Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone

2021 ◽  
Author(s):  
Guiqin Liu ◽  
Yang Lu ◽  
Yongming Dai ◽  
Ke Xue ◽  
Yangyang Yi ◽  
...  
Keyword(s):  
Transition Zone ◽  
Fractional Order ◽  
Diffusion Weighted Imaging ◽  
Fractional Order Calculus ◽  
Diffusion Weighted

scholarly journals Differentiation of salivary gland tumor using diffusion-weighted imaging with a fractional order calculus model

2020 ◽  
Vol 93 (1113) ◽  
pp. 20200052
Author(s):  
Wei Chen ◽  
Liu-Ning Zhu ◽  
Yong-Ming Dai ◽  
Jia-Suo Jiang ◽  
Shou-Shan Bu ◽  
...  
Keyword(s):  
Salivary Gland ◽  
Diffusion Model ◽  
Fractional Order ◽  
Diffusion Weighted Imaging ◽  
Diagnostic Performance ◽  
Salivary Gland Tumors ◽  
Characteristic Analysis ◽  
Fractional Order Calculus ◽  
Diffusion Weighted ◽  
Significant Difference

Objective: To evaluate the feasibility of using imaging parameters (D, β and μ) obtained from fractional order calculus (FROC) diffusion model to differentiate salivary gland tumors. Methods: 15 b-value (0–2000 s/mm2) diffusion-weighted imaging (DWI) was scanned in 62 patients with salivary gland tumors (47 benign and 15 malignant). Diffusion coefficient D, fractional order parameter β (which correlates with tissue heterogeneity) and a microstructural quantity μ of the solid portion within the tumor were calculated, and compared between benign and malignant groups, or among pleomorphic adenoma (PA), Warthin’s tumor (WT), and malignant tumor (MT) groups. Performance of FROC parameters for differentiation was assessed using receiver operating characteristic analysis. Results: None of the FROC parameters exhibited significant differences between benign and malignant group (D, p = 0.150; β, p = 0.967; μ, p = 0.693). WT showed significantly lower D (p < 0.001) and β (p < 0.001), while higher μ (p = 0.001) than PA. Combination of D, β and μ showed optimal diagnostic performance (area under the curve, AUC, 0.998). MT showed significantly lower D (p = 0.001) and β (p = 0.025) than PA, while no significant difference was found on μ (p = 0.064). Combination of D and β showed optimal diagnostic performance (AUC, 0.933). Significant difference was found on β (p = 0.027) between MT and WT, while not on D (p = 0.806) and μ (p = 0.789). Setting a βof 0.615 as the cut-off value, optimal diagnostic performance could be obtained (AUC = 0.806). Conclusion: A non-Gaussian FROC diffusion model can serve as a noninvasive and quantitative imaging technique for differentiating salivary gland tumors. Advances in knowledge: (1) PA showed higher D and β and lower μ than WT. (2) PA had higher D and β than MT. (3) WT demonstrated lower β than MT. (4) β, as a new FROC parameter, could offer an added value to the differentiation.

scholarly journals Differentiation of Low- and High-Grade Pediatric Brain Tumors with Highb-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model

Radiology ◽  
2015 ◽  
Vol 277 (2) ◽  
pp. 489-496 ◽  
Author(s):  
Yi Sui ◽  
He Wang ◽  
Guanzhong Liu ◽  
Frederick W. Damen ◽  
Christian Wanamaker ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Mr Imaging ◽  
Fractional Order ◽  
Pediatric Brain Tumors ◽  
High Grade ◽  
Fractional Order Calculus ◽  
Diffusion Weighted ◽  
Pediatric Brain

scholarly journals On a fractional order calculus model in diffusion weighted breast imaging to differentiate between malignant and benign breast lesions detected on X-ray screening mammography

PLoS ONE ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. e0176077 ◽  
Author(s):  
Sebastian Bickelhaupt ◽  
Franziska Steudle ◽  
Daniel Paech ◽  
Anna Mlynarska ◽  
Tristan Anselm Kuder ◽  
...  
Keyword(s):  
Fractional Order ◽  
Breast Imaging ◽  
Screening Mammography ◽  
Breast Lesions ◽  
Fractional Order Calculus ◽  
X Ray ◽  
Diffusion Weighted ◽  
Benign Breast Lesions

scholarly journals Diagnostic performance of diffusion-weighted imaging for prostate cancer: Peripheral zone versus transition zone

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0199636 ◽  
Author(s):  
Hakmin Lee ◽  
Sung Il Hwang ◽  
Hak Jong Lee ◽  
Seok-Soo Byun ◽  
Sang Eun Lee ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Transition Zone ◽  
Diffusion Weighted Imaging ◽  
Diagnostic Performance ◽  
Peripheral Zone ◽  
Diffusion Weighted ◽  
Zone Versus ◽  
Versus Transition
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