Diagnostic and Interventional Radiology
Abdominal Imaging - Original Article

MR quantitative 3D shape analysis helps to distinguish mucinous cystic neoplasm from serous oligocystic adenoma

1.

Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, Shanghai, China

2.

Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Diagn Interv Radiol 2022; 28: 193-199
DOI: 10.5152/dir.2022.20738
Read: 339 Downloads: 76 Published: 01 May 2022

PURPOSE
We aimed to assess the performance of quantitative 3D shape analysis in the differential diagno- sis of pancreatic serous oligocystic adenoma (SOA) and mucinous cystic neoplasm (MCN).

METHODS
Four hundred thirty-two patients diagnosed with serous cystic neoplasms (SCNs) or MCNs were retrospectively reviewed from August 2014 to July 2019 and finally 87 patients with MCNs (n = 45) and SOAs (n = 42) were included. Clinical data and magnetic resonance morphologic fea- tures with 3D shape analysis of lesions (shape sphericity, compacity, and volume) were recorded and compared between MCNs and SOAs according to the pathology. Univariable and multivari- able regression analyses were used to identify independent impact factors for differentiating MCN from SOA.

RESULTS
The age of MCN patients was younger than SOAs (43.02 ± 10.83 years vs. 52.78 ± 12.31 years; OR = 0.275; 95% CI: 0.098-0.768; P = .014). MCN has a higher female/male ratio than SOA (43/2 vs. 27/15; OR = 40.418; 95% CI: 2.704-604.171; P = .007) and was more often located in the distal of pancreas (OR = 31.403; 95% CI: 2.985-330.342; P = .004). Shape_Sphericity derived from 3D shape analysis was a significant independent factor in the multivariable analysis and the value of MCN was closer to 1 than SOA (OR = 35.153; 95% CI: 5.301-237.585; P < .001). Area under the receiver operating characteristic curve (AUC) of Shape_Sphericity was 0.923 (optimal cutoff value was 0.964876).

CONCLUSION
Shape_Sphericity in combination with age, sex, and location could help to distinguish MCN from SOA.

You may cite this article as: Zhu S, Wang W, Wu W, Lou W, Zeng M, Rao S. MR quantitative 3D shape analysis helps to distinguish mucinous cystic neoplasm from serous oligocystic adenoma. Diagn Interv Radiol. 2022;28(3):193-199.

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