Analyzing Intraductal Papillary Mucinous Neoplasms Using Artificial Neural Network Methodologic Triangulation

Analyzing Intraductal Papillary Mucinous Neoplasms Using Artificial Neural Network Methodologic Triangulation

Steven Walczak (School of Information, University of South Florida, Tampa, USA), Jennifer B. Permuth (Departments of Cancer Epidemiology and Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and R, Tampa, USA) and Vic Velanovich (Department of Surgery, College of Medicine, University of South Florida, Tampa, USA)
DOI: 10.4018/IJHISI.2019100102

Abstract

Intraductal papillary mucinous neoplasms (IPMN) are a type of mucinous pancreatic cyst. IPMN have been shown to be pre-malignant precursors to pancreatic cancer, which has an extremely high mortality rate with average survival less than 1 year. The purpose of this analysis is to utilize methodological triangulation using artificial neural networks and regression to examine the impact and effectiveness of a collection of variables believed to be predictive of malignant IPMN pathology. Results indicate that the triangulation is effective in both finding a new predictive variable and possibly reducing the number of variables needed for predicting if an IPMN is malignant or benign.
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Background

“The category of IPMN was created originally to embrace all mass-forming pre-invasive neoplasia comprising mucinous ductal cells, arising from the native pancreatic ducts” (Fernández–del Castillo & Adsay, 2010, pg. 709). The chief symptoms of individuals with IPMN are: abdominal pain, weight loss, jaundice, nausea, and fatigue and may also be concomitant with diabetes or pancreatitis (Adsay et al., 2002; Fernández–del Castillo & Adsay, 2010; Sohn et al. 2001, 2004). However, the vast majority of patients are asymptomatic and IPMN are discovered incidentally when abdominal imaging is performed for other unrelated problems (Fernández–del Castillo & Adsay, 2010; Sahora & Fernández-del Castillo, 2015). The prevalence of asymptomatic IPMN in patients has been estimated using CT and/or MRI to be from 2.6% to 27% for MD-IPMN or 83% for BD-IPMN (Laffan et al., 2008; D’Angelica et al., 2004; de Pretis et al., 2017; (Pergolini et al., 2017; Salvia et al., 2004).

IPMN are typically detected using CT (computed tomography) or MR (magnetic resonance) imaging (Adsay et al., 2002; Fernández–del Castillo & Adsay, 2010; Sahora & Fernández-del Castillo, 2015). A recent research study in the USA found that IPMN occur in 2.5% of the total population over age 40, with prevalence increasing with age to over 7% and 8% in 70 year olds and 80 year olds respectively (Gardner et al., 2013). Other research, based on autopsies, estimates the prevalence of IPMN at 3.4% of the total population (Tanaka et al., 2006).

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