ArticleAbdominal radiology (New York)2026
Transabdominal ultrasound subclassification of pancreatic serous cystic neoplasms: correlation with MRI and characterization of subtype-specific features.
Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesTo characterize the transabdominal ultrasound (US) features of pancreatic serous cystic neoplasm (SCN) morphological subtypes, evaluate US-MRI agreement, and explore reducing overtreatment. MATERIALS AND
methodsThis retrospective study included 125 patients with pathologically confirmed pancreatic SCNs who underwent preoperative US. Lesions were morphologically classified into macrocystic, microcystic, mixed, and solid subtypes. US-MRI concordance (71 patients, 56.8%) was assessed using Cohen's kappa. Demographics, grayscale features, and CEUS patterns (exploratory n = 14) were described.
resultsUS demonstrated excellent agreement with MRI for SCN subtyping (κ = 0.817, 95% CI: 0.711-0.923). Macrocystic was most common (38.4%) and occurred in younger patients (42.0 ± 12.3 years, p < 0.001). Overall, exophytic growth (84.1%) was a hallmark feature. Mixed subtypes exhibited the highest lobulation rate (p < 0.001) and peripheral macrocysts, whereas solid subtypes were predominantly non-lobulated. US and MRI discrepancies arose when microcysts were too small to resolve on US, mimicking solid. On CEUS, microcystic SCNs showed honeycomb architecture, whereas solid SCNs demonstrated arterial iso- or slight hyper-enhancement followed by slow washout.
conclusionConventional US provides reliable morphological subtyping of SCNs, comparable to MRI. Recognizing fine internal architectures, distinctive growth patterns (exophytic/lobulated), and the potential value of slow CEUS washout patterns may aid in the characterization of SCNs and provide supportive information for differential diagnosis. Given that most SCNs are benign and do not require routine intervention, improved non‑invasive characterization by US can help inform clinical decision‑making and potentially reduce surgical overtreatment.
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