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.
370 related articles for article (PubMed ID: 35155178)
21. Quantitative DWI implemented after DCE-MRI yields increased specificity for BI-RADS 3 and 4 breast lesions. Dijkstra H; Dorrius MD; Wielema M; Pijnappel RM; Oudkerk M; Sijens PE J Magn Reson Imaging; 2016 Dec; 44(6):1642-1649. PubMed ID: 27273694 [TBL] [Abstract][Full Text] [Related]
22. Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions. Sun SY; Ding Y; Li Z; Nie L; Liao C; Liu Y; Zhang J; Zhang D Front Oncol; 2021; 11():699127. PubMed ID: 34722246 [TBL] [Abstract][Full Text] [Related]
23. Radiomics Based on Multiparametric Magnetic Resonance Imaging to Predict Extraprostatic Extension of Prostate Cancer. Xu L; Zhang G; Zhao L; Mao L; Li X; Yan W; Xiao Y; Lei J; Sun H; Jin Z Front Oncol; 2020; 10():940. PubMed ID: 32612953 [No Abstract] [Full Text] [Related]
24. Radiomic Evaluations of the Diagnostic Performance of DM, DBT, DCE MRI, DWI, and Their Combination for the Diagnosisof Breast Cancer. Niu S; Wang X; Zhao N; Liu G; Kan Y; Dong Y; Cui EN; Luo Y; Yu T; Jiang X Front Oncol; 2021; 11():725922. PubMed ID: 34568055 [TBL] [Abstract][Full Text] [Related]
25. Diagnostic Usefulness of Combination of Diffusion-weighted Imaging and T2WI, Including Apparent Diffusion Coefficient in Breast Lesions: Assessment of Histologic Grade. Kim KW; Kuzmiak CM; Kim YJ; Seo JY; Jung HK; Lee MS Acad Radiol; 2018 May; 25(5):643-652. PubMed ID: 29339079 [TBL] [Abstract][Full Text] [Related]
26. Evaluating Tumor-Infiltrating Lymphocytes in Breast Cancer Using Preoperative MRI-Based Radiomics. Bian T; Wu Z; Lin Q; Mao Y; Wang H; Chen J; Chen Q; Fu G; Cui C; Su X J Magn Reson Imaging; 2022 Mar; 55(3):772-784. PubMed ID: 34453461 [TBL] [Abstract][Full Text] [Related]
27. Nomograms for prediction of breast cancer in breast imaging reporting and data system (BI-RADS) ultrasound category 4 or 5 lesions: A single-center retrospective study based on radiomics features. Hong ZL; Chen S; Peng XR; Li JW; Yang JC; Wu SS Front Oncol; 2022; 12():894476. PubMed ID: 36212503 [TBL] [Abstract][Full Text] [Related]
28. Radiomics model to classify mammary masses using breast DCE-MRI compared to the BI-RADS classification performance. Debbi K; Habert P; Grob A; Loundou A; Siles P; Bartoli A; Jacquier A Insights Imaging; 2023 Apr; 14(1):64. PubMed ID: 37052738 [TBL] [Abstract][Full Text] [Related]
29. Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment. Hao W; Gong J; Wang S; Zhu H; Zhao B; Peng W Front Oncol; 2020; 10():531476. PubMed ID: 33194589 [TBL] [Abstract][Full Text] [Related]
30. Evaluation of the prostate imaging reporting and data system for the detection of prostate cancer by the results of targeted biopsy of the prostate. Baur AD; Maxeiner A; Franiel T; Kilic E; Huppertz A; Schwenke C; Hamm B; Durmus T Invest Radiol; 2014 Jun; 49(6):411-20. PubMed ID: 24598440 [TBL] [Abstract][Full Text] [Related]
31. Prediction of Lymphovascular Space Invision in Endometrial Cancer based on Multi-parameter MRI Radiomics Model. Wang JJ; Zhang XH; Guo XH; Ying Y; Wang X; Luan ZH; Lv WQ; Wang PF Curr Med Imaging; 2024 Mar; ():. PubMed ID: 38529651 [TBL] [Abstract][Full Text] [Related]
32. Preoperative prediction of pelvic lymph nodes metastasis in early-stage cervical cancer using radiomics nomogram developed based on T2-weighted MRI and diffusion-weighted imaging. Wang T; Gao T; Yang J; Yan X; Wang Y; Zhou X; Tian J; Huang L; Zhang M Eur J Radiol; 2019 May; 114():128-135. PubMed ID: 31005162 [TBL] [Abstract][Full Text] [Related]
33. Multiparametric MRI model with synthetic MRI, DWI multi-quantitative parameters, and differential sub-sampling with cartesian ordering enables BI-RADS 4 lesions diagnosis with high accuracy. He H; Song M; Tian Z; Gao N; Ma J; Wang Z Front Oncol; 2023; 13():1180131. PubMed ID: 38250550 [TBL] [Abstract][Full Text] [Related]
34. Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions. Perre SV; Duron L; Milon A; Bekhouche A; Balvay D; Cornelis FH; Fournier L; Thomassin-Naggara I Eur Radiol; 2021 Jul; 31(7):4848-4859. PubMed ID: 33404696 [TBL] [Abstract][Full Text] [Related]
35. Value of radiomics model based on multi-parametric magnetic resonance imaging in predicting epidermal growth factor receptor mutation status in patients with lung adenocarcinoma. Wang Y; Wan Q; Xia X; Hu J; Liao Y; Wang P; Peng Y; Liu H; Li X J Thorac Dis; 2021 Jun; 13(6):3497-3508. PubMed ID: 34277045 [TBL] [Abstract][Full Text] [Related]
36. Predicting Tumor Perineural Invasion Status in High-Grade Prostate Cancer Based on a Clinical-Radiomics Model Incorporating T2-Weighted and Diffusion-Weighted Magnetic Resonance Images. Zhang W; Zhang W; Li X; Cao X; Yang G; Zhang H Cancers (Basel); 2022 Dec; 15(1):. PubMed ID: 36612083 [TBL] [Abstract][Full Text] [Related]
37. Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS. Luo WQ; Huang QX; Huang XW; Hu HT; Zeng FQ; Wang W Sci Rep; 2019 Aug; 9(1):11921. PubMed ID: 31417138 [TBL] [Abstract][Full Text] [Related]
38. Discrimination between HER2-overexpressing, -low-expressing, and -zero-expressing statuses in breast cancer using multiparametric MRI-based radiomics. Zheng S; Yang Z; Du G; Zhang Y; Jiang C; Xu T; Li B; Wang D; Qiu Y; Lin D; Zhang X; Shen J Eur Radiol; 2024 Sep; 34(9):6132-6144. PubMed ID: 38363315 [TBL] [Abstract][Full Text] [Related]
39. Combining Multiparametric MRI Radiomics Signature With the Vesical Imaging-Reporting and Data System (VI-RADS) Score to Preoperatively Differentiate Muscle Invasion of Bladder Cancer. Zheng Z; Xu F; Gu Z; Yan Y; Xu T; Liu S; Yao X Front Oncol; 2021; 11():619893. PubMed ID: 34055600 [TBL] [Abstract][Full Text] [Related]
40. Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study. Jin P; Shen J; Yang L; Zhang J; Shen A; Bao J; Wang X BMC Med Imaging; 2023 Mar; 23(1):47. PubMed ID: 36991347 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]