Synapse - A combined radiomics and cyst fluid inflammatory markers model to predict preoperative risk in pancreatic cystic lesions

A combined radiomics and cyst fluid inflammatory markers model to predict preoperative risk in pancreatic cystic lesions Conference Paper

Authors:	Williams, T. L.; Harrington, K. A.; Lawrence, S. A.; Chakraborty, J.; Al Efishat, M. A.; Attiyeh, M. A.; Askan, G.; Chou, Y.; Pulvirenti, A.; McIntyre, C. A.; Gonen, M.; Basturk, O.; Balachandran, V. P.; Kingham, T. P.; D'Angelica, M. I.; Jarnagin, W. R.; Drebin, J. A.; Do, R. K. G.; Allen, P. J.; Simpson, A. L.
Editors:	Fei, B.; Linte, C. A.
Title:	A combined radiomics and cyst fluid inflammatory markers model to predict preoperative risk in pancreatic cystic lesions
Conference Title:	Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Abstract:	This paper contributes to the burgeoning field of surgical data science. Specifically, multi-modal integration of relevant patient data is used to determine who should undergo a complex pancreatic resection. Intraductal papillary mucinous neoplasms (IPMNs) represent cystic precursor lesions of pancreatic cancer with varying risk for malignancy. We combine radiomic analysis of diagnostic computed tomography (CT) with protein markers extracted from the cyst fluid to create a unified prediction model to identify high-risk IPMNs. Patients with high-risk IPMN would be sent for resection, whereas patients with low-risk cystic lesions would be spared an invasive procedure. We extracted radiomic features from CT scans and combined this with cyst-fluid markers. The cyst fluid model yielded an area under the curve (AUC) of 0.74. Adding the QI model improved performance with an AUC of 0.88. Radiomic analysis of routinely acquired CT scans combined with cyst fluid inflammatory markers provides accurate prediction of risk of pancreatic cancer progression. © 2020 SPIE.
Keywords:	pancreas; risk assessment; computerized tomography; medical imaging; diagnosis; forecasting; robotics; diseases; intraductal papillary mucinous neoplasms; quantitative image analysis; prediction model; precursor lesions; pancreatic cancers; patient data; hospital data processing; radiomics; area under the curves; cystic lesion; cyst fiuid; accurate prediction; protein markers
Journal Title	Proceedings of SPIE
Volume:	11315
Conference Dates:	2020 Feb 16-19
Conference Location:	Houston, TX
ISBN:	0277-786X
Publisher:	SPIE
Date Published:	2020-01-01
Start Page:	113151Q
Language:	English
DOI:	10.1117/12.2566425
PROVIDER:	scopus
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085247265&doi=10.1117%2f12.2566425&partnerID=40&md5=c8e7151e0a99ec72c1c58e7a21105d71
Notes:	Conference Paper -- Source: Scopus