Texture analysis for survival prediction of pancreatic ductal adenocarcinoma patients with neoadjuvant chemotherapy Conference Paper
| Authors: | Chakraborty, J.; Langdon-Embry, L.; Escalon, J. G.; Allen, P. J.; Lowery, M. A.; O'Reilly, E. M.; Do, R. K. G.; Simpson, A. L. |
| Editors: | Styner, M. A.; Angelini, E. D. |
| Title: | Texture analysis for survival prediction of pancreatic ductal adenocarcinoma patients with neoadjuvant chemotherapy |
| Conference Title: | Medical Imaging 2016: Image Processing |
| Abstract: | Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death in the United States. The five-year survival rate for all stages is approximately 6%, and approximately 2% when presenting with distant disease.1 Only 10-20% of all patients present with resectable disease, but recurrence rates are high with only 5 to 15% remaining free of disease at 5 years. At this time, we are unable to distinguish between resectable PDAC patients with occult metastatic disease from those with potentially curable disease. Early classification of these tumor types may eventually lead to changes in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant treatments. Texture analysis is an emerging methodology in oncologic imaging for quantitatively assessing tumor heterogeneity that could potentially aid in the stratification of these patients. The present study derives several texture-based features from CT images of PDAC patients, acquired prior to neoadjuvant chemotherapy, and analyzes their performance, individually as well as in combination, as prognostic markers. A fuzzy minimum redundancy maximum relevance method with leave-one-image-out technique is included to select discriminating features from the set of extracted features. With a naive Bayes classifier, the proposed method predicts the 5-year overall survival of PDAC patients prior to neoadjuvant therapy and achieves the best results in terms of the area under the receiver operating characteristic curve of 0:858 and accuracy of 83:0% with four-fold cross-validation techniques. © 2016 SPIE. |
| Keywords: | chemotherapy; computerized tomography; medical imaging; tumors; patient treatment; image processing; pancreatic ductal adenocarcinoma; texture analysis; prognostic marker; prognostic markers; ductal adenocarcinomas; survival prediction; classifiers; medical image processing; neoad-juvant therapy |
| Journal Title | Proceedings of SPIE |
| Volume: | 9784 |
| Conference Dates: | 2016 Feb 27-Mar 3 |
| Conference Location: | San Diego, CA |
| ISBN: | 0277-786X |
| Publisher: | SPIE |
| Date Published: | 2016-01-01 |
| Start Page: | 9784 1W |
| Language: | English |
| DOI: | 10.1117/12.2214470 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference Paper -- Conference code: 122964 -- Export Date: 1 September 2016 -- Bruker; imXPAD; Modus Medical Devices Inc.; Poco Graphite; The Society of Photo-Optical Instrumentation Engineers (SPIE) -- 1 March 2016 through 3 March 2016 -- Source: Scopus |
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