Evaluation of Ethnic Variations in Visceral, Subcutaneous, Intra-Pancreatic, and Intra-Hepatic Fat Depositions by Magnetic Resonance Imaging among New Zealanders

Abstract

Anthropometric indices, such as body mass index (BMI), waist circumference (WC), and waist to height ratio (WHtR), have limitations in accurately predicting the pathophysiology of diabetes mellitus, cardiovascular diseases, and metabolic syndrome due to ethnic differences in fat distribution. Recent studies showed that the visceral adipose tissue (VAT) deposition and fat content of internal organs, most notably intra-hepatic and intra-pancreatic fat, has emerged as a more important parameter. In this study, we aimed to assess the coordination between the traditional anthropometric indices and the various fat depositions within different ethnicities in New Zealand. We recruited 104 participants with different ethnic backgrounds, including New Zealand Europeans, Māori (the indigenous people of New Zealand), Pacific Islanders (PI), and Asians. Their weight, height, and WC were measured, and subcutaneous, visceral, intra-hepatic, and intra-pancreatic fat depositions were obtained by magnetic resonance imaging (MRI). The result showed VAT, but not subcutaneous adipose tissue (SAT) depositions at all levels were significantly varied among the three groups. BMI was associated best with L23SAT in NZ Europeans (30%) and L45VAT in Māori/PI (24.3%). WC and WHtR were correlated well with L45SAT in the total population (18.8% and 12.2%, respectively). Intra-pancreatic fat deposition had a positive Pearson relationship with NZ European BMI and Māori/PI WC, but no regression correlation with anthropometric indices. Conventional anthropometric indices did not correspond to the same fat depositions across different ethnic groups.

Discussion: Anatomical Guidelines for Thigh Lipoplasty Based on Cadaveric Dissection of the Superficial Fascial System in the Thigh

“…Well, we do agree with the authors' suggestion of thorough deep and superficial liposuction over zones where fat pads are easily recognized (degree I) and that liposuction should be limited or restricted over adhesion zones (degree IV). In contrast, we disagree about degrees II and III, because the fat distribution over the saddlebags and the lateral thighs varies considerably among patients depending on their age, sex, underlying anatomy, and ethnic origins, [5][6][7] which means the treatment of those areas should be individualized. 8 The authors' report agrees with our recommendation of performing deep liposuction and almost no superficial liposuction over the posterior thigh, unless muscular definition is requested for the hamstrings/biceps femoris (extreme definition) 8 ; likewise, the retinaculum cutis profundus thickness close to the infragluteal crease follows our concept of gluteal pillars (surprisingly, the authors were inspired by the dougong structure) which should require only deep liposuction and smooth transitions toward the lateral borders (sometimes even fat grafting), to improve the strength and support of the buttocks.…”

“…Well, we do agree with the authors’ suggestion of thorough deep and superficial liposuction over zones where fat pads are easily recognized (degree I) and that liposuction should be limited or restricted over adhesion zones (degree IV). In contrast, we disagree about degrees II and III, because the fat distribution over the saddlebags and the lateral thighs varies considerably among patients depending on their age, sex, underlying anatomy, and ethnic origins, 5–7 which means the treatment of those areas should be individualized. 8…”

An Adapted Deep Convolutional Neural Network for Automatic Measurement of Pancreatic Fat and Pancreatic Volume in Clinical Multi-Protocol Magnetic Resonance Images: A Retrospective Study with Multi-Ethnic External Validation

“…All participants included in the study provided written informed consent. Our previous published datasets containing anthropometric measurement and pancreatic fat fractions from MRI readings and specialists were used as a reference for the newly trained DCNN [ 37 ]. The independent validation set was derived from additional data from 10 participants who were each scanned twice at the same center.…”

A fat fraction phantom for establishing new convolutional neural network to determine the pancreatic fat deposition

“…The pancreas fat fraction was also segmented manually by experts followed the description of MR-opsy method described by Al-Mrabeh et al. [ 20 , 25 , 26 ]. Using Image J to measure the percentage fat for all highlighted RoiSets within the ROI manager.…”