Your CT scans are hiding crucial TAVI survival data: Are you looking?

Figures

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  Fig. 1. Adipose tissue analysis for TAVI risk stratification. This figure illustrates how standard pre-TAVI CT assessment can be enhanced with adipose tissue evaluation at the L3 level, including measurements of SAT/VAT area, tissue density, and distribution patterns. The U-shaped curve demonstrates that both extremely low and high adipose tissue measures correlate with worse outcomes, with an optimal middle range associated with better survival. Integration of these parameters into clinical workflow may enable more precise patient selection and personalized management without additional testing burden.

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  Fig. 2. CT-derived body composition risk stratification algorithm for TAVI patients. The decision tree provides sex-specific thresholds for skeletal muscle index (S M I), visceral adipose tissue (VAT) density, subcutaneous adipose tissue (SAT) density, and VAT:SAT ratio measurements at the L3 vertebral level. Risk classification guides clinical decision-making and peri-procedural management strategies. Abbreviations: CT, computed tomography; HU, Hounsfield units; L3, third lumbar vertebra; MDT, multidisciplinary team; SAT, subcutaneous adipose tissue; SMI, skeletal muscle index; STS, Society of Thoracic Surgeons; TA VI, transcatheter aortic valve implantation; V AT, visceral adipose tissue. Data source: Risk thresholds adopted from [8]. Validation performed in Central European population; international validation recommended prior to widespread implementation.

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  Fig. 3. AI-automated tissue segmentation at the third lumbar vertebra (L3) demonstrating sarcopenic phenotype in a 51-year-old female patient (BMI 18.94). (A) Segmentation results using AI-based algorithm showing tissue classification: Skeletal muscle (red, reduced area indicative of sarcopenia); Visceral adipose tissue (yellow, VAT_CSA: 31.24 cm2); Subcutaneous adipose tissue (turquoise, SAT_CSA: 73.79 cm2, reduced layer); Intramuscular adipose tissue (not visible, IMAT_CSA: 7.24 cm2); Excluded regions (black). (B) Overlay of segmentation map on the original CT image demonstrating anatomical correspondence of tissue classification. (C) Original axial CT image at L3 level. This automated approach quantifies body composition parameters at L3 level, which our research identifies as having significant prognostic value in TAVI patients. The segmentation methodology employs neural networks for automated analysis of clinically acquired CT scans [11], enabling the extraction of adipose tissue characteristics with demonstrated prognostic value. The patient demonstrates a skeletal muscle index (SMI) of 34.07 cm2/m2, confirming sarcopenia in female patients. On the other hand, the adipose tissue…