Optimizing CT‐Based Models for Predicting Whole‐Body Fat in Rabbits

> 0.7, p < 0.001) for all but one body region-counting combination. The best model predicting whole-body Fat% used CT data from left kidney region, HU Range 2, and three-dimensional counting technique. The optimal model predicting whole-body fat (g) used CT data from the entire abdominal region, HU Range 1, and a one-dimensional counting technique. The CT-based models for estimating whole-body fat in rabbits are feasible. Model optimization requires appropriate selection of the body region, CT number ranges, and counting techniques.

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Publication Details

Journal
Veterinary Radiology & Ultrasound
Published
2026-05-01
DOI
https://doi.org/10.1111/vru.70160
Primary Topic
Body Composition Measurement Techniques
Type
article
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article

Optimizing CT‐Based Models for Predicting Whole‐Body Fat in Rabbits

Mette Louise Halck, Charlotte Reinhard Bjørnvad, Eva González Pérez, Fintan J. McEvoy et al.
Veterinary Radiology & Ultrasound
Body Composition Measurement Techniques
article

Optimizing CT‐Based Models for Predicting Whole‐Body Fat in Rabbits

Mette Louise Halck, Charlotte Reinhard Bjørnvad, Eva González Pérez, Fintan J. McEvoy, Panida Pongvittayanon, Cecilie Olsen, Anna Hvidbjerg Poulsen
article en

Abstract

> 0.7, p < 0.001) for all but one body region-counting combination. The best model predicting whole-body Fat% used CT data from left kidney region, HU Range 2, and three-dimensional counting technique. The optimal model predicting whole-body fat (g) used CT data from the entire abdominal region, HU Range 1, and a one-dimensional counting technique. The CT-based models for estimating whole-body fat in rabbits are feasible. Model optimization requires appropriate selection of the body region, CT number ranges, and counting techniques.

Veterinary Radiology & UltrasoundVol. 67(3)
University of Copenhagen (DK)
Openalex Percentile: Top 9%
Body Composition Measurement Techniques
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