ArticleFrontiers in oncology2023
Preoperative prediction of VETC in hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging at high b values: a pilot study.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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14 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Effectiveness of Machine Learning in Detecting Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Precise zonal diagnosis: multi-b-value DWI model reveals differential predictors of clinically significant prostate cancer in peripheral and transition zones.Insights into imaging · 2026Article
- A web-based prognostic nomogram incorporating VETC-associated imaging markers for predicting postoperative recurrence in hepatocellular carcinoma.BMC cancer · 2026Article
- Non-Gaussian diffusion MRI models for preoperative assessment of microvascular invasion in hepatocellular carcinoma.Abdominal radiology (New York) · 2026Article
- The diagnostic accuracy of imaging methods in preoperative prediction of vessels encapsulating tumor clusters in hepatocellular carcinoma in East Asian populations: a systematic review and meta-analysis.Quantitative imaging in medicine and surgery · 2026Article
- Differentiation of early-stage endometrial carcinoma from benign endometrial lesions: a comparative study of six diffusion models.Quantitative imaging in medicine and surgery · 2025Article
- Using non-Gaussian diffusion models to distinguish benign from malignant head and neck lesions.Frontiers in oncology · 2025Article
- Histogram analysis of continuous-time random walk and restrictive spectrum imaging for identifying hepatocellular carcinoma and intrahepatic cholangiocarcinoma.Frontiers in oncology · 2025Article
- Predicting IDH and 1p/19q molecular status of gliomas with multi-b values DWI.Frontiers in oncology · 2025Article
- Predicting the Ki-67 proliferation index in cervical cancer: a preliminary comparative study of four non-Gaussian diffusion-weighted imaging models combined with histogram analysis.Quantitative imaging in medicine and surgery · 2024Article
- 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
- Whole-tumor histogram analysis of multiple non-Gaussian diffusion models at high b values for assessing cervical cancer.Abdominal radiology (New York) · 2024Article
- Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values.Frontiers in oncology · 2024Article
- Assessment of pathological grade and variants of bladder cancer with a continuous-time random-walk diffusion model.Frontiers in oncology · 2024Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Vessels encapsulating tumor clusters (VETC) have been considered an important cause of hepatocellular carcinoma (HCC) metastasis. Purpose: To compare the potential of various diffusion parameters derived from the monoexponential model and four non-Gaussian models (DKI, SEM, FROC, and CTRW) in preoperatively predicting the VETC of HCC. Methods: 86 HCC patients (40 VETC-positive and 46 VETC-negative) were prospectively enrolled. Diffusion-weighted images were acquired using six b-values (range from 0 to 3000 s/mm2). Various diffusion parameters derived from diffusion kurtosis (DK), stretched-exponential (SE), fractional-order calculus (FROC), and continuous-time random walk (CTRW) models, together with the conventional apparent diffusion coefficient (ADC) derived from the monoexponential model were calculated. All parameters were compared between VETC-positive and VETC-negative groups using an independent sample t-test or Mann-Whitney U test, and then the parameters with significant differences between the two groups were combined to establish a predictive model by binary logistic regression. Receiver operating characteristic (ROC) analyses were used to assess diagnostic performance. Results: Among all studied diffusion parameters, only DKI_K and CTRW_α significantly differed between groups (P=0.002 and 0.004, respectively). For predicting the presence of VETC in HCC patients, the combination of DKI_K and CTRW_α had the larger area under the ROC curve (AUC) than the two parameters individually (AUC=0.747 vs. 0.678 and 0.672, respectively). Conclusion: DKI_K and CTRW_α outperformed traditional ADC for predicting the VETC of HCC.
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