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AimsMucoepidermoid carcinomas (MEC) are the most common malignant neoplasms of salivary glands, but are uncommon in other sites. Salivary gland MEC are most frequently associated with CRTC1–MAML2 translocations. Exceedingly rare MEC of the breast demonstrate a basal‐like and often triple (oestrogen and progesterone receptor, HER2)‐negative immunophenotype, with a single case previously reported to show MAML2 rearrangement, although the fusion partner was not known. Comprehensive genomic studies of breast MEC are lacking. In this study, we analysed the immunophenotype and molecular landscape of two breast MEC to elucidate the pathogenesis of these rare tumours.Methods and resultsTwo breast MEC were subjected to capture‐based next‐generation DNA sequencing of 479 cancer‐related genes. The presence of the CRTC1–MAML2 fusion transcript was interrogated by reverse transcriptase–polymerase chain reaction. In addition, the immunoprofiles of breast MEC were compared to salivary gland MEC. Both breast MEC harboured CRTC1–MAML2 fusions. In contrast to most triple‐negative breast carcinomas of no special type, the mutational burden of MEC was very low, with one case demonstrating only an inactivating SETD2 mutation, and the other harbouring no somatic variants in genes on the panel. No copy number alterations were identified. The immunoprofiles of breast and salivary gland MEC were overlapping, but not identical.ConclusionsThe findings highlight MEC as a breast cancer subtype more closely related to its salivary gland counterpart than to basal‐like/triple‐negative breast cancers of no special type.

PurposeProvide an adaptive multicriteria optimization (MCO) method for intensity‐modulated proton therapy (IMPT) utilizing GPU technology. Previously described limitations of MCO such as Pareto approximation and limitation on the number of objectives were addressed.MethodsThe treatment planning process for IMPT must account for multiple objectives, which requires extensive treatment planning resources. Often a large number of objectives (>10) are required. Hence the need for an MCO algorithm that can handle large number of objectives. The novelty of the MCO method presented here lies on the introduction of the adaptive weighting scheme that can generate a well‐distributed and dense representation of the Pareto surface for a large number of objectives in an efficient manner. In our approach the generated Pareto surface is constructed for a set of DVH objectives. The MCO algorithm is based on the augmented weighted Chebychev metric (AWCM) method with an adaptive weighting scheme. This scheme uses the differential evolution (DE) method to generate a set of well‐distributed Pareto points. The quality of the Pareto points’ distribution in the objective space was assessed quantitatively using the Pareto sampling metric. The MCO algorithm was developed to perform multiple parallel searches to achieve a rapid mapping of the Pareto surface, produce clinically deliverable plans, and was implemented on a GPU cluster. The MCO algorithm was tested on two clinical cases with 10 and 18 objectives. For each case one of the MCO‐generated plans was selected for comparison with the clinically generated plan. The MCO plan was randomly selected out of the set of MCO plans that had target coverage similar to the clinically generated plan and the same or better sparing of the organs at risk (OAR). Additionally, a validation study of the AWCM method vs the weighted sum method was performed.ResultsThe adaptive MCO algorithm generated Pareto points on the Pareto hypersurface in a fast (2–3 hr) and efficient manner for 2 cases with 10 and 18 objectives. The MCO algorithm generated a dense and well‐distributed set of Pareto points on the objective space, and was able to achieve minimization of the Pareto sampling metric. The selected MCO plan showed an improvement of the DVH objectives in comparison to the clinically optimized plan in both cases. For case one, the MCO plan showed a 48% reduction of the 50% dose to OARs and a 16% reduction of the 1% dose to OARs. For case 2, the MCO plan showed a 72% reduction of the 50% dose to OARs and a 42% reduction of the 1% dose to OARs. The comparison of AWCM to WS showed that the AWCM method has a dosimetric advantage over WS for both patient cases.ConclusionWe introduced an adaptive MCO algorithm for IMPT accelerated using GPUs. The algorithm is based on an adaptive method for generating Pareto plans in the objective space. We have shown that the algorithm can provide rapid and efficient mapping of the multicriteria Pareto surface with clinically deliverable plans.

Abstract Motion and uncertainty in radiotherapy is traditionally handled via margins. The clinical target volume (CTV) is expanded to a larger planning target volume (PTV), which is irradiated to the prescribed dose. However, the PTV concept has several limitations, especially in proton therapy. Therefore, robust and probabilistic optimization methods have been developed that directly incorporate motion and uncertainty into treatment plan optimization for intensity modulated radiotherapy (IMRT) and intensity modulated proton therapy (IMPT). Thereby, the explicit definition of a PTV becomes obsolete and treatment plan optimization is directly based on the CTV. Initial work focused on random and systematic setup errors in IMRT. Later, inter-fraction prostate motion and intra-fraction lung motion became a research focus. Over the past ten years, IMPT has emerged as a new application for robust planning methods. In proton therapy, range or setup errors may lead to dose degradation and misalignment of dose contributions from different beams – a problem that cannot generally be addressed by margins. Therefore, IMPT has led to the first implementations of robust planning methods in commercial planning systems, making these methods available for clinical use. This paper first summarizes the limitations of the PTV concept. Subsequently, robust optimization methods are introduced and their applications in IMRT and IMPT planning are reviewed.

Maternity care access in the United States is in crisis. The American Congress of Obstetrics and Gynecology projects that by 2030 there will be a nationwide shortage of 9,000 obstetrician-gynecologists (OB/GYNs). Midwives and OB/GYNs have been called upon to address this crisis, yet in underserved areas, family physicians are often providing a majority of this care. Family medicine maternity care, a natural fit for the discipline, has been on sharp decline in recent years for many reasons including difficulties cultivating interdisciplinary relationships, navigating privileging, developing and maintaining adequate volume/competency, and preventing burnout. In 2016 and 2017, workshops were held among family medicine educators with resultant recommendations for essential strategies to support family physician maternity care providers. This article summarizes these strategies, provides guidance, and highlights the role family physicians have in addressing maternity care access for the underserved as well as presenting innovative ideas to train and retain rural family physician maternity care providers.

Abstract Primary mediastinal large B-cell lymphoma (PMBCL) is recognized as a distinct entity in the World Health Organization classification. Currently, the diagnosis relies on consensus of histopathology, clinical variables, and presentation, giving rise to diagnostic inaccuracy in routine practice. Previous studies have demonstrated that PMBCL can be distinguished from subtypes of diffuse large B-cell lymphoma (DLBCL) based on gene expression signatures. However, requirement of fresh-frozen biopsy material has precluded the transfer of gene expression–based assays to the clinic. Here, we developed a robust and accurate molecular classification assay (Lymph3Cx) for the distinction of PMBCL from DLBCL subtypes based on gene expression measurements in formalin-fixed, paraffin-embedded tissue. A probabilistic model accounting for classification error, comprising 58 gene features, was trained on 68 cases of PMBCL and DLBCL. Performance of the model was subsequently evaluated in an independent validation cohort of 158 cases and showed high agreement of the Lymph3Cx molecular classification with the clinicopathological diagnosis of an expert panel (frank misclassification rate, 3.8%). Furthermore, we demonstrate reproducibility of the assay with 100% concordance of subtype assignments at 2 independent laboratories. Future studies will determine Lymph3Cx’s utility for routine diagnostic purposes and therapeutic decision making.

Adverse clinical events in primary sclerosing cholangitis (PSC) happen too slowly to capture during clinical trials. Surrogate endpoints are needed, but no such validated endpoints exist for children with PSC. We evaluated the association between gamma glutamyltransferase (GGT) reduction and long‐term outcomes in pediatric PSC patients. We evaluated GGT normalization (< 50 IU/L) at 1 year among a multicenter cohort of children with PSC who did or did not receive treatment with ursodeoxycholic acid (UDCA). We compared rates of event‐free survival (no portal hypertensive or biliary complications, cholangiocarcinoma, liver transplantation, or liver‐related death) at 5 years. Of the 287 children, mean age of 11.4 years old, UDCA was used in 81% at a mean dose of 17 mg/kg/day. Treated and untreated groups had similar GGT at diagnosis (314 versus 300, P= not significant [NS]). The mean GGT was reduced at 1 year in both groups, with lower values seen in treated (versus untreated) patients (99 versus 175, P= 0.002), but 5‐year event‐free survival was similar (74% versus 77%, P= NS). In patients with GGT normalization (versus no normalization) by 1 year, regardless of UDCA treatment status, 5‐year event‐free survival was better (91% versus 67%, P< 0.001). Similarly, larger reduction in GGT over 1 year (> 75% versus < 25% reduction) was also associated with improved outcome (5‐year event‐free survival 88% versus 61%, P= 0.005). Conclusion:A GGT < 50 and/or GGT reduction of > 75% by 1 year after PSC diagnosis predicts favorable 5‐year outcomes in children. GGT has promise as a potential surrogate endpoint in future clinical trials for pediatric PSC.