Radiomics-based texture and shape analysis to differentiate between lipoma and liposarcoma on magnetic resonance imaging
DOI:
https://doi.org/10.46475/asean-jr.v27i2.987Keywords:
Lipoma, Liposarcoma, Radiomics, Texture analysis, Shape analysis, Atypical lipomatous tumorAbstract
Objective: This retrospective study aimed to assess the utility of magnetic resonance texture and shape analysis (MRTA) in enhancing the diagnostic accuracy of lipoma and liposarcoma differentiation on preoperative magnetic resonance imaging (MRI).
Materials and Methods: A total of 89 cases with pathologically confirmed lipoma or liposarcoma that underwent MRI before surgery at King Chulalongkorn Memorial Hospital between January 2010 and December 2022, were retrospectively included in this IRB-approved study. Axial T1-weighted (T1WI) and axial T1-weighted fat-saturated post-contrast (T1WI FS Gd) images were processed and segmented using the 3D Slicer program. Feature extraction was performed using PyRadiomics. Models were trained and internally validated using 5-fold stratified cross-validation and diagnostic accuracy was compared between MRTA and a musculoskeletal radiologist.
Results: Among 89 lesions (51 lipomas, 38 liposarcomas), MRTA demonstrated a sensitivity and specificity of 74.6% and 94.7%, respectively, on T1WI, and 77.6% and 97.4%, respectively, on T1WI FS Gd. MRTA demonstrated comparable or incrementally improved diagnostic performance compared with radiologist interpretation.
Conclusion: MRTA can effectively differentiate lipoma from liposarcoma, with higher sensitivity and specificity than visual radiological assessment. Segmentation on both T1WI and T1WI FS Gd sequences showed that contrast-enhanced fat-suppressed imaging provides superior diagnostic performance by more effectively highlighting enhancing septa and non-lipomatous components
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