Dataset Information

Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis.

ABSTRACT:

Background

The obesity epidemic has prompted the need to better understand the impact of adipose tissue on human pathophysiology. However, accurate, efficient, and replicable models of quantifying adiposity have yet to be developed and clinically implemented. We propose a novel semiautomated radiologic method of measuring the visceral fat area (VFA) using computed tomography scan analysis.

Materials and methods

We obtained a cohort of 100 patients with rectal adenocarcinoma, with a median age of 60.9 y (age range: 35-87 y) and an average body mass index of 28.8 kg/m² ± 6.56 kg/m². The semiautomated quantification method of adiposity was developed using a commercial imaging suite. The method was compared to two manual delineations performed using two different picture archiving communication systems. We quantified VFA, subcutaneous fat area (SFA), total fat area (TFA), and visceral-to-subcutaneous fat ratio (V/S ratio) on computed tomography axial slices that were at the L4-L5 intervertebral level.

Results

The semiautomated method was comparable to manual measurements for TFA, VFA, and SFA with intraclass correlation (ICC) of 0.99, 0.97, and 0.96, respectively. However, the ICC for the V/S ratio was only 0.44, which led to the identification of technical outliers that were identified using robust regression. After removal of these outliers, the ICC improved to 0.99 for TFA, VFA, and SFA and 0.97 for the V/S ratio. Measurements from the manual methodology highly correlated between the two picture archiving communication system platforms, with ICC of 0.98 for TFA, 0.98 for VFA, 0.96 for SFA, and 0.95 for the V/S ratio.

Conclusions

This semiautomated method is able to generate precise and reproducible results. In the future, this method may be applied on a larger scale to facilitate risk stratification of patients using measures of abdominal adiposity.

SUBMITTER: Srikumar T

PROVIDER: S-EPMC7771581 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis.

Srikumar Thejal T Siegel Erin M EM Gu Yuhua Y Balagurunathan Yoganand Y Garcia Alberto L AL Chen Y Ann YA Zhou Jun-Min JM Zhao Xiuhua X Gillies Robert R Clark Whalen W Gamenthaler Andrew A Choi Junsung J Shibata David D

The Journal of surgical research 20190114

<h4>Background</h4>The obesity epidemic has prompted the need to better understand the impact of adipose tissue on human pathophysiology. However, accurate, efficient, and replicable models of quantifying adiposity have yet to be developed and clinically implemented. We propose a novel semiautomated radiologic method of measuring the visceral fat area (VFA) using computed tomography scan analysis.<h4>Materials and methods</h4>We obtained a cohort of 100 patients with rectal adenocarcinoma, with ...[more]

PMID: 30694786

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Project description:Higher body mass index is associated with increased risk of acute kidney injury after major trauma. Since body mass index is nonspecific, reflecting lean, fluid, and adipose mass, we evaluated the use of CT to determine if abdominal adiposity underlies the body mass index-acute kidney injury association.Prospective cohort study.Level I Trauma Center of a university hospital.Patients older than 13 years with an Injury Severity Score greater than or equal to 16 admitted to the trauma ICU were followed for development of acute kidney injury over 5 days. Those with isolated severe head injury or on chronic dialysis were excluded.None.Clinical, anthropometric, and demographic variables were collected prospectively. CT images at the level of the L4-5 intervertebral disc space were extracted from the medical record and used by two operators to quantitate visceral adipose tissue and subcutaneous adipose tissue areas. Acute kidney injury was defined by Acute Kidney Injury Network creatinine and dialysis criteria. Of 400 subjects, 327 (81.8%) had CT scans suitable for analysis: 264 of 285 (92.6%) blunt trauma subjects and 63 of 115 (54.8%) penetrating trauma subjects. Visceral adipose tissue and subcutaneous adipose tissue areas were highly correlated between operators (intraclass correlation > 0.99, p < 0.001 for each) and within operator (intraclass correlation > 0.99, p < 0.001 for each). In multivariable analysis, the standardized risk of acute kidney injury was 15.1% (95% CI, 10.6-19.6%), 18.1% (14-22.2%), and 23.1% (18.3-27.9%) at the 25th, 50th, and 75th percentiles of visceral adipose tissue area, respectively (p = 0.001), with similar findings when using subcutaneous adipose tissue area as the adiposity measure.Quantitation of abdominal adiposity using CT scans obtained for clinical reasons is feasible and highly reliable in critically ill trauma patients. Abdominal adiposity is independently associated with acute kidney injury in this population, confirming that excess adipose tissue contributes to the body mass index-acute kidney injury association. Further studies of the potential mechanisms linking adiposity with acute kidney injury are warranted.

Project description:In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series.Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols.Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use of the previous normal-dose scan via the presented ndiNLM algorithm is noticeable as compared to a similar approach without using the previous normal-dose scan.For low-dose CT image restoration, the presented ndiNLM method is robust in preserving the spatial resolution and identifying the low-contrast structure. The authors can draw the conclusion that the presented ndiNLM algorithm may be useful for some clinical applications such as in perfusion imaging, radiotherapy, tumor surveillance, etc.

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Dataset Information

Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis.

Background

Materials and methods

Results

Conclusions

Publications

Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis.

Similar Datasets

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