Scholarlink

Background <p>Sarcopenia significantly impacts quality of life and increases the risk for various health issues. This study aims to establish a new, effective diagnostic criterion for sarcopenia based on psoas muscle volume (PV) using computed tomography (CT).</p> Aims <p>We analyzed the population distribution of psoas muscle volume (PV), assessed its correlation with ASM indices, and developed CT-based diagnostic criteria for sarcopenia.</p> Methods <p>A total of 3,999 adults (2,085 men, 1,914 women; aged 22–89) who underwent abdominal CT and bioimpedance analysis (BIA) were included. Psoas muscle volume was automatically segmented using a deep-learning algorithm. Correlations with ASM indices were evaluated, and diagnostic criteria were established using (1) linear regression, (2) ROC analysis, and (3) T-score analysis referencing young, non-sarcopenic adults.</p> Results <p>The distribution of PV indices peaked in the 30s and declined with age, more sharply in men. PV showed strong correlations with ASM indices, particularly the PV/BMI index, which demonstrated the highest diagnostic accuracy. T-score adjustment to -2.0 better matched known prevalence rates.</p> Discussion <p>This study proposes CT-based diagnostic criteria for sarcopenia using psoas muscle volume, demonstrating strong correlation with established indices. These findings support opportunistic screening via CT, offering a practical, population-wide tool for early sarcopenia detection.</p> Conclusions <p>This study uncovers the distribution of PV across age groups, noting a significant decline from the 30s to the 70s. This advancement in the objective diagnosis of sarcopenia via imaging positions abdomen CT scans as a potential diagnostic screening tool for low muscle mass compatible with sarcopenia.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Psoas muscle volume as a diagnostic indicator for sarcopenia: criteria development and comparison with traditional diagnostic approaches

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月15日

查看全文
  • Woorim Choi,
  • Chul-Ho Kim,
  • Ji Wan Kim

摘要

Background

Sarcopenia significantly impacts quality of life and increases the risk for various health issues. This study aims to establish a new, effective diagnostic criterion for sarcopenia based on psoas muscle volume (PV) using computed tomography (CT).

Aims

We analyzed the population distribution of psoas muscle volume (PV), assessed its correlation with ASM indices, and developed CT-based diagnostic criteria for sarcopenia.

Methods

A total of 3,999 adults (2,085 men, 1,914 women; aged 22–89) who underwent abdominal CT and bioimpedance analysis (BIA) were included. Psoas muscle volume was automatically segmented using a deep-learning algorithm. Correlations with ASM indices were evaluated, and diagnostic criteria were established using (1) linear regression, (2) ROC analysis, and (3) T-score analysis referencing young, non-sarcopenic adults.

Results

The distribution of PV indices peaked in the 30s and declined with age, more sharply in men. PV showed strong correlations with ASM indices, particularly the PV/BMI index, which demonstrated the highest diagnostic accuracy. T-score adjustment to -2.0 better matched known prevalence rates.

Discussion

This study proposes CT-based diagnostic criteria for sarcopenia using psoas muscle volume, demonstrating strong correlation with established indices. These findings support opportunistic screening via CT, offering a practical, population-wide tool for early sarcopenia detection.

Conclusions

This study uncovers the distribution of PV across age groups, noting a significant decline from the 30s to the 70s. This advancement in the objective diagnosis of sarcopenia via imaging positions abdomen CT scans as a potential diagnostic screening tool for low muscle mass compatible with sarcopenia.