Threshold Isocontouring on High b-Value Diffusion-Weighted Images in Magnetic Resonance Mammography

Differentiating Benign and Malignant Breast Lesions in Diffusion Kurtosis MRI: Does the Averaging Procedure Matter?

BACKGROUND

Diffusion kurtosis imaging (DKI) is used to differentiate between benign and malignant breast lesions. DKI fits are performed either on voxel-by-voxel basis or using volume-averaged signal.

PURPOSE

Investigate and compare DKI parameters' diagnostic performance using voxel-by-voxel and volume-averaged signal fit approach.

STUDY TYPE

Retrospective.

STUDY POPULATION

A total of 104 patients, aged 24.1-86.4 years.

FIELD STRENGTH/SEQUENCE

A 3 T Spin-echo planar diffusion-weighted sequence with b-values: 50 s/mm² , 750 s/mm² , and 1500 s/mm² . Dynamic contrast enhanced (DCE) sequence.

ASSESSMENT

Lesions were manually segmented by M.P. under supervision of S.O. (2 and 5 years of experience in breast MRI). DKI fits were performed on voxel-by-voxel basis and with volume-averaged signal. Diagnostic performance of DKI parameters D K (kurtosis corrected diffusion coefficient) and kurtosis K was compared between both approaches.

STATISTICAL TESTS

Receiver operating characteristics analysis and area under the curve (AUC) values were computed. Wilcoxon rank sum and Students t-test tested DKI parameters for significant (P <0.05) difference between benign and malignant lesions. DeLong test was used to test the DKI parameter performance for significant fit approach dependency. Correlation between parameters of the two approaches was determined by Pearson correlation coefficient.

RESULTS

DKI parameters were significantly different between benign and malignant lesions for both fit approaches. Median benign vs. malignant values for voxel-by-voxel and volume-averaged approach were 2.00 vs. 1.28 ( D K in μm² /msec), 2.03 vs. 1.26 ( D K in μm² /msec), 0.54 vs. 0.90 ( K ), 0.55 vs. 0.99 ( K ). AUC for voxel-by-voxel and volume-averaged fit were 0.9494 and 0.9508 ( D K ); 0.9175 and 0.9298 ( K ). For both, AUC did not differ significantly (P = 0.20). Correlation of values between the two approaches was very high (r = 0.99 for D K and r = 0.97 for K ).

DATA CONCLUSION

Voxel-by-voxel and volume-averaged signal fit approach are equally well suited for differentiating between benign and malignant breast lesions in DKI.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Ultra-High b-Value Diffusion-Weighted Imaging-Based Abbreviated Protocols for Breast Cancer Detection

OBJECTIVES

Contrast-enhanced (CE) magnetic resonance imaging (MRI) is the most effective imaging modality for breast cancer detection. A contrast agent-free examination technique would be desirable for breast MRI screening. The purpose of this study was to evaluate the capability to detect and characterize suspicious breast lesions with an abbreviated, non-contrast-enhanced MRI protocol featuring ultra-high b-value diffusion-weighted imaging (DWI) compared with CE images.

MATERIALS AND METHODS

The institutional review board-approved prospective study included 127 female subjects with different clinical indications for breast MRI. Magnetic resonance imaging examinations included DWI sequences with b-values of 1500 s/mm2 (b1500) and 2500 s/mm2 (b2500), native T1- and T2-weighted images, and CE sequences at 1.5 T and 3 T scanners. Two reading rounds were performed, including either the b1500 or the b2500 DWI in consecutive assessment steps: (A) maximum intensity projections (MIPs) of DWI, (B) DWI and apparent diffusion coefficient maps, (C) as (B) but with additional native T1- and T2-weighted images, and (D) as (C) but with additional CE images (full-length protocol). Two readers independently determined the presence of a suspicious lesion. Histological confirmation was obtained for conspicuous lesions, whereas the full MRI data set was obtained for inconspicuous and clearly benign lesions. Statistical analysis included calculation of diagnostic accuracy and interrater agreement via the intraclass correlation coefficient.

RESULTS

The cohort comprised 116 cases with BI-RADS 1 findings and 138 cases with BI-RADS ≥2 findings, including 38 histologically confirmed malignancies. For (A), breasts without pathological findings could be recognized with high diagnostic accuracy (negative predictive value, ≥97.0%; sensitivity, ≥92.1% for both readers), but with a limited specificity (≥58.3%; positive predictive value, ≥28.6%). Within the native readings, approach (C) with b2500 performed best (negative predictive value, 99.5%; sensitivity, 97.4%; specificity, 88.4%). The intraclass correlation coefficient was between 0.683 (MIP b1500) and 0.996 (full protocol).

CONCLUSIONS

A native abbreviated breast MRI protocol with advanced high b-value DWI might allow nearly equivalent diagnostic accuracy as CE breast MRI and seems to be well suited for lesion detection purposes.