138 related articles for article (PubMed ID: 33967085)
1. A logistic regression model for prediction of glioma grading based on radiomics.
Sun X; Liao W; Cao D; Zhao Y; Zhou G; Wang D; Mao Y
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2021 Apr; 46(4):385-392. PubMed ID: 33967085
[TBL] [Abstract][Full Text] [Related]
2. Glioma grading prediction using multiparametric magnetic resonance imaging-based radiomics combined with proton magnetic resonance spectroscopy and diffusion tensor imaging.
Lin K; Cidan W; Qi Y; Wang X
Med Phys; 2022 Jul; 49(7):4419-4429. PubMed ID: 35366379
[TBL] [Abstract][Full Text] [Related]
3. Radiomics Nomogram Building From Multiparametric MRI to Predict Grade in Patients With Glioma: A Cohort Study.
Wang Q; Li Q; Mi R; Ye H; Zhang H; Chen B; Li Y; Huang G; Xia J
J Magn Reson Imaging; 2019 Mar; 49(3):825-833. PubMed ID: 30260592
[TBL] [Abstract][Full Text] [Related]
4. Application of Enhanced T1WI of MRI Radiomics in Glioma Grading.
Zhou H; Xu R; Mei H; Zhang L; Yu Q; Liu R; Fan B
Int J Clin Pract; 2022; 2022():3252574. PubMed ID: 35685548
[TBL] [Abstract][Full Text] [Related]
5. Diffusion- and perfusion-weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma.
Kim M; Jung SY; Park JE; Jo Y; Park SY; Nam SJ; Kim JH; Kim HS
Eur Radiol; 2020 Apr; 30(4):2142-2151. PubMed ID: 31828414
[TBL] [Abstract][Full Text] [Related]
6. Multiparametric MR radiomics in brain glioma: models comparation to predict biomarker status.
He J; Ren J; Niu G; Liu A; Wu Q; Xie S; Ma X; Li B; Wang P; Shen J; Wu J; Gao Y
BMC Med Imaging; 2022 Aug; 22(1):137. PubMed ID: 35931979
[TBL] [Abstract][Full Text] [Related]
7. Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas.
Jiang C; Kong Z; Liu S; Feng S; Zhang Y; Zhu R; Chen W; Wang Y; Lyu Y; You H; Zhao D; Wang R; Wang Y; Ma W; Feng F
Eur J Radiol; 2019 Dec; 121():108714. PubMed ID: 31704598
[TBL] [Abstract][Full Text] [Related]
8. Prediction of histopathologic grades of myxofibrosarcoma with radiomics based on magnetic resonance imaging.
Yao Y; Zhao Y; Lu L; Zhao Y; Lin X; Xia J; Zheng X; Shen Y; Cai Z; Li Y; Yang Z; Lin D
J Cancer Res Clin Oncol; 2023 Sep; 149(12):10169-10179. PubMed ID: 37264266
[TBL] [Abstract][Full Text] [Related]
9. Predicting histological grade in pediatric glioma using multiparametric radiomics and conventional MRI features.
Zhou T; Qiao B; Peng B; Liu Y; Gong Z; Kang M; He Y; Pang C; Dai Y; Sheng M
Sci Rep; 2024 Jun; 14(1):13683. PubMed ID: 38871755
[TBL] [Abstract][Full Text] [Related]
10. The efficacy of using a multiparametric magnetic resonance imaging-based radiomics model to distinguish glioma recurrence from pseudoprogression.
Fu FX; Cai QL; Li G; Wu XJ; Hong L; Chen WS
Magn Reson Imaging; 2024 Sep; 111():168-178. PubMed ID: 38729227
[TBL] [Abstract][Full Text] [Related]
11. Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI.
Han Y; Wang T; Wu P; Zhang H; Chen H; Yang C
Magn Reson Imaging; 2021 Apr; 77():36-43. PubMed ID: 33220449
[TBL] [Abstract][Full Text] [Related]
12. [Quantitative analysis of hepatocellular carcinomas pathological grading in non-contrast magnetic resonance images].
Gao F; Yan B; Zeng L; Wu M; Tan H; Hai J; Ning P; Shi D
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2019 Aug; 36(4):581-589. PubMed ID: 31441258
[TBL] [Abstract][Full Text] [Related]
13. Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure.
Zhu WS; Shi SY; Yang ZH; Song C; Shen J
World J Gastroenterol; 2020 Mar; 26(11):1208-1220. PubMed ID: 32231424
[TBL] [Abstract][Full Text] [Related]
14. Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas.
Park CJ; Han K; Kim H; Ahn SS; Choi YS; Park YW; Chang JH; Kim SH; Jain R; Lee SK
Eur Radiol; 2020 Dec; 30(12):6464-6474. PubMed ID: 32740813
[TBL] [Abstract][Full Text] [Related]
15. Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.
Nakamoto T; Takahashi W; Haga A; Takahashi S; Kiryu S; Nawa K; Ohta T; Ozaki S; Nozawa Y; Tanaka S; Mukasa A; Nakagawa K
Sci Rep; 2019 Dec; 9(1):19411. PubMed ID: 31857632
[TBL] [Abstract][Full Text] [Related]
16. Predicting the microvascular invasion and tumor grading of intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance imaging radiomics and morphological features.
Chen S; Zhu Y; Wan L; Zou S; Zhang H
Quant Imaging Med Surg; 2023 Dec; 13(12):8079-8093. PubMed ID: 38106327
[TBL] [Abstract][Full Text] [Related]
17. Do the combination of multiparametric MRI-based radiomics and selected blood inflammatory markers predict the grade and proliferation in glioma patients?
Guo J; Ren J; Shen J; Cheng R; He Y
Diagn Interv Radiol; 2021 May; 27(3):440-449. PubMed ID: 33769289
[TBL] [Abstract][Full Text] [Related]
18. Integrating IASLC grading and radiomics for predicting postoperative outcomes in stage IA invasive lung adenocarcinoma.
Chen Y; Wu J; You J; Gao M; Lu S; Sun C; Shu Y; Wang X
Med Phys; 2024 May; ():. PubMed ID: 38781536
[TBL] [Abstract][Full Text] [Related]
19. Distinguishing brain inflammation from grade II glioma in population without contrast enhancement: a radiomics analysis based on conventional MRI.
Han Y; Yang Y; Shi ZS; Zhang AD; Yan LF; Hu YC; Feng LL; Ma J; Wang W; Cui GB
Eur J Radiol; 2021 Jan; 134():109467. PubMed ID: 33307462
[TBL] [Abstract][Full Text] [Related]
20. Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: invasive prediction.
Sun Y; Li C; Jin L; Gao P; Zhao W; Ma W; Tan M; Wu W; Duan S; Shan Y; Li M
Eur Radiol; 2020 Jul; 30(7):3650-3659. PubMed ID: 32162003
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
