The predictive value of DKI in breast cancer: Does tumour subtype affect pathological response evaluations?

Dandan Zhang; Xiaochuan Geng; Shiteng Suo; Zhiguo Zhuang; Yajia Gu; Jia Hua

doi:10.1016/j.mri.2021.10.013

The predictive value of DKI in breast cancer: Does tumour subtype affect pathological response evaluations?

Magn Reson Imaging. 2022 Jan:85:28-34. doi: 10.1016/j.mri.2021.10.013. Epub 2021 Oct 16.

Authors

Dandan Zhang¹, Xiaochuan Geng², Shiteng Suo³, Zhiguo Zhuang³, Yajia Gu⁴, Jia Hua⁵

Affiliations

¹ Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No.270 Dongan Rd., Shanghai 200032, People's Republic of China.
² Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 Pujian Rd., Shanghai 200127, People's Republic of China; Department of Radiology, Renji Hospital South Campus, School of Medicine, Shanghai Jiao Tong University, No.2000 Jiangyue Rd., Shanghai 201112, People's Republic of China.
³ Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 Pujian Rd., Shanghai 200127, People's Republic of China.
⁴ Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No.270 Dongan Rd., Shanghai 200032, People's Republic of China. Electronic address: cjr.guyajia@vip.163.com.
⁵ Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 Pujian Rd., Shanghai 200127, People's Republic of China. Electronic address: Jill_JiaHua_SJTU@126.com.

PMID: 34662700
DOI: 10.1016/j.mri.2021.10.013

Abstract

Purpose: To explore the differences in quantitative parameters based on diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) between different immunohistochemical indicator statuses and their predictive value for neoadjuvant chemotherapy (NAC) among different phenotypes of breast cancer.

Methods: Eighty-one breast cancer patients who underwent NAC were enrolled in this retrospective study. Correlations between diffusion parameters and immunohistochemical indicators were determined using Spearman's test, and receiver operating characteristic (ROC) curves were constructed to assess the apparent diffusion coefficient (ADC), mean diffusivity (MD), and mean kurtosis (MK) in predicting the pathologic complete response (PCR).

Results: Correlations were observed between MK values and hormone receptor (HR) expression (oestrogen receptor (ER): r = 0.315 and progesterone receptor (PR): r = 0.268). The parameters ADC_(0,1000), MK, and MD all showed correlations with Ki67 expression (r = 0.276, 0.316 and - 0.224, respectively). ER and Ki67 expression and the parameters MD and MK were significantly different between the PCR and non-PCR groups (AUC = 0.783, 0.688, 0.649 and 0.684, respectively). After splitting patients into subgroups, no significant differences were observed between the PCR and non-PCR groups with human epidermal growth factor receptor 2 (HER2) + and triple-negative (TN) breast cancer. However, we were surprised to find that ADC_{(0, 1000)}, MD, and MK were significantly different between different remission groups with HR+/HER2+ subtypes, and the AUCs of each parameter reached 0.794, 0.825, and 0.712, respectively.

Conclusion: MK was correlated with HR expression. ADC_{(0, 1000)} and DKI were correlated with Ki67 expression. ADC_{(0, 1000)} and the non-Gaussian diffusion model are suitable for predicting PCR in patients with HR+/HER2+ breast cancer before NAC.

Keywords: Breast cancer; Diffusion kurtosis imaging; Diffusion weighted imaging; Neoadjuvant chemotherapy.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms* / pathology
Diffusion Magnetic Resonance Imaging / methods
Diffusion Tensor Imaging
Female
Humans
Neoadjuvant Therapy
Retrospective Studies