Paul Manning1,2,3, Shadi Daghighi4,5, Matthew K Rajaratnam5, Sowmya Parthiban5, Naeim Bahrami5, Anders M Dale4,5,6, Divya Bolar4,7, David E Piccioni6, Carrie R McDonald5,6,8, Nikdokht Farid4,5. 1. Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA. pmanning@ucsd.edu. 2. Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA. pmanning@ucsd.edu. 3. Department of Radiology, University of California, San Diego, 200 West Arbor Drive, Mailbox # 8756, San Diego, CA, 92103, USA. pmanning@ucsd.edu. 4. Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA. 5. Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA. 6. Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA. 7. Center for Functional Magnetic Resonance Imaging, University of California, San Diego, La Jolla, CA, 92037, USA. 8. Department of Psychiatry, University of California, San Diego, La Jolla, CA, 92037, USA.
Abstract
PURPOSE: To use 3D pseudocontinuous arterial spin labeling (3D PCASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion MRI to differentiate progressive disease from pseudoprogression in patients with glioblastoma (GBM). METHODS: Thirty-two patients with GBM who developed progressively enhancing lesions within the radiation field following resection and chemoradiation were included in this retrospective, single-institution study. The updated modified RANO criteria were used to establish progressive disease or pseudoprogression. Following 3D PCASL and DSC MR imaging, perfusion parameter estimates of cerebral blood flow (ASL-nCBF and DSC-nrCBF) and cerebral blood volume (DSC-nrCBV) were calculated. Additionally, contrast enhanced volumes were measured. Mann-Whitney U tests were used to compare groups. Linear discriminant analysis (LDA) and area under receiver operator characteristic curve (AUC) analyses were used to evaluate performance of each perfusion parameter and to determine optimal cut-off points. RESULTS: All perfusion parameter measurements were higher in patients with progressive disease (mean, 95% CI ASL-nCBF 2.48, [2.03, 2.93]; DSC-nrCBF = 2.27, [1.85, 2.69]; DSC-nrCBV = 3.51, [2.37, 4.66]) compared to pseudoprogression (mean, 95% CI ASL-nCBF 0.99, [0.47, 1.52]; DSC-nrCBF = 1.05, [0.36, 1.74]; DSC-nCBV = 1.19, [0.34, 2.05]), and findings were significant at the p < 0.0125 level (p = 0.001, 0.003, 0.002; effect size: Cohen's d = 1.48, 1.27, and 0.92). Contrast enhanced volumes were not significantly different between groups (p > 0.447). All perfusion parameters demonstrated high AUC (0.954 for ASL-nCBF, 0.867 for DSC-nrCBF, and 0.891 for DSC-nrCBV), however, ASL-nCBF demonstrated the highest AUC and misclassified the fewest cases (N = 6). Lesions correctly classified by ASL but misclassified by DSC were located along the skull base or adjacent to large resection cavities with residual blood products, at areas of increased susceptibility. CONCLUSION: Both 3D PCASL and DSC perfusion MRI techniques have nearly equivalent performance for the differentiation of progressive disease from pseudoprogression in patients with GBM. However, 3D PCASL is less sensitive to susceptibility artifact and may allow for improved classification in select cases.
PURPOSE: To use 3D pseudocontinuous arterial spin labeling (3D PCASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion MRI to differentiate progressive disease from pseudoprogression in patients with glioblastoma (GBM). METHODS: Thirty-two patients with GBM who developed progressively enhancing lesions within the radiation field following resection and chemoradiation were included in this retrospective, single-institution study. The updated modified RANO criteria were used to establish progressive disease or pseudoprogression. Following 3D PCASL and DSC MR imaging, perfusion parameter estimates of cerebral blood flow (ASL-nCBF and DSC-nrCBF) and cerebral blood volume (DSC-nrCBV) were calculated. Additionally, contrast enhanced volumes were measured. Mann-Whitney U tests were used to compare groups. Linear discriminant analysis (LDA) and area under receiver operator characteristic curve (AUC) analyses were used to evaluate performance of each perfusion parameter and to determine optimal cut-off points. RESULTS: All perfusion parameter measurements were higher in patients with progressive disease (mean, 95% CI ASL-nCBF 2.48, [2.03, 2.93]; DSC-nrCBF = 2.27, [1.85, 2.69]; DSC-nrCBV = 3.51, [2.37, 4.66]) compared to pseudoprogression (mean, 95% CI ASL-nCBF 0.99, [0.47, 1.52]; DSC-nrCBF = 1.05, [0.36, 1.74]; DSC-nCBV = 1.19, [0.34, 2.05]), and findings were significant at the p < 0.0125 level (p = 0.001, 0.003, 0.002; effect size: Cohen's d = 1.48, 1.27, and 0.92). Contrast enhanced volumes were not significantly different between groups (p > 0.447). All perfusion parameters demonstrated high AUC (0.954 for ASL-nCBF, 0.867 for DSC-nrCBF, and 0.891 for DSC-nrCBV), however, ASL-nCBF demonstrated the highest AUC and misclassified the fewest cases (N = 6). Lesions correctly classified by ASL but misclassified by DSC were located along the skull base or adjacent to large resection cavities with residual blood products, at areas of increased susceptibility. CONCLUSION: Both 3D PCASL and DSC perfusion MRI techniques have nearly equivalent performance for the differentiation of progressive disease from pseudoprogression in patients with GBM. However, 3D PCASL is less sensitive to susceptibility artifact and may allow for improved classification in select cases.
Authors: Anna Lavrova; Wouter H T Teunissen; Esther A H Warnert; Martin van den Bent; Marion Smits Journal: Front Oncol Date: 2022-05-20 Impact factor: 5.738
Authors: Yan Li; Yiqi Ma; Zijun Wu; Ruoxi Xie; Fanxin Zeng; Huawei Cai; Su Lui; Bin Song; Lei Chen; Min Wu Journal: Front Immunol Date: 2021-11-25 Impact factor: 7.561
Authors: Thomas C Booth; Mariusz Grzeda; Alysha Chelliah; Andrei Roman; Ayisha Al Busaidi; Carmen Dragos; Haris Shuaib; Aysha Luis; Ayesha Mirchandani; Burcu Alparslan; Nina Mansoor; Jose Lavrador; Francesco Vergani; Keyoumars Ashkan; Marc Modat; Sebastien Ourselin Journal: Front Oncol Date: 2022-01-31 Impact factor: 6.244