High-Resolution DWI with Simultaneous Multi-Slice Readout-Segmented Echo Planar Imaging for the Evaluation of Malignant and Benign Breast Lesions

To investigate the feasibility and effectiveness of high-resolution readout-segmented echo planar imaging (rs-EPI), diffusion-weighted imaging (DWI) is used simultaneously with multi-slice (SMS) imaging (SMS rs-EPI) for the differentiation of breast malignant and benign lesions in comparison to conventional rs-EPI on a 3T MR scanner. A total of 102 patients with 113 breast lesions underwent bilateral breast MRI using a prototype SMS rs-EPI sequence and a conventional rs-EPI sequence. Subjective image quality was assessed using a 5-point Likert scale (1 = poor, 5 = excellent). Signal-to-noise ratio (SNR), lesion contrast-to-noise ratio (CNR) and apparent diffusion coefficients (ADC) value of the lesion were measured for comparison. Receiver operating characteristic curve analysis was performed to evaluate the diagnosis performance of ADC, and the corresponding area under curve (AUC) was calculated. The image quality scores in anatomic distortion, lesion conspicuity, sharpness of anatomical details and overall image quality of SMS rs-EPI were significantly higher than those of conventional rs-EPI. CNR was enhanced in the high-resolution SMS rs-EPI acquisition (6.48 ± 1.71 vs. 4.23 ± 1.49; p < 0.001). The mean ADC value was comparable in SMS rs-EPI and conventional rs-EPI (benign 1.45 × 10−3 vs. 1.43 × 10−3 mm2/s, p = 0.702; malignant 0.91 × 10−3 vs. 0.89 × 10−3 mm2/s, p = 0.076). The AUC was 0.957 in SMS rs-EPI and 0.983 in conventional rs-EPI. SMS rs-EPI technique allows for higher spatial resolution and slight reduction of scan time in comparison to conventional rs-EPI, which has potential for better differentiation between malignant and benign lesions of the breast.

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Improving the image quality of DWI in breast cancer: comparison of multi-shot DWI using multiplexed sensitivity encoding to conventional single-shot echo-planar imaging DWI

British Journal of Radiology ◽

10.1259/bjr.20200427 ◽

2020 ◽

pp. 20200427

Author(s):

Gabrielle C Baxter ◽

Andrew J Patterson ◽

Ramona Woitek ◽

Iris Allajbeu ◽

Martin J Graves ◽

...

Keyword(s):

Breast Cancer ◽

Image Quality ◽

Coefficient Of Variation ◽

Echo Planar Imaging ◽

Single Shot ◽

Planar Imaging ◽

Benign Lesions ◽

Sensitivity Encoding ◽

Echo Planar

Objective: To compare diffusion-weighted images (DWI) acquired using single-shot echo-planar imaging (ss-EPI) and multiplexed sensitivity encoding (MUSE) in breast cancer. Methods 20 females with pathologically confirmed breast cancer (age 51 ± 12 years) were imaged with ss-EPI-DWI and MUSE-DWI. ADC, normalised ADC (nADC), blur and distortion metrics and qualitative image quality scores were compared. The Crété-Roffet and Mattes mutual information metrics were used to evaluate blurring and distortion, respectively. In a breast phantom, six permutations of MUSE-DWI with varying parallel acceleration factor and number of shots were compared. Differences in ADC and nADC were compared using the coefficient of variation in the phantom and a paired t-test in patients. Differences in blur, distortion and qualitative metrics were analysed using a Wilcoxon signed-rank test. Results: There was a low coefficient of variation (<2%) in ADC between ss-EPI-DWI and all MUSE-DWI permutations acquired using the phantom. 22 malignant and three benign lesions were identified in 20 patients. ADC values measured using MUSE were significantly lower compared to ss-EPI for malignant but not benign lesions (p < 0.001, p = 0.21). nADC values were not significantly different (p = 0.62, p = 0.28). Blurring and distortion improved with number of shots and acceleration factor, and significantly improved with MUSE in patients (p < 0.001, p = 0.002). Qualitatively, image quality improved using MUSE. Conclusion: MUSE improves the image quality of breast DWI compared to ss-EPI. Advances in knowledge: MUSE-DWI has superior image quality and reduced blurring and distortion compared to ss-EPI-DWI in breast cancer.

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