Is simultaneous multi-slice readout-segmented echo-planar imaging valuable for predicting molecular subtypes of breast cancer?

Abstract

PurposeTo investigate the feasibility of simultaneous multi-slice readout-segmented diffusion-weighted echo-planar imaging (SMS rs-EPI DWI) in predicting invasive breast cancer molecular subtypes using whole-tumor histogram and texture analyses. MethodsIn our retrospective study, 125 patients (mean age, 52.81 ± 12.01 years; range, 24–84 years) with single invasive breast cancer who underwent preoperative MRI with SMS rs-EPI DWI and surgery at our institution were included. Two radiologists independently performed whole-tumor histogram and texture analyses on the apparentdiffusioncoefficient (ADC) map of SMS rs-EPI DWI (TR, 3800.0 ms; TE 90.0 ms; field of view, 340 mm × 206 mm; in-plane matrix, 244 × 148; section thickness, 5 mm; readout segments, 5, b = 0, 800 s/mm2; scan time, 3 mins; slice acceleration factor, 2). The Mann–Whitney U test or Kruskal-Wallis test were used to compare histogram and texture parameters to assess their potential in differentiating molecular subtypes of breast cancer and predicting axillary lymph node status. Receiver operating characteristic (ROC) curves were generated for parameters with significant differences, and the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. ResultsCompared to luminal A breast cancer, the HER2-positive breast cancer subtype showed higher ADC_95th percentile values (p = 0.016). In addition, HER2-positive breast cancer yielded significantly higher ADC_mean (p = 0.025), ADC_median (p = 0.025), and ADC_5th percentile (p = 0.041) values than luminal B breast cancer. The ADC_skewness value was higher for triple-negative breast cancer (TNBC) than Luminal A breast cancer (p = 0.021). The difference in ADC_mean, ADC_median, ADC_5th percentile and ADC_95th percentile values between the HER2-positive breast cancer and luminal types was statistically significant, with a combined AUC for these parameters of 0.762 (sensitivity 72.41%, specificity 75.00%, PPV 27.27 %, and NPV 95.45 %). The ADC_skewness value for TNBC was higher than for luminal types (p = 0.012) and yielded an AUC value of 0.688 (sensitivity 96.15%, specificity 36.78%, PPV 31.25%, and NPV 96.97 %). Additionally, significantly higher ADC_skewness and ADC_95th percentile values (p = 0.003, 0.002, respectively) were reported for non-luminal types than luminal types yielding a combined AUC value of 0.712 (sensitivity 92.11%, and specificity 50.23%, PPV 41.18%, and NPV 92.50%). The AUC value for ADC_5th percentile for axillary lymph node status prediction was 0.659 (sensitivity 65.38%, specificity of 64.86%). ConclusionsThe whole-tumor histogram and texture analyses parameters based on SMS rs-EPI DWI may provide biological information on aggressive molecular subtypes of breast cancer. In addition, ADC_5th percentile values were significantly different between lymph node-positive and lymph node-negative breast cancer.