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Items: 1 to 20 of 99

1.

A mechanically coupled reaction-diffusion model for predicting the response of breast tumors to neoadjuvant chemotherapy.

Weis JA, Miga MI, Arlinghaus LR, Li X, Chakravarthy AB, Abramson V, Farley J, Yankeelov TE.

Phys Med Biol. 2013 Sep 7;58(17):5851-66. doi: 10.1088/0031-9155/58/17/5851. Epub 2013 Aug 6.

2.

Predicting the Response of Breast Cancer to Neoadjuvant Therapy Using a Mechanically Coupled Reaction-Diffusion Model.

Weis JA, Miga MI, Arlinghaus LR, Li X, Abramson V, Chakravarthy AB, Pendyala P, Yankeelov TE.

Cancer Res. 2015 Nov 15;75(22):4697-707. doi: 10.1158/0008-5472.CAN-14-2945. Epub 2015 Sep 2.

PMID:
26333809
3.

Identification of residual breast carcinoma following neoadjuvant chemotherapy: diffusion-weighted imaging--comparison with contrast-enhanced MR imaging and pathologic findings.

Woodhams R, Kakita S, Hata H, Iwabuchi K, Kuranami M, Gautam S, Hatabu H, Kan S, Mountford C.

Radiology. 2010 Feb;254(2):357-66. doi: 10.1148/radiol.2542090405.

PMID:
20093508
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6.

Prediction of pathologic response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and MRS.

Shin HJ, Baek HM, Ahn JH, Baek S, Kim H, Cha JH, Kim HH.

NMR Biomed. 2012 Dec;25(12):1349-59. doi: 10.1002/nbm.2807. Epub 2012 May 6.

PMID:
22566277
7.

Early prediction of the response of breast tumors to neoadjuvant chemotherapy using quantitative MRI and machine learning.

Mani S, Chen Y, Arlinghaus LR, Li X, Chakravarthy AB, Bhave SR, Welch EB, Levy MA, Yankeelov TE.

AMIA Annu Symp Proc. 2011;2011:868-77. Epub 2011 Oct 22.

8.

Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy.

Mani S, Chen Y, Li X, Arlinghaus L, Chakravarthy AB, Abramson V, Bhave SR, Levy MA, Xu H, Yankeelov TE.

J Am Med Inform Assoc. 2013 Jul-Aug;20(4):688-95. doi: 10.1136/amiajnl-2012-001332. Epub 2013 Apr 24.

9.

DW-MRI ADC values can predict treatment response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy.

Li XR, Cheng LQ, Liu M, Zhang YJ, Wang JD, Zhang AL, Song X, Li J, Zheng YQ, Liu L.

Med Oncol. 2012 Jun;29(2):425-31. doi: 10.1007/s12032-011-9842-y. Epub 2011 Feb 1.

PMID:
21286861
10.

Monitoring the size and response of locally advanced breast cancers to neoadjuvant chemotherapy (weekly paclitaxel and epirubicin) with serial enhanced MRI.

Cheung YC, Chen SC, Su MY, See LC, Hsueh S, Chang HK, Lin YC, Tsai CS.

Breast Cancer Res Treat. 2003 Mar;78(1):51-8.

PMID:
12611457
11.
12.

Accuracy of MRI for estimating residual tumor size after neoadjuvant chemotherapy in locally advanced breast cancer: relation to response patterns on MRI.

Kim HJ, Im YH, Han BK, Choi N, Lee J, Kim JH, Choi YL, Ahn JS, Nam SJ, Park YS, Choe YH, Ko YH, Yang JH.

Acta Oncol. 2007;46(7):996-1003.

PMID:
17851879
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14.

Diffusion-weighted and dynamic contrast-enhanced MRI in evaluation of early treatment effects during neoadjuvant chemotherapy in breast cancer patients.

Jensen LR, Garzon B, Heldahl MG, Bathen TF, Lundgren S, Gribbestad IS.

J Magn Reson Imaging. 2011 Nov;34(5):1099-109. doi: 10.1002/jmri.22726. Epub 2011 Aug 23.

PMID:
22002757
15.

Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer.

Ah-See ML, Makris A, Taylor NJ, Harrison M, Richman PI, Burcombe RJ, Stirling JJ, d'Arcy JA, Collins DJ, Pittam MR, Ravichandran D, Padhani AR.

Clin Cancer Res. 2008 Oct 15;14(20):6580-9. doi: 10.1158/1078-0432.CCR-07-4310.

16.

Combination of 18F-FDG PET/CT and diffusion-weighted MR imaging as a predictor of histologic response to neoadjuvant chemotherapy: preliminary results in osteosarcoma.

Byun BH, Kong CB, Lim I, Choi CW, Song WS, Cho WH, Jeon DG, Koh JS, Lee SY, Lim SM.

J Nucl Med. 2013 Jul;54(7):1053-9. doi: 10.2967/jnumed.112.115964. Epub 2013 May 13.

17.

Diffusion-weighted imaging in evaluating the response to neoadjuvant breast cancer treatment.

Belli P, Costantini M, Ierardi C, Bufi E, Amato D, Mule' A, Nardone L, Terribile D, Bonomo L.

Breast J. 2011 Nov-Dec;17(6):610-9. doi: 10.1111/j.1524-4741.2011.01160.x. Epub 2011 Sep 20.

PMID:
21929557
18.

Magnetic resonance imaging patterns of tumor regression after neoadjuvant chemotherapy in breast cancer patients: correlation with pathological response grading system based on tumor cellularity.

Kim TH, Kang DK, Yim H, Jung YS, Kim KS, Kang SY.

J Comput Assist Tomogr. 2012 Mar-Apr;36(2):200-6. doi: 10.1097/RCT.0b013e318246abf3.

PMID:
22446360
19.

Relationship of clinical and pathologic response to neoadjuvant chemotherapy and outcome of locally advanced breast cancer.

Gajdos C, Tartter PI, Estabrook A, Gistrak MA, Jaffer S, Bleiweiss IJ.

J Surg Oncol. 2002 May;80(1):4-11.

PMID:
11967899
20.

Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer.

Park SH, Moon WK, Cho N, Song IC, Chang JM, Park IA, Han W, Noh DY.

Radiology. 2010 Oct;257(1):56-63. doi: 10.1148/radiol.10092021.

PMID:
20851939
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