149 related articles for article (PubMed ID: 38114526)
1. A priori prediction of breast cancer response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivative and molecular subtype.
Sannachi L; Osapoetra LO; DiCenzo D; Halstead S; Wright F; Look-Hong N; Slodkowska E; Gandhi S; Curpen B; Kolios MC; Oelze M; Czarnota GJ
Sci Rep; 2023 Dec; 13(1):22687. PubMed ID: 38114526
[TBL] [Abstract][Full Text] [Related]
2. Quantitative ultrasound radiomics in predicting response to neoadjuvant chemotherapy in patients with locally advanced breast cancer: Results from multi-institutional study.
DiCenzo D; Quiaoit K; Fatima K; Bhardwaj D; Sannachi L; Gangeh M; Sadeghi-Naini A; Dasgupta A; Kolios MC; Trudeau M; Gandhi S; Eisen A; Wright F; Look Hong N; Sahgal A; Stanisz G; Brezden C; Dinniwell R; Tran WT; Yang W; Curpen B; Czarnota GJ
Cancer Med; 2020 Aug; 9(16):5798-5806. PubMed ID: 32602222
[TBL] [Abstract][Full Text] [Related]
3.
Osapoetra LO; Sannachi L; Quiaoit K; Dasgupta A; DiCenzo D; Fatima K; Wright F; Dinniwell R; Trudeau M; Gandhi S; Tran W; Kolios MC; Yang W; Czarnota GJ
Oncotarget; 2021 Jan; 12(2):81-94. PubMed ID: 33520113
[TBL] [Abstract][Full Text] [Related]
4. Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results.
Quiaoit K; DiCenzo D; Fatima K; Bhardwaj D; Sannachi L; Gangeh M; Sadeghi-Naini A; Dasgupta A; Kolios MC; Trudeau M; Gandhi S; Eisen A; Wright F; Look-Hong N; Sahgal A; Stanisz G; Brezden C; Dinniwell R; Tran WT; Yang W; Curpen B; Czarnota GJ
PLoS One; 2020; 15(7):e0236182. PubMed ID: 32716959
[TBL] [Abstract][Full Text] [Related]
5. Quantitative Ultrasound Monitoring of Breast Tumour Response to Neoadjuvant Chemotherapy: Comparison of Results Among Clinical Scanners.
Sannachi L; Gangeh M; Naini AS; Bhargava P; Jain A; Tran WT; Czarnota GJ
Ultrasound Med Biol; 2020 May; 46(5):1142-1157. PubMed ID: 32111456
[TBL] [Abstract][Full Text] [Related]
6. Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features.
Sannachi L; Gangeh M; Tadayyon H; Sadeghi-Naini A; Gandhi S; Wright FC; Slodkowska E; Curpen B; Tran W; Czarnota GJ
PLoS One; 2018; 13(1):e0189634. PubMed ID: 29298305
[TBL] [Abstract][Full Text] [Related]
7. Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response.
Hussain L; Huang P; Nguyen T; Lone KJ; Ali A; Khan MS; Li H; Suh DY; Duong TQ
Biomed Eng Online; 2021 Jun; 20(1):63. PubMed ID: 34183038
[TBL] [Abstract][Full Text] [Related]
8. A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound.
Tadayyon H; Sannachi L; Gangeh MJ; Kim C; Ghandi S; Trudeau M; Pritchard K; Tran WT; Slodkowska E; Sadeghi-Naini A; Czarnota GJ
Sci Rep; 2017 Apr; 7():45733. PubMed ID: 28401902
[TBL] [Abstract][Full Text] [Related]
9. Comparison of methods for texture analysis of QUS parametric images in the characterization of breast lesions.
Osapoetra LO; Chan W; Tran W; Kolios MC; Czarnota GJ
PLoS One; 2020; 15(12):e0244965. PubMed ID: 33382837
[TBL] [Abstract][Full Text] [Related]
10. Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.
Wu J; Gong G; Cui Y; Li R
J Magn Reson Imaging; 2016 Nov; 44(5):1107-1115. PubMed ID: 27080586
[TBL] [Abstract][Full Text] [Related]
11. Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.
Yu FH; Miao SM; Li CY; Hang J; Deng J; Ye XH; Liu Y
Eur Radiol; 2023 Aug; 33(8):5634-5644. PubMed ID: 36976336
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy.
Falou O; Sannachi L; Haque M; Czarnota GJ; Kolios MC
Sci Rep; 2024 Jan; 14(1):2340. PubMed ID: 38282158
[TBL] [Abstract][Full Text] [Related]
14. Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysis.
Tran WT; Gangeh MJ; Sannachi L; Chin L; Watkins E; Bruni SG; Rastegar RF; Curpen B; Trudeau M; Gandhi S; Yaffe M; Slodkowska E; Childs C; Sadeghi-Naini A; Czarnota GJ
Br J Cancer; 2017 May; 116(10):1329-1339. PubMed ID: 28419079
[TBL] [Abstract][Full Text] [Related]
15. Quantitative ultrasound assessment of breast tumor response to chemotherapy using a multi-parameter approach.
Tadayyon H; Sannachi L; Gangeh M; Sadeghi-Naini A; Tran W; Trudeau ME; Pritchard K; Ghandi S; Verma S; Czarnota GJ
Oncotarget; 2016 Jul; 7(29):45094-45111. PubMed ID: 27105515
[TBL] [Abstract][Full Text] [Related]
16. Early Changes in Quantitative Ultrasound Imaging Parameters during Neoadjuvant Chemotherapy to Predict Recurrence in Patients with Locally Advanced Breast Cancer.
Bhardwaj D; Dasgupta A; DiCenzo D; Brade S; Fatima K; Quiaoit K; Trudeau M; Gandhi S; Eisen A; Wright F; Look-Hong N; Curpen B; Sannachi L; Czarnota GJ
Cancers (Basel); 2022 Feb; 14(5):. PubMed ID: 35267555
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Breast lesion characterization using Quantitative Ultrasound (QUS) and derivative texture methods.
Osapoetra LO; Sannachi L; DiCenzo D; Quiaoit K; Fatima K; Czarnota GJ
Transl Oncol; 2020 Oct; 13(10):100827. PubMed ID: 32663657
[TBL] [Abstract][Full Text] [Related]
19. Using Flow Characteristics in Three-Dimensional Power Doppler Ultrasound Imaging to Predict Complete Responses in Patients Undergoing Neoadjuvant Chemotherapy.
Shia WC; Huang YL; Wu HK; Chen DR
J Ultrasound Med; 2017 May; 36(5):887-900. PubMed ID: 28109009
[TBL] [Abstract][Full Text] [Related]
20. Identifying an early treatment window for predicting breast cancer response to neoadjuvant chemotherapy using immunohistopathology and hemoglobin parameters.
Zhu Q; Tannenbaum S; Kurtzman SH; DeFusco P; Ricci A; Vavadi H; Zhou F; Xu C; Merkulov A; Hegde P; Kane M; Wang L; Sabbath K
Breast Cancer Res; 2018 Jun; 20(1):56. PubMed ID: 29898762
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]