183 related articles for article (PubMed ID: 35778618)
1. T2-weighted MRI radiomics in high-grade intramedullary osteosarcoma: predictive accuracy in assessing histologic response to chemotherapy, overall survival, and disease-free survival.
White LM; Atinga A; Naraghi AM; Lajkosz K; Wunder JS; Ferguson P; Tsoi K; Griffin A; Haider M
Skeletal Radiol; 2023 Mar; 52(3):553-564. PubMed ID: 35778618
[TBL] [Abstract][Full Text] [Related]
2. Prediction of Histologic Neoadjuvant Chemotherapy Response in Osteosarcoma Using Pretherapeutic MRI Radiomics.
Bouhamama A; Leporq B; Khaled W; Nemeth A; Brahmi M; Dufau J; Marec-Bérard P; Drapé JL; Gouin F; Bertrand-Vasseur A; Blay JY; Beuf O; Pilleul F
Radiol Imaging Cancer; 2022 Sep; 4(5):e210107. PubMed ID: 36178349
[TBL] [Abstract][Full Text] [Related]
3. Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram.
Zhong J; Zhang C; Hu Y; Zhang J; Liu Y; Si L; Xing Y; Ding D; Geng J; Jiao Q; Zhang H; Yang G; Yao W
Eur Radiol; 2022 Sep; 32(9):6196-6206. PubMed ID: 35364712
[TBL] [Abstract][Full Text] [Related]
4. [Prediction of chemotherapy response in primary osteosarcoma using the machine learning technique on radiomic data].
Dufau J; Bouhamama A; Leporq B; Malaureille L; Beuf O; Gouin F; Pilleul F; Marec-Berard P
Bull Cancer; 2019 Nov; 106(11):983-999. PubMed ID: 31587802
[TBL] [Abstract][Full Text] [Related]
5. Prediction of response to preoperative neoadjuvant chemotherapy in extremity high-grade osteosarcoma using X-ray and multiparametric MRI radiomics.
Luo Z; Li J; Liao Y; Huang W; Li Y; Shen X
J Xray Sci Technol; 2023; 31(3):611-626. PubMed ID: 37005907
[TBL] [Abstract][Full Text] [Related]
6. MRI-based radiomics signature for pretreatment prediction of pathological response to neoadjuvant chemotherapy in osteosarcoma: a multicenter study.
Chen H; Zhang X; Wang X; Quan X; Deng Y; Lu M; Wei Q; Ye Q; Zhou Q; Xiang Z; Liang C; Yang W; Zhao Y
Eur Radiol; 2021 Oct; 31(10):7913-7924. PubMed ID: 33825032
[TBL] [Abstract][Full Text] [Related]
7. Correlation of histopathology and multi-modal magnetic resonance imaging in childhood osteosarcoma: Predicting tumor response to chemotherapy.
Teo KY; Daescu O; Cederberg K; Sengupta A; Leavey PJ
PLoS One; 2022; 17(2):e0259564. PubMed ID: 35157711
[TBL] [Abstract][Full Text] [Related]
8. Non-invasive intravoxel incoherent motion MRI in prediction of histopathological response to neoadjuvant chemotherapy and survival outcome in osteosarcoma at the time of diagnosis.
Baidya Kayal E; Bakhshi S; Kandasamy D; Sharma MC; Khan SA; Kumar VS; Khare K; Sharma R; Mehndiratta A
J Transl Med; 2022 Dec; 20(1):625. PubMed ID: 36575510
[TBL] [Abstract][Full Text] [Related]
9. Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study.
Huang B; Wang J; Sun M; Chen X; Xu D; Li ZP; Ma J; Feng ST; Gao Z
BMC Cancer; 2020 Apr; 20(1):322. PubMed ID: 32293344
[TBL] [Abstract][Full Text] [Related]
10. A Delta-radiomics model for preoperative evaluation of Neoadjuvant chemotherapy response in high-grade osteosarcoma.
Lin P; Yang PF; Chen S; Shao YY; Xu L; Wu Y; Teng W; Zhou XZ; Li BH; Luo C; Xu LM; Huang M; Niu TY; Ye ZM
Cancer Imaging; 2020 Jan; 20(1):7. PubMed ID: 31937372
[TBL] [Abstract][Full Text] [Related]
11. Radiomics signature extracted from diffusion-weighted magnetic resonance imaging predicts outcomes in osteosarcoma.
Zhao S; Su Y; Duan J; Qiu Q; Ge X; Wang A; Yin Y
J Bone Oncol; 2019 Dec; 19():100263. PubMed ID: 31667064
[TBL] [Abstract][Full Text] [Related]
12. The accuracy of breast MRI radiomic methodologies in predicting pathological complete response to neoadjuvant chemotherapy: A systematic review and network meta-analysis.
O'Donnell JPM; Gasior SA; Davey MG; O'Malley E; Lowery AJ; McGarry J; O'Connell AM; Kerin MJ; McCarthy P
Eur J Radiol; 2022 Dec; 157():110561. PubMed ID: 36308849
[TBL] [Abstract][Full Text] [Related]
13. Imaging presentation of extraskeletal osteosarcomas on CT and MRI and correlation with patients outcome: A two-center retrospective study of 54 patients.
Crombé A; Spinnato P; Righi A; Leopardi MP; Carpenzano M; Izzo F; Parmeggiani A; Linck PA; Perret R; Cesari M; Longhi A; Miceli M; Kind M; Bianchi G
Diagn Interv Imaging; 2023 Jun; 104(6):297-306. PubMed ID: 36813659
[TBL] [Abstract][Full Text] [Related]
14. MRI for evaluation of preoperative chemotherapy in osteosarcoma.
Yildirim O; Al Khatalin M; Kargin OA; Camurdan VB
Radiography (Lond); 2022 Aug; 28(3):593-604. PubMed ID: 35537246
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of the neoadjuvant chemotherapy response in osteosarcoma using the MRI DWI-based machine learning radiomics nomogram.
Zhang L; Gao Q; Dou Y; Cheng T; Xia Y; Li H; Gao S
Front Oncol; 2024; 14():1345576. PubMed ID: 38577327
[TBL] [Abstract][Full Text] [Related]
16. MRI-based delta-radiomics predicts pathologic complete response in high-grade soft-tissue sarcoma patients treated with neoadjuvant therapy.
Peeken JC; Asadpour R; Specht K; Chen EY; Klymenko O; Akinkuoroye V; Hippe DS; Spraker MB; Schaub SK; Dapper H; Knebel C; Mayr NA; Gersing AS; Woodruff HC; Lambin P; Nyflot MJ; Combs SE
Radiother Oncol; 2021 Nov; 164():73-82. PubMed ID: 34506832
[TBL] [Abstract][Full Text] [Related]
17. Comparison of 99mTc-methyl diphosphonate bone scintigraphy and 18F-fluorodeoxyglucose positron emission tomography/computed tomography to predict histologic response to neoadjuvant chemotherapy in patients with osteosarcoma.
Lee I; Byun BH; Lim I; Kim BI; Kong CB; Song WS; Cho WH; Koh JS; Lim SM
Medicine (Baltimore); 2018 Sep; 97(37):e12318. PubMed ID: 30212975
[TBL] [Abstract][Full Text] [Related]
18. Texture analysis for chemotherapy response evaluation in osteosarcoma using MR imaging.
Baidya Kayal E; Kandasamy D; Khare K; Bakhshi S; Sharma R; Mehndiratta A
NMR Biomed; 2021 Feb; 34(2):e4426. PubMed ID: 33078438
[TBL] [Abstract][Full Text] [Related]
19. "Real-world" radiomics from multi-vendor MRI: an original retrospective study on the prediction of nodal status and disease survival in breast cancer, as an exemplar to promote discussion of the wider issues.
Doran SJ; Kumar S; Orton M; d'Arcy J; Kwaks F; O'Flynn E; Ahmed Z; Downey K; Dowsett M; Turner N; Messiou C; Koh DM
Cancer Imaging; 2021 May; 21(1):37. PubMed ID: 34016188
[TBL] [Abstract][Full Text] [Related]
20. Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI.
Yardimci AH; Kocak B; Sel I; Bulut H; Bektas CT; Cin M; Dursun N; Bektas H; Mermut O; Yardimci VH; Kilickesmez O
Jpn J Radiol; 2023 Jan; 41(1):71-82. PubMed ID: 35962933
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
