» Articles » PMID: 34688263

Predicting Pathologic Response to Neoadjuvant Chemotherapy in Patients with Locally Advanced Breast Cancer Using Multiparametric MRI

Overview
Journal BMC Med Imaging
Publisher Biomed Central
Specialty Radiology
Date 2021 Oct 24
PMID 34688263
Citations 4
Authors
Affiliations
Soon will be listed here.
Abstract

Background: This study aims to observe and analyze the effect of diffusion weighted magnetic resonance imaging (MRI) on the patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy.

Methods: Fifty patients (mean age, 48.7 years) with stage II-III breast cancer who underwent neoadjuvant chemotherapy and preoperative MRI between 2016 and 2020 were retrospectively evaluated. The associations between preoperative breast MRI findings/clinicopathological features and outcomes of neoadjuvant chemotherapy were assessed.

Results: Clinical stage at baseline (OR: 0.104, 95% confidence interval (CI) 0.021-0.516, P = 0.006) and standard apparent diffusion coefficient (ADC) change (OR: 9.865, 95% CI 1.024-95.021, P = 0.048) were significant predictive factors of the effects of neoadjuvant chemotherapy. The percentage increase of standard ADC value in pathologic complete response (pCR) group was larger than that in non-pCR group at first time point (P < 0.05). A correlation was observed between the change in standard ADC values and tumor diameter at first follow-up (r: 0.438, P < 0.05).

Conclusions: Our findings support that change in standard ADC values and clinical stage at baseline can predict the effects of neoadjuvant chemotherapy for patients with breast cancer in early stage.

Citing Articles

Predictive value of ultrasound doppler parameters in neoadjuvant chemotherapy response of breast cancer: Prospective comparison with magnetic resonance and mammography.

Conz L, Jales R, Doria M, Melloni I, Cres Lyrio C, Menossi C PLoS One. 2024; 19(6):e0302527.

PMID: 38833499 PMC: 11149875. DOI: 10.1371/journal.pone.0302527.


Multiparametric MRI for characterization of the tumour microenvironment.

Hoffmann E, Masthoff M, Kunz W, Seidensticker M, Bobe S, Gerwing M Nat Rev Clin Oncol. 2024; 21(6):428-448.

PMID: 38641651 DOI: 10.1038/s41571-024-00891-1.


Development of a multiparametric model for predicting the response to neoadjuvant chemotherapy in breast cancer.

Qian F, Mao Y, Dong J, Xie F, Fang X, Zhang Q Transl Cancer Res. 2024; 13(2):558-568.

PMID: 38482410 PMC: 10928635. DOI: 10.21037/tcr-23-770.


Evaluation of pretreatment ADC values as predictors of treatment response to neoadjuvant chemotherapy in patients with breast cancer - a multicenter study.

Surov A, Pech M, Meyer H, Bitencourt A, Fujimoto H, Baxter G Cancer Imaging. 2022; 22(1):68.

PMID: 36494872 PMC: 9733082. DOI: 10.1186/s40644-022-00501-2.

References
1.
Park S, Moon W, Cho N, Song I, Chang J, Park I . Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Radiology. 2010; 257(1):56-63. DOI: 10.1148/radiol.10092021. View

2.
Zhang X, Sun Y, Tang L, Xue W, Zhang X . Correlation of diffusion-weighted imaging data with apoptotic and proliferation indexes in CT26 colorectal tumor homografts in balb/c mouse. J Magn Reson Imaging. 2011; 33(5):1171-6. DOI: 10.1002/jmri.22558. View

3.
Bufi E, Belli P, Costantini M, Cipriani A, Di Matteo M, Bonatesta A . Role of the Apparent Diffusion Coefficient in the Prediction of Response to Neoadjuvant Chemotherapy in Patients With Locally Advanced Breast Cancer. Clin Breast Cancer. 2015; 15(5):370-80. DOI: 10.1016/j.clbc.2015.02.002. View

4.
Kang J, Youk J, Kim J, Gweon H, Eun N, Ko K . Identification of Preoperative Magnetic Resonance Imaging Features Associated with Positive Resection Margins in Breast Cancer: A Retrospective Study. Korean J Radiol. 2018; 19(5):897-904. PMC: 6082768. DOI: 10.3348/kjr.2018.19.5.897. View

5.
Galban C, Hoff B, Chenevert T, Ross B . Diffusion MRI in early cancer therapeutic response assessment. NMR Biomed. 2016; 30(3). PMC: 4947029. DOI: 10.1002/nbm.3458. View