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CT Body Composition as Predictor of Exercise Therapy Outcome in Peripheral Arterial Disease

NCT07433309 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 128

Last updated 2026-02-25

No results posted yet for this study

Summary

Supervised exercise therapy (SET) is the recommended first treatment for patients with leg artery disease (peripheral arterial disease, PAD) causing pain when walking. However, approximately 40% of patients do not benefit meaningfully and go on to require a procedure to open the blocked arteries within three months. This study investigates whether body composition measurements - specifically the quality of muscle and the amount of belly fat - taken from a CT scan already performed as part of routine care, can identify before treatment begins which patients are unlikely to respond to exercise therapy. If confirmed, this approach would allow doctors to use information from a scan patients are already having, with no additional tests, to better match patients to the right treatment from the start.

Conditions

  • Sarcopenia
  • Body Composition
  • Sarcopenic Obesity
  • Peripheral Arterial Disease

Interventions

PROCEDURE

SET physiotherapy

36-session AHA 2019-concordant supervised exercise programme delivered over 12 weeks (3 sessions per week, 60 minutes each). Each session consists of 45 minutes of structured treadmill and resistance exercise plus 15 minutes of patient education on vascular risk factor management. Treadmill protocol: 3.2 km/h, walking to claudication pain level 3 on a four-point scale, resting to level 1, five to six cycles per session. Progression weeks 1-4: speed +0.3 km/h every two weeks (maximum 4.0 km/h); weeks 5-8: grade +1% every two weeks (maximum 3%). Resistance training from week 5 targeting major lower extremity muscle groups (progressing from 2 sets × 10 repetitions to 5 sets at \~70% one-repetition maximum). This is standard clinical care; the study does not allocate participants to exercise.

RADIATION

CT scan

Single-slice CT body composition analysis at the L3 vertebral level, extracted opportunistically from existing diagnostic CT angiography. Segmentation performed using AutoMATiCA (U-Net convolutional neural network). Compartments quantified: skeletal muscle (-29 to +150 HU within muscle fascia mask), visceral adipose tissue (-150 to -50 HU within peritoneal cavity), subcutaneous adipose tissue (-190 to -30 HU exterior to body wall), and intramuscular adipose tissue (-190 to -30 HU within muscle fascia, exterior to individual muscle boundaries). A second dedicated CT acquisition is performed at 3 months (T1) for exploratory longitudinal analysis.

Sponsors & Collaborators

  • Nemocnice AGEL Trinec-Podlesi a.s.

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2030-12-31
Completion
2031-01-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07433309 on ClinicalTrials.gov