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Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

  • Rikiya Yamashita
  • Thomas Perrin
  • Jayasree Chakraborty
  • Joanne F. Chou
  • Natally Horvat
  • Maura A. Koszalka
  • Abhishek Midya
  • Mithat Gonen
  • Peter Allen
  • William R. Jarnagin
  • Amber L. Simpson
  • Richard K. G. DoEmail author
Hepatobiliary-Pancreas
  • 72 Downloads

Abstract

Objectives

This study aims to measure the reproducibility of radiomic features in pancreatic parenchyma and ductal adenocarcinomas (PDAC) in patients who underwent consecutive contrast-enhanced computed tomography (CECT) scans.

Methods

In this IRB-approved and HIPAA-compliant retrospective study, 37 pairs of scans from 37 unique patients who underwent CECTs within a 2-week interval were included in the analysis of the reproducibility of features derived from pancreatic parenchyma, and a subset of 18 pairs of scans were further analyzed for the reproducibility of features derived from PDAC. In each patient, pancreatic parenchyma and pancreatic tumor (when present) were manually segmented by two radiologists independently. A total of 266 radiomic features were extracted from the pancreatic parenchyma and tumor region and also the volume and diameter of the tumor. The concordance correlation coefficient (CCC) was calculated to assess feature reproducibility for each patient in three scenarios: (1) different radiologists, same CECT; (2) same radiologist, different CECTs; and (3) different radiologists, different CECTs.

Results

Among pancreatic parenchyma-derived features, using a threshold of CCC > 0.90, 58/266 (21.8%) and 48/266 (18.1%) features met the threshold for scenario 1, 14/266 (5.3%) and 15/266 (5.6%) for scenario 2, and 14/266 (5.3%) and 10/266 (3.8%) for scenario 3. Among pancreatic tumor-derived features, 11/268 (4.1%) and 17/268 (6.3%) features met the threshold for scenario 1, 1/268 (0.4%) and 5/268 (1.9%) features met the threshold for scenario 2, and no features for scenario 3 met the threshold, respectively.

Conclusions

Variations between CECT scans affected radiomic feature reproducibility to a greater extent than variation in segmentation. A smaller number of pancreatic tumor-derived radiomic features were reproducible compared with pancreatic parenchyma-derived radiomic features under the same conditions.

Key Points

• For pancreatic-derived radiomic features from contrast-enhanced CT (CECT), fewer than 25% are reproducible (with a threshold of CCC < 0.9) in a clinical heterogeneous dataset.

• Variations between CECT scans affected the number of reproducible radiomic features to a greater extent than variations in radiologist segmentation.

• A smaller number of pancreatic tumor-derived radiomic features were reproducible compared with pancreatic parenchyma-derived radiomic features under the same conditions.

Keywords

Reproducibility of results Pancreatic ductal carcinoma X-ray computed tomography Radiomics Texture analysis 

Abbreviations and acronyms

ACM

Angle co-occurrence matrix

CCC

Concordance correlation coefficient

CECT

Contrast-enhanced computed tomography

DICOM

Digital Imaging and Communications in Medicine

FD

Fractal dimension

GLCM

Gray-level co-occurrence matrix

ICC

Intraclass correlation coefficient

IH

Intensity histogram

IQR

Interquartile range

LBP

Local binary pattern

PDAC

Pancreatic ductal adenocarcinoma

RLM

Run length matrix

Notes

Acknowledgments

We thank Luz Adriana Escobar Hoyos and Juliana Brooke Schilsky for their support in figure creation and Joanne Chin for editorial assistance.

Funding

This study was funded in part through the 2016 Society of Abdominal Radiology Wylie J. Dodds Research Award, the National Institutes of Health/National Cancer Institute Cancer Center Support Grant P30 CA008748, and the Japan Society Promotion of Science Overseas Research Fellowships JSPS/OT/290125.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Richard K. G. Do, MD, PhD.

Conflict of interest

The authors declare that they have no conflict of interest.

Statistics and biometry

Two of the authors (Joanne Chou and Mithat Gonen, PhD) have significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• cross-sectional study

• performed at one institution

Supplementary material

330_2019_6381_MOESM1_ESM.docx (24 kb)
ESM 1 (DOCX 24 kb)
330_2019_6381_MOESM2_ESM.xlsx (18 kb)
ESM 2 (XLSX 17 kb)
330_2019_6381_MOESM3_ESM.docx (15.8 mb)
ESM 3 (DOCX 16189 kb)

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Rikiya Yamashita
    • 1
  • Thomas Perrin
    • 2
  • Jayasree Chakraborty
    • 2
  • Joanne F. Chou
    • 3
  • Natally Horvat
    • 1
  • Maura A. Koszalka
    • 2
  • Abhishek Midya
    • 2
  • Mithat Gonen
    • 3
  • Peter Allen
    • 2
  • William R. Jarnagin
    • 2
  • Amber L. Simpson
    • 2
  • Richard K. G. Do
    • 1
    Email author
  1. 1.Department of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkUSA
  2. 2.Department of SurgeryMemorial Sloan Kettering Cancer CenterNew YorkUSA
  3. 3.Department of Epidemiology and BiostatisticsMemorial Sloan Kettering Cancer CenterNew YorkUSA

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