The added value of qualitative and quantitative diffusion-weighted magnetic resonance imaging (DW-MRI) in differentiating benign from malignant breast lesions

Accuracy of multiparametric MRI in distinguishing the breast malignant lesions from benign lesions: a meta-analysis

BACKGROUND

The sensitivity of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for detecting breast cancer was high and the specificity was relatively low. However, diffusion-weighted imaging (DWI) has a high specificity in the diagnosis of malignant lesions.

PURPOSE

To evaluate the accuracy of the multiparametric MRI (mp-MRI) in distinguishing the breast malignant lesions from the benign lesions.

MATERIAL AND METHODS

A comprehensive search of the PubMed, Embase, and Cochrane Library electronic databases was conducted up to March 2020. Data were analyzed for the following indexes: pooled sensitivity and specificity; positive likelihood ratio; negative likelihood ratio; diagnostic odds ratio; and the area under the curve.

RESULTS

A total of 2356 patients with 1604 malignant and 967 benign breast lesions were included from 22 studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve for mp-MRI were 0.93, 0.85, 6.3, 0.08, 81, and 0.96, respectively. The pooled sensitivity, specificity, and area under the curve for DCE-MRI alone were 0.95, 0.71, and 0.92, respectively. The pooled sensitivity, specificity, and area under the curve for DWI alone were 0.88, 0.84, and 0.93, respectively.

CONCLUSION

The mp-MRI did not improve the sensitivity but increased the specificity for the diagnosis of breast malignant lesions.

Role of diffusion-weighted magnetic resonance imaging in assessment of mammographically detected asymmetric densities

Background

Asymmetric breast density is a potentially perplexing finding; it may be due to normal hormonal variation of the parenchymal pattern and summation artifact or it may indicate an underlying true pathology. The current study aimed to identify the role of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) values in the assessment of breast asymmetries.

Results

Fifty breast lesions were detected corresponding to the mammographic asymmetry. There were 35 (70%) benign lesions and 15 (30%) malignant lesions. The mean ADC value was 1.59 ± 0.4 × 10–3 mm2/s for benign lesions and 0.82 ± 0.3 × 10–3 mm2/s for malignant lesions. The ADC cutoff value to differentiate between benign and malignant lesions was 1.10 × 10–3 mm2/s with sensitivity 80%, specificity 88.6%, positive predictive value 75%, negative predictive value 91%, and accuracy 86%. Best results were achieved by implementation of the combined DCE-MRI and DWI protocol, with sensitivity 93.3%, specificity 94.3%, positive predictive value 87.5%, negative predictive value 97.1%, and accuracy 94%.

Conclusion

Dynamic contrast-enhanced MRI (DCE-MRI) was the most sensitive method for the detection of the underlying malignant pathology of breast asymmetries. However, it provided a limited specificity that may cause improper final BIRADS classification and may increase the unnecessary invasive procedures. DWI was used as an adjunctive method to DCE-MRI that maintained high sensitivity and increased specificity and the overall diagnostic accuracy of breast MRI examination. Best results can be achieved by the combined protocol of DCE-MRI and DWI.

Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis

BACKGROUND

Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC).

METHODS AND FINDINGS

In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ≥ 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95).

CONCLUSIONS

None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.