Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity
Abstract Abdominal adipose tissue (AT) amounts are increasingly considered as potential biomarkers for a variety of diseases and clinical questions, for instance, in diabetology, oncology or cardiovascular medicine. Despite the emergence of automated deep-learning methods for tissue quantification,...
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Nature Portfolio
2025-03-01
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| Online Access: | https://doi.org/10.1038/s41598-025-87578-4 |
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| author | A. Linder T. Eggebrecht N. Linder R. Stange A. Schaudinn M. Blüher T. Denecke Harald Busse |
| author_facet | A. Linder T. Eggebrecht N. Linder R. Stange A. Schaudinn M. Blüher T. Denecke Harald Busse |
| author_sort | A. Linder |
| collection | DOAJ |
| description | Abstract Abdominal adipose tissue (AT) amounts are increasingly considered as potential biomarkers for a variety of diseases and clinical questions, for instance, in diabetology, oncology or cardiovascular medicine. Despite the emergence of automated deep-learning methods for tissue quantification, interactive (supervised) segmentation tools will typically be used for model training. In comparison with CT-based approaches, MRI segmentation tools are more complex and less common. This work aims to validate a novel MRI-based tissue volumetry against a reference method in patients with (pre-) obesity. The new tool (segfatMR) was developed under a Matlab-based, open-source software framework and combines fast automatic pre-segmentation followed by manual (expert) corrections where needed. Analyses were performed retrospectively on a subset of clinical research MRI datasets (1.5 T Achieva XR, Philips Healthcare) and involved the segmentation of datasets from 20 patients (10 women/men) aged 25.1–63.1 (mean 48.5) years with BMIs between 28.3 and 58.8 (mean 36.8) kg/m2. Two independent expert readers analyzed the abdominopelvic data (30–40 slices, mean 35.8) with segfatMR and a widely used commercial tool (sliceOmatic). Coefficients of determination (R 2), bias and limits of agreement (Bland Altman) were determined. Segmentation performance (R 2 between methods) was excellent for both readers for SAT (> 0.99) and very high for VAT (around 0.90). The novel method was almost twice as fast as the reference standard – 25 and 19 s/slice (R1 and R2) vs. 40 and 34 s/slice. The presented semiautomatic segmentation tool enables a fast and accurate quantification of whole abdominopelvic adipose tissue volume in obesity studies. Use, adjustments and extensions of the MRI volumetry tool are facilitated by the open-source design on a standard PC. |
| format | Article |
| id | doaj-art-0e903e10247944b5b51a21c188828fa8 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0e903e10247944b5b51a21c188828fa82025-08-20T03:42:22ZengNature PortfolioScientific Reports2045-23222025-03-0115111010.1038/s41598-025-87578-4Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesityA. Linder0T. Eggebrecht1N. Linder2R. Stange3A. Schaudinn4M. Blüher5T. Denecke6Harald Busse7Department of Diagnostic and Interventional Radiology, Leipzig University HospitalDepartment of Diagnostic and Interventional Radiology, Leipzig University HospitalDepartment of Diagnostic and Interventional Radiology, Leipzig University HospitalDepartment of Diagnostic and Interventional Radiology, Leipzig University HospitalDepartment of Diagnostic and Interventional Radiology, Leipzig University HospitalIntegrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical CenterDepartment of Diagnostic and Interventional Radiology, Leipzig University HospitalDepartment of Diagnostic and Interventional Radiology, Leipzig University HospitalAbstract Abdominal adipose tissue (AT) amounts are increasingly considered as potential biomarkers for a variety of diseases and clinical questions, for instance, in diabetology, oncology or cardiovascular medicine. Despite the emergence of automated deep-learning methods for tissue quantification, interactive (supervised) segmentation tools will typically be used for model training. In comparison with CT-based approaches, MRI segmentation tools are more complex and less common. This work aims to validate a novel MRI-based tissue volumetry against a reference method in patients with (pre-) obesity. The new tool (segfatMR) was developed under a Matlab-based, open-source software framework and combines fast automatic pre-segmentation followed by manual (expert) corrections where needed. Analyses were performed retrospectively on a subset of clinical research MRI datasets (1.5 T Achieva XR, Philips Healthcare) and involved the segmentation of datasets from 20 patients (10 women/men) aged 25.1–63.1 (mean 48.5) years with BMIs between 28.3 and 58.8 (mean 36.8) kg/m2. Two independent expert readers analyzed the abdominopelvic data (30–40 slices, mean 35.8) with segfatMR and a widely used commercial tool (sliceOmatic). Coefficients of determination (R 2), bias and limits of agreement (Bland Altman) were determined. Segmentation performance (R 2 between methods) was excellent for both readers for SAT (> 0.99) and very high for VAT (around 0.90). The novel method was almost twice as fast as the reference standard – 25 and 19 s/slice (R1 and R2) vs. 40 and 34 s/slice. The presented semiautomatic segmentation tool enables a fast and accurate quantification of whole abdominopelvic adipose tissue volume in obesity studies. Use, adjustments and extensions of the MRI volumetry tool are facilitated by the open-source design on a standard PC.https://doi.org/10.1038/s41598-025-87578-4ObesityAdipose tissueVisceral fatSubcutaneous fatQuantificationSoftware tool |
| spellingShingle | A. Linder T. Eggebrecht N. Linder R. Stange A. Schaudinn M. Blüher T. Denecke Harald Busse Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity Scientific Reports Obesity Adipose tissue Visceral fat Subcutaneous fat Quantification Software tool |
| title | Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity |
| title_full | Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity |
| title_fullStr | Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity |
| title_full_unstemmed | Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity |
| title_short | Stand-alone MRI tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity |
| title_sort | stand alone mri tool for semiautomatic volumetry of abdominal adipose compartments in patients with obesity |
| topic | Obesity Adipose tissue Visceral fat Subcutaneous fat Quantification Software tool |
| url | https://doi.org/10.1038/s41598-025-87578-4 |
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