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Hamon G, Lecler A, Ferré JC, Bourdillon P, Duron L, Savatovsky J. 3-Tesla amide proton transfer-weighted imaging (APT-WI): elevated signal also in tumor mimics. Eur Radiol 2025; 35:3558-3567. [PMID: 39592486 DOI: 10.1007/s00330-024-11202-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 09/12/2024] [Accepted: 10/11/2024] [Indexed: 11/28/2024]
Abstract
OBJECTIVES To explore amide proton transfer-weighted imaging (APTwi) for the initial classification of brain masses in clinical practice by systematically reporting APTwi signal intensity (APT-SI) in tumor mimics and brain tumors. MATERIALS AND METHODS Single-center retrospective analysis (2017-2020) of APTwi in 156 patients (84 men, mean age: 50.9 ± 20) who underwent characterization imaging of a brain mass prior to any treatment, using 3-Tesla MRI. 125/156 (80%) patients presented with brain tumor and 31/156 (20%) with tumor mimics. Regions of interest were manually drawn on 2D axial slices by two readers on APTwi map in lesional and perilesional areas and APT-SI, corresponding to the Magnetization Transfer Ratio asymmetry at 3.5 ppm, was systematically reported. Student's t-test or Wilcoxon-test were used to compare groups of patients. RESULTS The mean APT-SI in lesional and perilesional areas were significantly higher in tumors compared to tumor mimics: 3% [2.10-4] (median [Q1-Q3]) vs 1.7% [0.80-2.55] (p < 0.001) and 1.9% [1.2-2.80] vs. 1.0% [0.55-2.3] (p < 0.01). There were no differences in mean APT-SI in the tumor core between low and high-grade tumors: 2.5% [1.80-4.0] vs. 3.25% [2.5-4.0]. The mean APT-SI was significantly higher in high-grade glioma compared to low-grade glioma: 3.4% [2.7-4] vs. 2.1% [1.7-2.5] (p < 0.001). Highest mean APT-SI in tumor core were found in mesenchymal tumors (5.83% ± 1.45, mean ± SD), embryonal tumors (5.27% ± 3.5) and meningiomas (4.28% ± 0.70). In tumor mimics, highest mean APT-SI was found in the core of infectious lesions (3.52% ± 0.67). CONCLUSION High signal on ATPwi is not exclusive to high-grade brain tumors but can be observed in some tumor mimics and subtypes of low-grade tumors. KEY POINTS Question What is the value of amide proton transfer-weighted imaging (APTwi) in the setting of brain mass classification? Findings High APT-signal intensity in the tumor core of a brain mass could correspond to a high- or low-grade tumor or tumor mimic. Clinical relevance In patients presenting for the initial classification of brain masses, APTwi findings should be interpreted with caution and in conjunction with other MRI parameters, as a high APTwi signal does not necessarily indicate a high-grade tumor.
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Affiliation(s)
- Guillaume Hamon
- Department of Neuroradiology, University Hospital Pontchaillou, Rennes, France
| | - Augustin Lecler
- Department of Neuroradiology, Rothschild Foundation Hospital, Paris, France.
| | | | - Pierre Bourdillon
- Department of Neurosurgery, Rothschild Foundation Hospital, Paris, France
| | - Loïc Duron
- Department of Neuroradiology, Rothschild Foundation Hospital, Paris, France
| | - Julien Savatovsky
- Department of Neuroradiology, Rothschild Foundation Hospital, Paris, France
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Yang Q, Su S, Zhang T, Wang M, Dou W, Li K, Ren Y, Zheng Y, Wang M, Xu Y, Sun Y, Liu Z, Tan T. A deep learning framework for reconstructing Breast Amide Proton Transfer weighted imaging sequences from sparse frequency offsets to dense frequency offsets. Comput Med Imaging Graph 2025; 123:102563. [PMID: 40373577 DOI: 10.1016/j.compmedimag.2025.102563] [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: 10/22/2024] [Revised: 03/23/2025] [Accepted: 04/24/2025] [Indexed: 05/17/2025]
Abstract
Amide Proton Transfer (APT) technique is a novel functional MRI technique that enables quantification of protein metabolism, but its wide application is largely limited in clinical settings by its long acquisition time. One way to reduce the scanning time is to obtain fewer frequency offset images during image acquisition. However, sparse frequency offset images are not inadequate to fit the z-spectral, a curve essential to quantifying the APT effect, which might compromise its quantification. In our study, we develop a deep learning-based model that allows for reconstructing dense frequency offsets from sparse ones, potentially reducing scanning time. We propose to leverage time-series convolution to extract both short and long-range spatial and frequency features of the APT imaging sequence. Our proposed model outperforms other seq2seq models, achieving superior reconstruction with a peak signal-to-noise ratio of 45.8 (95% confidence interval (CI): [44.9 46.7]), and a structural similarity index of 0.989 (95% CI:[0.987 0.993]) for the tumor region. We have integrated a weighted layer into our model to evaluate the impact of individual frequency offset on the reconstruction process. The weights assigned to the frequency offset at ±6.5 ppm, 0 ppm, and 3.5 ppm demonstrate higher significance as learned by the model. Experimental results demonstrate that our proposed model effectively reconstructs dense frequency offsets (n = 29, from 7 to -7 with 0.5 ppm as an interval) from data with 21 frequency offsets, reducing scanning time by 25%. This work presents a method for shortening the APT imaging acquisition time, offering potential guidance for parameter settings in APT imaging and serving as a valuable reference for clinicians.
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Affiliation(s)
- Qiuhui Yang
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China; Guangxi Key Laboratory of Machine Vision and Intelligent Control, Wuzhou University, Wuzhou, China
| | - Shu Su
- First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Tianyu Zhang
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Meng Wang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | | | - Kefeng Li
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
| | - Ya Ren
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Yijia Zheng
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Mingwei Wang
- Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Yi Xu
- Shanghai Key Lab of Digital Media Processing and Transmission, Shanghai Jiao Tong University, Shanghai, China
| | - Yue Sun
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
| | - Zhou Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
| | - Tao Tan
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China.
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3
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Ramaglia A, Parodi C, Milanaccio C, Verrico A, Molteni M, Garrè ML, Pacetti M, Vella S, Resaz M, Tortora D, Severino M, Rossi A. Use of amide proton transfer (APT) imaging in the differentiation of pediatric low-grade brain tumors from tumor-like brain lesions. Neuroradiology 2025:10.1007/s00234-025-03582-5. [PMID: 40116946 DOI: 10.1007/s00234-025-03582-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Accepted: 03/02/2025] [Indexed: 03/23/2025]
Abstract
BACKGROUND AND PURPOSE Low grade tumors (LGT) are the most frequent central nervous system lesions observed in children. Despite the high-throughput research, differentiating LGT from tumor- like lesions (TLL) and providing an accurate differential diagnosis based on conventional MRI remains a challenge. For this reason, advanced MR sequences are routinely investigated and applied in clinical practice. The aim of this study is to explore the potential of the amide proton transfer (APTw) sequence as a tool for discriminating LGT from TLL. MATERIALS AND METHODS In this single-center retrospective study, we recruited 35 patients (20 with a histologically confirmed LGT, and 15 with a TLL) with both conventional and APT MRI images obtained on a 3T clinical scanner at onset or prior to treatment/surgery. Two volumes of interest (VOI), namely the whole lesion and the normal appearing white matter (NAWM), were defined using the semi-automatic segmentation tool from Philips Intellispace portal for Windows (v. 8). The mean APTw (mAPTw) and difference between the mAPTw lesion and the NAWM (dAPTw) were measured and compared between the two groups. RESULTS Lower values were found in the TLL group compared to the LGT group for both the mAPTw (1.51 ± 0.64% vs. 2.87 ± 0.96%) and dAPTw (0.24 ± 0.72% vs. 1.53 ± 1.08%) (p-value < 0.001). Based on ROC curve analysis, optimal cut-offs value for mAPTw and dATPw were 1.79 and 0.53, respectively. CONCLUSION APT imaging may prove useful to discriminate between LGT and TLL in pediatric patients.
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Affiliation(s)
- Antonia Ramaglia
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy.
| | - Costanza Parodi
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | - Claudia Milanaccio
- Neuro-Oncology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | - Antonio Verrico
- Neuro-Oncology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | - Marta Molteni
- Neuro-Oncology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Maria Luisa Garrè
- Neuro-Oncology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | - Mattia Pacetti
- Division of Neurosurgery, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | - Stephanie Vella
- Medical Imaging Department, Mater Dei Hospital, Msida, Malta
| | - Martina Resaz
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | - Domenico Tortora
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
| | | | - Andrea Rossi
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, 16147, Italy
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
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Simegn GL, Sun PZ, Zhou J, Kim M, Reddy R, Zu Z, Zaiss M, Yadav NN, Edden RA, van Zijl PC, Knutsson L. Motion and magnetic field inhomogeneity correction techniques for chemical exchange saturation transfer (CEST) MRI: A contemporary review. NMR IN BIOMEDICINE 2025; 38:e5294. [PMID: 39532518 PMCID: PMC11606773 DOI: 10.1002/nbm.5294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Revised: 10/14/2024] [Accepted: 10/31/2024] [Indexed: 11/16/2024]
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful imaging technique sensitive to tissue molecular composition, pH, and metabolic processes in situ. CEST MRI uniquely probes the physical exchange of protons between water and specific molecules within tissues, providing a window into physiological phenomena that remain invisible to standard MRI. However, given the very low concentration (millimolar range) of CEST compounds, the effects measured are generally only on the order of a few percent of the water signal. Consequently, a few critical challenges, including correction of motion artifacts and magnetic field (B0 and B1 +) inhomogeneities, have to be addressed in order to unlock the full potential of CEST MRI. Motion, whether from patient movement or inherent physiological pulsations, can distort the CEST signal, hindering accurate quantification. B0 and B1 + inhomogeneities, arising from scanner hardware imperfections, further complicate data interpretation by introducing spurious variations in the signal intensity. Without proper correction of these confounding factors, reliable analysis and clinical translation of CEST MRI remain challenging. Motion correction methods aim to compensate for patient movement during (prospective) or after (retrospective) image acquisition, reducing artifacts and preserving data quality. Similarly, B0 and B1 + inhomogeneity correction techniques enhance the spatial and spectral accuracy of CEST MRI. This paper aims to provide a comprehensive review of the current landscape of motion and magnetic field inhomogeneity correction methods in CEST MRI. The methods discussed apply to saturation transfer (ST) MRI in general, including semisolid magnetization transfer contrast (MTC) and relayed nuclear Overhauser enhancement (rNOE) studies.
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Affiliation(s)
- Gizeaddis Lamesgin Simegn
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30329, USA
- Emory National Primate Research Center, Emory University, Atlanta, GA 30329, USA
| | - Jinyuan Zhou
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Mina Kim
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Moritz Zaiss
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Nirbhay Narayan Yadav
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Richard A.E. Edden
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Peter C.M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
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5
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Wang X, Ishimatsu K, Li J, Wen X, Ou W, Anwar A, Chaudhary J, Takahashi M, Sherry AD, Corbin IR. APT imaging of hepatocellular carcinoma signals an effective therapeutic response in advance of tumor shrinkage. Hepat Oncol 2024; 11:2389031. [PMID: 39881558 PMCID: PMC11407511 DOI: 10.1080/20450923.2024.2389031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 07/23/2024] [Indexed: 01/31/2025] Open
Abstract
Aim: The aim of this study was to assess the utility of weighted amide proton transfer (APTw) MRI in three different rodent models of hepatocellular carcinoma (HCC).Methods: APTw MRI was evaluated in models of diethylnitrosamine (DEN) induced HCC, N1S1 syngeneic orthotopic xenograft and human HepG2 ectopic xenograft.Results: All models of HCC showed a higher APTw signal over the surrounding normal tissues. In the DEN model, the APTw signal could differentiate HCC lesions from benign nodules. Intra-arterial administration of low-density lipoprotein docosahexaenoic acid (LDL-DHA) nanoparticles to N1S1 xenografts rapidly lowered the tumor APTw signal within 72 h. Direct injections of LDL-DHA nanoparticles into HepG2 xenografts also showed similar therapeutic responses.Conclusion: We have demonstrated the utility of APTw imaging in the diagnostic/therapeutic management of HCC.
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Affiliation(s)
- Xiaojing Wang
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Keisuke Ishimatsu
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Junjie Li
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Xiaodong Wen
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Weijun Ou
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
- Organ Transplantation Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China
| | - Arnida Anwar
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Jaideep Chaudhary
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Masaya Takahashi
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - A Dean Sherry
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
- Internal Medicine Division of Liver & Digestive Diseases, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
| | - Ian R Corbin
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
- Internal Medicine Division of Liver & Digestive Diseases, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
- Department of Radiology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX75390, USA
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Yang C, Hassan HA, Omar NF, Soo TH, Shuib bin Yahaya A, Shi T, Luo Y, Wu M. Effects of amide proton transfer imaging in diagnosis, grading and prognosis prediction of cervical cancer: A systematic review and meta-analysis. Heliyon 2024; 10:e40291. [PMID: 39748993 PMCID: PMC11693897 DOI: 10.1016/j.heliyon.2024.e40291] [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: 08/30/2024] [Revised: 11/06/2024] [Accepted: 11/07/2024] [Indexed: 01/04/2025] Open
Abstract
Purpose To assess the effectiveness of Amide Proton Transfer (APT) imaging in predicting the histopathological characteristics of cervical cancer. Methods A comprehensive literature search was conducted across multiple databases, covering studies until December 27, 2023. The meta-analysis was performed using Stata 15 and Review Manager 5.4 software. Key metrics analyzed included pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and summary receiver operating characteristic curves. The analysis focused on differentiating cervical cancer types, squamous carcinoma differentiation, and lymph node involvement. Meta-regression was employed to investigate heterogeneity. Results Thirteen studies involving 868 patients were included in the meta-analysis. For differentiating adenocarcinoma from squamous carcinoma, the pooled sensitivity was 0.82 (95%CI: 0.71-0.90), specificity was 0.65 (95%CI: 0.48-0.79), and DOR was 9 (95%CI: 1.6-3.5). When distinguishing poorly differentiated from moderately/well-differentiated squamous carcinoma, the sensitivity was 0.74 (95%CI: 0.66-0.81), specificity was 0.83 (95%CI: 0.75-0.89), and DOR was 14 (95%CI: 8-23). For identifying lymph node involvement, the sensitivity was 0.87 (95%CI: 0.78-0.92), specificity was 0.66 (95%CI: 0.59-0.73), and DOR was 13 (95%CI: 7-26). No publication bias was detected. Conclusions APT imaging demonstrates high sensitivity and specificity in distinguishing between cervical cancer types, grading squamous carcinoma, and detecting lymph node involvement. It can be considered a reliable technique for predicting the pathological features of cervical cancer in clinical practice.
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Affiliation(s)
- Chongshuang Yang
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
- Department of Radiology, Tongren People's Hospital, Tongren, Guizhou Province, 554300, China
| | - Hasyma Abu Hassan
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
| | - Nur Farhayu Omar
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
| | - Tze Hui Soo
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
| | - Ahmad Shuib bin Yahaya
- Department of Obstetrics and Gynecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, UPM Serdang, Selangor, Malaysia
| | - Tianliang Shi
- Department of Radiology, Tongren People's Hospital, Tongren, Guizhou Province, 554300, China
| | - Yinbin Luo
- Department of Radiology, Tongren People's Hospital, Tongren, Guizhou Province, 554300, China
| | - Min Wu
- Department of Radiology, Tongren People's Hospital, Tongren, Guizhou Province, 554300, China
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Borges de Almeida G, Pascuzzo R, Mambrin F, Aquino D, Verri M, Moscatelli M, Del Bene M, DiMeco F, Silvani A, Pollo B, Grisoli M, Doniselli FM. The Role of Amide Proton Transfer (APT)-Weighted Imaging in Glioma: Assessment of Tumor Grading, Molecular Profile and Survival in Different Tumor Components. Cancers (Basel) 2024; 16:3014. [PMID: 39272871 PMCID: PMC11394364 DOI: 10.3390/cancers16173014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 08/14/2024] [Accepted: 08/21/2024] [Indexed: 09/15/2024] Open
Abstract
Amide Proton Transfer-weighted (APTw) imaging is a molecular MRI technique used to quantify protein concentrations in gliomas, which have heterogeneous components with varying cellularity and metabolic activity. This study aimed to assess the correlation between the component-specific APT signal of the neoplasm and WHO grade, molecular profile and survival status. Sixty-one patients with adult-type diffuse gliomas were retrospectively analyzed. APT values were semi-automatically extracted from tumor solid and, whenever present, necrotic components. APT values were compared between groups stratified by WHO grade, IDH-mutation, MGMT promoter methylation and 1- and 2-year survival status using Wilcoxon rank-sum test, adjusting for multiple comparisons. Overall survival (OS) was analyzed in the subgroup of 48 patients with grade 4 tumors using Cox proportional-hazards models. Random-effects models were used to assess inter-subject heterogeneity of the mean APT values in each tumor component. APT values of the solid component significantly differed between patients with grades 2-3 and 4 tumors (mean 1.58 ± 0.50 vs. 2.04 ± 0.56, p = 0.028) and correlated with OS after 1 year (1.81 ± 0.58 in survivors vs. 2.17 ± 0.51 in deceased patients, p = 0.030). APT values did not differ by IDH-mutation, MGMT methylation, and 2-year survival status. Within grade 4 glioma patients, higher APT kurtosis of the solid component was a negative prognostic factor (hazard ratio = 1.60, p = 0.040). Mean APT values of the necrosis showed high inter-subject variability, although most necrotic tumors were grade 4 and IDH wildtype. In conclusion, APTw imaging in the solid component provided metrics associated with glioma grade and survival status but showed weak correlation with IDH-mutation and MGMT promoter methylation status, in contrast to previous works. Further research is needed to understand APT signal variability within the necrotic component of high-grade gliomas.
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Affiliation(s)
| | - Riccardo Pascuzzo
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Francesca Mambrin
- Neuroradiology Unit, Department of Diagnostics and Pathology, Azienda Ospedaliera Universitaria Integrata Verona, Piazzale Aristide Stefani 1, 37126 Verona, Italy
| | - Domenico Aquino
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Mattia Verri
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Marco Moscatelli
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Massimiliano Del Bene
- Neurosurgery Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Francesco DiMeco
- Neurosurgery Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
- Department of Oncology and Hematology-Oncology, Università Degli Studi di Milano, 20122 Milan, Italy
- Department of Neurological Surgery, Johns Hopkins Medical School, Baltimore, MD 21205, USA
| | - Antonio Silvani
- Neuro-Oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Bianca Pollo
- Neuropathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Marina Grisoli
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
| | - Fabio Martino Doniselli
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133 Milan, Italy
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8
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Filimonova E, Pashkov A, Borisov N, Kalinovsky A, Rzaev J. Utilizing the amide proton transfer technique to characterize diffuse gliomas based on the WHO 2021 classification of CNS tumors. Neuroradiol J 2024; 37:490-499. [PMID: 38548655 PMCID: PMC11366199 DOI: 10.1177/19714009241242658] [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] [Indexed: 08/28/2024] Open
Abstract
PURPOSE Diffuse gliomas present a significant challenge for healthcare systems globally. While brain MRI plays a vital role in diagnosis, prognosis, and treatment monitoring, accurately characterizing gliomas using conventional MRI techniques alone is challenging. In this study, we explored the potential of utilizing the amide proton transfer (APT) technique to predict tumor grade and type based on the WHO 2021 Classification of CNS Tumors. METHODS Forty-two adult patients with histopathologically confirmed brain gliomas were included in the study. They underwent 3T MRI imaging, which involved APT sequence. Multinomial and binary logistic regression models were employed to classify patients into clinically relevant groups based on MRI findings and demographic variables. RESULTS We found that the best model for tumor grade classification included patient age along with APT values. The highest sensitivity (88%) was observed for Grade 4 tumors, while Grade 3 tumors showed the highest specificity (79%). For tumor type classification, our model incorporated four predictors: APT values, patient's age, necrosis, and the presence of hemorrhage. The glioblastoma group had the highest sensitivity and specificity (87%), whereas balanced accuracy was the lowest for astrocytomas (0.73). CONCLUSION The APT technique shows great potential for noninvasive evaluation of diffuse gliomas. The changes in the classification of gliomas as per the WHO 2021 version of the CNS Tumor Classification did not affect its usefulness in predicting tumor grade or type.
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Affiliation(s)
- Elena Filimonova
- FSBI “Federal Center of Neurosurgery”, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | - Anton Pashkov
- FSBI “Federal Center of Neurosurgery”, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
- Department of Data Collection and Processing Systems, Novosibirsk State Technical University, Novosibirsk, Russia
| | - Norayr Borisov
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | - Anton Kalinovsky
- FSBI “Federal Center of Neurosurgery”, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | - Jamil Rzaev
- FSBI “Federal Center of Neurosurgery”, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
- Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
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9
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Deng HZ, Zhang HW, Huang B, Deng JH, Luo SP, Li WH, Lei Y, Liu XL, Lin F. Advances in diffuse glioma assessment: preoperative and postoperative applications of chemical exchange saturation transfer. Front Neurosci 2024; 18:1424316. [PMID: 39148521 PMCID: PMC11325484 DOI: 10.3389/fnins.2024.1424316] [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: 04/27/2024] [Accepted: 07/16/2024] [Indexed: 08/17/2024] Open
Abstract
Chemical Exchange Saturation Transfer (CEST) is a technique that uses specific off-resonance saturation pulses to pre-saturate targeted substances. This process influences the signal intensity of free water, thereby indirectly providing information about the pre-saturated substance. Among the clinical applications of CEST, Amide Proton Transfer (APT) is currently the most well-established. APT can be utilized for the preoperative grading of gliomas. Tumors with higher APTw signals generally indicate a higher likelihood of malignancy. In predicting preoperative molecular typing, APTw values are typically lower in tumors with favorable molecular phenotypes, such as isocitrate dehydrogenase (IDH) mutations, compared to IDH wild-type tumors. For differential diagnosis, the average APTw values of meningiomas are significantly lower than those of high-grade gliomas. Various APTw measurement indices assist in distinguishing central nervous system lesions with similar imaging features, such as progressive multifocal leukoencephalopathy, central nervous system lymphoma, solitary brain metastases, and glioblastoma. Regarding prognosis, APT effectively differentiates between tumor recurrence and treatment effects, and also possesses predictive capabilities for overall survival (OS) and progression-free survival (PFS).
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Affiliation(s)
- Hua-Zhen Deng
- Shantou University Medical College, Shantou City, China
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Han-Wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Biao Huang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Jin-Huan Deng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Si-Ping Luo
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Wei-Hua Li
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yi Lei
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Xiao-Lei Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
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10
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Schüre JR, Casagranda S, Sedykh M, Liebig P, Papageorgakis C, Mancini L, Bisdas S, Nichelli L, Pinter N, Mechtler L, Jafari R, Boddaert N, Dangouloff-Ros V, Poujol J, Schmidt M, Doerfler A, Zaiss M. Fluid suppression in amide proton transfer-weighted (APTw) CEST imaging: New theoretical insights and clinical benefits. Magn Reson Med 2024; 91:1354-1367. [PMID: 38073061 DOI: 10.1002/mrm.29915] [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: 06/07/2023] [Revised: 10/17/2023] [Accepted: 10/18/2023] [Indexed: 02/03/2024]
Abstract
PURPOSE Amide proton transfer-weighted (APTw) MRI at 3T provides a unique contrast for brain tumor imaging. However, APTw imaging suffers from hyperintensities in liquid compartments such as cystic or necrotic structures and provides a distorted APTw signal intensity. Recently, it has been shown that heuristically motivated fluid suppression can remove such artifacts and significantly improve the readability of APTw imaging. THEORY AND METHODS In this work, we show that the fluid suppression can actually be understood by the known concept of spillover dilution, which itself can be derived from the Bloch-McConnell equations in comparison to the heuristic approach. Therefore, we derive a novel post-processing formula that efficiently removes fluid artifact, and explains previous approaches. We demonstrate the utility of this APTw assessment in silico, in vitro, and in vivo in brain tumor patients acquired at MR scanners from different vendors. RESULTS Our results show a reduction of the CEST signals from fluid environments while keeping the APTw-CEST signal intensity almost unchanged for semi-solid tissue structures such as the contralateral normal appearing white matter. This further allows us to use the same color bar settings as for conventional APTw imaging. CONCLUSION Fluid suppression has considerable value in improving the readability of APTw maps in the neuro-oncological field. In this work, we derive a novel post-processing formula from the underlying Bloch-McConnell equations that efficiently removes fluid artifact, and explains previous approaches which justify the derivation of this metric from a theoretical point of view, to reassure the scientific and medical field about its use.
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Affiliation(s)
- Jan-Rüdiger Schüre
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Stefano Casagranda
- Department of R&D Advanced Applications, Olea Medical, La Ciotat, France
| | - Maria Sedykh
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | | | | | - Laura Mancini
- Lysholm Department of Neuroradiology, University College of London Hospitals NHS Foundation Trus, London, UK
- Institute of Neurology UCL, London, UK
| | - Sotirios Bisdas
- Lysholm Department of Neuroradiology, University College of London Hospitals NHS Foundation Trus, London, UK
- Institute of Neurology UCL, London, UK
| | - Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière-Charles Foix, Paris, France
| | - Nandor Pinter
- DENT Neurologic Institute, Buffalo, New York, USA
- Department of Radiology, Jacobs School of Medicine and Biomedical Sciences, State University of New York, Buffalo, New York, USA
| | | | - Ramin Jafari
- Philips Healthcare, Cambridge, Massachusetts, USA
| | - Nathalie Boddaert
- Necker-Enfants Malades Hospital, AP-HP, Pediatric Radiology Department, Université Paris, Paris, France
- Imagine Institute, INSERM U1163, Université Paris cité, Paris, France
| | - Volodia Dangouloff-Ros
- Necker-Enfants Malades Hospital, AP-HP, Pediatric Radiology Department, Université Paris, Paris, France
- Imagine Institute, INSERM U1163, Université Paris cité, Paris, France
| | | | - Manuel Schmidt
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Arnd Doerfler
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Moritz Zaiss
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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11
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Cheng D, Zhuo Z, Zhang P, Qu L, Duan Y, Xu X, Xie C, Liu X, Haller S, Barkhof F, Zhang L, Liu Y. Amide proton transfer-weighted imaging of pediatric brainstem glioma and its predicted value for H3 K27 alteration. Acta Radiol 2023; 64:2922-2930. [PMID: 37722801 DOI: 10.1177/02841851231197503] [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] [Indexed: 09/20/2023]
Abstract
BACKGROUND Non-invasive determination of H3 K27 alteration of pediatric brainstem glioma (pedBSG) remains a clinical challenge. PURPOSE To predict H3 K27-altered pedBSG using amide proton transfer-weighted (APTw) imaging. MATERIAL AND METHODS This retrospective study included patients with pedBSG who underwent APTw imaging and had the H3 K27 alteration status determined by immunohistochemical staining. The presence or absence of foci of markedly increased APTw signal in the lesion was visually assessed. Quantitative APTw histogram parameters within the entire solid portion of tumors were extracted and compared between H3 K27-altered and wild-type groups using Student's t-test. The ability of APTw for differential diagnosis was evaluated using logistic regression. RESULTS Sixty pedBSG patients included 48 patients with H3 K27-altered tumor (aged 2-48 years) and 12 patients with wild-type tumor (aged 3-53 years). Visual assessment showed that the foci of markedly increased APTw signal intensity were more common in the H3 K27-altered group than in wild-type group (60% vs. 16%, P = 0.007). Histogram parameters of APTw signal intensity in the H3 K27-altered group were significantly higher than those in the wild-type group (median, 2.74% vs. 2.22%, P = 0.02). The maximum (area under the receiver operating characteristic curve [AUC] = 0.72, P = 0.01) showed the highest diagnostic performance among histogram analysis. A combination of age, median and maximum APTw signal intensity could predict H3 K27 alteration with a sensitivity of 81%, specificity of 75% and AUC of 0.80. CONCLUSION APTw imaging may serve as an imaging biomarker for H3 K27 alteration of pedBSGs.
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Affiliation(s)
- Dan Cheng
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Peng Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Liying Qu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaolu Xu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Cong Xie
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Liu
- Beijing Neurosurgical Institute, Beijing, China
| | - Sven Haller
- Department of Imaging and Medical Informatics, University Hospitals of Geneva and Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- UCL Institutes of Neurology and Healthcare Engineering, London, UK
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Liwei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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12
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Nichelli L, Zaiss M, Casagranda S. APT weighted imaging in diffuse gliomas. BJR Open 2023; 5:20230025. [PMID: 37942492 PMCID: PMC10630980 DOI: 10.1259/bjro.20230025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 06/21/2023] [Accepted: 08/02/2023] [Indexed: 11/10/2023] Open
Abstract
Amide proton transfer-weighted (APTw) imaging is a non-invasive molecular MRI technique with a wide range of applications in neuroradiology and particularly neuro-oncology imaging. More than 15 years of pre-clinical experiments and clinical studies have demonstrated that APTw metrics are reproducible and reliable, leading to large-scale clinical acceptance. At present, major vendors of MRI scanners provide APTw sequences upon request. However, most neuroradiologists are unfamiliar with this advanced MRI contrast, its related metrics, and its established added value to patient care. In this manuscript, we present the APTw contrast and illustrate its clinical potential for glioma patients, before and after tumor therapy. We also show common artifacts of APTw imaging and discuss potential limitations and future refinements. Our goal is to suggest how this emerging technique can aid in diffuse gliomas work-up.
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Affiliation(s)
- Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France
| | - Moritz Zaiss
- Department of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Stefano Casagranda
- Department of Research & Development Advanced Applications, Olea Medical, La Ciotat, France
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13
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Vinogradov E, Keupp J, Dimitrov IE, Seiler S, Pedrosa I. CEST-MRI for body oncologic imaging: are we there yet? NMR IN BIOMEDICINE 2023; 36:e4906. [PMID: 36640112 PMCID: PMC10200773 DOI: 10.1002/nbm.4906] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST-MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro-oncology. The slower migration of CEST-MRI to non-neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST-MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker.
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Affiliation(s)
- Elena Vinogradov
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Ivan E Dimitrov
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Philips Healthcare, Gainesville, FL, USA
| | - Stephen Seiler
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
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14
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Jiang S, Wen Z, Ahn SS, Cai K, Paech D, Eberhart CG, Zhou J. Applications of chemical exchange saturation transfer magnetic resonance imaging in identifying genetic markers in gliomas. NMR IN BIOMEDICINE 2023; 36:e4731. [PMID: 35297117 PMCID: PMC10557022 DOI: 10.1002/nbm.4731] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 03/07/2022] [Accepted: 03/14/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) imaging is an important molecular magnetic resonance imaging technique that can image numerous low-concentration biomolecules with water-exchangeable protons (such as cellular proteins) and tissue pH. CEST, or more specially amide proton transfer-weighted imaging, has been widely used for the detection, diagnosis, and response assessment of brain tumors, and its feasibility in identifying molecular markers in gliomas has also been explored in recent years. In this paper, after briefing on the basic principles and quantification methods of CEST imaging, we review its early applications in identifying isocitrate dehydrogenase mutation status, MGMT methylation status, 1p/19q deletion status, and H3K27M mutation status in gliomas. Finally, we discuss the limitations or weaknesses in these studies.
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Affiliation(s)
- Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | | | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
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15
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Siakallis L, Topriceanu CC, Panovska-Griffiths J, Bisdas S. The role of DSC MR perfusion in predicting IDH mutation and 1p19q codeletion status in gliomas: meta-analysis and technical considerations. Neuroradiology 2023:10.1007/s00234-023-03154-5. [PMID: 37173578 DOI: 10.1007/s00234-023-03154-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 04/18/2023] [Indexed: 05/15/2023]
Abstract
PURPOSE Isocitrate dehydrogenase (IDH) mutation and 1p19q codeletion status are important for managing glioma patients. However, current practice dictates invasive tissue sampling for histomolecular classification. We investigated the current value of dynamic susceptibility contrast (DSC) MR perfusion imaging as a tool for the non-invasive identification of these biomarkers. METHODS A systematic search of PubMed, Medline, and Embase up to 2023 was performed, and meta-analyses were conducted. We removed studies employing machine learning models or using multiparametric imaging. We used random-effects standardized mean difference (SMD) and bivariate sensitivity-specificity meta-analyses, calculated the area under the hierarchical summary receiver operating characteristic curve (AUC) and performed meta-regressions using technical acquisition parameters (e.g., time to echo [TE], repetition time [TR]) as moderators to explore sources of heterogeneity. For all estimates, 95% confidence intervals (CIs) are provided. RESULTS Sixteen eligible manuscripts comprising 1819 patients were included in the quantitative analyses. IDH mutant (IDHm) gliomas had lower rCBV values compared to their wild-type (IDHwt) counterparts. The highest SMD was observed for rCBVmean, rCBVmax, and rCBV 75th percentile (SMD≈ - 0.8, 95% CI ≈ [- 1.2, - 0.5]). In meta-regression, shorter TEs, shorter TRs, and smaller slice thicknesses were linked to higher absolute SMDs. When discriminating IDHm from IDHwt, the highest pooled specificity was observed for rCBVmean (82% [72, 89]), and the highest pooled sensitivity (i.e., 92% [86, 93]) and AUC (i.e., 0.91) for rCBV 10th percentile. In the bivariate meta-regression, shorter TEs and smaller slice gaps were linked to higher pooled sensitivities. In IDHm, 1p19q codeletion was associated with higher rCBVmean (SMD = 0.9 [0.2, 1.5]) and rCBV 90th percentile (SMD = 0.9 [0.1, 1.7]) values. CONCLUSIONS Identification of vascular signatures predictive of IDH and 1p19q status is a novel promising application of DSC perfusion. Standardization of acquisition protocols and post-processing of DSC perfusion maps are warranted before widespread use in clinical practice.
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Affiliation(s)
- Loizos Siakallis
- University College London (UCL) Queen Square Institute of Neurology, London, UK.
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK.
| | - Constantin-Cristian Topriceanu
- University College London (UCL) Queen Square Institute of Neurology, London, UK
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK
- UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Jasmina Panovska-Griffiths
- The Big Data Institute and the Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The Queen's College, University of Oxford, Oxford, UK
| | - Sotirios Bisdas
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK
- Department of Brain Repair & Rehabilitation, Queen Square Institute of Neurology, University College London, London, UK
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16
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Ohba S, Murayama K, Teranishi T, Kumon M, Nakae S, Yui M, Yamamoto K, Yamada S, Abe M, Hasegawa M, Hirose Y. Three-Dimensional Amide Proton Transfer-Weighted Imaging for Differentiating between Glioblastoma, IDH-Wildtype and Primary Central Nervous System Lymphoma. Cancers (Basel) 2023; 15:952. [PMID: 36765909 PMCID: PMC9913574 DOI: 10.3390/cancers15030952] [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: 12/07/2022] [Revised: 01/26/2023] [Accepted: 01/28/2023] [Indexed: 02/05/2023] Open
Abstract
Distinguishing primary central nervous system lymphoma (PCNSL) from glioblastoma, isocitrate dehydrogenase (IDH)-wildtype is sometimes hard. Because the role of operation on them varies, accurate preoperative diagnosis is crucial. In this study, we evaluated whether a specific kind of chemical exchange saturation transfer imaging, i.e., amide proton transfer-weighted (APTw) imaging, was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. A total of 14 PCNSL and 27 glioblastoma, IDH-wildtype cases were evaluated. There was no significant difference in the mean APTw signal values between the two groups. However, the percentile values from the 1st percentile to the 20th percentile APTw signals and the width1-100 APTw signals significantly differed. The highest area under the curve was 0.796, which was obtained from the width1-100 APTw signal values. The sensitivity and specificity values were 64.3% and 88.9%, respectively. APTw imaging was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. To avoid unnecessary aggressive surgical resection, APTw imaging is recommended for cases in which PCNSL is one of the differential diagnoses.
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Affiliation(s)
- Shigeo Ohba
- Department of Neurosurgery, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Kazuhiro Murayama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Takao Teranishi
- Department of Neurosurgery, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Masanobu Kumon
- Department of Neurosurgery, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Shunsuke Nakae
- Department of Neurosurgery, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara 324-8550, Tochigi, Japan
| | - Kaori Yamamoto
- Canon Medical Systems Corporation, Otawara 324-8550, Tochigi, Japan
| | - Seiji Yamada
- Department of Diagnostic Pathology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Masato Abe
- Department of Pathology, Fujita Health University School of Health Sciences, Toyoake 470-1192, Aichi, Japan
| | - Mitsuhiro Hasegawa
- Department of Neurosurgery, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
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17
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Jabehdar Maralani P, Chan RW, Lam WW, Oakden W, Oglesby R, Lau A, Mehrabian H, Heyn C, Chan AK, Soliman H, Sahgal A, Stanisz GJ. Chemical Exchange Saturation Transfer MRI: What Neuro-Oncology Clinicians Need To Know. Technol Cancer Res Treat 2023; 22:15330338231208613. [PMID: 37872686 PMCID: PMC10594966 DOI: 10.1177/15330338231208613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/19/2023] [Accepted: 09/28/2023] [Indexed: 10/25/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) is a relatively novel magnetic resonance imaging (MRI) technique with an image contrast designed for in vivo measurement of certain endogenous molecules with protons that are exchangeable with water protons, such as amide proton transfer commonly used for neuro-oncology applications. Recent technological advances have made it feasible to implement CEST on clinical grade scanners within practical acquisition times, creating new opportunities to integrate CEST in clinical workflow. In addition, the majority of CEST applications used in neuro-oncology are performed without the use gadolinium-based contrast agents which are another appealing feature of this technique. This review is written for clinicians involved in neuro-oncologic care (nonphysicists) as the target audience explaining what they need to know as CEST makes its way into practice. The purpose of this article is to (1) review the basic physics and technical principles of CEST MRI, and (2) review the practical applications of CEST in neuro-oncology.
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Affiliation(s)
- Pejman Jabehdar Maralani
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Rachel W. Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Wilfred W. Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Wendy Oakden
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Ryan Oglesby
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Angus Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Hatef Mehrabian
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Chris Heyn
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Aimee K.M. Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Hany Soliman
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Greg J. Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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18
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Jiang S, Guo P, Heo HY, Zhang Y, Wu J, Jin Y, Laterra J, Eberhart CG, Lim M, Blakeley JO. Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas. NMR IN BIOMEDICINE 2023; 36:e4824. [PMID: 36057449 PMCID: PMC10502874 DOI: 10.1002/nbm.4824] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/25/2022] [Accepted: 08/28/2022] [Indexed: 06/15/2023]
Abstract
The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T1 w, T2 w, FLAIR, and Gd-T1 w, respectively. Model classification accuracy was 82.6% when using the combined structural MR images (T1 w, T2 w, FLAIR, Gd-T1 w), and increased to 89.5% when using these structural plus APTw images. The corresponding sensitivity and specificity were 85.0% and 76.9% for the combination of structural MR images, and 85.0% and 100% after adding APTw image features. Adding APTw-based radiomic features increased MRI accuracy in the assessment of the treatment response in post-treatment malignant gliomas.
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Affiliation(s)
- Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Pengfei Guo
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yi Zhang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jingpu Wu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yuecen Jin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - John Laterra
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
- Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | | | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Neurosurgery, Stanford University, Palo Alto, California, USA
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19
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Zhou J, Jia G. Editorial for "Amide Proton Transfer-Weighted Imaging Could Complement Apparent Diffusion Coefficient for More Lesion Characterization in Transition Zone of the Prostate". J Magn Reson Imaging 2022; 56:1320-1321. [PMID: 35503454 DOI: 10.1002/jmri.28224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 04/23/2022] [Indexed: 12/15/2022] Open
Affiliation(s)
- Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Guang Jia
- School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, China
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20
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Chen K, Jiang XW, Deng LJ, She HL. Differentiation between glioma recurrence and treatment effects using amide proton transfer imaging: A mini-Bayesian bivariate meta-analysis. Front Oncol 2022; 12:852076. [PMID: 35978813 PMCID: PMC9376615 DOI: 10.3389/fonc.2022.852076] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 06/29/2022] [Indexed: 11/24/2022] Open
Abstract
Background Amide proton transfer (APT) imaging as an emerging MRI approach has been used for distinguishing tumor recurrence (TR) and treatment effects (TEs) in glioma patients, but the initial results from recent studies are different. Aim The aim of this study is to systematically review and quantify the diagnostic performance of APT in assessing treatment response in patients with post-treatment gliomas. Methods A systematic search in PubMed, EMBASE, and the Web of Science was performed to retrieve related original studies. For the single and added value of APT imaging in distinguishing TR from TEs, we calculated pooled sensitivity and specificity by using Bayesian bivariate meta-analyses. Results Six studies were included, five of which reported on single APT imaging parameters and four of which reported on multiparametric MRI combined with APT imaging parameters. For single APT imaging parameters, the pooled sensitivity and specificity were 0.85 (95% CI: 0.75–0.92) and 0.88 (95% CI: 0.74–0.97). For multiparametric MRI including APT, the pooled sensitivity and specificity were 0.92 (95% CI: 0.85–0.97) and 0.83 (95% CI: 0.55–0.97), respectively. In addition, in the three studies reported on both single and added value of APT imaging parameters, the combined imaging parameters further improved diagnostic performance, yielding pooled sensitivity and specificity of 0.91 (95% CI: 0.80–0.97) and 0.92 (95% CI: 0.79–0.98), respectively, but the pooled sensitivity was 0.81 (95% CI: 0.65-0.93) and specificity was 0.82 (95% CI: 0.61–0.94) for single APT imaging parameters. Conclusion APT imaging showed high diagnostic performance in assessing treatment response in patients with post-treatment gliomas, and the addition of APT imaging to other advanced MRI techniques can improve the diagnostic accuracy for distinguishing TR from TE.
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Affiliation(s)
- Kai Chen
- Department of Medical Imaging, Shenzhen Samii Medical Center, Shenzhen, China
| | - Xi-Wen Jiang
- Department of Medical Imaging, Affiliated Hospital of Xiangnan University (Clinical College), Chenzhou, China
| | - Li-jing Deng
- Department of Neonatology, Shenzhen Third People’s Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Hua-Long She
- Department of Medical Imaging, Affiliated Hospital of Xiangnan University (Clinical College), Chenzhou, China
- *Correspondence: Hua-Long She,
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21
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Zhang HW, Liu XL, Zhang HB, Li YQ, Wang YL, Feng YN, Deng K, Lei Y, Huang B, Lin F. Differentiation of Meningiomas and Gliomas by Amide Proton Transfer Imaging: A Preliminary Study of Brain Tumour Infiltration. Front Oncol 2022; 12:886968. [PMID: 35646626 PMCID: PMC9132094 DOI: 10.3389/fonc.2022.886968] [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] [Received: 03/01/2022] [Accepted: 04/07/2022] [Indexed: 11/22/2022] Open
Abstract
Background Gliomas are more malignant and invasive than meningiomas. Objective To distinguish meningiomas from low-grade/high-grade gliomas (LGGs/HGGs) using amide proton transfer imaging (APT) combined with conventional magnetic resonance imaging (MRI) and to explore the application of APT in evaluating brain tumour invasiveness. Materials and Methods The imaging data of 50 brain tumors confirmed by pathology in patients who underwent APT scanning in our centre were retrospectively analysed. Of these tumors, 25 were meningiomas, 10 were LGGs, and 15 were HGGs. The extent of the tumour-induced range was measured on APT images, T2-weighted imaging (T2WI), and MRI enhancement; additionally, and the degree of enhancement was graded. Ratios (RAPT/T2 and RAPT/E) were obtained by dividing the range of changes observed by APT by the range of changes observed via T2WI and MR enhancement, respectively, and APTmean values were measured. The Mann–Whitney U test was used to compare the above measured values with the pathological results obtained for gliomas and meningiomas, the Kruskal-Wallis test was used to compare LGGs, HGGs and meningiomas, and Dunn’s test was used for pairwise comparisons. In addition, receiver operating characteristic (ROC) curves were drawn. Results The Mann–Whitney U test showed that APTmean (p=0.005), RAPT/T2 (p<0.001), and RAPT/E (p<0.001) values were statistically significant in the identification of meningioma and glioma. The Kruskal-Wallis test showed that the parameters APTmean, RAPT/T2, RAPT/E and the degree of enhancement are statistically significant. Dunn’s test revealed that RAPT/T2 (p=0.004) and RAPT/E (p=0.008) could be used for the identification of LGGs and meningiomas. APTmean (p<0.001), RAPT/T2 (p<0.001), and RAPT/E (p<0.001) could be used for the identification of HGGs and meningiomas. APTmean (p<0.001) was statistically significant in the comparison of LGGs and HGGs. ROC curves showed that RAPT/T2 (area under the curve (AUC)=0.947) and RAPT/E (AUC=0.919) could be used to distinguish gliomas from meningiomas. Conclusion APT can be used for the differential diagnosis of meningioma and glioma, but APTmean values can only be used for the differential diagnosis of HGGs and meningiomas or HGGs and LGGs. Gliomas exhibit more obvious changes than meningiomas in APT images of brain tissue; this outcome may be caused by brain infiltration.
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Affiliation(s)
- Han-Wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Xiao-Lei Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Hong-Bo Zhang
- Department of Radiology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Ying-Qi Li
- Department of Radiology, Songgang People's Hospital, Shenzhen, China
| | - Yu-Li Wang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yu-Ning Feng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Kan Deng
- Research Department, Philips Healthcare, Guangzhou, China
| | - Yi Lei
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Biao Huang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong, China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
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22
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Zhou J, Zaiss M, Knutsson L, Sun PZ, Ahn SS, Aime S, Bachert P, Blakeley JO, Cai K, Chappell MA, Chen M, Gochberg DF, Goerke S, Heo HY, Jiang S, Jin T, Kim SG, Laterra J, Paech D, Pagel MD, Park JE, Reddy R, Sakata A, Sartoretti-Schefer S, Sherry AD, Smith SA, Stanisz GJ, Sundgren PC, Togao O, Vandsburger M, Wen Z, Wu Y, Zhang Y, Zhu W, Zu Z, van Zijl PCM. Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors. Magn Reson Med 2022; 88:546-574. [PMID: 35452155 PMCID: PMC9321891 DOI: 10.1002/mrm.29241] [Citation(s) in RCA: 123] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/26/2022] [Accepted: 03/02/2022] [Indexed: 12/16/2022]
Abstract
Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.
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Affiliation(s)
- Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Linda Knutsson
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Medical Radiation Physics, Lund University, Lund, Sweden.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Silvio Aime
- Molecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Peter Bachert
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Jaishri O Blakeley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Michael A Chappell
- Mental Health and Clinical Neurosciences and Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.,Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Daniel F Gochberg
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Physics, Vanderbilt University, Nashville, Tennessee, USA
| | - Steffen Goerke
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - John Laterra
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Mark D Pagel
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Ravinder Reddy
- Center for Advance Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - A Dean Sherry
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Chemistry and Biochemistry, University of Texas at Dallas, Richardson, Texas, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Pia C Sundgren
- Department of Diagnostic Radiology/Clinical Sciences Lund, Lund University, Lund, Sweden.,Lund University Bioimaging Center, Lund University, Lund, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter C M van Zijl
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
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23
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Prediction of H3 K27M-mutant in midline gliomas by magnetic resonance imaging: a systematic review and meta-analysis. Neuroradiology 2022; 64:1311-1319. [PMID: 35416485 DOI: 10.1007/s00234-022-02947-4] [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: 01/08/2022] [Accepted: 04/04/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE To summarize the predictive value of MRI for H3 K27M-mutant in midline gliomas using meta-analysis. METHODS Systematic electronic searches of the PubMed, Embase, ISI Web of Science, and Cochrane Library up to Jun 31, 2021, were conducted by two experienced neuroradiologists with the keywords of "MRI," "Glioma," and "H3 K27M." The hierarchical summary receiver-operating characteristic (HSROC) model was used to calculate the pooled sensitivity, specificity, positive likelihood ratio (LR +), negative likelihood ratio (LR -), and diagnostic odds ratio (DOR). Coupled forest plots were used to evaluate the heterogeneity of the included studies. RESULTS Of seven original studies with a total of 593 patients, 240 glioma patients were included, with 45.5-70.6% H3 K27M-mutant gliomas. Using MRI, a pooled sensitivity of 0.78 (95% CI, 0.66-0.87), specificity of 0.85 (95% CI, 0.76-0.91), LR + of 5.07 (95% CI, 3.19-8.08), LR - of 0.26 (95% CI, 0.16-0.42), and DOR of 19.80 (95% CI, 9.28-42.28) were achieved for H3 K27M-mutant prediction. Significant heterogeneity was observed among the studies in terms of sensitivity (Q = 16.83, df = 7, p = 0.02; I2 = 58.40 [95% CI, 25.83-90.97]), LR - (Q = 16.61, df = 7, p = 0.02; I2 = 57.87 [95% CI, 24.81-90.93]), and DOR (Q = 14.05, df = 7, p = 0.05; I2 = 50.18 [95% CI, 10.06-90.31]). CONCLUSIONS This meta-analysis demonstrated a clinical value of MRI to predict H3 K27M-mutant in midline gliomas with a pooled sensitivity of 0.78 and specificity of 0.85.
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24
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Huang J, Chen Z, Park SW, Lai JHC, Chan KWY. Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges. Pharmaceutics 2022; 14:451. [PMID: 35214183 PMCID: PMC8880023 DOI: 10.3390/pharmaceutics14020451] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/10/2022] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.
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Affiliation(s)
- Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Zilin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Se-Weon Park
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Joseph H. C. Lai
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Kannie W. Y. Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
- Tung Biomedical Science Centre, City University of Hong Kong, Hong Kong, China
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25
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Zhang HW, Zhang YQ, Liu XL, Mo YQ, Lei Y, Lin F, Feng YN. MR imaging features of Lhermitte-Duclos disease: Case reports and literature review. Medicine (Baltimore) 2022; 101:e28667. [PMID: 35089210 PMCID: PMC8797601 DOI: 10.1097/md.0000000000028667] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 12/31/2021] [Accepted: 01/05/2022] [Indexed: 01/05/2023] Open
Abstract
RATIONALE Lhermitte-Duclos disease (LDD) is a rare tumor of the nervous system with a typical "tiger striped'" sign, but its features on functional magnetic resonance imaging (fMRI) are still inconclusive. PATIENT CONCERNS To explore the characteristics of LDDs using fMRI. DIAGNOSES We report 3 cases of pathologically confirmed LDDs. INTERVENTIONS Three patients underwent brain tumor surgery. OUTCOMES All the patients had a good prognosis. LESSONS Magnetic resonance spectroscopy and susceptibility-weighted imaging combined with conventional MRI can be used to better diagnose LDDs. Perfusion-weighted imaging is not specific for distinguishing cerebellar tumors. The combined application of fMRI and conventional MRI can improve the accuracy of LDD diagnoses.
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Affiliation(s)
- Han-wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yuan-qing Zhang
- Special Clinic, Shenzhen Children's Hospital, Shenzhen, YiTian Road, China
| | - Xiao-lei Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yong-qian Mo
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yi Lei
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
| | - Yu-ning Feng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen, China
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26
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Li J, Lin L, Gao X, Li S, Cheng J. Amide Proton Transfer Weighted and Intravoxel Incoherent Motion Imaging in Evaluation of Prognostic Factors for Rectal Adenocarcinoma. Front Oncol 2022; 11:783544. [PMID: 35047400 PMCID: PMC8761907 DOI: 10.3389/fonc.2021.783544] [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: 09/26/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives To analyze the value of amide proton transfer (APT) weighted and intravoxel incoherent motion (IVIM) imaging in evaluation of prognostic factors for rectal adenocarcinoma, compared with diffusion weighted imaging (DWI). Materials and Methods Preoperative pelvic MRI data of 110 patients with surgical pathologically confirmed diagnosis of rectal adenocarcinoma were retrospectively evaluated. All patients underwent high-resolution T2-weighted imaging (T2WI), APT, IVIM, and DWI. Parameters including APT signal intensity (APT SI), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient (ADC) were measured in different histopathologic types, grades, stages, and structure invasion statuses. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy, and the corresponding area under the curves (AUCs) were calculated. Results APT SI, D and ADC values of rectal mucinous adenocarcinoma (MC) were significantly higher than those of rectal common adenocarcinoma (AC) ([3.192 ± 0.661%] vs. [2.333 ± 0.471%], [1.153 ± 0.238×10-3 mm2/s] vs. [0.792 ± 0.173×10-3 mm2/s], and [1.535 ± 0.203×10-3 mm2/s] vs. [0.986 ± 0.124×10-3 mm2/s], respectively; all P<0.001). In AC group, the APT SI and D values showed significant differences between low- and high-grade tumors ([2.226 ± 0.347%] vs. [2.668 ± 0.638%], and [0.842 ± 0.148×10-3 mm2/s] vs. [0.777 ± 0.178×10-3 mm2/s], respectively, both P<0.05). The D value had significant difference between positive and negative extramural vascular invasion (EMVI) tumors ([0.771 ± 0.175×10-3 mm2/s] vs. [0.858 ± 0.151×10-3 mm2/s], P<0.05). No significant difference of APT SI, D, D*, f or ADC was observed in different T stages, N stages, perineural and lymphovascular invasions (all P>0.05). The ROC curves showed that the AUCs of APT SI, D and ADC values for distinguishing MC from AC were 0.921, 0.893 and 0.995, respectively. The AUCs of APT SI and D values in distinguishing low- from high-grade AC were 0.737 and 0.663, respectively. The AUC of the D value for evaluating EMVI involvement was 0.646. Conclusion APT and IVIM were helpful to assess the prognostic factors related to rectal adenocarcinoma, including histopathological type, tumor grade and the EMVI status.
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Affiliation(s)
- Juan Li
- Department of Magnetic Resonance Imaging (MRI), The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liangjie Lin
- Advanced Technical Support, Philips Healthcare, Beijing, China
| | - Xuemei Gao
- Department of Magnetic Resonance Imaging (MRI), The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shenglei Li
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging (MRI), The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Guo P, Unberath M, Heo HY, Eberhart CG, Lim M, Blakeley JO, Jiang S. Learning-based analysis of amide proton transfer-weighted MRI to identify true progression in glioma patients. NEUROIMAGE: CLINICAL 2022; 35:103121. [PMID: 35905666 PMCID: PMC9421489 DOI: 10.1016/j.nicl.2022.103121] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Pengfei Guo
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Mathias Unberath
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Hye-Young Heo
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | | | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | | | - Shanshan Jiang
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA.
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28
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Su C, Xu S, Lin D, He H, Chen Z, Damen FC, Ke C, Lv X, Cai K. Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients. Eur Radiol 2021; 32:101-111. [PMID: 34272981 DOI: 10.1007/s00330-021-08175-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/13/2021] [Accepted: 06/28/2021] [Indexed: 12/30/2022]
Abstract
OBJECTIVES To comprehensively and noninvasively risk-stratify glioma grade, isocitrate dehydrogenase (IDH) genotype, and 1p/19q codeletion status using multi-contrast Z-spectral magnetic resonance imaging (MRI). METHODS One hundred and thirteen patients with glioma were retrospectively included. Multiple contrasts contributing to Z-spectra, including direct saturation of water (DSW), semi-solid magnetization transfer contrast (MTC), amide proton transfer (APT) effect, aliphatic nuclear Overhauser effect, and the 2-ppm chemical exchange saturation transfer peak (CEST@2ppm), were fitted with five individual Lorentzian functions. Z-spectral contrasts were compared according to the three most important risk stratifications: tumor grade, IDH genotype, and 1p/19q codeletion status. We further investigated the differentiation of 1p/19q codeletion status within IDH mutant gliomas. The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic (ROC) analyses. RESULTS DSW was significantly different within grade, IDH genotypes, and 1p/19q codeletion status. APT was significantly different with grade and IDH mutation, but not with 1p/19q subtypes. CEST@2ppm was only significantly different with 1p/19q codeletion subtypes. DSW and CEST@2ppm were the two Z-spectral contrasts able to differentiate 1p/19q codeletion subtypes within IDH mutant gliomas. For differentiating glioma grades using ROC analyses, DSW achieved the largest AUC. For differentiating IDH genotypes, DSW and APT achieved comparable AUCs. DSW was the best metric for differentiating 1p/19q codeletion status within all patients and within the IDH mutant patients. Combining all Z-spectral contrasts improved sensitivity and specificity for all risk stratifications. CONCLUSIONS Multi-parametric Z-spectral MRI serves as a useful, comprehensive, and noninvasive imaging technique for glioma stratification in clinical patients. KEY POINTS • Multiple contrasts contributing to Z-spectra were separately fitted with Lorentzian functions. • Z-spectral contrasts were compared within the three most important and common tumor risk stratifications for gliomas: tumor grade, IDH genotype, and 1p/19q codeletion status. • The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic analyses, which found Z-spectral MRI to be a useful and comprehensive imaging biomarker for glioma stratification.
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Affiliation(s)
- Changliang Su
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China
| | - Shijie Xu
- Department of Neurosurgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China
| | - Danlin Lin
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China
| | - Haoqiang He
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China
| | - Zhenghe Chen
- Department of Neurosurgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China
| | - Frederick C Damen
- Department of Radiology College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Chao Ke
- Department of Neurosurgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China.
| | - Xiaofei Lv
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, 510060, Guangzhou, China.
| | - Kejia Cai
- Department of Radiology College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
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Zhuo Z, Qu L, Zhang P, Duan Y, Cheng D, Xu X, Sun T, Ding J, Xie C, Liu X, Haller S, Barkhof F, Zhang L, Liu Y. Prediction of H3K27M-mutant brainstem glioma by amide proton transfer-weighted imaging and its derived radiomics. Eur J Nucl Med Mol Imaging 2021; 48:4426-4436. [PMID: 34131804 DOI: 10.1007/s00259-021-05455-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 06/07/2021] [Indexed: 01/28/2023]
Abstract
PURPOSE H3K27M-mutant associated brainstem glioma (BSG) carries a very poor prognosis. We aimed to predict H3K27M mutation status by amide proton transfer-weighted (APTw) imaging and radiomic features. METHODS Eighty-one BSG patients with APTw imaging at 3T MR and known H3K27M status were retrospectively studied. APTw values (mean, median, and max) and radiomic features within manually delineated 3D tumor masks were extracted. Comparison of APTw measures between H3K27M-mutant and wildtype groups was conducted by two-sample Student's T/Mann-Whitney U test and receiver operating characteristic curve (ROC) analysis. H3K27M-mutant prediction using APTw-derived radiomics was conducted using a machine learning algorithm (support vector machine) in randomly selected train (n = 64) and test (n = 17) sets. Sensitivity analysis with additional random splits of train and test sets, 2D tumor masks, and other classifiers were conducted. Finally, a prospective cohort including 29 BSG patients was acquired for validation of the radiomics algorithm. RESULTS BSG patients with H3K27M-mutant were younger and had higher max APTw values than those with wildtype. APTw-derived radiomic measures reflecting tumor heterogeneity could predict H3K27M mutation status with an accuracy of 0.88, sensitivity of 0.92, and specificity of 0.80 in the test set. Sensitivity analysis confirmed the predictive ability (accuracy range: 0.71-0.94). In the independent prospective validation cohort, the algorithm reached an accuracy of 0.86, sensitivity of 0.88, and specificity of 0.85 for predicting H3K27M-mutation status. CONCLUSION BSG patients with H3K27M-mutant had higher max APTw values than those with wildtype. APTw-derived radiomics could accurately predict a H3K27M-mutant status in BSG patients.
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Affiliation(s)
- Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Liying Qu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Peng Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 10070, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Dan Cheng
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Xiaolu Xu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Ting Sun
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Jinli Ding
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Cong Xie
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Xing Liu
- Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 10070, China
| | - Sven Haller
- Department of Imaging and Medical Informatics, University Hospitals of Geneva and Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- UCL Institutes of Neurology and Healthcare Engineering, London, UK.,Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Liwei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 10070, China.
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
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