Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

This study provides strong preclinical evidence that radiation-induced cardiotoxicity is modulated by the PD-1 axis and that PD-1 blockade should be administered with careful radiotherapy planning with an effort of reducing cardiac dose.

Brain extraction, or skull-stripping, is an essential pre-processing step in neuro-imaging that has a direct impact on the quality of all subsequent processing and analyses steps. It is also a key requirement in multi-institutional collaborations to comply with privacy-preserving regulations. Existing automated methods, including Deep Learning (DL) based methods that have obtained state-of-the-art results in recent years, have primarily targeted brain extraction without considering pathologically-affected brains. Accordingly, they perform sub-optimally when applied on magnetic resonance imaging (MRI) brain scans with apparent pathologies such as brain tumors. Furthermore, existing methods focus on using only T1-weighted MRI scans, even though multi-parametric MRI (mpMRI) scans are routinely acquired for patients with suspected brain tumors. In this study, we present a comprehensive performance evaluation of recent deep learning architectures for brain extraction, training models on mpMRI scans of pathologically-affected brains, with a particular focus on seeking a practically-applicable, low computational footprint approach, generalizable across multiple institutions, further facilitating collaborations. We identified a large retrospective multi-institutional dataset of n = 3340 mpMRI brain tumor scans, with manually-inspected and approved gold-standard segmentations, acquired during standard clinical practice under varying acquisition protocols, both from private institutional data and public (TCIA) collections. To facilitate optimal utilization of rich mpMRI data, we further introduce and evaluate a novel “modality-agnostic training” technique that can be applied using any available modality, without need for model retraining. Our results indicate that the modality-agnostic approach 1 obtains accurate results, providing a generic and practical tool for brain extraction on scans with brain tumors.

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This book surveys the leading modern theories of property – Lockean, libertarian, utilitarian/law-and-economics, personhood, Kantian and human flourishing – and then applies those theories to concrete contexts in which property issues have been especially controversial. These include redistribution, the right to exclude, regulatory takings, eminent domain and intellectual property. The book highlights the Aristotelian human flourishing theory of property, providing the most comprehensive and accessible introduction to that theory to date. The book's goal is neither to cover every conceivable theory nor to discuss every possible facet of the theories covered. Instead, it aims to make the major property theories comprehensible to beginners, without sacrificing accuracy or sophistication. The book will be of particular interest to students seeking an accessible introduction to contemporary theories of property, but even specialists will benefit from the book's lucid descriptions of contemporary debates.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Many people assume that what morally justifies private ownership of property is either individual freedom or social welfare, defined in terms of maximizing personal preference-satisfaction. This book offers an alternative way of understanding the moral underpinning of private ownership of property. Rather than identifying any single moral value, this book argues that human flourishing is property’s moral foundation. It develops a theory that connects ownership and human flourishing with obligations. Owners owe obligations to members of the communities that have enabled the owners to live flourishing lives by cultivating in their community members certain capabilities that are essential to leading a well-lived life. These obligations are rooted in the interdependence that exists between owners and their community members, a condition that is inherent in the human condition. Obligations have always been inherent in ownership. The human flourishing theory explains why owners at times owe obligations that enable their fellow community members to develop certain necessary capabilities. This book considers implications for a wide variety of property issues of importance both in the literature and in modern society. These include questions such as: When is a government’s expropriation of property legitimate? May the owner of a historic house destroy it without restriction? Do institutions that owned African slaves or otherwise profited from the slave trade owe any obligations to the African American community? What insights may be gained from the human flourishing concept into resolving current housing problems like homelessness, eviction, and mortgage foreclosure?

BackgroundPembrolizumab is a monoclonal antibody that is designed against programmed cell death protein 1 (PD-1). Pembrolizumab and other immunocheckpoint-blocking monoclonal antibodies work by modulating a patient’s own immune system to increase anti-tumor activity. While immunocheckpoint blockade has shown promising results, only 20–40 % of patients experience objective clinical benefit. Differences in individual tumor biology and the presence multiple immune checkpoints present a challenge for treatment. Because radiotherapy has immunomodulatory effects on the tumor microenvironment, it has the potential to synergize with immunotherapy and augment tumor response. NCT02318771 is a phase 1 clinical trial designed to investigate the immunomodulatory effects of radiation therapy in combination with pembrolizumab.Case presentationThe patient is a 64-year-old male with metastatic clear cell renal cell carcinoma, Fuhrman grade 4, pathologically staged as T3 N0. Metastatic disease was well controlled for several years with sunitinib. Following disease progression, he was switched to axitinib. When disease progression continued, the patient was enrolled in NCT02318771, a phase 1 clinical trial combining radiotherapy and pembrolizumab. The patient experienced unusually rapid disease progression during treatment, which was confirmed by repeated CT scans to rule out pseudoprogression. Tissue biopsies and peripheral blood draws were obtained before, during, and after treatment. Samples were analyzed to provide plausible rationale for rapid treatment failure.ConclusionsBiomarker analysis demonstrated an absence of TILs, which may be a cause of treatment failure as pembrolizumab works through T cell-dependent mechanisms. Furthermore, the presence of other non-redundant immune checkpoints in the periphery and tumor microenvironment presents a treatment challenge. Additionally, the radiation dose and fractionation schedule may have played a role in treatment failure as these factors play a role in the effect radiotherapy on the tumor microenvironment as well as the potential for synergy with immunotherapy.Trial registrationAn Exploratory Study to Investigate the Immunomodulatory Activity of Radiation Therapy (RT) in Combination With MK-3475 in Patients With Recurrent/Metastatic Head and Neck, Renal Cell Cancer, Melanoma and Lung Cancer, NCT02318771.