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About 20–40% of cancer patients develop brain metastases, causing significant morbidity and mortality. Stereotactic radiation treatment is an established option that delivers high dose radiation to the target while sparing the surrounding normal tissue. However, up to 20% of metastatic brain tumours progress despite stereotactic treatment, and it can take months before it is evident on follow-up imaging. An early predictor of radiation therapy outcome in terms of tumour local failure (LF) is crucial, and can facilitate treatment adjustments or allow for early salvage treatment. In this study, an MR-based radiomics framework was proposed to derive and investigate quantitative MRI (qMRI) biomarkers for the outcome of LF in brain metastasis patients treated with hypo-fractionated stereotactic radiation therapy (SRT). The qMRI biomarkers were constructed through a multi-step feature extraction/reduction/selection framework using the conventional MR imaging data acquired from 100 patients (133 lesions), and were applied in conjunction with machine learning techniques for outcome prediction and risk assessment. The results indicated that the majority of the features in the optimal qMRI biomarkers characterize the heterogeneity in the surrounding regions of tumour including edema and tumour/lesion margins. The optimal qMRI biomarker consisted of five features that predict the outcome of LF with an area under the curve (AUC) of 0.79, and a cross-validated sensitivity and specificity of 81% and 79%, respectively. The Kaplan-Meier analyses showed a statistically significant difference in local control (p-value < 0.0001) and overall survival (p = 0.01). Findings from this study are a step towards using qMRI for early prediction of local failure in brain metastasis patients treated with SRT. This may facilitate early adjustments in treatment, such as surgical resection or salvage radiation, that can potentially improve treatment outcomes. Investigations on larger cohorts of patients are, however, required for further validation of the technique. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to evaluate the prognostic value of dynamic susceptibility contrast (DSC) MR perfusion in elderly patients with glioblastomas (GBM). Methods: Thirty five patients aged ≥65 and 35 aged <65 years old, (referred to as elderly and younger, respectively) were included in this retrospective study. The median relative cerebral volume (rCBV) from the enhancing region (rCBV) and immediate peritumoral region (rCBV) and maximum rCBV from the enhancing region of the tumor (rCBV) were compared and correlated with survival data. Analysis was repeated after rCBVs were dichotomized into high and low values and after excluding elderly patients who did not receive postoperative chemoradiation (34.3 %). Kaplan-Meyer survival curves and parametric and semi-parametric regression tests were used for analysis. Results: All rCBV parameters were higher in elderly compared to younger patients ( p < 0.05). After adjustment for age, none were independently associated with shorter survival ( p > 0.05). After rCBV dichotomization into high and low values, high rCBV in elderly was independently associated with shorter survival compared to low rCBV in elderly, or any rCBV in younger patients ( p < 0.05). Conclusion: rCBV can be an imaging biomarker to identify a subgroup of GBM patients in the elderly with worse prognosis compared to others. Key Points: • GBM perfusion parameters are higher in elderly compared to younger patients. • rCBV can identify a subgroup of elderly patients with worse prognosis. • rCBV can be an imaging biomarker for prognostication in GBM. • The identified elderly patients may benefit from anti-angiogenic treatment. [ABSTRACT FROM AUTHOR]