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Du Y, Wang T, Qu L, Li H, Guo Q, Wang H, Liu X, Wu X, Song Z. Preoperative Molecular Subtype Classification Prediction of Ovarian Cancer Based on Multi-Parametric Magnetic Resonance Imaging Multi-Sequence Feature Fusion Network. Bioengineering (Basel) 2024; 11:472. [PMID: 38790338 PMCID: PMC11117786 DOI: 10.3390/bioengineering11050472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/22/2024] [Accepted: 04/30/2024] [Indexed: 05/26/2024] Open
Abstract
In the study of the deep learning classification of medical images, deep learning models are applied to analyze images, aiming to achieve the goals of assisting diagnosis and preoperative assessment. Currently, most research classifies and predicts normal and cancer cells by inputting single-parameter images into trained models. However, for ovarian cancer (OC), identifying its different subtypes is crucial for predicting disease prognosis. In particular, the need to distinguish high-grade serous carcinoma from clear cell carcinoma preoperatively through non-invasive means has not been fully addressed. This study proposes a deep learning (DL) method based on the fusion of multi-parametric magnetic resonance imaging (mpMRI) data, aimed at improving the accuracy of preoperative ovarian cancer subtype classification. By constructing a new deep learning network architecture that integrates various sequence features, this architecture achieves the high-precision prediction of the typing of high-grade serous carcinoma and clear cell carcinoma, achieving an AUC of 91.62% and an AP of 95.13% in the classification of ovarian cancer subtypes.
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Affiliation(s)
- Yijiang Du
- Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China; (Y.D.)
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai 200032, China
| | - Tingting Wang
- Department of Nuclear Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Linhao Qu
- Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China; (Y.D.)
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai 200032, China
| | - Haiming Li
- Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Qinhao Guo
- Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Haoran Wang
- Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China; (Y.D.)
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai 200032, China
| | - Xinyuan Liu
- Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Xiaohua Wu
- Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Zhijian Song
- Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China; (Y.D.)
- Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai 200032, China
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Qiu X, Gao J, Yang J, Hu J, Hu W, Zhang X, Lu JJ, Kong L. Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:1199. [PMID: 36544672 PMCID: PMC9761124 DOI: 10.21037/atm-20-1646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 04/27/2020] [Indexed: 12/24/2022]
Abstract
Background To assess the survival predictability of perfusion magnetic resonance imaging (MRI) by the normalized cerebral blood volume (nCBV) prior to particle beam radiotherapy (PBRT) in high-grade glioma (HGG) patients underwent particle therapy. Methods The study retrieved dynamic susceptibility contrast MRI acquired prior to PBRT between 6/2015 and 3/2019 in 45 patients with HGG. Maximum nCBV (nCBVmax) within or adjacent to surgical/tumor bed was measured using 'hot-spot' method. The predictive values of nCBVmax for progression-free survival (PFS) and overall survival (OS) were assessed in univariate Kaplan-Meier curve and multivariate Cox proportional hazards (CPH) models. Nomograms based on CPH results were constructed to individualize the predicted probability of OS and PFS. Results The Kaplan-Meier curves and all CPH models based on nCBVmax as continuous variable (nCBVmax-C), group by cut-off derived from median value and Youden-index method showed that nCBVmax prior to radiotherapy was a strong predictor for both PFS and OS in HGG patients who underwent PBRT. Nomograms built on CPH models showed similar excellent performance in both discrimination and calibration. Conclusions Perfusion imaging prior to PBRT is a strong predictor of survival in HGG. Novel perfusion MR-based nomogram with prospective validation could potentially be formally used in future clinical practice to individualize survival probability.
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Affiliation(s)
- Xianxin Qiu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Jing Gao
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Jing Yang
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Jiyi Hu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Weixu Hu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Xiaoyong Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China;,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jiade J. Lu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Lin Kong
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Center, Shanghai, China
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Farrell C, Shi W, Bodman A, Olson JJ. Congress of neurological surgeons systematic review and evidence-based guidelines update on the role of emerging developments in the management of newly diagnosed glioblastoma. J Neurooncol 2020; 150:269-359. [PMID: 33215345 DOI: 10.1007/s11060-020-03607-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 08/23/2020] [Indexed: 12/12/2022]
Abstract
TARGET POPULATION These recommendations apply to adult patients with newly diagnosed or suspected glioblastoma. IMAGING Question What imaging modalities are in development that may be able to provide improvements in diagnosis, and therapeutic guidance for individuals with newly diagnosed glioblastoma? RECOMMENDATION Level III: It is suggested that techniques utilizing magnetic resonance imaging for diffusion weighted imaging, and to measure cerebral blood and magnetic spectroscopic resonance imaging of N-acetyl aspartate, choline and the choline to N-acetyl aspartate index to assist in diagnosis and treatment planning in patients with newly diagnosed or suspected glioblastoma. SURGERY Question What new surgical techniques can be used to provide improved tumor definition and resectability to yield better tumor control and prognosis for individuals with newly diagnosed glioblastoma? RECOMMENDATIONS Level II: The use of 5-aminolevulinic acid is recommended to improve extent of tumor resection in patients with newly diagnosed glioblastoma. Level II: The use of 5-aminolevulinic acid is recommended to improve median survival and 2 year survival in newly diagnosed glioblastoma patients with clinical characteristics suggesting poor prognosis. Level III: It is suggested that, when available, patients be enrolled in properly designed clinical trials assessing the value of diffusion tensor imaging in improving the safety of patients with newly diagnosed glioblastoma undergoing surgery. NEUROPATHOLOGY Question What new pathology techniques and measurement of biomarkers in tumor tissue can be used to provide improved diagnostic ability, and determination of therapeutic responsiveness and prognosis for patients with newly diagnosed glioblastomas? RECOMMENDATIONS Level II: Assessment of tumor MGMT promoter methylation status is recommended as a significant predictor of a longer progression free survival and overall survival in patients with newly diagnosed with glioblastoma. Level II: Measurement of tumor expression of neuron-glia-2, neurofilament protein, glutamine synthetase and phosphorylated STAT3 is recommended as a predictor of overall survival in patients with newly diagnosed with glioblastoma. Level III: Assessment of tumor IDH1 mutation status is suggested as a predictor of longer progression free survival and overall survival in patients with newly diagnosed with glioblastoma. Level III: Evaluation of tumor expression of Phosphorylated Mitogen-Activated Protein Kinase protein, EGFR protein, and Insulin-like Growth Factor-Binding Protein-3 is suggested as a predictor of overall survival in patients with newly diagnosed with glioblastoma. RADIATION Question What radiation therapy techniques are in development that may be used to provide improved tumor control and prognosis for individuals with newly diagnosed glioblastomas? RECOMMENDATIONS Level III: It is suggested that patients with newly diagnosed glioblastoma undergo pretreatment radio-labeled amino acid tracer positron emission tomography to assess areas at risk for tumor recurrence to assist in radiation treatment planning. Level III: It is suggested that, when available, patients be with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of radiation dose escalation, altered fractionation, or new radiation delivery techniques. CHEMOTHERAPY Question What emerging chemotherapeutic agents or techniques are available to provide better tumor control and prognosis for patients with newly diagnosed glioblastomas? RECOMMENDATION Level III: As no emerging chemotherapeutic agents or techniques were identified in this review that improved tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of chemotherapy. MOLECULAR AND TARGETED THERAPY Question What new targeted therapy agents are available to provide better tumor control and prognosis for individuals with newly diagnosed glioblastomas? RECOMMENDATION Level III: As no new molecular and targeted therapies have clearly provided better tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of molecular and targeted therapies IMMUNOTHERAPY: Question What emerging immunotherapeutic agents or techniques are available to provide better tumor control and prognosis for patients with newly diagnosed glioblastomas? RECOMMENDATION Level III: As no immunotherapeutic agents have clearly provided better tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of immunologically-based therapies. NOVEL THERAPIES Question What novel therapies or techniques are in development to provide better tumor control and prognosis for individuals with newly diagnosed glioblastomas? RECOMMENDATIONS Level II: The use of tumor-treating fields is recommended for patients with newly diagnosed glioblastoma who have undergone surgical debulking and completed concurrent chemoradiation without progression of disease at the time of tumor-treating field therapy initiation. Level II: It is suggested that, when available, enrollment in properly designed studies of vector containing herpes simplex thymidine kinase gene and prodrug therapies be considered in patients with newly diagnosed glioblastoma.
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Affiliation(s)
- Christopher Farrell
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - Wenyin Shi
- Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA, USA
| | | | - Jeffrey J Olson
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA.
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Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. Sci Rep 2018; 8:17062. [PMID: 30459364 PMCID: PMC6244161 DOI: 10.1038/s41598-018-34820-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 10/24/2018] [Indexed: 12/18/2022] Open
Abstract
Functional MRI may identify critical windows of opportunity for drug delivery and distinguish between early treatment responders and non-responders. Using diffusion-weighted, dynamic contrast-enhanced, and dynamic susceptibility contrast MRI, as well as pro-angiogenic and pro-inflammatory blood markers, we prospectively studied the physiologic tumor-related changes in fourteen newly diagnosed glioblastoma patients during standard therapy. 153 MRI scans and blood collection were performed before chemoradiation (baseline), weekly during chemoradiation (week 1–6), monthly before each cycle of adjuvant temozolomide (pre-C1-C6), and after cycle 6. The apparent diffusion coefficient, volume transfer coefficient (Ktrans), and relative cerebral blood volume (rCBV) and flow (rCBF) were calculated within the tumor and edema regions and compared to baseline. Cox regression analysis was used to assess the effect of clinical variables, imaging, and blood markers on progression-free (PFS) and overall survival (OS). After controlling for additional covariates, high baseline rCBV and rCBF within the edema region were associated with worse PFS (microvessel rCBF: HR = 7.849, p = 0.044; panvessel rCBV: HR = 3.763, p = 0.032; panvessel rCBF: HR = 3.984; p = 0.049). The same applied to high week 5 and pre-C1 Ktrans within the tumor region (week 5 Ktrans: HR = 1.038, p = 0.003; pre-C1 Ktrans: HR = 1.029, p = 0.004). Elevated week 6 VEGF levels were associated with worse OS (HR = 1.034; p = 0.004). Our findings suggest a role for rCBV and rCBF at baseline and Ktrans and VEGF levels during treatment as markers of response. Functional imaging changes can differ substantially between tumor and edema regions, highlighting the variable biologic and vascular state of tumor microenvironment during therapy.
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Marino MA, Helbich T, Baltzer P, Pinker-Domenig K. Multiparametric MRI of the breast: A review. J Magn Reson Imaging 2017. [DOI: 10.1002/jmri.25790] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Affiliation(s)
- Maria Adele Marino
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging; Medical University of Vienna; Austria
- Department of Biomedical Sciences and Morphologic and Functional Imaging, Policlinico Universitario G. Martino; University of Messina; Messina Italy
| | - Thomas Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging; Medical University of Vienna; Austria
| | - Pascal Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging; Medical University of Vienna; Austria
| | - Katja Pinker-Domenig
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging; Medical University of Vienna; Austria
- Department of Radiology; Molecular Imaging and Therapy Service, Memorial Sloan Kettering Cancer Center; New York New York USA
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Dynamic contrast-enhanced MR imaging in predicting progression of enhancing lesions persisting after standard treatment in glioblastoma patients: a prospective study. Eur Radiol 2016; 27:3156-3166. [PMID: 27975145 DOI: 10.1007/s00330-016-4692-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Revised: 11/02/2016] [Accepted: 11/29/2016] [Indexed: 12/19/2022]
Abstract
OBJECTIVES To prospectively explore the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the progression of enhancing lesions persisting after standard treatment in patients with surgically resected glioblastoma (GBM). METHODS Forty-seven GBM patients, who underwent near-total tumorectomy followed by concurrent chemoradiation therapy (CCRT) with temozolomide (TMZ) between May 2014 and February 2016, were enrolled. Twenty-four patients were finally analyzed for measurable enhancing lesions persisting after standard treatment. DCE-MRI parameters were calculated at enhancing lesions. Mann-Whitney U tests and multivariable stepwise logistic regression were used to compare parameters between progression (n = 16) and non-progression (n = 8) groups. RESULTS Mean Ktrans and ve were significantly lower in progression than in non-progression (P = 0.037 and P = 0.037, respectively). The 5th percentile of the cumulative Ktrans histogram was also significantly lower in the progression than in non-progression group (P = 0.017). Mean ve was the only independent predictor of progression (P = 0.007), with a sensitivity of 100%, specificity of 63%, and an overall accuracy of 88% at a cut-off value of 0.873. CONCLUSIONS DCE-MRI may help predict the progression of enhancing lesions persisting after the completion of standard treatment in patients with surgically resected GBM, with mean ve serving as an independent predictor of progression. KEY POINTS • Enhancing lesions may persist after standard treatment in GBM patients. • DCE-MRI may help predict the progression of the enhancing lesions. • Mean K trans and v e were lower in progression than in non-progression group. • DCE-MRI may help identify patients requiring close follow-up after standard treatment. • DCE-MRI may help plan treatment strategies for GBM patients.
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Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation? J Neurooncol 2016; 130:181-192. [DOI: 10.1007/s11060-016-2232-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 07/31/2016] [Indexed: 01/18/2023]
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Kerkhof M, Hagenbeek RE, van der Kallen BFW, Lycklama À Nijeholt GJ, Dirven L, Taphoorn MJB, Vos MJ. Interobserver variability in the radiological assessment of magnetic resonance imaging (MRI) including perfusion MRI in glioblastoma multiforme. Eur J Neurol 2016; 23:1528-33. [PMID: 27424939 DOI: 10.1111/ene.13070] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Accepted: 05/13/2016] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE Conventional magnetic resonance imaging (MRI) has limited value for differentiation of true tumor progression and pseudoprogression in treated glioblastoma multiforme (GBM). Perfusion weighted imaging (PWI) may be helpful in the differentiation of these two phenomena. Here interobserver variability in routine radiological evaluation of GBM patients is assessed using MRI, including PWI. METHODS Three experienced neuroradiologists evaluated MR scans of 28 GBM patients during temozolomide chemoradiotherapy at three time points: preoperative (MR1) and postoperative (MR2) MR scan and the follow-up MR scan after three cycles of adjuvant temozolomide (MR3). Tumor size was measured both on T1 post-contrast and T2 weighted images according to the Response Assessment in Neuro-Oncology criteria. PW images of MR3 were evaluated by visual inspection of relative cerebral blood volume (rCBV) color maps and by quantitative rCBV measurements of enhancing areas with highest rCBV. Image interpretability of PW images was also scored. Finally, the neuroradiologists gave a conclusion on tumor status, based on the interpretation of both T1 and T2 weighted images (MR1, MR2 and MR3) in combination with PWI (MR3). RESULTS Interobserver agreement on visual interpretation of rCBV maps was good (κ = 0.63) but poor on quantitative rCBV measurements and on interpretability of perfusion images (intraclass correlation coefficient 0.37 and κ = 0.23, respectively). Interobserver agreement on the overall conclusion of tumor status was moderate (κ = 0.48). CONCLUSIONS Interobserver agreement on the visual interpretation of PWI color maps was good. However, overall interpretation of MR scans (using both conventional and PW images) showed considerable interobserver variability. Therefore, caution should be applied when interpreting MRI results during chemoradiation therapy.
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Affiliation(s)
- M Kerkhof
- Department of Neurology, Medical Center Haaglanden, The Hague, The Netherlands.
| | - R E Hagenbeek
- Department of Radiology, Medical Center Haaglanden, The Hague, The Netherlands
| | | | | | - L Dirven
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - M J B Taphoorn
- Department of Neurology, Medical Center Haaglanden, The Hague, The Netherlands.,Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - M J Vos
- Department of Neurology, Medical Center Haaglanden, The Hague, The Netherlands
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Burth S, Kickingereder P, Eidel O, Tichy D, Bonekamp D, Weberling L, Wick A, Löw S, Hertenstein A, Nowosielski M, Schlemmer HP, Wick W, Bendszus M, Radbruch A. Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma. Neuro Oncol 2016; 18:1673-1679. [PMID: 27298312 DOI: 10.1093/neuonc/now122] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Accepted: 05/03/2016] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The purpose of this study was to determine the relevance of clinical data, apparent diffusion coefficient (ADC), and relative cerebral blood volume (rCBV) from dynamic susceptibility contrast (DSC) perfusion and the volume transfer constant (ktrans) from dynamic contrast-enhanced (DCE) perfusion for predicting overall survival (OS) and progression-free survival (PFS) in newly diagnosed treatment-naïve glioblastoma patients. METHODS Preoperative MR scans including standardized contrast-enhanced T1 (cT1), T2 - fluid-attenuated inversion recovery (FLAIR), ADC, DSC, and DCE of 125 patients with subsequent histopathologically confirmed glioblastoma were performed on a 3 Tesla MRI scanner. ADC, DSC, and DCE parameters were analyzed in semiautomatically segmented tumor volumes on contrast-enhanced (CE) cT1 and hyperintense signal changes on T2 FLAIR (ED). Univariate and multivariable Cox regression analyses including age, sex, extent of resection (EOR), and KPS were performed to assess the influence of each parameter on OS and PFS. RESULTS Univariate Cox regression analysis demonstrated a significant association of age, KPS, and EOR with PFS and age, KPS, EOR, lower ADC, and higher rCBV with OS. Multivariable analysis showed independent significance of male sex, KPS, EOR, and increased rCBVCE for PFS, and age, sex, KPS, and EOR for OS. CONCLUSIONS MRI parameters help to predict OS in a univariate Cox regression analysis, and increased rCBVCE is associated with shorter PFS in the multivariable model. In summary, however, our findings suggest that the relevance of MRI parameters is outperformed by clinical parameters in a multivariable analysis, which limits their prognostic value for survival prediction at the time of initial diagnosis.
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Affiliation(s)
- Sina Burth
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Oliver Eidel
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Diana Tichy
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - David Bonekamp
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Lukas Weberling
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Antje Wick
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Sarah Löw
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Anne Hertenstein
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Martha Nowosielski
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Heinz-Peter Schlemmer
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Wolfgang Wick
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Alexander Radbruch
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
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10
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Khalifa J, Tensaouti F, Chaltiel L, Lotterie JA, Catalaa I, Sunyach MP, Ibarrola D, Noël G, Truc G, Walker P, Magné N, Charissoux M, Ken S, Peran P, Berry I, Moyal ECJ, Laprie A. Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation. Eur Radiol 2016; 26:4194-4203. [PMID: 26843012 DOI: 10.1007/s00330-016-4234-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Revised: 01/13/2016] [Accepted: 01/20/2016] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To identify relevant relative cerebral blood volume biomarkers from T2* dynamic-susceptibility contrast magnetic resonance imaging to anticipate glioblastoma progression after chemoradiation. METHODS Twenty-five patients from a prospective study with glioblastoma, primarily treated by chemoradiation, were included. According to the last follow-up MRI confirmed status, patients were divided into: relapse group (n = 13) and control group (n = 12). The time of last MR acquisition was tend; MR acquisitions performed at tend-2M, tend-4M and tend-6M (respectively 2, 4 and 6 months before tend) were analyzed to extract relevant variations among eleven perfusion biomarkers (B). These variations were assessed through R(B), as the absolute value of the ratio between ∆B from tend-4M to tend-2M and ∆B from tend-6M to tend-4M. The optimal cut-off for R(B) was determined using receiver-operating-characteristic curve analysis. RESULTS The fraction of hypoperfused tumor volume (F_hPg) was a relevant biomarker. A ratio R(F_hPg) ≥ 0.61 would have been able to anticipate relapse at the next follow-up with a sensitivity/specificity/accuracy of 92.3 %/63.6 %/79.2 %. High R(F_hPg) (≥0.61) was associated with more relapse at tend compared to low R(F_hPg) (75 % vs 12.5 %, p = 0.008). CONCLUSION Iterative analysis of F_hPg from consecutive examinations could provide surrogate markers to predict progression at the next follow-up. KEY POINTS • Related rCBV biomarkers from DSC were assessed to anticipate GBM progression. • Biomarkers were assessed through their patterns of variation during the follow-up. • The fraction of hypoperfused tumour volume (F_hP g ) seemed to be a relevant biomarker. • An innovative ratio R(F_hP g ) could be an early surrogate marker of relapse. • A significant time gain could be achieved in the management of GBM patients.
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Affiliation(s)
- J Khalifa
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France. .,Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, 1 avenue Irène-Joliot Curie, 31100, Toulouse, France.
| | - F Tensaouti
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France
| | - L Chaltiel
- Department of Biostatistics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, 1 avenue Irène-Joliot Curie, 31100, Toulouse, France
| | - J-A Lotterie
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France.,Department of Nuclear Medicine, CHU Rangueil, 1 Avenue du Professeur Jean Poulhès, 31400, Toulouse, France
| | - I Catalaa
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France.,Department of Radiology, CHU Rangueil, 1 Avenue du Professeur Jean Poulhès, 31400, Toulouse, France
| | - M P Sunyach
- Department of Radiation Oncology, Centre Léon Bérard, 28 Rue Laënnec, 69373, Lyon, France
| | - D Ibarrola
- CERMEP - Imagerie du Vivant, Lyon, France
| | - G Noël
- Department of Radiation Oncology, Centre Paul Strauss, EA 3430, University of Strasbourg, 3 rue de la Porte de l'Hôpital, 67065, Strasbourg, France
| | - G Truc
- Department of Radiation Oncology, Centre Georges-François Leclerc, 1 rue Professeur Marion, 21079, Dijon, France
| | - P Walker
- Laboratory of Electronics, Computer Science and Imaging (Le2I), UMR 6306 CNRS, University of Burgundy, Dijon, France
| | - N Magné
- Department of Radiation Oncology, Institut de cancérologie Lucien-Neuwirth, 108 bis, avenue Albert-Raimond, 42271, Saint-Priest-en-Jarez, France
| | - M Charissoux
- Department of Radiation Oncology, Institut du Cancer de Montpellier, 208 avenue des Apothicaires, parc Euromédecine, 34298, Montpellier cedex 5, France
| | - S Ken
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France.,Department of Medical Physics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, 1 avenue Irène-Joliot Curie, 31100, Toulouse, France
| | - P Peran
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France.,Université Toulouse III Paul Sabatier, UMR 1214, 31059, Toulouse, France
| | - I Berry
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France.,Department of Nuclear Medicine, CHU Rangueil, 1 Avenue du Professeur Jean Poulhès, 31400, Toulouse, France.,Université Toulouse III Paul Sabatier, UMR 1214, 31059, Toulouse, France
| | - E Cohen-Jonathan Moyal
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, 1 avenue Irène-Joliot Curie, 31100, Toulouse, France.,Université Toulouse III Paul Sabatier, 31000, Toulouse, France.,INSERM U1037, Centre de Recherches contre le Cancer de Toulouse, 1 avenue Irène-Joliot Curie, 31100, Toulouse, France
| | - A Laprie
- INSERM UMR 1214, TONIC (TOulouse NeuroImaging Centre), 31059, Toulouse, France.,Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, 1 avenue Irène-Joliot Curie, 31100, Toulouse, France.,Université Toulouse III Paul Sabatier, 31000, Toulouse, France
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11
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Xie K, Liu CY, Hasso AN, Crow RW. Visual field changes as an early indicator of glioblastoma multiforme progression: two cases of functional vision changes before MRI detection. Clin Ophthalmol 2015; 9:1041-7. [PMID: 26089636 PMCID: PMC4468993 DOI: 10.2147/opth.s79723] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Glioblastoma multiforme is an aggressive tumor associated with a high rate of recurrence even after maximal therapy. In a disease with poor prognosis and rapid deterioration, early detection of tumor progression is necessary to make timely treatment decisions or to initiate end of life care. We identify two cases where Humphrey visual field testing predated magnetic resonance imaging and positron emission tomography findings of tumor progression by months in glioblastoma multiforme. New or worsening visual field defects may indicate signs of tumor progression in glioblastoma multiforme and should prompt further investigation.
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Affiliation(s)
- Kate Xie
- Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, Irvine, CA, USA
| | - Catherine Y Liu
- Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, Irvine, CA, USA
| | - Anton N Hasso
- Department of Radiological Sciences, University of California Irvine Medical Center, Orange, CA, USA
| | - Robert Wade Crow
- Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, Irvine, CA, USA
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