ABSTRACT
Background: Distinguishing 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. Methods: Structural 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. Results: We 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); Pâ =â .03) with a median survival time of 13 months (compared to 22 months of subgroup 2). Conclusions: Our 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.
ABSTRACT
OBJECTIVE: Doppler ultrasonography (DUS) is used as initial measurement to diagnose and classify carotid artery stenosis. Local distorting factors such as vascular calcification can influence the ability to obtain DUS measurements. The DUS derived maximal systolic acceleration (ACCmax) provides a different way to determine the degree of stenosis. While conventional DUS parameters are measured at the stenosis itself, ACCmax is measured distal to the internal carotid artery (ICA) stenosis. The value of ACCmax in ICA stenosis was investigated in this study. MATERIAL AND METHODS: All carotid artery DUS studies of a tertiary academic center were reviewed from October 2007 until December 2017. Every ICA was included once. The ACCmax was compared to conventional DUS parameters: ICA peak systolic velocity (PSV), and PSV ratio (ICA PSV/ CCA PSV). ROC-curve analysis was used to evaluate accuracy of ACCmax, ICA PSV and PSV ratio as compared to CT-angiography (CTA) derived stenosis measurement as reference test. RESULTS: The study population consisted of 947 carotid arteries and was divided into 3 groups: <50% (710/947), 50-69% (109/947), and ≥70% (128/947). Between these groups ACCmax was significantly different. Strong correlations between ACCmax and ICA PSV (R2 0.88) and PSV ratio (R2 0.87) were found. In ROC subanalysis, the ACCmax had a sensitivity of 90% and a specificity of 89% to diagnose a ≥70% ICA stenosis, and a sensitivity of 82% and a specificity of 88% to diagnose a ≥50% ICA stenosis. For diagnosing a ≥50% ICA stenosis the area under the curve (AUC) of ACCmax (0.88) was significantly lower than the AUC of PSV ratio (0.94) and ICA PSV (0.94). To diagnose a ≥70% ICA stenosis there were no significant differences in AUC between ACCmax (0.89), PSV ratio (0.93) and ICA PSV (0.94). CONCLUSIONS: ACCmax is an interesting additional DUS measurement in determining the degree of ICA stenosis. ACCmax is measured distal to the stenosis and is not hampered by local distorting factors at the site of the stenosis. ACCmax can accurately diagnose an ICA stenosis, but was somewhat inferior compared to ICA PSV and PSV ratio to diagnose a ≥50% ICA stenosis.
