Increasing numbers of incidental pancreatic lesions are being detected each year. Accurate characterisation of pancreatic lesions into benign, precancerous, and cancer masses is crucial in deciding whether to use treatment or surveillance. Distinguishing benign lesions from precancerous and cancerous lesions can prevent patients from undergoing unnecessary major surgery. Despite the importance of accurately classifying pancreatic lesions, there is no clear algorithm for management of focal pancreatic lesions.

To determine and compare the diagnostic accuracy of various imaging modalities in detecting cancerous and precancerous lesions in people with focal pancreatic lesions.

We searched the CENTRAL, MEDLINE, Embase, and Science Citation Index until 19 July 2016. We searched the references of included studies to identify further studies. We did not restrict studies based on language or publication status, or whether data were collected prospectively or retrospectively.

We planned to include studies reporting cross-sectional information on the index test (CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), EUS (endoscopic ultrasound), EUS elastography, and EUS-guided biopsy or FNA (fine-needle aspiration)) and reference standard (confirmation of the nature of the lesion was obtained by histopathological examination of the entire lesion by surgical excision, or histopathological examination for confirmation of precancer or cancer by biopsy and clinical follow-up of at least six months in people with negative index tests) in people with pancreatic lesions irrespective of language or publication status or whether the data were collected prospectively or retrospectively.

Two review authors independently searched the references to identify relevant studies and extracted the data. We planned to use the bivariate analysis to calculate the summary sensitivity and specificity with their 95% confidence intervals and the hierarchical summary receiver operating characteristic (HSROC) to compare the tests and assess heterogeneity, but used simpler models (such as univariate random-effects model and univariate fixed-effect model) for combining studies when appropriate because of the sparse data. We were unable to compare the diagnostic performance of the tests using formal statistical methods because of sparse data.

We included 54 studies involving a total of 3,196 participants evaluating the diagnostic accuracy of various index tests. In these 54 studies, eight different target conditions were identified with different final diagnoses constituting benign, precancerous, and cancerous lesions. None of the studies was of high methodological quality. None of the comparisons in which single studies were included was of sufficiently high methodological quality to warrant highlighting of the results. For differentiation of cancerous lesions from benign or precancerous lesions, we identified only one study per index test. The second analysis, of studies differentiating cancerous versus benign lesions, provided three tests in which meta-analysis could be performed. The sensitivities and specificities for diagnosing cancer were: EUS-FNA: sensitivity 0.79 (95% confidence interval (CI) 0.07 to 1.00), specificity 1.00 (95% CI 0.91 to 1.00); EUS: sensitivity 0.95 (95% CI 0.84 to 0.99), specificity 0.53 (95% CI 0.31 to 0.74); PET: sensitivity 0.92 (95% CI 0.80 to 0.97), specificity 0.65 (95% CI 0.39 to 0.84). The third analysis, of studies differentiating precancerous or cancerous lesions from benign lesions, only provided one test (EUS-FNA) in which meta-analysis was performed. EUS-FNA had moderate sensitivity for diagnosing precancerous or cancerous lesions (sensitivity 0.73 (95% CI 0.01 to 1.00) and high specificity 0.94 (95% CI 0.15 to 1.00), the extremely wide confidence intervals reflecting the heterogeneity between the studies). The fourth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (dysplasia) provided three tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing invasive carcinoma were: CT: sensitivity 0.72 (95% CI 0.50 to 0.87), specificity 0.92 (95% CI 0.81 to 0.97); EUS: sensitivity 0.78 (95% CI 0.44 to 0.94), specificity 0.91 (95% CI 0.61 to 0.98); EUS-FNA: sensitivity 0.66 (95% CI 0.03 to 0.99), specificity 0.92 (95% CI 0.73 to 0.98). The fifth analysis, of studies differentiating cancerous (high-grade dysplasia or invasive carcinoma) versus precancerous (low- or intermediate-grade dysplasia) provided six tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing cancer (high-grade dysplasia or invasive carcinoma) were: CT: sensitivity 0.87 (95% CI 0.00 to 1.00), specificity 0.96 (95% CI 0.00 to 1.00); EUS: sensitivity 0.86 (95% CI 0.74 to 0.92), specificity 0.91 (95% CI 0.83 to 0.96); EUS-FNA: sensitivity 0.47 (95% CI 0.24 to 0.70), specificity 0.91 (95% CI 0.32 to 1.00); EUS-FNA carcinoembryonic antigen 200 ng/mL: sensitivity 0.58 (95% CI 0.28 to 0.83), specificity 0.51 (95% CI 0.19 to 0.81); MRI: sensitivity 0.69 (95% CI 0.44 to 0.86), specificity 0.93 (95% CI 0.43 to 1.00); PET: sensitivity 0.90 (95% CI 0.79 to 0.96), specificity 0.94 (95% CI 0.81 to 0.99). The sixth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (low-grade dysplasia) provided no tests in which meta-analysis was performed. The seventh analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) provided two tests in which meta-analysis was performed. The sensitivity and specificity for diagnosing cancer were: CT: sensitivity 0.83 (95% CI 0.68 to 0.92), specificity 0.83 (95% CI 0.64 to 0.93) and MRI: sensitivity 0.80 (95% CI 0.58 to 0.92), specificity 0.81 (95% CI 0.53 to 0.95), respectively. The eighth analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) or benign lesions provided no test in which meta-analysis was performed.There were no major alterations in the subgroup analysis of cystic pancreatic focal lesions (42 studies; 2086 participants). None of the included studies evaluated EUS elastography or sequential testing.

We were unable to arrive at any firm conclusions because of the differences in the way that study authors classified focal pancreatic lesions into cancerous, precancerous, and benign lesions; the inclusion of few studies with wide confidence intervals for each comparison; poor methodological quality in the studies; and heterogeneity in the estimates within comparisons.

To investigate the impact of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) in association with a multidisciplinary team evaluation for the detection of gastrointestinal malignancies.

A cohort of 1019 patients with suspected malignant lesions adjacent to the gastrointestinal tract received EUS-FNA after a standardized multidisciplinary team evaluation (MTE) and were divided into 4 groups according to their specific malignant risk score (MRS). Patients with a MRS of 0 (without detectable risk of malignancy) received only EUS without FNA. For patients with a MRS score ranging from 1 (low risk) - through 2 (intermediate risk) - to 3 (high risk), EUS-FNA cytology of the lesion was planned for a different time and was prioritized for those patients at higher risk for cancer. The accuracy, efficiency and quality assessment for the early detection of patients with potentially curable malignant lesions were evaluated for the whole cohort and in the different classes of MRSs. The time to definitive cytological diagnosis (TDCD), accuracy, sensitivity, specificity, positive and negative predictive values, and the rate of inconclusive tests were calculated for all patients and for each MRS group.

A total of 1019 patients with suspected malignant lesions were evaluated by EUS-FNA. In 515 patients of 616 with true malignant lesions the tumor was diagnosed by EUS-FNA; 421 patients with resectable lesions received early surgical treatment, and 94 patients received chemo-radiotherapy. The overall diagnostic accuracy for the 1019 lesions in which a final diagnosis was obtained by EUS-FNA was 0.95. When patients were stratified by MTE into 4 classes of MRSs, a higher rate of patients in the group with higher cancer risk (MRS-3) received early treatment and EUS-FNA showed the highest level of accuracy (1.0). TDCD was also shorter in the MRS-3 group. The number of patients who received surgical treatment or chemo-radiotherapy was significantly higher in the MRS-3 patient group (36.3% in MRS-3, 10.7% in MRS-2, and 3.5% in MRS-1).

EUS-FNA can effectively detect a curable malignant lesions at an earlier time and at a higher rate in patients with a higher cancer risk that were evaluated using MTE.

Preoperative differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) and focal masses in patients with chronic pancreatitis (CP) can be challenging. There are fine differences in the vascularization of these lesions; ultrasound contrast agents can aid in their differentiation. We evaluated the value of software-aided quantitative analysis of transabdominal contrast-enhanced ultrasonography for differential diagnosis of PDAC vs focal masses.

Sixty patients for whom it was not possible to differentiate between an inflammatory focal lesion of the pancreas and a pancreatic carcinoma underwent contrast-enhanced ultrasonography with a second-generation contrast agent. Time-intensity curves were obtained for all exams in 2 regions of interest within the lesion and within the normal pancreatic tissue. Images were processed using Axius ACQ software; the following parameters were obtained: maximum intensity, arrival time, time-to-peak, and area under the curve. Absolute values and differences between the lesion and the normal tissue were evaluated.

Histology analysis revealed 45 PDACs and 15 inflammatory masses in patients with CP. Time-dependent parameters (arrival time and time to peak) were significantly longer in PDACs compared to focal masses. Although markedly lower than in healthy pancreata, the maximum intensity and area under the curve parameters were not significantly different between PDACs and focal lesions in patients with CP.

In cases of CP, PDAC and focal masses exhibit different perfusion patterns at a capillary level that can be visualized using the small microbubbles of ultrasound contrast agents. Contrast quantification software supplements a subjective visual assessment with objective criteria to facilitate the differential diagnosis of focal lesions in pancreatic cancer and chronic pancreatitis.