Diagnostic performance of whole-lesion apparent diffusion coefficient histogram analysis metrics for differentiating benign and malignant breast lesions: a systematic review and diagnostic meta-analysis

Abstract

Background Although whole-lesion apparent diffusion coefficient (ADC) histogram has been increasingly used for breast lesions, it has not been routinely used in clinical practice as an emergent promising imaging tool. Purpose To evaluate the performance of whole-lesion ADC histogram analysis metrics for differentiating benign and malignant breast lesions. Material and Methods A systematic PubMed/EMBASE/Cochrane electronic database search was performed for original diagnostic studies from 1 January 1970 to 2 January 2019. Summary estimates of diagnostic accuracy were generated and meta-regression was performed to explore sources of heterogeneity according to study and magnetic resonance imaging characteristics. Results Five original articles involving 493 patients were included in the meta-analysis. The pooled sensitivity and specificity of whole-lesion ADC histogram analysis were 0.85 (95% confidence interval [CI] = 0.81–0.89) and 0.79 (95% CI = 0.72–0.84) for distinguishing benign and malignant breast lesions, respectively. The area under the curve (AUC) was 0.9178. No publication bias was detected ( P = 0.51). In subgroup analysis, the summary sensitivity and specificity of 50th percentile ADC value were 0.81 (95% CI = 0.71–0.88) and 0.86 (95% CI = 0.74–0.94), respectively. Meta-regression analysis indicated no covariates were sources of heterogeneity ( P > 0.05). Conclusion Whole-lesion ADC histogram analysis demonstrated good diagnostic performance for differentiating between benign and malignant breast lesions, with 50th percentile ADC value showing higher diagnostic accuracy than other histogram parameters. Given the limited number of studies included in the analysis, the findings from our meta-analysis will need further confirmation in future research.

Meme manyetik rezonans görüntülemede malign ve benign lezyonların ayrımında histogram analizi: ön çalışma

“…A meta-analysis showed that apparent diffusion coefficient (ADC) histogram analysis has 85% sensitivity and 79% specificity in the accurate differentiation of malignant and benign breast lesions, as well as a good diagnostic performance. The same meta-analysis concluded that the 50 th percentile had the greatest accuracy among histogram parameters 20 .…”

Diagnostic value of texture analysis of apparent diffusion coefficient maps for differentiating fat-poor angiomyolipoma from non-clear-cell renal cell carcinoma

“…Although the usefulness of the ADC value as an imaging biomarker has been reported in various malignancies, ADC values are affected by several image-dependent factors, including differences in gradient, coil, pulse-sequence system, and acquisition parameters [17]. The usefulness of skewness and kurtosis, which are less affected by these settings in ADC-related factors, obtained using histogram analysis is being investigated [18]. In this study, the diagnostic model using ADC map-based texture features showed high diagnostic performance comparable to intracross validation, unlike the mean ADC value alone, despite the differences between the two patient cohorts and MRI machines.…”

The development of breast radiology: the Acta Radiologica perspective

“…The usefulness of diffusion-weighted imaging in breast MRI has been an area of intensive investigations lately (75,76) as well as the role of background parenchymal enhancement as an imaging biomarker for breast cancer risk (77) (Figure 2). DCE-MRI has, in many settings, an important role in preoperative staging (78).…”