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CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma.

Publication ,  Journal Article
Attiyeh, MA; Chakraborty, J; McIntyre, CA; Kappagantula, R; Chou, Y; Askan, G; Seier, K; Gonen, M; Basturk, O; Balachandran, VP; Kingham, TP ...
Published in: Abdom Radiol (NY)
September 2019

PURPOSE: The aim of this study was to investigate the relationship between CT imaging phenotypes and genetic and biological characteristics in pancreatic ductal adenocarcinoma (PDAC). METHODS: In this retrospective study, consecutive patients between April 2015 and June 2016 who underwent PDAC resection were included if previously consented to a targeted sequencing protocol. Mutation status of known PDAC driver genes (KRAS, TP53, CDKN2A, and SMAD4) in the primary tumor was determined by targeted DNA sequencing and results were validated by immunohistochemistry (IHC). Radiomic features of the tumor were extracted from the preoperative CT scan and used to predict genotype and stromal content. RESULTS: The cohort for analysis consisted of 35 patients. Genomic and IHC analysis revealed alterations in KRAS in 34 (97%) patients, and changes in expression of CDKN2A in 29 (83%), SMAD4 in 16 (46%), and in TP53 in 29 (83%) patients. Models created from radiomic features demonstrated associations with SMAD4 status and the number of genes altered. The number of genes altered was the only significant predictor of overall survival (p = 0.016). By linear regression analysis, a prediction model for stromal content achieved an R2 value of 0.731 with a root mean square error of 19.5. CONCLUSIONS: In this study, we demonstrate that in PDAC SMAD4 status and tumor stromal content can be predicted using radiomic analysis of preoperative CT imaging. These data show an association between resectable PDAC imaging features and underlying tumor biology and their potential for future precision medicine.

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Published In

Abdom Radiol (NY)

DOI

EISSN

2366-0058

Publication Date

September 2019

Volume

44

Issue

9

Start / End Page

3148 / 3157

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Retrospective Studies
  • Pancreatic Neoplasms
  • Pancreas
  • Middle Aged
  • Male
  • Humans
  • Genotype
  • Female
  • Cohort Studies
 

Citation

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Attiyeh, M. A., Chakraborty, J., McIntyre, C. A., Kappagantula, R., Chou, Y., Askan, G., … Do, R. K. (2019). CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma. Abdom Radiol (NY), 44(9), 3148–3157. https://doi.org/10.1007/s00261-019-02112-1
Attiyeh, Marc A., Jayasree Chakraborty, Caitlin A. McIntyre, Rajya Kappagantula, Yuting Chou, Gokce Askan, Kenneth Seier, et al. “CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma.Abdom Radiol (NY) 44, no. 9 (September 2019): 3148–57. https://doi.org/10.1007/s00261-019-02112-1.
Attiyeh MA, Chakraborty J, McIntyre CA, Kappagantula R, Chou Y, Askan G, et al. CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma. Abdom Radiol (NY). 2019 Sep;44(9):3148–57.
Attiyeh, Marc A., et al. “CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma.Abdom Radiol (NY), vol. 44, no. 9, Sept. 2019, pp. 3148–57. Pubmed, doi:10.1007/s00261-019-02112-1.
Attiyeh MA, Chakraborty J, McIntyre CA, Kappagantula R, Chou Y, Askan G, Seier K, Gonen M, Basturk O, Balachandran VP, Kingham TP, D’Angelica MI, Drebin JA, Jarnagin WR, Allen PJ, Iacobuzio-Donahue CA, Simpson AL, Do RK. CT radiomics associations with genotype and stromal content in pancreatic ductal adenocarcinoma. Abdom Radiol (NY). 2019 Sep;44(9):3148–3157.
Journal cover image

Published In

Abdom Radiol (NY)

DOI

EISSN

2366-0058

Publication Date

September 2019

Volume

44

Issue

9

Start / End Page

3148 / 3157

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Retrospective Studies
  • Pancreatic Neoplasms
  • Pancreas
  • Middle Aged
  • Male
  • Humans
  • Genotype
  • Female
  • Cohort Studies