Radiomics-based prediction of local control in patients with brain metastases following postoperative stereotactic radiotherapy.

BACKGROUND: Surgical resection is the standard of care for patients with large or symptomatic brain metastases (BMs). Despite improved local control after adjuvant stereotactic radiotherapy, the risk of local failure (LF) persists. Therefore, we aimed to develop and externally validate a pre-therapeutic radiomics-based prediction tool to identify patients at high LF risk. METHODS: Data were collected from A Multicenter Analysis of Stereotactic Radiotherapy to the Resection Cavity of Brain Metastases (AURORA) retrospective study (training cohort: 253 patients from two centers; external test cohort: 99 patients from five centers). Radiomic features were extracted from the contrast-enhancing BM (T1-CE MRI sequence) and the surrounding edema (FLAIR sequence). Different combinations of radiomic and clinical features were compared. The final models were trained on the entire training cohort with the best parameter set previously determined by internal 5-fold cross-validation and tested on the external test set. RESULTS: The best performance in the external test was achieved by an elastic net regression model trained with a combination of radiomic and clinical features with a concordance index (CI) of 0.77, outperforming any clinical model (best CI: 0.70). The model effectively stratified patients by LF risk in a Kaplan-Meier analysis (p < 0.001) and demonstrated an incremental net clinical benefit. At 24 months, we found LF in 9% and 74% of the low and high-risk groups, respectively. CONCLUSIONS: A combination of clinical and radiomic features predicted freedom from LF better than any clinical feature set alone. Patients at high risk for LF may benefit from stricter follow-up routines or intensified therapy.

Identifying core MRI sequences for reliable automatic brain metastasis segmentation.

BACKGROUND: Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation. METHODS: We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers. A baseline 3D U-Net with all four sequences and six U-Nets with plausible sequence combinations (T1-CE, T1, T2-FLAIR, T1-CE + T2-FLAIR, T1-CE + T1 + T2-FLAIR, T1-CE + T1) were trained on 239 patients from two centers and subsequently tested on an external cohort of 100 patients from five centers. RESULTS: The model based on T1-CE alone achieved the best segmentation performance for BM segmentation with a median Dice similarity coefficient (DSC) of 0.96. Models trained without T1-CE performed worse (T1-only: DSC = 0.70 and T2-FLAIR-only: DSC = 0.73). For edema segmentation, models that included both T1-CE and T2-FLAIR performed best (DSC = 0.93), while the remaining four models without simultaneous inclusion of these both sequences reached a median DSC of 0.81-0.89. CONCLUSIONS: A T1-CE-only protocol suffices for the segmentation of BMs. The combination of T1-CE and T2-FLAIR is important for edema segmentation. Missing either T1-CE or T2-FLAIR decreases performance. These findings may improve imaging routines by omitting unnecessary sequences, thus allowing for faster procedures in daily clinical practice while enabling optimal neural network-based target definitions.

Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study.

BACKGROUND: Stereotactic radiotherapy is a standard treatment option for patients with brain metastases. The planning target volume is based on gross tumor volume (GTV) segmentation. The aim of this work is to develop and validate a neural network for automatic GTV segmentation to accelerate clinical daily routine practice and minimize interobserver variability. METHODS: We analyzed MRIs (T1-weighted sequence ± contrast-enhancement, T2-weighted sequence, and FLAIR sequence) from 348 patients with at least one brain metastasis from different cancer primaries treated in six centers. To generate reference segmentations, all GTVs and the FLAIR hyperintense edematous regions were segmented manually. A 3D-U-Net was trained on a cohort of 260 patients from two centers to segment the GTV and the surrounding FLAIR hyperintense region. During training varying degrees of data augmentation were applied. Model validation was performed using an independent international multicenter test cohort (n = 88) including four centers. RESULTS: Our proposed U-Net reached a mean overall Dice similarity coefficient (DSC) of 0.92 ± 0.08 and a mean individual metastasis-wise DSC of 0.89 ± 0.11 in the external test cohort for GTV segmentation. Data augmentation improved the segmentation performance significantly. Detection of brain metastases was effective with a mean F1-Score of 0.93 ± 0.16. The model performance was stable independent of the center (p = 0.3). There was no correlation between metastasis volume and DSC (Pearson correlation coefficient 0.07). CONCLUSION: Reliable automated segmentation of brain metastases with neural networks is possible and may support radiotherapy planning by providing more objective GTV definitions.

Treatment-outcome for synchronous head-and-neck and oesophageal squamous cell carcinoma.

BACKGROUND AND PURPOSE: Although head & neck and oesophageal carcinomas occur synchronously in up to 12%, almost no data on feasibility and outcome after radiotherapy are available. MATERIALS AND METHODS: From 1989 to 2002, 24 patients were treated at Tuebingen University and Fulda hospital with a radiation based, curative approach. These were analyzed retrospectively. RESULTS: The median overall survival was 37 (1-69) months with a few long-term survivors with a median follow-up of 26 months for patients at risk. 7 local recurrences occurred. No major toxicity was seen. DISCUSSION: Even though the prognosis of synchronous head & neck and oesophageal carcinomas is grim, long-term survival is possible. A radiation-based approach is feasible and can be chosen for a curative treatment approach which we recommend.

Prolonged infusional topotecan and accelerated hyperfractionated 3d-conformal radiation in patients with newly diagnosed glioblastoma--a phase I study.

PURPOSE: Topotecan has demonstrated exceptional central nervous system penetration as well as radiosensitizing properties in glioblastoma xenografts [Chastagner et al., Int J Radiat Oncol Biol Phy 50: 777-782, 2001]. This phase I trial was performed to determine the maximum tolerated dose and the recommended dose of topotecan continuous infusion administered together with concomitant radiotherapy in patients with glioblastoma. PATIENTS AND METHODS: A total of 20 patients were treated in this trial. Twenty one day topotecan continuous infusion was escalated from 0.3 mg/m2/d in increments of 0.1 mg/m2/d and cohorts of 3-6 patients until maximum tolerated dose was reached; Three-dimensional (3d) conformal radiotherapy was applied concurrently twice daily with a fraction size of 1.75 Gy up to 57.75 Gy total dose. Three additional cycles of maintenance topotecan chemotherapy were scheduled. RESULTS: Fifty-three courses were performed in 5 dose levels (0.3 mg/m2/d: 12 cycles, 0.4 mg/m2/d: 6 cycles, 0.5 mg/m2/d: 10 cycles, 0.6 mg/m2/d: 6 cycles, 0.7 mg/m2/d: 19 cycles). Maximum tolerated dose was reached at dose level 5 (0.7 mg/m2/d), because 3/7 patients suffered from dose limiting toxicity. These were febrile sinusitis, bacterial sepsis and grade 4 thrombocytopenia. Neutropenia of grade 4 was encountered in 2 cycles (0.5 and 0.7 mg/m2/d). Response data were available in 17 patients, 3 of which (18%) achieved partial remission, 12 (71%) stable disease throughout the observation period and 2 (11%) progressive disease. CONCLUSION: The recommended dose for further trials will be 0.6 mg/m2/d topotecan administered as 21 days continuous infusion in combination with accelerated 3d conformal radiation.