In vivo assessment of canine muscle adiposity by real time ultrasonography and image analysis (original) (raw)
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In vivo assessment of subcutaneous fat in dogs by real-time ultrasonography and image analysis
Acta Veterinaria Scandinavica, 2016
Background: Systems for estimating body condition score (BCS) are currently used in canine practice to monitor fatness levels. These tools are cheap and easy to use but lack the necessary precision to monitor small changes in body fat, particularly during weight control treatments or in research. The present work aims to study the application of real-time ultrasonography (RTU) together with image analysis in the assessment of subcutaneous fat depots in dogs. Ultrasound images were collected from five anatomical locations (chest, flank, abdomen, thigh and lumbar) from 28 healthy dogs of different breeds and with a body weight (BW) ranging from 5.2 to 33.0 kg. BCS was collected by visual appraisal using a 5-point scale. Subcutaneous fat thickness (SFT) was estimated from RTU images, using the average of three measurements taken in fat deposits located above the muscles represented in each image. Correlations were established between SFT and BW or BCS as well as a classification of BCS-based fatness [overweight (BCS = 4), ideal (BCS = 3) and lean (BCS = 2)]. Results: SFT was found to differ between the five regions considered (P < 0.001). Abdomen and thigh were the areas displaying the widest variation for the different dogs included in the study and also those correlating most with BW, in contrast to the chest, which showed the least variation. Overall, a strong correlation was found between BCS and SFT. The highest correlations were established for the flank, abdomen and lumbar areas. In every anatomical area, a decrease in SFT was observed across all three BCS classes, ranging from 48 to 65 % among overweight and ideal dogs, and from 46 to 83 % among ideal and lean dogs. Conclusions: Preliminary data showed that within this population there was a strong correlation between BCS and SFT estimated from RTU images. It was also observed that RTU measurements for fat thickness differed among the anatomical points surveyed suggesting differences in their sensitivity to a change in BCS. The images displaying the best prediction value for fatness variations were those collected at the lumbar and abdomen areas.
Journal of the American Veterinary Medical Association, 2014
To develop morphometric equations for prediction of body composition and create a body fat index (BFI) to estimate body fat percentage in overweight and obese dogs. Prospective evaluation study. 83 overweight or obese dogs ≥ 1 year of age. Body condition score (BCS) was assessed on a 5-point scale, morphometric measurements were made, and visual and palpation-based assessments and dual-energy x-ray absorptiometry (DEXA) were performed. Equations for predicting lean body mass, fat mass, and body fat as a percentage of total body weight (ie, body fat percentage) on the basis of morphometric measurements were generated with best-fit statistical models. Visual and palpation-based descriptors were used to develop a BFI. Predicted values for body composition components were compared with DEXA-measured values. For the study population, the developed morphometric equations accounted for 98% of the variation in lean body mass and fat mass and 82% of the variation in body fat percentage. The ...
Research in Veterinary Science, 2010
The objectives of this clinical study were firstly, to assess the effects of breed/genetic group on body composition in dogs using Dual-X-ray absorptiometry (DEXA) as the reference method and secondly, to check, in clinical field conditions, if methods easy to apply in veterinary practice [bioelectrical impedance (BIA), morphometric equations, body condition score and body mass index] can give similar body composition results to DEXA results, using canine breeds with very different genetic and morphologic backgrounds. 19 dogs from 6 breeds with different genetic origin were used. Results showed that breed differences exist regarding body composition in dogs. Body condition score and morphometric equation should be developed by breed or by groups of breeds for an accurate estimation of body composition of the various breeds of dogs with a different genetic background or morphology. Any of the other tested methodologies (BIA or morphometric equations) gave results in agreement with DEXA value, when dogs with different genetic background and morphologic characteristics are used, but BIA, eventually in combination with morphometric measurements, could be a method to develop to estimate fat-free mass in dogs of different breeds.
Canine body composition quantification using 3 tesla fat-water MRI
Journal of Magnetic Resonance Imaging, 2014
Purpose-To test the hypothesis that a whole-body fat-water MRI (FWMRI) protocol acquired at 3 Tesla combined with semi-automated image analysis techniques enables precise volume and mass quantification of adipose, lean and bone tissue depots that agree with static scale mass and scale mass changes in the context of a longitudinal study of large-breed dogs placed on an obesogenic high-fat, high-fructose diet. Materials and Methods-Six healthy adult male dogs were scanned twice, at weeks 0 (baseline) and 4, of the dietary regiment. FWMRI-derived volumes of adipose tissue (total, visceral, and subcutaneous), lean tissue, and cortical bone were quantified using a semi-automated approach. Volumes were converted to masses using published tissue densities. Results-FWMRI-derived total mass corresponds with scale mass with a concordance correlation coefficient of 0.931 (95% confidence interval = [0.813, 0.975]), and slope and intercept values of 1.12 and −2.23 kg respectively. Visceral, subcutaneous and total adipose tissue masses increased significantly from weeks 0 to 4, while neither cortical bone nor lean tissue masses changed significantly. This is evidenced by a mean percent change of 70.2% for visceral, 67.0% for subcutaneous, and 67.1% for total adipose tissue. Conclusion-FWMRI can precisely quantify and map body composition with respect to adipose, lean and bone tissue depots. The described approach provides a valuable tool to examine the role of distinct tissue depots in an established animal model of human metabolic disease.
Prediction of intramuscular fat in live bulls using real-time ultrasound and image analysis
Journal of Animal and Feed Sciences
Sonograms of Longissimus dorsi muscle (LDM) area were taken before slaughter on the last thoracic vertebra by an Aloka SSD-500. Three sonograms of each bull were taken with 60, 65 and 70% ultrasound intensity. A digital image of the LDM area was obtained on the last thoracic ver-tebra. Intramuscular fat content was detected by an Infratec 1265 -Meat Analyzer. The grey value of the sonogram measured by computer image analysis signifi cantly correlated with the content of IMF, r=0.78 for Slovak Simmental, and r=0.60 for Holstein bulls. Area proportion of marbling determined on images obtained by computer image analysis (MARB) correlated signifi cantly with IMF, r=0.65. This correlation was only signifi cant for Slovak Simmental bulls. The obtained results suggest that prediction of intramuscular fat in meat is possible using the technique of ultrasound and computer image analyses of live animals. Further investigation is needed to improve measurement precision and to validate applicab...
Veterinary World, 2022
Background and Aim: Obesity in dogs leads to several health problems, such as premature death, and contributes to other diseases. Recently, body fat percentage has been considered to represent the body condition of dogs, and bioelectrical impedance analysis (BIA) is the most effective method for accurately measuring body fat in dogs. In Thailand, information on the body condition of dogs is limited, and there is no standard body fat level for Thai or mongrel dogs. This study was designed to evaluate and analyze the body fat percentage in dogs through BIA using a handheld instrument. The results of this study can help enhance the quality of life and health of dogs and aid in setting a standard body fat level for Thai or mongrel dogs. Materials and Methods: The body fat percentage of 340 Thai and mongrel dogs in East Thailand was measured in the standing position, and the body condition score (BCS) (range, 1–5), sex, sterilization status, age, type of diet, and lifestyle were recorded. A linear regression model was developed to compare the variables and the predicted body fat percentage, and multiple linear regressions were used to analyze the factors for body fat increment. Results: The linear regression model used to estimate the percentage of body fat (y) for each BCS (x) was y = 0.84 + 8.36x (R2 = 0.7219; p < 0.0001); the average body fat percentage was 27.52% for all studied dogs; specifically, 24.83% for the Thai Bangkaew, 26.42% for the Thai Ridgeback, and 27.65% for mongrels. The median body fat percentage was significantly higher in female than in male dogs. We found that as age increases, body fat percentage also increases; this increasing trend begins at the age of 5 years. However, increasing the level of activity and decreasing meal frequency leads to an increase in body fat percentage in neutered male dogs. Conclusion: The average body fat percentage of dogs in East Thailand is 27.52% and this value is expected to increase when these dogs reach the age of 5 years. BIA is a valid and effective measurement tool for detecting the body fat percentage in dogs.
American Journal of Veterinary Research, 2001
Objective—To determine quantitative values for components of body composition in clinically normal dogs of various breeds by use of dual energy x-ray absorptiometry (DEXA) and validate the precision and accuracy of DEXA technology in dogs. Animals—103 clinically normal sexually intact adult dogs. Procedure—In a cross-sectional study, Beagles, Pembroke Welsh Corgis, Golden Retrievers, Great Danes, Pointers, Rottweilers, and nonpurebred dogs received total body DEXA scans. For the validation portion of the study, the results of DEXA scans of 6 dogs were compared with values obtained by chemical analyses of tissues from euthanatized dogs to determine the accuracy of this modality in dogs. Results—Results (coefficient of variation) of the precision tests ranged from 0.10% for lean tissue to 5.19% for fat tissue, whereas accuracy tests revealed a difference between percentage bone mineral content and ash values. Body composition differed by sex, such as higher lean tissue and bone minera...
BMC Veterinary Research, 2012
Background: Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations. Results: The independent variables determined by BIO, BIA and US that best correlated (p < 0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows'Cp statistics, p value and r 2 , 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats. Conclusions: The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed.
Exploration of body weight in 115 000 young adult dogs of 72 breeds
Scientific Reports, 2023
High body weight (BW), due to large size or excess body fat, has been associated with developmental and metabolic alterations, and degenerative diseases in dogs. Study objectives were to determine mean BW in young adult dogs of different breeds, including changes over a 10-year period. Body weight data from the official Swedish hip dysplasia screening program were used, including data from dogs screened at 1-2.5 years of age, in breeds with ≥ 15 individual observations/year during 2007-2016. Mean BW per breed and sex was established from 114 568 dogs representing 72 breeds. Estimates of breed BW showed significant change in 33 (45%) breeds over the 10-year period. Body weight increased in five breeds (2-14% change) and decreased in 26 breeds (1-8% change). In two breeds, BW increased in male and decreased in female dogs. This observational study provides extensive breed BW data on young adult dogs. The change in breed BW, noted in almost half of the breeds, could be due to changes either in size or in body fat mass. In certain breeds, the change in BW over time might have an impact on overall health. Studies with simultaneous evaluation of BW and body condition over time are warranted.
Acta Veterinaria Scandinavica, 2009
Background: Modern computer tomography (CT) equipment can be used to acquire whole-body data from large animals such as pigs in minutes or less. In some circumstances, computer assisted analysis of the resulting image data can identify and measure anatomical features. The thickness of subcutaneous adipose tissue at a specific site measured by ultrasound, is used in the pig industry to assess adiposity and inform management decisions that have an impact on reproduction, food conversion performance and sow longevity. The measurement site, called "P2", is used throughout the industry. We propose that CT can be used to measure subcutaneous adipose tissue thickness and identify novel measurement sites that can be used as predictors of general adiposity.