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CC BY-NC-ND 4.0 · Indian J Radiol Imaging 2022; 32(03): 332-338
DOI: 10.1055/s-0042-1750155
Original Article

Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes

Neetu Singh
,
Shivi Jain
1   Department of Radiodiagnosis and Imaging, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
,
Ashish Verma
1   Department of Radiodiagnosis and Imaging, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
,
Seema Khanna
2   Department of General Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
,
Ram Chandra Shukla
1   Department of Radiodiagnosis and Imaging, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
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Funding None.
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Abstract

Purpose The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) and hence diffusion-weighted imaging in prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) in locally advanced breast cancer (LABC) and its molecular subtypes.

Methods In this tertiary hospital-based prospective study, 30 patients aged 30 to 65 years, having clinically/cytologically diagnosed LABC, were included. Magnetic resonance imaging (MRI) was done to obtain prechemotherapy ADC (ADCpre), postchemotherapy ADC (ADCpost), change in ADC (ΔADC), and ΔADC% for each tumor and its subtype. Postsurgical pCR was used as the reference standard for determining tumor response. All four ADC parameters were compared between pCR and non-pCR groups.

Results Of the 30 patients, 19 (63.3%) patients showed pCR, while 11 (36.7%) patients did not. The pCR group showed significantly lower mean ADCpre (p <  0.001) and higher mean ADCpost (p <  0.05), ΔADC, and ΔADC% (p = 0.000) than non-pCR group. The best cutoff values to differentiate responders from nonresponders with receiver operating characteristic curve analysis of ADCpre, ADCpost, and ΔADC% were 0.98 × 10−3 mm2/s (68.4% sensitivity, 63.6% specificity), 1.31×10−3 mm2/s (68.4% sensitivity, 63.6% specificity), and 25% (84.2% sensitivity, 90.9% specificity), respectively. Human epidermal growth factor receptor 2 (HER2)-enriched subtype showed significant difference in mean ADCpre (p = 0.045), while triple-negative subtype showed significant differences in mean ADCpost (p = 0.032) and mean ΔADC (p = 0.019) between the two groups.

Conclusion ADCpre, ADCpost, and ΔADC can predict pCR to NACT in LABC. Among molecular subtypes, ADCpre was predictive only in HER2-enriched subtype, while ADCpost and ΔADC were predictive only in triple-negative subtype.

Keywords

apparent diffusion coefficient - diffusion-weighted imaging - locally advanced breast cancer - neoadjuvant chemotherapy - pathological complete response


Publikationsverlauf

Artikel online veröffentlicht:
17. August 2022

© 2022. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • References

  • 1 U.S. Food and Drug Administration (FDA). Guidance for industry: pathological complete response in neoadjuvant treatment of high-risk early-stage breast cancer: use as an endpoint to support accelerated approval. Accessed July 9, 2018 at: https://www.fda.gov/downloads/drugs/guidances/ucm305501.pdf
  • 2 Park SH, Moon WK, Cho N. et al. Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Radiology 2010; 257 (01) 56-63
    CrossrefPubMedSuche in Google Scholar
  • 3 Pereira NP, Curi C, Osório CABT. et al. Diffusion-weighted magnetic resonance imaging of patients with breast cancer following neoadjuvant chemotherapy provides early prediction of pathological response – a prospective study. Sci Rep 2019; 9 (01) 16372
    CrossrefPubMedSuche in Google Scholar
  • 4 Partridge SC, Zhang Z, Newitt DC. et al; ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators. Diffusion‐weighted MRI findings predict pathologic response in neoadjuvant treatment of breast cancer: the ACRIN 6698 multicenter trial. Radiology 2018; 289 (03) 618-627
    CrossrefPubMedSuche in Google Scholar
  • 5 Sharma U, Danishad KKA, Seenu V, Jagannathan NR. Longitudinal study of the assessment by MRI and diffusion-weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. NMR Biomed 2009; 22 (01) 104-113
    CrossrefPubMedSuche in Google Scholar
  • 6 Hu XY, Li Y, Jin GQ, Lai SL, Huang XY, Su DK. Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Oncotarget 2017; 8 (45) 79642-79649
    CrossrefPubMedSuche in Google Scholar
  • 7 Sugahara T, Korogi Y, Kochi M. et al. Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging 1999; 9 (01) 53-60
    Suche in Google Scholar
  • 8 Humphries PD, Sebire NJ, Siegel MJ, Olsen OE. Tumors in pediatric patients at diffusion-weighted MR imaging: apparent diffusion coefficient and tumor cellularity. Radiology 2007; 245 (03) 848-854
    CrossrefPubMedSuche in Google Scholar
  • 9 Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224 (01) 177-183
    Suche in Google Scholar