Assessment of the hypervascularized fraction of glioblastomas using a volume analysis of dynamic susceptibility contrast-enhanced MRI may help to identify pseudoprogression.

Purpose: Although perfusion magnetic resonance imaging (MRI) is widely used to identify pseudoprogression, this advanced technique lacks clinical reliability. Our aim was to develop a parameter assessing the hypervascularized fraction of glioblastomas based on volume analysis of dynamic susceptibility contrast-enhanced MRI and evaluate its performance in the diagnosis of pseudoprogression.

Methods: Patients with primary glioblastoma showing lesion progression on the first follow-up MRI after chemoradiotherapy were enrolled retrospectively. On both initial and first follow-up MRIs, the leakage-corrected cerebral blood volume (CBV) maps were post-processed using the conventional hot-spot method and a volume method, after manual segmentation of the contrast-enhanced delineated lesion. The maximum CBV (rCBVmax) was calculated with both methods. Secondly, the threshold of 2 was applied to the CBV values contained in the entire segmented volume, defining our new parameter: %rCBV>2. The probability of pseudoprogression based on rCBVmax and %rCBV>2 was calculated in logistic regression models and diagnostic performance assessed by receiving operator characteristic curves.

Results: Out of 25 patients, 11 (44%) were classified with pseudoprogression and 14 (56%) with true progression based on the Response Assessement in Neuro-Oncology criteria. rCBVmax was lower for pseudoprogression (3.4 vs. 7.6; p = 0.033) on early follow-up MRI. %rCBV>2, was lower for pseudoprogression on both initial (57.5% vs. 71.3%; p = 0.033) and early follow-up MRIs (22.1% vs. 51.8%; p = 0.0006). On early follow-up MRI, %rCBV>2 had the largest area under the curve for the diagnosis of pseudoprogression: 0.909 [0.725-0.986].

Conclusion: The fraction of hypervascularization of glioblastomas as assessed by %rCBV>2 was lower in tumours that subsequently developed pseudoprogression both on the initial and early follow-up MRIs. This fractional parameter may help identify pseudoprogression with greater accuracy than rCBVmax.