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Prognostic Value of Artificial Intelligence-Driven, Computed Tomography-Based, Volumetric Assessment of the Volume and Density of Muscle in Patients With Colon Cancer

OBJECTIVE: The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal w...

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Detalles Bibliográficos
Autores principales: Kim, Minsung, Lee, Sang Min, Son, Il Tae, Park, Taeyong, Oh, Bo Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462901/
https://www.ncbi.nlm.nih.gov/pubmed/37634640
http://dx.doi.org/10.3348/kjr.2023.0109
Descripción
Sumario:OBJECTIVE: The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. MATERIALS AND METHODS: We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. RESULTS: Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the non-sarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the non-myosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25–2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84–3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08–3.54]; P = 0.027). CONCLUSION: Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.