Diagnostic value of diffusion‑weighted imaging‑derived apparent diffusion coefficient and its association with histological prognostic factors in breast cancer

Ren,Congcong; Zou,Yu; Zhang,Xiaodan; Li,Kui

doi:10.3892/ol.2019.10651

Diagnostic value of diffusion‑weighted imaging‑derived apparent diffusion coefficient and its association with histological prognostic factors in breast cancer

Authors:
- Congcong Ren
- Yu Zou
- Xiaodan Zhang
- Kui Li
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Affiliations: Department of Radiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310006, P.R. China
Published online on: July 22, 2019 https://doi.org/10.3892/ol.2019.10651
Pages: 3295-3303
Copyright : © Ren et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

Diffusion‑weighted imaging (DWI) has been proven to be effective in detecting breast malignancies and has been widely implemented for breast imaging. However, the exact association between certain DWI biomarkers and well‑known prognostic factors remains to be fully elucidated. By studying the association between the apparent diffusion coefficient (ADC) and prognostic factors, the present study aimed to explore the diagnostic value and prognostic potential of the ADC in breast lesions. The study included 539 female subjects with histopathologically confirmed breast lesions who underwent DWI of the breast tissue. The diagnoses comprised 307 subjects with malignant breast tumors and 232 with benign breast tumors. The maximum ADC and mean ADC (ADCmean) values of the breast lesions were calculated. For malignant tumors, the association between ADC and major prognostic factors, including histological grade, nuclear grade and lymph node status, as well as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER‑2) and proliferation marker protein Ki‑67.(Ki‑67) status, were evaluated. The ADCmean demonstrated the best diagnostic performance in distinguishing between malignant and benign lesions. With the optimum cut‑off value at 1.30x10‑3 mm2/sec, ADCmean had a sensitivity and specificity of 84.1 and 90.2%, respectively. In those patients with malignant breast lesions, a decreased ADC was associated with breast lesions with high nuclear and histological grades, and lymph node‑positive, ER‑negative, PR‑negative and HER‑2‑negative status, and Ki‑67 ≥14%. In conclusion, the ADC is a useful imaging biomarker for differentiating between benign and malignant breast tumors. The marked association between the ADC and prognostic factors also demonstrated its value in evaluating the malignancy of breast lesions.

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