Abdominal adipose tissue quantification on water-suppressed and non-water-suppressed MRI at 3T using semi-automated FCM clustering algorithm

Sunil K. Valaparla, Qi Peng, Feng Gao, Geoffrey D. Clarke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate measurements of human body fat distribution are desirable because excessive body fat is associated with impaired insulin sensitivity, type 2 diabetes mellitus (T2DM) and cardiovascular disease. In this study, we hypothesized that the performance of water suppressed (WS) MRI is superior to non-water suppressed (NWS) MRI for volumetric assessment of abdominal subcutaneous (SAT), intramuscular (IMAT), visceral (VAT), and total (TAT) adipose tissues. We acquired T1-weighted images on a 3T MRI system (TIM Trio, Siemens), which was analyzed using semi-automated segmentation software that employs a fuzzy c-means (FCM) clustering algorithm. Sixteen contiguous axial slices, centered at the L4-L5 level of the abdomen, were acquired in eight T2DM subjects with water suppression (WS) and without (NWS). Histograms from WS images show improved separation of non-fatty tissue pixels from fatty tissue pixels, compared to NWS images. Paired t-tests of WS versus NWS showed a statistically significant lower volume of lipid in the WS images for VAT (145.3 cc less, p=0.006) and IMAT (305 cc less, p<0.001), but not SAT (14.1 cc more, NS). WS measurements of TAT also resulted in lower fat volumes (436.1 cc less, p=0.002). There is strong correlation between WS and NWS quantification methods for SAT measurements (r=0.999), but poorer correlation for VAT studies (r=0.845). These results suggest that NWS pulse sequences may overestimate adipose tissue volumes and that WS pulse sequences are more desirable due to the higher contrast generated between fatty and non-fatty tissues.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2014
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
PublisherSPIE
ISBN (Print)9780819498311
DOIs
StatePublished - Jan 1 2014
EventMedical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, CA, United States
Duration: Feb 16 2014Feb 18 2014

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9038
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CitySan Diego, CA
Period2/16/142/18/14

Keywords

  • Abdominal MRI
  • Fuzzy c-means clustering
  • Image segmentation
  • Inter-muscular fat
  • Subcutaneous adipose tissue
  • Type 2 diabetes mellitus
  • Visceral adipose tissue
  • Water-suppressed T1-W GRE

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Valaparla, S. K., Peng, Q., Gao, F., & Clarke, G. D. (2014). Abdominal adipose tissue quantification on water-suppressed and non-water-suppressed MRI at 3T using semi-automated FCM clustering algorithm. In Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging [903802] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9038). SPIE. https://doi.org/10.1117/12.2043172