Informace o publikaci
Beyond BMI: An opinion on the clinical value of AI-powered CT body composition analysis
| Autoři | |
|---|---|
| Rok publikování | 2025 |
| Druh | Recenzovaný odborný článek |
| Časopis / Zdroj | Biomolecules and Biomedicine |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | https://www.bjbms.org/ojs/index.php/bjbms/article/view/12774 |
| Doi | https://doi.org/10.17305/bb.2025.12774 |
| Klíčová slova | Body composition; artificial intelligence; AI; computed tomography; CT; sarcopenia; visceral adipose tissue |
| Popis | Body Mass Index (BMI) has long been used as a standard measure for assessing population-level health risks, but its clinical adequacy has increasingly been called into question. This opinion paper challenges the clinical adequacy of BMI and presents AIenhanced CT body composition analysis as a superior alternative for individualized risk assessment. While BMI serves population-level screening, its inability to differentiate between tissue types leads to critical misclassifications, particularly for sarcopenic obesity. AI-powered analysis of CT imaging at the L3 vertebra level provides precise quantification of skeletal muscle index, visceral, and subcutaneous adipose tissues-metrics that consistently outperform BMI in predicting outcomes across oncology, cardiology, and critical care. Recent technological advances have transformed this approach: the "opportunistic" use of existing clinical CT scans eliminates radiation concerns, while AI automation has reduced analysis time from 15-20 minutes to mere seconds. These innovations effectively address previous implementation barriers and enable practical clinical application with minimal resource demands, creating opportunities for targeted interventions and personalized care pathways. |
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