345 related articles for article (PubMed ID: 33691798)
1. Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET.
Tatekawa H; Hagiwara A; Uetani H; Bahri S; Raymond C; Lai A; Cloughesy TF; Nghiemphu PL; Liau LM; Pope WB; Salamon N; Ellingson BM
Cancer Imaging; 2021 Mar; 21(1):27. PubMed ID: 33691798
[TBL] [Abstract][Full Text] [Related]
2. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.
Inano R; Oishi N; Kunieda T; Arakawa Y; Yamao Y; Shibata S; Kikuchi T; Fukuyama H; Miyamoto S
Neuroimage Clin; 2014; 5():396-407. PubMed ID: 25180159
[TBL] [Abstract][Full Text] [Related]
3. Multiparametric MR-PET measurements in hypermetabolic regions reflect differences in molecular status and tumor grade in treatment-naïve diffuse gliomas.
Tatekawa H; Hagiwara A; Uetani H; Yao J; Oughourlian TC; Bahri S; Wang C; Raymond C; Lai A; Cloughesy TF; Nghiemphu PL; Liau LM; Pope WB; Salamon N; Ellingson BM
J Neurooncol; 2020 Sep; 149(2):337-346. PubMed ID: 32929644
[TBL] [Abstract][Full Text] [Related]
4. Visualization of tumor heterogeneity and prediction of isocitrate dehydrogenase mutation status for human gliomas using multiparametric physiologic and metabolic MRI.
Hagiwara A; Tatekawa H; Yao J; Raymond C; Everson R; Patel K; Mareninov S; Yong WH; Salamon N; Pope WB; Nghiemphu PL; Liau LM; Cloughesy TF; Ellingson BM
Sci Rep; 2022 Jan; 12(1):1078. PubMed ID: 35058510
[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. Maximum Uptake and Hypermetabolic Volume of 18F-FDOPA PET Estimate Molecular Status and Overall Survival in Low-Grade Gliomas: A PET and MRI Study.
Tatekawa H; Yao J; Oughourlian TC; Hagiwara A; Wang C; Raymond C; Lai A; Cloughesy TF; Nghiemphu PL; Liau LM; Salamon N; Ellingson BM
Clin Nucl Med; 2020 Dec; 45(12):e505-e511. PubMed ID: 33031233
[TBL] [Abstract][Full Text] [Related]
7. Static
Song S; Wang L; Yang H; Shan Y; Cheng Y; Xu L; Dong C; Zhao G; Lu J
Eur Radiol; 2021 Jun; 31(6):4087-4096. PubMed ID: 33211141
[TBL] [Abstract][Full Text] [Related]
8. Improving Noninvasive Classification of Molecular Subtypes of Adult Gliomas With Diffusion-Weighted MR Imaging: An Externally Validated Machine Learning Algorithm.
Guo Y; Ma Z; Pei D; Duan W; Guo Y; Liu Z; Guan F; Wang Z; Xing A; Guo Z; Luo L; Wang W; Yu B; Zhou J; Ji Y; Yan D; Cheng J; Liu X; Yan J; Zhang Z
J Magn Reson Imaging; 2023 Oct; 58(4):1234-1242. PubMed ID: 36727433
[TBL] [Abstract][Full Text] [Related]
9. Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study.
Verburg N; Koopman T; Yaqub MM; Hoekstra OS; Lammertsma AA; Barkhof F; Pouwels PJW; Reijneveld JC; Heimans JJ; Rozemuller AJM; Bruynzeel AME; Lagerwaard F; Vandertop WP; Boellaard R; Wesseling P; de Witt Hamer PC
Neuro Oncol; 2020 Mar; 22(3):412-422. PubMed ID: 31550353
[TBL] [Abstract][Full Text] [Related]
10. T2-FLAIR mismatch sign and machine learning-based multiparametric MRI radiomics in predicting IDH mutant 1p/19q non-co-deleted diffuse lower-grade gliomas.
Tang WT; Su CQ; Lin J; Xia ZW; Lu SS; Hong XN
Clin Radiol; 2024 May; 79(5):e750-e758. PubMed ID: 38360515
[TBL] [Abstract][Full Text] [Related]
11. Hybrid 11C-MET PET/MRI Combined With "Machine Learning" in Glioma Diagnosis According to the Revised Glioma WHO Classification 2016.
Kebir S; Weber M; Lazaridis L; Deuschl C; Schmidt T; Mönninghoff C; Keyvani K; Umutlu L; Pierscianek D; Forsting M; Sure U; Stuschke M; Kleinschnitz C; Scheffler B; Colletti PM; Rubello D; Rischpler C; Glas M
Clin Nucl Med; 2019 Mar; 44(3):214-220. PubMed ID: 30516675
[TBL] [Abstract][Full Text] [Related]
12. World Health Organization Grade II/III Glioma Molecular Status: Prediction by MRI Morphologic Features and Apparent Diffusion Coefficient.
Maynard J; Okuchi S; Wastling S; Busaidi AA; Almossawi O; Mbatha W; Brandner S; Jaunmuktane Z; Koc AM; Mancini L; Jäger R; Thust S
Radiology; 2020 Jul; 296(1):111-121. PubMed ID: 32315266
[TBL] [Abstract][Full Text] [Related]
13. Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.
Yuan J; Siakallis L; Li HB; Brandner S; Zhang J; Li C; Mancini L; Bisdas S
BMC Med Imaging; 2024 May; 24(1):104. PubMed ID: 38702613
[TBL] [Abstract][Full Text] [Related]
14. Predicting Isocitrate Dehydrogenase (IDH) Mutation Status in Gliomas Using Multiparameter MRI Radiomics Features.
Peng H; Huo J; Li B; Cui Y; Zhang H; Zhang L; Ma L
J Magn Reson Imaging; 2021 May; 53(5):1399-1407. PubMed ID: 33179832
[TBL] [Abstract][Full Text] [Related]
15. Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis.
Zhao J; Huang Y; Song Y; Xie D; Hu M; Qiu H; Chu J
Eur Radiol; 2020 Aug; 30(8):4664-4674. PubMed ID: 32193643
[TBL] [Abstract][Full Text] [Related]
16. Multiparametric evaluation of low grade gliomas at follow-up: comparison between diffusion and perfusion MR with (18)F-FDOPA PET.
Rossi Espagnet MC; Romano A; Mancuso V; Cicone F; Napolitano A; Scaringi C; Minniti G; Bozzao A
Br J Radiol; 2016 Oct; 89(1066):20160476. PubMed ID: 27505026
[TBL] [Abstract][Full Text] [Related]
17. Integration of dynamic parameters in the analysis of
Ginet M; Zaragori T; Marie PY; Roch V; Gauchotte G; Rech F; Blonski M; Lamiral Z; Taillandier L; Imbert L; Verger A
Eur J Nucl Med Mol Imaging; 2020 Jun; 47(6):1381-1390. PubMed ID: 31529264
[TBL] [Abstract][Full Text] [Related]
18. Comparison of [
Shymanskaya A; Worthoff WA; Stoffels G; Lindemeyer J; Neumaier B; Lohmann P; Galldiks N; Langen KJ; Shah NJ
Mol Imaging Biol; 2020 Feb; 22(1):198-207. PubMed ID: 30989437
[TBL] [Abstract][Full Text] [Related]
19. Exploring the mechanism of 18F-fluorodopa uptake in recurrent high-grade gliomas: A comprehensive histomolecular-positron emission tomography analysis.
Cobes N; Tran S; Mathon B; Nichelli L; Bielle F; Touat M; Kas A; Rozenblum L
Eur J Neurol; 2024 Jan; 31(1):e16093. PubMed ID: 37823694
[TBL] [Abstract][Full Text] [Related]
20. Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.
De Looze C; Beausang A; Cryan J; Loftus T; Buckley PG; Farrell M; Looby S; Reilly R; Brett F; Kearney H
J Neurooncol; 2018 Sep; 139(2):491-499. PubMed ID: 29770897
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]