MRI during radiotherapy of glioblastoma : Does MRI allow for prognostic stratification?

The impact of anatomical changes during photon or proton based radiation treatment on tumor dose in glioblastoma dose escalation trials

PURPOSE/OBJECTIVE

Most dose-escalation trials in glioblastoma patients integrate the escalated dose throughout the standard course by targeting a specific subvolume. We hypothesize that anatomical changes during irradiation may affect the dose coverage of this subvolume for both proton- and photon-based radiotherapy.

MATERIAL AND METHODS

For 24 glioblastoma patients a photon- and proton-based dose escalation treatment plan (of 75 Gy/30 fr) was simulated on the dedicated radiotherapy planning MRI obtained before treatment. The escalated dose was planned to cover the resection cavity and/or contrast enhancing lesion on the T1w post-gadolinium MRI sequence. To analyze the effect of anatomical changes during treatment, we evaluated on an additional MRI that was obtained during treatment the changes of the dose distribution on this specific high dose region.

RESULTS

The median time between the planning MRI and additional MRI was 26 days (range 16-37 days). The median time between the planning MRI and start of radiotherapy was relatively short (7 days, range 3-11 days). In 3 patients (12.5%) changes were observed which resulted in a substantial deterioration of both the photon and proton treatment plans. All these patients underwent a subtotal resection, and a decrease in dose coverage of more than 5% and 10% was observed for the photon- and proton-based treatment plans, respectively.

CONCLUSION

Our study showed that only for a limited number of patients anatomical changes during photon or proton based radiotherapy resulted in a potentially clinically relevant underdosage in the subvolume. Therefore, volume changes during treatment are unlikely to be responsible for the negative outcome of dose-escalation studies.

Evolution of the gross tumour volume extent during radiotherapy for glioblastomas

BACKGROUND AND PURPOSE

Tumour growth during radiotherapy may lead to geographical misses of the target volume. This study investigates the evolution of the tumour extent and evaluates the need for plan adaptation to ensure dose coverage of the target in glioblastoma patients.

MATERIALS AND METHODS

The prospective study included 29 patients referred for 59.4 Gy in 33 fractions. Magnetic resonance imaging (MRI) was performed at the time of treatment planning, at fraction 10, 20, 30, and three weeks after the end of radiotherapy. The gross tumour volume (GTV) was defined as the T1w contrast-enhanced region plus the surgical cavity on each MRI set. The relative GTV volume and the maximum distance (D_max) of the extent of the actual GTV outside the original GTV were measured. Based on the location of the actual GTV during radiotherapy and the original planned dose, a prospective clinical decision was made whether to adapt the treatment.

RESULTS

Dose coverage of the GTV during radiotherapy was not compromised, and none of the radiotherapy plans was adapted. The median D_max (range) was 5.7 (2.0-18.9) mm, 8.0 (2.0-27.4) mm, 8.0 (1.9-27.3) mm, and 8.9 (1.9-34.4) mm at fraction 10, 20, 30, and follow-up. The relative GTV volume and D_max observed at fraction 10 were correlated with the values observed at follow-up (R = 0.74, p < 0.001 and R = 0.79, p < 0.001, respectively).

CONCLUSION

Large variations in the GTV extent were observed, and changes often occurred early in the treatment. Plan adaptation for geographical misses was not performed in our cohort due to sufficient CTV margins.

Semantic imaging features predict disease progression and survival in glioblastoma multiforme patients

BACKGROUND

For glioblastoma (GBM), multiple prognostic factors have been identified. Semantic imaging features were shown to be predictive for survival prediction. No similar data have been generated for the prediction of progression. The aim of this study was to assess the predictive value of the semantic visually accessable REMBRANDT [repository for molecular brain neoplasia data] images (VASARI) imaging feature set for progression and survival, and the creation of joint prognostic models in combination with clinical and pathological information.

METHODS

189 patients were retrospectively analyzed. Age, Karnofsky performance status, gender, and MGMT promoter methylation and IDH mutation status were assessed. VASARI features were determined on pre- and postoperative MRIs. Predictive potential was assessed with univariate analyses and Kaplan-Meier survival curves. Following variable selection and resampling, multivariate Cox regression models were created. Predictive performance was tested on patient test sets and compared between groups. The frequency of selection for single variables and variable pairs was determined.

RESULTS

For progression free survival (PFS) and overall survival (OS), univariate significant associations were shown for 9 and 10 VASARI features, respectively. Multivariate models yielded concordance indices significantly different from random for the clinical, imaging, combined, and combined + MGMT models of 0.657, 0.636, 0.694, and 0.716 for OS, and 0.602, 0.604, 0.633, and 0.643 for PFS. "Multilocality," "deep white-matter invasion," "satellites," and "ependymal invasion" were over proportionally selected for multivariate model generation, underlining their importance.

CONCLUSIONS

We demonstrated a predictive value of several qualitative imaging features for progression and survival. The performance of prognostic models was increased by combining clinical, pathological, and imaging features.