Pancreatic Cystic Lesions: Review of the Current State of Diagnosis and Surveillance

CT Imaging of the Pancreas: A Review of Current Developments and Applications

Pancreatic cancer continues to pose daily challenges to clinicians, radiologists, and researchers. These challenges are encountered at each stage of pancreatic cancer management, including early detection, definite characterization, accurate assessment of tumour burden, preoperative planning when surgical resection is possible, prediction of tumour aggressiveness, response to treatment, and detection of recurrence. CT imaging of the pancreas has made major advances in recent years through innovations in research and clinical practice. Technical advances in CT imaging, often in combination with imaging biomarkers, hold considerable promise in addressing such challenges. Ongoing research in dual-energy and spectral photon-counting computed tomography, new applications of artificial intelligence and image rendering have led to innovative implementations that allow now a more precise diagnosis of pancreatic cancer and other diseases affecting this organ. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of CT imaging of the pancreas. By highlighting key contributions in diagnostic imaging, artificial intelligence, and image rendering, this article provides a comprehensive overview of how these innovations are enhancing diagnostic precision and improving outcome in patients with pancreatic diseases.

Percentage of Pancreatic Cysts on MRI With a Pancreatic Carcinoma: Systematic Review and Meta-Analysis

BACKGROUND

Pancreatic cystic lesions (PCLs) are frequent on MRI and are thought to be associated with pancreatic adenocarcinoma (PDAC) necessitating long-term surveillance based on older studies suffering from selection bias.

PURPOSE

To establish the percentage of patients with PCLs on MRI with a present or future PDAC.

STUDY TYPE

Systematic review, meta-analysis.

POPULATION

Adults with PCLs on MRI and a present or future diagnosis of PDAC were eligible. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Scopus were searched to April 2022 (PROSPERO:CRD42022320502). Studies limited to PCLs not requiring surveillance, <100 patients, or those with a history/genetic risk of PDAC were excluded.

FIELD STRENGTH/SEQUENCE

≥1.5 T with ≥1 T2-weighted sequence.

ASSESSMENT

Two investigators extracted data, with discrepancies resolved by a third. QUADAS-2 assessed bias. PDAC was diagnosed using a composite reference standard.

STATISTICAL TESTS

A meta-analysis of proportions was performed at the patient-level with 95% confidence intervals (95% CI).

RESULTS

Eight studies with 1289 patients contributed to the percentage of patients with a present diagnosis of PDAC, and 10 studies with 3422 patients to the percentage with a future diagnosis. Of patients with PCLs on MRI, 14.8% (95% CI 2.4-34.9) had a PDAC at initial MRI, which decreased to 6.0% (2.2-11.3) for studies at low risk of bias. For patients without PDAC on initial MRI, 2.0% (1.1-3.2) developed PDAC during surveillance, similar for low risk of bias studies at 1.9% (0.7-3.6), with no clear trend of increased PDAC for longer surveillance durations. For patients without worrisome features or high-risk stigmata, 0.9% (0.1-2.2) developed PDAC during surveillance. Of 10, eight studies had a median surveillance ≥3 years (range 3-157 months). Sources of bias included retrospectively limiting PCLs to those with histopathology and inconsistent surveillance protocols.

DATA CONCLUSION

A low percentage of patients with PCLs on MRI develop PDAC while on surveillance. The first MRI revealing a PCL should be scrutinized for PDAC.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Risk Models for Pancreatic Cyst Diagnosis

The overall prevalence of pancreatic cysts (PCs) is high in the general population. In clinical practice PCs are often incidentally discovered and are classified into benign, premalignant, and malignant lesions according to the World Health Organization. For this reason, in the absence of reliable biomarkers, to date clinical decision-making relies mostly on risk models based on morphological features. The aim of this narrative review is to present the current knowledge regarding PC's morphologic features with related estimated risk of malignancy and discuss available diagnostic tools to minimize clinically relevant diagnostic errors.