Role of the Intravoxel Incoherent Motion Diffusion Weighted Imaging in the Pre-treatment Prediction and Early Response Monitoring to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer

Abstract

The aim of this study was to explore whether intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) can probe pre-treatment differences or monitor early response in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC).Thirty-six patients with locally advanced breast cancer were imaged using multiple-b DWI with 12 b values ranging from 0 to 1000 s/mm2 at the baseline, and 28 patients were repeatedly scanned after the second cycle of NAC. Subjects were divided into pathologic complete response (pCR) and nonpathologic complete response (non-pCR) groups according to the surgical pathologic specimen. Parameters (D, D∗, f, maximum diameter [MD] and volume [V]) before and after 2 cycles of NAC and their corresponding change (Δparameter) between pCR and non-pCR groups were compared using the Student t test or nonparametric test. The diagnostic performance of different parameters was judged by the receiver-operating characteristic curve analysis.Before NAC, the f value of pCR group was significantly higher than that of non-pCR (32.40% vs 24.40%, P = 0.048). At the end of the second cycle of NAC, the D value was significantly higher and the f value was significantly lower in pCR than that in non-pCR (P = 0.001; P = 0.015, respectively), whereas the D∗ value and V of the pCR group was slightly lower than that of the non-pCR group (P = 0.507; P = 0.676, respectively). ΔD was higher in pCR (−0.45 × 10–3 mm2/s) than that in non-pCR (−0.07 × 10−3 mm2/s) after 2 cycles of NAC (P < 0.001). Δf value in the pCR group was significantly higher than that in the non-pCR group (17.30% vs 5.30%, P = 0.001). There was no significant difference in ΔD∗ between the pCR and non-pCR group (P = 0.456). The prediction performance of ΔD value was the highest (AUC [area under the curve] = 0.924, 95% CI [95% confidence interval] = 0.759–0.990). When the optimal cut-off was set at −0.163 × 10−3 mm2/s, the values for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were up to 100% (95% CI = 66.4–100), 73.7% (95% CI = 48.8–90.9), 64.3% (95% CI = 35.6–86.0), and 100% (95% CI = 73.2–99.3), respectively.IVIM-derived parameters, especially the D and f value, showed potential value in the pre-treatment prediction and early response monitoring to NAC in locally advanced breast cancer. ΔD value had the best prediction performance for pathologic response after NAC.

Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial

“…; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; manuscript final version approval, all authors; agrees to ensure any questions related to the work are appropriately resolved, all authors; literature research, S. from 0 to 800 sec/mm 2 , which likely included contributions from microvasculature (more prominent at low b values , 200 sec/ mm 2 ) and limited the sensitivity for identifying microstructural changes. Advanced DW MRI modeling techniques may better depict therapeutic effects, including intravoxel incoherent motion modeling to additionally quantify perfusion and kurtosis or stretched-exponential modeling to assess microstructural complexity (31,32). ROIs were manually defined; automated tumor segmentation approaches may reduce interoperator variability and improve accuracy for serial measures (33,34).…”

Intravoxel incoherent motion (IVIM) histogram biomarkers for prediction of neoadjuvant treatment response in breast cancer patients

“…Furthermore, histogram analysis of the spatial distribution of IVIM parameters can provide additional markers (e.g. skewness and kurtosis) for characterization of the heterogeneity of the tumor microenvironment [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] .…”

Potentialities of multi-b-values diffusion-weighted imaging for predicting efficacy of concurrent chemoradiotherapy in cervical cancer patients

“…During our research, we found that this might be caused by the poor repeatability and large uctuation of D fast . Che et.al also reported this phenomenon [12] . Andreou et al…”

“…Stretched exponential model (SEM) offers information on heterogeneity of intravoxel diffusion rates and the distributed diffusion effect, thus providing complementary information of tissue property [3] . MEM, BEM and SEM DWI models have already been applied as imaging biomarker to predict and assess treatment response in rectal cancer, head and neck squamous cell carcinoma, breast cancer, prostate cancer and esophageal squamous cell carcinoma [4][5][6][7][8][9][10][11][12][13][14][15] .…”