Computed tomography features of acinar cell carcinoma of the pancreas.
Diagn Interv Imaging
; 101(9): 565-575, 2020 Sep.
Article
en En
| MEDLINE
| ID: mdl-32146131
ABSTRACT
PURPOSE:
To report the computed tomography (CT) features of pancreatic acinar cell carcinoma (ACC) and identify CT features that may help discriminate between pancreatic ACC and pancreatic ductal adenocarcinoma (PDA). MATERIALS ANDMETHODS:
The CT examinations of 20 patients (13 men, 7 women; mean age, 66.5±10.7 [SD] years; range 51-88 years) with 20 histopathologically proven pancreatic ACC were reviewed. CT images were analyzed qualitatively and quantitatively and compared to those obtained in 20 patients with PDA. Comparisons were performed using univariate analysis with a conditional logistic regression model.RESULTS:
Pancreatic ACC presented as an enhancing (20/20; 100%), oval (15/20; 75%), well-delineated (14/20; 70%) and purely solid (13/20; 65%) pancreatic mass with a mean diameter of 52.6±28.0 (SD) mm (range 24-120mm) in association with visible lymph nodes (14/20; 70%). At univariate analysis, well-defined margins (Odds ratio [OR], 7.00; P=0.005), nondilated bile ducts (OR, 9.00; P=0.007), visible lymph nodes (OR, 4.33; P=0.028) and adjacent organ involvement (OR, 5.67; P=0.02) were the most discriminating CT features to differentiate pancreatic ACC from PDA. When present, lymph nodes were larger in patients with pancreatic ACC (14±4.8 [SD]; range 7-25mm) than in those with PDA (8.8±4.1 [SD]; range 5-15mm) (P=0.039).CONCLUSION:
On CT, pancreatic ACC presents as an enhancing, predominantly oval and purely solid pancreatic mass that most frequently present with no bile duct dilatation, no visible lymph nodes, no adjacent organ involvement and larger visible lymph nodes compared to PDA.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias Pancreáticas
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Carcinoma de Células Acinares
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Carcinoma Ductal Pancreático
Límite:
Aged
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Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
Diagn Interv Imaging
Año:
2020
Tipo del documento:
Article