Dataset Information

A guide for using NIH Image J for single slice cross-sectional area and composition analysis of the thigh from computed tomography.

ABSTRACT: Reports using computed tomography (CT) to estimate thigh skeletal muscle cross-sectional area and mean muscle attenuation are often difficult to evaluate due to inconsistent methods of quantification and/or poorly described analysis methods. This CT tutorial provides step-by-step instructions in using free, NIH Image J software to quantify both muscle size and composition in the mid-thigh, which was validated against a robust commercially available software, SliceOmatic. CT scans of the mid-thigh were analyzed from 101 healthy individuals aged 65 and older. Mean cross-sectional area and mean attenuation values are presented across seven defined Hounsfield unit (HU) ranges along with the percent contribution of each region to the total mid-thigh area. Inter-software correlation coefficients ranged from R2 = 0.92-0.99 for all specific area comparisons measured using the Image J method compared to SliceOmatic. We recommend reporting individual HU ranges for all areas measured. Although HU range 0-100 includes the majority of skeletal muscle area, HU range -29 to 150 appears to be the most inclusive for quantifying total thigh muscle. Reporting all HU ranges is necessary to determine the relative contribution of each, as they may be differentially affected by age, obesity, disease, and exercise. This standardized operating procedure will facilitate consistency among investigators reporting computed tomography characteristics of the thigh on single slice images. Trial Registration: ClinicalTrials.gov NCT02308228.

SUBMITTER: Long DE

PROVIDER: S-EPMC6366874 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A guide for using NIH Image J for single slice cross-sectional area and composition analysis of the thigh from computed tomography.

Long Douglas E DE Villasante Tezanos Alejandro G AG Wise James N JN Kern Philip A PA Bamman Marcas M MM Peterson Charlotte A CA Dennis Richard A RA

PloS one 20190207 2

Reports using computed tomography (CT) to estimate thigh skeletal muscle cross-sectional area and mean muscle attenuation are often difficult to evaluate due to inconsistent methods of quantification and/or poorly described analysis methods. This CT tutorial provides step-by-step instructions in using free, NIH Image J software to quantify both muscle size and composition in the mid-thigh, which was validated against a robust commercially available software, SliceOmatic. CT scans of the mid-thig ...[more]

PMID: 30730923

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Project description:BackgroundComputed tomography (CT) scans are routinely obtained in oncology and provide measures of muscle and adipose tissue predictive of morbidity and mortality. Automated segmentation of CT has advanced past single slices to multi-slice measurements, but the concordance of these approaches and their associations with mortality after cancer diagnosis have not been compared.MethodsA total of 2871 patients with colorectal cancer diagnosed during 2012-2017 at Kaiser Permanente Northern California underwent abdominal CT scans as part of routine clinical care from which mid-L3 cross-sectional areas and multi-slice T12-L5 volumes of skeletal muscle (SKM), subcutaneous adipose (SAT), visceral adipose (VAT) and intermuscular adipose (IMAT) tissues were assessed using Data Analysis Facilitation Suite, an automated multi-slice segmentation platform. To facilitate comparison between single-slice and multi-slice measurements, sex-specific z-scores were calculated. Pearson correlation coefficients and Bland-Altman analysis were used to quantify agreement. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for death adjusting for age, sex, race/ethnicity, height, and tumour site and stage.ResultsSingle-slice area and multi-slice abdominal volumes were highly correlated for all tissues (SKM R = 0.92, P < 0.001; SAT R = 0.97, P < 0.001; VAT R = 0.98, P < 0.001; IMAT R = 0.89, P < 0.001). Bland-Altman plots had a bias of 0 (SE: 0.00), indicating high average agreement between measures. The limits of agreement were narrowest for VAT ( ± 0.42 SD) and SAT ( ± 0.44 SD), and widest for SKM ( ± 0.78 SD) and IMAT ( ± 0.92 SD). The HRs had overlapping CIs, and similar magnitudes and direction of effects; for example, a 1-SD increase in SKM area was associated with an 18% decreased risk of death (HR = 0.82; 95% CI: 0.72-0.92), versus 15% for volume from T12 to L5 (HR = 0.85; 95% CI: 0.75-0.96).ConclusionsSingle-slice L3 areas and multi-slice T12-L5 abdominal volumes of SKM, VAT, SAT and IMAT are highly correlated. Associations between area and volume measures with all-cause mortality were similar, suggesting that they are equivalent tools for population studies if body composition is assessed at a single timepoint. Future research should examine longitudinal changes in multi-slice tissues to improve individual risk prediction.

Dataset Information

A guide for using NIH Image J for single slice cross-sectional area and composition analysis of the thigh from computed tomography.

Publications

A guide for using NIH Image J for single slice cross-sectional area and composition analysis of the thigh from computed tomography.

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