These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
313 related articles for article (PubMed ID: 35754067)
1. Application of a Convolutional Neural Network for Multitask Learning to Simultaneously Predict Microvascular Invasion and Vessels that Encapsulate Tumor Clusters in Hepatocellular Carcinoma. Chu T; Zhao C; Zhang J; Duan K; Li M; Zhang T; Lv S; Liu H; Wei F Ann Surg Oncol; 2022 Oct; 29(11):6774-6783. PubMed ID: 35754067 [TBL] [Abstract][Full Text] [Related]
2. Prediction of vessels encapsulating tumor clusters pattern and prognosis of hepatocellular carcinoma based on preoperative gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid magnetic resonance imaging. Wang M; Cao L; Wang Y; Huang H; Cao S; Tian X; Lei J J Gastrointest Surg; 2024 Apr; 28(4):442-450. PubMed ID: 38583894 [TBL] [Abstract][Full Text] [Related]
3. Preoperative Gadoxetic Acid-Enhanced MRI Features for Evaluation of Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma: Creating Nomograms for Risk Assessment. Qu Q; Liu Z; Lu M; Xu L; Zhang J; Liu M; Jiang J; Gu C; Ma Q; Huang A; Zhang X; Zhang T J Magn Reson Imaging; 2024 Sep; 60(3):1094-1110. PubMed ID: 38116997 [TBL] [Abstract][Full Text] [Related]
4. Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma. Yu Y; Fan Y; Wang X; Zhu M; Hu M; Shi C; Hu C Eur Radiol; 2022 Feb; 32(2):959-970. PubMed ID: 34480625 [TBL] [Abstract][Full Text] [Related]
5. A new horizon in risk stratification of hepatocellular carcinoma by integrating vessels that encapsulate tumor clusters and microvascular invasion. Lu L; Wei W; Huang C; Li S; Zhong C; Wang J; Yu W; Zhang Y; Chen M; Ling Y; Guo R Hepatol Int; 2021 Jun; 15(3):651-662. PubMed ID: 33835379 [TBL] [Abstract][Full Text] [Related]
6. Imaging features based on Gd-EOB-DTPA-enhanced MRI for predicting vessels encapsulating tumor clusters (VETC) in patients with hepatocellular carcinoma. Fan Y; Yu Y; Hu M; Wang X; Du M; Guo L; Hu C Br J Radiol; 2021 Mar; 94(1119):20200950. PubMed ID: 33417489 [TBL] [Abstract][Full Text] [Related]
7. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma. Chen YD; Zhang L; Zhou ZP; Lin B; Jiang ZJ; Tang C; Dang YW; Xia YW; Song B; Long LL World J Gastroenterol; 2022 Aug; 28(31):4399-4416. PubMed ID: 36159011 [TBL] [Abstract][Full Text] [Related]
8. Preoperative MRI features for characterization of vessels encapsulating tumor clusters and microvascular invasion in hepatocellular carcinoma. Yang J; Dong X; Wang G; Chen J; Zhang B; Pan W; Zhang H; Jin S; Ji W Abdom Radiol (NY); 2023 Feb; 48(2):554-566. PubMed ID: 36385192 [TBL] [Abstract][Full Text] [Related]
9. Preoperative prediction of microvascular invasion in hepatocellular cancer: a radiomics model using Gd-EOB-DTPA-enhanced MRI. Feng ST; Jia Y; Liao B; Huang B; Zhou Q; Li X; Wei K; Chen L; Li B; Wang W; Chen S; He X; Wang H; Peng S; Chen ZB; Tang M; Chen Z; Hou Y; Peng Z; Kuang M Eur Radiol; 2019 Sep; 29(9):4648-4659. PubMed ID: 30689032 [TBL] [Abstract][Full Text] [Related]
10. The value of the signal intensity of peritumoral tissue on Gd-EOB-DTPA dynamic enhanced MRI in assessment of microvascular invasion and pathological grade of hepatocellular carcinoma. Wang LL; Li JF; Lei JQ; Guo SL; Li JK; Xu YS; Dou Y Medicine (Baltimore); 2021 May; 100(20):e25804. PubMed ID: 34011043 [TBL] [Abstract][Full Text] [Related]
11. Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma. Zhang C; Ma LD; Zhang XL; Lei C; Yuan SS; Li JP; Geng ZJ; Li XM; Quan XY; Zheng C; Geng YY; Zhang J; Zheng QL; Hou J; Xie SY; Lu LH; Xie CM J Magn Reson Imaging; 2024 Jul; 60(1):231-242. PubMed ID: 37888871 [TBL] [Abstract][Full Text] [Related]
12. Establishment of nomogram prediction model of contrast-enhanced ultrasound and Gd-EOB-DTPA-enhanced MRI for vessels encapsulating tumor clusters pattern of hepatocellular carcinoma. Wang F; Numata K; Funaoka A; Liu X; Kumamoto T; Takeda K; Chuma M; Nozaki A; Ruan L; Maeda S Biosci Trends; 2024 Jul; 18(3):277-288. PubMed ID: 38866488 [TBL] [Abstract][Full Text] [Related]
13. Using deep learning to predict microvascular invasion in hepatocellular carcinoma based on dynamic contrast-enhanced MRI combined with clinical parameters. Song D; Wang Y; Wang W; Wang Y; Cai J; Zhu K; Lv M; Gao Q; Zhou J; Fan J; Rao S; Wang M; Wang X J Cancer Res Clin Oncol; 2021 Dec; 147(12):3757-3767. PubMed ID: 33839938 [TBL] [Abstract][Full Text] [Related]
14. Deep Learning Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma. Dong X; Yang J; Zhang B; Li Y; Wang G; Chen J; Wei Y; Zhang H; Chen Q; Jin S; Wang L; He H; Gan M; Ji W J Magn Reson Imaging; 2024 Jan; 59(1):108-119. PubMed ID: 37078470 [TBL] [Abstract][Full Text] [Related]
15. A deep learning model based on MRI for prediction of vessels encapsulating tumour clusters and prognosis in hepatocellular carcinoma. Yang J; Dong X; Wang F; Jin S; Zhang B; Zhang H; Pan W; Gan M; Duan S; Zhang L; Hu H; Ji W Abdom Radiol (NY); 2024 Apr; 49(4):1074-1083. PubMed ID: 38175256 [TBL] [Abstract][Full Text] [Related]
16. Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy. Yan M; Zhang X; Zhang B; Geng Z; Xie C; Yang W; Zhang S; Qi Z; Lin T; Ke Q; Li X; Wang S; Quan X Eur Radiol; 2023 Jul; 33(7):4949-4961. PubMed ID: 36786905 [TBL] [Abstract][Full Text] [Related]
17. Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma. Meng XP; Tang TY; Zhou Y; Xia C; Xia T; Shi Y; Long X; Liang Y; Xiao W; Wang YC; Fang X; Ju S JHEP Rep; 2023 Sep; 5(9):100806. PubMed ID: 37575884 [TBL] [Abstract][Full Text] [Related]
18. Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images. Wang F; Zhan G; Chen QQ; Xu HY; Cao D; Zhang YY; Li YH; Zhang CJ; Jin Y; Ji WB; Ma JB; Yang YJ; Zhou W; Peng ZY; Liang X; Deng LP; Lin LF; Chen YW; Hu HJ Liver Int; 2024 Jun; 44(6):1351-1362. PubMed ID: 38436551 [TBL] [Abstract][Full Text] [Related]
19. Deep Learning With 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Zhang Y; Lv X; Qiu J; Zhang B; Zhang L; Fang J; Li M; Chen L; Wang F; Liu S; Zhang S J Magn Reson Imaging; 2021 Jul; 54(1):134-143. PubMed ID: 33559293 [TBL] [Abstract][Full Text] [Related]
20. A Clinical Scoring System for Predicting Microvascular Invasion in Patients with Hepatocellular Carcinoma Within the Milan Criteria. Ryu T; Takami Y; Wada Y; Tateishi M; Hara T; Yoshitomi M; Momosaki S; Yasumori K; Saitsu H; Okuda K J Gastrointest Surg; 2019 Apr; 23(4):779-787. PubMed ID: 30788712 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]