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.

Coronavirus disease 2019 and radiation oncology-survey on the impact of the severe acute respiratory syndrome coronavirus 2 pandemic on health care professionals in radiation oncology.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has changed the lives of most humans worldwide. The aim of this study was to evaluate the impact of the SARS-CoV­2 pandemic on health care professionals (HCPs) in radiation oncology facilities. METHODS: We distributed an online survey to HCPs in radiation oncology (physicians, medical physics experts, radiology assistants/radiation therapists, nurses, and administrative personnel). The survey was completed by 334 participants between May 23 and June 9, 2020. RESULTS: In 66.2% of the cases, HCPs reported a shortage of protective clothing. The protective measures were regarded as very reasonable by 47.4%, while 0.8% regarded them as not reasonable (rather reasonable: 44.0%; less reasonable 7.8%). 29.0% of the participants had children who needed care. The most frequently used care options were public emergency childcare (36.1%) and private childcare (e.g. relatives/friends). HCPs reported about additional work burden (fully agreed: 27.2%, rather agreed: 34.4%, less agreed: 28.2%, not agreed: 10.2%), and reduced work satisfaction (fully agreed: 11.7%, rather agreed: 29.6%, less agreed: 39.8%, not agreed: 18.9%). 12.9% and 29.0% of the participants were fully or rather mentally strained (less mentally strained: 44.0%, not mentally strained: 14.1%). CONCLUSION: We must learn from this pandemic how to prepare for further outbreaks and similar conditions. This includes the vast availability of protective clothing and efficient tracing of infection chains among the HCPs, but also secured childcare programs and experienced mental health support are crucial. Further, work satisfaction and appreciation by employers is essential.

Feasibility and Outcome of PSMA-PET-Based Dose-Escalated Salvage Radiotherapy Versus Conventional Salvage Radiotherapy for Patients With Recurrent Prostate Cancer.

INTRODUCTION: Prostate-specific membrane antigen-positron emission tomography-(PSMA-PET) imaging facilitates dose-escalated salvage radiotherapy (DE-SRT) with simultaneous-integrated boost (SIB) for PET-positive lesions in patients with prostate cancer (PC). Therefore, we aimed to compare toxicity rates of DE-SRT with SIB to conventional SRT (C-SRT) without SIB and to report outcome. MATERIALS AND METHODS: We evaluated 199 patients who were treated with SRT between June 2014 and June 2020. 101 patients received DE-SRT with SIB for PET-positive local recurrence and/or PET-positive lymph nodes. 98 patients were treated with C-SRT to the prostate bed +/- elective pelvic lymphatic pathways without SIB. All patients received PSMA-PET imaging prior to DE-SRT ([68Ga]PSMA-11: 45.5%; [18F]-labeled PSMA: 54.5%). Toxicity rates for early (<6 months) and late (>6 months) gastrointestinal (GI) toxicities rectal bleeding, proctitis, stool incontinence, and genitourinary (GU) toxicities hematuria, cystitis, urine incontinence, urinary obstruction, and erectile dysfunction were assessed. Further, we analyzed the outcome with disease-free survival (DFS) and prostate-specific antigen (PSA) response. RESULTS: The overall toxicity rates for early GI (C-SRT: 2.1%, DE-SRT: 1.0%) and late GI (C-SRT: 1.4%, DE-SRT: 5.3%) toxicities ≥ grade 2 were similar. Early GU (C-SRT: 2.1%, DE-SRT: 3.0%) and late GU (C-SRT: 11.0%, DE-SRT: 14.7%) toxicities ≥ grade 2 were comparable, as well. Early and late toxicity rates did not differ significantly between DE-SRT versus C-SRT in all subcategories (p>0.05). PSA response (PSA ≤0.2 ng/ml) in the overall group of patients with DE-SRT was 75.0% and 86.4% at first and last follow-up, respectively. CONCLUSION: DE-SRT showed no significantly increased toxicity rates compared with C-SRT and thus is feasible. The outcome of DE-SRT showed good results. Therefore, DE-SRT with a PSMA-PET-based SIB can be considered for the personalized treatment in patients with recurrent PC.

Analysis of using high-precision radiotherapy in the treatment of liver metastases regarding toxicity and survival.

BACKGROUND: Hepatic metastases occur frequently in the context of many tumor entities. Patients with colorectal carcinoma have already developed liver metastases in 20% at the time of diagnosis, and 25-50% develop metastases in the further course of the disease and therapy. The frequent manifestation and the variable appearance of liver metastases result in an interdisciplinary challenge, regarding treatment management. The aim of this study was to evaluate high-precision stereotactic body radiotherapy (SBRT) for liver metastases. METHODS: A cohort of 115 patients with 150 irradiated liver metastases was analyzed. All metastases were treated between May 2004 and January 2020 using SBRT. A contrast-enhanced computed tomography (CT) was performed in all patients for treatment planning, followed by image-guided high-precision radiotherapy using cone-beam CT. A median cumulative dose of 35 Gy and a median single dose of 7 Gy was applied. RESULTS: Median OS was 20.4 months and median LC was 35.1 months with a 1-year probability of local failure of 18% (95%-CI: 12.0-24.3%). In this cohort, 18 patients were still alive at the time of evaluation. The median FU-time in total was 11.4 months and for living patients 26.6 months. 70.4% of patients suffered from acute toxicities. There were several cases of grade 1 and 2 toxicities, such as constipation (13.9%), nausea (24.4%), loss of appetite (7.8%), vomiting (10.4%), diarrhea (7.8%), and abdominal pain (16.5%). 10 patients (8.7%) suffered from grade 3 toxicities. Late toxicities affected 42.6% of patients, the majority of these affected the gastrointestinal system. CONCLUSION: SBRT is becoming increasingly important in the field of radiation oncology. It has evolved to be a highly effective treatment for primary and metastasized tumors, and offers a semi-curative treatment option also in the case of oligometastatic patients. Overall, it represents a very effective and well-tolerated therapy option to treat hepatic metastases. Based on the results of this work and the studies already available, high-precision radiotherapy should be considered as a valid and promising treatment alternative in the interdisciplinary discussion.

Web-Based Patient Self-Reported Outcome After Radiotherapy in Adolescents and Young Adults With Cancer: Survey on Acceptance of Digital Tools.

BACKGROUND: eHealth and mobile health (mHealth) are an evolving trend in the medical field. The acceptance of digital tools is high, and the need is growing. OBJECTIVE: Young adults (18-40 years) confronted with a cancer diagnosis present unique needs and require special care. They often have a strong affinity and are familiar with modern technology. On that account, we implemented a web-based symptom and quality of life (QoL) assessment to address patients' attitudes and willingness to use mHealth tools. The study also aims to evaluate sociodemographic parameters that could influence patients' opinions. METHODS: A total of 380 young patients aged 18-40 treated with radiotherapy between 2002 and 2017 were included in the trial. We assessed QoL via the European Organization for Research and Treatment of Cancer-Core 30 (EORTC C30) questionnaire and added general questions about mHealth technology. The added questions inquired patients' opinions regarding general aspects, including technical advances in medicine, mobile and app assistance during cancer treatment, data transfer, and app-specific features. The survey was conducted for 12 months. Participation was voluntary and pseudonymized; prior written consent was obtained. RESULTS: We achieved a participation rate of 57.6% (219/380) and a completion rate of 50.2% (110/219). The median age was 33 years (range 18-40). Of all participants, 89.1% (98/110) considered new technologies in medicine as positive; 10.9% (12/110) answered with neutral. Nearly all patients (96.4%, 106/110) stated that they would send further data via a web-based platform. Of all, 96.4% (106/110) considered the provided pseudonymization of their data as safe. We further asked the patients if they would use a mobile app for symptom and QoL assessment similar to the present web-based system: 74.5% (82/110) answered with yes and 25.5% (28/110) said they would not use a mobile app in the future. We tested the willingness to use an app on several sociodemographic parameters, such as age, gender, education, health insurance status, and cancer-related parameters: tumor stage, time since radiation treatment, and treatment intention. None of these parameters correlated with app use in this group of young adults. Patients who were generally positive regarding using an app rated several possible functions of a future app. The 3 most requested features were appointment reminders (89.0%, 73/82), contact overview of all involved clinics and physicians (87%, 71/82), and making an appointment via app (78%, 64/82). CONCLUSIONS: eHealth and mHealth tools should be available as an integrated part of a comprehensive cancer care approach. It provides automated, thorough documentation of health parameters during therapy and follow-up for doctors, medical staff, and tumor patients to optimize treatment. With this study, we could show that young adults are the ideal patient population to use eHealth/mHealth tools. Such tools offer further digital support and improve the patients' need for constant QoL during cancer care.

Multi-institutional Analysis of Prognostic Factors and Outcomes After Hypofractionated Stereotactic Radiotherapy to the Resection Cavity in Patients With Brain Metastases.

IMPORTANCE: For brain metastases, the combination of neurosurgical resection and postoperative hypofractionated stereotactic radiotherapy (HSRT) is an emerging therapeutic approach preferred to the prior practice of postoperative whole-brain radiotherapy. However, mature large-scale outcome data are lacking. OBJECTIVE: To evaluate outcomes and prognostic factors after HSRT to the resection cavity in patients with brain metastases. DESIGN, SETTING, AND PARTICIPANTS: An international, multi-institutional cohort study was performed in 558 patients with resected brain metastases and postoperative HSRT treated between December 1, 2003, and October 31, 2019, in 1 of 6 participating centers. Exclusion criteria were prior cranial radiotherapy (including whole-brain radiotherapy) and early termination of treatment. EXPOSURES: A median total dose of 30 Gy (range, 18-35 Gy) and a dose per fraction of 6 Gy (range, 5-10.7 Gy) were applied. MAIN OUTCOMES AND MEASURES: The primary end points were overall survival, local control (LC), and the analysis of prognostic factors associated with overall survival and LC. Secondary end points included distant intracranial failure, distant progression, and the incidence of neurologic toxicity. RESULTS: A total of 558 patients (mean [SD] age, 61 [0.50] years; 301 [53.9%] female) with 581 resected cavities were analyzed. The median follow-up was 12.3 months (interquartile range, 5.0-25.3 months). Overall survival was 65% at 1 year, 46% at 2 years, and 33% at 3 years, whereas LC was 84% at 1 year, 75% at 2 years, and 71% at 3 years. Radiation necrosis was present in 48 patients (8.6%) and leptomeningeal disease in 73 patients (13.1%). Neurologic toxic events according to the Common Terminology Criteria for Adverse Events grade 3 or higher occurred in 16 patients (2.8%) less than 6 months and 24 patients (4.1%) greater than 6 months after treatment. Multivariate analysis identified a Karnofsky Performance Status score of 80% or greater (hazard ratio [HR], 0.61; 95% CI, 0.46-0.82; P < .001), 22 to 33 days between resection and radiotherapy (HR, 1.50; 95% CI, 1.07-2.10; P = .02), and a controlled primary tumor (HR, 0.69; 95% CI, 0.52-0.90; P = .007) as prognostic factors associated with overall survival. For LC, a single brain metastasis (HR, 0.57; 95% CI, 0.35-0.93; P = .03) and a controlled primary tumor (HR, 0.59; 95% CI, 0.39-0.92; P = .02) were significant in the multivariate analysis. CONCLUSIONS AND RELEVANCE: To date, this cohort study includes one of the largest series of patients with brain metastases and postoperative HSRT and appears to confirm an excellent risk-benefit profile of local HSRT to the resection cavity. Additional studies will help determine radiation dose-volume parameters and provide a better understanding of synergistic effects with systemic and immunotherapies.