TY - JOUR
T1 - Learning the Hidden Signature of Fetal Arch Anatomy
T2 - a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta
AU - Hermida, Uxio
AU - van Poppel, Milou P.M.
AU - Lloyd, David F.A.
AU - Steinweg, Johannes K.
AU - Vigneswaran, Trisha V.
AU - Simpson, John M.
AU - Razavi, Reza
AU - De Vecchi, Adelaide
AU - Pushparajah, Kuberan
AU - Lamata, Pablo
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2023/6
Y1 - 2023/6
N2 - Neonatal coarctation of the aorta (CoA) is a common congenital heart defect. Its antenatal diagnosis remains challenging, and its pathophysiology is poorly understood. We present a novel statistical shape modeling (SSM) pipeline to study the role and predictive value of arch shape in CoA in utero. Cardiac magnetic resonance imaging (CMR) data of 112 fetuses with suspected CoA was acquired and motion-corrected to three-dimensional volumes. Centerlines from fetal arches were extracted and used to build a statistical shape model capturing relevant anatomical variations. A linear discriminant analysis was used to find the optimal axis between CoA and false positive cases. The CoA shape risk score classified cases with an area under the curve of 0.907. We demonstrate the feasibility of applying a SSM pipeline to three-dimensional fetal CMR data while providing novel insights into the anatomical determinants of CoA and the relevance of in utero arch anatomy for antenatal diagnosis of CoA. Graphical abstract: [Figure not available: see fulltext.]
AB - Neonatal coarctation of the aorta (CoA) is a common congenital heart defect. Its antenatal diagnosis remains challenging, and its pathophysiology is poorly understood. We present a novel statistical shape modeling (SSM) pipeline to study the role and predictive value of arch shape in CoA in utero. Cardiac magnetic resonance imaging (CMR) data of 112 fetuses with suspected CoA was acquired and motion-corrected to three-dimensional volumes. Centerlines from fetal arches were extracted and used to build a statistical shape model capturing relevant anatomical variations. A linear discriminant analysis was used to find the optimal axis between CoA and false positive cases. The CoA shape risk score classified cases with an area under the curve of 0.907. We demonstrate the feasibility of applying a SSM pipeline to three-dimensional fetal CMR data while providing novel insights into the anatomical determinants of CoA and the relevance of in utero arch anatomy for antenatal diagnosis of CoA. Graphical abstract: [Figure not available: see fulltext.]
KW - Clinical Biomarker
KW - Computational Anatomy
KW - Congenital Heart Disease
KW - Machine Learning
KW - Magnetic Resonance Imaging
KW - Statistical Shape Modeling
UR - http://www.scopus.com/inward/record.url?scp=85140832772&partnerID=8YFLogxK
U2 - 10.1007/s12265-022-10335-9
DO - 10.1007/s12265-022-10335-9
M3 - Article
AN - SCOPUS:85140832772
SN - 1937-5387
VL - 16
SP - 738
EP - 747
JO - Journal of Cardiovascular Translational Research
JF - Journal of Cardiovascular Translational Research
IS - 3
ER -