Comparison of continuous-time random walk and fractional order calculus models in characterizing breast lesions using histogram analysis
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View abstract on PubMed
Summary
This summary is machine-generated.The diffusion coefficient parameter showed superior diagnostic performance in distinguishing benign from malignant breast lesions compared to spatial and temporal heterogeneity parameters. Whole-tumor histogram analysis aids in breast lesion characterization.
Area Of Science
- Radiology
- Medical Imaging
- Oncology
Background
- Distinguishing benign from malignant breast lesions is crucial for effective patient management.
- Diffusion-weighted imaging (DWI) offers insights into tissue microstructure.
- Mathematical models and histogram analysis can enhance DWI's diagnostic capabilities.
Purpose Of The Study
- To compare the diagnostic performance of different mathematical models for DWI.
- To evaluate if spatial and temporal heterogeneity parameters offer better accuracy than diffusion coefficient in differentiating breast lesions.
- To utilize whole-tumor histogram analysis for this comparison.
Main Methods
- Retrospective analysis of 146 breast lesion cases (104 malignant, 42 benign).
- Breast MRI performed using a 3.0T scanner with simultaneous multi-slice (SMS) rs-EPI.
- Histogram metrics of apparent diffusion coefficient (ADC), continuous-time random walk (CTRW), and fractional-order calculus (FROC)-derived parameters were analyzed and compared using ROC curves.
Main Results
- The D<sub>FROC</sub>-median demonstrated the highest area under the curve (AUC) of 0.965 for distinguishing breast lesions.
- Temporal heterogeneity (α<sub>CTRW</sub>-median, AUC=0.850) showed significantly better performance than spatial heterogeneity (β<sub>CTRW</sub>-median, AUC=0.741).
- Combined CTRW parameters slightly outperformed FROC parameters (AUC=0.971 vs. 0.965), though not significantly.
Conclusions
- The diffusion coefficient parameter exhibits superior diagnostic performance over temporal and spatial heterogeneity parameters for breast lesion differentiation.
- Whole-tumor histogram analysis of DWI parameters is a valuable tool for characterizing breast lesions.
- Further research may explore combined parameter models for improved diagnostic accuracy.
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