Performance of diffusion-weighted imaging for the diagnosis of parotid gland malignancies: A meta-analysis

Abstract

Purpose: This study aimed to assess the diagnostic performance of diffusion-weighted imaging (DWI) for parotid gland malignancies.

Methods: Four databases (PubMed, the Cochrane Library, Embase, and Web of Science) were searched systematically and retrospectively by two researchers until May 18, 2020. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to pool the sensitivity and specificity data for the apparent diffusion coefficient (ADC). Summary receiver operating characteristic curve was constructed, and the area under the curve (AUC) was calculated. The positive (LR+) and negative likelihood ratios (LR-) were also calculated. Subgroup and meta-regression analyses were performed to evaluate heterogeneity within studies.

Results: Sixteen studies involving 1004 patients were included. The pooled sensitivity, specificity, and AUC for the ADC to distinguish malignant from begin parotid lesions were 89 %, 76 %, and 0.91, respectively. The LR + was 3.7 and LR- was 0.15, respectively. Subgroup analyses revealed that the applied cut-off b values and study size were sources of heterogeneity for the ADC. There were publication bias concerns.

Conclusions: Our meta-analysis suggests that the ADC value provides excellent sensitivity and moderate specificity for the diagnosis of malignant lesions in the parotid gland. However, substantial heterogeneity was found. Therefore, additional larger, prospective studies in combination with standard techniques focusing on parotid tumors should be conducted to determine the true performance of DWI for the differential diagnosis of parotid lesions.

Keywords: Apparent diffusion coefficient; Diffusion weighted imaging; Meta-Analysis; Parotid malignances.