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Does Computed Tomography Have the Ability to Differentiate Aggressive From Nonaggressive Solid Pseudopapillary Neoplasm?

ABSTRACT: OBJECTIVE:The aim of the study was to assess the ability of contrast-enhanced computed tomography (CECT) to differentiate aggressive from nonaggressive solid pseudopapillary neoplasms (SPNs). MATERIALS AND METHODS:Forty treatment-naive patients with pathologically proven pancreatic SPNs were included. Imaging characteristics were determined by consensus of 3 radiologists blinded to histopathologic aggressiveness. All patients underwent 4-phase CECT using a pancreatic protocol. The regions of interest of the tumor and the normal pancreas were documented on all phases. Lymph nodes were considered metastatic if greater than 1.0 cm in short-axis diameter.Fisher exact and Wilcoxon rank-sum tests were used to compare between aggressive and nonaggressive tumors. RESULTS:No significant difference was noted between imaging covariates, such as internal hemorrhage, calcification, wall thickness perceptibility, vascular invasion, margins, cystic component, and pancreatic and biliary ductal dilation. Tumors with greater than 62.5 Hounsfield units and progressive enhancement during the delayed phase had aggressive characteristics (P = 0.03). CONCLUSIONS:On delayed phase CECT, pathologically aggressive SPNs may show greater enhancement than nonaggressive SPNs.

SUBMITTER: Rastogi A

PROVIDER: S-EPMC5951735 | biostudies-literature | 2018 May/Jun

REPOSITORIES: biostudies-literature

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Does Computed Tomography Have the Ability to Differentiate Aggressive From Nonaggressive Solid Pseudopapillary Neoplasm?

Rastogi Ashita A Assing Mathew M Taggart Mellisa M Rao Brinda B Sun Jia J Elsayes Khaled K Tamm Eric E Bhosale Priya P

Journal of computer assisted tomography 20180501 3

<h4>Objective</h4>The aim of the study was to assess the ability of contrast-enhanced computed tomography (CECT) to differentiate aggressive from nonaggressive solid pseudopapillary neoplasms (SPNs).<h4>Materials and methods</h4>Forty treatment-naive patients with pathologically proven pancreatic SPNs were included. Imaging characteristics were determined by consensus of 3 radiologists blinded to histopathologic aggressiveness. All patients underwent 4-phase CECT using a pancreatic protocol. The ...[more]

PMID: 29287021

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Project description:ObjectiveSolid pseudopapillary neoplasm (SPN) of the pancreas is a rare tumor. This study aims to examine the clinicopathological features and surgical treatments of SPN and compare the clinical behavior and prognosis between men and women with SPN.MethodsWe collected the population data of patients with SPN diagnosed between 2004 and 2017 from the SEER database. The Kaplan-Meier method was used to analyze overall survival (OS) and disease-specific survival (DSS), and log-rank tests were used to evaluate the differences between subgroups. Univariate and multivariate Cox regression analyses were performed to screen out prognostic risk factors of SPN.ResultsA total of 378 patients with SPN were included, with 246 (65.1%) female patients. 1-, 3-, and 5-year overall survival rates were 98.9%, 95.7%, and 93.7%, respectively. Survival analysis revealed that regardless of stage, patients with SPN who underwent surgical interventions still had a significantly better prognosis than those without surgical interventions (P < .001). The patients with lymphatic dissection had a significantly better prognosis than those without lymphatic dissection (P < .001). Moreover, compared with female patients, male patients had significantly poorer OS and DSS (P < .001). Female SPN showed a bimodal age-frequency distribution with early-onset incidence at 28 years and late-onset peak incidence at 62 years, while male SPN presented a unimodal distribution with peak incidence at approximately age 64 years. In female patients, the tumor size in premenopausal females (<65 years old) was significantly larger than that in postmenopausal females (≥65 years old) (P < .001). Clinicopathological characteristic profiles were different not only between male SPN and premenopausal female SPN but also between premenopausal and postmenopausal female SPN.ConclusionSPN presents indolent behavior and predominantly occurs in young women. Regardless of stage, surgical intervention is recommended. Moreover, our study is the first large enough study to demonstrate sex-related discrepancies in SPN. Thus, different treatment strategies should be designed for patients of different sexes at different ages and hormone therapy is a promising approach for SPN.

Project description:PurposeIt is challenging for traditional CT signs to predict invasiveness of pancreatic solid pseudopapillary neoplasm (pSPN). We aim to develop and evaluate CT-based radiomics signature to preoperatively predict invasive behavior in pSPN.MethodsEighty-five patients who had pathologically confirmed pSPN and preoperative contrasted-enhanced CT imaging in our hospital were retrospectively analyzed (invasive: 24; non-invasive: 61). 1316 radiomics features were separately extracted from delineated 2D or 3D ROIs in arterial and venous phases. 200% (SMOTE) was used to generate balanced dataset (invasive: 72, non-invasive: 96) for each phase, which was for feature selection and modeling. The model was internally validated in the original dataset. Inter-observer consistency analysis, spearman correlation, univariate analysis, LASSO regression and backward stepwise logical regression were mainly applied to screen the features, and 6 logistic regression models were established based on multi-phase features from 2D or 3D segmentations. The ROC analysis and Delong's test were mainly used for model assessment and AUC comparison.ResultsIt retained 11, 8, 7 and 7 features to construct 3D-arterial, 3D-venous, 2D-arterial and 2D-venous model. Based on 3D ROIs, the arterial model (AUC: 0.914) performed better than venous (AUC: 0.815) and the arterial-venous combined model was slightly improved (AUC: 0.918). Based on 2D ROIs, the arterial model (AUC: 0.814) performed better than venous (AUC:0.768), while the arterial-venous combined model (AUC:0.893) performed better than any single-phase model. In addition, the 3D arterial model performed better than the best combined 2D model. The Delong's test showed that the significant difference of model AUC existed in arterial models in original dataset (p = 0.019) while not in arterial-venous combined model (p=0.49) as comparing 2D and 3D ROIs.ConclusionThe arterial radiomics model constructed by 3D-ROI feature is potential to predict the invasiveness of pSPN preoperatively.

Dataset Information

Does Computed Tomography Have the Ability to Differentiate Aggressive From Nonaggressive Solid Pseudopapillary Neoplasm?

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Does Computed Tomography Have the Ability to Differentiate Aggressive From Nonaggressive Solid Pseudopapillary Neoplasm?

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