Subcutaneous and Visceral Adipose Tissue Reference Values From the Framingham Heart Study Thoracic and Abdominal CT.

BACKGROUND: Computed tomography (CT) captures the quantity, density, and distribution of subcutaneous and visceral (SAT and VAT) adipose tissue compartments. These metrics may change with age and sex. OBJECTIVE: The study aims to provide age-, sex-, and vertebral level-specific reference values for SAT on chest CT and for SAT and VAT on abdomen CT. MATERIALS AND METHODS: This secondary analysis of an observational study describes SAT and VAT measurements in participants of the Framingham Heart Study without known cancer diagnosis who underwent at least 1 of 2 CT examinations between 2002 and 2011. We used a previously validated machine learning-assisted pipeline and rigorous quality assurance to segment SAT at the fifth, eighth, and tenth thoracic vertebra (T5, T8, T10) and SAT and VAT at the third lumbar vertebra (L3). For each metric, we measured cross-sectional area (cm2) and mean attenuation (Hounsfield units [HU]) and calculated index (area/height2) (cm2/m2) and gauge (attenuation × index) (HU × cm2/m2). We summarized body composition metrics by age and sex and modeled sex-, age-, and vertebral level-specific reference curves. RESULTS: We included 14,898 single-level measurements from up to 4 vertebral levels of 3797 scans of 3730 Framingham Heart Study participants (1889 [51%] male with a mean [standard deviation] age of 55.6 ± 10.6 years; range, 38-81 years). The mean VAT index increased with age from 65 (cm2/m2) in males and 29 (cm2/m2) in females in the <45-year-old age group to 99 (cm2/m2) in males and 60 (cm2/m2) in females in >75-year-old age group. The increase of SAT with age was less pronounced, resulting in the VAT/SAT ratio increasing with age. A free R package and online interactive visual web interface allow access to reference values. CONCLUSIONS: This study establishes age-, sex-, and vertebral level-specific reference values for CT-assessed SAT at vertebral levels T5, T8, T10, and L3 and VAT at vertebral level L3.

A Multicenter Evaluation of Treatment-associated Changes in Body Composition in Men With Germ Cell Tumors of the Testis: Implications for Adverse Events and Complications.

OBJECTIVE: To characterize changes in body composition following cytotoxic chemotherapy for germ cell carcinoma of the testis (GCT) and quantify associations between body composition metrics and chemotherapy-associated adverse events (AEs) and post-retroperitoneal lymph node dissection (RPLND) complications. MATERIALS AND METHODS: This retrospective multi-center study included 216 men with GCT treated with cytotoxic chemotherapy and/or RPLND (2005-2020). We measured body composition including skeletal muscle (SMI), visceral adipose (VAI,), subcutaneous adipose (SAI), and fat mass (FMI) indices on computed tomography. We quantified chemotherapy-associated changes in body composition and evaluated associations between body composition and incidence of grade 3 + AEs and post-RPLND complications on multivariable logistic regression analyses. RESULTS: One hundred and eighty-two men received a median of 3 cycles of cisplatin-based chemotherapy. Following chemotherapy, median change in SMI was -6% (P = <.0001), while VAI, SAI, and FMI increased by +13% (P = <.0001), +11% (P = <.0001), and +6% (P = <.0001), respectively. Seventy-nine patients (43%) experienced at least one grade 3 + AE. A decrease in SMI following chemotherapy was associated with increased risk of grade 3 + AEs (P = .047). One hundred and 3 men with a median age of 28.5 years (IQR 23-35.5) underwent RPLND of whom 22 (21.3%) experienced at least 1 grade 3 + post-RPLND complication. No baseline body composition metrics were associated with post-RPLND complications. CONCLUSION: In men with GCT of the testis, chemotherapy was associated with 6% loss of lean muscle mass and gains in adiposity. Lower skeletal muscle was associated with a higher incidence of chemotherapy-associated AEs. Body composition was not associated with the incidence of post-RPLND complications.

Factors Associated with Hospital Length of Stay and Adverse Events following Percutaneous Ablation of Lung Tumors.

PURPOSE: To explore the association between risk factors established in the surgical literature and hospital length of stay (HLOS), adverse events, and hospital readmission within 30 days after percutaneous image-guided thermal ablation of lung tumors. MATERIALS AND METHODS: This bi-institutional retrospective cohort study included 131 consecutive adult patients (67 men [51%]; median age, 65 years) with 180 primary or metastatic lung tumors treated in 131 sessions (74 cryoablation and 57 microwave ablation) from 2006 to 2019. Age-adjusted Charlson Comorbidity Index, sex, performance status, smoking status, chronic obstructive pulmonary disease (COPD), primary lung cancer versus pulmonary metastases, number of tumors treated per session, maximum axial tumor diameter, ablation modality, number of pleural punctures, anesthesia type, pulmonary artery-to-aorta ratio, lung densitometry, sarcopenia, and adipopenia were evaluated. Associations between risk factors and outcomes were assessed using univariable and multivariable generalized linear models. RESULTS: In univariable analysis, HLOS was associated with current smoking (incidence rate ratio [IRR], 4.54 [1.23-16.8]; P = .02), COPD (IRR, 3.56 [1.40-9.04]; P = .01), cryoablations with ≥3 pleural punctures (IRR, 3.13 [1.07-9.14]; P = .04), general anesthesia (IRR, 10.8 [4.18-27.8]; P < .001), and sarcopenia (IRR, 2.66 [1.10-6.44]; P = .03). After multivariable adjustment, COPD (IRR, 3.56 [1.57-8.11]; P = .003) and general anesthesia (IRR, 12.1 [4.39-33.5]; P < .001) were the only risk factors associated with longer HLOS. No associations were observed between risk factors and adverse events in multivariable analysis. Tumors treated per session were associated with risk of hospital readmission (P = .03). CONCLUSIONS: Identified preprocedural risk factors from the surgical literature may aid in risk stratification for HLOS after percutaneous ablation of lung tumors, but were not associated with adverse events.

Changes in skeletal muscle and adipose tissue during cytotoxic chemotherapy for testicular germ cell carcinoma and associations with adverse events.

OBJECTIVES: To quantify changes in body composition during cytotoxic chemotherapy for germ cell carcinoma of the testis (GCT) and evaluate associations between change in skeletal muscle and adipose tissue and chemotherapy-associated adverse events. MATERIALS AND METHODS: This retrospective single-institution study evaluated men with GCT treated with cytotoxic chemotherapy from 2005 to 2018. We measured skeletal muscle index (SMI [cm2/m2]), skeletal muscle density (SMD [Hounsfield Units (HU)]), skeletal muscle gauge (SMG [cm²*HU/m²]), fat mass index (FMI [kg/m2]), visceral adipose index (VAI [cm2/m2]), and subcutaneous adipose index (SAI [cm2/m2]) on axial computed tomography images at the level of the third lumbar vertebra within 75 days before and after chemotherapy. Chemotherapy-associated adverse events (AE) were graded based on the Common Terminology Criteria for Adverse Events (CTCAE v5.0.) Changes in body composition were quantified. Predictors of change in body composition were evaluated with multivariable linear regression. Associations between baseline or change in body composition and AEs were estimated with multivariable logistic regression adjusting for age, comorbidity, performance status, stage, and number/type of chemotherapy cycles. RESULTS: 141 patients (median age, 30 years [IQR 25-39]) including 86 patients (61%) with non-seminomatous GCT were included. Patients received a median of 3 cycles of cisplatin-based chemotherapy, and 124 patients (88%) completed planned chemotherapy. Median observed changes in SMI, SMD, and SMG were -6% (P<0.0001), -2% (P=0.07), and -7% (P<0.0001), respectively, while FMI increased 5.3% (P<0.0001). Overall, 120 patients (85%) experienced at least one AE including one or more ≥grade 3 AE in 57 patients (48%). Decrease in SMI (OR: 0.89, P=0.02), decrease in SMG (OR: 0.88, P=0.01,) and post-chemotherapy SMG (OR: 0.94, P=0.05) were independently associated with higher incidence of AEs, while pre-chemotherapy skeletal muscle parameters and post-chemotherapy SMI and SMD were not associated with AEs (P>0.05 for all). Preoperative adipose tissue or change in adiposity was not associated with incidence of AEs. CONCLUSIONS: In men with GCT receiving cytotoxic chemotherapy, a decrease in skeletal muscle mass and quality during chemotherapy were associated with a higher incidence of chemotherapy-associated AEs. Adipose tissue was not associated with the incidence of AEs.

Cenozoic evolution of deep ocean temperature from clumped isotope thermometry.

Characterizing past climate states is crucial for understanding the future consequences of ongoing greenhouse gas emissions. Here, we revisit the benchmark time series for deep ocean temperature across the past 65 million years using clumped isotope thermometry. Our temperature estimates from the deep Atlantic Ocean are overall much warmer compared with oxygen isotope-based reconstructions, highlighting the likely influence of changes in deep ocean pH and/or seawater oxygen isotope composition on classical oxygen isotope records of the Cenozoic. In addition, our data reveal previously unrecognized large swings in deep ocean temperature during early Eocene acute greenhouse warmth. Our results call for a reassessment of the Cenozoic history of ocean temperatures to achieve a more accurate understanding of the nature of climatic responses to tectonic events and variable greenhouse forcing.

Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy.

BACKGROUND. Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. OBJECTIVE. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). METHODS. This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. RESULTS. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], p = .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], p = .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], p < .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], p = .02, per 10-cm2/m2 increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; p < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. CONCLUSION. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. CLINICAL IMPACT. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.

A Fully Automated Deep Learning Pipeline for Multi-Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans.

Body composition on chest CT scans encompasses a set of important imaging biomarkers. This study developed and validated a fully automated analysis pipeline for multi-vertebral level assessment of muscle and adipose tissue on routine chest CT scans. This study retrospectively trained two convolutional neural networks on 629 chest CT scans from 629 patients (55% women; mean age, 67 years ± 10 [standard deviation]) obtained between 2014 and 2017 prior to lobectomy for primary lung cancer at three institutions. A slice-selection network was developed to identify an axial image at the level of the fifth, eighth, and 10th thoracic vertebral bodies. A segmentation network (U-Net) was trained to segment muscle and adipose tissue on an axial image. Radiologist-guided manual-level selection and segmentation generated ground truth. The authors then assessed the predictive performance of their approach for cross-sectional area (CSA) (in centimeters squared) and attenuation (in Hounsfield units) on an independent test set. For the pipeline, median absolute error and intraclass correlation coefficients for both tissues were 3.6% (interquartile range, 1.3%-7.0%) and 0.959-0.998 for the CSA and 1.0 HU (interquartile range, 0.0-2.0 HU) and 0.95-0.99 for median attenuation. This study demonstrates accurate and reliable fully automated multi-vertebral level quantification and characterization of muscle and adipose tissue on routine chest CT scans. Keywords: Skeletal Muscle, Adipose Tissue, CT, Chest, Body Composition Analysis, Convolutional Neural Network (CNN), Supervised Learning Supplemental material is available for this article. © RSNA, 2022.

Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels.

BACKGROUND: Skeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level. METHODS: We performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric. RESULTS: We included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, µ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, µ = 2), respectively. CONCLUSIONS: Multivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.

Muscle Loss Is Associated with Overall Survival in Patients with Metastatic Colorectal Cancer Independent of Tumor Mutational Status and Weight Loss.

BACKGROUND: Survival in patients with metastatic colorectal cancer (mCRC) has been associated with tumor mutational status, muscle loss, and weight loss. We sought to explore the combined effects of these variables on overall survival. MATERIALS AND METHODS: We performed an observational cohort study, prospectively enrolling patients receiving chemotherapy for mCRC. We retrospectively assessed changes in muscle (using computed tomography) and weight, each dichotomized as >5% or ≤5% loss, at 3, 6, and 12 months after diagnosis of mCRC. We used regression models to assess relationships between tumor mutational status, muscle loss, weight loss, and overall survival. Additionally, we evaluated associations between muscle loss, weight loss, and tumor mutational status. RESULTS: We included 226 patients (mean age 59 ± 13 years, 53% male). Tumor mutational status included 44% wild type, 42% RAS-mutant, and 14% BRAF-mutant. Patients with >5% muscle loss at 3 and 12 months experienced worse survival controlling for mutational status and weight (3 months hazard ratio, 2.66; p < .001; 12 months hazard ratio, 2.10; p = .031). We found an association of >5% muscle loss with BRAF-mutational status at 6 and 12 months. Weight loss was not associated with survival nor mutational status. CONCLUSION: Increased muscle loss at 3 and 12 months may identify patients with mCRC at risk for decreased overall survival, independent of tumor mutational status. Specifically, >5% muscle loss identifies patients within each category of tumor mutational status with decreased overall survival in our sample. Our findings suggest that quantifying muscle loss on serial computed tomography scans may refine survival estimates in patients with mCRC. IMPLICATIONS FOR PRACTICE: In this study of 226 patients with metastatic colorectal cancer, it was found that losing >5% skeletal muscle at 3 and 12 months after the diagnosis of metastatic disease was associated with worse overall survival, independent of tumor mutational status and weight loss. Interestingly, results did not show a significant association between weight loss and overall survival. These findings suggest that muscle quantification on serial computed tomography may refine survival estimates in patients with metastatic colorectal cancer beyond mutational status.

Machine Learning in Body Composition Analysis.

Body composition analysis (BCA) generates objective anthropometric data that can inform prognostication and treatment decisions across a wide variety of urologic conditions. A patient's body composition, specifically muscle and adipose tissue mass, may be characterized via segmentation of cross-sectional images (computed tomography, magnetic resonance imaging) obtained as part of routine clinical care. Unfortunately, conventional semi-automated segmentation techniques are time- and resource-intensive, precluding translation into clinical practice. Machine learning (ML) offers the potential to automate and scale rapid and accurate BCA. To date, ML for BCA has relied on algorithms called convolutional neural networks designed to detect and analyze images in ways similar to human neuronal connections. This mini review provides a clinically oriented overview of ML and its use in BCA. We address current limitations and future directions for translating ML and BCA into clinical practice. PATIENT SUMMARY: Body composition analysis is the measurement of muscle and fat in your body based on analysis of computed tomography or magnetic resonance imaging scans. We discuss the use of machine learning to automate body composition analysis. The information provided can be used to guide shared decision-making and to help in identifying the best therapy option.

Significance of Acquisition Parameters for Adipose Tissue Segmentation on CT Images.

OBJECTIVE. CT-based body composition analysis quantifies skeletal muscle and adipose tissue. However, acquisition parameters and quality can vary between CT images obtained for clinical care, which may lead to unreliable measurements and systematic error. The purpose of this study was to estimate the influence of IV contrast medium, tube current-exposure time product, tube potential, and slice thickness on cross-sectional area (CSA) and mean attenuation of subcutaneous (SAT), visceral (VAT), and inter-muscular adipose tissue (IMAT). MATERIALS AND METHODS. We retrospectively analyzed 244 images from 105 patients. We applied semiautomated threshold-based segmentation to CTA, dual-energy CT, and CT images acquired as part of PET examinations. An axial image at the level of the third lumbar vertebral body was extracted from each examination to generate 139 image pairs. Images from each pair were obtained with the same scanner, from the same patient, and during the same examination. Each image pair varied in only one acquisition parameter, which allowed us to estimate the effect of the parameter using one-sample t or median tests and Bland-Altman plots. RESULTS. IV contrast medium application reduced CSA in each adipose tissue compartment, with percentage change ranging from -0.4% (p = .03) to -9.3% (p < .001). Higher tube potential reduced SAT CSA (median percentage change, -4.2%; p < .001) and VAT CSA (median percentage change, -2.8%; p = .001) and increased IMAT CSA (median percentage change, -5.4%; p = .001). Thinner slices increased CSA in the VAT (mean percentage change, 3.0%; p = .005) and IMAT (median percentage change, 17.3%; p < .001) compartments. Lower tube current-exposure time product had a variable effect on CSA (median percentage change, -3.2% for SAT [p < .001], -12.6% for VAT [p = .001], and 58.8% for IMAT [p < .001]). IV contrast medium and higher tube potential increased mean attenuation, with percentage change ranging from 0.8% to 1.7% (p < .05) and from 6.2% to 20.8% (p < .001), respectively. Conversely, thinner slice and lower tube current-exposure time product reduced mean attenuation, with percentage change ranging from -5.4% to -1.0% (p < .001) and from -8.7% to -1.8% (p < .001), respectively. CONCLUSION. Acquisition parameters significantly affect CSA and mean attenuation of adipose tissue. Details of acquisition parameters used for CT-based body composition analysis need to be scrutinized and reported to facilitate interpretation of research studies.

Associations of Skeletal Muscle With Symptom Burden and Clinical Outcomes in Hospitalized Patients With Advanced Cancer.

BACKGROUND: Low muscle mass (quantity) is common in patients with advanced cancer, but little is known about muscle radiodensity (quality). We sought to describe the associations of muscle mass and radiodensity with symptom burden, healthcare use, and survival in hospitalized patients with advanced cancer. METHODS: We prospectively enrolled hospitalized patients with advanced cancer from September 2014 through May 2016. Upon admission, patients reported their physical (Edmonton Symptom Assessment System [ESAS]) and psychological (Patient Health Questionnaire-4 [PHQ-4]) symptoms. We used CT scans performed per routine care within 45 days before enrollment to evaluate muscle mass and radiodensity. We used regression models to examine associations of muscle mass and radiodensity with patients' symptom burden, healthcare use (hospital length of stay and readmissions), and survival. RESULTS: Of 1,121 patients enrolled, 677 had evaluable muscle data on CT (mean age, 62.86 ± 12.95 years; 51.1% female). Older age and female sex were associated with lower muscle mass (age: B, -0.16; P<.001; female: B, -6.89; P<.001) and radiodensity (age: B, -0.33; P<.001; female: B, -1.66; P=.014), and higher BMI was associated with higher muscle mass (B, 0.58; P<.001) and lower radiodensity (B, -0.61; P<.001). Higher muscle mass was significantly associated with improved survival (hazard ratio, 0.97; P<.001). Notably, higher muscle radiodensity was significantly associated with lower ESAS-Physical (B, -0.17; P=.016), ESAS-Total (B, -0.29; P=.002), PHQ-4-Depression (B, -0.03; P=.006), and PHQ-4-Anxiety (B, -0.03; P=.008) symptoms, as well as decreased hospital length of stay (B, -0.07; P=.005), risk of readmission or death in 90 days (odds ratio, 0.97; P<.001), and improved survival (hazard ratio, 0.97; P<.001). CONCLUSIONS: Although muscle mass (quantity) only correlated with survival, we found that muscle radiodensity (quality) was associated with patients' symptoms, healthcare use, and survival. These findings underscore the added importance of assessing muscle quality when seeking to address adverse muscle changes in oncology.

Impact of acute-on-chronic liver failure and decompensated liver cirrhosis on psychosocial burden and quality of life of patients and their close relatives.

BACKGROUND: Patients with liver cirrhosis often suffer from complications such as ascites, gastrointestinal bleeding, and infections, resulting in impaired quality of life. Frequently, the close relatives of patients also suffer from a lower quality of life in chronic diseases. In recent years, acute-to-chronic liver failure has been defined as a separate entity with high mortality. Often several organs are affected which makes intensive care therapy necessary. Little is known about the influence of acute-on-chronic-liver failure (ACLF) on the quality of life of patients and the psychosocial burden on close relatives. AIM: The purpose of this prospective study is to investigate the influence of decompensated liver cirrhosis and the onset of ACLF of the patient's' quality of life and the psychosocial burden of close relatives. METHOD: In this non - randomized prospective cohort study a total of 63 patients with acute decompensation of liver cirrhosis and hospital admission were enrolled in the study. To assess the quality of life of patients, the disease specific CLDQ questionnaire was assessed. In addition. Quality of life and psychosocial burden of first degree relatives was measured using the generic SF-36 questionnaire as well as the Zarit Burden Score. RESULTS: 21 of the 63 patients suffered from ACLF. Patients with ACLF showed a lower quality of life in terms of worries compared to patients with only decompensated liver cirrhosis (3,57 ± 1,17 vs. 4,48 ± 1,27; p value: 0,008) and increased systemic symptoms (3,29 ± 1,19 vs. 4,48 ± 1,58; p value: 0,004). The univariate analysis confirmed the link between the existence of an ACLF and the concerns of patients. (p value: 0,001). The organ failure score was significantly associated with overall CLDQ scores, especially with worries and systemic symptoms of patients. Interestingly the psychosocial burden and quality of life of close relative correlates with patient's quality of life and was influenced by the onset of an acute-on-chronic liver failure. CONCLUSION: Patients with decompensated liver cirrhosis suffer from impaired quality of life. In particular, patients with ACLF have a significantly reduced quality of life. The extent of the psychosocial burden on close relative correlates with poor quality of life in patients with decompensated liver disease and is influenced by the existence of ACLF.

The mitochondrial type IB topoisomerase drives mitochondrial translation and carcinogenesis.

Mitochondrial topoisomerase IB (TOP1MT) is a nuclear-encoded topoisomerase, exclusively localized to mitochondria, which resolves topological stress generated during mtDNA replication and transcription. Here, we report that TOP1MT is overexpressed in cancer tissues and demonstrate that TOP1MT deficiency attenuates tumor growth in human and mouse models of colon and liver cancer. Due to their mitochondrial dysfunction, TOP1MT-KO cells become addicted to glycolysis, which limits synthetic building blocks and energy supply required for the proliferation of cancer cells in a nutrient-deprived tumor microenvironment. Mechanistically, we show that TOP1MT associates with mitoribosomal subunits, ensuring optimal mitochondrial translation and assembly of oxidative phosphorylation complexes that are critical for sustaining tumor growth. The TOP1MT genomic signature profile, based on Top1mt-KO liver cancers, is correlated with enhanced survival of hepatocellular carcinoma patients. Our results highlight the importance of TOP1MT for tumor development, providing a potential rationale to develop TOP1MT-targeted drugs as anticancer therapies.

Prospective evaluation of the impact of covert hepatic encephalopathy on quality of life and sleep in cirrhotic patients.

BACKGROUND: Minimal hepatic encephalopathy (HE) and HE grade 1 (HE1) according to the West Haven criteria have recently been grouped as one entity named-covert HE- (CHE). Data regarding the impact of CHE on health-related quality of life (HRQoL) and sleep quality are controversial. AIM: First, to determine whether CHE affects HRQoL and sleep quality of cirrhotic patients and second, whether minimal HE (MHE) and HE1 affect HRQoL and sleep quality to a comparable extent. METHODS: A total of 145 consecutive cirrhotic patients were enrolled. HE1 was diagnosed clinically according to the West Haven criteria. Critical flicker frequency and the Psychometric Hepatic Encephalopathy Score were used to detect MHE. Chronic Liver Disease Questionnaire (CLDQ) was used to assess HRQoL and Pittsburgh Sleep Quality Index (PSQI) was applied to assess sleep quality. RESULTS: Covert HE was detected in 59 (40.7%) patients (MHE: n = 40; HE1: n = 19). Multivariate analysis identified CHE (P < 0.001) and female gender (P = 0.006) as independent predictors of reduced HRQoL (CLDQ total score). CHE (P = 0.021), low haemoglobin (P = 0.024) and female gender (P = 0.003) were identified as independent predictors of poor sleep quality (PSQI total score). Results of CLDQ and PSQI were comparable in patients with HE1 and MHE (CLDQ: 4.6 ± 0.9 vs 4.5 ± 1.2, P = 0.907; PSQI: 11.3 ± 3.8 vs 9.9 ± 5.0, P = 0.3). CONCLUSION: Covert HE was associated with impaired HRQoL and sleep quality. MHE and HE1 affected both outcomes to a comparable extent supporting the use of CHE as a clinically useful term for patients with both entities of HE in clinical practice.