Chao Li1,2, Shuo Wang3, Jiun-Lin Yan1,4,5, Turid Torheim6,7, Natalie R Boonzaier1,8, Rohitashwa Sinha1, Tomasz Matys3,9, Florian Markowetz6,7, Stephen J Price1,10. 1. 1Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences. 2. 2Department of Neurosurgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. 3. 3Department of Radiology. 4. 4Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Taiwan. 5. 5Chang Gung University College of Medicine, Taoyuan, Taiwan. 6. 6Cancer Research UK Cambridge Institute, and. 7. 7CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge. 8. 8Developmental Imaging and Biophysics Section, Great Ormond Street Institute of Child Health, University College London; and. 9. 9Cancer Trials Unit, Department of Oncology, Addenbrooke's Hospital, Cambridge, United Kingdom. 10. 10Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, United Kingdom.
Abstract
OBJECTIVE: The objective of this study was to characterize the abnormalities revealed by diffusion tensor imaging (DTI) using MR spectroscopy (MRS) and perfusion imaging, and to evaluate the prognostic value of a proposed quantitative measure of tumor invasiveness by combining contrast-enhancing (CE) and DTI abnormalities in patients with glioblastoma. METHODS: Eighty-four patients with glioblastoma were recruited preoperatively. DTI was decomposed into isotropic (p) and anisotropic (q) components. The relative cerebral blood volume (rCBV) was calculated from the dynamic susceptibility contrast imaging. Values of N-acetylaspartate, myoinositol, choline (Cho), lactate (Lac), and glutamate + glutamine (Glx) were measured from multivoxel MRS and normalized as ratios to creatine (Cr). Tumor regions of interest (ROIs) were manually segmented from the CE T1-weighted (CE-ROI) and DTI-q (q-ROI) maps. Perfusion and metabolic characteristics of these ROIs were measured and compared. The relative invasiveness coefficient (RIC) was calculated as a ratio of the characteristic radii of CE-ROI and q-ROI. The prognostic significance of RIC was tested using Kaplan-Meier and multivariate Cox regression analyses. RESULTS: The Cho/Cr, Lac/Cr, and Glx/Cr in q-ROI were significantly higher than CE-ROI (p = 0.004, p = 0.005, and p = 0.007, respectively). CE-ROI had significantly higher rCBV values than q-ROI (p < 0.001). A higher RIC was associated with worse survival in a multivariate overall survival (OS) model (hazard ratio [HR] 1.40, 95% confidence interval [CI] 1.06-1.85, p = 0.016) and progression-free survival (PFS) model (HR 1.55, 95% CI 1.16-2.07, p = 0.003). An RIC cutoff value of 0.89 significantly predicted shorter OS (median 384 vs 605 days, p = 0.002) and PFS (median 244 vs 406 days, p = 0.001). CONCLUSIONS: DTI-q abnormalities displayed higher tumor load and hypoxic signatures compared with CE abnormalities, whereas CE regions potentially represented the tumor proliferation edge. Integrating the extents of invasion visualized by DTI-q and CE images into clinical practice may lead to improved treatment efficacy.
OBJECTIVE: The objective of this study was to characterize the abnormalities revealed by diffusion tensor imaging (DTI) using MR spectroscopy (MRS) and perfusion imaging, and to evaluate the prognostic value of a proposed quantitative measure of tumor invasiveness by combining contrast-enhancing (CE) and DTI abnormalities in patients with glioblastoma. METHODS: Eighty-four patients with glioblastoma were recruited preoperatively. DTI was decomposed into isotropic (p) and anisotropic (q) components. The relative cerebral blood volume (rCBV) was calculated from the dynamic susceptibility contrast imaging. Values of N-acetylaspartate, myoinositol, choline (Cho), lactate (Lac), and glutamate + glutamine (Glx) were measured from multivoxel MRS and normalized as ratios to creatine (Cr). Tumor regions of interest (ROIs) were manually segmented from the CE T1-weighted (CE-ROI) and DTI-q (q-ROI) maps. Perfusion and metabolic characteristics of these ROIs were measured and compared. The relative invasiveness coefficient (RIC) was calculated as a ratio of the characteristic radii of CE-ROI and q-ROI. The prognostic significance of RIC was tested using Kaplan-Meier and multivariate Cox regression analyses. RESULTS: The Cho/Cr, Lac/Cr, and Glx/Cr in q-ROI were significantly higher than CE-ROI (p = 0.004, p = 0.005, and p = 0.007, respectively). CE-ROI had significantly higher rCBV values than q-ROI (p < 0.001). A higher RIC was associated with worse survival in a multivariate overall survival (OS) model (hazard ratio [HR] 1.40, 95% confidence interval [CI] 1.06-1.85, p = 0.016) and progression-free survival (PFS) model (HR 1.55, 95% CI 1.16-2.07, p = 0.003). An RIC cutoff value of 0.89 significantly predicted shorter OS (median 384 vs 605 days, p = 0.002) and PFS (median 244 vs 406 days, p = 0.001). CONCLUSIONS:DTI-q abnormalities displayed higher tumor load and hypoxic signatures compared with CE abnormalities, whereas CE regions potentially represented the tumor proliferation edge. Integrating the extents of invasion visualized by DTI-q and CE images into clinical practice may lead to improved treatment efficacy.
Entities:
Keywords:
5-ALA = 5-aminolevulinic acid; CE = contrast enhancing; CI = confidence interval; CSI = chemical shift imaging; Cho = choline; Cr = creatine; DSC = dynamic susceptibility contrast-enhancement; DTI = diffusion tensor imaging; DTI-p = DTI-isotropic; DTI-q = DTI-anisotropic; EOR = extent of resection; FSL = Functional MRI of the Brain Software Library; Glx = glutamate + glutamine; HR = hazard ratio; IDH-1 = isocitrate dehydrogenase 1; Lac = lactate; MGMT = O-6-methylguanine-DNA methyltransferase; MRI; MRS = magnetic resonance spectroscopy; NAA = N-acetylaspartate; NAWM = normal-appearing white matter; OS = overall survival; PFS = progression-free survival; RIC = relative invasiveness coefficient; ROI = region of interest; diffusion tensor imaging; glioblastoma; mIns = myoinositol; magnetic resonance spectroscopy; oncology; perfusion imaging; prognosis; rCBV = relative cerebral blood volume
Authors: María Carcelén; Carlos Velásquez; Veronica Vidal; Olga Gutierrez; Jose L Fernandez-Luna Journal: Int J Mol Sci Date: 2022-01-11 Impact factor: 5.923