Radiomics of coronary artery calcium in the framingham heart study

Parastou Eslami, Borek Foldy, Jan Erik Scholtz, Alexander Ivanov, Roman Zeleznik, Michael T. Lu, Maros Ferencik, Ramachandran S. Vasan, Kristin Baltrusaitis, Joseph M. Massaro, Ralph B. D’agostino, Thomas Mayrhofer, Christopher J. O’donnell, Hugo J.W.L. Aerts, Udo Hoffmann

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


Purpose: To extract radiomic features from coronary artery calcium (CAC) on CT images and to determine whether this approach could improve the ability to identify individuals at risk for a composite endpoint of clinical events. Materials and Methods: Participants from the Offspring and Third Generation cohorts of the community-based Framingham Heart Study underwent noncontrast cardiac CT (2002–2005) and were followed for more than a median of 9.1 years for composite major events. A total of 624 participants with CAC Agatston score (AS) of greater than 0 and good or excellent CT image quality were included for manual CAC segmentation and extraction of a predefined set of radiomic features reflecting intensity, shape, and texture. In a discov-ery cohort (n = 318), machine learning was used to select the 20 most informative and nonredundant CAC radiomic features, classify features predicting events, and define a radiomic-based score (RS). Performance of the RS was tested independently for the prediction of events in a validation cohort (n = 306). Results: The RS had a median value of 0.08 (interquartile range, 0.007–0.71) and a weak and modest correlation with Framingham risk score (FRS) (r = 0.2) and AS (r = 0.39), respectively. The continuous RS unadjusted, adjusted for age and sex, FRS, AS, and FRS plus AS were significantly associated with events (hazard ratio [HR] = 2.2, P <.001; HR = 1.8, P =.002; HR = 2.0, P <.001; HR = 1.7, P =.02; and HR = 1.8, P =.01, respectively). In participants with AS of less than 300, RS association with events remained significant when unadjusted and adjusted for age and sex, FRS, AS, and FRS plus AS (HR = 2.4, 2.8, 2.8, 2.3, and 2.6; P <.001, respec-tively). In the same subgroup of participants, adding the RS to AS resulted in a significant improvement in the discriminatory ability for events as compared with the AS (area under the receiver operating curve: 0.80 vs 0.68, respectively; P =.03). Conclusion: A radiomic-based score, including the complex properties of CAC, may constitute an imaging biomarker to be further de-veloped to identify individuals at risk for major adverse cardiovascular events in a community-based cohort.

Original languageEnglish (US)
Article numbere190119
JournalRadiology: Cardiothoracic Imaging
Issue number1
StatePublished - Feb 2020

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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