Diffusion‐weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping as a quantitative imaging biomarker for prediction of immunohistochemical receptor status, proliferation rate, and molecular subtypes of breast cancer

Abstract

Background Diffusion‐weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping is one of the most useful additional MRI parameters to improve diagnostic accuracy and is now often used in a multiparameric imaging setting for breast tumor detection and characterization. Purpose To evaluate whether different ADC metrics can also be used for prediction of receptor status, proliferation rate, and molecular subtype in invasive breast cancer. Study Type Retrospective. Subjects In all, 107 patients with invasive breast cancer met the inclusion criteria (mean age 57 years, range 32–87) and underwent multiparametric breast MRI. Field Strength/Sequence 3 T, readout‐segmented echo planar imaging (rsEPI) with IR fat suppression, dynamic contrast‐enhanced (DCE) T1‐weighted imaging, T2‐weighted turbo‐spin echo (TSE) with fatsat. Assessment Two readers independently drew a region of interest on ADC maps on the whole tumor (WTu), and on its darkest part (DpTu). Minimum, mean, and maximum ADC values of both WTu and DpTu were compared for receptor status, proliferation rate, and molecular subtypes. Statistical Tests Wilcoxon rank sum, Mann–Whitney U‐tests for associations between radiologic features and histopathology; histogram and q‐q plots, Shapiro–Wilk's test to assess normality, concordance correlation coefficient for precision and accuracy; receiver operating characteristics curve analysis. Results Estrogen receptor (ER) and progesterone receptor (PR) status had significantly different ADC values for both readers. Maximum WTu (P = 0.0004 and 0.0005) and mean WTu (P = 0.0101 and 0.0136) were significantly lower for ER‐positive tumors, while PR‐positive tumors had significantly lower maximum WTu values (P = 0.0089 and 0.0047). Maximum WTu ADC was the only metric that was significantly different for molecular subtypes for both readers (P = 0.0100 and 0.0132) and enabled differentiation of luminal tumors from nonluminal (P = 0.0068 and 0.0069) with an area under the curve of 0.685 for both readers. Data Conclusion Maximum WTu ADC values may be used to differentiate luminal from other molecular subtypes of breast cancer. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:836–846.

Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging with Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers

“…In our study, the results obtained from histogram analysis of ADC were not able to differentiate molecular subtypes. A previous study demonstrated that maximum values of ADC could be used to differentiate molecular subtypes of breast cancer [26]. Although the software used in our study did not specifically evaluate maximum ADC values, the mean, Perc10, Perc50, and Perc90 results obtained were lower for luminal cancers in comparison with other subtypes, but this difference was not statistically significant.…”

“…The assessment of receptor status using different ADC metrics has led to conflicting results in the literature [16, 24, 26–29]. While some studies demonstrated lower ADC values for ER and PR positive tumors and higher for HER2 positive lesions, others did not find any significant associations between ADC measurements and receptor status.…”

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

“…40 Lower ADC values in estrogen receptor (ER) or progesterone receptor (PgR) positive tumors have already been reported in many papers. [42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61] Kawashima et al 53 demonstrated significantly lower D and ADC values in luminal B compared with luminal A tumors. Iima et al 58 reported significantly lower sADC 200-1500 values in PgR expression.…”

Peritumor to tumor apparent diffusion coefficient ratio is associated with biologically more aggressive breast cancer features and correlates with the prognostication tools

“…Diffusion-weighted imaging (DWI) is a key noninvasive functional imaging technique, which exploits the random motion of water molecules, and is sensitive to tissue microstructure and cellularity. The apparent diffusion coefficient (ADC) is a quantitative measure of diffusion that is increasingly used to characterize and discriminate lesions [10]. Although some challenges to improve the generalizability and reproducibility of breast DWI [11], the limited reproducibility of ADC across different imaging manufacturers, field strengths, and imaging centers is contentious [12,13].…”