Area of muscle, fat, and bone is often measured in thigh CT scans when tissue composition is a key outcome. SliceOmatic software is commonly referenced for such analysis but published methods may be insufficient for new users. Thus, a quick start guide to calculating thigh composition using SliceOmatic has been developed.
CT images of the thigh were collected from older (69 ± 4 yrs, N = 24) adults before and after 12-weeks of resistance training. SliceOmatic was used to segment images into seven density regions encompassing fat, muscle, and bone from -190 to +2000 Hounsfield Units [HU]. The relative contributions to thigh area and the effects of tissue density overlap for skin and marrow with muscle and fat were determined.
The largest contributors to the thigh were normal fat (-190 to -30 HU, 29.1 ± 7.4%) and muscle (35 to 100 HU, 48.9 ± 8.2%) while the smallest were high density (101 to 150 HU, 0.79 ± 0.50%) and very high density muscle (151 to 200 HU, 0.07 ± 0.02%). Training significantly (P < 0.05) increased area for muscle in the very low (-29 to -1 HU, 5.5 ± 7.9%), low (0 to 34 HU, 9.6 ± 16.8%), normal (35 to 100 HU, 4.2 ± 7.9%), and high (100 to 150 HU, 70.9 ± 80.6%) density ranges for muscle. Normal fat, very high density muscle and bone did not change (P > 0.05). Contributions to area were altered by ~1% or less and the results of training were not affected by accounting for skin and marrow.
When using SliceOmatic to calculate thigh composition, accounting for skin and marrow may not be necessary. We recommend defining muscle as -29 to +200 HU but that smaller ranges (e.g. low density muscle, 0 to 34 HU) can easily be examined for relationships with the health condition and intervention of interest.
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This work was supported by Merit Review Award RX0012030 to RAD from the United States Department of Veterans Affairs, Rehabilitation Research and Development Service (https://www.research.va.gov/services/rrd.cfm) but does not represent the views of the VA or US Government.
All relevant data are within the paper and its Supporting Information files.
S1 File. This is the Scan 1.dcm file. https://doi.org/10.1371/journal.pone.0204529.s001 (DCM)
S2 File. This is the Scan 2.dcm file. https://doi.org/10.1371/journal.pone.0204529.s002 (DCM)
S3 File. This is the Scan 3.dcm file. https://doi.org/10.1371/journal.pone.0204529.s003 (DCM)
S4 File. This is the Scan 4.dcm file. https://doi.org/10.1371/journal.pone.0204529.s004 (DCM)
S5 File. This is the Scan 5.dcm file. https://doi.org/10.1371/journal.pone.0204529.s005 (DCM)
S6 File. This is the Thigh Segmentation Tutorial.scp file. https://doi.org/10.1371/journal.pone.0204529.s006 (SCP)
S7 File. This is the Thigh Threshold 1.scp file. https://doi.org/10.1371/journal.pone.0204529.s007 (SCP)
S8 File. This is the Thigh Threshold 2.scp file. https://doi.org/10.1371/journal.pone.0204529.s008 (SCP)
S9 File. This is the Scan Analysis Dataset.xlsx file. https://doi.org/10.1371/journal.pone.0204529.s009 (XLSX)
S10 File. This is the Results.csv file. https://doi.org/10.1371/journal.pone.0204529.s010 (CSV)
Dennis, Richard A.; Long, Douglas E.; Landes, Reid D.; Padala, Kalpana P.; Padala, Prasad R.; Garner, Kimberly K.; Wise, James N.; Peterson, Charlotte A.; and Sullivan, Dennis H., "Tutorial for Using SliceOmatic to Calculate Thigh Area and Composition from Computed Tomography Images from Older Adults" (2018). Center for Muscle Biology Faculty Publications. 6.
S1 File. This is the Scan 1.dcm file.
journal.pone.0204529.s002.dcm (514 kB)
S2 File. This is the Scan 2.dcm file.
journal.pone.0204529.s003.dcm (514 kB)
S3 File. This is the Scan 3.dcm file.
journal.pone.0204529.s004.dcm (514 kB)
S4 File. This is the Scan 4.dcm file.
journal.pone.0204529.s005.dcm (514 kB)
S5 File. This is the Scan 5.dcm file.
journal.pone.0204529.s006.scp (1 kB)
S6 File. This is the Thigh Segmentation Tutorial.scp file.
journal.pone.0204529.s007.scp (1 kB)
S7 File. This is the Thigh Threshold 1.scp file.
journal.pone.0204529.s008.scp (1 kB)
S8 File. This is the Thigh Threshold 2.scp file.
journal.pone.0204529.s009.xlsx (17 kB)
S9 File. This is the Scan Analysis Dataset.xlsx file.
journal.pone.0204529.s010.csv (1 kB)
S10 File. This is the Results.csv file.