ArticleBMC medical imaging2024
Value of fractional-order calculus (FROC) model diffusion-weighted imaging combined with simultaneous multi-slice (SMS) acceleration technology for evaluating benign and malignant breast lesions.
Article in BMC medical imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Distinguishing Ki67 stratification expression in ER-positive/HER2-negative breast cancers: comparison of advanced MRI diffusion models.BMC medical imaging · 2026Article
- Non-Gaussian diffusion MRI using CTRW and FROC models for early treatment response assessment in nasopharyngeal carcinoma.BMC medical imaging · 2026Article
- Breast Diffusion-weighted MR Imaging: Current Applications, Insights from Screening, and Future Directions.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- Comparison of four MRI diffusion models to differentiate benign from metastatic retropharyngeal lymph nodes.European radiology experimental · 2025Article
- Differentiating rectal cancer grades using virtual magnetic resonance elastography and fractional order calculus diffusion model.BMC cancer · 2025Article
- Histogram analysis of diffusion-weighted imaging with a fractional order calculus model in breast cancer: diagnostic performance and associations with prognostic factors.Frontiers in radiology · 2025Article
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Authors and funding
11 authors.
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Abstract
backgroundThis study explores the diagnostic value of combining fractional-order calculus (FROC) diffusion-weighted model with simultaneous multi-slice (SMS) acceleration technology in distinguishing benign and malignant breast lesions.
methods178 lesions (73 benign, 105 malignant) underwent magnetic resonance imaging with diffusion-weighted imaging using multiple b-values (14 b-values, highest 3000 s/mm
resultsMalignant lesions exhibited lower D, and ADC values than benign lesions (P < 0.05), with higher values (P < 0.05). In SSEPI-DWI and SMS-SSEPI-DWI sequences, the AUC and diagnostic accuracy of D value are maximal, with D value demonstrating the highest diagnostic sensitivity, while value exhibits the highest specificity. The D and combined model had the highest AUC and accuracy. D and ADC values showed high correlation between sequences, and moderate. Bland-Altman plot demonstrated unbiased parameter values.
conclusionSMS-SSEPI-DWI FROC model provides good image quality and lesion characteristic values within an acceptable time. It shows consistent diagnostic performance compared to SSEPI-DWI, particularly in D and values, and significantly reduces scanning time.
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