Objective: To determine whether subcutaneous fat thickness measured on thoracic radiographs was associated with body condition score (BCS) in dogs. Animals-87 client-owned dogs (41 males and 46 females) with a median age of 10.0 years (range, 1 to 16 years) and median weight of 20.3 kg (range, 3.1 to 58.0 kg).
Procedures: Age, sex, body weight, and breed were recorded. Body condition scores (scale from 1 to 9) and muscle condition scores were assigned by a single investigator. Subcutaneous fat thickness was measured at the level of the eighth rib head on a dorsoventral or ventrodorsal radiographic view of the thorax by a single investigator. Ratios of subcutaneous fat thickness to the width of the midbody of T8 on the ventrodorsal or dorsoventral radiographic view (T8 ratio) and to the length of the midbody of T4 on a right lateral radiographic view (T4 ratio) were calculated and compared with BCS by means of the Spearman correlation method.
Results: Median BCS was 6 (range, 1 to 9), and all muscle condition scores were represented. There were significant correlations between BCS and T4 ratio (r = 0.86) and between BCS and T8 ratio (r = 0.84).
Conclusions And Clinical Relevance: Results indicated that in this population, there was a significant association between BCS and subcutaneous fat thickness measured on thoracic radiographs. Findings suggested that measuring subcutaneous fat thickness could aid in the retrospective assignment of BCS in studies involving dogs in which BCS was not recorded in the medical record.
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http://dx.doi.org/10.2460/ajvr.74.11.1400 | DOI Listing |
J Biomed Opt
January 2025
Texas A&M University, Department of Biomedical Engineering, College Station, Texas, United States.
Significance: Accurate values of skin optical properties are essential for developing reliable computational models and optimizing optical imaging systems. However, published values show a large variability due to a variety of factors, including differences in sample collection, preparation, experimental methodology, and analysis.
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J Vet Med Sci
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Department of Bioresource Sciences, Faculty of Agriculture, Kyushu University.
Ovariectomized (OVX) mice serve as a key model for studying postmenopausal metabolic changes, particularly obesity, as they mimic the hormonal state of postmenopausal women. However, our understanding remains limited regarding how hormonal and dietary factors affect different adipose tissues. Furthermore, precise documentation of experimental procedures and their effects on specific adipose tissue depots is essential for reproducible translational research.
View Article and Find Full Text PDFChild Obes
January 2025
Department of Pediactrics, The Children's Obesity Clinic, Accredited European Centre for Obesity Management, Copenhagen University Hospital Holbæk, Holbæk, Denmark.
Steatotic liver disease (SLD) represents a multisystem disease and is a common complication of childhood obesity. We studied fat content at the abdominal level (liver, subcutaneous, and visceral) and the response to childhood obesity management. In this retrospective longitudinal study, 8-18-year-olds with a body mass index (BMI) z-score above 1.
View Article and Find Full Text PDFQuant Imaging Med Surg
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Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China.
Fatty acid can potentially serve as biomarker for evaluating metabolic disorder and inflammation condition, and quantifying the double bonds is the key for revealing fatty acid information. This study presents an assessment of a deep learning approach utilizing deep image prior (DIP) for the quantification of double bonds and methylene-interrupted double bonds of triglyceride derived from chemical-shift encoded multi-echo gradient echo images, all achieved without the necessity for network training. The methodology implemented a cost function grounded in signal constraints to continually refine the neural network's parameters on a single slice of images through iterative processes.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
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