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The value of interdisciplinary teams in improving outcomes and quality of care of patients with brain metastases remains uncertain, partly due to the lack of consensus on key indicators to evaluate interprofessional care. We aimed to obtain expert consensus across disciplines on indicators that evaluate the quality and value of brain metastases care. A steering committee of key opinion leaders curated relevant outcomes and process indicators from a literature review and a stakeholder needs assessment, and an international panel of physicians rated the outcomes and process indicators using a modified Delphi method. After three rounds, a consensus was reached on 29 indicators encompassing brain-directed oncological treatment, surgery, whole-brain radiotherapy, stereotactic radiosurgery, supportive or palliative care, and interdisciplinary team care. The Brain Metastases Quality-of-Care measure reflects the value and quality of brain metastases team-based care according to treatment modality and provides a benchmark of care for this under-studied patient population. The adoption, implementation, and sustainability of this set of indicators could help address the need expressed by patients with cancer, caregivers, and clinicians for more coordinated care across inpatient, outpatient, home, community, and tertiary academic settings.

Introduction NRG protocols for glioblastoma allow for clinical target volume (CTV) reductions at natural barriers; however, literature examining CTV contouring and the relevant white matter pathways is lacking. This study proposes consensus CTV guidelines, with a focus on areas of controversy while highlighting common errors in glioblastoma target delineation. Methods Ten academic radiation oncologists specializing in brain tumor treatment contoured CTVs on four glioblastoma cases. CTV expansions were based on NRG trial guidelines. Contour consensus was assessed and summarized by kappa statistics. A meeting was held to discuss the mathematically averaged contours and form consensus contours and recommendations. Results Contours of the cavity plus enhancement (mean kappa 0.69) and T2-FLAIR signal (mean kappa 0.74) showed moderate to substantial agreement. Experts were asked to trim off anatomic barriers while respecting pathways of spread to develop their CTVs. Submitted CTV_4600 (mean kappa 0.80) and CTV_6000 (mean kappa 0.81) contours showed substantial to near perfect agreement. Simultaneous truth and performance level estimation (STAPLE) contours were then reviewed and modified by group consensus. Anatomic trimming reduced the amount of total brain tissue planned for radiation targeting by a 13.6% (range 8.7–17.9%) mean proportional reduction. Areas for close scrutiny of target delineation were described, with accompanying recommendations. Conclusions Consensus contouring guidelines were established based on expert contours. Careful delineation of anatomic pathways and barriers to spread can spare radiation to uninvolved tissue without compromising target coverage. Further study is necessary to accurately define optimal target volumes beyond isometric expansion techniques for individual patients.

Brain metastases (BMs) account for a disproportionately high percentage of cancer morbidity and mortality. Historically, studies have focused on improving survival outcomes, and recent radiation oncology clinical trials have incorporated HRQOL and cognitive assessments. We are now equipped with a battery of assessments in the radiation oncology clinic, but there is a lack of consensus regarding how to incorporate them in modern clinical practice. Herein, we present validated assessments for BM patients, current recommendations for future clinical studies, and treatment advances that have improved HRQOL and cognitive outcomes for BM patients.

Patients with brain metastases (BMETS) need information about the prognosis and potential value of treatment options to make informed therapeutic decisions, but tools to predict survival in contemporary practice are scarce. We propose an Updated Recursive Partitioning Analysis (U-RPA) instrument to predict survival and benefit from brain-directed treatment (BDT) of contemporary patients. This was a retrospective analysis of patients with BMETS treated between 2017 and 2019. With survival as the primary endpoint, we calculated the U-RPA and generated estimates using Kaplan–Meier curves and hazard ratios. Of 862 eligible patients, 752 received BDT and 110 received best supportive care (BSC). Median overall survival with BDT and BSC was 9.3 and 1.3 months, respectively. Patients in RPA class 1, 2A, 2B and 3 who underwent BDT had median survival of 28.1, 14.7, 7.6 and 3.3 months, respectively. The median survival for patients in RPA 3 who received BDT (n = 147), WBRT (n = 79) and SRS (n = 54) was 3.3, 2.9 and 4.1 months, respectively. The U-RPA defines prognosis estimates, independent of tumor type and treatment modality, which can assist to make value-based care treatment decisions. The prognosis for patients in U-RPA class 2B and 3 remains poor, with consideration for early palliative care involvement in these cases.

Over 150,000 cancer patients will be diagnosed with brain metastases this year alone. Survival for those diagnosed with brain metastases remains poor despite multimodality management with surgery, chemotherapy, and radiation. Preventative strategies to mitigate brain metastases have met with mixed results. In leukemia and small cell lung cancer there are defined roles for preventative radiation to be delivered, which can result in improved local control and survival. There is a less defined role for preventative radiation in locally advanced non-small cell lung cancer and budding interest for radiation prevention in breast cancer. The potential impact preventative cranial irradiation may have on neurocognitive function and quality of life needs to be considered prior to its administration.

White matter injury is a known complication of whole brain radiation (WBRT). Little is known about the factors that predispose a patient to such injury. The current study used MR volumetrics to examine risk factors, in particular the influence of pre-treatment white matter health, in developing white matter change (WMC) following WBRT. Thirty-four patients with unilateral metastatic disease underwent FLAIR MRI pre-treatment and at several time points following treatment. The volume of abnormal FLAIR signal in the white matter was measured in the hemisphere contralateral to the diseased hemisphere at each time point. Analyses were restricted to the uninvolved hemisphere to allow for the measurement of WBRT effects without the potential confounding effects of the disease on imaging findings. The relationship between select pre-treatment clinical variables and the degree of WMC following treatment was examined using correlational and regression based analyses. Age when treated and volume of abnormal FLAIR prior to treatment were significantly associated with WMC following WBRT; however, pre-treatment FLAIR volume was the strongest predictor of post-treatment WMCs. Age did not add any predictive value once white matter status was considered. No significant relationships were found between biological equivalent dose and select cerebrovascular risk factors (total glucose, blood pressure, BMI) and development of WMCs. The findings from this study identify pre-treatment white matter health as an important risk factor in developing WMC following WBRT. This information can be used to make more informed decisions and counsel patients on their risk for treatment effects.

To evaluate the association of normalized and absolute ADC metrics with progression free survival (PFS) and overall survival (OS) in patients treated for glioblastoma multiforme (GBM). Fifty-two patients with preradiotherapy diffusion weighted imaging treated with post-operative chemoradiation for GBM were evaluated. Region of interest analysis for ADC metrics including mean and minimum ADC value (ADC mean ) and (ADC min ) was performed within the T2/FLAIR volume. Normalized (N) ADC values were generated relative to contralateral white matter. PFS and OS were analyzed relative to ADC parameters using a regression model. Kaplan–Meier and Cox proportional hazards analysis with respect to (N) ADC mean , and (N) ADC min was performed. A (N) ADC threshold <1.3 within the T2/FLAIR volume was analyzed with respect to PFS and OS. Regression analysis indicated that normalized ADC values provide the strongest association with PFS and OS. Kaplan–Meier analysis revealed a non-significant trend toward inferior PFS and OS associated with (N) ADC mean <1.7, and a significant decrement to PFS and OS associated with (N) ADC min <0.3. (N) ADC min was a significant prognostic factor when taking into account age, performance status, and extent of resection. ADC thresholding analysis revealed that a retained volume of >0.45 cc per mL FLAIR volume was associated with a trend toward inferior PFS and OS. In the post-operative, pre-radiotherapy setting, the (N) ADC min is the strongest predictor of outcomes in patients treated for GBM. ADC thresholding analysis indicates that a large volume of normalized ADC value <1.3 may be associated with adverse outcomes.

Abstract The proper treatment of brain metastases continues to be a challenge for oncologists given the variability of individual patients’ prognoses and the variety of treatment options available to address brain metasteses. There have been efforts since the 1990s to develop prognostic indices and nomograms to help clinicians determine the best approach for individuals with secondary malignant neoplasms of the central nervous system. A literature search was performed to identify the existing prognostic tools published between January 1995 and January 2017. While there have been several reported indices, many are limited by the number of patients analyzed or lack of generalizability. The most robust prognostic tools available are the Disease Specific Graded Prognostic Assessment and the Barnholtz-Sloan nomogram, both of which have online tools available to help clinicians. While these tools are helpful in stratifying different patients’ outcomes, they are limited by their retrospective nature and likely underestimate survival in the modern era, where there is a rapidly growing arsenal of systemic agents available to patients with metastatic disease.

Purpose : To investigate the association of pre-radiotherapy apparent diffusion coefficient (ADC) abnormalities with patterns of recurrence and outcomes in patients with glioblastoma multiforme (GBM). Materials and Methods : Fifty-two patients with recurrent GBM were retrospectively evaluated. Diffusion MRI images were acquired for all patients postoperatively prior to radiotherapy. ADC images were evaluated for geographic regions of diffusion restriction (hypointensity) within the FLAIR volume. If identified, the ADC map and the T1+C MRI at the time of recurrence were registered to the original plan to determine the pattern of recurrence and the coverage of the ADC abnormality by the 60 Gy isodose line (IDL). Progression-free and overall survival was determined for patients with and without an ADC hypointensity. Results : An ADC hypointensity was identified in 32 (62 %) of cases. The recurrence pattern in these cases was central in 27/32 (84 %), marginal in 4/32 (13 %) and distant in 1/32 (3 %). The recurrence overlapped with the ADC hypointensity in 28 (88 %) patients. The ADC hypointensity was covered by 95 % of the 60 Gy IDL in all cases. Kaplan–Meier analysis revealed inferior progression free survival and overall survival in patients with an ADC hypointensity compared to those without, despite similarities between the groups in terms of age, RT dose, performance status, and extent of resection. Conclusions : The presence of an ADC hypointensity on pre-radiotherapy diffusion-weighted imaging is associated with the location of tumor recurrence as demonstrated by frequent overlap in this series, and is associated with a trend toward inferior outcomes. This abnormality may reflect a high risk region of hypercellularity and warrants consideration with respect to radiotherapy planning.