ArticleAJNR. American journal of neuroradiology2016
Differentiation of Low- and High-Grade Gliomas Using High b-Value Diffusion Imaging with a Non-Gaussian Diffusion Model.
Article in AJNR. American journal of neuroradiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 44 citations in OpenAlex.
- Impact of Free Water Correction on the Mean Diffusivity of Glioblastoma is Regional and b-value Dependent: A Retrospective Study on Open-source Datasets.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- Noninvasive grading of renal interstitial fibrosis and prediction of annual renal function loss in chronic kidney disease: the optimal solution of seven MR diffusion models.Renal failure · 2025Article
- Continuous-time random walk and fractional order calculus models histogram analysis of glioma biomarkers, includingQuantitative imaging in medicine and surgery · 2025Article
- Using non-Gaussian diffusion models to distinguish benign from malignant head and neck lesions.Frontiers in oncology · 2025Article
- 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.BMC medical imaging · 2024Article
- Multi-b-value DWI to evaluate the synergistic antiproliferation and anti-heterogeneity effects of bufalin plus sorafenib in an orthotopic HCC model.European radiology experimental · 2024Article
- Accelerating High b-Value Diffusion-Weighted MRI Using a Convolutional Recurrent Neural Network (CRNN-DWI).Bioengineering (Basel, Switzerland) · 2023Article
- Optimal selection of b-values for differential diagnosis of mediastinal lymph nodes using diffusion-weighted imaging.Heliyon · 2023Article
- Incorporating multiple magnetic resonance diffusion models to differentiate low- and high-grade adult gliomas: a machine learning approach.Quantitative imaging in medicine and surgery · 2022Article
- Correlation of dual energy computed tomography electron density measurements with cerebral glioma grade.The neuroradiology journal · 2022Article
- Machine Learning Based on Diffusion Kurtosis Imaging Histogram Parameters for Glioma Grading.Journal of clinical medicine · 2022Article
- Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma.European radiology · 2022Article
- Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings.Frontiers in oncology · 2022Article
- In vivo assessment of Lauren classification for gastric adenocarcinoma using diffusion MRI with a fractional order calculus model.European radiology · 2021Article
- Differentiation of salivary gland tumor using diffusion-weighted imaging with a fractional order calculus model.The British journal of radiology · 2020Article
- High-Spatial-Resolution Diffusion MRI in Parkinson Disease: Lateral Asymmetry of the Substantia Nigra.Radiology · 2019Article
- White matter structural differences in OSA patients experiencing residual daytime sleepiness with high CPAP use: a non-Gaussian diffusion MRI study.Sleep medicine · 2019Article
- Diffusion MRI of cancer: From low to high b-values.Journal of magnetic resonance imaging : JMRI · 2019Review
- Improved Differentiation of Low-Grade and High-Grade Gliomas and Detection of Tumor Proliferation Using APT Contrast Fitted from Z-Spectrum.Molecular imaging and biology · 2018Article
- Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study.Scientific reports · 2018Article
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Authors and funding
7 authors at 5 institutions in 4 countries.
Funding
Abstract
background and purposeImaging-based tumor grading is highly desirable but faces challenges in sensitivity, specificity, and diagnostic accuracy. A recently proposed diffusion imaging method by using a fractional order calculus model offers a set of new parameters to probe not only the diffusion process itself but also intravoxel tissue structures, providing new opportunities for noninvasive tumor grading. This study aimed to demonstrate the feasibility of using the fractional order calculus model to differentiate low- from high-grade gliomas in adult patients and illustrate its improved performance over a conventional diffusion imaging method using ADC (or D). MATERIALS AND
methodsFifty-four adult patients (18-70 years of age) with histology-proved gliomas were enrolled and divided into low-grade (n = 24) and high-grade (n = 30) groups. Multi-b-value diffusion MR imaging was performed with 17 b-values (0-4000 s/mm(2)) and was analyzed by using a fractional order calculus model. Mean values and SDs of 3 fractional order calculus parameters (D, β, and μ) were calculated from the normal contralateral thalamus (as a control) and the tumors, respectively. On the basis of these values, the low- and high-grade glioma groups were compared by using a Mann-Whitney U test. Receiver operating characteristic analysis was performed to assess the performance of individual parameters and the combination of multiple parameters for low- versus high-grade differentiation.
resultsEach of the 3 fractional order calculus parameters exhibited a statistically higher value (P ≤ .011) in the low-grade than in the high-grade gliomas, whereas there was no difference in the normal contralateral thalamus (P ≥ .706). The receiver operating characteristic analysis showed that β (area under the curve = 0.853) produced a higher area under the curve than D (0.781) or μ (0.703) and offered a sensitivity of 87.5%, specificity of 76.7%, and diagnostic accuracy of 82.1%.
conclusionsThe study demonstrated the feasibility of using a non-Gaussian fractional order calculus diffusion model to differentiate low- and high-grade gliomas. While all 3 fractional order calculus parameters showed statistically significant differences between the 2 groups, β exhibited a better performance than the other 2 parameters, including ADC (or D).
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