Cancer cachexia and sarcopenia can occur frequently in patients with advanced cancer, and may negatively affect treatment outcomes. This article highlights the importance of assessing sarcopenia and describes the relationship between sarcopenia and patients' quality of life in patients with newly diagnosed, incurable cancer.

Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an “eyeball test” to assess whether patients will tolerate major surgery or chemotherapy, “eyeballing” is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.

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Editor’s Perspective What We Already Know about This Topic Obesity increases the propensity to atelectasis in acute respiratory distress syndrome, but the optimal approach to reversing this atelectasis is uncertain What This Article Tells Us That Is New A clinical crossover study comparing three approaches to titrate positive end-expiratory pressure (PEEP; according to a fixed table, according to end-expiratory esophageal pressure, and targeting the best compliance during a decremental PEEP trial) found that a recruitment maneuver followed by decremental PEEP minimized atelectasis and overdistension, and best restored compliance and oxygenation without causing hemodynamic impairment Background Obese patients are characterized by normal chest-wall elastance and high pleural pressure and have been excluded from trials assessing best strategies to set positive end-expiratory pressure (PEEP) in acute respiratory distress syndrome (ARDS). The authors hypothesized that severely obese patients with ARDS present with a high degree of lung collapse, reversible by titrated PEEP preceded by a lung recruitment maneuver. Methods Severely obese ARDS patients were enrolled in a physiologic crossover study evaluating the effects of three PEEP titration strategies applied in the following order: (1) PEEPARDSNET: the low PEEP/Fio2 ARDSnet table; (2) PEEPINCREMENTAL: PEEP levels set to determine a positive end-expiratory transpulmonary pressure; and (3) PEEPDECREMENTAL: PEEP levels set to determine the lowest respiratory system elastance during a decremental PEEP trial following a recruitment maneuver on respiratory mechanics, regional lung collapse, and overdistension according to electrical impedance tomography and gas exchange. Results Fourteen patients underwent the study procedures. At PEEPARDSNET (13 ± 1 cm H2O) end-expiratory transpulmonary pressure was negative (−5 ± 5 cm H2O), lung elastance was 27 ± 12 cm H2O/L, and PaO2/Fio2 was 194 ± 111 mmHg. Compared to PEEPARDSNET, at PEEPINCREMENTAL level (22 ± 3 cm H2O) lung volume increased (977 ± 708 ml), lung elastance decreased (23 ± 7 cm H2O/l), lung collapse decreased (18 ± 10%), and ventilation homogeneity increased thus rising oxygenation (251 ± 105 mmHg), despite higher overdistension levels (16 ± 12%), all values P < 0.05 versus PEEPARDSnet. Setting PEEP according to a PEEPDECREMENTAL trial after a recruitment maneuver (21 ± 4 cm H2O, P = 0.99 vs. PEEPINCREMENTAL) further lowered lung elastance (19 ± 6 cm H2O/l) and increased oxygenation (329 ± 82 mmHg) while reducing lung collapse (9 ± 2%) and overdistension (11 ± 2%), all values P < 0.05 versus PEEPARDSnet and PEEPINCREMENTAL. All patients were maintained on titrated PEEP levels up to 24 h without hemodynamic or ventilation related complications. Conclusions Among the PEEP titration strategies tested, setting PEEP according to a PEEPDECREMENTAL trial preceded by a recruitment maneuver obtained the best lung function by decreasing lung overdistension and collapse, restoring lung elastance, and oxygenation suggesting lung tissue recruitment.

Cystic airspaces preceded by nodules can evolve into NSCLCs. Wall thickening and/or mural nodularity may develop. Location in the periphery of the upper lobes, emphysema, additional cystic lesions or ground-glass nodules, lymphadenopathy, and prior lung cancer should further increase suspicion. Cystic airspaces on CT can be due to a check-valve mechanism obstructing the small airways, lepidic growth of adenocarcinoma in an area of emphysema, cystification of tumor due to degeneration, or adenocarcinoma growing along the wall of a preexisting bulla. KRAS mutations are the predominant genetic alterations.

Effectively targeting cancer stem cells, a subpopulation of tumorigenic, aggressive, and radioresistant cells, holds therapeutic promise. However, the effects of the microRNA miR-142-3p, a small endogenous regulator of gene expression on breast cancer stem cells, have not been investigated. This study identifies the influence of miR-142-3p on mammary stemness properties and breast cancer radioresistance to establish its role in this setting. miR-142-3p precursor transfection was performed in MDA-MB-468, HCC1806, and MCF-7 cells, and stem cell markers CD44, CD133, ALDH1 activity and mammosphere formation were measured. β-catenin, the canonical wnt signaling effector protein, was quantified by Western blots and cell fluorescence assays both in miR-142-3p-overexpressing and anti-miR-142-3p-treated cells. Radiation response was investigated by colony formation assays. Levels of BRCA1, BRCA2, and Bod1 in miR-142-3p-overexpressing cells as well as expression of miR-142-3p, Bod1, KLF4, and Oct4 in sorted CD44/CD24 cells were determined by quantitative polymerase chain reaction. miR-142-3p overexpression resulted in a strong decline in breast cancer stem cell characteristics with a decrease in CD44, CD133, ALDH1, Bod1, BRCA2, and mammosphere formation as well as reduced survival after irradiation. miR-142-3p expression was strongly reduced in sorted CD44/CD24 stem cells, while Bod1, Oct4, and KLF4 were overexpressed. β-catenin levels strongly decreased after miR-142-3p overexpression, but not after anti-miR-142-3p treatment. We conclude that miR-142-3p downregulates cancer stem cell characteristics and radioresistance in breast cancer, mediated by a reduced role of β-catenin in miR-142-3p-overexpressing cells. miR-142-3p might therefore help to target cancer stem cells.

The amounts of muscle and fat in a person's body, known as body composition, are correlated with cancer risks, cancer survival, and cardiovascular risk. The current gold standard for measuring body composition requires time-consuming manual segmentation of CT images by an expert reader. In this work, we describe a two-step process to fully automate the analysis of CT body composition using a DenseNet to select the CT slice and U-Net to perform segmentation. We train and test our methods on independent cohorts. Our results show Dice scores (0.95-0.98) and correlation coefficients (R=0.99) that are favorable compared to human readers. These results suggest that fully automated body composition analysis is feasible, which could enable both clinical use and large-scale population studies. Equal contribution

Rapid CT-based tissue characterization is feasible in patients referred for TAVR. Decreased PM area and increased SAT density are associated with long-term mortality after TAVR, even after accounting for age, sex, BMI, and STS score. Further studies are necessary to interrogate sex-specific relationships between CT tissue metrics and mortality and whether CT measures are incremental to well-established frailty metrics.