Sliceomatic v4

During this study, sarcopenia was diagnosed using the assessment criteria provided by the 2019 Consensus Update on Sarcopenia Diagnosis and Treatment reported by the AWGS³ . According to these criteria, sarcopenia was defined as a low SMI and low handgrip strength. Handgrip strength was measured using a Smedley handgrip dynamometer (TTM, Tokyo, Japan) while the participant was in a standing position. Two trials were performed for the right and left hands, and the two highest values were averaged and entered into the analysis. The cutoff values for low MS were 28 kg for males and 18 kg for females. The SMI was calculated using the BIA (InBody 770; InBody Japan, Tokyo, Japan)^{17 (link)}; the sum of the skeletal muscle mass of the arms and legs was divided by the square of the individual’s height (kg/m²). The cutoff values for a low SMI were 7.0 kg/m² for males and 5.7 kg/m² for females.
If a CT scan was performed according to clinical needs within approximately 1 month after consent was obtained, then the cross-sectional area of the skeletal muscles (cm²) at the level of the third lumbar (L3) vertebra was measured using image analysis software (sliceOmatic V4.3; TomoVision, Magog, Quebec, Canada)^{18 (link)}. The SMI was calculated based on the sum of this area divided by the square of the height (cm²/m²).

Skeletal muscle and density were calculated from the chest CT scan at thoracic vertebra 12 (T12). We used Hounsfield unit (HU) values at −29 to +150 HU to semi-automatically delineate muscle. Muscle area and density were quantified by SliceOmatic V4.3 software (Tomovision, Montreal, Canada). Mean paraspinal muscle density was measured to evaluate skeletal muscle fat content indirectly. According to previous study, the higher the muscle fat concentration, the lower the muscle density, skeletal muscle fat index (SMFI), was calculated as 100 *[Paraspinal muscle area (cm²)/paraspinal muscle density (HU)], to evaluate skeletal muscle fat content by CT-based paraspinal muscle density. Thus, and the higher the muscle fat content the higher the SMFI. All CT images were analyzed by one trained observer.

CT was performed within 7 days after enrollment. Muscle mass assessment was performed by measuring the muscle mass area at the level of L3, using appropriate software (SliceOmatic V4.3 software, Tomovision, Montreal, QC, Canada) as described by Georgiou A et al. [22 (link)]. Skeletal muscle was quantified using −29 to +150 Hounsfield Units (HU) range. The area was then adjusted to height in order to calculate skeletal mass index (SMI) (cm)²/height² (in m²). Furthermore, an analysis of muscular, visceral and subcutaneous adipose tissue was also performed. Myosteatosis was defined as muscle radiodensity at L3 < 41 HU for patients with dry BMI < 24.9 kg/m² and <33 HU for those with ≥25 kg/m² [9 (link),18 (link)]. The same software was utilized to calculate visceral adipose tissue index (VATI, cm²/m²) and subcutaneous adipose tissue index (SATI, cm²/m²).

To evaluate body composition, archived computed tomography (CT) images were requested from the Department of Radiology for eligible patients. Diagnostic images were used to assess pretreatment body composition. If available, the successive CT image was used to assess body composition change. A Radiology Technician accessed the Picture Archiving and Communication System to retrieve the specified test and locate the axial slice inclusive of the third lumbar (L3) region. All images were saved in Digital Imaging and Communications in Medicine (DICOM) format on an encrypted research network and subsequently analyzed by trained personnel using Slice-O-Matic (v 4.3, Tomovision, Montreal, QB). Automated tissue demarcation with manual correction was conducted using Hounsfield unit (HU) thresholds specific to the tissue compartment (−29 to +150 for SM, −190 to −30 for subcutaneous adipose tissue (SAT), and −150 to−50 for VAT) [26 (link)–28 ]. Quality assurance was performed on 10 random images by an outside expert (Dr. Sandra Gomez-Perez) certified in body composition analyses and not involved in data collection. Images were discussed and reanalyzed, if needed. Cross-sectional areas (cm²) of the SM and adipose tissue compartments were computed and normalized for stature to derive skeletal muscle index (SMI, cm²/m²), VAT Index (VATI, cm²/m²), and SAT Index (SATI, cm²/m²).