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Background/PurposeSarcopenia is a prognostic factor in patients with head and neck cancer (HNC). Sarcopenia can be determined using the skeletal muscle index (SMI) calculated from cervical neck skeletal muscle (SM) segmentations. However, SM segmentation requires manual input, which is time-consuming and variable. Therefore, we developed a fully-automated approach to segment cervical vertebra SM.Materials/Methods390 HNC patients with contrast-enhanced CT scans were utilized (300-training, 90-testing). Ground-truth single-slice SM segmentations at the C3 vertebra were manually generated. A multi-stage deep learning pipeline was developed, where a 3D ResUNet auto-segmented the C3 section (33 mm window), the middle slice of the section was auto-selected, and a 2D ResUNet auto-segmented the auto-selected slice. Both the 3D and 2D approaches trained five sub-models (5-fold cross-validation) and combined sub-model predictions on the test set using majority vote ensembling. Model performance was primarily determined using the Dice similarity coefficient (DSC). Predicted SMI was calculated using the auto-segmented SM cross-sectional area. Finally, using established SMI cutoffs, we performed a Kaplan-Meier analysis to determine associations with overall survival.ResultsMean test set DSC of the 3D and 2D models were 0.96 and 0.95, respectively. Predicted SMI had high correlation to the ground-truth SMI in males and females (r>0.96). Predicted SMI stratified patients for overall survival in males (log-rank p = 0.01) but not females (log-rank p = 0.07), consistent with ground-truth SMI.ConclusionWe developed a high-performance, multi-stage, fully-automated approach to segment cervical vertebra SM. Our study is an essential step towards fully-automated sarcopenia-related decision-making in patients with HNC.

In March 2012, a twenty-five-minute documentary was released by Al-Jazeera's English network showing never seen footage from the heart of the Syrian uprising, chronicling the lives of ordinary citizens and the men who have taken up arms against the regime of President Bashar al-Assad. The short film, "Syria: Songs of Defiance," was shot entirely via the iPhone of an undercover journalist and produced by Al-Jazeera. Voices are muffled (the reporter's included), faces are blurred, names and locations are omitted. "Taking a camera would be risky," the anonymous reporter said in the video. "I brought my cell phone with me as I moved around the country."Syrian activists have been defying government blocks and censorship by uploading videos online, often supplying foreign media organizations with what little footage they are able to access. The desperate hope is that their message will be heard and the plight of the Syrian people will not go ignored by the international community. The Al-Jazeera documentary described:In Deir ez-Zor, as in other neighborhoods, they often hang up a large screen in order to broadcast a live Al-Jazeera broadcasting of their own demonstration. This is a big deal for demonstrators throughout the country-they want to know they're being seen all over the place. So, every night after the demonstration, people will go home and turn on Al Jazeera to see who came out tonight and who was shot tonight. 1

Acute myeloid leukemia is associated with the abnormal proliferation of myeloid progenitor cells unable to differentiate. Somatic gain-of-function mutations in isocitrate dehydrogenase (IDH) 1 occur in 10% of newly diagnosed AML patients. IDH1 mutations cause intracellular accumulation of the oncometabolite, 2-hydroxyglutarate (2-HG), which results in a hyper-methylation phenotype and a block in differentiation. Inhibitors of IDH1 mutant enzyme reduce levels of 2-HG, which relieves the differentiation block allowing AML cells to achieve terminal maturation. Recently, Ivosidenib, an IDH1 inhibitor, has been approved for use in AML patients. However, based on clinical findings, a fraction of the IDH1 mutant AML patients treated with Ivosidenib are primary refractory or relapse while on therapy. This raises the need for development of more potent inhibitors targeting IDH1. Lilly Research Laboratories have developed a potent covalent inhibitor of mutant IDH1, LY3410738 that modifies a single cysteine (Cys269) in an allosteric binding pocket and rapidly inactivates the enzyme, selectively inhibiting 2-HG production without affecting alpha-ketoglutarate (a-KG) levels. Here, we have assessed the activity of LY3410738 in IDH1 mutated patient-derived AML models and AML cell lines engineered to express wild-type IDH1 or mutant IDH1R132H. In vitro, LY3410738 displayed greater potency for inhibition of 2-HG production and differentiation of the IDH1 mutant cells compared to AG-120. Similarly, in vivo, we observed sustained 2-HG inhibition leading to a more robust and durable efficacy for LY3410738 with respect to AG-120. We next evaluated the combination activity of LY3410738 with Cytarabine and Azacitidine or the FLT3 inhibitor Midostaurin, the latter in FLT3-mutated AML. Combining LY3410738 with the chemotherapeutics resulted in increased efficacy, exhibiting a potent anti-leukemic effect, reduction of 2-HG level, and enhanced differentiation of the leukemic blasts in the mice. In addition, since IDH1 mutant AML cells have been shown to strongly depend on the anti-apoptotic Bcl-2 for the survival, we also combined LY3410738 with FDA approved Bcl-2 inhibitor, venetoclax. In vitro, isogenic cells with IDH1R132H mutation were more sensitive to the combination than wild-type IDH1-expressing cells. Importantly, the combination of LY3410738 with Venetoclax was also efficacious in an AML xenograft model derived from a patient refractory to AG-120. In conclusion, LY3410738 exhibits enhanced efficacy in IDH1 mutant AML PDX models in combination with Cytarabine, Azacitidine, Midostaurin and Venetoclax and demonstrates improved potency and durability compared to Ivosidenib. Citation Format: Vivian Salama, Nathan Brooks, Anna Skwarska, Lisa Kays, Paul Milligan, Katherine Newell, Kenneth Roth, Sandaruwan Geeganage, Raymond Gilmour, Steven M. Chan, Jean-Emmanuel Sarry, Mary Sabatier, Courtney DiNardo, Marina Konopleva. LY3410738, a novel inhibitor of mutant IDH1 is more effective than Ivosidenib and potentiates antileukemic activity of standard chemotherapy in preclinical models of acute myeloid leukemia (AML) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6417.

The accurate determination of sarcopenia is critical for disease management in patients with head and neck cancer (HNC). Quantitative determination of sarcopenia is currently dependent on manually-generated segmentations of skeletal muscle derived from computed tomography (CT) cross-sectional imaging. This has prompted the increasing utilization of machine learning models for automated sarcopenia determination. However, extant datasets currently do not provide the necessary manually-generated skeletal muscle segmentations at the C3 vertebral level needed for building these models. In this data descriptor, a set of 394 HNC patients were selected from The Cancer Imaging Archive, and their skeletal muscle and adipose tissue was manually segmented at the C3 vertebral level using sliceOmatic. Subsequently, using publicly disseminated Python scripts, we generated corresponding segmentations files in Neuroimaging Informatics Technology Initiative format. In addition to segmentation data, additional clinical demographic data germane to body composition analysis have been retrospectively collected for these patients. These data are a valuable resource for studying sarcopenia and body composition analysis in patients with HNC.