Automated quantitative 3D analysis of aorta size, morphology, and mural calcification distributions.
OBJECTIVE
The purpose of this work is to develop a fully automated pipeline to compute aorta morphology and calcification measures in large cohorts of CT scans that can be used to investigate the potential of these measures as imaging biomarkers of cardiovascular disease.


METHODS
The first step of the automated pipeline is aorta segmentation. The algorithm the authors propose first detects an initial aorta boundary by exploiting cross-sectional circularity of aorta in axial slices and aortic arch in reformatted oblique slices. This boundary is then refined by a 3D level-set segmentation that evolves the boundary to the location of nearby edges. The authors then detect the aortic calcifications with thresholding and filter out the false positive regions due to nearby high intensity structures based on their anatomical location. The authors extract the centerline and oblique cross sections of the segmented aortas and compute the aorta morphology and calcification measures of the first 2500 subjects from COPDGene study. These measures include volume and number of calcified plaques and measures of vessel morphology such as average cross-sectional area, tortuosity, and arch width.


RESULTS
The authors computed the agreement between the algorithm and expert segmentations on 45 CT scans and obtained a closest point mean error of 0.62 ± 0.09 mm and a Dice coefficient of 0.92 ± 0.01. The calcification detection algorithm resulted in an improved true positive detection rate of 0.96 compared to previous work. The measurements of aorta size agreed with the measurements reported in previous work. The initial results showed associations of aorta morphology with calcification and with aging. These results may indicate aorta stiffening and unwrapping with calcification and aging.


CONCLUSIONS
The authors have developed an objective tool to assess aorta morphology and aortic calcium plaques on CT scans that may be used to provide information about the presence of cardiovascular disease and its clinical impact in smokers.
Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115.
Sila
S
Kurugol
Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115.
Carolyn E
CE
Come
Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115.
Alejandro A
AA
Diaz
Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115.
James C
JC
Ross
Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado 80045.
Greg L
GL
Kinney
Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado 80045.
Jennifer L
JL
Black-Shinn
Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado 80045.
John E
JE
Hokanson
Los Angeles Biomedical Research Center at Harbor and UCLA Medical Center, Torrance, California 90502.
Matthew J
MJ
Budoff
Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115.
George R
GR
Washko
Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115.
Raul
R
San Jose Estepar
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001011:Aorta / Q000473:pathology*; D001027:Aortography / Q000379:methods*; D001331:Automation; D002114:Calcinosis / Q000000981:diagnostic imaging* / Q000473:pathology; D015331:Cohort Studies; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D014057:Tomography, X-Ray Computed