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.
471 related articles for article (PubMed ID: 33349519)
1. Radiomics for the Prediction of Treatment Outcome and Survival in Patients With Colorectal Cancer: A Systematic Review. Staal FCR; van der Reijd DJ; Taghavi M; Lambregts DMJ; Beets-Tan RGH; Maas M Clin Colorectal Cancer; 2021 Mar; 20(1):52-71. PubMed ID: 33349519 [TBL] [Abstract][Full Text] [Related]
2. Radiomics in colorectal cancer patients. Inchingolo R; Maino C; Cannella R; Vernuccio F; Cortese F; Dezio M; Pisani AR; Giandola T; Gatti M; Giannini V; Ippolito D; Faletti R World J Gastroenterol; 2023 May; 29(19):2888-2904. PubMed ID: 37274803 [TBL] [Abstract][Full Text] [Related]
3. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer. Li ZY; Wang XD; Li M; Liu XJ; Ye Z; Song B; Yuan F; Yuan Y; Xia CC; Zhang X; Li Q World J Gastroenterol; 2020 May; 26(19):2388-2402. PubMed ID: 32476800 [TBL] [Abstract][Full Text] [Related]
4. Prediction of outcome using pretreatment Lucia F; Visvikis D; Desseroit MC; Miranda O; Malhaire JP; Robin P; Pradier O; Hatt M; Schick U Eur J Nucl Med Mol Imaging; 2018 May; 45(5):768-786. PubMed ID: 29222685 [TBL] [Abstract][Full Text] [Related]
6. Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation. Schurink NW; Min LA; Berbee M; van Elmpt W; van Griethuysen JJM; Bakers FCH; Roberti S; van Kranen SR; Lahaye MJ; Maas M; Beets GL; Beets-Tan RGH; Lambregts DMJ Eur Radiol; 2020 May; 30(5):2945-2954. PubMed ID: 32034488 [TBL] [Abstract][Full Text] [Related]
7. FDG-PET/CT and MRI for Evaluation of Pathologic Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer: A Meta-Analysis of Diagnostic Accuracy Studies. Sheikhbahaei S; Trahan TJ; Xiao J; Taghipour M; Mena E; Connolly RM; Subramaniam RM Oncologist; 2016 Aug; 21(8):931-9. PubMed ID: 27401897 [TBL] [Abstract][Full Text] [Related]
8. Performance of radiomics-based artificial intelligence systems in the diagnosis and prediction of treatment response and survival in esophageal cancer: a systematic review and meta-analysis of diagnostic accuracy. Menon N; Guidozzi N; Chidambaram S; Markar SR Dis Esophagus; 2023 May; 36(6):. PubMed ID: 37236811 [TBL] [Abstract][Full Text] [Related]
9. Prediction of local recurrence and distant metastasis using radiomics analysis of pretreatment nasopharyngeal [18F]FDG PET/CT images. Peng L; Hong X; Yuan Q; Lu L; Wang Q; Chen W Ann Nucl Med; 2021 Apr; 35(4):458-468. PubMed ID: 33543393 [TBL] [Abstract][Full Text] [Related]
10. Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Cui Y; Yang X; Shi Z; Yang Z; Du X; Zhao Z; Cheng X Eur Radiol; 2019 Mar; 29(3):1211-1220. PubMed ID: 30128616 [TBL] [Abstract][Full Text] [Related]
11. Current status and quality of radiomics studies in lymphoma: a systematic review. Wang H; Zhou Y; Li L; Hou W; Ma X; Tian R Eur Radiol; 2020 Nov; 30(11):6228-6240. PubMed ID: 32472274 [TBL] [Abstract][Full Text] [Related]
12. Semiquantitative Volumetry by Sequential PET/CT May Improve Prediction of Complete Response to Neoadjuvant Chemoradiation in Patients With Distal Rectal Cancer. Dos Anjos DA; Perez RO; Habr-Gama A; São Julião GP; Vailati BB; Fernandez LM; de Sousa JB; Buchpiguel CA Dis Colon Rectum; 2016 Sep; 59(9):805-12. PubMed ID: 27505108 [TBL] [Abstract][Full Text] [Related]
13. Functional imaging using radiomic features in assessment of lymphoma. Mayerhoefer ME; Umutlu L; Schöder H Methods; 2021 Apr; 188():105-111. PubMed ID: 32634555 [TBL] [Abstract][Full Text] [Related]
14. Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives. Dercle L; Henry T; Carré A; Paragios N; Deutsch E; Robert C Methods; 2021 Apr; 188():44-60. PubMed ID: 32697964 [TBL] [Abstract][Full Text] [Related]
15. PET/CT radiomics in breast cancer: Mind the step. Sollini M; Cozzi L; Ninatti G; Antunovic L; Cavinato L; Chiti A; Kirienko M Methods; 2021 Apr; 188():122-132. PubMed ID: 31978538 [TBL] [Abstract][Full Text] [Related]
16. The Role of Radiomics in Rectal Cancer. Miranda J; Horvat N; Araujo-Filho JAB; Albuquerque KS; Charbel C; Trindade BMC; Cardoso DL; de Padua Gomes de Farias L; Chakraborty J; Nomura CH J Gastrointest Cancer; 2023 Dec; 54(4):1158-1180. PubMed ID: 37155130 [TBL] [Abstract][Full Text] [Related]
17. Comparison of CT, MRI and FDG-PET in response prediction of patients with locally advanced rectal cancer after multimodal preoperative therapy: is there a benefit in using functional imaging? Denecke T; Rau B; Hoffmann KT; Hildebrandt B; Ruf J; Gutberlet M; Hünerbein M; Felix R; Wust P; Amthauer H Eur Radiol; 2005 Aug; 15(8):1658-66. PubMed ID: 15806369 [TBL] [Abstract][Full Text] [Related]
18. Predicting locally advanced rectal cancer response to neoadjuvant therapy with Giannini V; Mazzetti S; Bertotto I; Chiarenza C; Cauda S; Delmastro E; Bracco C; Di Dia A; Leone F; Medico E; Pisacane A; Ribero D; Stasi M; Regge D Eur J Nucl Med Mol Imaging; 2019 Apr; 46(4):878-888. PubMed ID: 30637502 [TBL] [Abstract][Full Text] [Related]
19. Prediction of neoadjuvant radiation chemotherapy response and survival using pretreatment [(18)F]FDG PET/CT scans in locally advanced rectal cancer. Bang JI; Ha S; Kang SB; Lee KW; Lee HS; Kim JS; Oh HK; Lee HY; Kim SE Eur J Nucl Med Mol Imaging; 2016 Mar; 43(3):422-31. PubMed ID: 26338180 [TBL] [Abstract][Full Text] [Related]
20. Gastric cancer and image-derived quantitative parameters: Part 2-a critical review of DCE-MRI and Tang L; Wang XJ; Baba H; Giganti F Eur Radiol; 2020 Jan; 30(1):247-260. PubMed ID: 31392480 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]