Validation of a free software for unsupervised assessment of abdominal fat in MRI |
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| Affiliation: | 1. Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy;2. Medical Physics Unit, Spedali Civili Hospital, Brescia, Italy;3. Radiology Unit, Spedali Civili Hospital, Brescia, Italy;1. Department of Recreation, Poznan University of Physical Education, Poland;2. Poznan Medical University, Dept. of Physiotherapy, Rheumatology and Rehabilitation, Jozef Strus Municipal Hospital, Poznan, Poland;3. Stanisław Staszic University of Applied Science in Pila, Poland;4. Department of Biochemistry, Poznan University of Physical Education, Poland;5. Department of Theory of Sports, Poznan University of Physical Education, Poland;6. Chair of Motor System Rehabilitation, Poznan University of Physical Education, Poland;1. Digestive Disease Center, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark;2. Copenhagen Wound Healing Center, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark;3. Nordic Bioscience A/S, Herlev, Denmark;1. Department of Respiratory Medicine, Ghent University Hospital, Belgium;2. Department of Medical Imaging, Ghent University Hospital, Belgium;3. Biostatistical Unit, Faculty of Medicine, Ghent University, Belgium;4. Thoracic Oncology, MOCA, Antwerp University Hospital, Belgium;1. University School of Physical Education, Anthropology and Biometry Department, Poznań, Poland;2. Poznań University of Medical Sciences, Department of Physiotherapy, Rheumatology and Rehabilitation, Józef Struś Municipal Hospital, Poznań, Poland |
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| Abstract: | PurposeTo demonstrate the accuracy of an unsupervised (fully automated) software for fat segmentation in magnetic resonance imaging. The proposed software is a freeware solution developed in ImageJ that enables the quantification of metabolically different adipose tissues in large cohort studies.MethodsThe lumbar part of the abdomen (19 cm in craniocaudal direction, centered in L3) of eleven healthy volunteers (age range: 21–46 years, BMI range: 21.7–31.6 kg/m2) was examined in a breath hold on expiration with a GE T1 Dixon sequence. Single-slice and volumetric data were considered for each subject. The results of the visceral and subcutaneous adipose tissue assessments obtained by the unsupervised software were compared to supervised segmentations of reference. The associated statistical analysis included Pearson correlations, Bland-Altman plots and volumetric differences (VD%).ResultsValues calculated by the unsupervised software significantly correlated with corresponding supervised segmentations of reference for both subcutaneous adipose tissue – SAT (R = 0.9996, p < 0.001) and visceral adipose tissue – VAT (R = 0.995, p < 0.001). Bland-Altman plots showed the absence of systematic errors and a limited spread of the differences. In the single-slice analysis, VD% were (1.6 ± 2.9)% for SAT and (4.9 ± 6.9)% for VAT. In the volumetric analysis, VD% were (1.3 ± 0.9)% for SAT and (2.9 ± 2.7)% for VAT.ConclusionsThe developed software is capable of segmenting the metabolically different adipose tissues with a high degree of accuracy. This free add-on software for ImageJ can easily have a widespread and enable large-scale population studies regarding the adipose tissue and its related diseases. |
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| Keywords: | Magnetic resonance imaging 2-point Dixon sequence Visceral adipose tissue Subcutaneous adipose tissue Segmentation Unsupervised software |
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