Dataset Information

Deep-Learning Assessed Muscular Hypodensity Independently Predicts Mortality in DLBCL Patients Younger Than 60 Years.

ABSTRACT: Muscle depletion (MD) assessed by computed tomography (CT) has been shown to be a predictive marker in solid tumors, but has not been assessed in non-Hodgkin's lymphomas. Despite software improvements, MD measurement remains highly time-consuming and cannot be used in clinical practice. This study reports the development of a Deep-Learning automatic segmentation algorithm (DLASA) to measure MD, and investigate its predictive value in a cohort of 656 diffuse large B cell lymphoma (DLBCL) patients included in the GAINED phase III prospective trial (NCT01659099). After training on a series of 190 patients, the DLASA achieved a Dice coefficient of 0.97 ± 0.03. In the cohort, the median skeletal muscle index was 50.2 cm2/m2 and median muscle attenuation (MA) was 36.1 Hounsfield units (HU). No impact of sarcopenia was found on either progression free survival (PFS) or overall survival (OS). Muscular hypodensity, defined as MA below the tenth percentile according to sex, was associated with a lower OS and PFS, respectively (HR = 2.80 (95% CI 1.58-4.95), p < 0.001, and HR = 2.22 (95% CI 1.43-3.45), p < 0.001). Muscular hypodensity appears to be an independent risk factor for mortality in DLBCL and because of DLASA can be estimated in routine practice.

SUBMITTER: Jullien M

PROVIDER: S-EPMC8466314 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deep-Learning Assessed Muscular Hypodensity Independently Predicts Mortality in DLBCL Patients Younger Than 60 Years.

Jullien Maxime M Tessoulin Benoit B Ghesquières Hervé H Oberic Lucie L Morschhauser Franck F Tilly Hervé H Ribrag Vincent V Lamy Thierry T Thieblemont Catherine C Villemagne Bruno B Gressin Rémy R Bouabdallah Kamal K Haioun Corinne C Damaj Gandhi G Fornecker Luc-Matthieu LM Schiano De Colella Jean-Marc JM Feugier Pierre P Hermine Olivier O Cartron Guillaume G Bonnet Christophe C André Marc M Bailly Clément C Casasnovas René-Olivier RO Le Gouill Steven S

Cancers 20210907 18

<h4>Background</h4>Muscle depletion (MD) assessed by computed tomography (CT) has been shown to be a predictive marker in solid tumors, but has not been assessed in non-Hodgkin's lymphomas. Despite software improvements, MD measurement remains highly time-consuming and cannot be used in clinical practice.<h4>Methods</h4>This study reports the development of a Deep-Learning automatic segmentation algorithm (DLASA) to measure MD, and investigate its predictive value in a cohort of 656 diffuse larg ...[more]

PMID: 34572728

Similar Datasets

Project description:BackgroundObesity, typically quantified in terms of Body Mass Index (BMI) exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI), it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC) is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC.Methods and findingsWe considered a USA population sample of 14,105 non-pregnant adults (age ≥ 18) from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 with follow-up for mortality averaging 5 yr (828 deaths). We developed A Body Shape Index (ABSI) based on WC adjusted for height and weight: ABSI ≡ WC/(BMI(2/3)height(1/2)). ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of +33% per standard deviation of ABSI [95% confidence interval: +20%-+48%), whereas elevated death rates were found for both high and low values of BMI and WC. 22% (8%-41%) of the population mortality hazard was attributable to high ABSI, compared to 15% (3%-30%) for BMI and 15% (4%-29%) for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity), and was not weakened by excluding deaths from the first 3 yr of follow-up.ConclusionsBody shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.

Dataset Information

Deep-Learning Assessed Muscular Hypodensity Independently Predicts Mortality in DLBCL Patients Younger Than 60 Years.

Publications

Deep-Learning Assessed Muscular Hypodensity Independently Predicts Mortality in DLBCL Patients Younger Than 60 Years.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets