ArticleBMC medical imaging2016
A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.
Article in BMC medical imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
55 citing papers in PubMed.
- Linking shape and clinical outcomes: Statistical shape model of Bidirectional Glenn connection in congenital single ventricle patients.PLOS digital health · 2026Article
- Right Ventricular Outflow Tract and Pulmonary Artery Strains During the Cardiac Cycle Prior to Pulmonary Valve Replacement.Pediatric cardiology · 2026Article
- The Case for Interpretable Geometry: Statistical Shape Models vs. Curvature-Based Descriptors in Aortic Disease Classification.medRxiv : the preprint server for health sciences · 2026Article
- Unveiling sex dimorphism in the healthy cardiac anatomy: Fundamental differences between male and female heart shapes.The Journal of physiology · 2026Article
- Full-field surrogate modeling of cardiac electrophysiology encoding geometric variability.Computer methods in applied mechanics and engineering · 2026Article
- Article
- Prediction of Rotator Cuff Muscle Fibre Orientations Using a Population-Averaged Atlas Generated With Anatomical and Diffusion-Weighted Magnetic Resonance Images.NMR in biomedicine · 2025Article
- Changes in abdominal subcutaneous adipose tissue thickness associate with disease and anthropometric factors.International journal of obesity (2005) · 2025Article
- Morphology and calcification characterization in patients undergoing TAVI: A 3D statistical shape modelling study.PLOS digital health · 2025Article
- Vascular Flow Phantom of A Cohort-Based Averaged Abdominal Aortic Aneurysm: Design, Fabrication and Characterization.Annals of biomedical engineering · 2025Article
- Generation of a virtual cohort of TAVI patients for in silico trials: a statistical shape and machine learning analysis.Medical & biological engineering & computing · 2025Article
- Impact of aortic morphology on VA-ECMO performance: a combined statistical shape modeling and CFD approach.Frontiers in bioengineering and biotechnology · 2025Article
- OpenHands: An Open-Source Statistical Shape Model of the Finger Bones.Annals of biomedical engineering · 2024Article
- A 3D Statistical Shape Model of the Right Ventricular Outflow Tract in Pulmonary Valve Replacement Patients Post-Surgical Repair.Journal of cardiovascular development and disease · 2024Article
- Machine Learning and Statistical Shape Modelling Methodologies to Assess Vascular Morphology before and after Aortic Valve Replacement.Journal of clinical medicine · 2024Article
- OPTIMIZATION-DRIVEN STATISTICAL MODELS OF ANATOMIES USING RADIAL BASIS FUNCTION SHAPE REPRESENTATION.Proceedings. IEEE International Symposium on Biomedical Imaging · 2024Article
- Understanding the influence of surgical parameters on craniofacial surgery outcomes: a computational study.Royal Society open science · 2024Article
- Fetal face shape analysis from prenatal 3D ultrasound images.Scientific reports · 2024Article
- Kidney shape statistical analysis: associations with disease and anthropometric factors.BMC nephrology · 2023Article
- Mesh2SSM: From Surface Meshes to Statistical Shape Models of Anatomy.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.