Imaging diagnosis for anterior talofibular ligament injury: a systemic review with meta-analysis.

A definite diagnosis of ankle ligament injury is crucial, and many imaging examinations can be used. This review systematically analyzed the effectiveness of various examination methods in the diagnosis of anterior talofibular ligament (ATFL) injuries. Three English databases (PubMed, Embase, and Cochrane Library) and three Chinese databases (CNKI, VIP Database, and Wanfang Database) were searched and relevant studies were summarized. A total of 25 randomized controlled trials met the selection criteria, including six, 16, and three studies recruiting patients with acute, chronic, and both acute and chronic ATFL injuries, respectively. A total of 1409 participants were included. The pooled sensitivity rates of acute ATFL injuries were 82.1% (77.1%-86.5%) by magnetic resonance imaging (MRI) and 88.6% (82.0%-93.5%) by ultrasonography (US). The pooled sensitivity rates of chronic ATFL injuries were 86.3% (82.5%-89.5%) by MRI, 98.7% (95.3%-99.8%) by US, 74.4% (63.6%-83.4%) by stress radiography, and 100% (87.7%-100.0%) for MR arthrography. The pooled specificity rates of acute ATFL injuries were 37.8% (29.1%-47.2%) by MRI and 90.3% (80.1%-96.4%) by US. The pooled specificity rates of chronic ATFL injuries were 86.8% (81.3%-91.2%) by MRI, 94.0% (85.4%-98.3%) for US, 89.4% (76.9%- 96.5%) by stress radiography and 100% (54.1%-100.0%) by MR arthrography. In conclusion, US may be a valuable imaging technique with high sensitivity for diagnosing chronic lateral ankle ligament injuries.

Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis.

PURPOSE: To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC). METHOD: A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed. RESULTS: Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I2 = 86 %) and 85 % (95 % CI, 79 %-90 %, I2 = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I2 = 45 %), 88 % (95 % CI, 77 %-94 %, I2 = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I2 = 87 %), 69 % (95 % CI, 52 %-82 %, I2 = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I2 = 79 %), 74 % (95 % CI, 60 %-84 %, I2 = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P＜0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P＜0.01), and thickness (sensitivity, P＜0.01; specificity, P = 0.01) were sources of ADC heterogeneity. CONCLUSIONS: DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.

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

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.