1
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Nguyen TB, Zakhari N, Velasco Sandoval S, Guarnizo-Capera A, Alexios Gulak M, Woulfe J, Jansen G, Thornhill R, Majtenyi N, Cron GO. Diagnostic Accuracy of Arterial Spin-Labeling, Dynamic Contrast-Enhanced, and DSC Perfusion Imaging in the Diagnosis of Recurrent High-Grade Gliomas: A Prospective Study. AJNR Am J Neuroradiol 2023; 44:134-142. [PMID: 36702501 PMCID: PMC9891339 DOI: 10.3174/ajnr.a7771] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 12/30/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE For patients with high-grade gliomas, the appearance of a new, enhancing lesion after surgery and chemoradiation represents a diagnostic dilemma. We hypothesized that MR perfusion without and with contrast can differentiate tumor recurrence from radiation necrosis. MATERIALS AND METHODS In this prospective study, we performed 3 MR perfusion methods: arterial spin-labeling, DSC, and dynamic contrast enhancement. For each lesion, we measured CBF from arterial spin-labeling, uncorrected relative CBV, and leakage-corrected relative CBV from DSC imaging. The volume transfer constant and plasma volume were obtained from dynamic contrast-enhanced imaging without and with T1 mapping using modified Look-Locker inversion recovery (MOLLI). The diagnosis of tumor recurrence or radiation necrosis was determined by either histopathology for patients who underwent re-resection or radiologic follow-up for patients who did not have re-resection. RESULTS There were 26 patients with 32 lesions, 19 lesions with tumor recurrence and 13 lesions with radiation necrosis. Compared with radiation necrosis, lesions with tumor recurrence had higher CBF (P = .033), leakage-corrected relative CBV (P = .048), and plasma volume using MOLLI T1 mapping (P = .012). For differentiating tumor recurrence from radiation necrosis, the areas under the curve were 0.81 for CBF, 0.80 for plasma volume using MOLLI T1 mapping, and 0.71 for leakage-corrected relative CBV. A correlation was found between CBF and leakage-corrected relative CBV (r s = 0.54), volume transfer constant, and plasma volume (0.50 < r s< 0.77) but not with uncorrected relative CBV (r s = 0.20, P = .29). CONCLUSIONS In the differentiation of tumor recurrence from radiation necrosis in a newly enhancing lesion, the diagnostic value of arterial spin-labeling-derived CBF is similar to that of DSC and dynamic contrast-enhancement-derived blood volume.
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Affiliation(s)
- T B Nguyen
- From the Department of Radiology (T.B.N., N.Z., R.T.), Radiation Oncology and Medical Physics
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - N Zakhari
- From the Department of Radiology (T.B.N., N.Z., R.T.), Radiation Oncology and Medical Physics
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - S Velasco Sandoval
- Division of Neuroradiology (S.V.S., A.G.-C.), Department of Radiology, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, D.C., Colombia
| | - A Guarnizo-Capera
- Division of Neuroradiology (S.V.S., A.G.-C.), Department of Radiology, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, D.C., Colombia
| | - M Alexios Gulak
- Department of Anesthesiology and Pain Medicine (M.A.G.), University of Toronto, Toronto, Ontario, Canada
| | - J Woulfe
- Department of Pathology and Laboratory Medicine (J.W., G.J.), The Ottawa Hospital, Ottawa, Ontario, Canada
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - G Jansen
- Department of Pathology and Laboratory Medicine (J.W., G.J.), The Ottawa Hospital, Ottawa, Ontario, Canada
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - R Thornhill
- From the Department of Radiology (T.B.N., N.Z., R.T.), Radiation Oncology and Medical Physics
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - N Majtenyi
- Department of Medical Physics (N.M.), Grand River Regional Cancer Centre, Kitchener, Ontario, Canada
| | - G O Cron
- Stanford University (G.O.C.), Stanford, California
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Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
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Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
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3
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Hwang I, Choi SH, Kim JW, Yeon EK, Lee JY, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH. Response prediction of vestibular schwannoma after gamma-knife radiosurgery using pretreatment dynamic contrast-enhanced MRI: a prospective study. Eur Radiol 2022; 32:3734-3743. [PMID: 35084518 DOI: 10.1007/s00330-021-08517-1] [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: 06/07/2021] [Revised: 11/09/2021] [Accepted: 12/10/2021] [Indexed: 11/04/2022]
Abstract
OBJECTIVES There are few known predictive factors for response to gamma-knife radiosurgery (GKRS) in vestibular schwannoma (VS). We investigated the predictive role of pretreatment dynamic contrast-enhanced (DCE)-MRI parameters regarding the tumor response after GKRS in sporadic VS. METHODS This single-center prospective study enrolled participants between April 2017 and February 2019. We performed a volumetric measurement of DCE-MRI-derived parameters before GKRS. The tumor volume was measured in a follow-up MRI. The pharmacokinetic parameters were compared between responders and nonresponders according to 20% or more tumor volume reduction. Stepwise multivariable logistic regression analyses were performed, and the diagnostic performance of DCE-MRI parameters for the prediction of tumor response was evaluated by receiver operating characteristic curve analysis. RESULTS Ultimately, 35 participants (21 women, 52 ± 12 years) were included. There were 22 (62.9%) responders with a mean follow-up interval of 30.2 ± 5.7 months. Ktrans (0.036 min-1 vs. 0.057 min-1, p = .008) and initial area under the time-concentration curve within 90 s (IAUC90) (84.4 vs. 143.6, p = .003) showed significant differences between responders and nonresponders. Ktrans (OR = 0.96, p = .021) and IAUC90 (OR = 0.97, p = .004) were significant differentiating variables in each multivariable model with clinical variables for tumor response prediction. Ktrans showed a sensitivity of 81.8% and a specificity of 69.2%, and IAUC90 showed a sensitivity of 100% and a specificity of 53.8% for tumor response prediction. CONCLUSION DCE-MRI (particularly Ktrans and IAUC90) has the potential to be a predictive factor for tumor response in VS after GKRS. KEY POINTS •Pretreatment prediction of gamma-knife radiosurgery response in vestibular schwannoma is still challenging. •Dynamic contrast-enhanced MRI could have predictive value for the response of vestibular schwannoma after gamma-knife radiosurgery.
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Affiliation(s)
- Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea. .,Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, 08826, Republic of Korea.
| | - Jin Wook Kim
- Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eung Koo Yeon
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Ji Ye Lee
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
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4
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Qiu J, Tao ZC, Deng KX, Wang P, Chen CY, Xiao F, Luo Y, Yuan SY, Chen H, Huang H. Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis. Chin Med J (Engl) 2021; 134:2535-2543. [PMID: 34748524 PMCID: PMC8577681 DOI: 10.1097/cm9.0000000000001445] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND It is crucial to differentiate accurately glioma recurrence and pseudoprogression which have entirely different prognosis and require different treatment strategies. This study aimed to assess the diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for distinguishing glioma recurrence and pseudoprogression. METHODS According to particular criteria of inclusion and exclusion, related studies up to May 1, 2019, were thoroughly searched from several databases including PubMed, Embase, Cochrane Library, and Chinese biomedical databases. The quality assessment of diagnostic accuracy studies was applied to evaluate the quality of the included studies. By using the "mada" package in R, the heterogeneity, overall sensitivity, specificity, and diagnostic odds ratio were calculated. Moreover, funnel plots were used to visualize and estimate the publication bias in this study. The area under the summary receiver operating characteristic (SROC) curve was computed to display the diagnostic efficiency of DCE-MRI. RESULTS In the present meta-analysis, a total of 11 studies covering 616 patients were included. The results showed that the pooled sensitivity, specificity, and diagnostic odds ratio were 0.792 (95% confidence interval [CI] 0.707-0.857), 0.779 (95% CI 0.715-0.832), and 16.219 (97.5% CI 9.123-28.833), respectively. The value of the area under the SROC curve was 0.846. In addition, the SROC curve showed high sensitivities (>0.6) and low false positive rates (<0.5) from most of the included studies, which suggest that the results of our study were reliable. Furthermore, the funnel plot suggested the existence of publication bias. CONCLUSIONS While the DCE-MRI is not the perfect diagnostic tool for distinguishing glioma recurrence and pseudoprogression, it was capable of improving diagnostic accuracy. Hence, further investigations combining DCE-MRI with other imaging modalities are required to establish an efficient diagnostic method for glioma patients.
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Affiliation(s)
- Jun Qiu
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Zhen-Chao Tao
- Department of Radiation Oncology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Ke-Xue Deng
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Peng Wang
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Chuan-Yu Chen
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Fang Xiao
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Yi Luo
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Shu-Ya Yuan
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Hao Chen
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
| | - Huan Huang
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230036, China
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5
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Park JE, Kim JY, Kim HS, Shim WH. Comparison of Dynamic Contrast-Enhancement Parameters between Gadobutrol and Gadoterate Meglumine in Posttreatment Glioma: A Prospective Intraindividual Study. AJNR Am J Neuroradiol 2020; 41:2041-2048. [PMID: 33060100 DOI: 10.3174/ajnr.a6792] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 07/22/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND PURPOSE Differences in molecular properties between one-molar and half-molar gadolinium-based contrast agents are thought to affect parameters obtained from dynamic contrast-enhanced imaging. The aim of our study was to investigate differences in dynamic contrast-enhanced parameters between one-molar nonionic gadobutrol and half-molar ionic gadoterate meglumine in patients with posttreatment glioma. MATERIALS AND METHODS This prospective study enrolled 32 patients who underwent 2 20-minute dynamic contrast-enhanced examinations, one with gadobutrol and one with gadoterate meglumine. The model-free parameter of area under the signal intensity curve from 30 to 1100 seconds and the Tofts model-based pharmacokinetic parameters were calculated and compared intraindividually using paired t tests. Patients were further divided into progression (n = 12) and stable (n = 20) groups, which were compared using Student t tests. RESULTS Gadobutrol and gadoterate meglumine did not show any significant differences in the area under the signal intensity curve or pharmacokinetic parameters of K trans, Ve, Vp, or Kep (all P > .05). Gadobutrol showed a significantly higher mean wash-in rate (0.83 ± 0.64 versus 0.29 ± 0.63, P = .013) and a significantly lower mean washout rate (0.001 ± 0.0001 versus 0.002 ± 0.002, P = .02) than gadoterate meglumine. Trends toward higher area under the curve, K trans, Ve, Vp, wash-in, and washout rates and lower Kep were observed in the progression group in comparison with the treatment-related-change group, regardless of the contrast agent used. CONCLUSIONS Model-free and pharmacokinetic parameters did not show any significant differences between the 2 gadolinium-based contrast agents, except for a higher wash-in rate with gadobutrol and a higher washout rate with gadoterate meglumine, supporting the interchangeable use of gadolinium-based contrast agents for dynamic contrast-enhanced imaging in patients with posttreatment glioma.
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Affiliation(s)
- J E Park
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., W.H.S.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - J Y Kim
- Department of Radiology (J.Y.K.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - H S Kim
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., W.H.S.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - W H Shim
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., W.H.S.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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Gatson NTN, Bross SP, Odia Y, Mongelluzzo GJ, Hu Y, Lockard L, Manikowski JJ, Mahadevan A, Kazmi SAJ, Lacroix M, Conger AR, Vadakara J, Nayak L, Chi TL, Mehta MP, Puduvalli VK. Early imaging marker of progressing glioblastoma: a window of opportunity. J Neurooncol 2020; 148:629-640. [PMID: 32602020 DOI: 10.1007/s11060-020-03565-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 06/17/2020] [Indexed: 12/28/2022]
Abstract
PURPOSE Therapeutic intervention at glioblastoma (GBM) progression, as defined by current assessment criteria, is arguably too late as second-line therapies fail to extend survival. Still, most GBM trials target recurrent disease. We propose integration of a novel imaging biomarker to more confidently and promptly define progression and propose a critical timepoint for earlier intervention to extend therapeutic exposure. METHODS A retrospective review of 609 GBM patients between 2006 and 2019 yielded 135 meeting resection, clinical, and imaging inclusion criteria. We qualitatively and quantitatively analyzed 2000+ sequential brain MRIs (initial diagnosis to first progression) for development of T2 FLAIR signal intensity (SI) within the resection cavity (RC) compared to the ventricles (V) for quantitative inter-image normalization. PFS and OS were evaluated using Kaplan-Meier curves stratified by SI. Specificity and sensitivity were determined using a 2 × 2 table and pathology confirmation at progression. Multivariate analysis evaluated SI effect on the hazard rate for death after adjusting for established prognostic covariates. Recursive partitioning determined successive quantifiers and cutoffs associated with outcomes. Neurological deficits correlated with SI. RESULTS Seventy-five percent of patients developed SI on average 3.4 months before RANO-assessed progression with 84% sensitivity. SI-positivity portended neurological decline and significantly poorer outcomes for PFS (median, 10 vs. 15 months) and OS (median, 20 vs. 29 months) compared to SI-negative. RC/V ratio ≥ 4 was the most significant prognostic indicator of death. CONCLUSION Implications of these data are far-reaching, potentially shifting paradigms for glioma treatment response assessment, altering timepoints for salvage therapeutic intervention, and reshaping glioma clinical trial design.
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Affiliation(s)
- Na Tosha N Gatson
- Neuroscience Institute, Geisinger Health, Danville, PA, 17822, USA. .,Cancer Institute, Geisinger Health, Danville, PA, 17822, USA. .,Geisinger Commonwealth School of Medicine, Scranton, PA, 18509, USA. .,Geisinger Medical Center, Neuroscience Institute MC 14-03, 100 N. Academy Ave, Danville, PA, 17822, USA.
| | - Shane P Bross
- Neuroscience Institute, Geisinger Health, Danville, PA, 17822, USA
| | - Yazmin Odia
- Department of Neuro-Oncology, Miami Cancer Institute/Baptist Health South Florida, Miami, FL, 33176, USA
| | | | - Yirui Hu
- Department of Population Health Sciences, Geisinger Health, Danville, PA, 17822, USA
| | - Laura Lockard
- Geisinger Commonwealth School of Medicine, Scranton, PA, 18509, USA
| | | | - Anand Mahadevan
- Cancer Institute, Geisinger Health, Danville, PA, 17822, USA
| | - Syed A J Kazmi
- Department of Pathology, Geisinger Health, Danville, PA, 17822, USA
| | - Michel Lacroix
- Neuroscience Institute, Geisinger Health, Danville, PA, 17822, USA
| | - Andrew R Conger
- Neuroscience Institute, Geisinger Health, Danville, PA, 17822, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, 18509, USA
| | - Joseph Vadakara
- Cancer Institute, Geisinger Health, Danville, PA, 17822, USA
| | - Lakshmi Nayak
- Harvard Medical School, Center for Neuro-Oncology,, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - T Linda Chi
- Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Minesh P Mehta
- Department of Radiation Oncology, Miami Cancer Institute/Baptist Health South Florida, Miami, FL, 33176, USA
| | - Vinay K Puduvalli
- Division of Neuro-Oncology, The OH State University Comprehensive Cancer Center - James and OSU Neurological Institute, Columbus, OH, 43210, USA.,Department of Neuro-Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
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7
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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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8
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Dynamic contrast-enhanced MRI of orbital and anterior visual pathway lesions. Magn Reson Imaging 2018; 51:44-50. [DOI: 10.1016/j.mri.2018.04.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/19/2018] [Accepted: 04/26/2018] [Indexed: 01/13/2023]
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9
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Dongas J, Asahina AT, Bacchi S, Patel S. Magnetic Resonance Perfusion Imaging in the Diagnosis of High-Grade Glioma Progression and Treatment-Related Changes: A Systematic Review. ACTA ACUST UNITED AC 2018. [DOI: 10.4236/ojmn.2018.83024] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Choi YS, Ahn SS, Lee HJ, Chang JH, Kang SG, Kim EH, Kim SH, Lee SK. The Initial Area Under the Curve Derived from Dynamic Contrast-Enhanced MRI Improves Prognosis Prediction in Glioblastoma with Unmethylated MGMT Promoter. AJNR Am J Neuroradiol 2017. [PMID: 28642265 DOI: 10.3174/ajnr.a5265] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND AND PURPOSE Although perfusion and permeability MR parameters have known to have prognostic value, they have reproducibility issues. Our aim was to evaluate whether the initial area under the time-to-signal intensity curve (IAUC) derived from dynamic contrast-enhanced MR imaging can improve prognosis prediction in patients with glioblastoma with known MGMT status. MATERIALS AND METHODS We retrospectively examined 88 patients with glioblastoma who underwent preoperative dynamic contrast-enhanced MR imaging. The means of IAUC values at 30 and 60 seconds (IAUC30mean and IAUC60mean) were extracted from enhancing tumors. The prognostic values of IAUC parameters for overall survival and progression-free survival were assessed with log-rank tests, according to the MGMT status. Multivariate overall survival and progression-free survival models before and after adding the IAUC parameters as covariates were explored by net reclassification improvement after receiver operating characteristic analysis for 1.5-year overall survival and 1-year progression-free survival and by random survival forest. RESULTS High IAUC parameters were associated with worse overall survival and progression-free survival in the unmethylated MGMT group, but not in the methylated group. In the unmethylated MGMT group, 1.5-year overall survival and 1-year progression-free survival prediction improved significantly after adding IAUC parameters (overall survival area under the receiver operating characteristic curve, 0.86; progression-free survival area under the receiver operating characteristic curve, 0.74-0.76) to the model with other prognostic factors (overall survival area under the receiver operating characteristic curve, 0.81; progression-free survival area under the receiver operating characteristic curve, 0.69; P < .05 for all) except in the case of IAUC60mean for 1-year progression-free survival prediction (P = .059). Random survival forest models indicated that the IAUC parameters were the second or most important predictors in the unmethylated MGMT group, except in the case of the IAUC60mean for progression-free survival. CONCLUSIONS IAUC can be a useful prognostic imaging biomarker in patients with glioblastoma with known MGMT status, improving prediction of glioblastoma prognosis with the unmethylated MGMT promoter status.
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Affiliation(s)
- Y S Choi
- From the Department of Radiology and Research Institute of Radiological Science (Y.S.C., S.S.A., H.-J.L., S.-K.L.)
| | - S S Ahn
- From the Department of Radiology and Research Institute of Radiological Science (Y.S.C., S.S.A., H.-J.L., S.-K.L.)
| | - H-J Lee
- From the Department of Radiology and Research Institute of Radiological Science (Y.S.C., S.S.A., H.-J.L., S.-K.L.)
| | - J H Chang
- Neurosurgery (J.H.C., S.-G.K., E.H.K.), Yonsei University College of Medicine, Seoul, Korea
| | - S-G Kang
- Neurosurgery (J.H.C., S.-G.K., E.H.K.), Yonsei University College of Medicine, Seoul, Korea
| | - E H Kim
- Neurosurgery (J.H.C., S.-G.K., E.H.K.), Yonsei University College of Medicine, Seoul, Korea
| | - S H Kim
- Departments of Pathology (S.H.K.)
| | - S-K Lee
- From the Department of Radiology and Research Institute of Radiological Science (Y.S.C., S.S.A., H.-J.L., S.-K.L.)
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Jittapiromsak N, Hou P, Williams MD, Chi TL. Orbital oncocytoma: evaluation with dynamic contrast-enhanced magnetic resonance imaging using a time-signal intensity curve and positive enhancement integral images. Clin Imaging 2017; 42:161-164. [DOI: 10.1016/j.clinimag.2016.11.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 11/16/2016] [Accepted: 11/28/2016] [Indexed: 11/25/2022]
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Patel P, Baradaran H, Delgado D, Askin G, Christos P, John Tsiouris A, Gupta A. MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis. Neuro Oncol 2016; 19:118-127. [PMID: 27502247 DOI: 10.1093/neuonc/now148] [Citation(s) in RCA: 165] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Distinction between tumor and treatment related changes is crucial for clinical management of patients with high-grade gliomas. Our purpose was to evaluate whether dynamic susceptibility contrast-enhanced (DSC) and dynamic contrast enhanced (DCE) perfusion-weighted imaging (PWI) metrics can effectively differentiate between recurrent tumor and posttreatment changes within the enhancing signal abnormality on conventional MRI. METHODS A comprehensive literature search was performed for studies evaluating PWI-based differentiation of recurrent tumor and posttreatment changes in patients with high-grade gliomas (World Health Organization grades III and IV). Only studies published in the "temozolomide era" beginning in 2005 were included. Summary estimates of diagnostic accuracy were obtained by using a random-effects model. RESULTS Of 1581 abstracts screened, 28 articles were included. The pooled sensitivities and specificities of each study's best performing parameter were 90% and 88% (95% CI: 0.85-0.94; 0.83-0.92) and 89% and 85% (95% CI: 0.78-0.96; 0.77-0.91) for DSC and DCE, respectively. The pooled sensitivities and specificities for detecting tumor recurrence using the 2 most commonly evaluated parameters, mean relative cerebral blood volume (rCBV) (threshold range, 0.9-2.15) and maximum rCBV (threshold range, 1.49-3.1), were 88% and 88% (95% CI: 0.81-0.94; 0.78-0.95) and 93% and 76% (95% CI: 0.86-0.98; 0.66-0.85), respectively. CONCLUSIONS PWI-derived thresholds separating viable tumor from treatment changes demonstrate relatively good accuracy in individual studies. However, because of significant variability in optimal reported thresholds and other limitations in the existing body of literature, further investigation and standardization is needed before implementing any particular quantitative PWI strategy across institutions.
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Affiliation(s)
- Praneil Patel
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
| | - Hediyeh Baradaran
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
| | - Diana Delgado
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
| | - Gulce Askin
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
| | - Paul Christos
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
| | - Apostolos John Tsiouris
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medical College/New York-Presbyterian Hospital, New York, New York (P.P., H.B., A.J.T., A.G.); Samuel J. Wood Library & C. V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, New York (D.D.); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York (G.A., P.C.)
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Choi YS, Lee HJ, Ahn SS, Chang JH, Kang SG, Kim EH, Kim SH, Lee SK. Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient. Eur Radiol 2016; 27:1344-1351. [DOI: 10.1007/s00330-016-4484-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 06/05/2016] [Accepted: 06/21/2016] [Indexed: 12/18/2022]
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Choi YJ, Lee JH, Sung YS, Yoon RG, Park JE, Nam SY, Baek JH. Value of Dynamic Contrast-Enhanced MRI to Detect Local Tumor Recurrence in Primary Head and Neck Cancer Patients. Medicine (Baltimore) 2016; 95:e3698. [PMID: 27175712 PMCID: PMC4902554 DOI: 10.1097/md.0000000000003698] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Treatment failures in head and neck cancer patients are mainly related to locoregional tumor recurrence. The objective of the present study was to evaluate the diagnostic accuracy of model-free dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to detect local recurrence during the surveillance of head and neck cancer patients.Our retrospective study enrolled 24 patients with primary head and neck cancer who had undergone definitive treatment. Patients were grouped into local recurrence (n = 12) or posttreatment change (n = 12) groups according to the results of biopsy or clinicoradiologic follow-up. The types of time-signal intensity (TSI) curves were classified as follows: "progressive increment" as type I, "plateau" as type II, and "washout" as type III. TSI curve types and their parameters (i.e., wash-in, Emax, Tmax, area under the curve [AUC]60, AUC90, and AUC120) were compared between the 2 study groups.The distributions of TSI curve types for local recurrence versus posttreatment change were statistically significant (P < 0.001) (i.e., 0% vs 83.3% for type I, 58.3% vs 16.7% for type II, and 41.7% vs 0% for type III). There were statistically significant differences in Emax, Tmax, and all of the AUC parameters between 2 groups (P < 0.0083 [0.05/6]). Receiver operating characteristic (ROC) curve analyses indicated that the TSI curve type was the best predictor of local recurrence with a sensitivity of 100% (95% CI, 73.5-100.0) and a specificity of 83.3% (95% CI, 51.6-97.9) (cutoff with type II).Model-free DCE-MRI using TSI curves and TSI curve-derived parameters detects local recurrence in head and neck cancer patients with a high diagnostic accuracy.
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Affiliation(s)
- Young Jun Choi
- From the Department of Radiology and Research Institute of Radiology (YJC, JHL, YSS, RGY, JEP, JHB); and Department of Otolaryngology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea (SYN)
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Filice S, Crisi G. Dynamic Contrast-Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function. J Neuroimaging 2015; 26:124-9. [PMID: 25923172 DOI: 10.1111/jon.12254] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 03/26/2015] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE The aim of this study was to evaluate the differences in dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) perfusion estimates of high-grade brain gliomas (HGG) due to the use of an input function (IF) obtained respectively from arterial (AIF) and venous (VIF) approaches by two different commercially available software applications. METHODS This prospective study includes 20 patients with pathologically confirmed diagnosis of high-grade gliomas. The data source was processed by using two DCE dedicated commercial packages, both based on the extended Toft model, but the first customized to obtain input function from arterial measurement and the second from sagittal sinus sampling. The quantitative parametric perfusion maps estimated from the two software packages were compared by means of a region of interest (ROI) analysis. The resulting input functions from venous and arterial data were also compared. RESULTS No significant difference has been found between the perfusion parameters obtained with the two different software packages (P-value < .05). The comparison of the VIFs and AIFs obtained by the two packages showed no statistical differences. CONCLUSIONS Direct comparison of DCE-MRI measurements with IF generated by means of arterial or venous waveform led to no statistical difference in quantitative metrics for evaluating HGG. However, additional research involving DCE-MRI acquisition protocols and post-processing would be beneficial to further substantiate the effectiveness of venous approach as the IF method compared with arterial-based IF measurement.
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Affiliation(s)
- Silvano Filice
- Department of Medical Physics and the Department of Neuroradiology, University Hospital of Parma, Parma, Italy
| | - Girolamo Crisi
- Department of Medical Physics and the Department of Neuroradiology, University Hospital of Parma, Parma, Italy
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