Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging
Objective: To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Design: Feature evaluation and test–retest reliability of softwares (NIHImage, SliceOmatic,...
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Published in | International Journal of Obesity Vol. 32; no. 1; pp. 100 - 111 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
01.01.2008
Nature Publishing Nature Publishing Group |
Subjects | |
Online Access | Get full text |
ISSN | 0307-0565 1476-5497 1476-5497 |
DOI | 10.1038/sj.ijo.0803696 |
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Abstract | Objective:
To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results.
Design:
Feature evaluation and test–retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue.
Subjects:
A random sample of 15 obese adults with type 2 diabetes.
Measurements:
Axial T1-weighted spin echo images centered at vertebral bodies of L2–L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test–retest reliability.
Results:
Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test–retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness.
Conclusion:
Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. |
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AbstractList | To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results.OBJECTIVETo examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results.Feature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue.DESIGNFeature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue.A random sample of 15 obese adults with type 2 diabetes.SUBJECTSA random sample of 15 obese adults with type 2 diabetes.Axial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability.MEASUREMENTSAxial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability.Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness.RESULTSThree of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness.Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages.CONCLUSIONFour out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Feature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. A random sample of 15 obese adults with type 2 diabetes. Axial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability. Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. Objective: To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Design: Feature evaluation and test–retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. Subjects: A random sample of 15 obese adults with type 2 diabetes. Measurements: Axial T1-weighted spin echo images centered at vertebral bodies of L2–L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test–retest reliability. Results: Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test–retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Conclusion: Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Feature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. A random sample of 15 obese adults with type 2 diabetes. Axial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability. Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. |
Audience | Academic |
Author | Ghosh, P Diehl, A.M Bonekamp, S Solga, S.F Smith, S Clark, J.M Horska, A Crawford, S Brancati, F.L |
AuthorAffiliation | 3 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA 4 Division of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA 5 Division of Neuroradiology, Russel H Morgan, Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA 2 The Johns Hopkins University School of Medicine, Baltimore, MD, USA 7 Division of Gastroenterology, Duke University Medical Center, Durham, NC, USA 1 Russel H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA 6 Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA 8 Pennington Biomedical Research Center, Baton Rouge, LA, USA |
AuthorAffiliation_xml | – name: 1 Russel H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA – name: 6 Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA – name: 3 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA – name: 7 Division of Gastroenterology, Duke University Medical Center, Durham, NC, USA – name: 5 Division of Neuroradiology, Russel H Morgan, Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA – name: 2 The Johns Hopkins University School of Medicine, Baltimore, MD, USA – name: 4 Division of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA – name: 8 Pennington Biomedical Research Center, Baton Rouge, LA, USA |
Author_xml | – sequence: 1 fullname: Bonekamp, S – sequence: 2 fullname: Ghosh, P – sequence: 3 fullname: Crawford, S – sequence: 4 fullname: Solga, S.F – sequence: 5 fullname: Horska, A – sequence: 6 fullname: Brancati, F.L – sequence: 7 fullname: Diehl, A.M – sequence: 8 fullname: Smith, S – sequence: 9 fullname: Clark, J.M |
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Keywords | subcutaneous adipose tissue magnetic resonance imaging abdominal adipose tissue image segmentation software evaluation visceral adipose tissue Human Evaluation Obesity Adipose tissue Nutrition Segmentation Nutrition disorder Software package Nuclear magnetic resonance imaging Abdomen Distribution Medical imagery Software Subcutaneous tissue Nutritional status Comparative study Quantitative analysis Viscus |
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PublicationTitle | International Journal of Obesity |
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Snippet | Objective:
To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features... To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess... |
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SubjectTerms | Abdomen abdominal fat Abdominal Fat - pathology Adipose tissue Adipose tissues adults Aged Algorithms Analysis Applications software Automation Biological and medical sciences Body fat computer software Correlation coefficient Design Diabetes diagnosis Diagnostic Imaging Diagnostic Imaging - methods Diagnostic Imaging - standards Epidemiology Female Gastroenterology Genital system. Mammary gland Health Promotion and Disease Prevention Humans Image Processing, Computer-Assisted Image Processing, Computer-Assisted - methods Internal Medicine Investigative techniques, diagnostic techniques (general aspects) longitudinal studies Magnetic resonance imaging Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - standards Male Medical sciences Medicine Medicine & Public Health Metabolic Diseases methods Middle Aged noninsulin-dependent diabetes mellitus Obesity Obesity - diagnosis Observer Variation original-article Overweight persons pathology Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques Public Health quantitative analysis Radiology Reproducibility Reproducibility of Results Software packages Software Validation Type 2 diabetes visceral fat Weight control |
Title | Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging |
URI | https://link.springer.com/article/10.1038/sj.ijo.0803696 https://www.ncbi.nlm.nih.gov/pubmed/17700582 https://www.proquest.com/docview/219174319 https://www.proquest.com/docview/47689599 https://www.proquest.com/docview/70196092 https://pubmed.ncbi.nlm.nih.gov/PMC3096530 |
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