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Differentiation of soft-tissue lymphoma from undifferentiated sarcoma: apparent diffusion coefficient histogram
Ji Hyun Hong1,2, Won-Hee Jee1, Sunyoung Whang1
1Department of Radiology, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, Republic of Korea.
Acta Radiologica (Stockholm, Sweden : 1987)
|August 28, 2020
Summary
Apparent diffusion coefficient (ADC) histogram analysis accurately differentiates soft-tissue lymphoma from sarcoma. This imaging technique provides reliable preoperative diagnosis, guiding appropriate treatment decisions for these distinct conditions.
Area of Science:
- Radiology and Medical Imaging
- Oncology
- Diffusion-Weighted MRI
Background:
- Preoperative diagnosis is crucial for distinguishing soft-tissue lymphoma from sarcoma due to differing treatment protocols.
- Accurate differentiation impacts patient management and therapeutic strategies.
Purpose of the Study:
- To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) histogram analysis in differentiating soft-tissue lymphoma from undifferentiated sarcoma.
- To compare the reliability of single-slice versus whole-tumor ADC histogram metrics.
Main Methods:
- Retrospective analysis of 3-T MRI diffusion-weighted imaging in patients with soft-tissue lymphoma or undifferentiated sarcoma.
- Single-slice and whole-tumor ADC histogram analysis using quantitative metrics (mean, SD, percentiles, kurtosis).
- Receiver operating characteristic (ROC) curve analysis to determine diagnostic accuracy (Area Under the Curve - AUC).
Main Results:
- ADC histogram analysis revealed significantly lower mean, SD, and 5th/95th percentiles in lymphoma compared to sarcoma.
- Whole-tumor kurtosis was significantly higher in lymphoma.
- High AUC values (0.949-1.000) were observed for most metrics, indicating excellent diagnostic performance.
Conclusions:
- Single-slice and whole-tumor ADC histogram analysis demonstrates high reliability and accuracy in differentiating soft-tissue lymphoma from undifferentiated sarcoma.
- This non-invasive imaging technique can aid in preoperative diagnosis and treatment planning.
