MS6 - Measuring Thoracic Muscle by Chest CT to Foresee Sarcopenia in Post-Covid 19 Patients
Year: 2025
Type: conference-paper
Abstract: Sarcopenia is characterized by progressive and generalized loss of strength and muscle mass, and may be a manifestation of post-COVID-19 syndrome.The diagnosis of sarcopenia can be obtained on Computed Tomography (CT) images using Cross Sectional Area (CSA) measurement.Quantify total CSA (CSAt), pectoral muscle (CSAp) and Skeletal Muscle Index (SMI) to predict the development of sarcopenia in post-Covid-19 patients.In 48 chest CT scans of post-Covid-19 adult patients, a slice at T4 level, was selected, at the level of descending and ascending aorta, as anatomic references. The CSAt of the pectoralis major muscle and total CSA of the pectoral, intercostal, paraspinal, dentate, latissimus dorsi and subscapularis muscles were calculated using ImageJ® software. The Skeletal Muscular Index (SMI) value was also calculated. A scale of 16 pixels/cm was determined and the background of the images was eliminated. Pixels were converted into a grey scale, then using the threshold technique (59 and 168), into binary images. A GE system with 64 rows, were used. The average total muscle area was (136.2 cm2) and the pectoral muscle area was (34.9 cm2). The maximum calculated value of the total SMI was 74.12 cm2/m2 and 26.16 cm2/m2 for the pectoral muscle. The correlation between BMI and the variables CSAt and SMIt did not show statistically significant results (R2=0.036 and R2=0.049): P>0.05No values were found for comparison of patients with sarcopenia in populations with similar characteristics.BMI isn’t a good predictor of CSAt and SMIt values, however it was concluded that a decrease in SMIt leads to a decrease in BMI in post-Covid-19 patients, which may represent an indicator of the development of sarcopenia. Women were more likely to develop sarcopenia.
Authors: Ribeiro, Maria M.C.P., Sarmento, Marta S.C.
Institution: Centro de Investigação em Saúde e Tecnologia
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6912109503
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