Synopsis

The quantitative parameters derived from ultrafast dynamic contrast enhanced (UF-DCE) breast MRI using DISCO were analyzed for the assessment of possible utility in the differentiation between subcentimeter invasive carcinoma and benign lesions. Of all these parameters (MS, CER, IAUGC, BAT and Ktrans), BAT was the only parameter that predicted subcentimeter invasive carcinoma. We believe the significantly shorter BAT for subcentimeter invasive carcinomas is congruent with the known pathophysiology of cancer and may reflect its increased vascularity or shunt formation. BAT can be a complementary parameter to conventional steady-state DCE MRI, which could further stratify subcentimeter BI-RADS 4 and 5 lesions.

Introduction

Ultrafast dynamic contrast enhanced (UF-DCE) breast MRI using differential sub-sampling with cartesian ordering (DISCO), characterized by high temporal and spatial resolution, enables image acquisition at multiple time points starting simultaneously with the beginning of contrast injection. Quantitative parameters calculated from these images reflect contrast inflow effects and are known to be useful for the differentiation between cancers and benign lesions^1-6.

Breast MRI has the highest sensitivity for breast cancer detection. However, it often depicts subcentimeter lesions that result in biopsy recommendations (BI-RADS 4 and 5) of which the majority are benign, resulting in low breast MRI positive predictive value and specificity^7-9. This study aims to evaluate the quantitative parameters derived from UF-DCE MRI in differentiating between subcentimeter BI-RADS 4 and 5 invasive carcinomas and benign lesions.

Methods

This retrospective Health Insurance Portability and Accountability Act (HIPAA)-compliant study received institutional review board approval. We identified female patients between February-August 2017 with a: 1) UF-DCE MRI with DISCO as part of hybrid protocol with conventional steady-state DCE MRI (Figure 1) and 2) biopsy proven BI-RADS 4, 5 or 6 lesion. BI-RADS 4 and 5 subcentimeter invasive carcinomas and benign lesion were identified as those with a volume<0.523 cm³ (corresponding to a sphere with a diameter of 1cm) using 3D volumetric segmentation. All biopsy-proven BI-RADS 4, 5 and 6 invasive carcinomas and benign lesions were also analysed for a comparison purpose (Figure 2).

All MRI examinations were performed with a 3.0T MRI system (Discovery 750, GE Medical Systems, Waukesha, WI) with a dedicated 16 or 8 channel breast coil. All DCE images were acquired in the axial orientation. After scanning the pre phase for conventional DCE MRI, UF-DCE MR images were acquired continuously 10-15 times during the first 60 sec (temporal resolution of 3.5-6 sec) starting simultaneously with the beginning of contrast injection of 0.1 mmol gadobutrol per kilogram body weight (Gadavist; Bayer Healthcare Pharmaceuticals Inc., Whippany, NJ) at a rate of 2ml/sec with an automatic injector. Following these, conventional 3-phase DCE MR images were acquired continuously three times. The parameters were as follows; UF-DCE MRI using DISCO (TR/TE/FA=3.8/1.7/10°; Reconstructed Matrix, 256×256; FOV, 1.6 × 1.6mm; thickness, 1.6mm; temporal resolution, 3.5-6 sec); conventional DCE MRI (TR/TE/FA=7.9/4.3/12°; Reconstructed Matrix, 512×512; FOV, 1.1 × 1.1mm; thickness, 1.1mm; temporal resolution, ~120 sec).

Using GenIQ Software (GE Healthcare), 3D volumetric segmentation was manually performed for each lesion on the 1st post contrast conventional DCE images and cloned to UF-DCE MRI. Maximum slope (MS), contrast enhancement ratio (CER), initial area under the gadolinium curve (IAUGC), bolus arrival time (BAT) and Ktrans were calculated for UF-DCE MRI. Maximum slope of increase (MSI), signal enhancement ratio (SER), and positive enhancement integral (PEI) were calculated for conventional DCE MRI.

Wilcoxon signed rank sum test and t-tests was used to compare these parameters between invasive carcinomas and benign lesions. To evaluate the diagnostic accuracy of each parameter to predict invasive carcinoma, areas under the receiver operating characteristic (ROC) curve (AUC) were calculated. AUC values were evaluated as follows; 1.0>AUC≥0.9, high accuracy; 0.9>AUC≥0.7, moderate accuracy; 0.7>AUC>0.5, low accuracy. P values less than 0.05 were considered statistically significant. All analyses were performed using SAS 9.4 (The SAS Institute, Cary, NC).

Results

In total, 190 BI-RADS 4,5 or 6 MRI examinations were included and 237 lesions (invasive carcinomas, 141; benign lesions, 96) were identified (cohort A). Of these, there were 103(43.5%) BI-RADS 4 and 5 subcentimeter lesions, 21 invasive carcinomas and 82 benign lesions (cohort B) (Figure 2).

Results of the analysis are shown in Figure 3. In both cohorts (A and B), all the parameters presented significant difference between invasive carcinomas and benign lesions. The AUC evaluation for BI-RADS 4 and 5 subcentimeter lesions (cohort B) demonstrated that BAT (UF-DCE MRI parameter) was the only parameter showing AUC>0.7. When all biopsy-proven lesions were included (cohort A), all the UF-DCE MRI parameters presented AUC>0.7 with higher accuracy than SER (conventional DCE MRI parameter) showing AUC=0.763. Representative two cases are shown in Figure 4-5.

Discussion

Conclusion

Acknowledgements

We thank Ms. Maggie Fung, GE Healthcare for her technical support for GenIQ.

This work was supported by NCI P30 Cancer Center Support Grant (CCSG) (P30 CA008748)

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