Quantification of Abdominal Fat Depots in Rats and Mice during Obesity and Weight Loss Interventions

Abstract

Background & AimsObesity is a leading healthcare issue contributing to metabolic diseases. There is a great interest in non-invasive approaches for quantitating abdominal fat in obese animals and humans. In this work, we propose an automated method to distinguish and quantify subcutaneous and visceral adipose tissues (SAT and VAT) in rodents during obesity and weight loss interventions. We have also investigated the influence of different magnetic resonance sequences and sources of variability in quantification of fat depots.Materials and MethodsHigh-fat diet fed rodents were utilized for investigating the changes during obesity, exercise, and calorie restriction interventions (N = 7/cohort). Imaging was performed on a 7T Bruker ClinScan scanner using fast spin echo (FSE) and Dixon imaging methods to estimate the fat depots. Finally, we quantified the SAT and VAT volumes between the L1–L5 lumbar vertebrae using the proposed automatic hybrid geodesic region-based curve evolution algorithm.ResultsSignificant changes in SAT and VAT volumes (p<0.01) were observed between the pre- and post-intervention measurements. The SAT and VAT were 44.22±9%, 21.06±1.35% for control, −17.33±3.07%, −15.09±1.11% for exercise, and 18.56±2.05%, −3.9±0.96% for calorie restriction cohorts, respectively. The fat quantification correlation between FSE (with and without water suppression) sequences and Dixon for SAT and VAT were 0.9709, 0.9803 and 0.9955, 0.9840 respectively. The algorithm significantly reduced the computation time from 100 sec/slice to 25 sec/slice. The pre-processing, data-derived contour placement and avoidance of strong background–image boundary improved the convergence accuracy of the proposed algorithm.ConclusionsWe developed a fully automatic segmentation algorithm to quantitate SAT and VAT from abdominal images of rodents, which can support large cohort studies. We additionally identified the influence of non-algorithmic variables including cradle disturbance, animal positioning, and MR sequence on the fat quantification. There were no large variations between FSE and Dixon-based estimation of SAT and VAT.

Hepatic fat fraction and visceral adipose tissue fatty acid composition in mice: Quantification with 7.0T MRI

“…Rodent models are widely used to monitor both the dynamics of fat accumulation during obesity and antiobesity interventions (13). MRI and MR spectroscopy (MRS) have mainly been used for fat quantification (14)(15)(16)(17)(18)(19).…”

Application of Raman spectroscopy in comparative study of antiobesity influence of oxytocin and freeze‐dried extracts of Uvariodendron anisatum Verdeck (Annonaceae) in Sprague Dawley rats

“…There is no consensus yet on the method of determining obese from nonobese rats. Often, rats with fasting blood glucose (FBG) levels above 7 mmol/L and those with increased volumes of subcutaneous and visceral adipose tissues are regarded as obese. Treatment of obesity involves either administration of antiobesity drugs or increase in physical exercise plus reduction of high‐energy diet.…”

Raman Spectroscopic comparative study of Oxytocin and Freeze-dried Extract of Uvariodendron anisatum Verdeck (Annonaceae) and their influence on diet induced obesity in Sprague Dawley rats

“…obesity and is overweight. In rodent models, there is no universally agreed method of determining obese from 60 non-obese rats but often those with fasting blood glucose (FBG) levels above 7 mmol/L [4] and 61 those with increased volumes of subcutaneous and visceral adipose tissues [3] The Raman spectra from UAV freeze dried extracts and those from commercially available 159 oxytocin displayed identical profiles and so indicating similar molecular composition (see Fig. 1).…”

“…The peaks centered at 1033 and 1130 cm -1 are ascribed to C-N stretch, NH 3 When Raman spectroscopy is to be used to make quick examination of influence of oxytocin and 228 UA extracts on obesity, a method to distinguish between spectral profiles from the different blood had explained variance of 74.7% and 9.5% respectively. The spectra from obese rats were clearly 240 distinguished from non-obese and the treated rats.…”

“…are regarded as62 obese. An obese individual has risks of developing chronic metabolic diseases such as type II 63 diabetes, hypertension, coronary heart disease, cancer among others[1,3,5]. Management of this 64 metabolic condition involves use of anti-obesity drugs, increase in physical exercise, reduction of males, the levels of oxytocin in blood of type II diabetic subjects were found to be lower than in 82 healthy ones[19].…”