162 related articles for article (PubMed ID: 38512616)
21. Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort.
Boldrini L; Lenkowicz J; Orlandini LC; Yin G; Cusumano D; Chiloiro G; Dinapoli N; Peng Q; Casà C; Gambacorta MA; Valentini V; Lang J
Radiat Oncol; 2022 Apr; 17(1):78. PubMed ID: 35428267
[TBL] [Abstract][Full Text] [Related]
22. Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study.
Li Z; Zhang J; Zhong Q; Feng Z; Shi Y; Xu L; Zhang R; Yu F; Lv B; Yang T; Huang C; Cui F; Chen F
Eur Radiol; 2023 Mar; 33(3):1835-1843. PubMed ID: 36282309
[TBL] [Abstract][Full Text] [Related]
23. MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy.
Shin J; Seo N; Baek SE; Son NH; Lim JS; Kim NK; Koom WS; Kim S
Radiology; 2022 May; 303(2):351-358. PubMed ID: 35133200
[TBL] [Abstract][Full Text] [Related]
24. THeragnostic utilities for neoplastic DisEases of the rectum by MRI guided radiotherapy (THUNDER 2) phase II trial: interim safety analysis.
Chiloiro G; Romano A; Cusumano D; Boldrini L; Panza G; Placidi L; Meldolesi E; Nardini M; Meffe G; Nicolini G; Votta C; Indovina L; Gambacorta MA
Radiat Oncol; 2023 Oct; 18(1):163. PubMed ID: 37803322
[TBL] [Abstract][Full Text] [Related]
25. Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models.
Shahzadi I; Zwanenburg A; Lattermann A; Linge A; Baldus C; Peeken JC; Combs SE; Diefenhardt M; Rödel C; Kirste S; Grosu AL; Baumann M; Krause M; Troost EGC; Löck S
Sci Rep; 2022 Jun; 12(1):10192. PubMed ID: 35715462
[TBL] [Abstract][Full Text] [Related]
26. Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics.
Wan L; Sun Z; Peng W; Wang S; Li J; Zhao Q; Wang S; Ouyang H; Zhao X; Zou S; Zhang H
J Magn Reson Imaging; 2022 Oct; 56(4):1130-1142. PubMed ID: 35142001
[TBL] [Abstract][Full Text] [Related]
27. MRI-Based Radiomic Models Outperform Radiologists in Predicting Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
Wen L; Liu J; Hu P; Bi F; Liu S; Jian L; Zhu S; Nie S; Cao F; Lu Q; Yu X; Liu K
Acad Radiol; 2023 Sep; 30 Suppl 1():S176-S184. PubMed ID: 36739228
[TBL] [Abstract][Full Text] [Related]
28. Feature selection based on unsupervised clustering evaluation for predicting neoadjuvant chemoradiation response for patients with locally advanced rectal cancer.
Chen H; Li X; Pan X; Qiang Y; Qi XS
Phys Med Biol; 2023 Dec; 68(23):. PubMed ID: 37972413
[TBL] [Abstract][Full Text] [Related]
29. Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study.
Shaish H; Aukerman A; Vanguri R; Spinelli A; Armenta P; Jambawalikar S; Makkar J; Bentley-Hibbert S; Del Portillo A; Kiran R; Monti L; Bonifacio C; Kirienko M; Gardner KL; Schwartz L; Keller D
Eur Radiol; 2020 Nov; 30(11):6263-6273. PubMed ID: 32500192
[TBL] [Abstract][Full Text] [Related]
30. Delta Radiomics Analysis for Local Control Prediction in Pancreatic Cancer Patients Treated Using Magnetic Resonance Guided Radiotherapy.
Cusumano D; Boldrini L; Yadav P; Casà C; Lee SL; Romano A; Piras A; Chiloiro G; Placidi L; Catucci F; Votta C; Mattiucci GC; Indovina L; Gambacorta MA; Bassetti M; Valentini V
Diagnostics (Basel); 2021 Jan; 11(1):. PubMed ID: 33466307
[TBL] [Abstract][Full Text] [Related]
31. Developing a prediction model based on MRI for pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Wan L; Zhang C; Zhao Q; Meng Y; Zou S; Yang Y; Liu Y; Jiang J; Ye F; Ouyang H; Zhao X; Zhang H
Abdom Radiol (NY); 2019 Sep; 44(9):2978-2987. PubMed ID: 31327039
[TBL] [Abstract][Full Text] [Related]
32. Rectal Cancer: Assessment of Neoadjuvant Chemoradiation Outcome based on Radiomics of Multiparametric MRI.
Nie K; Shi L; Chen Q; Hu X; Jabbour SK; Yue N; Niu T; Sun X
Clin Cancer Res; 2016 Nov; 22(21):5256-5264. PubMed ID: 27185368
[TBL] [Abstract][Full Text] [Related]
33. Local tuning of radiomics-based model for predicting pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Tang B; Lenkowicz J; Peng Q; Boldrini L; Hou Q; Dinapoli N; Valentini V; Diao P; Yin G; Orlandini LC
BMC Med Imaging; 2022 Mar; 22(1):44. PubMed ID: 35287607
[TBL] [Abstract][Full Text] [Related]
34. A field strength independent MR radiomics model to predict pathological complete response in locally advanced rectal cancer.
Cusumano D; Meijer G; Lenkowicz J; Chiloiro G; Boldrini L; Masciocchi C; Dinapoli N; Gatta R; Casà C; Damiani A; Barbaro B; Gambacorta MA; Azario L; De Spirito M; Intven M; Valentini V
Radiol Med; 2021 Mar; 126(3):421-429. PubMed ID: 32833198
[TBL] [Abstract][Full Text] [Related]
35. Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
Liu Z; Zhang XY; Shi YJ; Wang L; Zhu HT; Tang Z; Wang S; Li XT; Tian J; Sun YS
Clin Cancer Res; 2017 Dec; 23(23):7253-7262. PubMed ID: 28939744
[No Abstract] [Full Text] [Related]
36. Development and validation of an MRI-based radiomic nomogram to distinguish between good and poor responders in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy.
Wang J; Liu X; Hu B; Gao Y; Chen J; Li J
Abdom Radiol (NY); 2021 May; 46(5):1805-1815. PubMed ID: 33151359
[TBL] [Abstract][Full Text] [Related]
37. Endorectal ultrasound radiomics in locally advanced rectal cancer patients: despeckling and radiotherapy response prediction using machine learning.
Abbaspour S; Abdollahi H; Arabalibeik H; Barahman M; Arefpour AM; Fadavi P; Ay M; Mahdavi SR
Abdom Radiol (NY); 2022 Nov; 47(11):3645-3659. PubMed ID: 35951085
[TBL] [Abstract][Full Text] [Related]
38. Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer.
Cheng Y; Luo Y; Hu Y; Zhang Z; Wang X; Yu Q; Liu G; Cui E; Yu T; Jiang X
Abdom Radiol (NY); 2021 Nov; 46(11):5072-5085. PubMed ID: 34302510
[TBL] [Abstract][Full Text] [Related]
39. [Application of MRI-based Radiomics Models in the Assessment of Hepatic Metastasis of Rectal Cancer].
Hu SX; Yang K; Wang XR; Wen DG; Xia CC; Li X; Li ZL
Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Mar; 52(2):311-318. PubMed ID: 33829708
[TBL] [Abstract][Full Text] [Related]
40. Prognostic value of multiparametric MRI-based radiomics model: Potential role for chemotherapeutic benefits in locally advanced rectal cancer.
Cui Y; Yang W; Ren J; Li D; Du X; Zhang J; Yang X
Radiother Oncol; 2021 Jan; 154():161-169. PubMed ID: 32976874
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]