| 1. |
- Haufe, William, et al.
(författare)
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Feasibility of an automated tissue segmentation technique in a longitudinal weight loss study
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- To address the problems inherent in manual methods, a novel, semi-automated tissue segmentation image analysis technique has been developed. The purpose of this study was to demonstrate the feasibility and describe preliminary observations of applying this technique to quantify and monitor longitudinal changes in abdominal adipose tissue and thigh muscle volume in obese adults during weight loss. Abdominal adipose tissue and thigh muscle volume decreased during weight loss. As a proportion of body weight, adipose tissue volumes decreased during weight loss. By comparison, as a proportion of body weight, thigh muscle volume increased.
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| 2. |
- Middleton, Michael, et al.
(författare)
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Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction : Repeatability and Accuracy of an MR Imaging–based, Semiautomated Analysis Method
- 2017
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Ingår i: Radiology. - : Radiological Society of North America, Inc.. - 0033-8419 .- 1527-1315. ; 283:2, s. 438-449
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Tidskriftsartikel (refereegranskat)abstract
- PurposeThe purpose of this study was to determine the repeatability and accuracy of an commercially available (Advanced MR Analytics [AMRA®]; Linköping, Sweden) magnetic resonance imaging (MRI)-based, semi-automated method to quantify abdominal adipose tissue and thigh muscle volume as well as hepatic proton density fat fraction (PDFF)Materials and MethodsThis prospective study was approved by an institutional review board (IRB) and was Health Insurance Portability and Accountability Act (HIPAA) compliant. All subjects provided written informed consent. Inclusion criteria were age ≥ 18 years, and willingness to participate. Exclusion criteria were contraindication to MRI. Three-dimensional, T1-weighted, dual-echo body-coil images were acquired from base of skull to knees at 3T, twice before and once after taking subjects off the scanner table (total of three acquisitions). Source images were reconstructed offline to generate water, and calibrated fat images where pure adipose tissue has unit value and absence of adipose tissue has zero value. Abdominal adipose tissues and thigh muscles were segmented, and their volumes estimated using AMRA a semi-automated analysis method and, as a reference standard, manually. Hepatic PDFF was estimated using a confounder-corrected chemical-shift encoded MRI method with hybrid complex-magnitude reconstruction., and, as a reference standard, with magnetic resonance spectroscopy (MRS). Tissue volume and hepatic PDFF intra- and inter-examination repeatability was assessed by intraclass correlation (ICC) and coefficient of variation (CV) analysis. Tissue volume and hepatic PDFF accuracies were assessed by linear regression using their respective reference standards.ResultsTwenty adult subjects were enrolled (18 female, age range 25 - 76 yrs, body mass index range 19.3 to 43.9 kg/m2). Adipose and thigh muscle tissue volumes estimated using the semi-automated analysis method had intra-and inter-examination ICCs between 0.996 and 0.998, and CVs between 1.5 and 3.6%. For hepatic MRI PDFF, intra- and inter-examination ICCs were ≥ 0.994 and CVs, ≤ 7.3%. Agreement between semi-automated and manual volume estimates, and between MRI and MRS hepatic PDFF estimates, was high, with regression slopes and intercepts not significantly different from the identity line (all p’s > 0.05), and R2’s between 0.744 and 0.994.ConclusionsThis MRI-based, semi-automated method provides high repeatability, and high accuracy for estimating abdominal adipose tissue and thigh muscle volumes, and hepatic PDFF.
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| 3. |
- Middleton, Michael, et al.
(författare)
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Repeatability and accuracy of a novel, MRI-based, semi-automated analysis method for quantifying abdominal adipose tissue and thigh muscle volumes
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Current MRI methods to estimate body tissue compartment volumes rely on manual segmentation, which is laborious, expensive, not widely available outside specialized centers, and not standardized. To address these concerns, a novel, semi-automated image analysis method has been developed. Image acquisition takes about six minutes, and uses widely available MRI pulse sequences. We found that this method permits comprehensive body compartment analysis and provides high repeatability and accuracy. Current and future clinical and drug development studies may benefit from this methodology, as may clinical settings where monitoring change in these measures is desired.
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