BackgroundMedical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements.MethodsSteps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient’s anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters.ResultsThe computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors.ConclusionsThe suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s12880-016-0142-z) contains supplementary material, which is available to authorized users.

Independently of hemodynamically important arch obstruction or residual aortic coarctation, specific aortic arch shape features late after successful aortic coarctation repair seem to be associated with worse left ventricular function. Analyzing 3-dimensional shape information via statistical shape modeling can be an adjunct to long-term risk assessment in patients after aortic coarctation repair.

Three-dimensional (3D) imaging is an important tool for diagnostics, surgical planning, and evaluation of surgical outcomes in craniofacial procedures. Gold standard for acquiring 3D imaging is computed tomography that entails ionizing radiations and, in young children, a general anaesthesia. Three-dimensional photographic imaging is an alternative method to assess patients who have undergone calvarial reconstructive surgery. The aim of this study was to assess the utility of 3D handheld scanning photography in a cohort of patients who underwent spring-assisted correction surgery for scaphocephaly. Pre- and postoperative 3D scans acquired in theater and at the 3-week follow-up in clinic were postprocessed for 9 patients. Cephalic index (CI), head circumference, volume, sagittal length, and coronal width over the head at pre-op, post-op, and follow-up were measured from the 3D scans. Cephalic index from 3D scans was compared with measurements from planar x-rays. Statistical shape modeling (SSM) was used to calculate the 3D mean anatomical head shape of the 9 patients at the pre-op, post-op, and follow-up. No significant differences were observed in the CI between 3D and x-ray. Cephalic index, volume, and coronal width increased significantly over time. Mean shapes from SSM visualized the overall and regional 3D changes due to the expansion of the springs in situ. Three-dimensional handheld scanning followed by SSM proved to be an efficacious and practical method to evaluate 3D shape outcomes after spring-assisted cranioplasty in individual patients and the population.