Citations

AbstractThis report by the Radiation Oncology Discipline of Children's Oncology Group (COG) describes the practice patterns of pediatric image‐guided radiotherapy (IGRT) based on a member survey and provides practice recommendations accordingly. The survey comprised of 11 vignettes asking clinicians about their recommended treatment modalities, IGRT preferences, and frequency of in‐room verification. Technical questions asked physicists about imaging protocols, dose reduction, setup correction, and adaptive therapy. In this report, the COG Radiation Oncology Discipline provides an IGRT modality/frequency decision tree and the expert guidelines for the practice of ionizing image guidance in pediatric radiotherapy patients.

High-grade neuroendocrine carcinomas (NEC) of the endometrium are rare and account for <1% of all endometrial carcinomas. Both small cell neuroendocrine carcinoma (SCNEC) and large cell neuroendocrine carcinoma (LCNEC) morphologies have been reported. Little is known regarding the molecular features of endometrial NEC including how they compare to pulmonary NEC (the most common site for these neoplasms) and the more common endometrial carcinoma histotypes. In this study, we investigated the molecular alterations in a series of endometrial NEC using a targeted next generation sequencing panel (Oncopanel). Fourteen NEC were sequenced; pure NEC (n=4) and mixed (n=10) with endometrioid adenocarcinoma (n=9) or carcinosarcoma (n=1). The NEC components of mixed tumors comprised LCNEC (n=6) and SCNEC (n=4). The 4 pure NEC comprised LCNEC (n=2) and SCNEC (n=2). Molecular analysis classified tumors into the 4 The Cancer Genome Atlas groups: (1) POLE-mutated/ultramutated (1/14; 7%), (2) microsatellite instability/hypermutated (6/14; 43%), (3) TP53 mutated/copy number high (2/14; 14%), or (4) no specific molecular profile (5/14; 36%). Overall, 50% of cases were ultramutated or hypermutated. In 8 cases of mixed carcinomas, the different histologic components were macrodissected and separately sequenced; molecular alterations were nearly identical among the 2 components, with the non-NEC component harboring slightly increased tumor mutational burden. Only 2 carcinomas (both with pure SCNEC morphology) had a molecular profile that would be expected in typical pulmonary SCNEC (RB1 deletion and TP53 mutations). Our findings, similar to data from NECs of other anatomic sites, suggest that the molecular context may be important when selecting therapies for women with endometrial NEC. Immune checkpoint inhibition may be a reasonable approach to treatment of microsatellite instability-NEC and we thus recommend that all endometrial NEC be tested for mismatch repair abnormalities, either molecularly or by mismatch repair protein immunohistochemistry.

Objectives Some patients with postural orthostatic tachycardia syndrome (POTS) demonstrate improved dysautonomic symptoms following treatment for pelvic venous insufficiency (PVI). This study assessed the prevalence of significant left common iliac vein (LCIV) compression in POTS patients. Methods Radiologists retrospectively reviewed CT images of pelvic veins for 216 women (191 with POTS and 25 age-comparable controls).Quantitative vascular analysis identified percent-diameter compression of the LCIV by the right common iliac artery. Significant LCIV compression was defined as >50%. Results Significant LCIV compression was found in 69% (131/191) of females with POTS versus 40% (10/25) in controls. The hypothesis that venous compression and presence of POTS are independent was rejected ( p = .005). Conclusions Significant LCIV compression was noted in a majority of female POTS patients, suggesting that incidence of iliac venous obstruction may be higher than the general population. Patients with POTS and symptoms of PVI may benefit from assessment for venous outflow obstruction.

PurposeOrgan segmentation of computed tomography (CT) imaging is essential for radiotherapy treatment planning. Treatment planning requires segmentation not only of the affected tissue, but nearby healthy organs‐at‐risk, which is laborious and time‐consuming. We present a fully automated segmentation method based on the three‐dimensional (3D) U‐Net convolutional neural network (CNN) capable of whole abdomen and pelvis segmentation into 33 unique organ and tissue structures, including tissues that may be overlooked by other automated segmentation approaches such as adipose tissue, skeletal muscle, and connective tissue and vessels. Whole abdomen segmentation is capable of quantifying exposure beyond a handful of organs‐at‐risk to all tissues within the abdomen.MethodsSixty‐six (66) CT examinations of 64 individuals were included in the training and validation sets and 18 CT examinations from 16 individuals were included in the test set. All pixels in each examination were segmented by image analysts (with physician correction) and assigned one of 33 labels. Segmentation was performed with a 3D U‐Net variant architecture which included residual blocks, and model performance was quantified on 18 test cases. Human interobserver variability (using semiautomated segmentation) was also reported on two scans, and manual interobserver variability of three individuals was reported on one scan. Model performance was also compared to several of the best models reported in the literature for multiple organ segmentation.ResultsThe accuracy of the 3D U‐Net model ranges from a Dice coefficient of 0.95 in the liver, 0.93 in the kidneys, 0.79 in the pancreas, 0.69 in the adrenals, and 0.51 in the renal arteries. Model accuracy is within 5% of human segmentation in eight of 19 organs and within 10% accuracy in 13 of 19 organs.ConclusionsThe CNN approaches the accuracy of human tracers and on certain complex organs displays more consistent prediction than human tracers. Fully automated deep learning‐based segmentation of CT abdomen has the potential to improve both the speed and accuracy of radiotherapy dose prediction for organs‐at‐risk.

Receptor heterogeneity in cancer is a major limitation of molecular targeting for cancer therapeutics. Single-receptor-targeted treatment exerts selection pressures that result in treatment escape for low-receptor-expressing tumor subpopulations. To overcome this potential for heterogeneity-driven resistance to molecular targeted photodynamic therapy (PDT), we present for the first time a triple-receptor-targeted photoimmuno-nanoconjugate (TR-PIN) platform. TR-PIN functionalization with cetuximab, holo-transferrin, and trastuzumab conferred specificity for epidermal growth factor receptor (EGFR), transferrin receptor (TfR), and human epidermal growth factor receptor 2 (HER-2), respectively. The TR-PINs exhibited up to a 24-fold improvement in cancer cell binding compared with EGFR-specific cetuximab-targeted PINs (Cet-PINs) in low-EGFR-expressing cell lines. Photodestruction using TR-PINs was significantly higher than the monotargeted Cet-PINs in heterocellular 3D in vitro models of heterogeneous pancreatic ductal adenocarcinoma (PDAC; MIA PaCa-2 cells) and heterogeneous head and neck squamous cell carcinoma (HNSCC, SCC9 cells) containing low-EGFR-expressing T47D (high TfR) or SKOV-3 (high HER-2) cells. Through their capacity for multiple tumor target recognition, TR-PINs can serve as a unique and amenable platform for the effective photodynamic eradication of diverse tumor subpopulations in heterogeneous cancers to mitigate escape for more complete and durable treatment responses.

PURPOSENRG Oncology/RTOG 9802 (ClinicalTrials.gov Identifier: NCT00003375 ) is a practice-changing study for patients with WHO low-grade glioma (LGG, grade II), as it was the first to demonstrate a survival benefit of adjuvant chemoradiotherapy over radiotherapy. This post hoc study sought to determine the prognostic and predictive impact of the WHO-defined molecular subgroups and corresponding molecular alterations within NRG Oncology/RTOG 9802.METHODSIDH1/2 mutations were determined by immunohistochemistry and/or deep sequencing. A custom Ion AmpliSeq panel was used for mutation analysis. 1p/19q codeletion and MGMT promoter methylation were determined by copy-number arrays and/or Illumina 450K array, respectively. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Hazard ratios (HRs) were calculated using the Cox proportional hazard model and tested using the log-rank test. Multivariable analyses (MVAs) were performed incorporating treatment and common prognostic factors as covariates.RESULTSOf the eligible patients successfully profiled for the WHO-defined molecular groups (n = 106/251), 26 (24%) were IDH-wild type, 43 (41%) were IDH-mutant/non-codeleted, and 37(35%) were IDH-mutant/codeleted. MVAs demonstrated that WHO subgroup was a significant predictor of PFS after adjustment for clinical variables and treatment. Notably, treatment with postradiation chemotherapy (PCV; procarbazine, lomustine (CCNU), and vincristine) was associated with longer PFS (HR, 0.32; P = .003; HR, 0.13; P < .001) and OS (HR, 0.38; P = .013; HR, 0.21; P = .029) in the IDH-mutant/non-codeleted and IDH-mutant/codeleted subgroups, respectively. In contrast, no significant difference in either PFS or OS was observed with the addition of PCV in the IDH-wild-type subgroup.CONCLUSIONThis study is the first to report the predictive value of the WHO-defined diagnostic classification in a set of uniformly treated patients with LGG in a clinical trial. Importantly, this post hoc analysis supports the notion that patients with IDH-mutant high-risk LGG regardless of codeletion status receive benefit from the addition of PCV.

AbstractThe COVID-19 pandemic response in the United States has exposed significant gaps in information systems and processes that prevent timely clinical and public health decision-making. Specifically, the use of informatics to mitigate the spread of SARS-CoV-2, support COVID-19 care delivery, and accelerate knowledge discovery bring to the forefront issues of privacy, surveillance, limits of state powers, and interoperability between public health and clinical information systems. Using a consensus-building process, we critically analyze informatics-related ethical issues in light of the pandemic across 3 themes: (1) public health reporting and data sharing, (2) contact tracing and tracking, and (3) clinical scoring tools for critical care. We provide context and rationale for ethical considerations and recommendations that are actionable during the pandemic and conclude with recommendations calling for longer-term, broader change (beyond the pandemic) for public health organization and policy reform.

Abstract Defining patient-to-patient similarity is essential for the development of precision medicine in clinical care and research. Conceptually, the identification of similar patient cohorts appears straightforward; however, universally accepted definitions remain elusive. Simultaneously, an explosion of vendors and published algorithms have emerged and all provide varied levels of functionality in identifying patient similarity categories. To provide clarity and a common framework for patient similarity, a workshop at the American Medical Informatics Association 2019 Annual Meeting was convened. This workshop included invited discussants from academics, the biotechnology industry, the FDA, and private practice oncology groups. Drawing from a broad range of backgrounds, workshop participants were able to coalesce around 4 major patient similarity classes: (1) feature, (2) outcome, (3) exposure, and (4) mixed-class. This perspective expands into these 4 subtypes more critically and offers the medical informatics community a means of communicating their work on this important topic.

ObjectiveGiant cell arteritis (GCA) is a large‐vessel vasculitis that primarily affects the aorta and its branches. Extracranial branches of the carotid artery are frequently affected; however, intracranial involvement in GCA is rare.MethodsA retrospective medical record review was performed to identify all patients with intracranial GCA (IC‐GCA) from January 1996 through May 2018.ResultsNine patients with IC‐GCA were included (78% male; mean age, 72.1 years [SD: 7.9]). All patients met ACR criteria for GCA. The median time from onset of GCA to intracranial involvement was 0.6 months (interquartile range: 0.1‐5.1). All patients had neurologic symptoms, 89% had an ischemic cerebrovascular event. Transient or permanent vision loss was frequent (56% of patients). IC‐GCA was diagnosed by cranial imaging in all nine patients. Intracranial vasculitis most commonly affected the internal carotid artery (100%), followed by the vertebral artery (67%), posterior cerebral artery (67%), middle cerebral artery (44%), anterior cerebral artery (33%), and posterior inferior cerebral artery (11%). Intracranial vessel stenosis was present in 89%, occlusion in 33%, wall thickening in 33%, and dilation in 11%.All patients received glucocorticoids. Additional therapeutic agents included cyclophosphamide (67%) and tocilizumab (22%). Despite treatment, five patients had rapid deterioration and mortality. Comparing IC‐GCA patient survival to the expected rates from the US population, the standardized mortality ratio (95% CI) for IC‐GCA was 58.1 (18.9‐135.6).ConclusionAlthough rare, IC‐GCA is associated with significant morbidity and mortality. It occurs predominantly in men and presents with ischemic cerebrovascular events. Current treatment strategies appear to be of limited efficacy for IC‐GCA.