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Yilmaz MT, Kahvecioglu A, Yedekci FY, Yigit E, Ciftci GC, Kertmen N, Zorlu F, Yazici G. Comparison of different target volume delineation strategies based on recurrence patterns in adjuvant radiotherapy for glioblastoma. Neurooncol Pract 2024; 11:275-283. [PMID: 38737611 PMCID: PMC11085836 DOI: 10.1093/nop/npae009] [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] [Indexed: 05/14/2024] Open
Abstract
Background Radiation Therapy Oncology Group (RTOG) and the European Organization for Research and Treatment of Cancer (EORTC) recommendations are commonly used guidelines for adjuvant radiotherapy in glioblastoma. In our institutional protocol, we delineate T2-FLAIR alterations as gross target volume (GTV) with reduced clinical target volume (CTV) margins. We aimed to present our oncologic outcomes and compare the recurrence patterns and planning parameters with EORTC and RTOG delineation strategies. Methods Eighty-one patients who received CRT between 2014 and 2021 were evaluated retrospectively. EORTC and RTOG delineations performed on the simulation computed tomography and recurrence patterns and planning parameters were compared between delineation strategies. Statistical Package for the Social Sciences (SPSS) version 23.0 (IBM, Armonk, NY, USA) was utilized for statistical analyses. Results Median overall survival and progression-free survival were 21 months and 11 months, respectively. At a median 18 month follow-up, of the 48 patients for whom recurrence pattern analysis was performed, recurrence was encompassed by only our institutional protocol's CTV in 13 (27%) of them. For the remaining 35 (73%) patients, recurrence was encompassed by all separate CTVs. In addition to the 100% rate of in-field recurrence, the smallest CTV and lower OAR doses were obtained by our protocol. Conclusions The current study provides promising results for including the T2-FLAIR alterations to the GTV with smaller CTV margins with impressive survival outcomes without any marginal recurrence. The fact that our protocol did not result in larger irradiated brain volume is further encouraging in terms of toxicity.
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Affiliation(s)
- Melek Tugce Yilmaz
- Department of Radiation Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Alper Kahvecioglu
- Department of Radiation Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Fazli Yagiz Yedekci
- Department of Radiation Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Ecem Yigit
- Department of Radiation Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Gokcen Coban Ciftci
- Radiology Department, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Neyran Kertmen
- Department of Medical Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Faruk Zorlu
- Department of Radiation Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Gozde Yazici
- Department of Radiation Oncology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
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Tropeano MP, Raspagliesi L, Bono BC, Baram A, Rossini Z, Franzini A, Navarria P, Clerici E, Bellu L, Simonelli M, Scorsetti M, Riva M, Politi LS, Pessina F. Supramaximal resection: retrospective study on IDH-wildtype Glioblastomas based on the new RANO-Resect classification. Acta Neurochir (Wien) 2024; 166:196. [PMID: 38676720 DOI: 10.1007/s00701-024-06090-2] [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: 01/26/2024] [Accepted: 04/15/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND The prognostic value of the extent of resection in the management of Glioblastoma is a long-debated topic, recently widened by the 2022 RANO-Resect Classification, which advocates for the resection of the non-enhancing disease surrounding the main core of tumors (supramaximal resection, SUPR) to achieve additional survival benefits. We conducted a retrospective analysis to corroborate the role of SUPR by the RANO-Resect Classification in a single center, homogenous cohort of patients. METHODS Records of patients operated for WHO-2021 Glioblastomas at our institution between 2007 and 2018 were retrospectively reviewed; volumetric data of resected lesions were computed and classified by RANO-Resect criteria. Survival and correlation analyses were conducted excluding patients below near-total resection. RESULTS 117 patients met the inclusion criteria, encompassing 45 near-total resections (NTR), 31 complete resections (CR), and 41 SUPR. Median progression-free and overall survival were 11 and 15 months for NTR, 13 and 17 months or CR, 20 and 24 months for SUPR, respectively (p < 0.001), with inverse correlation observed between survival and FLAIR residual volume (r -0.28). SUPR was not significantly associated with larger preoperative volumes or higher rates of postoperative deficits, although it was less associated with preoperative neurological deficits (OR 3.37, p = 0.003). The impact of SUPR on OS varied between MGMT unmethylated (HR 0.606, p = 0.044) and methylated (HR 0.273, p = 0.002) patient groups. CONCLUSIONS Results of the present study support the validity of supramaximal resection by the new RANO-Resect classification, also highlighting a possible surgical difference between tumors with methylated and unmethylated MGMT promoter.
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Affiliation(s)
- Maria Pia Tropeano
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Luca Raspagliesi
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy.
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy.
| | - Beatrice Claudia Bono
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Ali Baram
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Zefferino Rossini
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Andrea Franzini
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Pierina Navarria
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Elena Clerici
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Luisa Bellu
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Matteo Simonelli
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Department of Medical Oncology and Hematology, Humanitas Clinical and Research Center - IRCCS, Humanitas Cancer Center, Milan, Italy
| | - Marta Scorsetti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Marco Riva
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
| | - Letterio Salvatore Politi
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Department of Neuroradiology, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
| | - Federico Pessina
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Milan, Pieve Emanuele, Italy
- Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Milan, Rozzano, Italy
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Styliara EI, Astrakas LG, Alexiou G, Xydis VG, Zikou A, Kafritsas G, Voulgaris S, Argyropoulou MI. Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics. Curr Oncol 2024; 31:2233-2243. [PMID: 38668068 PMCID: PMC11048751 DOI: 10.3390/curroncol31040165] [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: 03/09/2024] [Revised: 04/10/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
Background: Extracting multiregional radiomic features from multiparametric MRI for predicting pretreatment survival in isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients is a promising approach. Methods: MRI data from 49 IDH wild-type glioblastoma patients pre-treatment were utilized. Diffusion and perfusion maps were generated, and tumor subregions segmented. Radiomic features were extracted for each tissue type and map. Feature selection on 1862 radiomic features identified 25 significant features. The Cox proportional-hazards model with LASSO regularization was used to perform survival analysis. Internal and external validation used a 38-patient training cohort and an 11-patient validation cohort. Statistical significance was set at p < 0.05. Results: Age and six radiomic features (shape and first and second order) from T1W, diffusion, and perfusion maps contributed to the final model. Findings suggest that a small necrotic subregion, inhomogeneous vascularization in the solid non-enhancing subregion, and edema-related tissue damage in the enhancing and edema subregions are linked to poor survival. The model's C-Index was 0.66 (95% C.I. 0.54-0.80). External validation demonstrated good accuracy (AUC > 0.65) at all time points. Conclusions: Radiomics analysis, utilizing segmented perfusion and diffusion maps, provide predictive indicators of survival in IDH wild-type glioblastoma patients, revealing associations with microstructural and vascular heterogeneity in the tumor.
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Affiliation(s)
- Effrosyni I. Styliara
- Department of Radiology, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (E.I.S.); (V.G.X.); (A.Z.); (M.I.A.)
| | - Loukas G. Astrakas
- Medical Physics Lab, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece;
| | - George Alexiou
- Department of Neurosurgery, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (G.K.); (S.V.)
| | - Vasileios G. Xydis
- Department of Radiology, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (E.I.S.); (V.G.X.); (A.Z.); (M.I.A.)
| | - Anastasia Zikou
- Department of Radiology, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (E.I.S.); (V.G.X.); (A.Z.); (M.I.A.)
| | - Georgios Kafritsas
- Department of Neurosurgery, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (G.K.); (S.V.)
| | - Spyridon Voulgaris
- Department of Neurosurgery, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (G.K.); (S.V.)
| | - Maria I. Argyropoulou
- Department of Radiology, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (E.I.S.); (V.G.X.); (A.Z.); (M.I.A.)
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Wang L, Wang H, D’Angelo F, Curtin L, Sereduk CP, Leon GD, Singleton KW, Urcuyo J, Hawkins-Daarud A, Jackson PR, Krishna C, Zimmerman RS, Patra DP, Bendok BR, Smith KA, Nakaji P, Donev K, Baxter LC, Mrugała MM, Ceccarelli M, Iavarone A, Swanson KR, Tran NL, Hu LS, Li J. Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. PLoS One 2024; 19:e0299267. [PMID: 38568950 PMCID: PMC10990246 DOI: 10.1371/journal.pone.0299267] [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: 07/31/2023] [Accepted: 02/06/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND AND OBJECTIVE Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.
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Affiliation(s)
- Lujia Wang
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Hairong Wang
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Fulvio D’Angelo
- Institute for Cancer Genetics, Columbia University Medical Center, New York City, New York, United States of America
| | - Lee Curtin
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Christopher P. Sereduk
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Gustavo De Leon
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Kyle W. Singleton
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Javier Urcuyo
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Andrea Hawkins-Daarud
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Pamela R. Jackson
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Chandan Krishna
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Richard S. Zimmerman
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Devi P. Patra
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Bernard R. Bendok
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute—St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Peter Nakaji
- Department of Neurosurgery, Barrow Neurological Institute—St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Kliment Donev
- Department of Pathology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Leslie C. Baxter
- Department of Neuropsychology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Maciej M. Mrugała
- Department of Neuro-Oncology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Michele Ceccarelli
- Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, Naples, Italy
| | - Antonio Iavarone
- Institute for Cancer Genetics, Columbia University Medical Center, New York City, New York, United States of America
| | - Kristin R. Swanson
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Nhan L. Tran
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
- Department of Cancer Biology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Jing Li
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
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Harat M, Miechowicz I, Rakowska J, Zarębska I, Małkowski B. A Biopsy-Controlled Prospective Study of Contrast-Enhancing Diffuse Glioma Infiltration Based on FET-PET and FLAIR. Cancers (Basel) 2024; 16:1265. [PMID: 38610944 PMCID: PMC11010945 DOI: 10.3390/cancers16071265] [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: 01/19/2024] [Revised: 03/15/2024] [Accepted: 03/16/2024] [Indexed: 04/14/2024] Open
Abstract
Accurately defining glioma infiltration is crucial for optimizing radiotherapy and surgery, but glioma infiltration is heterogeneous and MRI imperfectly defines the tumor extent. Currently, it is impossible to determine the tumor infiltration gradient within a FLAIR signal. O-(2-[18F]fluoroethyl)-L-tyrosine (FET)-PET often reveals high-grade glioma infiltration beyond contrast-enhancing areas on MRI. Here, we studied FET uptake dynamics in tumor and normal brain structures by dual-timepoint (10 min and 40-60 min post-injection) acquisition to optimize analysis protocols for defining glioma infiltration. Over 300 serial stereotactic biopsies from 23 patients (mean age 47, 12 female/11 male) of diffuse contrast-enhancing gliomas were taken from areas inside and outside contrast enhancement or outside the FET hotspot but inside FLAIR. The final diagnosis was G4 in 11, grade 3 in 10, and grade 2 in 2 patients. The target-to-background (TBRs) ratios and standardized uptake values (SUVs) were calculated in areas used for biopsy planning and in background structures. The optimal method and threshold values were determined to find a preferred strategy for defining glioma infiltration. Standard thresholding (1.6× uptake in the contralateral brain) in standard acquisition PET images differentiated a tumor of any grade from astrogliosis, although the uptake in astrogliosis and grade 2 glioma was similar. Analyzing an optimal strategy for infiltration volume definition astrogliosis could be accurately differentiated from tumor samples using a choroid plexus as a background. Early acquisition improved the AUC in many cases, especially within FLAIR, from 56% to 90% sensitivity and 41% to 61% specificity (standard TBR 1.6 vs. early TBR plexus). The current FET-PET evaluation protocols for contrast-enhancing gliomas are limited, especially at the tumor border where grade 2 tumor and astrogliosis have similar uptake, but using choroid plexus uptake in early acquisitions as a background, we can precisely define a tumor within FLAIR that was outside of the scope of current FET-PET protocols.
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Affiliation(s)
- Maciej Harat
- Department of Neurooncology and Radiosurgery, Franciszek Lukaszczyk Oncology Center, 85-796 Bydgoszcz, Poland
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, 85-796 Bydgoszcz, Poland
| | - Izabela Miechowicz
- Department of Computer Science and Statistics, Poznan University of Medical Sciences, 61-701 Poznań, Poland;
| | - Józefina Rakowska
- Department of Neurosurgery, 10th Military Research Hospital, 85-681 Bydgoszcz, Poland;
| | - Izabela Zarębska
- Department of Radiotherapy, Franciszek Lukaszczyk Oncology Center, 85-796 Bydgoszcz, Poland;
| | - Bogdan Małkowski
- Department of Nuclear Medicine, Franciszek Lukaszczyk Oncology Center, 85-796 Bydgoszcz, Poland
- Department of Diagnostic Imaging, Ludwik Rydygier Collegium Medicum, Nicolaus Copernicus University, 85-067 Bydgoszcz, Poland
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He L, Zhang H, Li T, Yang J, Zhou Y, Wang J, Saidaer T, Liu X, Wang L, Wang Y. Distinguishing Tumor Cell Infiltration and Vasogenic Edema in the Peritumoral Region of Glioblastoma at the Voxel Level via Conventional MRI Sequences. Acad Radiol 2024; 31:1082-1090. [PMID: 37689557 DOI: 10.1016/j.acra.2023.08.008] [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: 06/02/2023] [Revised: 07/22/2023] [Accepted: 08/07/2023] [Indexed: 09/11/2023]
Abstract
RATIONALE AND OBJECTIVES The peritumoral region of glioblastoma (GBM) is composed of infiltrating tumor cells and vasogenic edema, which are difficult to distinguish manually on MRI. To distinguish tumor cell infiltration and vasogenic edema in GBM peritumoral regions, it is crucial to develop a method that is precise, effective, and widely applicable. MATERIALS AND METHODS We retrieved the image characteristics of 379,730 voxels (marker of tumor infiltration) from 28 non-enhanced gliomas and 365,262 voxels (marker of edema) from the peritumoral edema region of 14 meningiomas on conventional MRI sequences (T1-weighted image, the contrast-enhancing T1-weighted image, the T2-weighted image, the T2-fluid attenuated inversion recovery image, and the apparent diffusion coefficient map). Using the SVM classifier, a model for predicting tumor cell infiltration and vasogenic edema at the voxel level was developed. The accuracy of the model's predictions was then evaluated using 15 GBM patients who underwent stereotactic biopsies. RESULTS The area under the curve (AUC), accuracy, sensitivity, and specificity of the prediction model were 0.93, 0.84, 0.83, and 0.85 in the training set, and 0.90, 0.82, 0.83, and 0.83 in the test set (704,992 voxels), respectively. The pathology verification of 28 biopsy points with an accuracy of 0.79. CONCLUSION At the voxel level, it seems possible to forecast tumor cell infiltration and vasogenic edema in the peritumoral region of GBM based on conventional MRI sequences.
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Affiliation(s)
- Lei He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Hong Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Tianshi Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Jianing Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Yanpeng Zhou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Jiaxiang Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Tuerhong Saidaer
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.)
| | - Xing Liu
- Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (X.L.)
| | - Lei Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.); Beijing Neurosurgical Institute, Capital Medical University, Beijing, China (L.W., Y.W.).
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (L.H., H.Z., T.L., J.Y., Y.Z., J.W., T.S., L.W., Y.W.); Beijing Neurosurgical Institute, Capital Medical University, Beijing, China (L.W., Y.W.)
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7
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Chohan MO, Flores RA, Wertz C, Jung RE. "Non-Eloquent" brain regions predict neuropsychological outcome in tumor patients undergoing awake craniotomy. PLoS One 2024; 19:e0284261. [PMID: 38300915 PMCID: PMC10833519 DOI: 10.1371/journal.pone.0284261] [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: 10/20/2022] [Accepted: 03/28/2023] [Indexed: 02/03/2024] Open
Abstract
Supratotal resection of primary brain tumors is being advocated especially when involving "non-eloquent" tissue. However, there is extensive neuropsychological data implicating functions critical to higher cognition in areas considered "non-eloquent" by most surgeons. The goal of the study was to determine pre-surgical brain regions that would be predictive of cognitive outcome at 4-6 months post-surgery. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer-v6.0 image analysis suite. Linear regression models were used to regress cortical volumes from both hemispheres, against the total cognitive z-score to determine the relationship between brain structure and broad cognitive functioning while controlling for age, sex, and total segmented brain volume. We identified 62 consecutive patients who underwent planned awake resections of primary (n = 55, 88%) and metastatic at the University of New Mexico Hospital between 2015 and 2019. Of those, 42 (23 males, 25 left hemispheric lesions) had complete pre and post-op neuropsychological data available and were included in this study. Overall, total neuropsychological functioning was somewhat worse (p = 0.09) at post-operative neuropsychological outcome (Mean = -.20) than at baseline (Mean = .00). Patients with radiation following resection (n = 32) performed marginally worse (p = .036). We found that several discrete brain volumes obtained pre-surgery predicted neuropsychological outcome post-resection. For the total sample, these volumes included: left fusiform, right lateral orbital frontal, right post central, and right paracentral regions. Regardless of lesion lateralization, volumes within the right frontal lobe, and specifically right orbitofrontal cortex, predicted neuropsychological difference scores. The current study highlights the gaps in our current understanding of brain eloquence. We hypothesize that the volume of tissue within the right lateral orbital frontal lobe represents important cognitive reserve capacity in patients undergoing tumor surgery. Our data also cautions the neurosurgeon when considering supratotal resections of tumors that do not extend into areas considered "non-eloquent" by current standards.
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Affiliation(s)
- Muhammad Omar Chohan
- Department of Neurosurgery, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Ranee Ann Flores
- Department of Neurosurgery, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States of America
| | - Christopher Wertz
- Department of Neurosurgery, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States of America
| | - Rex Eugene Jung
- Department of Neurosurgery, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States of America
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Yoon J, Baek N, Yoo RE, Choi SH, Kim TM, Park CK, Park SH, Won JK, Lee JH, Lee ST, Choi KS, Lee JY, Hwang I, Kang KM, Yun TJ. Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients. Sci Rep 2024; 14:2171. [PMID: 38273075 PMCID: PMC10810891 DOI: 10.1038/s41598-024-52841-7] [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: 08/25/2023] [Accepted: 01/24/2024] [Indexed: 01/27/2024] Open
Abstract
Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the non-enhancing T2 hyperintensity areas using conventional MRI alone. Quantitative DCE MRI parameters such as Ktrans and Ve convey permeability information of glioblastomas that cannot be provided by conventional MRI. We used the publicly available nnU-Net to train a deep learning model that incorporated both conventional and DCE MRI to detect the subtle difference in vessel leakiness due to neoangiogenesis between the non-recurrence area and the local recurrence area, which contains a higher proportion of high-grade glioma cells. We found that the addition of Ve doubled the sensitivity while nonsignificantly decreasing the specificity for prediction of local recurrence in glioblastomas, which implies that the combined model may result in fewer missed cases of local recurrence. The deep learning model predictive of local recurrence may enable risk-adapted radiotherapy planning in patients with grade 4 adult-type diffuse gliomas.
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Affiliation(s)
- Jungbin Yoon
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Nayeon Baek
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
- Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea.
- School of Chemical and Biological Engineering, Seoul National University, 1, Gwanak-ro, Gwanak-gu, Seoul, 302-909, Republic of Korea.
| | - Tae Min Kim
- Department of Internal Medicine, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Biomedical Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sung-Hye Park
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jae-Kyung Won
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Joo Ho Lee
- Department of Radiation Oncology, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soon Tae Lee
- Department of Neurology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Ji Ye Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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9
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Rydelius A, Bengzon J, Engelholm S, Kinhult S, Englund E, Nilsson M, Lätt J, Lampinen B, Sundgren PC. Predictive value of diffusion MRI-based parametric response mapping for prognosis and treatment response in glioblastoma. Magn Reson Imaging 2023; 104:88-96. [PMID: 37734574 DOI: 10.1016/j.mri.2023.09.005] [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: 01/29/2023] [Revised: 09/15/2023] [Accepted: 09/17/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND Early detection of treatment response is important for the management of patients with malignant brain tumors such as glioblastoma to assure good quality of life in relation to therapeutic efficacy. AIM To investigate whether parametric response mapping (PRM) with diffusion MRI may provide prognostic information at an early stage of standard therapy for glioblastoma. MATERIALS AND METHODS This prospective study included 31 patients newly diagnosed with glioblastoma WHO grade IV, planned for primary standard postoperative treatment with radiotherapy 60Gy/30 fractions with concomitant and adjuvant Temozolomide. MRI follow-up including diffusion and perfusion weighting was performed at 3 T at start of postoperative chemoradiotherapy, three weeks into treatment, and then regularly until twelve months postoperatively. Regional mean diffusivity (MD) changes were analyzed voxel-wise using the PRM method (MD-PRM). At eight and twelve months postoperatively, after completion of standard treatment, patients were classified using conventional MRI and clinical evaluation as either having stable disease (SD, including partial response) or progressive disease (PD). It was assessed whether MD-PRM differed between patients having SD versus PD and whether it predicted the risk of disease progression (progression-free survival, PFS) or death (overall survival, OS). A subgroup analysis was performed that compared MD-PRM between SD and PD in patients only undergoing diagnostic biopsy. MGMT-promotor methylation status (O6-methylguanine-DNA methyltransferase) was registered and analyzed with respect to PFS, OS and MD-PRM. RESULTS Of the 31 patients analyzed: 21 were operated by resection and ten by diagnostic biopsy. At eight months, 19 patients had SD and twelve had PD. At twelve months, ten patients had SD and 20 had PD, out of which ten were deceased within twelve months and one was deceased without known tumor progression. Median PFS was nine months, and median OS was 17 months. Eleven patients had methylated MGMT-promotor, 16 were MGMT unmethylated, and four had unknown MGMT-status. MD-PRM did not significantly predict patients having SD versus PD neither at eight nor at twelve months. Patients with an above median MD-PRM reduction had a slightly longer PFS (P = 0.015) in Kaplan-Maier analysis, as well as a non-significantly longer OS (P = 0.099). In the subgroup of patients only undergoing biopsy, total MD-PRM change at three weeks was generally higher for patients with SD than for patients with PD at eight months, although no tests were performed. MGMT status strongly predicted both PFS and OS but not MD-PRM change. CONCLUSION MD-PRM at three weeks was not demonstrated to be predictive of treatment response, disease progression, or survival. Preliminary results suggested a higher predictive value in non-resected patients, although this needs to be evaluated in future studies.
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Affiliation(s)
- A Rydelius
- Department of Clinical Sciences Lund, Division of Neurology, Lund University, Skane University Hospital, Lund, Sweden; Department of Clinical Sciences Lund, Division of Diagnostic Radiology, Lund University, Skane University Hospital, Lund, Sweden.
| | - J Bengzon
- Department of Clinical Sciences Lund, Division of Neurosurgery, Lund University, Skane University Hospital, Lund, Sweden
| | - S Engelholm
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, Skane University Hospital, Lund, Sweden
| | - S Kinhult
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, Skane University Hospital, Lund, Sweden
| | - E Englund
- Department of Clinical Sciences Lund, Division of Pathology, Lund University, Clinical Genetics, Pathology and Molecular Diagnostics, Medical Service, Lund, Skane University Hospital, Lund, Sweden
| | - M Nilsson
- Department of Clinical Sciences Lund, Division of Diagnostic Radiology, Lund University, Skane University Hospital, Lund, Sweden
| | - J Lätt
- Department for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - B Lampinen
- Department of Clinical Sciences Lund, Division of Diagnostic Radiology, Lund University, Skane University Hospital, Lund, Sweden
| | - P C Sundgren
- Department of Clinical Sciences Lund, Division of Diagnostic Radiology, Lund University, Skane University Hospital, Lund, Sweden; Department for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden; Lund University, BioImaging Centre (LBIC), Lund University, Lund, Sweden; Department of Radiology, University of Michigan, Ann Arbor, MI, USA
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10
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Würtemberger U, Erny D, Rau A, Hosp JA, Akgün V, Reisert M, Kiselev VG, Beck J, Jankovic S, Reinacher PC, Hohenhaus M, Urbach H, Diebold M, Demerath T. Mesoscopic Assessment of Microstructure in Glioblastomas and Metastases by Merging Advanced Diffusion Imaging with Immunohistopathology. AJNR Am J Neuroradiol 2023; 44:1262-1269. [PMID: 37884304 PMCID: PMC10631536 DOI: 10.3174/ajnr.a8022] [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: 06/08/2023] [Accepted: 08/30/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND AND PURPOSE Glioblastomas and metastases are the most common malignant intra-axial brain tumors in adults and can be difficult to distinguish on conventional MR imaging due to similar imaging features. We used advanced diffusion techniques and structural histopathology to distinguish these tumor entities on the basis of microstructural axonal and fibrillar signatures in the contrast-enhancing tumor component. MATERIALS AND METHODS Contrast-enhancing tumor components were analyzed in 22 glioblastomas and 21 brain metastases on 3T MR imaging using DTI-fractional anisotropy, neurite orientation dispersion and density imaging-orientation dispersion, and diffusion microstructural imaging-micro-fractional anisotropy. Available histopathologic specimens (10 glioblastomas and 9 metastases) were assessed for the presence of axonal structures and scored using 4-level scales for Bielschowsky staining (0: no axonal structures, 1: minimal axonal fragments preserved, 2: decreased axonal density, 3: no axonal loss) and glial fibrillary acid protein expression (0: no glial fibrillary acid protein positivity, 1: limited expression, 2: equivalent to surrounding parenchyma, 3: increased expression). RESULTS When we compared glioblastomas and metastases, fractional anisotropy was significantly increased and orientation dispersion was decreased in glioblastomas (each P < .001), with a significant shift toward increased glial fibrillary acid protein and Bielschowsky scores. Positive associations of fractional anisotropy and negative associations of orientation dispersion with glial fibrillary acid protein and Bielschowsky scores were revealed, whereas no association between micro-fractional anisotropy with glial fibrillary acid protein and Bielschowsky scores was detected. Receiver operating characteristic curves revealed high predictive values of both fractional anisotropy (area under the curve = 0.8463) and orientation dispersion (area under the curve = 0.8398) regarding the presence of a glioblastoma. CONCLUSIONS Diffusion imaging fractional anisotropy and orientation dispersion metrics correlated with histopathologic markers of directionality and may serve as imaging biomarkers in contrast-enhancing tumor components.
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Affiliation(s)
- Urs Würtemberger
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology (D.E., M.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Berta-Ottenstein-Program for Advanced Clinician Scientists (D.E.), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alexander Rau
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Department of Diagnostic and Interventional Radiology (A.R.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jonas A Hosp
- Department of Neurology and Neurophysiology (J.A.H.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Veysel Akgün
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Marco Reisert
- Department of Medical Physics (M.R., V.G.K.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Department of Stereotactic and Functional Neurosurgery (M.R., P.C.R.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Valerij G Kiselev
- Department of Medical Physics (M.R., V.G.K.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jürgen Beck
- Department of Neurosurgery (J.B., M.H.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Sonja Jankovic
- Department of Radiology (S.J.), Faculty of Medicine, University Clinical Center Nis, University of Nis, Nis, Serbia
| | - Peter C Reinacher
- Department of Stereotactic and Functional Neurosurgery (M.R., P.C.R.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Fraunhofer Institute for Laser Technology (P.C.R.), Aachen, Germany
| | - Marc Hohenhaus
- Department of Neurosurgery (J.B., M.H.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Horst Urbach
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Martin Diebold
- Institute of Neuropathology (D.E., M.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- IMM-PACT Clinician Scientist Program (M.D.), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Theo Demerath
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
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11
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Salvalaggio A, Pini L, Gaiola M, Velco A, Sansone G, Anglani M, Fekonja L, Chioffi F, Picht T, Thiebaut de Schotten M, Zagonel V, Lombardi G, D’Avella D, Corbetta M. White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma. JAMA Neurol 2023; 80:1222-1231. [PMID: 37747720 PMCID: PMC10520843 DOI: 10.1001/jamaneurol.2023.3284] [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: 02/22/2023] [Accepted: 07/07/2023] [Indexed: 09/26/2023]
Abstract
Importance The prognosis of overall survival (OS) in patients with glioblastoma (GBM) may depend on the underlying structural connectivity of the brain. Objective To examine the association between white matter tracts affected by GBM and patients' OS by means of a new tract density index (TDI). Design, Setting, and Participants This prognostic study in patients with a histopathologic diagnosis of GBM examined a discovery cohort of 112 patients who underwent surgery between February 1, 2015, and November 30, 2020 (follow-up to May 31, 2023), in Italy and 70 patients in a replicative cohort (n = 70) who underwent surgery between September 1, 2012, and November 30, 2015 (follow-up to May 31, 2023), in Germany. Statistical analyses were performed from June 1, 2021, to May 31, 2023. Thirteen and 12 patients were excluded from the discovery and the replicative sets, respectively, because of magnetic resonance imaging artifacts. Exposure The density of white matter tracts encompassing GBM. Main Outcomes and Measures Correlation, linear regression, Cox proportional hazards regression, Kaplan-Meier, and prediction analysis were used to assess the association between the TDI and OS. Results were compared with common prognostic factors of GBM, including age, performance status, O6-methylguanine-DNA methyltransferase methylation, and extent of surgery. Results In the discovery cohort (n = 99; mean [SD] age, 62.2 [11.5] years; 29 female [29.3%]; 70 male [70.7%]), the TDI was significantly correlated with OS (r = -0.34; P < .001). This association was more stable compared with other prognostic factors. The TDI showed a significant regression pattern (Cox: hazard ratio, 0.28 [95% CI, 0.02-0.55; P = .04]; linear: t = -2.366; P = .02). and a significant Kaplan-Meier stratification of patients as having lower or higher OS based on the TDI (log-rank test = 4.52; P = .03). Results were confirmed in the replicative cohort (n = 58; mean [SD] age, 58.5 [11.1] years, 14 female [24.1%]; 44 male [75.9%]). High (24-month cutoff) and low (18-month cutoff) OS was predicted based on the TDI computed in the discovery cohort (accuracy = 87%). Conclusions and Relevance In this study, GBMs encompassing regions with low white matter tract density were associated with longer OS. These findings indicate that the TDI is a reliable presurgical outcome predictor that may be considered in clinical trials and clinical practice. These findings support a framework in which the outcome of GBM depends on the patient's brain organization.
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Affiliation(s)
- Alessandro Salvalaggio
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Lorenzo Pini
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Matteo Gaiola
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | - Aron Velco
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | - Giulio Sansone
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | | | - Lucius Fekonja
- Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
- Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany
| | - Franco Chioffi
- Division of Neurosurgery, Azienda Ospedaliera Università di Padova, Padova, Italy
| | - Thomas Picht
- Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
- Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Vittorina Zagonel
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Domenico D’Avella
- Academic Neurosurgery, Department of Neurosciences, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Venetian Institute of Molecular Medicine, Fondazione Biomedica, Padova, Italy
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12
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Zhu A, Shih R, Huang RY, DeMarco JK, Bhushan C, Morris HD, Kohls G, Yeo DTB, Marinelli L, Mitra J, Hood M, Ho VB, Foo TKF. Revealing tumor microstructure with oscillating diffusion encoding MRI in pre-surgical and post-treatment glioma patients. Magn Reson Med 2023; 90:1789-1801. [PMID: 37335831 DOI: 10.1002/mrm.29758] [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: 03/06/2023] [Revised: 05/09/2023] [Accepted: 05/24/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE We hypothesized that the time-dependent diffusivity at short diffusion times, as measured by oscillating gradient spin echo (OGSE) diffusion MRI, can characterize tissue microstructures in glioma patients. THEORY AND METHODS Five adult patients with known diffuse glioma, including two pre-surgical and three with new enhancing lesions after treatment for high-grade glioma, were scanned in an ultra-high-performance gradient 3.0T MRI system. OGSE diffusion MRI at 30-100 Hz and pulsed gradient spin echo diffusion imaging (approximated as 0 Hz) were obtained. The ADC and trace-diffusion-weighted image at each acquired frequency were calculated, that is, ADC (f) and TraceDWI (f). RESULTS In pre-surgical patients, biopsy-confirmed solid enhancing tumor in a high-grade glioblastoma showed higherADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lowerTraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\ (f)}{\mathrm{TraceDWI}\ \left(0\ \mathrm{Hz}\right)} $$ , compared to that at same OGSE frequency in a low-grade astrocytoma. In post-treatment patients, the enhancing lesions of two patients who were diagnosed with tumor progression contained more voxels with highADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lowTraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\left(\mathrm{f}\right)}{\mathrm{TraceDWI}\left(0\ \mathrm{Hz}\right)} $$ , compared to the enhancing lesions of a patient who was diagnosed with treatment effect. Non-enhancing T2 signal abnormality lesions in both the pre-surgical high-grade glioblastoma and post-treatment tumor progressions showed regions with highADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lowTraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\ \left(\mathrm{f}\right)}{\mathrm{TraceDWI}\ \left(0\ \mathrm{Hz}\right)} $$ , consistent with infiltrative tumor. The solid tumor of the glioblastoma, the enhancing lesions of post-treatment tumor progressions, and the suspected infiltrative tumors showed high diffusion time-dependency from 30 to 100 Hz, consistent with high intra-tumoral volume fraction (cellular density). CONCLUSION Different characteristics of OGSE-based time-dependent diffusivity can reveal heterogenous tissue microstructures that indicate cellular density in glioma patients.
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Affiliation(s)
- Ante Zhu
- GE Research, Niskayuna, New York, USA
| | - Robert Shih
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - J Kevin DeMarco
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | | | - H Douglas Morris
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Gail Kohls
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | | | | | | | - Maureen Hood
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Vincent B Ho
- Uniformed Services University, Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Thomas K F Foo
- GE Research, Niskayuna, New York, USA
- Uniformed Services University, Bethesda, Maryland, USA
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13
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Shin H, Park JE, Jun Y, Eo T, Lee J, Kim JE, Lee DH, Moon HH, Park SI, Kim S, Hwang D, Kim HS. Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI. Eur Radiol 2023; 33:5859-5870. [PMID: 37150781 DOI: 10.1007/s00330-023-09710-0] [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: 09/07/2022] [Revised: 01/31/2023] [Accepted: 03/06/2023] [Indexed: 05/09/2023]
Abstract
OBJECTIVES An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to apply an interpretable deep learning (DL) system to multiparametric MRI to obtain clinical referral suggestion for IMLLs, and to validate it in the setting of nontraumatic emergency neuroradiology. METHODS A DL system was developed in 747 patients with IMLLs ranging 30 diseases who underwent pre- and post-contrast T1-weighted (T1CE), FLAIR, and diffusion-weighted imaging (DWI). A DL system that segments IMLLs, classifies tumourous conditions, and suggests clinical referral among surgery, systematic work-up, medical treatment, and conservative treatment, was developed. The system was validated in an independent cohort of 130 emergency patients, and performance in referral suggestion and tumour discrimination was compared with that of radiologists using receiver operating characteristics curve, precision-recall curve analysis, and confusion matrices. Multiparametric interpretable visualisation of high-relevance regions from layer-wise relevance propagation overlaid on contrast-enhanced T1WI and DWI was analysed. RESULTS The DL system provided correct referral suggestions in 94 of 130 patients (72.3%) and performed comparably to radiologists (accuracy 72.6%, McNemar test; p = .942). For distinguishing tumours from non-tumourous conditions, the DL system (AUC, 0.90 and AUPRC, 0.94) performed similarly to human readers (AUC, 0.81~0.92, and AUPRC, 0.88~0.95). Solid portions of tumours showed a high overlap of relevance, but non-tumours did not (Dice coefficient 0.77 vs. 0.33, p < .001), demonstrating the DL's decision. CONCLUSIONS Our DL system could appropriately triage patients using multiparametric MRI and provide interpretability through multiparametric heatmaps, and may thereby aid neuroradiologic diagnoses in emergency settings. CLINICAL RELEVANCE STATEMENT Our AI triages patients with raw MRI images to clinical referral pathways in brain intra-axial mass-like lesions. We demonstrate that the decision is based on the relative relevance between contrast-enhanced T1-weighted and diffusion-weighted images, providing explainability across multiparametric MRI data. KEY POINTS • A deep learning (DL) system using multiparametric MRI suggested clinical referral to patients with intra-axial mass-like lesions (IMLLs) similar to radiologists (accuracy 72.3% vs. 72.6%). • In the differentiation of tumourous and non-tumourous conditions, the DL system (AUC, 0.90) performed similar with radiologists (AUC, 0.81-0.92). • The DL's decision basis for differentiating tumours from non-tumours can be quantified using multiparametric heatmaps obtained via the layer-wise relevance propagation method.
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Affiliation(s)
- Hyungseob Shin
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Yohan Jun
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Taejoon Eo
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
| | - Jeongryong Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
| | - Ji Eun Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Da Hyun Lee
- Department of Radiology, Ajou University School of Medicine, Gyeonggi-Do, Korea
| | - Hye Hyeon Moon
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sang Ik Park
- Department of Radiology, Chung-Ang University Hospital, Seoul, Korea
| | - Seonok Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Dosik Hwang
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
- Center for Healthcare Robotics, Korea Institute of Science and Technology, 5, Hwarang-Ro 14-Gil, Seongbuk-Gu, Seoul, 02792, Korea.
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Korea.
- Department of Radiology and Center for Clinical Imaging Data Science (CCIDS), Yonsei University College of Medicine, Seoul, Korea.
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
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14
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Yang J, Zhang X, Gao X, Wu H, Li X, Yang L, Zhang N. Fiber Density and Structural Brain Connectome in Glioblastoma Are Correlated With Glioma Cell Infiltration. Neurosurgery 2023; 92:1234-1242. [PMID: 36744904 DOI: 10.1227/neu.0000000000002356] [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: 08/25/2022] [Accepted: 11/08/2022] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Glioblastoma (GBM) preferred to infiltrate into white matter (WM) beyond the recognizable tumor margin. OBJECTIVE To investigate whether fiber density (FD) and structural brain connectome can provide meaningful information about WM destruction and glioma cell infiltration. METHODS GBM cases were collected based on inclusion criteria, and baseline information and preoperative MRI results were obtained. GBM lesions were automatically segmented into necrosis, contrast-enhanced tumor, and edema areas. We obtained the FD map to compute the FD and lnFD values in each subarea and reconstructed the structural brain connectome to obtain the topological metrics in each subarea. We also divided the edema area into a nonenhanced tumor (NET) area and a normal WM area based on the contralesional lnFD value in the edema area, and computed the NET ratio. RESULTS Twenty-five GBM cases were included in this retrospective study. The FD/lnFD value and topological metrics (aCp, aLp, aEg, aEloc, and ar) were significantly correlated with GBM subareas, which represented the extent of WM destruction and glioma cell infiltration. The FD/lnFD values and topological parameters were correlated with the NET ratio. In particular, the lnFD value in the edema area was correlated with the NET ratio (coefficient, 0.92). Therefore, a larger lnFD value indicates more severe glioma infiltration in the edema area and suggests an extended resection for better clinical outcomes. CONCLUSION The FD and structural brain connectome in this study provide a new insight into glioma infiltration and a different consideration of their clinical application in neuro-oncology.
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Affiliation(s)
- Jia Yang
- Department of Neurosurgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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15
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Guberina N, Padeberg F, Pöttgen C, Guberina M, Lazaridis L, Jabbarli R, Deuschl C, Herrmann K, Blau T, Wrede KH, Keyvani K, Scheffler B, Hense J, Layer JP, Glas M, Sure U, Stuschke M. Location of Recurrences after Trimodality Treatment for Glioblastoma with Respect to the Delivered Radiation Dose Distribution and Its Influence on Prognosis. Cancers (Basel) 2023; 15:cancers15112982. [PMID: 37296942 DOI: 10.3390/cancers15112982] [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: 03/24/2023] [Revised: 05/22/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND While prognosis of glioblastoma after trimodality treatment is well examined, recurrence pattern with respect to the delivered dose distribution is less well described. Therefore, here we examine the gain of additional margins around the resection cavity and gross-residual-tumor. METHODS All recurrent glioblastomas initially treated with radiochemotherapy after neurosurgery were included. The percentage overlap of the recurrence with the gross tumor volume (GTV) expanded by varying margins (10 mm to 20 mm) and with the 95% and 90% isodose was measured. Competing-risks analysis was performed in dependence on recurrence pattern. RESULTS Expanding the margins from 10 mm to 15 mm, to 20 mm, to the 95%- and 90% isodose of the delivered dose distribution with a median margin of 27 mm did moderately increase the proportion of relative in-field recurrence volume from 64% to 68%, 70%, 88% and 88% (p < 0.0001). Overall survival of patients with in-and out-field recurrence was similar (p = 0.7053). The only prognostic factor significantly associated with out-field recurrence was multifocality of recurrence (p = 0.0037). Cumulative incidences of in-field recurrences at 24 months were 60%, 22% and 11% for recurrences located within a 10 mm margin, outside a 10 mm margin but within the 95% isodose, or outside the 95% isodose (p < 0.0001). Survival from recurrence was improved after complete resection (p = 0.0069). Integrating these data into a concurrent-risk model shows that extending margins beyond 10 mm has only small effects on survival hardly detectable by clinical trials. CONCLUSIONS Two-thirds of recurrences were observed within a 10 mm margin around the GTV. Smaller margins reduce normal brain radiation exposure allowing for more extensive salvage radiation therapy options in case of recurrence. Prospective trials using margins smaller than 20 mm around the GTV are warranted.
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Affiliation(s)
- Nika Guberina
- Department of Radiation Therapy, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Florian Padeberg
- Department of Radiation Therapy, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Christoph Pöttgen
- Department of Radiation Therapy, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Maja Guberina
- Department of Radiation Therapy, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Lazaros Lazaridis
- Department of Neurology, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Ramazan Jabbarli
- Department of Neurosurgery and Spine Surgery, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Cornelius Deuschl
- Institute of Diagnostic and Interventional Radiology and Neuroradiology, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Ken Herrmann
- Department of Nuclear Medicine, University Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Tobias Blau
- Institute of Neuropathology, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Karsten H Wrede
- Department of Neurosurgery and Spine Surgery, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Kathy Keyvani
- Institute of Neuropathology, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Björn Scheffler
- German Cancer Consortium (DKTK), Partner Site University Hospital Essen, 45147 Essen, Germany
- DKFZ-Division Translational Neurooncology at the West German Cancer Center (WTZ), DKTK Partner Site, University Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Jörg Hense
- Department of Medical Oncology, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Julian P Layer
- Department of Radiation Oncology, University of Bonn, University Hospital Bonn, 53127 Bonn, Germany
- Institute of Experimental Oncology, University of Bonn, University Hospital Bonn, 53127 Bonn, Germany
| | - Martin Glas
- Department of Neurology, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Ulrich Sure
- Department of Neurosurgery and Spine Surgery, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
| | - Martin Stuschke
- Department of Radiation Therapy, West German Cancer Center, University of Duisburg-Essen, University Hospital Essen, 45147 Essen, Germany
- German Cancer Consortium (DKTK), Partner Site University Hospital Essen, 45147 Essen, Germany
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16
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López-Goerne T, Padilla-Godínez FJ. Catalytic Nanomedicine as a Therapeutic Approach to Brain Tumors: Main Hypotheses for Mechanisms of Action. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:nano13091541. [PMID: 37177086 PMCID: PMC10180296 DOI: 10.3390/nano13091541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 04/19/2023] [Accepted: 04/25/2023] [Indexed: 05/15/2023]
Abstract
Glioblastoma multiforme (GBM) is the most aggressive primary malignant tumor of the brain. Although there are currently a wide variety of therapeutic approaches focused on tumor elimination, such as radiotherapy, chemotherapy, and tumor field therapy, among others, the main approach involves surgery to remove the GBM. However, since tumor growth occurs in normal brain tissue, complete removal is impossible, and patients end up requiring additional treatments after surgery. In this line, Catalytic Nanomedicine has achieved important advances in developing bionanocatalysts, brain-tissue-biocompatible catalytic nanostructures capable of destabilizing the genetic material of malignant cells, causing their apoptosis. Previous work has demonstrated the efficacy of bionanocatalysts and their selectivity for cancer cells without affecting surrounding healthy tissue cells. The present review provides a detailed description of these nanoparticles and their potential mechanisms of action as antineoplastic agents, covering the most recent research and hypotheses from their incorporation into the tumor bed, internalization via endocytosis, specific chemotaxis by mitochondrial and nuclear genetic material, and activation of programmed cell death. In addition, a case report of a patient with GBM treated with the bionanocatalysts following tumor removal surgery is described. Finally, the gaps in knowledge that must be bridged before the clinical translation of these compounds with such a promising future are detailed.
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Affiliation(s)
- Tessy López-Goerne
- Nanotechnology and Nanomedicine Laboratory, Department of Health Care, Metropolitan Autonomous University-Xochimilco, Mexico City 04960, Mexico
| | - Francisco J Padilla-Godínez
- Nanotechnology and Nanomedicine Laboratory, Department of Health Care, Metropolitan Autonomous University-Xochimilco, Mexico City 04960, Mexico
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17
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Polonara G, Aiudi D, Iacoangeli A, Raggi A, Ottaviani MM, Antonini R, Iacoangeli M, Dobran M. Glioblastoma: A Retrospective Analysis of the Role of the Maximal Surgical Resection on Overall Survival and Progression Free Survival. Biomedicines 2023; 11:biomedicines11030739. [PMID: 36979717 PMCID: PMC10045159 DOI: 10.3390/biomedicines11030739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 01/26/2023] [Accepted: 01/27/2023] [Indexed: 03/05/2023] Open
Abstract
Background: Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults; despite advances in the understanding of GBM pathogenesis, significant achievements in treating this disease are still lacking. The aim of this study was to evaluate the prognostic significance of the extent of surgical resection (EOR), beyond the neoplastic mass, on the overall survival (OS). Methods: A retrospective review of a single-institution glioblastoma patient database (January 2012–September 2021) was undertaken. The series is composed of 64 patients who underwent surgery at the University Department of Neurosurgery of Ancona; the series was divided into four groups based on the amount of tumor mass excision with the fluid-attenuated inversion recovery (FLAIR) abnormalities (SUPr-supratotal resection, GTR-gross total resection, STR-subtotal resection, BIOPSY). The hypothesis was that the maximal resection of FLAIR abnormalities may improve the overall survival compared to the resection of the visible T1 contrast-enhanced neoplastic area only. Results: In the univariate analysis, SUPr and GTR are correlated with the overall survival (p = 0.001); the percentage of total neoplastic removal threshold conditioning outcome was 90% (p = 0.027). These results were confirmed by the multivariate analysis. Conclusions: Maximal surgical resection, when feasible, involving areas of FLAIR abnormalities represents an advantageous approach for the OS in GBM patients.
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Affiliation(s)
- Gabriele Polonara
- Department of Neuroradiology, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
| | - Denis Aiudi
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
- Correspondence: (D.A.); (M.D.)
| | - Alessio Iacoangeli
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
| | - Alessio Raggi
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
| | - Matteo Maria Ottaviani
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
| | - Ruggero Antonini
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
| | - Maurizio Iacoangeli
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
| | - Mauro Dobran
- Department of Neurosurgery, Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
- Correspondence: (D.A.); (M.D.)
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18
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Willman M, Willman J, Figg J, Dioso E, Sriram S, Olowofela B, Chacko K, Hernandez J, Lucke-Wold B. Update for astrocytomas: medical and surgical management considerations. EXPLORATION OF NEUROSCIENCE 2023; 2:1-26. [PMID: 36935776 PMCID: PMC10019464 DOI: 10.37349/en.2023.00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 12/10/2022] [Indexed: 02/25/2023]
Abstract
Astrocytomas include a wide range of tumors with unique mutations and varying grades of malignancy. These tumors all originate from the astrocyte, a star-shaped glial cell that plays a major role in supporting functions of the central nervous system (CNS), including blood-brain barrier (BBB) development and maintenance, water and ion regulation, influencing neuronal synaptogenesis, and stimulating the immunological response. In terms of epidemiology, glioblastoma (GB), the most common and malignant astrocytoma, generally occur with higher rates in Australia, Western Europe, and Canada, with the lowest rates in Southeast Asia. Additionally, significantly higher rates of GB are observed in males and non-Hispanic whites. It has been suggested that higher levels of testosterone observed in biological males may account for the increased rates of GB. Hereditary syndromes such as Cowden, Lynch, Turcot, Li-Fraumeni, and neurofibromatosis type 1 have been linked to increased rates of astrocytoma development. While there are a number of specific gene mutations that may influence malignancy or be targeted in astrocytoma treatment, O 6-methylguanine-DNA methyltransferase (MGMT) gene function is an important predictor of astrocytoma response to chemotherapeutic agent temozolomide (TMZ). TMZ for primary and bevacizumab in the setting of recurrent tumor formation are two of the main chemotherapeutic agents currently approved in the treatment of astrocytomas. While stereotactic radiosurgery (SRS) has debatable implications for increased survival in comparison to whole-brain radiotherapy (WBRT), SRS demonstrates increased precision with reduced radiation toxicity. When considering surgical resection of astrocytoma, the extent of resection (EoR) is taken into consideration. Subtotal resection (STR) spares the margins of the T1 enhanced magnetic resonance imaging (MRI) region, gross total resection (GTR) includes the margins, and supramaximal resection (SMR) extends beyond the margin of the T1 and into the T2 region. Surgical resection, radiation, and chemotherapy are integral components of astrocytoma treatment.
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Affiliation(s)
- Matthew Willman
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Jonathan Willman
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - John Figg
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Emma Dioso
- School of Medicine, University of Utah, Salt Lake City, UT 84132, USA
| | - Sai Sriram
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Bankole Olowofela
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Kevin Chacko
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Jairo Hernandez
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Brandon Lucke-Wold
- Department of Neurosurgery, University of Florida, Gainesville, FL 32608, USA
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19
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Giussani C, Carrabba G, Rui CB, Chiarello G, Stefanoni G, Julita C, De Vito A, Cinalli MA, Basso G, Remida P, Citerio G, Di Cristofori A. Perilesional resection technique of glioblastoma: intraoperative ultrasound and histological findings of the resection borders in a single center experience. J Neurooncol 2023; 161:625-632. [PMID: 36690859 PMCID: PMC9992251 DOI: 10.1007/s11060-022-04232-z] [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: 07/07/2022] [Accepted: 12/29/2022] [Indexed: 01/25/2023]
Abstract
INTRODUCTION The surgical goal in glioblastoma treatment is the maximal safe resection of the tumor. Currently the lack of consensus on surgical technique opens different approaches. This study describes the "perilesional technique" and its outcomes in terms of the extent of resection, progression free survival and overall survival. METHODS Patients included (n = 40) received a diagnosis of glioblastoma and underwent surgery using the perilesional dissection technique at "San Gerardo Hospital"between 2018 and 2021. The tumor core was progressively isolated using a circumferential movement, healthy brain margins were protected with Cottonoid patties in a "shingles on the roof" fashion, then the tumorwas removed en bloc. Intraoperative ultrasound (iOUS) was used and at least 1 bioptic sample of "healthy" margin of the resection was collected and analyzed. The extent of resection was quantified. Extent of surgical resection (EOR) and progression free survival (PFS)were safety endpoints of the procedure. RESULTS Thirty-four patients (85%) received a gross total resection(GTR) while 3 (7.5%) patients received a sub-total resection (STR), and 3 (7.5%) a partial resection (PR). The mean post-operative residual volume was 1.44 cm3 (range 0-15.9 cm3).During surgery, a total of 76 margins were collected: 51 (67.1%) were tumor free, 25 (32.9%) were infiltrated. The median PFS was 13.4 months, 15.3 in the GTR group and 9.6 months in the STR-PR group. CONCLUSIONS Perilesional resection is an efficient technique which aims to bring the surgeon to a safe environment, carefully reaching the "healthy" brain before removing the tumoren bloc. This technique can achieve excellent tumor margins, extent of resection, and preservation of apatient's functions.
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Affiliation(s)
- Carlo Giussani
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy. .,Neurosurgery, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy.
| | - Giorgio Carrabba
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.,Neurosurgery, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Chiara Benedetta Rui
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.,Neurosurgery, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Gaia Chiarello
- Neuropathology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, MB, 20900, Monza, Italy
| | - Giovanni Stefanoni
- Neurology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Chiara Julita
- Radiotherapy, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Andrea De Vito
- Neuroradiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Maria Allegra Cinalli
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.,Neurosurgery, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Gianpaolo Basso
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.,Neuroradiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Paolo Remida
- Neuroradiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
| | - Giuseppe Citerio
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.,Neurointensive Care Unit, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy
| | - Andrea Di Cristofori
- Department of Medicine and Surgery, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.,Neurosurgery, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900, Monza, MB, Italy
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20
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Sinha R, Masina R, Morales C, Burton K, Wan Y, Joannides A, Mair RJ, Morris RC, Santarius T, Manly T, Price SJ. A Prospective Study of Longitudinal Risks of Cognitive Deficit for People Undergoing Glioblastoma Surgery Using a Tablet Computer Cognition Testing Battery: Towards Personalized Understanding of Risks to Cognitive Function. J Pers Med 2023; 13:jpm13020278. [PMID: 36836511 PMCID: PMC9967594 DOI: 10.3390/jpm13020278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 01/26/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023] Open
Abstract
Glioblastoma and the surgery to remove it pose high risks to the cognitive function of patients. Little reliable data exist about these risks, especially postoperatively before radiotherapy. We hypothesized that cognitive deficit risks detected before surgery will be exacerbated by surgery in patients with glioblastoma undergoing maximal treatment regimens. We used longitudinal electronic cognitive testing perioperatively to perform a prospective, longitudinal, observational study of 49 participants with glioblastoma undergoing surgery. Before surgery (A1), the participant risk of deficit in 5/6 cognitive domains was increased compared to normative data. Of these, the risks to Attention (OR = 31.19), Memory (OR = 97.38), and Perception (OR = 213.75) were markedly increased. These risks significantly increased in the early period after surgery (A2) when patients were discharged home or seen in the clinic to discuss histology results. For participants tested at 4-6 weeks after surgery (A3) before starting radiotherapy, there was evidence of risk reduction towards A1. The observed risks of cognitive deficit were independent of patient-specific, tumour-specific, and surgery-specific co-variates. These results reveal a timeframe of natural recovery in the first 4-6 weeks after surgery based on personalized deficit profiles for each participant. Future research in this period could investigate personalized rehabilitation tools to aid the recovery process found.
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Affiliation(s)
- Rohitashwa Sinha
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
- Leeds Institute of Medical Research, University of Leeds, Leeds LS9 7TF, UK
- Correspondence:
| | - Riccardo Masina
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Cristina Morales
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Katherine Burton
- Department of Oncology, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Yizhou Wan
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Alexis Joannides
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Richard J. Mair
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Robert C. Morris
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Thomas Santarius
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
| | - Tom Manly
- MRC Cognition and Brain Sciences Unit, Cambridge CB2 7EF, UK
| | - Stephen J. Price
- Department of Neurosurgery, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
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21
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Würtemberger U, Rau A, Reisert M, Kellner E, Diebold M, Erny D, Reinacher PC, Hosp JA, Hohenhaus M, Urbach H, Demerath T. Differentiation of Perilesional Edema in Glioblastomas and Brain Metastases: Comparison of Diffusion Tensor Imaging, Neurite Orientation Dispersion and Density Imaging and Diffusion Microstructure Imaging. Cancers (Basel) 2022; 15:cancers15010129. [PMID: 36612127 PMCID: PMC9817519 DOI: 10.3390/cancers15010129] [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: 10/28/2022] [Revised: 12/12/2022] [Accepted: 12/24/2022] [Indexed: 12/28/2022] Open
Abstract
Although the free water content within the perilesional T2 hyperintense region should differ between glioblastomas (GBM) and brain metastases based on histological differences, the application of classical MR diffusion models has led to inconsistent results regarding the differentiation between these two entities. Whereas diffusion tensor imaging (DTI) considers the voxel as a single compartment, multicompartment approaches such as neurite orientation dispersion and density imaging (NODDI) or the recently introduced diffusion microstructure imaging (DMI) allow for the calculation of the relative proportions of intra- and extra-axonal and also free water compartments in brain tissue. We investigate the potential of water-sensitive DTI, NODDI and DMI metrics to detect differences in free water content of the perilesional T2 hyperintense area between histopathologically confirmed GBM and brain metastases. Respective diffusion metrics most susceptible to alterations in the free water content (MD, V-ISO, V-CSF) were extracted from T2 hyperintense perilesional areas, normalized and compared in 24 patients with GBM and 25 with brain metastases. DTI MD was significantly increased in metastases (p = 0.006) compared to GBM, which was corroborated by an increased DMI V-CSF (p = 0.001), while the NODDI-derived ISO-VF showed only trend level increase in metastases not reaching significance (p = 0.060). In conclusion, diffusion MRI metrics are able to detect subtle differences in the free water content of perilesional T2 hyperintense areas in GBM and metastases, whereas DMI seems to be superior to DTI and NODDI.
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Affiliation(s)
- Urs Würtemberger
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- Correspondence:
| | - Alexander Rau
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- Department of Diagnostic and Interventional Radiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Elias Kellner
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Martin Diebold
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- IMM-PACT Clinician Scientist Program, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- Berta-Ottenstein-Program for Advanced Clinician Scientists, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Peter C. Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- Fraunhofer Institute for Laser Technology, 52074 Aachen, Germany
| | - Jonas A. Hosp
- Department of Neurology and Neurophysiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Marc Hohenhaus
- Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Horst Urbach
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Theo Demerath
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
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A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon's Perspective. Cancers (Basel) 2022; 15:cancers15010090. [PMID: 36612085 PMCID: PMC9817716 DOI: 10.3390/cancers15010090] [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: 09/30/2022] [Revised: 12/04/2022] [Accepted: 12/13/2022] [Indexed: 12/29/2022] Open
Abstract
Amino acid PET imaging has been used for a few years in the clinical and surgical management of gliomas with satisfactory results in diagnosis and grading for surgical and radiotherapy planning and to differentiate recurrences. Biological tumor volume (BTV) provides more meaningful information than standard MR imaging alone and often exceeds the boundary of the contrast-enhanced nodule seen in MRI. Since a gross total resection reflects the resection of the contrast-enhanced nodule and the majority of recurrences are at a tumor's margins, an integration of PET imaging during resection could increase PFS and OS. A systematic review of the literature searching for "PET" [All fields] AND "glioma" [All fields] AND "resection" [All fields] was performed in order to investigate the diffusion of integration of PET imaging in surgical practice. Integration in a neuronavigation system and intraoperative use of PET imaging in the primary diagnosis of adult high-grade gliomas were among the criteria for article selection. Only one study has satisfied the inclusion criteria, and a few more (13) have declared to use multimodal imaging techniques with the integration of PET imaging to intentionally perform a biopsy of the PET uptake area. Despite few pieces of evidence, targeting a biologically active area in addition to other tools, which can help intraoperatively the neurosurgeon to increase the amount of resected tumor, has the potential to provide incremental and complementary information in the management of brain gliomas. Since supramaximal resection based on the extent of MRI FLAIR hyperintensity resulted in an advantage in terms of PFS and OS, PET-based biological tumor volume, avoiding new neurological deficits, deserves further investigation.
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A Head-to-Head Comparison of 18F-Fluorocholine PET/CT and Conventional MRI as Predictors of Outcome in IDH Wild-Type High-Grade Gliomas. J Clin Med 2022; 11:jcm11206065. [PMID: 36294385 PMCID: PMC9605635 DOI: 10.3390/jcm11206065] [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: 08/22/2022] [Revised: 10/01/2022] [Accepted: 10/06/2022] [Indexed: 01/24/2023] Open
Abstract
(1) Aim: To study the associations between imaging parameters derived from contrast-enhanced MRI (CE-MRI) and 18F-fluorocholine PET/CT and their performance as prognostic predictors in isocitrate dehydrogenase wild-type (IDH-wt) high-grade gliomas. (2) Methods: A prospective, multicenter study (FuMeGA: Functional and Metabolic Glioma Analysis) including patients with baseline CE-MRI and 18F-fluorocholine PET/CT and IDH wild-type high-grade gliomas. Clinical variables such as performance status, extent of surgery and adjuvant treatments (Stupp protocol vs others) were obtained and used to discriminate overall survival (OS) and progression-free survival (PFS) as end points. Multilesionality was assessed on the visual analysis of PET/CT and CE-MRI images. After tumor segmentation, standardized uptake value (SUV)-based variables for PET/CT and volume-based and geometrical variables for PET/CT and CE-MRI were calculated. The relationships among imaging techniques variables and their association with prognosis were evaluated using Pearson’s chi-square test and the t-test. Receiver operator characteristic, Kaplan−Meier and Cox regression were used for the survival analysis. (3) Results: 54 patients were assessed. The median PFS and OS were 5 and 11 months, respectively. Significant strong relationships between volume-dependent variables obtained from PET/CT and CE-MRI were found (r > 0.750, p < 0.05). For OS, significant associations were found with SUVmax, SUVpeak, SUVmean and sphericity (HR: 1.17, p = 0.035; HR: 1.24, p = 0.042; HR: 1.62, p = 0.040 and HR: 0.8, p = 0.022, respectively). Among clinical variables, only Stupp protocol and age showed significant associations with OS and PFS. No CE-MRI derived variables showed significant association with prognosis. In multivariate analysis, age (HR: 1.04, p = 0.002), Stupp protocol (HR: 2.81, p = 0.001), multilesionality (HR: 2.20, p = 0.013) and sphericity (HR: 0.79, p = 0.027) derived from PET/CT showed independent associations with OS. For PFS, only age (HR: 1.03, p = 0.021) and treatment protocol (HR: 2.20, p = 0.008) were significant predictors. (4) Conclusions: 18F-fluorocholine PET/CT metabolic and radiomic variables were robust prognostic predictors in patients with IDH-wt high-grade gliomas, outperforming CE-MRI derived variables.
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Using quantitative MRI to study the association of isocitrate dehydrogenase (IDH) status with oxygen metabolism and cellular structure changes in glioma. Eur J Radiol 2022; 155:110502. [PMID: 36049408 DOI: 10.1016/j.ejrad.2022.110502] [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: 06/14/2022] [Revised: 08/14/2022] [Accepted: 08/23/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To investigate the characteristics of oxygen metabolism and the cellular structure of glioma using quantitative MRI to predict the isocitrate dehydrogenase 1 (IDH1) status and to further understand the biological characteristics of gliomas. METHODS In this retrospective study, 94 patients with gliomas eventually received quantitative MRI measures to study oxygen metabolism. The oxygen metabolism biomarker maps (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO2]) and the tissue-cellular-specific (R2t*) MRI relaxation parameter were evaluated in different regions of glioma. RESULTS MRI results showed differences in oxygen metabolism measures in all patients with gliomas of different IDH1 statuses. Compared to patients with IDH1 mutant gliomas, patients with IDH1 wild type gliomas showed increased (P < 0.01) CMRO2, OEF, cerebral blood volume [CBF], and R2t* measures in tumor regions, while only OEF, CBF and R2t* were found to be increased (P < 0.05) in the peritumoral area. OEF achieved the best performance for distinguishing IDH1 wild type and mutant gliomas in the tumor area (AUC = 0.732, P < 0.001). R2t* values correlated with Ki-67(R = 0.35, P < 0.001) in the tumor area, while no significant correlations between Ki-67 and R2t* were found in the peritumoral area (R = 0.19, P = 0.072). CONCLUSION Quantitative MRI has potential applications in studying the tumor and peritumoral areas of glioma, and it has the ability to predict and reveal the characteristics of oxygen metabolism and cellular structure in different regions of gliomas.
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25
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Blee JA, Liu X, Harland AJ, Fatania K, Currie S, Kurian KM, Hauert S. Liquid biopsies for early diagnosis of brain tumours: in silico mathematical biomarker modelling. J R Soc Interface 2022; 19:20220180. [PMID: 35919979 PMCID: PMC9346349 DOI: 10.1098/rsif.2022.0180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/07/2022] [Indexed: 11/12/2022] Open
Abstract
Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml-1 may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.
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Affiliation(s)
- Johanna A. Blee
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, Bristol BS8 1TW, UK
| | - Xia Liu
- Brain Tumour Research Centre, Bristol Medical School, Bristol BS2 8DZ, UK
| | - Abigail J. Harland
- Brain Tumour Research Centre, Bristol Medical School, Bristol BS2 8DZ, UK
| | - Kavi Fatania
- Department of Radiology, Leeds General Infirmary, Great George Street, Leeds LS1 3EX, UK
| | - Stuart Currie
- Department of Radiology, Leeds General Infirmary, Great George Street, Leeds LS1 3EX, UK
| | | | - Sabine Hauert
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, Bristol BS8 1TW, UK
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26
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The new era of bio-molecular imaging with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) in neurosurgery of gliomas. Clin Transl Imaging 2022. [DOI: 10.1007/s40336-022-00509-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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27
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Drai M, Testud B, Brun G, Hak JF, Scavarda D, Girard N, Stellmann JP. Borrowing strength from adults: Transferability of AI algorithms for paediatric brain and tumour segmentation. Eur J Radiol 2022; 151:110291. [DOI: 10.1016/j.ejrad.2022.110291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 03/28/2022] [Accepted: 03/31/2022] [Indexed: 11/03/2022]
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Zhang N, Zhang H, Gao B, Miao Y, Liu A, Song Q, Lin L, Wang J. 3D Amide Proton Transfer Weighted Brain Tumor Imaging With Compressed SENSE: Effects of Different Acceleration Factors. Front Neurosci 2022; 16:876587. [PMID: 35692419 PMCID: PMC9178274 DOI: 10.3389/fnins.2022.876587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/13/2022] [Indexed: 12/05/2022] Open
Abstract
Objectives The aim of the current study was to evaluate the performance of compressed SENSE (CS) for 3D amide proton transfer weighted (APTw) brain tumor imaging with different acceleration factors (AFs), and the results were compared with those of conventional SENSE. Methods Approximately 51 patients with brain tumor (22 males, 49.95 ± 10.52 years) with meningiomas (n = 16), metastases (n = 12), or gliomas (n = 23) were enrolled. All the patients received 3D APTw imaging scans on a 3.0 T scanner with acceleration by CS (AFs: CS2, CS3, CS4, and CS5) and SENSE (AF: S1.6). Two readers independently and subjectively evaluated the APTw images relative to image quality and measured confidence concerning image blur, distortion, motion, and ghosting artifacts, lesion recognition, and contour delineation with a 5-point Likert scale. Mean amide proton transfer (APT) values of brain tumors (APTtumor), the contralateral normal-appearing white matter (APTCNAWM), and the peritumoral edema area (if present, APTedema) and the tumor volume (VAPT) were measured for objective evaluation and determination of the optimal AF. The Ki67 labeling index was also measured by using standard immunohistochemical staining procedures in samples from patients with gliomas, and the correlation between tumor APT values and the Ki67 index was analyzed. Results The image quality of AF = CS5 was significantly lower than that of other groups. VAPT showed significant differences among the six sequences in meningiomas (p = 0.048) and gliomas (p = 0.023). The pairwise comparison showed that the VAPT values of meningiomas measured from images by CS5 were significantly lower, and gliomas were significantly larger than those by SENSE1.6 and other CS accelerations, (p < 0.05). APTtumor (p = 0.191) showed no significant difference among the three types of tumors. The APTtumor values of gliomas measured by APTw images with the SENSE factor of 1.6 and the CS factor of 2, 3, and 4 (except for CS5) were all positively correlated with Ki67. Conclusion Compressed SENSE could be successfully extended to accelerated 3D APTw imaging of brain tumors without compromising image quality using the AF of 4.
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Affiliation(s)
- Nan Zhang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai, China
| | - Haonan Zhang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Bingbing Gao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yanwei Miao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
- *Correspondence: Qingwei Song,
| | - Liangjie Lin
- MSC Clinical and Technical Solutions, Philips Healthcare, Beijing, China
| | - Jiazheng Wang
- MSC Clinical and Technical Solutions, Philips Healthcare, Beijing, China
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29
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Ruiz-Garcia H, Middlebrooks EH, Trifiletti DM, Chaichana KL, Quinones-Hinojosa A, Sheehan JP. The Extent of Resection in Gliomas-Evidence-Based Recommendations on Methodological Aspects of Research Design. World Neurosurg 2022; 161:382-395.e3. [PMID: 35505558 DOI: 10.1016/j.wneu.2021.08.140] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 08/30/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Modern neurosurgery has established maximal safe resection as a cornerstone in the management of diffuse gliomas. Evaluation of the extent of resection (EOR), and its association with certain outcomes or interventions, heavily depends on an adequate methodology to draw strong conclusions. We aim to identify weaknesses and limitations that may threaten the internal validity and generalizability of studies involving the EOR in patients with glioma and to suggest methodological recommendations that may help mitigate these threats. METHODS A systematic search was performed by querying PubMed, Web of Science, and Scopus since inception to April 30, 2021 using PICOS/PRISMA guidelines. Articles were then screened to identify high-impact studies evaluating the EOR in patients diagnosed with diffuse gliomas in accordance with predefined criteria. We identify common weakness and limitations during the evaluation of the EOR in the selected studies and then delineate potential methodological recommendations for future endeavors dealing with the EOR. RESULTS We identified 31 high-impact studies and found several research design issues including inconsistencies regarding EOR terminology, measurement, data collection, analysis, and reporting. Although some of these issues were related to now outdated reporting standards, many were still present in recent publications and deserve attention in contemporary and future research. CONCLUSIONS There is a current need to focus more attention to the methodological aspects of glioma research. Methodological inconsistencies may introduce weaknesses into the internal validity of the studies and hamper comparative analysis of cohorts from different institutions. We hope our recommendations will eventually help develop stronger methodological designs in future research endeavors.
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Affiliation(s)
- Henry Ruiz-Garcia
- Department of Neurological Surgery, Mayo Clinic, Jacksonville, Florida, USA; Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida, USA
| | - Erik H Middlebrooks
- Department of Neurological Surgery, Mayo Clinic, Jacksonville, Florida, USA; Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA
| | - Daniel M Trifiletti
- Department of Neurological Surgery, Mayo Clinic, Jacksonville, Florida, USA; Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
| | | | | | - Jason P Sheehan
- Department of Neurological Surgery, University of Virginia, Charlottesville, Virginia, USA.
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Haddad AF, Young JS, Morshed RA, Berger MS. FLAIRectomy: Resecting beyond the Contrast Margin for Glioblastoma. Brain Sci 2022; 12:brainsci12050544. [PMID: 35624931 PMCID: PMC9139350 DOI: 10.3390/brainsci12050544] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/21/2022] [Accepted: 04/21/2022] [Indexed: 12/11/2022] Open
Abstract
The standard of care for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) is maximal resection followed by chemotherapy and radiation. Studies investigating the resection of GBM have primarily focused on the contrast enhancing portion of the tumor on magnetic resonance imaging. Histopathological studies, however, have demonstrated tumor infiltration within peri-tumoral fluid-attenuated inversion recovery (FLAIR) abnormalities, which is often not resected. The histopathology of FLAIR and local recurrence patterns of GBM have prompted interest in the resection of peri-tumoral FLAIR, or FLAIRectomy. To this point, recent studies have suggested a significant survival benefit associated with safe peri-tumoral FLAIR resection. In this review, we discuss the evidence surrounding the composition of peri-tumoral FLAIR, outcomes associated with FLAIRectomy, future directions of the field, and potential implications for patients.
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31
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Van Hese L, De Vleeschouwer S, Theys T, Larivière E, Solie L, Sciot R, Siegel TP, Rex S, Heeren RM, Cuypers E. Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery. J Mass Spectrom Adv Clin Lab 2022; 24:80-89. [PMID: 35572786 PMCID: PMC9095887 DOI: 10.1016/j.jmsacl.2022.04.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/27/2022] [Accepted: 04/27/2022] [Indexed: 11/17/2022] Open
Abstract
REIMS can differentiate glioblastoma from normal brain with 99.2% sensitivity. Starting from 5% glioblastoma, REIMS showed a 100% correct classification rate. Low-grade gliomas can be identified with a 97.5% sensitivity.
Introduction Objectives Methods Results Conclusion
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Affiliation(s)
- Laura Van Hese
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
- Department of Anaesthesiology, UZ Leuven; Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Steven De Vleeschouwer
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Tom Theys
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Emma Larivière
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Lien Solie
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Raf Sciot
- Department of Pathology, University Hospitals Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Tiffany Porta Siegel
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Steffen Rex
- Department of Anaesthesiology, UZ Leuven; Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Ron M.A. Heeren
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Eva Cuypers
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
- Corresponding author at: M4I Institute, Division of Imaging Mass Spectrometry, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands.
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32
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Harris DC, Mignucci-Jiménez G, Xu Y, Eikenberry SE, Quarles CC, Preul MC, Kuang Y, Kostelich EJ. Tracking glioblastoma progression after initial resection with minimal reaction-diffusion models. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:5446-5481. [PMID: 35603364 DOI: 10.3934/mbe.2022256] [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] [Indexed: 06/15/2023]
Abstract
We describe a preliminary effort to model the growth and progression of glioblastoma multiforme, an aggressive form of primary brain cancer, in patients undergoing treatment for recurrence of tumor following initial surgery and chemoradiation. Two reaction-diffusion models are used: the Fisher-Kolmogorov equation and a 2-population model, developed by the authors, that divides the tumor into actively proliferating and quiescent (or necrotic) cells. The models are simulated on 3-dimensional brain geometries derived from magnetic resonance imaging (MRI) scans provided by the Barrow Neurological Institute. The study consists of 17 clinical time intervals across 10 patients that have been followed in detail, each of whom shows significant progression of tumor over a period of 1 to 3 months on sequential follow up scans. A Taguchi sampling design is implemented to estimate the variability of the predicted tumors to using 144 different choices of model parameters. In 9 cases, model parameters can be identified such that the simulated tumor, using both models, contains at least 40 percent of the volume of the observed tumor. We discuss some potential improvements that can be made to the parameterizations of the models and their initialization.
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Affiliation(s)
- Duane C Harris
- School of Mathematical & Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Giancarlo Mignucci-Jiménez
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Yuan Xu
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Steffen E Eikenberry
- School of Mathematical & Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - C Chad Quarles
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Mark C Preul
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Yang Kuang
- School of Mathematical & Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Eric J Kostelich
- School of Mathematical & Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA
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The Extension of the LeiCNS-PK3.0 Model in Combination with the "Handshake" Approach to Understand Brain Tumor Pathophysiology. Pharm Res 2022; 39:1343-1361. [PMID: 35258766 PMCID: PMC9246813 DOI: 10.1007/s11095-021-03154-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 12/10/2021] [Indexed: 12/22/2022]
Abstract
Micrometastatic brain tumor cells, which cause recurrence of malignant brain tumors, are often protected by the intact blood–brain barrier (BBB). Therefore, it is essential to deliver effective drugs across not only the disrupted blood-tumor barrier (BTB) but also the intact BBB to effectively treat malignant brain tumors. Our aim is to predict pharmacokinetic (PK) profiles in brain tumor regions with the disrupted BTB and the intact BBB to support the successful drug development for malignant brain tumors. LeiCNS-PK3.0, a comprehensive central nervous system (CNS) physiologically based pharmacokinetic (PBPK) model, was extended to incorporate brain tumor compartments. Most pathophysiological parameters of brain tumors were obtained from literature and two missing parameters of the BTB, paracellular pore size and expression level of active transporters, were estimated by fitting existing data, like a “handshake”. Simultaneous predictions were made for PK profiles in extracellular fluids (ECF) of brain tumors and normal-appearing brain and validated on existing data for six small molecule anticancer drugs. The LeiCNS-tumor model predicted ECF PK profiles in brain tumor as well as normal-appearing brain in rat brain tumor models and high-grade glioma patients within twofold error for most data points, in combination with estimated paracellular pore size of the BTB and active efflux clearance at the BTB. Our model demonstrated a potential to predict PK profiles of small molecule drugs in brain tumors, for which quantitative information on pathophysiological alterations is available, and contribute to the efficient and successful drug development for malignant brain tumors.
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Würtemberger U, Diebold M, Erny D, Hosp JA, Schnell O, Reinacher PC, Rau A, Kellner E, Reisert M, Urbach H, Demerath T. Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas. Cancers (Basel) 2022; 14:cancers14051155. [PMID: 35267463 PMCID: PMC8908999 DOI: 10.3390/cancers14051155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/12/2022] Open
Abstract
Purpose: Glioblastomas (GBM) and brain metastases are often difficult to differentiate in conventional MRI. Diffusion microstructure imaging (DMI) is a novel MR technique that allows the approximation of the distribution of the intra-axonal compartment, the extra-axonal cellular, and the compartment of interstitial/free water within the white matter. We hypothesize that alterations in the T2 hyperintense areas surrounding contrast-enhancing tumor components may be used to differentiate GBM from metastases. Methods: DMI was performed in 19 patients with glioblastomas and 17 with metastatic lesions. DMI metrics were obtained from the T2 hyperintense areas surrounding contrast-enhancing tumor components. Resected brain tissue was assessed in six patients in each group for features of an edema pattern and tumor infiltration in the perilesional interstitium. Results: Within the perimetastatic T2 hyperintensities, we observed a significant increase in free water (p < 0.001) and a decrease in both the intra-axonal (p = 0.006) and extra-axonal compartments (p = 0.024) compared to GBM. Perilesional free water fraction was discriminative regarding the presence of GBM vs. metastasis with a ROC AUC of 0.824. Histologically, features of perilesional edema were present in all assessed metastases and absent or marginal in GBM. Conclusion: Perilesional T2 hyperintensities in brain metastases and GBM differ significantly in DMI-values. The increased free water fraction in brain metastases suits the histopathologically based hypothesis of perimetastatic vasogenic edema, whereas in glioblastomas there is additional tumor infiltration.
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Affiliation(s)
- Urs Würtemberger
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
- Correspondence: urs.wü; Tel.: +49-761-270-51810; Fax: +49-761-270-51950
| | - Martin Diebold
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (M.D.); (D.E.)
- IMM-PACT Clinician Scientist Program, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (M.D.); (D.E.)
- Berta-Ottenstein-Program for Advanced Clinician Scientists, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Jonas A. Hosp
- Department of Neurology and Neurophysiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Peter C. Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (P.C.R.); (M.R.)
- Fraunhofer Institute for Laser Technology, 52074 Aachen, Germany
| | - Alexander Rau
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
- Department of Diagnostic and Interventional Radiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Elias Kellner
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (P.C.R.); (M.R.)
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Horst Urbach
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
| | - Theo Demerath
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
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Cui W, Wang Y, Ren J, Hubbard CS, Fu X, Fang S, Wang D, Zhang H, Li Y, Li L, Jiang T, Liu H. Personalized
fMRI
delineates functional regions preserved within brain tumors. Ann Neurol 2022; 91:353-366. [PMID: 35023218 PMCID: PMC9107064 DOI: 10.1002/ana.26303] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 01/09/2022] [Accepted: 01/10/2022] [Indexed: 11/09/2022]
Abstract
Objective Methods Results Interpretation
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Affiliation(s)
- Weigang Cui
- Department of Automation Science and Electrical Engineering Beihang University Beijing China
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
- School of Engineering Medicine, Beihang University Beijing China
| | - Yinyan Wang
- Department of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing China
- Beijing Neurosurgical Institute, Capital Medical University Beijing China
| | - Jianxun Ren
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- National Engineering Laboratory for Neuromodulation School of Aerospace Engineering, Tsinghua University Beijing China
| | - Catherine S. Hubbard
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
| | - Xiaoxuan Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China
| | - Shengyu Fang
- Beijing Neurosurgical Institute, Capital Medical University Beijing China
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
| | - Hao Zhang
- Department of Neurological Rehabilitation Beijing Bo'ai Hospital, China Rehabilitation Research Center Beijing China
| | - Yang Li
- Department of Automation Science and Electrical Engineering Beihang University Beijing China
| | - Luming Li
- National Engineering Laboratory for Neuromodulation School of Aerospace Engineering, Tsinghua University Beijing China
- Precision Medicine & Healthcare Research Center, Tsinghua‐Berkeley Shenzhen Institute, Tsinghua University Shenzhen Guangdong China
- IDG/McGovern Institute for Brain Research at Tsinghua University Beijing China
| | - Tao Jiang
- Department of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing China
- Beijing Neurosurgical Institute, Capital Medical University Beijing China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
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36
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Aabedi AA, Young JS, Zhang Y, Ammanuel S, Morshed RA, Dalle Ore C, Brown D, Phillips JJ, Oberheim Bush NA, Taylor JW, Butowski N, Clarke J, Chang SM, Aghi M, Molinaro AM, Berger MS, Hervey-Jumper SL. Association of Neurological Impairment on the Relative Benefit of Maximal Extent of Resection in Chemoradiation-Treated Newly Diagnosed Isocitrate Dehydrogenase Wild-Type Glioblastoma. Neurosurgery 2022; 90:124-130. [PMID: 34982879 PMCID: PMC9514750 DOI: 10.1227/neu.0000000000001753] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 08/24/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Increases in the extent of resection of both contrast-enhanced (CE) and non-contrast-enhanced (NCE) tissue are associated with substantial survival benefits in patients with isocitrate dehydrogenase wild-type glioblastoma. The fact, however, remains that these lesions exist within the framework of complex neural circuitry subserving cognition, movement, and behavior, all of which affect the ultimate survival outcome. The prognostic significance of the interplay between CE and NCE cytoreduction and neurological morbidity is poorly understood. OBJECTIVE To identify a clinically homogenous population of 228 patients with newly diagnosed isocitrate dehydrogenase wild-type glioblastoma, all of whom underwent maximal safe resection of CE and NCE tissue and adjuvant chemoradiation. We then set out to delineate the competing interactions between resection of CE and NCE tissue and postoperative neurological impairment with respect to overall survival. METHODS Nonparametric multivariate models of survival were generated via recursive partitioning to provide a clinically intuitive framework for the prognostication and surgical management of such patients. RESULTS We demonstrated that the presence of a new postoperative neurological impairment was the key factor in predicting survival outcomes across the entire cohort. Patients older than 60 yr who suffered from at least one new impairment had the worst survival outcome regardless of extent of resection (median of 11.6 mo), whereas those who did not develop a new impairment had the best outcome (median of 28.4 mo) so long as all CE tissue was resected. CONCLUSION Our data provide novel evidence for management strategies that prioritize safe and complete resection of CE tissue.
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Affiliation(s)
- Alexander A Aabedi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Jacob S Young
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Yalan Zhang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Simon Ammanuel
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Ramin A Morshed
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Cecilia Dalle Ore
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Desmond Brown
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Joanna J Phillips
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA.,Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA.,Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Jennie W Taylor
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA.,Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Nicholas Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Jennifer Clarke
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA.,Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Manish Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Mitchel S Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
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Starck L, Zaccagna F, Pasternak O, Gallagher FA, Grüner R, Riemer F. Effects of Multi-Shell Free Water Correction on Glioma Characterization. Diagnostics (Basel) 2021; 11:2385. [PMID: 34943621 PMCID: PMC8700586 DOI: 10.3390/diagnostics11122385] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/10/2021] [Accepted: 12/13/2021] [Indexed: 01/31/2023] Open
Abstract
Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity.
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Affiliation(s)
- Lea Starck
- Department of Physics and Technology, University of Bergen, N-5007 Bergen, Norway;
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, University of Bergen, N-5021 Bergen, Norway;
| | - Fulvio Zaccagna
- Department of Biomedical and Neuromotor Sciences, University of Bologna, 40125 Bologna, Italy;
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Functional and Molecular Neuroimaging Unit, Bellaria Hospital, 40139 Bologna, Italy
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, USA;
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - Ferdia A. Gallagher
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK;
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
| | - Renate Grüner
- Department of Physics and Technology, University of Bergen, N-5007 Bergen, Norway;
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, University of Bergen, N-5021 Bergen, Norway;
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, University of Bergen, N-5021 Bergen, Norway;
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Nonparametric D-R 1-R 2 distribution MRI of the living human brain. Neuroimage 2021; 245:118753. [PMID: 34852278 DOI: 10.1016/j.neuroimage.2021.118753] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 11/23/2022] Open
Abstract
Diffusion-relaxation correlation NMR can simultaneously characterize both the microstructure and the local chemical composition of complex samples that contain multiple populations of water. Recent developments on tensor-valued diffusion encoding and Monte Carlo inversion algorithms have made it possible to transfer diffusion-relaxation correlation NMR from small-bore scanners to clinical MRI systems. Initial studies on clinical MRI systems employed 5D D-R1 and D-R2 correlation to characterize healthy brain in vivo. However, these methods are subject to an inherent bias that originates from not including R2 or R1 in the analysis, respectively. This drawback can be remedied by extending the concept to 6D D-R1-R2 correlation. In this work, we present a sparse acquisition protocol that records all data necessary for in vivo 6D D-R1-R2 correlation MRI across 633 individual measurements within 25 min-a time frame comparable to previous lower-dimensional acquisition protocols. The data were processed with a Monte Carlo inversion algorithm to obtain nonparametric 6D D-R1-R2 distributions. We validated the reproducibility of the method in repeated measurements of healthy volunteers. For a post-therapy glioblastoma case featuring cysts, edema, and partially necrotic remains of tumor, we present representative single-voxel 6D distributions, parameter maps, and artificial contrasts over a wide range of diffusion-, R1-, and R2-weightings based on the rich information contained in the D-R1-R2 distributions.
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Clinicopathologic analysis of microscopic tumor extension in glioma for external beam radiotherapy planning. BMC Med 2021; 19:269. [PMID: 34784919 PMCID: PMC8597244 DOI: 10.1186/s12916-021-02143-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 09/27/2021] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND There is no consensus regarding the clinical target volume (CTV) margins in radiotherapy for glioma. In this study, we aimed to perform a complete macropathologic analysis examining microscopic tumor extension (ME) to more accurately define the CTV in glioma. METHODS Thirty-eight supra-total resection specimens of glioma patients were examined on histologic sections. The ME distance, defined as the maximum linear distance from the tumor border to the invasive tumor cells, was measured at each section. We defined the CTV based on the relationships between ME distance and clinicopathologic features. RESULTS Between February 2016 and July 2020, a total of 814 slides were examined, corresponding to 162 slides for low-grade glioma (LGG) and 652 slides for high-grade glioma (HGG). The ME value was 0.69 ± 0.43 cm for LGG and 1.29 ± 0.54 cm for HGG (P < 0.001). After multivariate analysis, tumor grade, O6-methylguanine-DNA-methyltransferase promoter methylated status (MGMTm), isocitrate dehydrogenase wild-type status (IDHwt), and 1p/19q non-co-deleted status (non-codel) were positively correlated with ME distance (all P < 0.05). We defined the CTV of glioma based on tumor grade. To take into account approximately 95% of the ME, a margin of 1.00 cm, 1.50 cm, and 2.00 cm were chosen for grade II, grade III, and grade IV glioma, respectively. Paired analysis of molecularly defined patients confirmed that tumors that had all three molecular alterations (i.e., MGMTm/IDHwt/non-codel) were the most aggressive subgroups (all P < 0.05). For these patients, the margin could be up to 1.50 cm, 2.00 cm, and 2.50 cm for grade II, grade III, and grade IV glioma, respectively, to cover the subclinical lesions in 95% of cases. CONCLUSIONS The ME was different between the grades of gliomas. It may be reasonable to recommend 1.00 cm, 1.50 cm, and 2.00 cm CTV margins for grade II, grade III, and grade IV glioma, respectively. Considering the highly aggressive nature of MGMTm/IDHwt/non-codel tumors, for these patients, the margin could be further expanded by 0.5 cm. These recommendations would encompass microscopic disease extension in 95% of cases. TRIAL REGISTRATION The trial was registered with Chinese Clinical Trial Registry ( ChiCTR2100049376 ).
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40
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Malik N, Geraghty B, Dasgupta A, Maralani PJ, Sandhu M, Detsky J, Tseng CL, Soliman H, Myrehaug S, Husain Z, Perry J, Lau A, Sahgal A, Czarnota GJ. MRI radiomics to differentiate between low grade glioma and glioblastoma peritumoral region. J Neurooncol 2021; 155:181-191. [PMID: 34694564 DOI: 10.1007/s11060-021-03866-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 10/05/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND The peritumoral region (PTR) of glioblastoma (GBM) appears as a T2W-hyperintensity and is composed of microscopic tumor and edema. Infiltrative low grade glioma (LGG) comprises tumor cells that seem similar to GBM PTR on MRI. The work here explored if a radiomics-based approach can distinguish between the two groups (tumor and edema versus tumor alone). METHODS Patients with GBM and LGG imaged using a 1.5 T MRI were included in the study. Image data from cases of GBM PTR, and LGG were manually segmented guided by T2W hyperintensity. A set of 91 first-order and texture features were determined from each of T1W-contrast, and T2W-FLAIR, diffusion-weighted imaging sequences. Applying filtration techniques, a total of 3822 features were obtained. Different feature reduction techniques were employed, and a subsequent model was constructed using four machine learning classifiers. Leave-one-out cross-validation was used to assess classifier performance. RESULTS The analysis included 42 GBM and 36 LGG. The best performance was obtained using AdaBoost classifier using all the features with a sensitivity, specificity, accuracy, and area of curve (AUC) of 91%, 86%, 89%, and 0.96, respectively. Amongst the feature selection techniques, the recursive feature elimination technique had the best results, with an AUC ranging from 0.87 to 0.92. Evaluation with the F-test resulted in the most consistent feature selection with 3 T1W-contrast texture features chosen in over 90% of instances. CONCLUSIONS Quantitative analysis of conventional MRI sequences can effectively demarcate GBM PTR from LGG, which is otherwise indistinguishable on visual estimation.
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Affiliation(s)
- Nauman Malik
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Benjamin Geraghty
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Archya Dasgupta
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Pejman Jabehdar Maralani
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada.,Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Michael Sandhu
- Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Zain Husain
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - James Perry
- Department of Neurology, Sunnybrook Health Sciences Centre, Toronto, Canada.,Department of Medicine, University of Toronto, Toronto, Canada
| | - Angus Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Gregory J Czarnota
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON, M4N3M5, Canada. .,Department of Radiation Oncology, University of Toronto, Toronto, Canada. .,Physical Sciences, Sunnybrook Research Institute, Toronto, Canada. .,Department of Medical Biophysics, University of Toronto, Toronto, Canada.
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Wei RL, Wei XT. Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences. Front Oncol 2021; 11:694498. [PMID: 34422648 PMCID: PMC8374052 DOI: 10.3389/fonc.2021.694498] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/19/2021] [Indexed: 12/15/2022] Open
Abstract
Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.
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Affiliation(s)
- Ruo-Lun Wei
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin-Ting Wei
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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42
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Martín-Noguerol T, Mohan S, Santos-Armentia E, Cabrera-Zubizarreta A, Luna A. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions. Eur J Radiol 2021; 143:109900. [PMID: 34412007 DOI: 10.1016/j.ejrad.2021.109900] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/24/2021] [Accepted: 08/03/2021] [Indexed: 12/30/2022]
Abstract
Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.
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Affiliation(s)
| | - Suyash Mohan
- Division of Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
| | | | | | - Antonio Luna
- MRI Unit, Radiology Department, HT Medica, Jaén, Spain.
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Magnetic Resonance Relaxometry for Tumor Cell Density Imaging for Glioma: An Exploratory Study via 11C-Methionine PET and Its Validation via Stereotactic Tissue Sampling. Cancers (Basel) 2021; 13:cancers13164067. [PMID: 34439221 PMCID: PMC8393497 DOI: 10.3390/cancers13164067] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/01/2021] [Accepted: 08/11/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary To test the hypothesis that quantitative magnetic resonance relaxometry reflects glioma tumor load within tissue and that it can be an imaging surrogate for visualizing non-contrast-enhancing tumors, we investigated the correlation between T1- and T2-weighted relaxation times, apparent diffusion coefficient (ADC) on magnetic resonance imaging, and 11C-methionine (MET) on positron emission tomography (PET). Moreover, we compared T1- and T2-relaxation times and ADC with tumor cell density (TCD) findings obtained via stereotactic image-guided tissue sampling. A T1-relaxation time of >1850 ms but <3200 ms or a T2-relaxation time of >115 ms but <225 ms under 3 T indicated high MET uptake. The stereotactic tissue sampling findings confirmed that the T1-relaxation time of 1850–3200 ms significantly indicated higher TCD while the T2-relaxation time and ADC did not significantly correlate with the stereotactic tissue sampling findings. However, synthetically synthesized tumor load images from the T1- and T2-relaxation maps were able to visualize MET uptake presented on PET. Abstract One of the most crucial yet challenging issues for glioma patient care is visualizing non-contrast-enhancing tumor regions. In this study, to test the hypothesis that quantitative magnetic resonance relaxometry reflects glioma tumor load within tissue and that it can be an imaging surrogate for visualizing non-contrast-enhancing tumors, we investigated the correlation between T1- and T2-weighted relaxation times, apparent diffusion coefficient (ADC) on magnetic resonance imaging, and 11C-methionine (MET) on positron emission tomography (PET). Moreover, we compared the T1- and T2-relaxation times and ADC with tumor cell density (TCD) findings obtained via stereotactic image-guided tissue sampling. Regions that presented a T1-relaxation time of >1850 ms but <3200 ms or a T2-relaxation time of >115 ms but <225 ms under 3 T indicated a high MET uptake. In addition, the stereotactic tissue sampling findings confirmed that the T1-relaxation time of 1850–3200 ms significantly indicated a higher TCD (p = 0.04). However, ADC was unable to show a significant correlation with MET uptake or with TCD. Finally, synthetically synthesized tumor load images from the T1- and T2-relaxation maps were able to visualize MET uptake presented on PET.
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Cudalbu C, Bady P, Lai M, Xin L, Gusyatiner O, Hamou MF, Lepore M, Brouland JP, Daniel RT, Hottinger AF, Hegi ME. Metabolic and transcriptomic profiles of glioblastoma invasion revealed by comparisons between patients and corresponding orthotopic xenografts in mice. Acta Neuropathol Commun 2021; 9:133. [PMID: 34348785 PMCID: PMC8336020 DOI: 10.1186/s40478-021-01232-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 07/21/2021] [Indexed: 02/07/2023] Open
Abstract
The invasive behavior of glioblastoma, the most aggressive primary brain tumor, is considered highly relevant for tumor recurrence. However, the invasion zone is difficult to visualize by Magnetic Resonance Imaging (MRI) and is protected by the blood brain barrier, posing a particular challenge for treatment. We report biological features of invasive growth accompanying tumor progression and invasion based on associated metabolic and transcriptomic changes observed in patient derived orthotopic xenografts (PDOX) in the mouse and the corresponding patients’ tumors. The evolution of metabolic changes, followed in vivo longitudinally by 1H Magnetic Resonance Spectroscopy (1H MRS) at ultra-high field, reflected growth and the invasive properties of the human glioblastoma transplanted into the brains of mice (PDOX). Comparison of MRS derived metabolite signatures, reflecting temporal changes of tumor development and invasion in PDOX, revealed high similarity to spatial metabolite signatures of combined multi-voxel MRS analyses sampled across different areas of the patients’ tumors. Pathway analyses of the transcriptome associated with the metabolite profiles of the PDOX, identified molecular signatures of invasion, comprising extracellular matrix degradation and reorganization, growth factor binding, and vascular remodeling. Specific analysis of expression signatures from the invaded mouse brain, revealed extent of invasion dependent induction of immune response, recapitulating respective signatures observed in glioblastoma. Integrating metabolic profiles and gene expression of highly invasive PDOX provided insights into progression and invasion associated mechanisms of extracellular matrix remodeling that is essential for cell–cell communication and regulation of cellular processes. Structural changes and biochemical properties of the extracellular matrix are of importance for the biological behavior of tumors and may be druggable. Ultra-high field MRS reveals to be suitable for in vivo monitoring of progression in the non-enhancing infiltration zone of glioblastoma.
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Lee S, Choi SH, Cho HR, Koh J, Park CK, Ichikawa T. Multiparametric magnetic resonance imaging features of a canine glioblastoma model. PLoS One 2021; 16:e0254448. [PMID: 34242365 PMCID: PMC8270200 DOI: 10.1371/journal.pone.0254448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 06/27/2021] [Indexed: 11/18/2022] Open
Abstract
PURPOSE To assess glioblastoma multiforme (GBM) formation with similar imaging characteristics to human GBM using multiparametric magnetic resonance imaging (MRI) in an orthotopic xenograft canine GBM model. MATERIALS AND METHODS The canine GBM cell line J3T1 was subcutaneously injected into 6-week-old female BALB/c nude mice to obtain tumour fragments. Tumour fragments were implanted into adult male mongrel dog brains through surgery. Multiparametric MRI was performed with conventional MRI, diffusion-weighted imaging, and dynamic susceptibility contrast-enhanced perfusion-weighted imaging at one week and two weeks after surgery in a total of 15 surgical success cases. The presence of tumour cells, the necrotic area fraction, and the microvessel density (MVD) of the tumour on the histologic specimen were assessed. Tumour volume, diffusion, and perfusion parameters were compared at each time point using Wilcoxon signed-rank tests, and the differences between tumour and normal parenchyma were compared using unpaired t-tests. Spearman correlation analysis was performed between the imaging and histologic parameters. RESULTS All animals showed a peripheral enhancing lesion on MRI and confirmed the presence of a tumour through histologic analysis (92.3%). The normalized perfusion values did not show significant decreases through at least 2 weeks after the surgery (P > 0.05). There was greater cerebral blood volume and flow in the GBM than in the normal-appearing white matter (1.46 ± 0.25 vs. 1.13 ± 0.16 and 1.30 ± 0.22 vs. 1.02 ± 0.14; P < 0.001 and P < 0.001, respectively). The MVD in the histologic specimens was correlated with the cerebral blood volume in the GBM tissue (r = 0.850, P = 0.004). CONCLUSION Our results suggest that the canine GBM model showed perfusion imaging characteristics similar to those of humans, and it might have potential as a model to assess novel technical developments for GBM treatment.
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Affiliation(s)
- Seunghyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea
- School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea
| | - Hye Rim Cho
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jaemoon Koh
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tomotsugu Ichikawa
- Department of Neurological Surgery, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama, Japan
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Brown HM, Alfaro CM, Pirro V, Dey M, Hattab EM, Cohen-Gadol AA, Cooks RG. Intraoperative Mass Spectrometry Platform for IDH Mutation Status Prediction, Glioma Diagnosis, and Estimation of Tumor Cell Infiltration. J Appl Lab Med 2021; 6:902-916. [PMID: 33523209 PMCID: PMC8266740 DOI: 10.1093/jalm/jfaa233] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 11/23/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Surgical tumor resection is the primary treatment option for diffuse glioma, the most common malignant brain cancer. The intraoperative diagnosis of gliomas from tumor core samples can be improved by use of molecular diagnostics. Further, residual tumor at surgical margins is a primary cause of tumor recurrence and malignant progression. This study evaluates a desorption electrospray ionization mass spectrometry (DESI-MS) system for intraoperative isocitrate dehydrogenase (IDH) mutation assessment, estimation of tumor cell infiltration as tumor cell percentage (TCP), and disease status. This information could be used to enhance the extent of safe resection and so potentially improve patient outcomes. METHODS A mobile DESI-MS instrument was modified and used in neurosurgical operating rooms (ORs) on a cohort of 49 human subjects undergoing craniotomy with tumor resection for suspected diffuse glioma. Small tissue biopsies (ntotal = 203) from the tumor core and surgical margins were analyzed by DESI-MS in the OR and classified using univariate and multivariate statistical methods. RESULTS Assessment of IDH mutation status using DESI-MS/MS to measure 2-hydroxyglutarate (2-HG) ion intensities from tumor cores yielded a sensitivity, specificity, and overall diagnostic accuracy of 89, 100, and 94%, respectively (ncore = 71). Assessment of TCP (categorized as low or high) in tumor margin and core biopsies using N-acetyl-aspartic acid (NAA) intensity provided a sensitivity, specificity, and accuracy of 91, 76, and 83%, respectively (ntotal = 203). TCP assessment using lipid profile deconvolution provided sensitivity, specificity, and accuracy of 76, 85, and 81%, respectively (ntotal = 203). Combining the experimental data and using PCA-LDA predictions of disease status, the sensitivity, specificity, and accuracy in predicting disease status are 63%, 83%, and 74%, respectively (ntotal = 203). CONCLUSIONS The DESI-MS system allowed for identification of IDH mutation status, glioma diagnosis, and estimation of tumor cell infiltration intraoperatively in a large human glioma cohort. This methodology should be further refined for clinical diagnostic applications.
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Affiliation(s)
| | - Clint M. Alfaro
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
| | - Valentina Pirro
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
| | - Mahua Dey
- Department of Neurological Surgery, Indiana University School of Medicine, Goodman Campbell Brain and Spine, Indianapolis, IN, USA
| | - Eyas M. Hattab
- Department of Pathology and Laboratory Medicine, University of Louisville, KY, USA
| | - Aaron A. Cohen-Gadol
- Department of Neurological Surgery, Indiana University School of Medicine, Goodman Campbell Brain and Spine, Indianapolis, IN, USA
| | - R. Graham Cooks
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
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Chen J, Patel TR, Pinho MC, Choi C, Harrison CE, Baxter JD, Derner K, Pena S, Liticker J, Raza J, Hall RG, Reed GD, Cai C, Hatanpaa KJ, Bankson JA, Bachoo RM, Malloy CR, Mickey BE, Park JM. Preoperative imaging of glioblastoma patients using hyperpolarized 13C pyruvate: Potential role in clinical decision making. Neurooncol Adv 2021; 3:vdab092. [PMID: 34355174 PMCID: PMC8331053 DOI: 10.1093/noajnl/vdab092] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Background Glioblastoma remains incurable despite treatment with surgery, radiation therapy, and cytotoxic chemotherapy, prompting the search for a metabolic pathway unique to glioblastoma cells.13C MR spectroscopic imaging with hyperpolarized pyruvate can demonstrate alterations in pyruvate metabolism in these tumors. Methods Three patients with diagnostic MRI suggestive of a glioblastoma were scanned at 3 T 1–2 days prior to tumor resection using a 13C/1H dual-frequency RF coil and a 13C/1H-integrated MR protocol, which consists of a series of 1H MR sequences (T2 FLAIR, arterial spin labeling and contrast-enhanced [CE] T1) and 13C spectroscopic imaging with hyperpolarized [1-13C]pyruvate. Dynamic spiral chemical shift imaging was used for 13C data acquisition. Surgical navigation was used to correlate the locations of tissue samples submitted for histology with the changes seen on the diagnostic MR scans and the 13C spectroscopic images. Results Each tumor was histologically confirmed to be a WHO grade IV glioblastoma with isocitrate dehydrogenase wild type. Total hyperpolarized 13C signals detected near the tumor mass reflected altered tissue perfusion near the tumor. For each tumor, a hyperintense [1-13C]lactate signal was detected both within CE and T2-FLAIR regions on the 1H diagnostic images (P = .008). [13C]bicarbonate signal was maintained or decreased in the lesion but the observation was not significant (P = .3). Conclusions Prior to surgical resection, 13C MR spectroscopic imaging with hyperpolarized pyruvate reveals increased lactate production in regions of histologically confirmed glioblastoma.
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Affiliation(s)
- Jun Chen
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Toral R Patel
- Department of Neurosurgery, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Marco C Pinho
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Changho Choi
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Crystal E Harrison
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jeannie D Baxter
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Kelley Derner
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Salvador Pena
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jeff Liticker
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jaffar Raza
- Department of Pharmacy Practice, Texas Tech University Health Sciences Center, Dallas, Texas, USA
| | - Ronald G Hall
- Department of Pharmacy Practice, Texas Tech University Health Sciences Center, Dallas, Texas, USA
| | | | - Chunyu Cai
- Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Kimmo J Hatanpaa
- Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - James A Bankson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Robert M Bachoo
- Department of Neurosurgery and Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Craig R Malloy
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Bruce E Mickey
- Department of Neurosurgery, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jae Mo Park
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, Texas, USA
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Moon HH, Kim HS, Park JE, Kim YH, Kim JH. Refinement of response assessment in neuro-oncology (RANO) using non-enhancing lesion type and contrast enhancement evolution pattern in IDH wild-type glioblastomas. BMC Cancer 2021; 21:654. [PMID: 34074252 PMCID: PMC8170938 DOI: 10.1186/s12885-021-08414-2] [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: 02/08/2021] [Accepted: 05/24/2021] [Indexed: 11/24/2022] Open
Abstract
Background Updated response assessment in neuro-oncology (RANO) does not consider peritumoral non-enhancing lesion (NEL) and baseline (residual) contrast enhancement (CE) volume. The objective of this study is to explore helpful imaging characteristics to refine RANO for assessing early treatment response (pseudoprogression and time-to-progression [TTP]) in patients with IDH wild-type glioblastoma. Methods This retrospective study enrolled 86 patients with IDH wild-type glioblastoma who underwent consecutive MRI examinations before and after concurrent chemoradiotherapy (CCRT). NEL was classified as edema- or tumor-dominant type on pre-CCRT MRI. CE evolution was categorized into 4 patterns based on post-operative residual CE (measurable vs. non-measurable) and CE volume change (same criteria with RANO) during CCRT. Multivariable logistic regression, including clinical parameters, NEL type, and CE evolution pattern, was used to analyze pseudoprogression rate. TTP and OS according to NEL type and CE evolution pattern was analyzed by the Kaplan–Meier method. Results Pseudoprogression rate was significantly lower (chi-square test, P = .047) and TTP was significantly shorter (hazard ratio [HR] = 2.03, P = .005) for tumor-dominant type than edema-dominant type of NEL. NEL type was the only predictive marker of pseudoprogression on multivariate analysis (odds ratio = 0.26, P = .046). Among CE evolution patterns, TTP and OS was shortest in patients with residual CE compared with those exhibiting new CE (HR = 4.33, P < 0.001 and HR = 3.71, P = .009, respectively). In edema-dominant NEL type, both TTP and OS was stratified by CE evolution pattern (log-rank, P = .001), whereas it was not in tumor-dominant NEL. Conclusions NEL type improves prediction of pseudoprogression and, together with CE evolution pattern, further stratifies TTP and OS in patients with IDH wild-type glioblastoma and may become a helpful biomarker for refining RANO. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08414-2.
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Affiliation(s)
- Hye Hyeon Moon
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea.
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Young-Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
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Grossman SA, Romo CG, Rudek MA, Supko J, Fisher J, Nabors LB, Wen PY, Peereboom DM, Ellingson BM, Elmquist W, Barker FG, Kamson D, Sarkaria JN, Timmer W, Bindra RS, Ye X. Baseline requirements for novel agents being considered for phase II/III brain cancer efficacy trials: conclusions from the Adult Brain Tumor Consortium's first workshop on CNS drug delivery. Neuro Oncol 2021; 22:1422-1424. [PMID: 32506123 DOI: 10.1093/neuonc/noaa142] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
| | | | | | - Jeffrey Supko
- Massachusetts General Hospital, Boston, Massachusetts
| | - Joy Fisher
- Johns Hopkins University, Baltimore, Maryland
| | - L Burt Nabors
- University of Alabama Birmingham, Birmingham, Alabama
| | | | | | | | | | - Fred G Barker
- Massachusetts General Hospital, Boston, Massachusetts
| | | | | | | | | | - Xiaobu Ye
- Johns Hopkins University, Baltimore, Maryland
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Quantitative mapping of individual voxels in the peritumoral region of IDH-wildtype glioblastoma to distinguish between tumor infiltration and edema. J Neurooncol 2021; 153:251-261. [PMID: 33905055 DOI: 10.1007/s11060-021-03762-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 04/20/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE The peritumoral region (PTR) in glioblastoma (GBM) represents a combination of infiltrative tumor and vasogenic edema, which are indistinguishable on magnetic resonance imaging (MRI). We developed a radiomic signature by using imaging data from low grade glioma (LGG) (marker of tumor) and PTR of brain metastasis (BM) (marker of edema) and applied it on the GBM PTR to generate probabilistic maps. METHODS 270 features were extracted from T1-weighted, T2-weighted, and apparent diffusion coefficient maps in over 3.5 million voxels of LGG (36 segments) and BM (45 segments) scanned in a 1.5T MRI. A support vector machine classifier was used to develop the radiomics model from approximately 50% voxels (downsampled to 10%) and validated with the remaining. The model was applied to over 575,000 voxels of the PTR of 10 patients with GBM to generate a quantitative map using Platt scaling (infiltrative tumor vs. edema). RESULTS The radiomics model had an accuracy of 0.92 and 0.79 in the training and test set, respectively (LGG vs. BM). When extrapolated on the GBM PTR, 9 of 10 patients had a higher percentage of voxels with a tumor-like signature over radiological recurrence areas. In 7 of 10 patients, the areas under curves (AUC) were > 0.50 confirming a positive correlation. Including all the voxels from the GBM patients, the infiltration signature had an AUC of 0.61 to predict recurrence. CONCLUSION A radiomic signature can demarcate areas of microscopic tumors from edema in the PTR of GBM, which correlates with areas of future recurrence.
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