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Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation.

Publication ,  Journal Article
Huang, EP; Pennello, G; deSouza, NM; Wang, X; Buckler, AJ; Kinahan, PE; Barnhart, HX; Delfino, JG; Hall, TJ; Raunig, DL; Guimaraes, AR; Obuchowski, NA
Published in: Acad Radiol
February 2023

Combinations of multiple quantitative imaging biomarkers (QIBs) are often able to predict the likelihood of an event of interest such as death or disease recurrence more effectively than single imaging measurements can alone. The development of such multiparametric quantitative imaging and evaluation of its fitness of use differs from the analogous processes for individual QIBs in several key aspects. A computational procedure to combine the QIB values into a model output must be specified. The output must also be reproducible and be shown to have reasonably strong ability to predict the risk of an event of interest. Attention must be paid to statistical issues not often encountered in the single QIB scenario, including overfitting and bias in the estimates of model performance. This is the fourth in a five-part series on statistical methodology for assessing the technical performance of multiparametric quantitative imaging. Considerations for data acquisition are discussed and recommendations from the literature on methodology to construct and evaluate QIB-based models for risk prediction are summarized. The findings in the literature upon which these recommendations are based are demonstrated through simulation studies. The concepts in this manuscript are applied to a real-life example involving prediction of major adverse cardiac events using automated plaque analysis.

Duke Scholars

Published In

Acad Radiol

DOI

EISSN

1878-4046

Publication Date

February 2023

Volume

30

Issue

2

Start / End Page

196 / 214

Location

United States

Related Subject Headings

  • Nuclear Medicine & Medical Imaging
  • Humans
  • Diagnostic Imaging
  • Computer Simulation
  • Biomarkers
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Huang, E. P., Pennello, G., deSouza, N. M., Wang, X., Buckler, A. J., Kinahan, P. E., … Obuchowski, N. A. (2023). Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation. Acad Radiol, 30(2), 196–214. https://doi.org/10.1016/j.acra.2022.09.018
Huang, Erich P., Gene Pennello, Nandita M. deSouza, Xiaofeng Wang, Andrew J. Buckler, Paul E. Kinahan, Huiman X. Barnhart, et al. “Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation.Acad Radiol 30, no. 2 (February 2023): 196–214. https://doi.org/10.1016/j.acra.2022.09.018.
Huang EP, Pennello G, deSouza NM, Wang X, Buckler AJ, Kinahan PE, et al. Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation. Acad Radiol. 2023 Feb;30(2):196–214.
Huang, Erich P., et al. “Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation.Acad Radiol, vol. 30, no. 2, Feb. 2023, pp. 196–214. Pubmed, doi:10.1016/j.acra.2022.09.018.
Huang EP, Pennello G, deSouza NM, Wang X, Buckler AJ, Kinahan PE, Barnhart HX, Delfino JG, Hall TJ, Raunig DL, Guimaraes AR, Obuchowski NA. Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation. Acad Radiol. 2023 Feb;30(2):196–214.
Journal cover image

Published In

Acad Radiol

DOI

EISSN

1878-4046

Publication Date

February 2023

Volume

30

Issue

2

Start / End Page

196 / 214

Location

United States

Related Subject Headings

  • Nuclear Medicine & Medical Imaging
  • Humans
  • Diagnostic Imaging
  • Computer Simulation
  • Biomarkers
  • 3202 Clinical sciences
  • 1103 Clinical Sciences