themselves on conventional radiographs until at least 30 % to 50 % of the bone mass has been destroyed. Hence, early diagnosis of osteolytic lesions necessitates the utilization of more complex and advanced imaging modalities, such as PET. One of the PET radiotracers that has been frequently investigated in MM is 18F-FDG, which has demonstrated a high level of sensitivity and specificity in detecting myeloma lesions. However, 18F-FDG PET/CT has several restrictions, and therefore the novel PET tracers that can overcome the limitations of 18F-FDG PET/CT should be further examined in assessment of MBD. The objective of this review article is to thoroughly examine the significance of both conventional and novel PET radiotracers in the assessment of MBD. The intention is to present the information in a manner that would be easily understood by healthcare professionals from diverse backgrounds, while minimizing the use of complex nuclear medicine terminology.
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Affiliation(s)
- Mahdi Zirakchian Zadeh
- Molecular Imaging and Therapy and Interventional Radiology Services, Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
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Wang Y, Li Y, Jiang H, Zuo C, Xu W. Elevated splenic 18F-fluorodeoxyglucose positron emission tomography/computed tomography activity is associated with 5-year risk of recurrence in non-metastatic invasive ductal carcinoma of the breast. Br J Radiol 2024; 97:237-248. [PMID: 38263821 PMCID: PMC11027281 DOI: 10.1093/bjr/tqad015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 10/31/2023] [Accepted: 11/06/2023] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVE To construct prediction models including baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters of tumoural lesions and non-tumour lymphoid tissue for recurrence-free survival within 5 years (5y-RFS) after imaging examination in patients with invasive ductal carcinomas (IDCs) of the breast. METHODS The study included 101 consecutive female patients. Univariable and multivariable Cox regression were used to identify clinicopathological and metabolic parameters associated with risk of recurrence. Four prediction models based on the results of multivariable analysis were constructed and visualized as nomograms. Performance of each nomogram was evaluated using the concordance index (C-index), integrated discrimination improvement, decision curve analysis (DCA), and calibration curve. RESULTS N3 status, total metabolic tumour volume, the maximum standardized uptake value of spleen, and spleen-to-liver ratio were significant predictors of 5y-RFS. The nomogram including all significant predictors demonstrated superior predictive performance for 5y-RFS, with a C-index of 0.907 (95% CI, 0.833-0.981), greatest net benefit on DCA, good accuracy on calibration curves, and excellent risk stratification on Kaplan-Meier curves. CONCLUSIONS The model that included metabolic parameters of the spleen had the best performance for predicting 5y-RFS in patients with IDCs of the breast. This model may guide personalized treatment decisions and inform patients and clinicians about prognosis. ADVANCES IN KNOWLEDGE This research identifies 18F-FDG PET/CT metabolic parameters of non-tumour lymphoid tissue as predictors of recurrence in breast cancer.
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Affiliation(s)
- Yiting Wang
- Department of Nuclear Medicine, Changhai Hospital, Naval Medical University, Shanghai 200433, PR China
| | - Yuchao Li
- Department of Nuclear Medicine, Changhai Hospital, Naval Medical University, Shanghai 200433, PR China
| | - Hongyuan Jiang
- Department of Nuclear Medicine, Changhai Hospital, Naval Medical University, Shanghai 200433, PR China
| | - Changjing Zuo
- Department of Nuclear Medicine, Changhai Hospital, Naval Medical University, Shanghai 200433, PR China
| | - Wengui Xu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, PR China
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Pham A, Garai I, Árpád K, Dér Á, Szanto E, Hascsi Z, Bátyi F, Berényi E, Pham TM. Impact of Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography on Therapeutic Decisions and Radiotherapy Planning in Head and Neck Squamous Carcinoma: A Retrospective Study of 46 Patients. Med Sci Monit 2024; 30:e942122. [PMID: 38243589 PMCID: PMC10807175 DOI: 10.12659/msm.942122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/15/2023] [Indexed: 01/21/2024] Open
Abstract
BACKGROUND Positron emission tomography/computed tomography (PET/CT) using fluorodeoxyglucose (FDG) is essential in oncology for precise tumor delineation. This study evaluated FDG PET/CT's impact on therapeutic decisions in head and neck cancer, comparing metabolic tumor volumes (MTV) measured by different methods with radiotherapy targets, crucial for treatment planning and patient outcomes. MATERIAL AND METHODS We retrospectively analyzed 46 patients with histologically confirmed head and neck cancer who underwent FDG PET/CT examination before radiotherapy. The mean age was 62 years (46-78 years). Then, we calculated MTV of the primary tumor or local recurrence using a local threshold of 41% of the standard uptake volume (SUV) corrected for lean body mass (SULmax) of the lesion and absolute threshold of SUV 2.5. Descriptive analysis of the recruited patients was assessed based on the clinical database (Medsol). RESULTS The study included 45 patients with squamous carcinoma and 1 with sarcoid cell carcinoma. PET/CT examination led to therapeutic decision changes in 11 cases. No significant difference was found in median values of Gross Tumor Volume (GTV) and MTV absolute (p=0.130). However, significant differences were observed in MTV local, MTV absolute, and GTV median values (p<0.001), with both MTVs showing significant correlation with GTV (p<0.01), especially MTV absolute (r=0.886). CONCLUSIONS FDG PET/CT examination prior to radiotherapy significantly influences therapeutic decisions in head and neck cancer patients. Based on our findings, the absolute threshold method (SUV: 2.5) appears to be an effective approach for calculating MTV for radiotherapy planning purposes.
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Affiliation(s)
- Anh Pham
- Department of Radiology, Hanoi Medical University, Hanoi, Vietnam
| | - Ildiko Garai
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, University of Debrecen, Debrecen, Hungary
| | - Kovács Árpád
- Department of Oncoradiology, University of Debrecen, Debrecen, Hungary
| | - Ádám Dér
- Department of Oncoradiology, University of Debrecen, Debrecen, Hungary
| | - Erika Szanto
- Department of Oncoradiology, University of Debrecen, Debrecen, Hungary
| | - Zsolt Hascsi
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, University of Debrecen, Debrecen, Hungary
| | - Ferenc Bátyi
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, University of Debrecen, Debrecen, Hungary
| | - Ervin Berényi
- Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, University of Debrecen, Debrecen, Hungary
| | - Thong Minh Pham
- Department of Radiology, Hanoi Medical University, Hanoi, Vietnam
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Jalloul W, Moscalu M, Moscalu R, Jalloul D, Grierosu IC, Gutu M, Haba D, Mocanu V, Gutu MM, Stefanescu C. Are MTV and TLG Accurate for Quantifying the Intensity of Brown Adipose Tissue Activation? Biomedicines 2024; 12:151. [PMID: 38255256 PMCID: PMC10813038 DOI: 10.3390/biomedicines12010151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 12/31/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
Recent research has suggested that one novel mechanism of action for anti-obesity medications is to stimulate the activation of brown adipose tissue (BAT). 18FDG PET/CT remains the gold standard for defining and quantifying BAT. SUVmax is the most often used quantification tool in clinical practice. However, this parameter does not reflect the entire BAT volume. As a potential method for precisely evaluating BAT, we have utilised metabolic tumour volume (MTV) and total lesion glycolysis (TLG) to answer the question: Are MTV and TLG accurate in quantifying the intensity of BAT activation? After analysing the total number of oncological 18F-FDG PET/CT scans between 2021-2023, we selected patients with active BAT. Based on the BAT SUVmax, the patients were divided into BAT-moderate activation (MA) vs. BAT-high activation (HA). Furthermore, we statistically analysed the accuracy of TLG and MTV in assessing BAT activation intensity. The results showed that both parameters increased their predictive value regarding BAT activation, and presented a significantly high sensitivity and specificity for the correct classification of BAT activation intensity. To conclude, these parameters could be important indicators with increased accuracy for classifying BAT expression, and could bring additional information about the volume of BAT to complement the limitations of the SUVmax.
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Affiliation(s)
- Wael Jalloul
- Department of Biophysics and Medical Physics-Nuclear Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (W.J.); (D.J.); (I.C.G.); (C.S.)
| | - Mihaela Moscalu
- Department of Preventive Medicine and Interdisciplinarity, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Roxana Moscalu
- Manchester Academic Health Science Centre, Cell Matrix Biology and Regenerative Medicine, The University of Manchester, Manchester M13 9PT, UK;
| | - Despina Jalloul
- Department of Biophysics and Medical Physics-Nuclear Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (W.J.); (D.J.); (I.C.G.); (C.S.)
| | - Irena Cristina Grierosu
- Department of Biophysics and Medical Physics-Nuclear Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (W.J.); (D.J.); (I.C.G.); (C.S.)
| | - Mihaela Gutu
- County Hospital of Emergency “Saint John the New”, 720224 Suceava, Romania; (M.G.); (M.M.G.)
| | - Danisia Haba
- Department 1 Surgery, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
| | - Veronica Mocanu
- Department of Morpho-Functional Sciences (Pathophysiology), “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
| | - Mihai Marius Gutu
- County Hospital of Emergency “Saint John the New”, 720224 Suceava, Romania; (M.G.); (M.M.G.)
| | - Cipriana Stefanescu
- Department of Biophysics and Medical Physics-Nuclear Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (W.J.); (D.J.); (I.C.G.); (C.S.)
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Nicolò E, Tarantino P, D’Ecclesiis O, Antonarelli G, Boscolo Bielo L, Marra A, Gandini S, Crimini E, Giugliano F, Zagami P, Corti C, Trapani D, Morganti S, Criscitiello C, Locatelli M, Belli C, Esposito A, Minchella I, Cristofanilli M, Tolaney SM, Curigliano G. Baseline Tumor Size as Prognostic Index in Patients With Advanced Solid Tumors Receiving Experimental Targeted Agents. Oncologist 2024; 29:75-83. [PMID: 37548439 PMCID: PMC10769799 DOI: 10.1093/oncolo/oyad212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 06/30/2023] [Indexed: 08/08/2023] Open
Abstract
BACKGROUND Baseline tumor size (BTS) has been associated with outcomes in patients with cancer treated with immunotherapy. However, the prognostic impact of BTS on patients receiving targeted therapies (TTs) remains undetermined. METHODS We reviewed data of patients with advanced solid tumors consecutively treated within early-phase clinical trials at our institution from 01/2014 to 04/2021. Treatments were categorized as immunotherapy-based or TT-based (biomarker-matched or not). BTS was calculated as the sum of RECIST1.1 baseline target lesions. RESULTS A total of 444 patients were eligible; the median BTS was 69 mm (IQR 40-100). OS was significantly longer for patients with BTS lower versus higher than the median (16.6 vs. 8.2 months, P < .001), including among those receiving immunotherapy (12 vs. 7.5 months, P = .005). Among patients receiving TT, lower BTS was associated with longer PFS (4.7 vs. 3.1 months, P = .002) and OS (20.5 vs. 9.9 months, P < .001) as compared to high BTS. However, such association was only significant among patients receiving biomarker-matched TT, with longer PFS (6.2 vs. 3.3 months, P < .001) and OS (21.2 vs. 6.7 months, P < .001) in the low-BTS subgroup, despite a similar ORR (28% vs. 22%, P = .57). BTS was not prognostic among patients receiving unmatched TT, with similar PFS (3.7 vs. 4.4 months, P = .30), OS (19.3 vs. 11.8 months, P = .20), and ORR (33% vs. 28%, P = .78) in the 2 BTS groups. Multivariate analysis confirmed that BTS was independently associated with PFS (P = .03) and OS (P < .001) but not with ORR (P = .11). CONCLUSIONS Higher BTS is associated with worse survival outcomes among patients receiving biomarker-matched, but not biomarker-unmatched TT.
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Affiliation(s)
- Eleonora Nicolò
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Paolo Tarantino
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Oriana D’Ecclesiis
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Gabriele Antonarelli
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Luca Boscolo Bielo
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Antonio Marra
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
| | - Sara Gandini
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Edoardo Crimini
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Federica Giugliano
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Paola Zagami
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Chiara Corti
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Dario Trapani
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
| | - Stefania Morganti
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Carmen Criscitiello
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Marzia Locatelli
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
| | - Carmen Belli
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
| | - Angela Esposito
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
| | - Ida Minchella
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
| | - Massimo Cristofanilli
- Department of Medicine, Division of Hematology-Oncology, Weill Cornell Medicine, New York, NY, USA
| | - Sara M Tolaney
- Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Giuseppe Curigliano
- Division of New Drugs and Early Drug Development, European Institute of Oncology, IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
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Wang F, Liu C, Vidal I, Mana-Ay M, Voter AF, Solnes LB, Ross AE, Gafita A, Schaeffer EM, Bivalacqua TJ, Pienta KJ, Pomper MG, Lodge MA, Song DY, Oldan JD, Allaf ME, De Marzo AM, Sheikhbahaei S, Gorin MA, Rowe SP. Comparison of Multiple Segmentation Methods for Volumetric Delineation of Primary Prostate Cancer with Prostate-Specific Membrane Antigen-Targeted 18F-DCFPyL PET/CT. J Nucl Med 2024; 65:87-93. [PMID: 38050147 PMCID: PMC10755517 DOI: 10.2967/jnumed.123.266005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 10/17/2023] [Indexed: 12/06/2023] Open
Abstract
This study aimed to assess the accuracy of intraprostatic tumor volume measurements on prostate-specific membrane antigen-targeted 18F-DCFPyL PET/CT made with various segmentation methods. An accurate understanding of tumor volumes versus segmentation techniques is critical for therapy planning, such as radiation dose volume determination and response assessment. Methods: Twenty-five men with clinically localized, high-risk prostate cancer were imaged with 18F-DCFPyL PET/CT before radical prostatectomy. The tumor volumes and tumor-to-prostate ratios (TPRs) of dominant intraprostatic foci of uptake were determined using semiautomatic segmentation (applying SUVmax percentage [SUV%] thresholds of SUV30%-SUV70%), adaptive segmentation (using adaptive segmentation percentage [A%] thresholds of A30%-A70%), and manual contouring. The histopathologic tumor volume (TV-Histo) served as the reference standard. The significance of differences between TV-Histo and PET-based tumor volume were assessed using the paired-sample Wilcoxon signed-rank test. The Spearman correlation coefficient was used to establish the strength of the association between TV-Histo and PET-derived tumor volume. Results: Median TV-Histo was 2.03 cm3 (interquartile ratio [IQR], 1.16-3.36 cm3), and median TPR was 10.16%. The adaptive method with an A40% threshold most closely determined the tumor volume, with a median difference of +0.19 (IQR, -0.71 to +2.01) and a median relative difference of +7.6%. The paired-sample Wilcoxon test showed no significant difference in PET-derived tumor volume and TV-Histo using A40%, A50%, SUV40%, and SUV50% threshold segmentation algorithms (P > 0.05). For both threshold-based segmentation methods, use of higher thresholds (e.g., SUV60% or SUV70% and A50%-A70%) resulted in underestimation of tumor volumes, and use of lower thresholds (e.g., SUV30% or SUV40% and A30%) resulted in overestimation of tumor volumes relative to TV-Histo and TPR. Manual segmentation overestimated the tumor volume, with a median difference of +2.49 (IQR, 0.42-4.11) and a median relative difference of +130%. Conclusion: Segmentation of intraprostatic tumor volume and TPR with an adaptive segmentation approach most closely approximates TV-Histo. This information might be used to guide the primary treatment of men with clinically localized, high-risk prostate cancer.
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Affiliation(s)
- Felicia Wang
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Chen Liu
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Beijing, China
- Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Igor Vidal
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | | | - Andrew F Voter
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Lilja B Solnes
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Brady Urological Institute, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Urology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Ashley E Ross
- Department of Urology, Feinberg School of Medicine, Northwestern Medicine, Chicago, Illinois
| | - Andrei Gafita
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Edward M Schaeffer
- Department of Urology, Feinberg School of Medicine, Northwestern Medicine, Chicago, Illinois
| | - Trinity J Bivalacqua
- Division of Urology, Perelman Center for Advanced Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Kenneth J Pienta
- Brady Urological Institute, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Urology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Martin G Pomper
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Brady Urological Institute, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Urology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Martin A Lodge
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Daniel Y Song
- Brady Urological Institute, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Urology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Radiation Oncology and Molecular Radiation Science, Sidney Kimmel Comprehensive Center, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Jorge D Oldan
- Molecular Imaging and Therapeutics, University of North Carolina, Chapel Hill, North Carolina; and
| | - Mohamad E Allaf
- Brady Urological Institute, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Urology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Angelo M De Marzo
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Brady Urological Institute, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Urology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Sara Sheikhbahaei
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Michael A Gorin
- Milton and Carroll Petrie Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Steven P Rowe
- Molecular Imaging and Therapeutics, University of North Carolina, Chapel Hill, North Carolina; and
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Seifert R, Gafita A, Telli T, Voter A, Herrmann K, Pomper M, Hadaschik B, Rowe SP, Fendler WP. Standardized PSMA-PET Imaging of Advanced Prostate Cancer. Semin Nucl Med 2024; 54:60-68. [PMID: 37573199 DOI: 10.1053/j.semnuclmed.2023.07.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/14/2023]
Abstract
Imaging of advanced prostate cancer is a challenging task, as it requires longitudinal characterization of disease extent in a standardized way to enable appropriate treatment selection and evaluation of treatment efficacy. In the last years, prostate-specific membrane antigen (PSMA)-PET/CT has become the reference standard examination for patients with advanced prostate cancer. Together with the rise of PSMA-PET, standardized frameworks for the reporting of image findings have been proposed, eg, the Prostate Cancer Molecular Imaging Standardized Evaluation (PROMISE) and the structured reporting system for PSMA targeted PET imaging (PSMA-RADS) framework. Therefore, recent evidence on PSMA-PET derived tumor volume as useful a biomarker for outcome prognostication and related frameworks will be discussed in the article. The PROMISE framework recommends quantifying the tumor volume per-organ system, which accounts for the fact that the location of the metastases greatly influence its biological aggressiveness. In addition, changes in PSMA-PET derived tumor volume have been shown to be promising biomarkers for response assessment. Limitations of PSMA-PET will also be discussed because the tumor volume might not always be suited for response assessment. As a pitfall of PSMA-based systems, decreasing PSMA-expression might erroneously be interpreted as response to therapy. Also, especially for patients with limited disease, the tumor volume might not be ideal for response assessment. Therefore, various frameworks have been introduced to objectively measure response to therapy with PSMA-PET. Amongst these, the PSMA-PET progression (PPP) criteria and the response evaluation criteria in PSMA (RECIP) are optimized for earlier and later phenotypes of advanced prostate cancer, respectively. Variables needed to determine PPP or RECIP outcome on PSMA-PET are recorded under the umbrella of PROMISE recommendations. In this article, various reporting and response assessment frameworks are explained and discussed. Also, recent evidence for the relevance of PSMA-PET biomarkers for clinical management and outcome prognostication are shown.
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Affiliation(s)
- R Seifert
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany.
| | - A Gafita
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - T Telli
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Andrew Voter
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - K Herrmann
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Martin Pomper
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - B Hadaschik
- Department of Urology, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Steven P Rowe
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - W P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany; PET Committee of the German Society of Nuclear Medicine, Göttingen, Germany
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Zirakchian Zadeh M. PET/CT in assessment of colorectal liver metastases: a comprehensive review with emphasis on 18F-FDG. Clin Exp Metastasis 2023; 40:465-491. [PMID: 37682423 DOI: 10.1007/s10585-023-10231-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 08/21/2023] [Indexed: 09/09/2023]
Abstract
Approximately 25% of those who are diagnosed with colorectal cancer will develop colorectal liver metastases (CRLM) as their illness advances. Despite major improvements in both diagnostic and treatment methods, the prognosis for patients with CRLM is still poor, with low survival rates. Accurate employment of imaging methods is critical in identifying the most effective treatment approach for CRLM. Different imaging modalities are used to evaluate CRLM, including positron emission tomography (PET)/computed tomography (CT). Among the PET radiotracers, fluoro-18-deoxyglucose (18F-FDG), a glucose analog, is commonly used as the primary radiotracer in assessment of CRLM. As the importance of 18F-FDG-PET/CT continues to grow in assessment of CRLM, developing a comprehensive understanding of this subject becomes imperative for healthcare professionals from diverse disciplines. The primary aim of this article is to offer a simplified and comprehensive explanation of PET/CT in the evaluation of CRLM, with a deliberate effort to minimize the use of technical nuclear medicine terminology. This approach intends to provide various healthcare professionals and researchers with a thorough understanding of the subject matter.
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Affiliation(s)
- Mahdi Zirakchian Zadeh
- Molecular Imaging and Therapy and Interventional Radiology Services, Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
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Murad V, Glicksman RM, Berlin A, Santiago A, Ramotar M, Metser U. Association of PSMA PET-derived Parameters and Outcomes of Patients Treated for Oligorecurrent Prostate Cancer. Radiology 2023; 309:e231407. [PMID: 38051188 DOI: 10.1148/radiol.231407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Background Prostate-specific membrane antigen (PSMA) PET is useful in the early detection of oligorecurrent prostate cancer (PCa), but whether PSMA PET parameters can be used to identify patients who would benefit from metastasis-directed therapy (MDT) with radiation or surgery remains uncertain. Purpose To assess the association of PSMA PET parameters with outcomes of patients with oligorecurrent PCa after MDT. Materials and Methods In this retrospective analysis of a single-center phase II trial that enrolled patients with biochemical recurrence of PCa after maximal local therapy and with no evidence of disease at conventional imaging, patients underwent PSMA PET (between May 2017 and November 2021), and unveiled recurrences were treated with MDT. Maximum standardized uptake value (SUVmax) and mean standardized uptake value (SUVmean) and PSMA tumor volume derived using thresholds of 2.5 (SUVmean2.5) and 41% (SUVmean41%), respectively, were recorded for sites of recurrence on PSMA PET scans, and a molecular imaging PSMA score was assigned. These parameters were also corrected for smooth filter and partial volume effects, and the PSMA score was reassigned. Cox proportional hazards models were used to evaluate the relationship between PSMA PET parameters and outcomes. Results A total of 74 men (mean age, 68.3 years ± 6.6 [SD]) with biochemical recurrence of PCa were included. PSMA PET revealed 145 lesions in the entire cohort, of which 125 (86%) were metastatic lymph nodes. Application of the correction factor changed the PSMA score in 88 of 145 lesions (61%). Mean SUVmax, SUVmean2.5, and SUVmean41% were associated with lower risk of biochemical progression (hazard ratio [HR] range, 0.77-0.95; 95% CI: 0.61, 1.00; P = .03 to P = .04). For corrected parameters, mean SUVmax, mean SUVmean2.5, mean SUVmean41%, mean PSMA score, maximum SUVmean2.5, maximum SUVmean41%, and maximum PSMA score were associated with a lower risk of biochemical progression (HR, 0.61-0.98; 95% CI: 0.39, 1.00; P = .01 to P = .04). Conclusion Measured and corrected PSMA PET parameters were associated with biochemical progression in men with oligorecurrent PCa treated with MDT. Clinical trial registration no. NCT03160794 © RSNA, 2023 See also the editorial by Civelek in this issue.
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Affiliation(s)
- Vanessa Murad
- From University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Princess Margaret Cancer Centre, 610 University Ave, Suite 3-920, Toronto, ON, Canada M5G 2M9 (V.M., U.M.); Department of Medical Imaging (V.M., U.M.), Department of Radiation Oncology (R.M.G., A.B., M.R.), and TECHNA Institute, University Health Network (A.B., U.M.), University of Toronto, Toronto, Canada; and Radiation Medicine Program (R.M.G., A.B.) and Department of Biostatistics (A.S.), Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Rachel M Glicksman
- From University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Princess Margaret Cancer Centre, 610 University Ave, Suite 3-920, Toronto, ON, Canada M5G 2M9 (V.M., U.M.); Department of Medical Imaging (V.M., U.M.), Department of Radiation Oncology (R.M.G., A.B., M.R.), and TECHNA Institute, University Health Network (A.B., U.M.), University of Toronto, Toronto, Canada; and Radiation Medicine Program (R.M.G., A.B.) and Department of Biostatistics (A.S.), Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Alejandro Berlin
- From University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Princess Margaret Cancer Centre, 610 University Ave, Suite 3-920, Toronto, ON, Canada M5G 2M9 (V.M., U.M.); Department of Medical Imaging (V.M., U.M.), Department of Radiation Oncology (R.M.G., A.B., M.R.), and TECHNA Institute, University Health Network (A.B., U.M.), University of Toronto, Toronto, Canada; and Radiation Medicine Program (R.M.G., A.B.) and Department of Biostatistics (A.S.), Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Anna Santiago
- From University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Princess Margaret Cancer Centre, 610 University Ave, Suite 3-920, Toronto, ON, Canada M5G 2M9 (V.M., U.M.); Department of Medical Imaging (V.M., U.M.), Department of Radiation Oncology (R.M.G., A.B., M.R.), and TECHNA Institute, University Health Network (A.B., U.M.), University of Toronto, Toronto, Canada; and Radiation Medicine Program (R.M.G., A.B.) and Department of Biostatistics (A.S.), Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Matthew Ramotar
- From University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Princess Margaret Cancer Centre, 610 University Ave, Suite 3-920, Toronto, ON, Canada M5G 2M9 (V.M., U.M.); Department of Medical Imaging (V.M., U.M.), Department of Radiation Oncology (R.M.G., A.B., M.R.), and TECHNA Institute, University Health Network (A.B., U.M.), University of Toronto, Toronto, Canada; and Radiation Medicine Program (R.M.G., A.B.) and Department of Biostatistics (A.S.), Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Ur Metser
- From University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Princess Margaret Cancer Centre, 610 University Ave, Suite 3-920, Toronto, ON, Canada M5G 2M9 (V.M., U.M.); Department of Medical Imaging (V.M., U.M.), Department of Radiation Oncology (R.M.G., A.B., M.R.), and TECHNA Institute, University Health Network (A.B., U.M.), University of Toronto, Toronto, Canada; and Radiation Medicine Program (R.M.G., A.B.) and Department of Biostatistics (A.S.), Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
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Jönsson H, Ahlström H, Kullberg J. Spatial mapping of tumor heterogeneity in whole-body PET-CT: a feasibility study. Biomed Eng Online 2023; 22:110. [PMID: 38007471 PMCID: PMC10675915 DOI: 10.1186/s12938-023-01173-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 11/17/2023] [Indexed: 11/27/2023] Open
Abstract
BACKGROUND Tumor heterogeneity is recognized as a predictor of treatment response and patient outcome. Quantification of tumor heterogeneity across all scales may therefore provide critical insight that ultimately improves cancer management. METHODS An image registration-based framework for the study of tumor heterogeneity in whole-body images was evaluated on a dataset of 490 FDG-PET-CT images of lung cancer, lymphoma, and melanoma patients. Voxel-, lesion- and subject-level features were extracted from the subjects' segmented lesion masks and mapped to female and male template spaces for voxel-wise analysis. Resulting lesion feature maps of the three subsets of cancer patients were studied visually and quantitatively. Lesion volumes and lesion distances in subject spaces were compared with resulting properties in template space. The strength of the association between subject and template space for these properties was evaluated with Pearson's correlation coefficient. RESULTS Spatial heterogeneity in terms of lesion frequency distribution in the body, metabolic activity, and lesion volume was seen between the three subsets of cancer patients. Lesion feature maps showed anatomical locations with low versus high mean feature value among lesions sampled in space and also highlighted sites with high variation between lesions in each cancer subset. Spatial properties of the lesion masks in subject space correlated strongly with the same properties measured in template space (lesion volume, R = 0.986, p < 0.001; total metabolic volume, R = 0.988, p < 0.001; maximum within-patient lesion distance, R = 0.997, p < 0.001). Lesion volume and total metabolic volume increased on average from subject to template space (lesion volume, 3.1 ± 52 ml; total metabolic volume, 53.9 ± 229 ml). Pair-wise lesion distance decreased on average by 0.1 ± 1.6 cm and maximum within-patient lesion distance increased on average by 0.5 ± 2.1 cm from subject to template space. CONCLUSIONS Spatial tumor heterogeneity between subsets of interest in cancer cohorts can successfully be explored in whole-body PET-CT images within the proposed framework. Whole-body studies are, however, especially prone to suffer from regional variation in lesion frequency, and thus statistical power, due to the non-uniform distribution of lesions across a large field of view.
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Affiliation(s)
- Hanna Jönsson
- Section of Radiology, Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
| | - Håkan Ahlström
- Section of Radiology, Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden
- Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
| | - Joel Kullberg
- Section of Radiology, Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden
- Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
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Zirakchian Zadeh M. Clinical Application of 18F-FDG-PET Quantification in Hematological Malignancies: Emphasizing Multiple Myeloma, Lymphoma and Chronic Lymphocytic Leukemia. CLINICAL LYMPHOMA, MYELOMA & LEUKEMIA 2023; 23:800-814. [PMID: 37558532 DOI: 10.1016/j.clml.2023.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/15/2023] [Accepted: 07/20/2023] [Indexed: 08/11/2023]
Abstract
Most hematological malignancies display heightened glycolytic activity, leading to their detectability through 18F-FDG-PET imaging. PET quantification enables the extraction of metabolic information from tumors. Among various PET measurements, maximum standardized uptake value (SUVmax), which indicates the highest value of 18F-FDG uptake within the tumor, has emerged as the commonly used parameter in clinical oncology. This is because of SUVmax ease of calculation using most available commercial workstations, as well as its simplicity and independence from observer interpretation. Nonetheless, SUVmax represents the increase in activity within a specific small area, which may not fully capture the overall tumor uptake. Volumetric PET parameters have been identified as a potential solution to overcome certain limitations associated with SUVmax. However, these parameters are influenced by the low spatial resolution of PET when assessing small lesions. Another challenge is the high number of lesions observed in some patients, leading to a time-consuming process for evaluating all focal lesions. Some institutions recently have started advocating for CT-based segmentation as a method for measuring radiotracer uptake in the bone marrow and overall bone of the patients. This review article aims to provide insights into clinical application of PET quantification specifically focusing on 3 major hematologic malignancies: multiple myeloma, lymphoma, and chronic lymphocytic leukemia.
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Affiliation(s)
- Mahdi Zirakchian Zadeh
- Molecular Imaging and Therapy and Interventional Radiology Services, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY.
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Subtirelu RC, Teichner EM, Ashok A, Parikh C, Talasila S, Matache IM, Alnemri AG, Anderson V, Shahid O, Mannam S, Lee A, Werner T, Revheim ME, Alavi A. Advancements in dendritic cell vaccination: enhancing efficacy and optimizing combinatorial strategies for the treatment of glioblastoma. Front Neurol 2023; 14:1271822. [PMID: 38020665 PMCID: PMC10644823 DOI: 10.3389/fneur.2023.1271822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 10/11/2023] [Indexed: 12/01/2023] Open
Abstract
Glioblastomas (GBM) are highly invasive, malignant primary brain tumors. The overall prognosis is poor, and management of GBMs remains a formidable challenge, necessitating novel therapeutic strategies such as dendritic cell vaccinations (DCVs). While many early clinical trials demonstrate an induction of an antitumoral immune response, outcomes are mixed and dependent on numerous factors that vary between trials. Optimization of DCVs is essential; the selection of GBM-specific antigens and the utilization of 18F-fludeoxyglucose Positron Emission Tomography (FDG-PET) may add significant value and ultimately improve outcomes for patients undergoing treatment for glioblastoma. This review provides an overview of the mechanism of DCV, assesses previous clinical trials, and discusses future strategies for the integration of DCV into glioblastoma treatment protocols. To conclude, the review discusses challenges associated with the use of DCVs and highlights the potential of integrating DCV with standard therapies.
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Affiliation(s)
- Robert C. Subtirelu
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Eric M. Teichner
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States
| | - Arjun Ashok
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States
| | - Chitra Parikh
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States
| | - Sahithi Talasila
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States
| | - Irina-Mihaela Matache
- Department of Physiology, Faculty of Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Ahab G. Alnemri
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Victoria Anderson
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States
| | - Osmaan Shahid
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Sricharvi Mannam
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Andrew Lee
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Thomas Werner
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Mona-Elisabeth Revheim
- Division of Technology and Innovation, Oslo University Hospital, Oslo, Norway
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
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Xiong X, Smith BJ, Graves SA, Graham MM, Buatti JM, Beichel RR. Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers. Tomography 2023; 9:1933-1948. [PMID: 37888743 PMCID: PMC10611182 DOI: 10.3390/tomography9050151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023] Open
Abstract
Convolutional neural networks (CNNs) have a proven track record in medical image segmentation. Recently, Vision Transformers were introduced and are gaining popularity for many computer vision applications, including object detection, classification, and segmentation. Machine learning algorithms such as CNNs or Transformers are subject to an inductive bias, which can have a significant impact on the performance of machine learning models. This is especially relevant for medical image segmentation applications where limited training data are available, and a model's inductive bias should help it to generalize well. In this work, we quantitatively assess the performance of two CNN-based networks (U-Net and U-Net-CBAM) and three popular Transformer-based segmentation network architectures (UNETR, TransBTS, and VT-UNet) in the context of HNC lesion segmentation in volumetric [F-18] fluorodeoxyglucose (FDG) PET scans. For performance assessment, 272 FDG PET-CT scans of a clinical trial (ACRIN 6685) were utilized, which includes a total of 650 lesions (primary: 272 and secondary: 378). The image data used are highly diverse and representative for clinical use. For performance analysis, several error metrics were utilized. The achieved Dice coefficient ranged from 0.833 to 0.809 with the best performance being achieved by CNN-based approaches. U-Net-CBAM, which utilizes spatial and channel attention, showed several advantages for smaller lesions compared to the standard U-Net. Furthermore, our results provide some insight regarding the image features relevant for this specific segmentation application. In addition, results highlight the need to utilize primary as well as secondary lesions to derive clinically relevant segmentation performance estimates avoiding biases.
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Affiliation(s)
- Xiaofan Xiong
- Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242, USA
| | - Brian J. Smith
- Department of Biostatistics, The University of Iowa, Iowa City, IA 52242, USA
| | - Stephen A. Graves
- Department of Radiology, The University of Iowa, Iowa City, IA 52242, USA; (S.A.G.)
| | - Michael M. Graham
- Department of Radiology, The University of Iowa, Iowa City, IA 52242, USA; (S.A.G.)
| | - John M. Buatti
- Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA
| | - Reinhard R. Beichel
- Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA
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Feng Y, Wang P, Chen Y, Dai W. 18 F-FDG PET/CT for evaluation of metastases in nonsmall cell lung cancer on the efficacy of immunotherapy. Nucl Med Commun 2023; 44:900-909. [PMID: 37503694 PMCID: PMC10498844 DOI: 10.1097/mnm.0000000000001737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/04/2023] [Indexed: 07/29/2023]
Abstract
OBJECTIVE This study aimed to investigate the relationship between 18 F-fluorodeoxyglucose PET/computed tomography ( 18 F-FDG PET/CT) metabolic parameters and clinical benefit and prognosis in nonsmall cell lung cancer (NSCLC). METHODS In total, 34 advanced NSCLC patients who received 18 F-FDG PET/CT before immunotherapy were retrospectively included in this study. All patients were divided into two groups, the clinical benefit (CB) group and the no-clinical benefit (no-CB) group, based on the efficacy of evaluation after 6 months of treatment. Also clinical information, characteristics of metastases, survival, PD-L1 expression level and glucose metabolic parameters were evaluated. RESULTS Finally, 24 patients were in the CB group, and 10 patients were in the no-CB group. There was a significant difference between the CB group and the no-CB group in TNM stages ( P = 0.005), visceral and bone metastasis ( P = 0.031), metabolic tumor volume of primary lesion (MTV-P; P = 0.003), the metabolic tumor volume of whole-body (MTVwb; P = 0.005) and total lesion glycolysis of whole-body (TLGwb, P = 0.015). However, for patient outcomes, the independent prognostic factors associated with progression free survival were TNM stage (HR = 0.113; 95% CI, 0.029-0.439; P = 0.002), TLG-P (HR = 0.085; 95% CI, 0.018-0.402; P = 0.002) and TLG-LN (HR = 0.068; 95% CI, 0.015-0.308; P = 0.000), and the TLG-LN (HR = 0.242; 95% CI, 0.066-0.879; P = 0.002) was the independent prognostic factor associated with overall survival. CONCLUSIONS Metastatic lesion burden evaluated by 18 F-FDG PET/ CT can predict response to immunotherapy in advanced NSCLC patients, in which lymph node metastasis lesion metabolic burden is a meaningful predictor, but a large multicenter trial is still needed to validate this conclusion.
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Affiliation(s)
- Yawen Feng
- Department of Nuclear Medicine, The First College of Clinical Medical Science
| | - Peng Wang
- Department of Nuclear Medicine, The First College of Clinical Medical Science
| | - Yuqi Chen
- Department of Nuclear Medicine, The First College of Clinical Medical Science
| | - Wenli Dai
- Department of Nuclear Medicine, The First College of Clinical Medical Science
- Hubei Key Laboratory of Tumor Microenvironment and Immunotherapy, China Three Gorges University, Yichang, Hubei, China
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Bianconi F, Salis R, Fravolini ML, Khan MU, Minestrini M, Filippi L, Marongiu A, Nuvoli S, Spanu A, Palumbo B. Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [ 18F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) in Patients with Head and Neck Cancer. SENSORS (BASEL, SWITZERLAND) 2023; 23:7952. [PMID: 37766009 PMCID: PMC10537871 DOI: 10.3390/s23187952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/01/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023]
Abstract
Background. Head and neck cancer (HNC) is the seventh most common neoplastic disorder at the global level. Contouring HNC lesions on [18F] Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) scans plays a fundamental role for diagnosis, risk assessment, radiotherapy planning and post-treatment evaluation. However, manual contouring is a lengthy and tedious procedure which requires significant effort from the clinician. Methods. We evaluated the performance of six hand-crafted, training-free methods (four threshold-based, two algorithm-based) for the semi-automated delineation of HNC lesions on FDG PET/CT. This study was carried out on a single-centre population of n=103 subjects, and the standard of reference was manual segmentation generated by nuclear medicine specialists. Figures of merit were the Sørensen-Dice coefficient (DSC) and relative volume difference (RVD). Results. Median DSC ranged between 0.595 and 0.792, median RVD between -22.0% and 87.4%. Click and draw and Nestle's methods achieved the best segmentation accuracy (median DSC, respectively, 0.792 ± 0.178 and 0.762 ± 0.107; median RVD, respectively, -21.6% ± 1270.8% and -32.7% ± 40.0%) and outperformed the other methods by a significant margin. Nestle's method also resulted in a lower dispersion of the data, hence showing stronger inter-patient stability. The accuracy of the two best methods was in agreement with the most recent state-of-the art results. Conclusions. Semi-automated PET delineation methods show potential to assist clinicians in the segmentation of HNC lesions on FDG PET/CT images, although manual refinement may sometimes be needed to obtain clinically acceptable ROIs.
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Affiliation(s)
- Francesco Bianconi
- Department of Engineering, Università degli Studi di Perugia, Via Goffredo Duranti 93, 06125 Perugia, Italy; (M.L.F.); (M.U.K.)
| | - Roberto Salis
- Unit of Nuclear Medicine, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy; (R.S.); (A.M.); (S.N.)
| | - Mario Luca Fravolini
- Department of Engineering, Università degli Studi di Perugia, Via Goffredo Duranti 93, 06125 Perugia, Italy; (M.L.F.); (M.U.K.)
| | - Muhammad Usama Khan
- Department of Engineering, Università degli Studi di Perugia, Via Goffredo Duranti 93, 06125 Perugia, Italy; (M.L.F.); (M.U.K.)
| | - Matteo Minestrini
- Section of Nuclear Medicine and Health Physics, Department of Medicine and Surgery, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132 Perugia, Italy; (M.M.); (B.P.)
| | - Luca Filippi
- Policlinico Tor Vergata Hospital, Viale Oxford 81, 00133 Rome, Italy;
| | - Andrea Marongiu
- Unit of Nuclear Medicine, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy; (R.S.); (A.M.); (S.N.)
| | - Susanna Nuvoli
- Unit of Nuclear Medicine, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy; (R.S.); (A.M.); (S.N.)
| | - Angela Spanu
- Unit of Nuclear Medicine, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy; (R.S.); (A.M.); (S.N.)
| | - Barbara Palumbo
- Section of Nuclear Medicine and Health Physics, Department of Medicine and Surgery, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132 Perugia, Italy; (M.M.); (B.P.)
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Metser U, Kulanthaivelu R, Salawu A, Razak A, Mak V, Li X, Langer DL, MacCrostie P, Singnurkar A. [ 18F]FDG PET/CT in the Initial Staging and Restaging of Soft-Tissue or Bone Sarcoma in Patients with Negative or Equivocal Findings for Metastases or Limited Recurrence on Conventional Work-up: Results of a Prospective Multicenter Registry. J Nucl Med 2023; 64:1371-1377. [PMID: 37414444 DOI: 10.2967/jnumed.122.265278] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 04/25/2023] [Indexed: 07/08/2023] Open
Abstract
The purpose of this study was to determine the impact of [18F]FDG PET/CT on the initial staging, restaging, clinical management, and outcomes of patients with soft-tissue and bone sarcomas. Methods: This single-arm, prospective multicenter registry enrolled 304 patients with 320 [18F]FDG PET/CT scans (November 2018 to October 2021). Eligibility included the initial staging of a grade 2 or higher or ungradable soft-tissue or bone sarcoma, with negative or equivocal findings for nodal or distant metastases on conventional imaging before curative-intent therapy, or restaging of patients with a history of treated sarcoma with a suspicion or confirmation of local recurrence or limited metastatic disease who were being considered for curative-intent or salvage therapy. The presence of local recurrence or metastases on [18F]FDG PET/CT was recorded. Clinical management after [18F]FDG PET/CT compared with pre-[18F]FDG PET/CT planned management and quantitative metabolic tumor parameters (SUVmax, metabolic tumor volume, total lesion glycolysis) were correlated with the outcome data for 171 patients. Results: At the initial staging, [18F]FDG PET/CT detected metastases in 17 of 105 patients (16.2%) with no metastases on conventional work-up and confirmed metastases in 44 of 92 patients (47.8%) with equivocal findings for metastases. At the time of restaging, [18F]FDG PET/CT detected local recurrence in 37 of 123 patients (30.1%) and distant metastases in 71 of 123 patients (57.7%). Overall, the change in treatment intent and treatment type was recorded in 64 of 171 cases (37.4%) and 56 of 171 cases (32.8%), respectively. The presence of metastases on [18F]FDG PET/CT was associated with shorter progression-free survival at the initial staging (P = 0.04) and shorter overall survival at the time of recurrence (P = 0.002). All quantitative metabolic tumor parameters correlated with progression-free survival and overall survival. Conclusion: [18F]FDG PET/CT frequently detects additional sites of disease compared with conventional imaging in patients with sarcomas that were being considered for curative-intent or salvage therapy. This increased detection impacts the clinical management in a third of patients referred for initial staging or presumed limited recurrence after primary therapy. The presence of metastases on [18F]FDG PET/CT is associated with poorer outcomes.
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Affiliation(s)
- Ur Metser
- University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Health System, Women's College Hospital, University of Toronto, Toronto, Ontario, Canada;
| | - Roshini Kulanthaivelu
- University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network, Mount Sinai Health System, Women's College Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Abdulazeez Salawu
- Division of Medical Oncology, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Albiruni Razak
- Division of Medical Oncology, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Victor Mak
- Cancer Imaging Program, Ontario Health-Cancer Care Ontario, Toronto, Ontario, Canada
| | - Xuan Li
- Department of Biostatistics, University Health Network, Toronto, Ontario, Canada; and
| | - Deanna L Langer
- Cancer Imaging Program, Ontario Health-Cancer Care Ontario, Toronto, Ontario, Canada
| | - Pamela MacCrostie
- Cancer Imaging Program, Ontario Health-Cancer Care Ontario, Toronto, Ontario, Canada
| | - Amit Singnurkar
- Department of Medical Imaging, Sunnybrook Health Sciences Center, University of Toronto, Toronto, Ontario, Canada
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50
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Breen WG, Young JR, Hathcock MA, Kowalchuk RO, Thorpe MP, Bansal R, Khurana A, Bennani NN, Paludo J, Bisneto JV, Wang Y, Ansell SM, Peterson JL, Johnston PB, Lester SC, Lin Y. Metabolic PET/CT analysis of aggressive Non-Hodgkin lymphoma prior to Axicabtagene Ciloleucel CAR-T infusion: predictors of progressive disease, survival, and toxicity. Blood Cancer J 2023; 13:127. [PMID: 37591834 PMCID: PMC10435575 DOI: 10.1038/s41408-023-00895-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/11/2023] [Accepted: 08/01/2023] [Indexed: 08/19/2023] Open
Abstract
PET/CT is used to evaluate relapsed/refractory non-Hodgkin lymphoma (NHL) prior to chimeric antigen receptor T-cell (CAR-T) infusion at two time points: pre-leukapheresis (pre-leuk) and pre-lymphodepletion chemotherapy (pre-LD). We hypothesized that changes in PET/CT between these time points predict outcomes after CAR-T. Metabolic tumor volume (MTV), total lesion glycolysis (TLG), and other metrics were calculated from pre-leuk and pre-LD PET/CT scans in patients with NHL who received axicabtagene ciloleucel, and assessed for association with outcomes. Sixty-nine patients were analyzed. While single time point PET/CT characteristics were not associated with risk of PD or death, increases from pre-leuk to pre-LD in parenchymal MTV, nodal MTV, TLG of the largest lesion, and total number of lesions were associated with increased risk of death (p < 0.05 for all). LASSO analysis identified increasing extranodal MTV and increasing TLG of the largest lesion as strong predictors of death (AUC 0.74). Greater pre-LD total MTV was associated with higher risk of grade 3+ immune effector cell-associated neurotoxicity syndrome (ICANS) (p = 0.042). Increasing metabolic disease burden during CAR-T manufacturing is associated with increased risk of progression and death. A two variable risk score stratifies prognosis prior to CAR-T infusion and may inform risk-adapted strategies.
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Affiliation(s)
- William G Breen
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Jason R Young
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Matthew A Hathcock
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | | | | | - Radhika Bansal
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Arushi Khurana
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - N Nora Bennani
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Jonas Paludo
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Yucai Wang
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Stephen M Ansell
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Patrick B Johnston
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Scott C Lester
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Yi Lin
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
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