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Arevalo-Perez J, Yllera-Contreras E, Peck KK, Hatzoglou V, Yildirim O, Rosenblum MK, Holodny AI. Differentiating Low-Grade from High-Grade Intracranial Ependymomas: Comparison of Dynamic Contrast-Enhanced MRI and Diffusion-Weighted Imaging. AJNR Am J Neuroradiol 2024:ajnr.A8226. [PMID: 38782589 DOI: 10.3174/ajnr.a8226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 02/07/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND AND PURPOSE The aim of this study was to determine the diagnostic value of fractional plasma volume derived from dynamic contrast-enhanced perfusion MR imaging versus ADC, obtained from DWI in differentiating between grade 2 (low-grade) and grade 3 (high-grade) intracranial ependymomas. MATERIALS AND METHODS A hospital database was created for the period from January 2013 through June 2022, including patients with histologically-proved ependymoma diagnosis with available dynamic contrast-enhanced MR imaging. Both dynamic contrast-enhanced perfusion and DWI were performed on each patient using 1.5T and 3T scanners. Fractional plasma volume maps and ADC maps were calculated. ROIs were defined by a senior neuroradiologist manually by including the enhancing tumor on every section and conforming a VOI to obtain the maximum value of fractional plasma volume (Vpmax) and the minimum value of ADC (ADCmin). A Mann-Whitney U test at a significance level of corrected P = .01 was used to evaluate the differences. Additionally, receiver operating characteristic curve analysis was applied to assess the sensitivity and specificity of Vpmax and ADCmin values. RESULTS A total of 20 patients with ependymomas (10 grade 2 tumors and 10 grade 3 tumors) were included. Vpmax values for grade 3 ependymomas were significantly higher (P < .002) than those for grade 2. ADCmin values were overall lower in high-grade lesions. However, no statistically significant differences were found (P = .12114). CONCLUSIONS As a dynamic contrast-enhanced perfusion MR imaging metric, fractional plasma volume can be used as an indicator to differentiate grade 2 and grade 3 ependymomas. Dynamic contrast-enhanced perfusion MR imaging plays an important role with high diagnostic value in differentiating low- and high-grade ependymoma.
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Affiliation(s)
- Julio Arevalo-Perez
- From the Department of Radiology (J.A.-P., E.Y.-C., V.H., O.Y., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - Elena Yllera-Contreras
- From the Department of Radiology (J.A.-P., E.Y.-C., V.H., O.Y., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - Kyung K Peck
- Department of Medical Physics (K.K.P.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - Vaios Hatzoglou
- From the Department of Radiology (J.A.-P., E.Y.-C., V.H., O.Y., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - Onur Yildirim
- From the Department of Radiology (J.A.-P., E.Y.-C., V.H., O.Y., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - Marc K Rosenblum
- Department of Pathology (M.K.R.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - Andrei I Holodny
- From the Department of Radiology (J.A.-P., E.Y.-C., V.H., O.Y., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
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Arevalo-Perez J, Trang A, Yllera-Contreras E, Yildirim O, Saha A, Young R, Lyo J, Peck KK, Holodny AI. Longitudinal Evaluation of DCE-MRI as an Early Indicator of Progression after Standard Therapy in Glioblastoma. Cancers (Basel) 2024; 16:1839. [PMID: 38791921 PMCID: PMC11119591 DOI: 10.3390/cancers16101839] [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: 03/05/2024] [Revised: 05/06/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024] Open
Abstract
Background and Purpose: Distinguishing treatment-induced imaging changes from progressive disease has important implications for avoiding inappropriate discontinuation of a treatment. Our goal in this study is to evaluate the utility of dynamic contrast-enhanced (DCE) perfusion MRI as a biomarker for the early detection of progression. We hypothesize that DCE-MRI may have the potential as an early predictor for the progression of disease in GBM patients when compared to the current standard of conventional MRI. Methods: We identified 26 patients from 2011 to 2023 with newly diagnosed primary glioblastoma by histopathology and gross or subtotal resection of the tumor. Then, we classified them into two groups: patients with progression of disease (POD) confirmed by pathology or change in chemotherapy and patients with stable disease without evidence of progression or need for therapy change. Finally, at least three DCE-MRI scans were performed prior to POD for the progression cohort, and three consecutive DCE-MRI scans were performed for those with stable disease. The volume of interest (VOI) was delineated by a neuroradiologist to measure the maximum values for Ktrans and plasma volume (Vp). A Friedman test was conducted to evaluate the statistical significance of the parameter changes between scans. Results: The mean interval between subsequent scans was 57.94 days, with POD-1 representing the first scan prior to POD and POD-3 representing the third scan. The normalized maximum Vp values for POD-3, POD-2, and POD-1 are 1.40, 1.86, and 3.24, respectively (FS = 18.00, p = 0.0001). It demonstrates that Vp max values are progressively increasing in the three scans prior to POD when measured by routine MRI scans. The normalized maximum Ktrans values for POD-1, POD-2, and POD-3 are 0.51, 0.09, and 0.51, respectively (FS = 1.13, p < 0.57). Conclusions: Our analysis of the longitudinal scans leading up to POD significantly correlated with increasing plasma volume (Vp). A longitudinal study for tumor perfusion change demonstrated that DCE perfusion could be utilized as an early predictor of tumor progression.
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Affiliation(s)
- Julio Arevalo-Perez
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Radiology, Weill Medical College of Cornell University, 525 East 68th Street, New York, NY 10065, USA
| | - Andy Trang
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
| | - Elena Yllera-Contreras
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
| | - Onur Yildirim
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Radiology, Weill Medical College of Cornell University, 525 East 68th Street, New York, NY 10065, USA
| | - Atin Saha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Radiology, Weill Medical College of Cornell University, 525 East 68th Street, New York, NY 10065, USA
| | - Robert Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Radiology, Weill Medical College of Cornell University, 525 East 68th Street, New York, NY 10065, USA
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | - John Lyo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Radiology, Weill Medical College of Cornell University, 525 East 68th Street, New York, NY 10065, USA
| | - Kyung K. Peck
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | - Andrei I. Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; (A.T.); (E.Y.-C.); (O.Y.); (A.S.); (R.Y.); (K.K.P.); (A.I.H.)
- Department of Radiology, Weill Medical College of Cornell University, 525 East 68th Street, New York, NY 10065, USA
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
- Department of Neuroscience, Weill-Cornell Graduate School of the Medical Sciences, 1300 York Ave, New York, NY 10065, USA
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Conte M, Woodall RT, Gutova M, Chen BT, Shiroishi MS, Brown CE, Munson JM, Rockne RC. Structural and practical identifiability of contrast transport models for DCE-MRI. PLoS Comput Biol 2024; 20:e1012106. [PMID: 38748755 PMCID: PMC11132485 DOI: 10.1371/journal.pcbi.1012106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 05/28/2024] [Accepted: 04/24/2024] [Indexed: 05/28/2024] Open
Abstract
Contrast transport models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.
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Affiliation(s)
- Martina Conte
- Department of Mathematical Sciences “G. L. Lagrange”, Politecnico di Torino, Torino, Italy
- Division of Mathematical Oncology and Computational Systems Biology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, California, United States of America
| | - Ryan T. Woodall
- Division of Mathematical Oncology and Computational Systems Biology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, California, United States of America
| | - Margarita Gutova
- Department of Stem Cell Biology and Regenerative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, California, United States of America
| | - Bihong T. Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, California, United States of America
| | - Mark S. Shiroishi
- Department of Radiology, Keck School of Medicine of the University of Southern California, Los Angeles, California, United States of America
| | - Christine E. Brown
- Departments of Hematology & Hematopoietic Cell Transplantation and Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center Duarte, California, United States of America
| | - Jennifer M. Munson
- Fralin Biomedical Research Institute, Virginia Tech, Roanoke, Virginia, United States of America
| | - Russell C. Rockne
- Division of Mathematical Oncology and Computational Systems Biology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, California, United States of America
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Yang H, Zhu Z, Long C, Niu F, Zhou J, Chen S, Ye M, Peng S, Zhang X, Chen Y, Wei L, Wang H, Liu D, Yao M, Zhang X, Zhang B. Quantitative and Qualitative Parameters of DCE-MRI Predict CDKN2A/B Homozygous Deletion in Gliomas. Acad Radiol 2024:S1076-6332(24)00087-4. [PMID: 38443208 DOI: 10.1016/j.acra.2024.02.017] [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: 01/12/2024] [Revised: 02/05/2024] [Accepted: 02/11/2024] [Indexed: 03/07/2024]
Abstract
RATIONALE AND OBJECTIVES Homozygous deletion (HD) of CDKN2A/B holds important prognostic value in gliomas. This study aimed to explore the predictive potential of conventional MRI characteristics combined with dynamic contrast-enhanced MRI parameters in predicting CDKN2A/B HD status in gliomas. MATERIALS AND METHODS Preoperative MRI data of 105 patients (69 without CDKN2A/B HD, and 36 with CDKN2A/B homozygous deletion) with gliomas were retrospectively collected. Conventional MRI features and dynamic contrast-enhanced-MRI qualitative parameter time-intensity curve type, quantitative parameters Ktrans, Kep, Ve, Vp, and iAUC were obtained. Logistic regression models for prediction of CDKN2A/B HD status were constructed in all types of gliomas and both subtypes of IDH-mutant and IDH-wild gliomas. RESULTS Multivariate analysis for all patients demonstrated that age (OR=1.103, p = 0.002) and Ktrans (OR=1.051, p < 0.001) independently predicted CDKN2A/B HD. In IDH-mutant subgroup, multivariate analysis results indicated that Ktrans (OR=1.098, p = 0.031) emerged as autonomous predictors of CDKN2A/B HD. In IDH-wild subgroup, age (OR=1.111, p = 0.002) and Ktrans (OR=1.032, p = 0.001) were independent predictors of CDKN2A/B HD according to the multivariate analysis. The areas under the receiver operating characteristic curve of the corresponding models were 0.90, 0.95 and 0.84, respectively. CONCLUSION Ktrans can serve as valuable predictive parameters for identifying CDKN2A/B HD status in all types of gliomas and both subtypes of IDH-mutant and IDH-wild gliomas. These findings provide a foundation for precise preoperative non-invasive diagnosis and personalized treatment approaches for glioma patients.
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Affiliation(s)
- Huiquan Yang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zhengyang Zhu
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Cong Long
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Fengnan Niu
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Jianan Zhou
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Sixuan Chen
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Meiping Ye
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Siqi Peng
- School of Life Science and Technology, Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China
| | - Xue Zhang
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Ying Chen
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Liangpeng Wei
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Haoyao Wang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Dongming Liu
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Mei Yao
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Xin Zhang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
| | - Bing Zhang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China; Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China; Jiangsu Key Laboratory of Molecular Medicine, Nanjing, China; Institute of brain Science, Nanjing University, Nanjing, China
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Liguori GL. Challenges and Promise for Glioblastoma Treatment through Extracellular Vesicle Inquiry. Cells 2024; 13:336. [PMID: 38391949 PMCID: PMC10886570 DOI: 10.3390/cells13040336] [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: 12/15/2023] [Revised: 01/31/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024] Open
Abstract
Glioblastoma (GB) is a rare but extremely aggressive brain tumor that significantly impacts patient outcomes, affecting both duration and quality of life. The protocol established by Stupp and colleagues in 2005, based on radiotherapy and chemotherapy with Temozolomide, following maximum safe surgical resection remains the gold standard for GB treatment; however, it is evident nowadays that the extreme intratumoral and intertumoral heterogeneity, as well as the invasiveness and tendency to recur, of GB are not compatible with a routine and unfortunately ineffective treatment. This review article summarizes the main challenges in the search for new valuable therapies for GB and focuses on the impact that extracellular vesicle (EV) research and exploitation may have in the field. EVs are natural particles delimited by a lipidic bilayer and filled with functional cellular content that are released and uptaken by cells as key means of cell communication. Furthermore, EVs are stable in body fluids and well tolerated by the immune system, and are able to cross physiological, interspecies, and interkingdom barriers and to target specific cells, releasing inherent or externally loaded functionally active molecules. Therefore, EVs have the potential to be ideal allies in the fight against GB and to improve the prognosis for GB patients. The present work describes the main preclinical results obtained so far on the use of EVs for GB treatment, focusing on both the EV sources and molecular cargo used in the various functional studies, primarily in vivo. Finally, a SWOT analysis is performed, highlighting the main advantages and pitfalls of developing EV-based GB therapeutic strategies. The analysis also suggests the main directions to explore to realize the possibility of exploiting EVs for the treatment of GB.
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Affiliation(s)
- Giovanna L Liguori
- Institute of Genetics and Biophysics (IGB) "Adriano Buzzati-Traverso", National Research Council (CNR) of Italy, 80131 Naples, Italy
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Richter V, Nägele T, Erb G, Klose U, Ernemann U, Hauser TK. Improved diagnostic confidence and tumor type prediction in adult-type diffuse glioma by multimodal imaging including DCE perfusion and diffusion kurtosis mapping - A standardized multicenter study. Eur J Radiol 2024; 171:111293. [PMID: 38218066 DOI: 10.1016/j.ejrad.2024.111293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 01/04/2024] [Indexed: 01/15/2024]
Abstract
BACKGROUND AND PURPOSE To evaluate the feasibility of a multimodal approach involving dynamic contrast-enhanced (DCE) perfusion imaging and diffusion kurtosis imaging (DKI) in the preoperative imaging of brain tumors in a multicenter setting, and to evaluate the effect on diagnostic confidence and accuracy for tumor grade and type prediction. MATERIALS AND METHODS One hundred and thirty-three patients with brain tumors were imaged in six hospitals with a standardized multimodal protocol. Standard imaging and six parameter maps derived from DCE and DKI sequences were reviewed off-site by two independent readers. Image quality and diagnostic confidence were evaluated in qualitative analyses. Quantitative analyses were performed to assess diagnostic accuracy and the performance of DKI and DCE parameters for tumor grade differentiation and molecular tumor type determination. RESULTS Standardized acquisition of DCE and DKI maps was feasible with excellent image quality. Diagnostic confidence was significantly improved from 85 % to 96 % (p = 0.0005) by additional review of the DCE and DKI maps. The combination of mean kurtosis and CBV was particularly advantageous for differentiating low-grade and high-grade glioma, oligodendroglial vs. astrocytic, and IDH1/2 wild type vs. mutated tumors. CONCLUSION A multimodal imaging approach with DCE and DKI improves diagnostic confidence and yields higher diagnostic accuracy for predicting tumor grade and type in adult-type glioma.
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Affiliation(s)
- Vivien Richter
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Thomas Nägele
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Günther Erb
- Bracco Group, Medical and Regulatory Affairs, Konstanz, Germany.
| | - Uwe Klose
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Ulrike Ernemann
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Till-Karsten Hauser
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
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Jin B, Yang J, Zhen J, Xu Y, Wang C, Jing Q, Shang Y. Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Differentiate Between Atypical Cartilaginous Tumors and High-Grade Chondrosarcoma: Correlation With Histological Vessel Characteristics. J Comput Assist Tomogr 2024; 48:123-128. [PMID: 37558644 DOI: 10.1097/rct.0000000000001515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
OBJECTIVE To differentiate between atypical cartilaginous tumors and high-grade chondrosarcoma of the major long bones using intravoxel incoherent motion (IVIM) and Dynamic Contrast-Enhanced magnetic resonance imaging (DCE-MRI), and explore the correlation of quantitative parameters with hypoxia inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) and microvessel density (MVD). METHOD Between September 2016 and March 2022, 35 patients (17 atypical cartilaginous tumors, 18 high-grade chondrosarcoma) underwent MRI examination and pathological confirmation at our hospital. First, IVIM-derived parameters ( D , D* , and f ), and DCE-MRI parameters ( Ktrans , Kep , and V e ) were measured, and intraclass correlation efficient (ICC) and Mann-Whitney U test were performed. Second, receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance. Finally, Spearman's correlation analysis was performed between the quantitative parameters of IVIM-DWI and DCE-MRI and the immunohistochemical factors HIF-1α, VEGF, and MVD in chondrosarcoma tissue. RESULTS D in atypical cartilaginous tumors was significantly higher than that in high-grade chondrosarcoma ( P = 0.003), whereas D* , Ktrans , and K ep in atypical cartilaginous tumors were significantly lower than those in high-grade chondrosarcoma (all P < 0.001). Ktrans demonstrated the highest area under the curve (AUC) of 0.979. The D* , Ktrans , and K ep were positively correlated with HIF-1α, VEGF, and MVD (all P < 0.001), whereas D had no correlation with HIF-1α, VEGF, and MVD ( P = 0.113, 0.077, 0.058, respectively). CONCLUSION The IVIM-DWI quantitative parameters ( D , D* ) and DCE-MRI quantitative parameters ( Ktrans , Kep ) are helpful to differentiate between atypical cartilaginous tumors and high-grade chondrosarcoma and could be imaging biomarkers to reflect the expressions of HIF-1α, VEGF, and angiogenesis of chondrosarcoma.
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Affiliation(s)
- Bo Jin
- From the Department of Radiology, Children's Hospital of Shanxi
| | - Jie Yang
- Department of Radiology, Shanxi Traditional Chinese Medical Hospital
| | | | - Yang Xu
- Department of Imaging and Nuclear Medicine, College of Medical Imaging, Shanxi Medical University
| | - Chen Wang
- Department of Pathology, Shanxi Medical University Second Affiliated Hospital
| | - Qing Jing
- Department of Biochemistry and Molecular Biology, College of Basic Medicine, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yangwei Shang
- Department of Pathology, Shanxi Medical University Second Affiliated Hospital
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Conte M, Woodall RT, Gutova M, Chen BT, Shiroishi MS, Brown CE, Munson JM, Rockne RC. Structural and practical identifiability of contrast transport models for DCE-MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572294. [PMID: 38187554 PMCID: PMC10769233 DOI: 10.1101/2023.12.19.572294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Compartment models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.
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Sanvito F, Kaufmann TJ, Cloughesy TF, Wen PY, Ellingson BM. Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration. FRONTIERS IN RADIOLOGY 2023; 3:1267615. [PMID: 38152383 PMCID: PMC10751345 DOI: 10.3389/fradi.2023.1267615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, United States
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Wang J, Chen Z, Chen J. Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis. Oncol Lett 2023; 26:436. [PMID: 37664663 PMCID: PMC10472021 DOI: 10.3892/ol.2023.14023] [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: 11/30/2022] [Accepted: 07/13/2023] [Indexed: 09/05/2023] Open
Abstract
No clear conclusions have yet been reached regarding the accuracy of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade glioma (HGG) from low-grade glioma (LGG). In the present study, a meta-analysis was conducted to determine the diagnostic value of MRI radiomics in differentiating between HGG and LGG, in order to guide their clinical diagnosis. PubMed, Embase and the Cochrane Library databases were searched up to November 2022. The search included studies in which true positive, false positive, true negative and false negative values for the differentiation of HGG from LGG were reported or could be calculated by retrograde extrapolation. Duplicate publications, research without full text, studies with incomplete information or unextractable data, animal studies, reviews and systematic reviews were excluded. STATA 15.1 was used to analyze the data. The meta-analysis included 15 studies, which comprised a total of 1,124 patients, of which 701 had HGG and 423 had LGG. The pooled sensitivity and specificity of the studies overall were 0.92 (95% CI: 0.89-0.95) and 0.89 (95% CI: 0.85-0.92), respectively. The positive and negative likelihood ratios of the studies overall were 7.89 (95% CI: 6.01-10.37) and 0.09 (95% CI: 0.07-0.12), respectively. The pooled diagnostic odds ratio of the studies was 85.20 (95% CI: 54.52-133.14). The area under the summary receiver operating characteristic curve was 0.91. These findings indicate that radiomics may be an accurate tool for the differentiation of glioma grades. However, further research is needed to verify the most appropriate of these technologies.
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Affiliation(s)
- Jiefang Wang
- Department of Radiology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Zhichao Chen
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
| | - Jieyun Chen
- Department of Radiology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
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Zheng J, Dong H, Li M, Lin X, Wang C. Prediction of IDH1 gene mutation by a nomogram based on multiparametric and multiregional MR images. Clinics (Sao Paulo) 2023; 78:100238. [PMID: 37354775 DOI: 10.1016/j.clinsp.2023.100238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/19/2023] [Accepted: 06/06/2023] [Indexed: 06/26/2023] Open
Abstract
OBJECTIVE To investigate the value of a nomogram based on multiparametric and multiregional MR images to predict Isocitrate Dehydrogenase-1 (IDH1) gene mutations in glioma. DATA AND METHODS The authors performed a retrospective analysis of 110 MR images of surgically confirmed pathological gliomas; 33 patients with IDH1 gene Mutation (IDH1-M) and 77 patients with Wild-type IDH1 (IDH1-W) were divided into training and validation sets in a 7:3 ratio. The clinical features were statistically analyzed using SPSS and R software. Three glioma regions (rCET, rE, rNEC) were outlined using ITK-SNAP software and projected to four conventional sequences (T1, T2, Flair, T1C) for feature extraction using AI-Kit software. The extracted features were screened using R software. A logistic regression model was established, and a nomogram was generated using the selected clinical features. Eight models were developed based on different sequences and ROIs, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive efficacy. Decision curve analysis was performed to assess the clinical usefulness. RESULTS Age was selected with Radscore to construct the nomogram. The Model 1 AUC values based on four sequences and three ROIs were the highest in these models, at 0.93 and 0.89, respectively. Decision curve analysis indicated that the net benefit of model 1 was higher than that of the other models for most Pt-values. CONCLUSION A nomogram based on multiparametric and multiregional MR images can predict the mutation status of the IDH1 gene accurately.
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Affiliation(s)
- Jinjing Zheng
- Department of Radiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, China
| | - Haibo Dong
- Department of Radiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, China.
| | - Ming Li
- Department of Radiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, China
| | - Xueyao Lin
- Department of Radiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, China
| | - Chaochao Wang
- Department of Radiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, China
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Seo M, Choi Y, Soo Lee Y, Ahn KJ, Kim BS, Park JS, Jeon SS. Glioma grading using multiparametric MRI: head-to-head comparison among dynamic susceptibility contrast, dynamic contrast-enhancement, diffusion-weighted images, and MR spectroscopy. Eur J Radiol 2023; 165:110888. [PMID: 37257338 DOI: 10.1016/j.ejrad.2023.110888] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 05/20/2023] [Indexed: 06/02/2023]
Abstract
PURPOSE To assess the diagnostic accuracy of dynamic susceptibility contrast, dynamic contrast-enhancement, MR spectroscopy (MRS), and diffusion-weighted imaging for differentiating high-grade (HGGs) from low-grade gliomas (LGGs). METHODS Seventy-two patients (16 LGGs, 56 HGGs) with pathologically confirmed gliomas were retrospectively included. From three-dimensionally segmented tumor, histogram analyses of relative cerebral blood volume (rCBV), volume transfer constant (Ktrans), and apparent diffusion coefficient (ADC) were performed. Choline-to-creatinine ratio (Cho/Cr) was calculated using MRS. Logistic regression analyses were performed to differentiate HGGs (grade ≥ 3) from LGGs (grade ≤ 2). Areas under the receiver operating characteristics curves (AUC) were plotted. Subgroup analysis was performed between IDH-wildtype glioblastomas and IDH-mutant astrocytomas. Pairwise Spearman's correlation coefficients (ρ) were computed. RESULTS HGGs had higher 95th percentile rCBV, Ktrans and Cho/Cr (P < 0.01) than LGGs. AUC of 95th percentiles of rCBV and Ktrans were 0.79 (95% CI, 0.67-0.91) and 0.74 (95% CI, 0.59-0.88), respectively. AUC of 5th percentile of ADC was 0.63 (95% CI, 0.48-0.79), and that of Cho/Cr was 0.67 (95% CI, 0.52-0.81). IDH-wildtype glioblastomas and IDH-mutant astrocytomas showed significantly different 95th percentile rCBV (P = 0.04) and Ktrans (P < 0.01), with Ktrans showing the highest AUC (0.73, 95% CI 0.57-0.89) in IDH status prediction. Moderate correlations were observed between 95th percentile rCBV and Ktrans (ρ = 0.47), Cho/Cr (ρ = 0.40), and 5th percentile ADC (ρ = -0.36) (all P < 0.01). CONCLUSIONS The 95th percentile rCBV may be most helpful in discriminating HGGs from LGGs. The 95th percentile Ktrans may aid predicting IDH status of diffuse gliomas.
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Affiliation(s)
- Minkook Seo
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yangsean Choi
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
| | - Youn Soo Lee
- Department of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kook-Jin Ahn
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bum-Soo Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jae-Sung Park
- Department of Neurosurgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sin-Soo Jeon
- Department of Neurosurgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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Kiser K, Zhang J, Kim SG. Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution. Tomography 2023; 9:721-735. [PMID: 37104129 PMCID: PMC10141208 DOI: 10.3390/tomography9020058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 03/20/2023] [Accepted: 03/23/2023] [Indexed: 04/28/2023] Open
Abstract
This paper investigates the effect of anisotropic resolution on the image textural features of pharmacokinetic (PK) parameters of a murine glioma model using dynamic contrast-enhanced (DCE) MR images acquired with an isotropic resolution at 7T with pre-contrast T1 mapping. The PK parameter maps of whole tumors at isotropic resolution were generated using the two-compartment exchange model combined with the three-site-two-exchange model. The textural features of these isotropic images were compared with those of simulated, thick-slice, anisotropic images to assess the influence of anisotropic voxel resolution on the textural features of tumors. The isotropic images and parameter maps captured distributions of high pixel intensity that were absent in the corresponding anisotropic images with thick slices. A significant difference was observed in 33% of the histogram and textural features extracted from anisotropic images and parameter maps, compared to those extracted from corresponding isotropic images. Anisotropic images in different orthogonal orientations demonstrated 42.1% of the histogram and textural features to be significantly different from those of isotropic images. This study demonstrates that the anisotropy of voxel resolution needs to be carefully considered when comparing the textual features of tumor PK parameters and contrast-enhanced images.
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Affiliation(s)
- Karl Kiser
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065, USA
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El-Abtah ME, Murayi R, Lee J, Recinos PF, Kshettry VR. Radiological Differentiation Between Intracranial Meningioma and Solitary Fibrous Tumor/Hemangiopericytoma: A Systematic Literature Review. World Neurosurg 2023; 170:68-83. [PMID: 36403933 DOI: 10.1016/j.wneu.2022.11.062] [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: 09/03/2022] [Revised: 11/12/2022] [Accepted: 11/14/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Intracranial solitary fibrous tumor (SFT) is characterized by aggressive local behavior and high post-resection recurrence rates. It is difficult to distinguish between SFT and meningiomas, which are typically benign. The goal of this study was to systematically review radiological features that differentiate meningioma and SFT. METHODS We performed a systematic review in accordance with PRISMA guidelines to identify studies that used imaging techniques to identify radiological differentiators of SFT and meningioma. RESULTS Eighteen studies with 1565 patients (SFT: 662; meningiomas: 903) were included. The most commonly used imaging modality was diffusion weighted imaging, which was reported in 11 studies. Eight studies used a combination of diffusion weighted imaging and T1- and T2-weighted sequences to distinguish between SFT and meningioma. Compared to all grades/subtypes of meningioma, SFT is associated with higher apparent diffusion coefficient, presence of narrow-based dural attachments, lack of dural tail, less peritumoral brain edema, extensive serpentine flow voids, and younger age at initial diagnosis. Tumor volume was a poor differentiator of SFT and meningioma, and overall, there were less consensus findings in studies exclusively comparing angiomatous meningiomas and SFT. CONCLUSIONS Clinicians can differentiate SFT from meningiomas on preoperative imaging by looking for higher apparent diffusion coefficient, lack of dural tail/narrow-based dural attachment, less peritumoral brain edema, and vascular flow voids on neuroimaging, in addition to younger age at diagnosis. Distinguishing between angiomatous meningioma and SFT is much more challenging, as both are highly vascular pathologies. Tumor volume has limited utility in differentiating between SFT and various grades/subtypes of meningioma.
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Affiliation(s)
- Mohamed E El-Abtah
- Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Roger Murayi
- Department of Neurological Surgery, Cleveland Clinic, Cleveland, Ohio, USA
| | - Jonathan Lee
- Department of Radiology, Cleveland Clinic, Cleveland, Ohio, USA
| | - Pablo F Recinos
- Department of Neurological Surgery and Rosa Ella Burkhardt Brain Tumor & Neuro-Oncology Center, Cleveland Clinic, Cleveland, Ohio, USA; Cleveland Clinic Lerner College of Medicine, Cleveland, Ohio, USA
| | - Varun R Kshettry
- Department of Neurological Surgery and Rosa Ella Burkhardt Brain Tumor & Neuro-Oncology Center, Cleveland Clinic, Cleveland, Ohio, USA; Cleveland Clinic Lerner College of Medicine, Cleveland, Ohio, USA.
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15
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Bailo M, Pecco N, Callea M, Scifo P, Gagliardi F, Presotto L, Bettinardi V, Fallanca F, Mapelli P, Gianolli L, Doglioni C, Anzalone N, Picchio M, Mortini P, Falini A, Castellano A. Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study. Front Neurosci 2022; 16:885291. [PMID: 35911979 PMCID: PMC9326318 DOI: 10.3389/fnins.2022.885291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundTumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging.ObjectivesThis study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity.Materials and MethodsSeventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats’ spatial distribution, quantitative features and histopathological characteristics were analyzed.ResultsA highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed.ConclusionPreliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.
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Affiliation(s)
- Michele Bailo
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Nicolò Pecco
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Paola Scifo
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Filippo Gagliardi
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luca Presotto
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Federico Fallanca
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paola Mapelli
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luigi Gianolli
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Nicoletta Anzalone
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria Picchio
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Pietro Mortini
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Antonella Castellano
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Antonella Castellano,
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Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
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Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
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Kouwenberg V, van Santwijk L, Meijer FJA, Henssen D. Reliability of dynamic susceptibility contrast perfusion metrics in pre- and post-treatment glioma. Cancer Imaging 2022; 22:28. [PMID: 35715866 PMCID: PMC9205029 DOI: 10.1186/s40644-022-00466-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/26/2022] [Indexed: 11/26/2022] Open
Abstract
Background In neuro-oncology, dynamic susceptibility contrast magnetic resonance (DSC-MR) perfusion imaging emerged as a tool to aid in the diagnostic work-up and to surveil effectiveness of treatment. However, it is believed that a significant variability exists with regard to the measured in DSC-MR perfusion parameters. The aim of this study was to assess the observer variability in measured DSC-MR perfusion parameters in patients before and after treatment. In addition, we investigated whether region-of-interest (ROI) shape impacted the observer variability. Materials and methods Twenty non-treated patients and a matched group of twenty patients post-treatment (neurosurgical resection and post-chemoradiotherapy) were included. Six ROIs were independently placed by three readers: circular ROIs and polygonal ROIs covering 1) the tumor hotspot; 2) the peritumoral region (T2/FLAIR-hyperintense region) and 3) the whole tumor region. A two-way random Intra-class coefficient (ICC) model was used to assess variability in measured DSC-MRI perfusion parameters. The perfusion metrics as assessed by the circular and the polygonal ROI were compared by use of the dependent T-test. Results In the non-treated group, circular ROIs showed good–excellent overlap (ICC-values ranging from 0.741–0.963) with the exception of those representing the tumor hotspot. Polygonal ROIs showed lower ICC-values, ranging from 0.113 till 0.856. ROI-placement in the posttreatment group showed to be highly variable with a significant deterioration of ICC-values. Furthermore, perfusion metric assessment in similar tumor regions was not impacted by ROI shape. Discussion This study shows that posttreatment quantitative interpretation of DSC-MR perfusion imaging is highly variable and should be carried out with precaution. Pretreatment assessment of DSC-MR images, however, could be carried out be a single reader in order to provide valid data for further analyses. • DSC-MR perfusion imaging measurements in non-treated glioma is highly reliable between readers, even readers with little experience. • DSC-MR perfusion imaging measurements in treated glioma is show to be inconsistent between readers. • When using DSC-MR perfusion imaging as a quantitative surveillance tool for the recurrence of glioma after treatment, double-reading should be preferred.
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Affiliation(s)
- Valentina Kouwenberg
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Lusien van Santwijk
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands.
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Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading. Cancers (Basel) 2022; 14:cancers14061432. [PMID: 35326580 PMCID: PMC8946242 DOI: 10.3390/cancers14061432] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/08/2022] [Indexed: 11/17/2022] Open
Abstract
Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.
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19
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Albano D, Bruno F, Agostini A, Angileri SA, Benenati M, Bicchierai G, Cellina M, Chianca V, Cozzi D, Danti G, De Muzio F, Di Meglio L, Gentili F, Giacobbe G, Grazzini G, Grazzini I, Guerriero P, Messina C, Micci G, Palumbo P, Rocco MP, Grassi R, Miele V, Barile A. Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging. Jpn J Radiol 2021; 40:341-366. [PMID: 34951000 DOI: 10.1007/s11604-021-01223-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 11/17/2021] [Indexed: 12/18/2022]
Abstract
Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.
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Affiliation(s)
- Domenico Albano
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- IRCCS Istituto Ortopedico Galeazzi, Milan, Italy
- Dipartimento Di Biomedicina, Neuroscienze E Diagnostica Avanzata, Sezione Di Scienze Radiologiche, Università Degli Studi Di Palermo, via Vetoio 1L'Aquila, 67100, Palermo, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy.
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
| | - Andrea Agostini
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Clinical, Special and Dental Sciences, Department of Radiology, University Politecnica delle Marche, University Hospital "Ospedali Riuniti Umberto I - G.M. Lancisi - G. Salesi", Ancona, Italy
| | - Salvatore Alessio Angileri
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Radiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimo Benenati
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Dipartimento di Diagnostica per Immagini, Fondazione Policlinico Universitario A. Gemelli IRCCS, Oncologia ed Ematologia, RadioterapiaRome, Italy
| | - Giulia Bicchierai
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Michaela Cellina
- Department of Radiology, ASST Fatebenefratelli Sacco, Ospedale Fatebenefratelli, Milan, Italy
| | - Vito Chianca
- Ospedale Evangelico Betania, Naples, Italy
- Clinica Di Radiologia, Istituto Imaging Della Svizzera Italiana - Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Diletta Cozzi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Emergency Radiology, Careggi University Hospital, Florence, Italy
| | - Ginevra Danti
- Department of Emergency Radiology, Careggi University Hospital, Florence, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | - Letizia Di Meglio
- Postgraduation School in Radiodiagnostics, University of Milan, Milan, Italy
| | - Francesco Gentili
- Unit of Diagnostic Imaging, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Giuliana Giacobbe
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Giulia Grazzini
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Irene Grazzini
- Department of Radiology, Section of Neuroradiology, San Donato Hospital, Arezzo, Italy
| | - Pasquale Guerriero
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | | | - Giuseppe Micci
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Dipartimento Di Biomedicina, Neuroscienze E Diagnostica Avanzata, Sezione Di Scienze Radiologiche, Università Degli Studi Di Palermo, via Vetoio 1L'Aquila, 67100, Palermo, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Abruzzo Health Unit 1, Department of diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, L'Aquila, Italy
| | - Maria Paola Rocco
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Roberto Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Antonio Barile
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
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Drug Repurposing for Glioblastoma and Current Advances in Drug Delivery-A Comprehensive Review of the Literature. Biomolecules 2021; 11:biom11121870. [PMID: 34944514 PMCID: PMC8699739 DOI: 10.3390/biom11121870] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 11/19/2021] [Accepted: 12/03/2021] [Indexed: 12/22/2022] Open
Abstract
Glioblastoma (GBM) is the most common primary malignant brain tumor in adults with an extremely poor prognosis. There is a dire need to develop effective therapeutics to overcome the intrinsic and acquired resistance of GBM to current therapies. The process of developing novel anti-neoplastic drugs from bench to bedside can incur significant time and cost implications. Drug repurposing may help overcome that obstacle. A wide range of drugs that are already approved for clinical use for the treatment of other diseases have been found to target GBM-associated signaling pathways and are being repurposed for the treatment of GBM. While many of these drugs are undergoing pre-clinical testing, others are in the clinical trial phase. Since GBM stem cells (GSCs) have been found to be a main source of tumor recurrence after surgery, recent studies have also investigated whether repurposed drugs that target these pathways can be used to counteract tumor recurrence. While several repurposed drugs have shown significant efficacy against GBM cell lines, the blood–brain barrier (BBB) can limit the ability of many of these drugs to reach intratumoral therapeutic concentrations. Localized intracranial delivery may help to achieve therapeutic drug concentration at the site of tumor resection while simultaneously minimizing toxicity and side effects. These strategies can be considered while repurposing drugs for GBM.
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21
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Assessing the reproducibility of high temporal and spatial resolution dynamic contrast-enhanced magnetic resonance imaging in patients with gliomas. Sci Rep 2021; 11:23217. [PMID: 34853347 PMCID: PMC8636480 DOI: 10.1038/s41598-021-02450-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/23/2021] [Indexed: 11/11/2022] Open
Abstract
Temporal and spatial resolution of dynamic contrast-enhanced MR imaging (DCE-MRI) is critical to reproducibility, and the reproducibility of high-resolution (HR) DCE-MRI was evaluated. Thirty consecutive patients suspected to have brain tumors were prospectively enrolled with written informed consent. All patients underwent both HR-DCE (voxel size, 1.1 × 1.1 × 1.1 mm3; scan interval, 1.6 s) and conventional DCE (C-DCE; voxel size, 1.25 × 1.25 × 3.0 mm3; scan interval, 4.0 s) MRI. Regions of interests (ROIs) for enhancing lesions were segmented twice in each patient with glioblastoma (n = 7) to calculate DCE parameters (Ktrans, Vp, and Ve). Intraclass correlation coefficients (ICCs) of DCE parameters were obtained. In patients with gliomas (n = 25), arterial input functions (AIFs) and DCE parameters derived from T2 hyperintense lesions were obtained, and DCE parameters were compared according to WHO grades. ICCs of HR-DCE parameters were good to excellent (0.84–0.95), and ICCs of C-DCE parameters were moderate to excellent (0.66–0.96). Maximal signal intensity and wash-in slope of AIFs from HR-DCE MRI were significantly greater than those from C-DCE MRI (31.85 vs. 7.09 and 2.14 vs. 0.63; p < 0.001). Both 95th percentile Ktrans and Ve from HR-DCE and C-DCE MRI could differentiate grade 4 from grade 2 and 3 gliomas (p < 0.05). In conclusion, HR-DCE parameters generally showed better reproducibility than C-DCE parameters, and HR-DCE MRI provided better quality of AIFs.
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Using of Laplacian Re-decomposition image fusion algorithm for glioma grading with SWI, ADC, and FLAIR images. POLISH JOURNAL OF MEDICAL PHYSICS AND ENGINEERING 2021. [DOI: 10.2478/pjmpe-2021-0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Abstract
Introduction: Based on the tumor’s growth potential and aggressiveness, glioma is most often classified into low or high-grade groups. Traditionally, tissue sampling is used to determine the glioma grade. The aim of this study is to evaluate the efficiency of the Laplacian Re-decomposition (LRD) medical image fusion algorithm for glioma grading by advanced magnetic resonance imaging (MRI) images and introduce the best image combination for glioma grading.
Material and methods: Sixty-one patients (17 low-grade and 44 high-grade) underwent Susceptibility-weighted image (SWI), apparent diffusion coefficient (ADC) map, and Fluid attenuated inversion recovery (FLAIR) MRI imaging. To fuse different MRI image, LRD medical image fusion algorithm was used. To evaluate the effectiveness of LRD in the classification of glioma grade, we compared the parameters of the receiver operating characteristic curve (ROC).
Results: The average Relative Signal Contrast (RSC) of SWI and ADC maps in high-grade glioma are significantly lower than RSCs in low-grade glioma. No significant difference was detected between low and high-grade glioma on FLAIR images. In our study, the area under the curve (AUC) for low and high-grade glioma differentiation on SWI and ADC maps were calculated at 0.871 and 0.833, respectively.
Conclusions: By fusing SWI and ADC map with LRD medical image fusion algorithm, we can increase AUC for low and high-grade glioma separation to 0.978. Our work has led us to conclude that, by fusing SWI and ADC map with LRD medical image fusion algorithm, we reach the highest diagnostic accuracy for low and high-grade glioma differentiation and we can use LRD medical fusion algorithm for glioma grading.
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23
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Panara V, Chiacchiaretta P, Rapino M, Maruotti V, Parenti M, Piccirilli E, Pizzi AD, Caulo M. Dynamic susceptibility MR perfusion imaging of the brain: not a question of contrast agent molarity. Neuroradiology 2021; 64:685-692. [PMID: 34557937 DOI: 10.1007/s00234-021-02807-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 09/10/2021] [Indexed: 11/29/2022]
Abstract
PURPOSE Dynamic susceptibility contrast (DSC) perfusion-weighted MR imaging (PWI) is increasingly used in clinical neuroimaging for a range of conditions. More highly concentrated GBCAs (e.g., gadobutrol) are often preferred for DSC imaging because it is thought that more Gd is present in the volume of interest during first pass for a given equivalent injection rate. However, faster injection of a less viscous GBCA (e.g., gadoteridol) might generate a more compact and narrower contrast bolus thus obviating any perceived benefit of higher Gd concentration. This preliminary study aimed to analyze and compare DSC examinations in the healthy brain hemisphere of patients with brain tumors using gadobutrol and gadoteridol administered at injection rates of 4 and 6 mL/s. METHODS Thirty-nine brain tumor patients studied with DSC-PWI were evaluated. A simplified gamma-variate model function was applied to calculate the mean peak, area under the curve (AUC), and full-width at half-maximum (FHWM) of concentration-time curves derived from ΔR2* signals at four different regions-of-interest (ROIs). Qualitative assessment of the derived CBV maps was also performed independently by 2 neuroradiologists. RESULTS No qualitative or quantitative differences between the two GBCAs were observed when administered at a flow rate of 4 mL/s. At a flow rate of 6 mL/s, gadoteridol showed lower FWHM values. CONCLUSION Gadobutrol and gadoteridol are equivalent for clinical assessment of qualitative CBV maps and quantitative perfusion parameters (FHWM) at a flow rate of 4 mL/s. At 6 mL/s, gadoteridol produces a narrower bolus shape and potentially improves quantitative assessment of perfusion parameters.
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Affiliation(s)
- Valentina Panara
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy. .,ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy.
| | - Piero Chiacchiaretta
- Department of Psychological, Health and Territory Sciences, University "G. D'Annunzio" of Chieti, Pescara, Italy.,Center for Advanced Studies and Technology (CAST), University "G. D'Annunzio" of Chieti, Pescara, Italy
| | - Matteo Rapino
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Valerio Maruotti
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Matteo Parenti
- ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy
| | - Eleonora Piccirilli
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Andrea Delli Pizzi
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Massimo Caulo
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
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24
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Azab MA, Ghozy S, Hassanein SF, Azzam AY. Specific Preoperative Dynamic Contrast-Enhanced MRI Semi-quantitative Markers Can Correlate With Vascularity in Specific Areas of Glioblastoma Tissue and Predict Recurrence. Cureus 2021; 13:e15528. [PMID: 34277164 PMCID: PMC8269995 DOI: 10.7759/cureus.15528] [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] [Accepted: 06/08/2021] [Indexed: 11/25/2022] Open
Abstract
Background: Glioblastoma is one of the most aggressive tumours despite all advanced therapies. We aimed to investigate the correlation between qualitative markers of dynamic contrast-enhanced magnetic resonance imaging and vascularity in different tumour regions and elucidate their potential in predicting recurrence. Methods: Radiological markers of vascularity as wash-in rate, washout rate, and capillary time to peak in different single tumour regions were extracted for all glioblastoma patients before being surgically resected using preoperative dynamic contrast-enhanced MRI (DCE-MRI). Tissue samples were obtained from different intratumoral regions and peritumoral oedema and evaluated for the vascular endothelial growth factor (VEGF). Results: Two hundred sixty individuals were included in the final analysis, with 180 dead ones and 80 survivors. Radio- and chemo-therapy were received by all surviving patients and 77.8% (n= 140) of the dead ones. The mean time to peak, in seconds, was longest at the peritumoral oedema region (71.7±23.5), followed by the tumour's necrotic centre (50.0±28.5) and its periphery (2.9±1.8). The expression of VEGF at the peritumoral edema region was inversely correlated to the washout rate at the periphery (r= -0.66; P-value= 0.014) and positively correlated to peritumoral TTP (r= 0.94; P-value< 0.001). Conclusion: Using DCE-MRI, VEGF expression may be used as a non-invasive marker to estimate tumour grade for clinical diagnosis and treatment. Moreover, the risk of glioblastoma recurrence could be determined by evaluating the washout rate at the tumour's periphery. Further large-scale studies are needed to validate the results and to have concrete evidence.
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Affiliation(s)
- Mohammed A Azab
- Department of Biochemistry, Boise State University, Boise, USA.,Neurological Surgery, Cairo University Hospital, Cairo, EGY
| | - Sherief Ghozy
- Neurological Surgery, Faculty of Medicine, Mansoura University, Mansoura, EGY
| | | | - Ahmed Y Azzam
- Neurological Surgery, October 6 University, 6th of October City, EGY
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25
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Patel B, Yang PH, Kim AH. The effect of thermal therapy on the blood-brain barrier and blood-tumor barrier. Int J Hyperthermia 2021; 37:35-43. [PMID: 32672118 DOI: 10.1080/02656736.2020.1783461] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The blood-brain and blood-tumor barriers represent highly specialized structures responsible for tight regulation of molecular transit into the central nervous system. Under normal circumstances, the relative impermeability of the blood-brain barrier (BBB) protects the brain from circulating toxins and contributes to a brain microenvironment necessary for optimal neuronal function. However, in the context of tumors and other diseases of central nervous system, the BBB and the more recently appreciated blood-tumor barrier (BTB) represent barriers that prevent effective drug delivery. Overcoming both barriers to optimize treatment of central nervous system diseases remains the subject of intense scientific investigation. Although many newer technologies have been developed to overcome these barriers, thermal therapy, which dates back to the 1890 s, has been known to disrupt the BBB since at least the early 1980s. Recently, as a result of several technological advances, laser interstitial thermal therapy (LITT), a method of delivering targeted thermal therapy, has gained widespread use as a surgical technique to ablate brain tumors. In addition, accumulating evidence indicates that laser ablation may also increase local BBB/BTB permeability after treatment. We herein review the structure and function of the BBB and BTB and the impact of thermal injury, including LITT, on barrier function.
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Affiliation(s)
- Bhuvic Patel
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Peter H Yang
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Albert H Kim
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
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26
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Zhang L, Yang LQ, Wen L, Lv SQ, Hu JH, Li QR, Xu JP, Xu RF, Zhang D. Noninvasively Evaluating the Grading of Glioma by Multiparametric Magnetic Resonance Imaging. Acad Radiol 2021; 28:e137-e146. [PMID: 32417035 DOI: 10.1016/j.acra.2020.03.035] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 03/22/2020] [Accepted: 03/22/2020] [Indexed: 11/25/2022]
Abstract
RATIONALE AND OBJECTIVE To investigate the performance of multi-parametric magnetic resonance imaging (MRI) for glioma grading. MATERIALS AND METHODS Seventy consecutive patients with histopathologically confirmed glioma were retrospectively evaluated by conventional MRI, dynamic susceptibility-weighted contrast-enhanced, multiple diffusion-weighted imaging signal models including mono-exponential, bi-exponential, stretched exponential, and diffusion kurtosis imaging. One-way analysis of variance and independent-samples t test were used to compare the MR parameter values between low and high grades as well as among all grades of glioma. Receiver operating characteristic analysis, Spearman's correlation analysis, and binary logistic regression analysis were used to assess their diagnostic performance. RESULTS The diagnostic performance (the optimal thresholds, area under the receiver operating characteristic curve, sensitivity, and specificity) was achieved with normalized relative cerebral blood flow (rCBV) (2.240 ml/100 g, 0.844, 87.8%, and 75.9%, respectively), mean kurtosis (MK) (0.471, 0.873, 92.7%, and 79.3%), and water molecular diffusion heterogeneity index (α) (1.064, 0.847, 79.3% and 78.0%) for glioma grading. There were positive correlations between rCBV and MK and the tumor grades and negative correlations between α and the tumor grades (p < 0.01). The parameter of α yielded a diagnostic accuracy of 85.3%, the combination of MK and α yielded a diagnostic accuracy of 89.7%, while the combination of rCBV, MK, and α were more accurate (94.2%) in predicting tumor grade. CONCLUSION The most accurate parameters were rCBV, MK, and α in dynamic susceptibility-weighted contrast, diffusion kurtosis imaging, and Multi-b diffusion-weighted imaging for glioma grading, respectively. Multiparametric MRI can increase the accuracy of glioma grading.
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Guo L, Li X, Cao H, Hua J, Mei Y, Pillai JJ, Wu Y. Inflow-based vascular-space-occupancy (iVASO) might potentially predict IDH mutation status and tumor grade in diffuse cerebral gliomas. J Neuroradiol 2021; 49:267-274. [PMID: 33482231 DOI: 10.1016/j.neurad.2021.01.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 12/13/2020] [Accepted: 01/11/2021] [Indexed: 02/08/2023]
Abstract
PURPOSE The aim of the study is to assess the diagnostic performance of inflow-based vascular-space-occupancy (iVASO) MR imaging for differentiating glioblastomas (grade IV, GBM) and lower-grade diffuse gliomas (grade II and III, LGG) and its potential to predict IDH mutation status. METHODS One hundred and two patients with diffuse cerebral glioma (56 males; median age, 43.5 years) underwent iVASO and dynamic susceptibility contrast (DSC) MR imaging. The iVASO-derived arteriolar cerebral blood volume (CBVa), relative CBVa (rCBVa), and the DSC-derived relative cerebral blood volume (rCBV) were obtained, and these measurements were compared between the GBM group (n = 43) and the LGG group (n = 59) and between the IDH-mutation group (n = 54) and the IDH-wild group (n = 48). RESULTS Significant correlation was observed between rCBV and CBVa (P < 0.001) or rCBVa (P < 0.001). Both CBVa (P < 0.001) and rCBVa (P < 0.001) were higher in the GBM group. Both CBVa (P < 0.001) and rCBVa (P < 0.001) were lower in the IDH-mutation group compared to the IDH-wild group. Receiver operating characteristic analyses showed the area under curve (AUC) of 0.95 with CBVa and 0.97 with rCBVa in differentiating GBM from LGG. The AUCs were 0.82 and 0.85 for CBVa and rCBVa in predicting IDH gene status, respectively, which were lower than that of rCBV (AUC = 0.90). Combined rCBV and rCBVa significantly improved the diagnostic performance (AUC = 0.95). CONCLUSIONS iVASO MR imaging has the potential to predict IDH mutation and grade in glioma.
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Affiliation(s)
- Liuji Guo
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, PR China
| | - Xiaodan Li
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, PR China
| | - Haimei Cao
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, PR China
| | - Jun Hua
- Neurosection, Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Yingjie Mei
- China International Center, Philips Healthcare, Guangzhou, PR China
| | - Jay J Pillai
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yuankui Wu
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
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28
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Ohba S, Murayama K, Kuwahara K, Pareira ES, Nakae S, Nishiyama Y, Adachi K, Yamada S, Sasaki H, Yamamoto N, Abe M, Mukherjee J, Hasegawa M, Pieper RO, Hirose Y. The Correlation of Fluorescence of Protoporphyrinogen IX and Status of Isocitrate Dehydrogenase in Gliomas. Neurosurgery 2021; 87:408-417. [PMID: 31833548 DOI: 10.1093/neuros/nyz524] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 10/01/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND The extent of resection has been reported to be associated with overall survival in gliomas. The use of 5-aminolevulinic acid (5-ALA) has been recognized to increase the extent of tumor resection. OBJECTIVE To evaluate what factors affect the intraoperative fluorescence after administration of 5-ALA in gliomas. METHODS Correlation of intraoperative fluorescence and several clinical, radiographic, molecular biologic, and histopathologic characters was retrospectively evaluated in 104 patients (53 males and 51 females; mean age 54.2 yr) with gliomas at our institution. To clarify the mechanisms that mutant isocitrate dehydrogenase (IDH) affect the intraoperative fluorescence, in Vitro experiments using genetically engineered glioma cells harboring mutant IDH1 were performed. RESULTS Intraoperative fluorescence was observed in 82 patients (78.8%). In addition to age, magnetic resonance imaging enhancement, World Health Organization grades, and MIB-1 index, the status of IDH was revealed to be correlated with intraoperative fluorescence. In Vitro assay revealed that mutant IDH indirectly reduced the amount of exogenous 5-ALA-derived protoporphyrinogen IX in glioma cells by increasing activity of ferrochelatase and heme oxygenase 1. CONCLUSION Mutant IDH1/2-induced metabolite changes of exogenous 5-ALA were suggested to contribute to the lesser intraoperative fluorescence in gliomas with mutant IDH1/2 than in those without.
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Affiliation(s)
- Shigeo Ohba
- Department of Neurosurgery, Fujita Health University, Toyoake, Japan
| | | | - Kiyonori Kuwahara
- Department of Neurosurgery, Fujita Health University, Toyoake, Japan
| | | | - Shunsuke Nakae
- Department of Neurosurgery, Fujita Health University, Toyoake, Japan
| | - Yuya Nishiyama
- Department of Neurosurgery, Fujita Health University, Toyoake, Japan
| | - Kazuhide Adachi
- Department of Neurosurgery, Fujita Health University, Toyoake, Japan
| | - Seiji Yamada
- Department of Pathology, Fujita Health University, Toyoake, Japan
| | - Hikaru Sasaki
- Department of Neurosurgery, Keio University School of Medicine, Tokyo, Japan
| | - Naoki Yamamoto
- Laboratory of Molecular Biology, Fujita Health University Institute of Joint Research, Toyoake, Japan
| | - Masato Abe
- Department of Pathology, School of Health Sciences, Fujita Health University, Toyoake, Japan
| | - Joydeep Mukherjee
- Department of Neurological Surgery, UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California
| | | | - Russell O Pieper
- Department of Neurological Surgery, UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California
| | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University, Toyoake, Japan
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Lu D, Li Y, Lu H, Pillai JJ. Histogram-based analysis of cerebral blood flow using arterial spin labeling MRI in de novo brain gliomas: relationship to histopathologic grade and molecular markers. Neuroradiology 2021; 63:751-760. [PMID: 33392733 DOI: 10.1007/s00234-020-02625-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/14/2020] [Indexed: 01/12/2023]
Abstract
PURPOSE We developed multiple histogram-based CBF indices and evaluated their association with histopathologic grade in de novo brain tumor patients. Furthermore, the associations between these advanced CBF indices and molecular markers, including IDH1 mutation, ATRX loss, and 1p/19q co-deletion were also investigated. METHODS Thirteen de novo brain tumor patients (age 21-68 years, 9 M/4F) who were enrolled in our prospective study were scanned on 3 T MRI using a pCASL perfusion sequence following IRB-approved written informed consent. All patients have since undergone surgical intervention with tissue sampling for histopathologic tumor grading and molecular marker assessment. Tumor region of interest (ROI) were manually delineated on FLAIR images including the full extent of the tumor and peritumoral edema. Fourteen rCBF indices were derived from the histogram of the voxels with the ROI. Multi-linear regression was then used to compare rCBF indices with histopathologic tumor grade and molecular markers. RESULTS Averaged rCBF in top 10 and top 20 voxels (p < 0.004), but not the entire tumor ROI, was positively associated with WHO tumor grade. After accounting for tumor grade, the presence of 1p/19q co-deletion was associated with higher rCBF in top voxels, as well as with standard deviation of rCBF in the tumor ROI (p < 0.001). ATRX retention was related to higher rCBF, and this effect appears to be present in both higher-perfusion (p < 0.004) and low-perfusion (p < 0.05) voxels. IDH mutation was not significantly associated with any of the CBF indices investigated. CONCLUSION ASL MRI may provide useful supplemental noninvasive imaging assessment of brain tumor grade and molecular marker status.
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Affiliation(s)
- David Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yang Li
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Jay J Pillai
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Blood-Brain Barrier Modulation to Improve Glioma Drug Delivery. Pharmaceutics 2020; 12:pharmaceutics12111085. [PMID: 33198244 PMCID: PMC7697580 DOI: 10.3390/pharmaceutics12111085] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 11/09/2020] [Accepted: 11/10/2020] [Indexed: 02/07/2023] Open
Abstract
The blood-brain barrier (BBB) is formed by brain microvascular endothelial cells that are sealed by tight junctions, making it a significant obstacle for most brain therapeutics. The poor BBB penetration of newly developed therapeutics has therefore played a major role in limiting their clinical success. A particularly challenging therapeutic target is glioma, which is the most frequently occurring malignant brain tumor. Thus, to enhance therapeutic uptake in tumors, researchers have been developing strategies to modulate BBB permeability. However, most conventional BBB opening strategies are difficult to apply in the clinical setting due to their broad, non-specific modulation of the BBB, which can result in damage to normal brain tissue. In this review, we have summarized strategies that could potentially be used to selectively and efficiently modulate the tumor BBB for more effective glioma treatment.
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Soliman MA, Guccione J, Reiter AM, Moawad AW, Etchison A, Kamel S, Khatchikian AD, Elsayes KM. Current Concepts in Multi-Modality Imaging of Solid Tumor Angiogenesis. Cancers (Basel) 2020; 12:cancers12113239. [PMID: 33153067 PMCID: PMC7692820 DOI: 10.3390/cancers12113239] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 10/15/2020] [Accepted: 10/19/2020] [Indexed: 12/11/2022] Open
Abstract
Simple Summary The recent increase in the use of targeted molecular therapy including anti-angiogenetic agents in cancer treatment necessitate the use of robust tools to assess and guide treatment. Angiogenesis, the formation of new disorganized blood vessels, is used by tumor cells to grow and spread using different mechanisms that could be targeted by anti-angiogenetic agents. In this review, we discuss the biological principles of tumor angiogenesis and the imaging modalities that could provide information beyond gross tumor size and morphology to capture the efficacy of anti-angiogenetic therapeutic response. Abstract There have been rapid advancements in cancer treatment in recent years, including targeted molecular therapy and the emergence of anti-angiogenic agents, which necessitate the need to quickly and accurately assess treatment response. The ideal tool is robust and non-invasive so that the treatment can be rapidly adjusted or discontinued based on efficacy. Since targeted therapies primarily affect tumor angiogenesis, morphological assessment based on tumor size alone may be insufficient, and other imaging modalities and features may be more helpful in assessing response. This review aims to discuss the biological principles of tumor angiogenesis and the multi-modality imaging evaluation of anti-angiogenic therapeutic responses.
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Affiliation(s)
- Moataz A. Soliman
- Department of Diagnostic Radiology, Northwestern University, Evanston, IL 60201, USA;
| | - Jeffrey Guccione
- Department of Diagnostic and Interventional Imaging, The University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA;
| | - Anna M. Reiter
- School of Medicine, University of Texas Southwestern, Dallas, TX 75390, USA;
| | - Ahmed W. Moawad
- Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA;
| | - Ashley Etchison
- Department of Diagnostic Radiology, Baylor College of Medicine, Houston, TX 76798, USA;
| | - Serageldin Kamel
- Department of Lymphoma and Myeloma, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA;
| | - Aline D. Khatchikian
- Department of Diagnostic Radiology, McGill University, Montreal, QC H3G 1A4, Canada;
| | - Khaled M. Elsayes
- Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA;
- Correspondence:
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Luan J, Wu M, Wang X, Qiao L, Guo G, Zhang C. The diagnostic value of quantitative analysis of ASL, DSC-MRI and DKI in the grading of cerebral gliomas: a meta-analysis. Radiat Oncol 2020; 15:204. [PMID: 32831106 PMCID: PMC7444047 DOI: 10.1186/s13014-020-01643-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 08/12/2020] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE To perform quantitative analysis on the efficacy of using relative cerebral blood flow (rCBF) in arterial spin labeling (ASL), relative cerebral blood volume (rCBV) in dynamic magnetic sensitivity contrast-enhanced magnetic resonance imaging (DSC-MRI), and mean kurtosis (MK) in diffusion kurtosis imaging (DKI) to grade cerebral gliomas. METHODS Literature regarding ASL, DSC-MRI, or DKI in cerebral gliomas grading in both English and Chinese were searched from PubMed, Embase, Web of Science, CBM, China National Knowledge Infrastructure (CNKI), and Wanfang Database as of 2019. A meta-analysis was performed to evaluate the efficacy of ASL, DSC-MRI, and DKI in the grading of cerebral gliomas. RESULT A total of 54 articles (11 in Chinese and 43 in English) were included. Three quantitative parameters in the grading of cerebral gliomas, rCBF in ASL, rCBV in DSC-MRI, and MK in DKI had the pooled sensitivity of 0.88 [95% CI (0.83,0.92)], 0.92 [95% CI (0.83,0.96)], 0.88 [95% CI (0.82,0.92)], and the pooled specificity of 0.91 [95% CI (0.84,0.94)], 0.81 [95% CI (0.73,0.88)], 0.86 [95% CI (0.78,0.91)] respectively. The pooled area under the curve (AUC) were 0.95 [95% CI (0.93,0.97)], 0.91 [95% CI (0.89,0.94)], 0.93 [95% CI (0.91,0.95)] respectively. CONCLUSION Quantitative parameters rCBF, rCBV and MK have high diagnostic accuracy for preoperative grading of cerebral gliomas.
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Affiliation(s)
- Jixin Luan
- Department of Radiology, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, 67, Dongchang West Road, Liaocheng District, 252000, Shandong Province, China
| | - Mingzhen Wu
- Department of Radiology, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, 67, Dongchang West Road, Liaocheng District, 252000, Shandong Province, China
| | - Xiaohui Wang
- Department of Science and Education, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, 67, Dongchang West Road, Liaocheng District, 252000, Shandong Province, China
| | - Lishan Qiao
- School of Mathematics, Liaocheng University, Liaocheng District, 252000, Shandong Province, China
| | - Guifang Guo
- Department of Radiology, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, 67, Dongchang West Road, Liaocheng District, 252000, Shandong Province, China
| | - Chuanchen Zhang
- Department of Radiology, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, 67, Dongchang West Road, Liaocheng District, 252000, Shandong Province, China.
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Sanders JW, Chen HSM, Johnson JM, Schomer DF, Jimenez JE, Ma J, Liu HL. Synthetic generation of DSC-MRI-derived relative CBV maps from DCE MRI of brain tumors. Magn Reson Med 2020; 85:469-479. [PMID: 32726488 DOI: 10.1002/mrm.28432] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 06/21/2020] [Accepted: 06/24/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. METHODS One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. RESULTS Pearson correlation analysis showed that both the tumor rCBV and tumor-to-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. CONCLUSION Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.
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Affiliation(s)
- Jeremiah W Sanders
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Medical Physics Graduate Program, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
| | - Henry Szu-Meng Chen
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason M Johnson
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Donald F Schomer
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jorge E Jimenez
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Medical Physics Graduate Program, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Sudre CH, Panovska-Griffiths J, Sanverdi E, Brandner S, Katsaros VK, Stranjalis G, Pizzini FB, Ghimenton C, Surlan-Popovic K, Avsenik J, Spampinato MV, Nigro M, Chatterjee AR, Attye A, Grand S, Krainik A, Anzalone N, Conte GM, Romeo V, Ugga L, Elefante A, Ciceri EF, Guadagno E, Kapsalaki E, Roettger D, Gonzalez J, Boutelier T, Cardoso MJ, Bisdas S. Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status. BMC Med Inform Decis Mak 2020; 20:149. [PMID: 32631306 PMCID: PMC7336404 DOI: 10.1186/s12911-020-01163-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 06/24/2020] [Indexed: 12/15/2022] Open
Abstract
Background Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied to dynamic susceptibility contrast (DSC)-MRI in classifying treatment-naïve gliomas from a multi-center patients into WHO grades II-IV and across their isocitrate dehydrogenase (IDH) mutation status. Methods Three hundred thirty-three patients from 6 tertiary centres, diagnosed histologically and molecularly with primary gliomas (IDH-mutant = 151 or IDH-wildtype = 182) were retrospectively identified. Raw DSC-MRI data was post-processed for normalised leakage-corrected relative cerebral blood volume (rCBV) maps. Shape, intensity distribution (histogram) and rotational invariant Haralick texture features over the tumour mask were extracted. Differences in extracted features across glioma grades and mutation status were tested using the Wilcoxon two-sample test. A random-forest algorithm was employed (2-fold cross-validation, 250 repeats) to predict grades or mutation status using the extracted features. Results Shape, distribution and texture features showed significant differences across mutation status. WHO grade II-III differentiation was mostly driven by shape features while texture and intensity feature were more relevant for the III-IV separation. Increased number of features became significant when differentiating grades further apart from one another. Gliomas were correctly stratified by mutation status in 71% and by grade in 53% of the cases (87% of the gliomas grades predicted with distance less than 1). Conclusions Despite large heterogeneity in the multi-center dataset, machine learning assisted DSC-MRI radiomics hold potential to address the inherent variability and presents a promising approach for non-invasive glioma molecular subtyping and grading.
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Affiliation(s)
- Carole H Sudre
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK.,Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Jasmina Panovska-Griffiths
- Department of Applied Health Research, Institute of Epidemiology & Health Care, University College London, London, UK. .,Institute for Global Health, University College London, London, UK. .,The Queen's College, Oxford University, Oxford, UK.
| | - Eser Sanverdi
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London, UK
| | - Sebastian Brandner
- Division of Neuropathology, UCL Queen Square Institute of Neurology, London, UK
| | - Vasileios K Katsaros
- Department of Advanced Imaging Modalities, MRI Unit, General Anti-Cancer and Oncological Hospital of Athens "St. Savvas", Athens, Greece.,Department of Neurosurgery, General Hospital Evangelismos, Medical School, University of Athens, Athens, Greece
| | - George Stranjalis
- Department of Neurosurgery, General Hospital Evangelismos, Medical School, University of Athens, Athens, Greece
| | - Francesca B Pizzini
- Neuroradiology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - Claudio Ghimenton
- Neuropathology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - Katarina Surlan-Popovic
- Department of Neuroradiology, University Medical Centre, Ljubljana, Slovenia.,Department of Radiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Jernej Avsenik
- Department of Neuroradiology, University Medical Centre, Ljubljana, Slovenia.,Department of Radiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Maria Vittoria Spampinato
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Mario Nigro
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Arindam R Chatterjee
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Arnaud Attye
- Grenoble Institute of Neurosciences, INSERM, University Grenoble Alpes, Grenoble, France
| | - Sylvie Grand
- Grenoble Institute of Neurosciences, INSERM, University Grenoble Alpes, Grenoble, France
| | - Alexandre Krainik
- Grenoble Institute of Neurosciences, INSERM, University Grenoble Alpes, Grenoble, France
| | - Nicoletta Anzalone
- Department of Neuroradiology, San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Gian Marco Conte
- Department of Neuroradiology, San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Valeria Romeo
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Andrea Elefante
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Elisa Francesca Ciceri
- Neuropathology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy.,Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Elia Guadagno
- Department of Advanced Biomedical Sciences, Pathology Section, University of Naples Federico II, Naples, Italy
| | - Eftychia Kapsalaki
- Department of Radiology, School of Health Sciences, Faculty of Medicine, University of Thessaly, Larisa, Greece
| | | | | | | | - M Jorge Cardoso
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK.,Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sotirios Bisdas
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London, UK.,Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology, UCL, London, UK
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Song Q, Zhang C, Chen X, Cheng Y. Comparing amide proton transfer imaging with dynamic susceptibility contrast-enhanced perfusion in predicting histological grades of gliomas: a meta-analysis. Acta Radiol 2020; 61:549-557. [PMID: 31495179 DOI: 10.1177/0284185119871667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background As a subtype of chemical exchange saturation transfer imaging without contrast agent administration, amide proton transfer (APT) imaging has demonstrated the potential for differentiating the histologic grades of gliomas. Dynamic susceptibility contrast-enhanced perfusion, a perfusion-weighted imaging technique, is a well-established technique in grading gliomas. Purpose To compare the ability of amide proton transfer and dynamic susceptibility contrast-enhanced imaging for predicting the grades of gliomas. Material and Methods A comprehensive literature search was performed independently by two observers to identify articles about the diagnostic performance of amide proton transfer and dynamic susceptibility contrast-enhanced perfusion in predicting the grade of gliomas. Summary estimates of diagnostic accuracy were obtained by using a random-effects model. Results Of 179 studies identified, 23 studies were included the analysis. Eight studies evaluated amide proton transfer and 16 studies evaluated dynamic susceptibility contrast-enhanced perfusion with the parameter rCBV. The pooled sensitivities and specificities of each study’s best performing parameter were 88% (95% confidence interval [CI] 74–95) and 89% (95% CI 78–95) for amide proton transfer, and 95% (95% CI 87–98), 88% (95% CI 81–93) for perfusion-weighted imaging–dynamic susceptibility contrast-enhanced perfusion, respectively. The pooled sensitivities and specificities for grading gliomas using the two most commonly evaluated parameters, were 92% (95% CI 80–97) and 90% (95% CI 75–96) for APTmax, and 97% (95% CI 91–99) and 87% (95% CI 80–92) for rCBVmax, respectively. Conclusion Considering the similar performance of APT and dynamic susceptibility contrast-enhanced (DSC) in predicting glioma grade, the former method appears preferable since it needs no contrast agent.
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Affiliation(s)
- Qingxu Song
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, PR China
| | - Chencheng Zhang
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, PR China
| | - Xin Chen
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan, PR China
| | - Yufeng Cheng
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, PR China
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Kim MM, Parmar HA, Aryal MP, Mayo CS, Balter JM, Lawrence TS, Cao Y. Developing a Pipeline for Multiparametric MRI-Guided Radiation Therapy: Initial Results from a Phase II Clinical Trial in Newly Diagnosed Glioblastoma. ACTA ACUST UNITED AC 2020; 5:118-126. [PMID: 30854449 PMCID: PMC6403045 DOI: 10.18383/j.tom.2018.00035] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric dynamic contrast-enhanced (DCE-) and diffusion-weighted (DW-) magnetic resonance imaging (MRI) data for delineation of these subvolumes requires additional steps that go beyond the standard practices of target definition, we sought to devise a workflow to support the timely planning and treatment of patients. A phase II study implementing a multiparametric imaging biomarker for tumor hyperperfusion and hypercellularity consisting of DCE-MRI and high b-value DW-MRI to guide intensified (75 Gy/30 fractions) radiation therapy (RT) in patients with newly diagnosed glioblastoma was launched. In this report, the workflow and the initial imaging outcomes of the first 12 patients are described. Among all the first 12 patients, treatment was initiated within 6 weeks of surgery and within 2 weeks of simulation. On average, the combined hypercellular volume and high cerebral blood volume/tumor perfusion volume were 1.8 times smaller than the T1 gadolinium abnormality and 10 times smaller than the FLAIR abnormality. Hypercellular volume and high cerebral blood volume/tumor perfusion volume each identified largely distinct regions and showed 57% overlap with the enhancing abnormality, and minimal-to-no extension outside of the FLAIR. These results show the feasibility of implementing a workflow for multiparametric magnetic resonance-guided radiation therapy into clinical trials with a coordinated multidisciplinary team, and the unique and complementary tumor subregions identified by the combination of high b-value DW-MRI and DCE-MRI.
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Affiliation(s)
| | | | | | | | | | | | - Yue Cao
- Departments of Radiation Oncology and
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Dijkstra H, Sijens PE, van der Hoorn A, van Laar PJ. Inter-observer reproducibility of quantitative dynamic susceptibility contrast and diffusion MRI parameters in histogram analysis of gliomas. Acta Radiol 2020; 61:76-84. [PMID: 31159557 PMCID: PMC6935831 DOI: 10.1177/0284185119852729] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background Dynamic-susceptibility contrast and diffusion-weighted imaging are promising techniques in diagnosing glioma grade. Purpose To compare the inter-observer reproducibility of multiple dynamic-susceptibility contrast and diffusion-weighted imaging parameters and to assess their potential in differentiating low- and high-grade gliomas. Material and Methods Thirty patients (16 men; mean age = 40.6 years) with low-grade (n = 13) and high-grade (n = 17) gliomas and known pathology, scanned with dynamic-susceptibility contrast and diffusion-weighted imaging were included retrospectively between March 2006 and March 2014. Three observers used three different methods to define the regions of interest: (i) circles at maximum perfusion and minimum apparent diffusion coefficient; (ii) freeform 2D encompassing the tumor at largest cross-section only; (iii) freeform 3D on all cross-sections. The dynamic-susceptibility contrast curve was analyzed voxelwise: maximum contrast enhancement; time-to-peak; wash-in rate; wash-out rate; and relative cerebral blood volume. The mean was calculated for all regions of interest. For 2D and 3D methods, histogram analysis yielded additional statistics: the minimum and maximum 5% and 10% pixel values of the tumor (min5%, min10%, max5%, max10%). Intraclass correlations coefficients (ICC) were calculated between observers. Low- and high-grade tumors were compared with independent t-tests or Mann–Whitney tests. Results ICCs were highest for 3D freeform (ICC = 0.836–0.986) followed by 2D freeform (ICC = 0.854–0.974) and circular regions of interest (0.141–0.641). High ICC and significant discrimination between low- and high-grade gliomas was found for the following optimized parameters: apparent diffusion coefficient (P < 0.001; ICC = 0.641; mean; circle); time-to-peak (P = 0.015; ICC = 0.986; mean; 3D); wash-in rate (P = 0.004; ICC = 0.826; min10%; 3D); wash-out rate (P < 0.001; ICC = 0.860; min10%; 2D); and relative cerebral blood volume (P ≤ 0.001; ICC = 0.961; mean; 3D). Conclusion Dynamic-susceptibility contrast perfusion parameters relative cerebral blood volume and time-to-peak yielded high inter-observer reproducibility and significant glioma grade differentiation for the means of 2D and 3D freeform regions of interest. Choosing a freeform 2D method optimizes observer agreement and differentiation in clinical practice, while a freeform 3D method provides no additional benefit.
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Affiliation(s)
- Hildebrand Dijkstra
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Paul E Sijens
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anouk van der Hoorn
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Peter Jan van Laar
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Radiology, Ziekenhuis Groep Twente, Almelo-Hengelo, The Netherlands
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Li C, Wang S, Serra A, Torheim T, Yan JL, Boonzaier NR, Huang Y, Matys T, McLean MA, Markowetz F, Price SJ. Multi-parametric and multi-regional histogram analysis of MRI: modality integration reveals imaging phenotypes of glioblastoma. Eur Radiol 2019; 29:4718-4729. [PMID: 30707277 PMCID: PMC6682853 DOI: 10.1007/s00330-018-5984-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 12/18/2018] [Indexed: 12/11/2022]
Abstract
OBJECTIVES Integrating multiple imaging modalities is crucial for MRI data interpretation. The purpose of this study is to determine whether a previously proposed multi-view approach can effectively integrate the histogram features from multi-parametric MRI and whether the selected features can offer incremental prognostic values over clinical variables. METHODS Eighty newly-diagnosed glioblastoma patients underwent surgery and chemoradiotherapy. Histogram features of diffusion and perfusion imaging were extracted from contrast-enhancing (CE) and non-enhancing (NE) regions independently. An unsupervised patient clustering was performed by the multi-view approach. Kaplan-Meier and Cox proportional hazards regression analyses were performed to evaluate the relevance of patient clustering to survival. The metabolic signatures of patient clusters were compared using multi-voxel spectroscopy analysis. The prognostic values of histogram features were evaluated by survival and ROC curve analyses. RESULTS Two patient clusters were generated, consisting of 53 and 27 patients respectively. Cluster 2 demonstrated better overall survival (OS) (p = 0.007) and progression-free survival (PFS) (p < 0.001) than Cluster 1. Cluster 2 displayed lower N-acetylaspartate/creatine ratio in NE region (p = 0.040). A higher mean value of anisotropic diffusion in NE region was associated with worse OS (hazard ratio [HR] = 1.40, p = 0.020) and PFS (HR = 1.36, p = 0.031). The seven features selected by this approach showed significantly incremental value in predicting 12-month OS (p = 0.020) and PFS (p = 0.022). CONCLUSIONS The multi-view clustering method can provide an effective integration of multi-parametric MRI. The histogram features selected may be used as potential prognostic markers. KEY POINTS • Multi-parametric magnetic resonance imaging captures multi-faceted tumor physiology. • Contrast-enhancing and non-enhancing tumor regions represent different tumor components with distinct clinical relevance. • Multi-view data analysis offers a method which can effectively select and integrate multi-parametric and multi-regional imaging features.
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Affiliation(s)
- Chao Li
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Box 167 Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
- Department of Neurosurgery, Shanghai General Hospital (originally named "Shanghai First People's Hospital"), Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- The Centre for Mathematical Imaging in Healthcare, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, UK.
| | - Shuo Wang
- The Centre for Mathematical Imaging in Healthcare, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, UK
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Institute of Biosciences and Medical Technologies (BioMediTech), Tampere, Finland
- NeuRoNe Lab, DISA-MIS, University of Salerno, Fisciano, SA, Italy
| | - Turid Torheim
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge, UK
| | - Jiun-Lin Yan
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Box 167 Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Taiwan
- Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Natalie R Boonzaier
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Box 167 Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- Developmental Imaging and Biophysics Section, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Yuan Huang
- The Centre for Mathematical Imaging in Healthcare, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, UK
| | - Tomasz Matys
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Mary A McLean
- Department of Radiology, University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Florian Markowetz
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge, UK
| | - Stephen J Price
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Box 167 Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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Okuchi S, Rojas-Garcia A, Ulyte A, Lopez I, Ušinskienė J, Lewis M, Hassanein SM, Sanverdi E, Golay X, Thust S, Panovska-Griffiths J, Bisdas S. Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis. Cancer Med 2019; 8:5564-5573. [PMID: 31389669 PMCID: PMC6745862 DOI: 10.1002/cam4.2369] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 05/19/2019] [Accepted: 06/10/2019] [Indexed: 02/06/2023] Open
Abstract
Background T1‐weighted dynamic contrast‐enhanced (DCE) perfusion magnetic resonance imaging (MRI) has been broadly utilized in the evaluation of brain tumors. We aimed at assessing the diagnostic accuracy of DCE‐MRI in discriminating between low‐grade gliomas (LGGs) and high‐grade gliomas (HGGs), between tumor recurrence and treatment‐related changes, and between primary central nervous system lymphomas (PCNSLs) and HGGs. Methods We performed this study based on the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis of Diagnostic Test Accuracy Studies criteria. We systematically surveyed studies evaluating the diagnostic accuracy of DCE‐MRI for the aforementioned entities. Meta‐analysis was conducted with the use of a random effects model. Results Twenty‐seven studies were included after screening of 2945 possible entries. We categorized the eligible studies into three groups: those utilizing DCE‐MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment‐related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients). The pooled sensitivity, specificity, and area under the curve for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment‐related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively. Conclusions Dynamic contrast‐enhanced‐Magnetic resonance imaging is a promising noninvasive imaging method that has moderate or high accuracy in stratifying gliomas. DCE‐MRI shows high diagnostic accuracy in discriminating between HGGs and their low‐grade counterparts, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment‐related changes as well as PCNSLs and HGGs.
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Affiliation(s)
- Sachi Okuchi
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | | | - Agne Ulyte
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Ingeborg Lopez
- Neuroradiology, Institute of Neurosurgery Dr. A. Asenjo, Santiago, Chile
| | - Jurgita Ušinskienė
- Diagnostic and Interventional Radiology Department, Faculty of Medicine, National Cancer Institute, Vilnius University, Vilnius, Lithuania
| | - Martin Lewis
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Sara M Hassanein
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.,Diagnostic Radiology Department, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Eser Sanverdi
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Stefanie Thust
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - Sotirios Bisdas
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
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Wang X, Chen XZ, Shi L, Dai JP. Glioma grading and IDH1 mutational status: assessment by intravoxel incoherent motion MRI. Clin Radiol 2019; 74:651.e7-651.e14. [DOI: 10.1016/j.crad.2019.03.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 03/22/2019] [Indexed: 01/07/2023]
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Daboudi M, Papadaki E, Vakis A, Chlouverakis G, Makrakis D, Karageorgou D, Simos P, Koukouraki S. Brain SPECT and perfusion MRI: do they provide complementary information about the tumour lesion and its grading? Clin Radiol 2019; 74:652.e1-652.e9. [PMID: 31164195 DOI: 10.1016/j.crad.2019.03.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 03/22/2019] [Indexed: 10/26/2022]
Abstract
AIM To evaluate the relative and combined utility of 99mTc-tetrofosmin (99mTc-TF) brain single-photon-emission computed tomography (SPECT) and dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) in grading brain gliomas. MATERIALS AND METHODS Thirty-six patients with clinically suspected brain tumours were assessed by 99mTc-TF SPECT and DSC-MRI. Brain tumour malignancy was confirmed in all patients at histopathology. On both techniques brain lesions were evaluated via visual and semi-quantitative analysis methods (deriving tetrofosmin index [T-index] and relative cerebral blood volume [rCBV] ratios, respectively). RESULTS 99mTc-TF SPECT showed abnormally elevated tracer uptake in 31/36 patients whereas MRI detected the brain tumour in all patients. Optimal cut-off values of each index for discriminating between low- and high-grade gliomas were obtained through receiver operating characteristic (ROC) analyses. A T-index cut-off of 6.35 ensured 82% sensitivity and 71% specificity for discriminating between high- and low-grade gliomas, whereas a relative rCBV ratio cut-off of 1.80 achieved 91% sensitivity and 100% specificity. Requiring a positive result on either technique to characterise a high-grade glioma was associated with similar specificity and slightly increased sensitivity. CONCLUSION Both imaging techniques, 99mTF SPECT and DSC MRI, may provide complementary indices of tumour grade and have an independent diagnostic value for high-risk tumours.
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Affiliation(s)
- M Daboudi
- Department of Nuclear Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece.
| | - E Papadaki
- Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece; Institute of Computer Science, Foundation of Research and Technology, Heraklion, Crete, Greece
| | - A Vakis
- Department of Neurosurgery, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - G Chlouverakis
- Biostatistics Lab., Department of Social and Family Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - D Makrakis
- Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - D Karageorgou
- Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - P Simos
- Institute of Computer Science, Foundation of Research and Technology, Heraklion, Crete, Greece; Department of Psychiatry, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - S Koukouraki
- Department of Nuclear Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece
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Su CQ, Lu SS, Han QY, Zhou MD, Hong XN. Intergrating conventional MRI, texture analysis of dynamic contrast-enhanced MRI, and susceptibility weighted imaging for glioma grading. Acta Radiol 2019; 60:777-787. [PMID: 30244590 DOI: 10.1177/0284185118801127] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND The application of conventional magnetic resonance imaging (MRI) in glioma grading is limited and non-specific. PURPOSE To investigate the application values of MRI, texture analysis (TA) of dynamic contrast-enhanced MRI (DCE-MRI) and intratumoral susceptibility signal (ITSS) on susceptibility weighted imaging (SWI), alone and in combination, for glioma grading. MATERIAL AND METHODS Fifty-two patients with pathologically confirmed gliomas who underwent DCE-MRI and SWI were enrolled in this retrospective study. Conventional MRIs were evaluated by the VASARI scoring system. TA of DCE-MRI-derived parameters and the degree of ITSS were compared between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). The diagnostic ability of each parameter and their combination for glioma grading were analyzed. RESULTS Significant statistical differences in VASARI features were observed between LGGs and HGGs ( P < 0.05), of which the enhancement quality had the highest area under the curve (AUC) (0.873) with 93.3% sensitivity and 80% specificity. The TA of DCE-MRI derived parameters were significantly different between LGGs and HGGs ( P < 0.05), of which the uniformity of Ktrans had the highest AUC (0.917) with 93.3% sensitivity and 90% specificity. The degree of ITSS was significantly different between LGGs and HGGs ( P < 0.001). The AUC of the ITSS was 0.925 with 93.3% sensitivity and 90% specificity. The best discriminative power was obtained from a combination of enhancement quality, Ktrans- uniformity, and ITSS, resulting in 96.7% sensitivity, 100.0% specificity, and AUC of 0.993. CONCLUSION Combining conventional MRI, TA of DCE-MRI, and ITSS on SWI may help to improve the differentiation between LGGs and HGGs.
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Affiliation(s)
- Chun-Qiu Su
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Shan-Shan Lu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Qiu-Yue Han
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Mao-Dong Zhou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Xun-Ning Hong
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
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Saini J, Gupta RK, Kumar M, Singh A, Saha I, Santosh V, Beniwal M, Kandavel T, Cauteren MV. Comparative evaluation of cerebral gliomas using rCBV measurements during sequential acquisition of T1-perfusion and T2*-perfusion MRI. PLoS One 2019; 14:e0215400. [PMID: 31017934 PMCID: PMC6481809 DOI: 10.1371/journal.pone.0215400] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 04/01/2019] [Indexed: 12/31/2022] Open
Abstract
Objective To assess the inter-technique agreement of relative cerebral blood volume (rCBV) measurements obtained using T1- and T2*-perfusion MRI on 3T scanner in glioma patients. Methods A total of 49 adult patients with gliomas underwent both on T1- and T2*-perfusion in the same scanning session, and rCBV maps were estimated using both methods. For the quantitative analysis; Two independent observers recorded the rCBV values from the tumor as well as contralateral brain tissue from both T1- and T2*-perfusion. Inter-observer and inter-technique rCBV measurement agreement were determined by using 95% Bland-Altman limits of agreement and intra-class correlation coefficient (ICC) statistics. Results Qualitative analysis of the conventional and perfusion images showed that 16/49 (32.65%) tumors showed high susceptibility, and in these patients T2*-perfusion maps were suboptimal. Bland-Altman plots revealed an agreement between two independent observers recorded rCBV values for both T1- and T2*-perfusion. The ICC demonstrated strong agreement between rCBV values recorded by two observers for both T2* (ICC = 0.96, p = 0.040) and T1 (ICC = 0.97, p = 0.026) perfusion and similarly, good agreement was noted between rCBV estimated using two methods (ICC = 0.74, P<0.001). ROC analysis showed that rCBV estimated using T1- and T2*-perfusion methods were able to discriminate between grade-III and grade-IV tumors with AUC of 0.723 and 0.767 respectively. Comparison of AUC values of two ROC curves did not show any significant difference. Conclusions In the current study, T1- and T2*-perfusion showed similar diagnostic performance for discrimination of grade III and grade IV gliomas; however, T1-perfusion was found to be better for the evaluation of tumors with intratumoral hemorrhage, postoperative recurrent tumors, and lesions near skull base. We conclude that T1-perfusion MRI with a single dose of contrast could be used as an alternative to T2*-perfusion to overcome the issues associated with this technique in brain tumors for reliable perfusion quantification.
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Affiliation(s)
- Jitender Saini
- Department of Neuroimaging & Interventional Radiology, National Institute of Mental, Health and Neurosciences, Bangalore, Karnataka, India
- * E-mail:
| | - Rakesh Kumar Gupta
- Department of Radiology and Imaging, Fortis Memorial Hospital and Research Institute, Gurgaon, Haryana, India
| | - Manoj Kumar
- Department of Neuroimaging & Interventional Radiology, National Institute of Mental, Health and Neurosciences, Bangalore, Karnataka, India
| | - Anup Singh
- Center for Biomedical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India
| | - Indrajit Saha
- Philips Health Systems, Philips India Limited, Gurgaon, Haryana, India
| | - Vani Santosh
- Department of Neuropathology, National Institute of Mental, Health and Neurosciences, Bangalore, Karnataka, India
| | - Manish Beniwal
- Department of Neurosurgery, National Institute of Mental, Health and Neurosciences, Bangalore, Karnataka, India
| | - Thennarasu Kandavel
- Department of Biostatistics, National Institute of Mental, Health and Neurosciences, Bangalore, Karnataka, India
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Ozturk K, Soylu E, Tolunay S, Narter S, Hakyemez B. Dynamic Contrast-Enhanced T1-Weighted Perfusion Magnetic Resonance Imaging Identifies Glioblastoma Immunohistochemical Biomarkers via Tumoral and Peritumoral Approach: A Pilot Study. World Neurosurg 2019; 128:e195-e208. [PMID: 31003026 DOI: 10.1016/j.wneu.2019.04.089] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 12/13/2022]
Abstract
OBJECTIVE We aimed to evaluate the usefulness of dynamic contrast-enhanced T1-weighted perfusion magnetic resonance imaging (DCE-pMRI) to predict certain immunohistochemical (IHC) biomarkers of glioblastoma (GB) in this pilot study. METHODS We retrospectively reviewed 36 patients (male/female, 25:11; mean age, 53 years; age range, 29-85 years) who had pretreatment DCE-pMRI with IHC analysis of their excised GBs. Regions of interest of the enhancing tumor (ER) and nonenhancing peritumoral region (NER) were used to calculate DCE-pMRI parameters of volume transfer constant, back flux constant, volume of the extravascular extracellular space, initial area under enhancement curve, and maximum slope. IHC biomarkers including Ki-67 labeling index, epidermal growth factor receptor (EGFR), oligodendrocyte transcription factor 2 (OLIG2), isocitrate dehydrogenase 1 (IDH1), and p53 mutation status were determined. The imaging metrics of GB with IHC markers were compared using the Kruskal-Wallis test and Spearman correlation analysis. RESULTS Among 30 patients with available IDH1 status, 14 patients (46.6%) had IDH1 mutation. EGFR amplification was present in 24/36 (66.6%) patients. Mean Ki-67 labeling index was 29% (range, 1.5%-80%). p53 mutation was present in 20/36 GBs (55%), whereas OLIG2 expression was positive in 29/36 GBs (80.5%). Various DCE-pMRI parameters gathered from the ER and NER were significantly correlated with IDH1 mutation, EGFR amplification, and OLIG2 expression (P < 0.05). Ki-67 labeling index showed a strong positive correlation with initial area under enhancement curve (r = 0.619; P < 0.001). CONCLUSIONS DCE-pMRI could determine surrogate IHC biomarkers in GB via tumoral and peritumoral approach, potential targets for individualized treatment protocols.
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Affiliation(s)
- Kerem Ozturk
- Department of Radiology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Esra Soylu
- Department of Radiology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Sahsine Tolunay
- Department of Pathology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Selin Narter
- Department of Pathology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Bahattin Hakyemez
- Department of Radiology, Uludag University Faculty of Medicine, Bursa, Turkey.
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Sarkaria JN, Hu LS, Parney IF, Pafundi DH, Brinkmann DH, Laack NN, Giannini C, Burns TC, Kizilbash SH, Laramy JK, Swanson KR, Kaufmann TJ, Brown PD, Agar NYR, Galanis E, Buckner JC, Elmquist WF. Is the blood-brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data. Neuro Oncol 2019; 20:184-191. [PMID: 29016900 DOI: 10.1093/neuonc/nox175] [Citation(s) in RCA: 381] [Impact Index Per Article: 76.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The blood-brain barrier (BBB) excludes the vast majority of cancer therapeutics from normal brain. However, the importance of the BBB in limiting drug delivery and efficacy is controversial in high-grade brain tumors, such as glioblastoma (GBM). The accumulation of normally brain impenetrant radiographic contrast material in essentially all GBM has popularized a belief that the BBB is uniformly disrupted in all GBM patients so that consideration of drug distribution across the BBB is not relevant in designing therapies for GBM. However, contrary to this view, overwhelming clinical evidence demonstrates that there is also a clinically significant tumor burden with an intact BBB in all GBM, and there is little doubt that drugs with poor BBB permeability do not provide therapeutically effective drug exposures to this fraction of tumor cells. This review provides an overview of the clinical literature to support a central hypothesis: that all GBM patients have tumor regions with an intact BBB, and cure for GBM will only be possible if these regions of tumor are adequately treated.
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Affiliation(s)
- Jann N Sarkaria
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Leland S Hu
- Mayo Clinic, Scottsdale, Arizona (L.S.H., K.R.S.)
| | - Ian F Parney
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Deanna H Pafundi
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Debra H Brinkmann
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Nadia N Laack
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Caterina Giannini
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Terence C Burns
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Sani H Kizilbash
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Janice K Laramy
- University of Minnesota, Minneapolis, Minnesota (J.K.L., W.F.E.)
| | | | - Timothy J Kaufmann
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Paul D Brown
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | | | - Evanthia Galanis
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - Jan C Buckner
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
| | - William F Elmquist
- Mayo Clinic, Rochester, Minnesota (J.N.S., I.F.P., D.H.P., D.H.B., N.N.L., C.G., T.C.B., S.H.K., T.J.K., P.D.B., E.G., J.C.B.)
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Zakhari N, Taccone MS, Torres CH, Chakraborty S, Sinclair J, Woulfe J, Jansen GH, Cron GO, Thornhill RE, McInnes MDF, Nguyen TB. Prospective comparative diagnostic accuracy evaluation of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) MR perfusion in differentiating tumor recurrence from radiation necrosis in treated high-grade gliomas. J Magn Reson Imaging 2019; 50:573-582. [PMID: 30614146 DOI: 10.1002/jmri.26621] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 12/04/2018] [Accepted: 12/05/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The appearance of a new enhancing lesion after surgery and chemoradiation for high-grade glioma (HGG) presents a common diagnostic dilemma. Histopathological analysis remains the reference standard in this situation. PURPOSE To prospectively compare the diagnostic accuracy of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) in differentiating tumor recurrence (TR) from radiation necrosis (RN). STUDY TYPE Prospective diagnostic accuracy study. POPULATION In all, 98 consecutive treated HGG patients with new enhancing lesion. We excluded 32 patients due to inadequate follow-up or technical limitation. FIELD STRENGTH/SEQUENCE 3 T DCE and DSC MR. ASSESSMENT Histogram and hot-spot analysis of cerebral blood volume (CBV), corrected CBV, Ktrans , area under the curve (AUC), and plasma volume (Vp). The reference standard of TR and/or RN was determined by histopathology in 43 surgically resected lesions or by clinical/imaging follow-up in the rest. STATISTICAL TESTS Mann-Whitney U-tests, receiver operating characteristic (ROC) curve, and logistic regression analysis. RESULTS A total of 68 lesions were included. There were 37 TR, 28 RN, and three lesions with equal proportions of TR and RN. TR had significantly higher CBV, corrected CBV, CBV ratio, corrected CBV ratio, AUC ratio, and Vp ratio (P < 0.05) than RN on hot-spot analysis. CBV had the highest diagnostic accuracy (AUROC 0.71). On histogram analysis, TR had higher CBV and corrected CBV maximal value compared with RN (P = 0.006, AUROC = 0.70). Only CBV on hot-spot analysis remained significant after correction for multiple comparison, with no significant improvement in diagnostic accuracy when using a combination of parameters (AUROC 0.71 vs. 0.76, P = 0.24). DATA CONCLUSION DSC-derived CBV is the most accurate perfusion parameter in differentiating TR and RN. DSC and DCE-derived parameters reflecting the blood volume in an enhancing lesion are more accurate than the DCE-derived parameter Ktrans . Clinical practice may be best guided by blood volume measurements, rather than permeability assessment for differentiation of TR from RN. LEVEL OF EVIDENCE 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:573-582.
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Affiliation(s)
- Nader Zakhari
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
| | - Michael S Taccone
- University of Ottawa, Ottawa, Ontario, Canada.,Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Carlos H Torres
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
| | - Santanu Chakraborty
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
| | - John Sinclair
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
| | - John Woulfe
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
| | - Gerard H Jansen
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
| | - Greg O Cron
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada.,Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | | | - Matthew D F McInnes
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada.,Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Thanh B Nguyen
- University of Ottawa, Ottawa, Ontario, Canada.,Ottawa Hospital, Ottawa, Ontario, Canada
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Li WF, Niu C, Shakir TM, Chen T, Zhang M, Wang Z. An evidence-based approach to assess the accuracy of intravoxel incoherent motion imaging for the grading of brain tumors. Medicine (Baltimore) 2018; 97:e13217. [PMID: 30407363 PMCID: PMC6250525 DOI: 10.1097/md.0000000000013217] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Differentiation of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) is an important clinical problem because treatment strategies vary greatly. This study was performed to investigate the potential diagnostic value of incoherent intravoxel motion imaging (IVIM) to distinguish HGG from LGG by meta-analysis. METHODS A computerized search of the literature was performed using the free-access PubMed database, Web of Science, and Chinese biomedical database, and relevant articles until September 18, 2018 that used IVIM to distinguish HGG from LGG were included. All analyses were performed using Review Manager 5.3 and Stata. Mean difference (MD) at 95% confidence interval (CI) of the apparent diffusion coefficient (ADC), diffusion coefficient value (D), perfusion fraction value (f), and perfusion coefficient value (D*) were summarized. RESULTS Nine studies were used for general data pooling. In the tumor parenchyma (TP) regions, subgroup analysis revealed D* in HGG is higher than in LGG (MD = 1.19, P = .002), and D in HGG is lower than in LGG (MD = -1.06, P = .001). However, no significant difference in f (MD = 0.89, P = .056) was detected between HGG and LGG. In the white matter regions, HGG had higher D* (MD = 0.76, P = .04) compared with LGG, while no marked differences between the D value (P = .07) and f (P = .09) values. CONCLUSION The present meta-analysis shows that the ADC, D, and D* values derived from IVIM may be useful in differentiating HGG from LGG. Considering the small sample of this study, we need to be cautious when interpreting the results of this study. Other prospective and large-sample randomized controlled trials were needed to establish the value of IVIM in differentiating HGG from LGG.
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Affiliation(s)
- Wen-fei Li
- Department of Radiology, The First Hospital of Qinhuangdao, Hebei
| | - Chen Niu
- Department of Radiology, First Affiliated Hospital of Xi’An Jiaotong University, Shaanxi
| | - Tahir Mehmood Shakir
- Department of Radiology, First Affiliated Hospital of Xi’An Jiaotong University, Shaanxi
| | - Tao Chen
- Department of Radiology, Xiang Yang Central Hospital, Hubei, China
| | - Ming Zhang
- Department of Radiology, First Affiliated Hospital of Xi’An Jiaotong University, Shaanxi
| | - Zhanqiu Wang
- Department of Radiology, The First Hospital of Qinhuangdao, Hebei
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Debus C, Afshar-Oromieh A, Floca R, Ingrisch M, Knoll M, Debus J, Haberkorn U, Abdollahi A. Feasibility and robustness of dynamic 18F-FET PET based tracer kinetic models applied to patients with recurrent high-grade glioma prior to carbon ion irradiation. Sci Rep 2018; 8:14760. [PMID: 30283013 PMCID: PMC6170489 DOI: 10.1038/s41598-018-33034-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 09/07/2018] [Indexed: 12/23/2022] Open
Abstract
The aim of this study was to analyze the robustness and diagnostic value of different compartment models for dynamic 18F-FET PET in recurrent high-grade glioma (HGG). Dynamic 18F-FET PET data of patients with recurrent WHO grade III (n:7) and WHO grade IV (n: 9) tumors undergoing re-irradiation with carbon ions were analyzed by voxelwise fitting of the time-activity curves with a simplified and an extended one-tissue compartment model (1TCM) and a two-tissue compartment model (2TCM), respectively. A simulation study was conducted to assess robustness and precision of the 2TCM. Parameter maps showed enhanced detail on tumor substructure. Neglecting the blood volume VB in the 1TCM yields insufficient results. Parameter K1 from both 1TCM and 2TCM showed correlation with overall patient survival after carbon ion irradiation (p = 0.043 and 0.036, respectively). The 2TCM yields realistic estimates for tumor blood volume, which was found to be significantly higher in WHO IV compared to WHO III (p = 0.031). Simulations on the 2TCM showed that K1 yields good accuracy and robustness while k2 showed lowest stability of all parameters. The 1TCM provides the best compromise between parameter stability and model accuracy; however application of the 2TCM is still feasible and provides a more accurate representation of tracer-kinetics at the cost of reduced robustness. Detailed tracer kinetic analysis of 18F-FET PET with compartment models holds valuable information on tumor substructures and provides additional diagnostic and prognostic value.
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Affiliation(s)
- Charlotte Debus
- German Cancer Consortium (DKTK), Heidelberg, Germany.
- Translational Radiation Oncology, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Division of Molecular and Translational Radiation Oncology, Heidelberg University Medical School, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
| | - Ali Afshar-Oromieh
- Department of Nuclear Medicine, Heidelberg University Hospital, Heidelberg, Germany
- Clinical Cooperation Unit Nuclear Medicine, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Ralf Floca
- Division of Molecular and Translational Radiation Oncology, Heidelberg University Medical School, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Ingrisch
- Department of Radiology, University Hospital Munich, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Maximilian Knoll
- German Cancer Consortium (DKTK), Heidelberg, Germany
- Translational Radiation Oncology, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Molecular and Translational Radiation Oncology, Heidelberg University Medical School, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen Debus
- German Cancer Consortium (DKTK), Heidelberg, Germany
- Translational Radiation Oncology, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Molecular and Translational Radiation Oncology, Heidelberg University Medical School, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Uwe Haberkorn
- Department of Nuclear Medicine, Heidelberg University Hospital, Heidelberg, Germany
- Clinical Cooperation Unit Nuclear Medicine, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Amir Abdollahi
- German Cancer Consortium (DKTK), Heidelberg, Germany
- Translational Radiation Oncology, National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Molecular and Translational Radiation Oncology, Heidelberg University Medical School, Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
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49
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Delgado AF, De Luca F, Hanagandi P, van Westen D, Delgado AF. Arterial Spin-Labeling in Children with Brain Tumor: A Meta-Analysis. AJNR Am J Neuroradiol 2018; 39:1536-1542. [PMID: 30072368 PMCID: PMC7410530 DOI: 10.3174/ajnr.a5727] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 05/18/2018] [Indexed: 12/19/2022]
Abstract
BACKGROUND The value of arterial spin-labeling in a pediatric population has not been assessed in a meta-analysis. PURPOSE Our aim was to assess the diagnostic accuracy of arterial spin-labeling-derived cerebral blood flow to discriminate low- and high-grade tumors. DATA SOURCES MEDLINE, EMBASE, the Web of Science Core Collection, and the Cochrane Library were used. STUDY SELECTION Pediatric patients with arterial spin-labeling MR imaging with verified neuropathologic diagnoses were included. DATA ANALYSIS Relative CBF and absolute CBF and tumor grade were extracted, including sequence-specific information. Mean differences in CBF between low- and high-grade tumors were calculated. Study quality was assessed. DATA SYNTHESIS Data were aggregated using the bivariate summary receiver operating characteristic curve model. Heterogeneity was explored with meta-regression and subgroup analyses. The study protocol was published at PROSPERO (CRD42017075055). Eight studies encompassing 286 pediatric patients were included. The mean differences in absolute CBF were 29.62 mL/min/100 g (95% CI, 10.43-48.82 mL/min/100 g), I2 = 74, P = .002, and 1.34 mL/min/100 g (95% CI, 0.95-1.74 mL/min/100 g), P < .001, I2 = 38 for relative CBF. Pooled sensitivity for relative CBF ranged from 0.75 to 0.90, and specificity, from 0.77 to 0.92 with an area under curve = 0.92. Meta-regression showed no moderating effect of sequence parameters TE, TR, acquisition time, or ROI method. LIMITATIONS Included tumor types, analysis method, and original data varied among included studies. CONCLUSIONS Arterial spin-labeling-derived CBF measures showed high diagnostic accuracy for discriminating low- and high-grade tumors in pediatric patients with brain tumors. The relative CBF showed less variation among studies than the absolute CBF.
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Affiliation(s)
- A F Delgado
- From the Departments of Clinical Neuroscience (Anna F.D.)
| | - F De Luca
- Faculty of Medicine and Surgery (F.D.L.), School of Medicine and Health Sciences, University "G. d'Annunzio," Chieti, Italy
| | - P Hanagandi
- Neuroradiology (P.H.), Karolinska Institute, Stockholm, Sweden
| | - D van Westen
- Faculty of Medicine (D.v.W.), Clinical Sciences, Lund University, Sweden
| | - A F Delgado
- Department of Surgical Sciences (Alberto F.D.), Uppsala University, Uppsala, Sweden
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50
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Anzalone N, Castellano A, Cadioli M, Conte GM, Cuccarini V, Bizzi A, Grimaldi M, Costa A, Grillea G, Vitali P, Aquino D, Terreni MR, Torri V, Erickson BJ, Caulo M. Brain Gliomas: Multicenter Standardized Assessment of Dynamic Contrast-enhanced and Dynamic Susceptibility Contrast MR Images. Radiology 2018; 287:933-943. [DOI: 10.1148/radiol.2017170362] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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