Differences in patterns of care and outcomes between grade II and grade III molecularly defined 1p19q co-deleted gliomas

Molecular markers are redefining classification of lower grade gliomas and ushering in a paradigm shift in their management. Our objective was to evaluate the differences in pattern of care and outcome by comparing grade II and grade III molecularly defined 1p19q co-deleted gliomas. We evaluated 1618 patients in the National Cancer Database diagnosed with 1p19q co-deleted gliomas from 2010 through 2014 and treated with surgery followed by radiation therapy (RT), chemotherapy (CT), or combined-modality therapy. Differences in patterns of care included that fifty-one percent of grade II tumors received surgery alone, whereas most patients with grade III tumors (86%) received surgery or biopsy followed by a form of post-operative therapy (p < 0.001). In a propensity score matched cohort, the Cox multivariable proportional hazards model with frailty testing identified significant covariates were age, comorbidity, histology and grade. Outcomes were different in overall survival even after adjusting for treatment received. The hazard for death for grade III 1p19q co-deleted gliomas was about 3.6 times higher ([HR] 3.69, 95% confidence interval [CI] 2.03–6.68, p < 0.001) than grade II 1p19q gliomas. Oligodendroglioma histology was associated with a lower likelihood of death (HR 0.40, 95% CI 0.23–0.70, p < 0.001). Our study is among the largest series to report on 1p19q co-deleted gliomas, which would otherwise require decades to acquire outside of large databases. Keywords: 1p19q co-deleted gliomas, Chemotherapy, Radiation, Concurrent chemoradiation, Grade, Surviva

Clinical implementation of automated treatment planning for whole-brain radiotherapy.

The purpose of the study was to develop and clinically deploy an automated, deep learning-based approach to treatment planning for whole-brain radiotherapy (WBRT). We collected CT images and radiotherapy treatment plans to automate a beam aperture definition from 520 patients who received WBRT. These patients were split into training (n = 312), cross-validation (n = 104), and test (n = 104) sets which were used to train and evaluate a deep learning model. The DeepLabV3+ architecture was trained to automatically define the beam apertures on lateral-opposed fields using digitally reconstructed radiographs (DRRs). For the beam aperture evaluation, 1st quantitative analysis was completed using a test set before clinical deployment and 2nd quantitative analysis was conducted 90 days after clinical deployment. The mean surface distance and the Hausdorff distances were compared in the anterior-inferior edge between the clinically used and the predicted fields. Clinically used plans and deep-learning generated plans were evaluated by various dose-volume histogram metrics of brain, cribriform plate, and lens. The 1st quantitative analysis showed that the average mean surface distance and Hausdorff distance were 7.1 mm (±3.8 mm) and 11.2 mm (±5.2 mm), respectively, in the anterior-inferior edge of the field. The retrospective dosimetric comparison showed that brain dose coverage (D99%, D95%, D1%) of the automatically generated plans was 29.7, 30.3, and 32.5 Gy, respectively, and the average dose of both lenses was up to 19.0% lower when compared to the clinically used plans. Following the clinical deployment, the 2nd quantitative analysis showed that the average mean surface distance and Hausdorff distance between the predicted and clinically used fields were 2.6 mm (±3.2 mm) and 4.5 mm (±5.6 mm), respectively. In conclusion, the automated patient-specific treatment planning solution for WBRT was implemented in our clinic. The predicted fields appeared consistent with clinically used fields and the predicted plans were dosimetrically comparable

The Effect of Slice Thickness on Contours of Brain Metastases for Stereotactic Radiosurgery

Objectives: Stereotactic radiosurgery is a common treatment for brain metastases and is typically planned on magnetic resonance imaging (MRI). However, the MR acquisition parameters used for patient selection and treatment planning for stereotactic radiosurgery can vary within and across institutions. In this work, we investigate the effect of MRI slice thickness on the detection and contoured volume of metastatic lesions in the brain. Methods and Materials: A retrospective cohort of 28 images acquired with a slice thickness of 1 mm were resampled to simulate acquisitions at 2- and 3-mm slice thickness. A total of 102 metastases ranging from 0.0030 cc to 5.08 cc (75-percentile 0.36 cc) were contoured on the original images. All 3 sets of images were recontoured by experienced physicians. Results: Of all the images detected and contoured on the 1 mm images, 3% of lesions were missed on the 2 mm images, and 13% were missed on the 3 mm images. One lesion that was identified on both the 2 mm and 3 mm images was determined to be a blood vessel on the 1 mm images. Additionally, the lesions were contoured 11% larger on the 2 mm and 43% larger on the 3 mm images. Conclusions: Using images with a slice thickness >1 mm effects detection and segmentation of brain lesions, which can have an important effect on patient management and treatment outcomes

An interdisciplinary consensus on the management of brain metastases in patients with renal cell carcinoma

Brain metastases are a challenging manifestation of renal cell carcinoma. We have a limited understanding of brain metastasis tumor and immune biology, drivers of resistance to systemic treatment, and their overall poor prognosis. Current data support a multimodal treatment strategy with radiation treatment and/or surgery. Nonetheless, the optimal approach for the management of brain metastases from renal cell carcinoma remains unclear. To improve patient care, the authors sought to standardize practical management strategies. They performed an unstructured literature review and elaborated on the current management strategies through an international group of experts from different disciplines assembled via the network of the International Kidney Cancer Coalition. Experts from different disciplines were administered a survey to answer questions related to current challenges and unmet patient needs. On the basis of the integrated approach of literature review and survey study results, the authors built algorithms for the management of single and multiple brain metastases in patients with renal cell carcinoma. The literature review, consensus statements, and algorithms presented in this report can serve as a framework guiding treatment decisions for patients. CA Cancer J Clin. 2022;72:454-489

National Cancer Institute Collaborative Workshop on Shaping the Landscape of Brain Metastases Research: challenges and recommended priorities

Brain metastases are an increasing global public health concern, even as survival rates improve for patients with metastatic disease. Both metastases and the sequelae of their treatment are key determinants of the inter-related priorities of patient survival, function, and quality of life, mandating a multidimensional approach to clinical care and research. At a virtual National Cancer Institute Workshop in September, 2022, key stakeholders convened to define research priorities to address the crucial areas of unmet need for patients with brain metastases to achieve meaningful advances in patient outcomes. This Policy Review outlines existing knowledge gaps, collaborative opportunities, and specific recommendations regarding consensus priorities and future directions in brain metastases research. Achieving major advances in research will require enhanced coordination between the ongoing efforts of individual organisations and consortia. Importantly, the continual and active engagement of patients and patient advocates will be necessary to ensure that the directionality of all efforts reflects what is most meaningful in the context of patient care