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Radiomics-based prediction of microsatellite instability in colorectal cancer at initial computed tomography evaluation

  • Jennifer S. Golia PernickaEmail author
  • Johan Gagniere
  • Jayasree Chakraborty
  • Rikiya Yamashita
  • Lorenzo Nardo
  • John M. Creasy
  • Iva Petkovska
  • Richard R. K. Do
  • David D. B. Bates
  • Viktoriya Paroder
  • Mithat Gonen
  • Martin R. Weiser
  • Amber L. Simpson
  • Marc J. Gollub
Special Section: Rectal Cancer
  • 53 Downloads

Abstract

Purpose

To predict microsatellite instability (MSI) status of colon cancer on preoperative CT imaging using radiomic analysis.

Methods

This retrospective study involved radiomic analysis of preoperative CT imaging of patients who underwent resection of stage II–III colon cancer from 2004 to 2012. A radiologist blinded to MSI status manually segmented the tumor region on CT images. 254 Intensity-based radiomic features were extracted from the tumor region. Three prediction models were developed with (1) only clinical features, (2) only radiomic features, and (3) “combined” clinical and radiomic features. Patients were randomly separated into training (n = 139) and test (n = 59) sets. The model was constructed from training data only; the test set was reserved for validation only. Model performance was evaluated using AUC, sensitivity, specificity, PPV, and NPV.

Results

Of the total 198 patients, 134 (68%) patients had microsatellite stable tumors and 64 (32%) patients had MSI tumors. The combined model performed slightly better than the other models, predicting MSI with an AUC of 0.80 for the training set and 0.79 for the test set (specificity = 96.8% and 92.5%, respectively), whereas the model with only clinical features achieved an AUC of 0.74 and the model with only radiomic features achieved an AUC of 0.76. The model with clinical features alone had the lowest specificity (70%) compared with the model with radiomic features alone (95%) and the combined model (92.5%).

Conclusions

Preoperative prediction of MSI status via radiomic analysis of preoperative CT adds specificity to clinical assessment and could contribute to personalized treatment selection.

Keywords

Colon Colonic neoplasms Microsatellite repeats Microsatellite instability Immunotherapy 

Notes

Acknowledgements

The authors thank Joanne Chin, MFA, for her editorial support of this article. This study has received funding from NIH/NCI P30 CA008748 Cancer Center Support Grant and the Colorectal Cancer Research Center CC50367 at Memorial Sloan Kettering.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the Ethical Standards of the Institutional Committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed consent

Written informed consent was waived by the Institutional Review Board.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Jennifer S. Golia Pernicka
    • 1
    Email author
  • Johan Gagniere
    • 2
    • 4
  • Jayasree Chakraborty
    • 2
  • Rikiya Yamashita
    • 1
  • Lorenzo Nardo
    • 1
    • 5
  • John M. Creasy
    • 2
  • Iva Petkovska
    • 1
  • Richard R. K. Do
    • 1
  • David D. B. Bates
    • 1
  • Viktoriya Paroder
    • 1
  • Mithat Gonen
    • 3
  • Martin R. Weiser
    • 2
  • Amber L. Simpson
    • 2
  • Marc J. Gollub
    • 1
  1. 1.Body Imaging Service, Department of Radiology, Evelyn H. Lauder Breast CenterMemorial Sloan Kettering Cancer CenterNew YorkUSA
  2. 2.Department of SurgeryMemorial Sloan Kettering Cancer CenterNew YorkUSA
  3. 3.Department of Epidemiology & BiostatisticsMemorial Sloan Kettering Cancer CenterNew YorkUSA
  4. 4.Department of Digestive and Hepatobiliary Surgery, U1071 INSERM / Clermont-Auvergne UniversityUniversity Hospital of Clermont-FerrandClermont-FerrandFrance
  5. 5.Department of RadiologyUniversity of California DavisSacramentoUSA

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