BackgroundDistinguishing true tumor progression (TP) from treatment-induced abnormalities (eg, pseudo-progression (PP) after radiotherapy) on conventional MRI scans remains challenging in patients... Show moreBackgroundDistinguishing true tumor progression (TP) from treatment-induced abnormalities (eg, pseudo-progression (PP) after radiotherapy) on conventional MRI scans remains challenging in patients with a glioblastoma. We aimed to establish brain MRI phenotypes of glioblastomas early after treatment by combined analysis of structural and perfusion tumor characteristics and assessed the relation with recurrence rate and overall survival time.MethodsStructural and perfusion MR images of 67 patients at 3 months post-radiotherapy were visually scored by a neuroradiologist. In total 23 parameters were predefined and used for hierarchical clustering analysis. Progression status was assessed based on the clinical course of each patient 9 months after radiotherapy (or latest available). Multivariable Cox regression models were used to determine the association between the phenotypes, recurrence rate, and overall survival.ResultsWe established 4 subgroups with significantly different tumor MRI characteristics, representing distinct MRI phenotypes of glioblastomas: TP and PP rates did not differ significantly between subgroups. Regression analysis showed that patients in subgroup 1 (characterized by having mostly small and ellipsoid nodular enhancing lesions with some hyper-perfusion) had a significant association with increased mortality at 9 months (HR: 2.6 (CI: 1.1–6.3); P = .03) with a median survival time of 13 months (compared to 22 months of subgroup 2).ConclusionsOur study suggests that distinct MRI phenotypes of glioblastomas at 3 months post-radiotherapy can be indicative of overall survival, but does not aid in differentiating TP from PP. The early prognostic information our method provides might in the future be informative for prognostication of glioblastoma patients. Show less
Schmitz Abecassis, B.; Vinogradov, E.; Wijnen, J.P.; Harten, T. van; Wiegers, E.C.; Hoogduin, H.; ... ; Ercan, E. 2021
Purpose Current challenges of in vivo CEST imaging include overlapping signals from different pools. The overlap arises from closely resonating pools and/or the broad magnetization transfer... Show morePurpose Current challenges of in vivo CEST imaging include overlapping signals from different pools. The overlap arises from closely resonating pools and/or the broad magnetization transfer contrast (MTC) from macromolecules. This study aimed to evaluate the feasibility of variable delay multipulse (VDMP) CEST to separately assess solute pools with different chemical exchange rates in the human brain in vivo, while mitigating the MTC. Methods VDMP saturation buildup curves were simulated for amines, amides, and relayed nuclear Overhauser effect. VDMP data were acquired from glutamate and bovine serum albumin phantoms, and from six healthy volunteers at 7T. For the in vivo data, MTC removal was performed via a three-pool Lorentzian fitting. Different B-1 amplitudes and mixing times were used to evaluate CEST pools with different exchange rates. Results The results show the importance of removing MTC when applying VDMP in vivo and the influence of B-1 for distinguishing different pools. Finally, the optimal B-1 and mixing times to effectively saturate slow- and fast-exchanging components are also reported. Slow-exchanging amides and rNOE components could be distinguished when using B-1 = 1 mu T and t(mix) = 10 ms and 40 ms, respectively. Fast-exchanging components reached the highest saturation when using a B-1 = 2.8 mu T and t(mix) = 0 ms. Conclusion VDMP is a powerful CEST-editing tool, exploiting chemical exchange-rate differences. After MTC removal, it allows separate assessment of slow- and fast-exchanging solute pools in in vivo human brain. Show less
