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Using non-Gaussian diffusion models to distinguish benign from malignant head and neck lesions
Li Hua1, Qiuyang Guo2, Yifan Tang2
1Department of Laboratory Medicine, Anhui Medical University Anqing Medical Center, Anqing Municipal Hospital, Anqing, China.
Frontiers in Oncology
|June 13, 2025
Summary
Fractional-order calculus (FROC) and continuous-time random-walk (CTRW) models offer advanced diffusion parameters for distinguishing benign from malignant head and neck lesions. The alpha parameter from CTRW (αCTRW) demonstrated superior diagnostic performance in this quantitative assessment.
Area of Science:
- Medical Imaging
- Radiology
- Oncology
Background:
- Distinguishing benign from malignant head and neck lesions is crucial for effective treatment planning.
- Conventional diffusion-weighted imaging (DWI) provides valuable information but can be limited in characterizing tumor heterogeneity.
- Advanced diffusion models, such as fractional-order calculus (FROC) and continuous-time random-walk (CTRW), offer potential for improved diagnostic accuracy.
Purpose of the Study:
- To evaluate the application value of FROC and CTRW-derived parameters in differentiating benign and malignant head and neck lesions.
- To compare the diagnostic performance of these advanced diffusion parameters against conventional DWI.
- To explore the correlation between diffusion parameters and Ki-67 expression in malignant lesions.
Main Methods:
- Retrospective analysis of 70 pathologically confirmed head and neck lesions (23 benign, 47 malignant).
- Acquisition of DWI data with 12 b-values, followed by extraction of parameters from conventional DWI, FROC, and CTRW models.
- Statistical comparison of diffusion parameters between lesion groups and evaluation of diagnostic performance using ROC curves and AUC analysis.
Main Results:
- Significant differences were observed between groups for ADC, DFROC, μFROC, DCTRW, and αCTRW.
- The αCTRW parameter exhibited the highest diagnostic performance (AUC) in differentiating lesion types.
- Significant correlations were found between Ki-67 expression and FROC/CTRW diffusion parameters (DFROC, DCTRW, αCTRW, βCTRW).
Conclusions:
- FROC and CTRW diffusion models provide effective parameters for distinguishing benign and malignant head and neck lesions, reflecting tumor heterogeneity.
- αCTRW demonstrates superior diagnostic performance, positioning it as a promising non-invasive biomarker for quantitative assessment and differential diagnosis.
- These advanced diffusion models can enhance diagnostic accuracy for head and neck tumors.
