248 related articles for article (PubMed ID: 33593702)
1. Nomogram for Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Dynamic Contrast-enhanced and Diffusion-weighted MRI.
Zhao R; Lu H; Li YB; Shao ZZ; Ma WJ; Liu PF
Acad Radiol; 2022 Jan; 29 Suppl 1():S155-S163. PubMed ID: 33593702
[TBL] [Abstract][Full Text] [Related]
2. Evaluation of Multiparametric MRI Radiomics-Based Nomogram in Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Two-Center study.
Wang X; Hua H; Han J; Zhong X; Liu J; Chen J
Clin Breast Cancer; 2023 Aug; 23(6):e331-e344. PubMed ID: 37321954
[TBL] [Abstract][Full Text] [Related]
3. Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.
Li Y; Chen Y; Zhao R; Ji Y; Li J; Zhang Y; Lu H
Eur Radiol; 2022 Mar; 32(3):1676-1687. PubMed ID: 34767068
[TBL] [Abstract][Full Text] [Related]
4. Radiomic signatures derived from multiparametric MRI for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer.
Bian T; Wu Z; Lin Q; Wang H; Ge Y; Duan S; Fu G; Cui C; Su X
Br J Radiol; 2020 Nov; 93(1115):20200287. PubMed ID: 32822542
[TBL] [Abstract][Full Text] [Related]
5. Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.
Tahmassebi A; Wengert GJ; Helbich TH; Bago-Horvath Z; Alaei S; Bartsch R; Dubsky P; Baltzer P; Clauser P; Kapetas P; Morris EA; Meyer-Baese A; Pinker K
Invest Radiol; 2019 Feb; 54(2):110-117. PubMed ID: 30358693
[TBL] [Abstract][Full Text] [Related]
6. Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL.
Li W; Newitt DC; Wilmes LJ; Jones EF; Arasu V; Gibbs J; La Yun B; Li E; Partridge SC; Kornak J; ; Esserman LJ; Hylton NM
J Magn Reson Imaging; 2019 Dec; 50(6):1742-1753. PubMed ID: 31026118
[TBL] [Abstract][Full Text] [Related]
7. Factors Affecting Pathologic Complete Response Following Neoadjuvant Chemotherapy in Breast Cancer: Development and Validation of a Predictive Nomogram.
Kim SY; Cho N; Choi Y; Lee SH; Ha SM; Kim ES; Chang JM; Moon WK
Radiology; 2021 May; 299(2):290-300. PubMed ID: 33754824
[TBL] [Abstract][Full Text] [Related]
8. Texture Analysis with 3.0-T MRI for Association of Response to Neoadjuvant Chemotherapy in Breast Cancer.
Eun NL; Kang D; Son EJ; Park JS; Youk JH; Kim JA; Gweon HM
Radiology; 2020 Jan; 294(1):31-41. PubMed ID: 31769740
[TBL] [Abstract][Full Text] [Related]
9. Evaluation of the efficacy of neoadjuvant chemotherapy for breast cancer using diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging.
Xu HD; Zhang YQ
Neoplasma; 2017; 64(3):430-436. PubMed ID: 28253722
[TBL] [Abstract][Full Text] [Related]
10. Prediction of pathological complete response to neoadjuvant chemotherapy in patients with breast cancer using a combination of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging.
Han X; Yang H; Jin S; Sun Y; Zhang H; Shan M; Cheng W
Cancer Med; 2023 Jan; 12(2):1389-1398. PubMed ID: 35822639
[TBL] [Abstract][Full Text] [Related]
11. Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer.
Liang X; Chen X; Yang Z; Liao Y; Wang M; Li Y; Fan W; Dai Z; Zhang Y
BMC Cancer; 2022 Dec; 22(1):1250. PubMed ID: 36460972
[TBL] [Abstract][Full Text] [Related]
12. Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment.
Tateishi U; Miyake M; Nagaoka T; Terauchi T; Kubota K; Kinoshita T; Daisaki H; Macapinlac HA
Radiology; 2012 Apr; 263(1):53-63. PubMed ID: 22438441
[TBL] [Abstract][Full Text] [Related]
13. Prediction of pathological complete response of breast cancer patients who received neoadjuvant chemotherapy with a nomogram based on clinicopathologic variables, ultrasound, and MRI.
Zhang MQ; Liu XP; Du Y; Zha HL; Zha XM; Wang J; Liu XA; Wang SJ; Zou QG; Zhang JL; Li CY
Br J Radiol; 2024 Jan; 97(1153):228-236. PubMed ID: 38263817
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Combining Dynamic Contrast-Enhanced Magnetic Resonance Imaging and Apparent Diffusion Coefficient Maps for a Radiomics Nomogram to Predict Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients.
Chen X; Chen X; Yang J; Li Y; Fan W; Yang Z
J Comput Assist Tomogr; 2020; 44(2):275-283. PubMed ID: 32004189
[TBL] [Abstract][Full Text] [Related]
16. Contrast-free MRI quantitative parameters for early prediction of pathological response to neoadjuvant chemotherapy in breast cancer.
Du S; Gao S; Zhao R; Liu H; Wang Y; Qi X; Li S; Cao J; Zhang L
Eur Radiol; 2022 Aug; 32(8):5759-5772. PubMed ID: 35267091
[TBL] [Abstract][Full Text] [Related]
17. Value of radiomics based on CE-MRI for predicting the efficacy of neoadjuvant chemotherapy in invasive breast cancer.
Li Q; Huang Y; Xiao Q; Duan S; Wang S; Li J; Niu Q; Gu Y
Br J Radiol; 2022 Oct; 95(1139):20220186. PubMed ID: 36005646
[TBL] [Abstract][Full Text] [Related]
18. Intravoxel incoherent motion diffusion-weighted MRI for predicting response to neoadjuvant chemotherapy in breast cancer.
Kim Y; Kim SH; Lee HW; Song BJ; Kang BJ; Lee A; Nam Y
Magn Reson Imaging; 2018 May; 48():27-33. PubMed ID: 29278762
[TBL] [Abstract][Full Text] [Related]
19. Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial.
Partridge SC; Zhang Z; Newitt DC; Gibbs JE; Chenevert TL; Rosen MA; Bolan PJ; Marques HS; Romanoff J; Cimino L; Joe BN; Umphrey HR; Ojeda-Fournier H; Dogan B; Oh K; Abe H; Drukteinis JS; Esserman LJ; Hylton NM;
Radiology; 2018 Dec; 289(3):618-627. PubMed ID: 30179110
[TBL] [Abstract][Full Text] [Related]
20. Multiparametric MRI-based radiomics nomogram for early prediction of pathological response to neoadjuvant chemotherapy in locally advanced gastric cancer.
Li J; Yin H; Wang Y; Zhang H; Ma F; Li H; Qu J
Eur Radiol; 2023 Apr; 33(4):2746-2756. PubMed ID: 36512039
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
