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.

Trigonocephaly in patients with metopic synostosis is corrected by fronto-orbital remodelling (FOR). The aim of this study was to quantitatively assess aesthetic outcomes of FOR by capturing 3D forehead scans of metopic patients pre- and post-operatively and comparing them with controls. Ten single-suture metopic patients undergoing FOR and 15 age-matched non-craniosynostotic controls were recruited at Great Ormond Street Hospital for Children (UK). Scans were acquired with a three-dimensional (3D) handheld camera and post-processed combining 3D imaging software. 3D scans were first used for cephalometric measurements. Statistical shape modelling was then used to compute the 3D mean head shapes of the three groups (FOR pre-op, post-op and controls). Head shape variations were described via principal component analysis (PCA). Cephalometric measurements showed that FOR significantly increased the forehead volume and improved trigonocephaly. This improvement was supported visually by pre- and post-operative computed mean 3D shapes and numerically by PCA (p < 0.001). Compared with controls, post-operative scans showed flatter foreheads (p < 0.001). In conclusion, 3D scanning followed by 3D statistical shape modelling enabled the 3D comparison of forehead shapes of metopic patients and non-craniosynostotic controls, and demonstrated that the adopted FOR technique was successful in correcting bitemporal narrowing but overcorrected the rounding of the forehead.

Computational models of congenital heart disease (CHD) have become increasingly sophisticated over the last 20 years. They can provide an insight into complex flow phenomena, allow for testing devices into patient-specific anatomies (pre-CHD or post-CHD repair) and generate predictive data. This has been applied to different CHD scenarios, including patients with single ventricle, tetralogy of Fallot, aortic coarctation and transposition of the great arteries. Patient-specific simulations have been shown to be informative for preprocedural planning in complex cases, allowing for virtual stent deployment. Novel techniques such as statistical shape modelling can further aid in the morphological assessment of CHD, risk stratification of patients and possible identification of new ‘shape biomarkers’. Cardiovascular statistical shape models can provide valuable insights into phenomena such as ventricular growth in tetralogy of Fallot, or morphological aortic arch differences in repaired coarctation. In a constant move towards more realistic simulations, models can also account for multiscale phenomena (eg, thrombus formation) and importantly include measures of uncertainty (ie, CIs around simulation results). While their potential to aid understanding of CHD, surgical/procedural decision-making and personalisation of treatments is undeniable, important elements are still lacking prior to clinical translation of computational models in the field of CHD, that is, large validation studies, cost-effectiveness evaluation and establishing possible improvements in patient outcomes.

Bitcoin is a decentralized, pseudonymous cryptocurrency that is one of the most used digital assets to date. Its unregulated nature and inherent anonymity of users have led to a dramatic increase in its use for illicit activities. This calls for the development of novel methods capable of characterizing different entities in the Bitcoin network.In this paper, a method to attack Bitcoin anonymity is presented, leveraging a novel cascading machine learning approach that requires only a few features directly extracted from Bitcoin blockchain data. Cascading, used to enrich entities information with data from previous classifications, led to considerably improved multi-class classification performance with excellent values of Precision close to 1.0 for each considered class. Final models were implemented and compared using different machine learning models and showed significantly higher accuracy compared to their baseline implementation.Our approach can contribute to the development of effective tools for Bitcoin entity characterization, which may assist in uncovering illegal activities.

OBJECTIVES This study aimed to explore aortic morphology and the associations between morphological features and cardiovascular function in a population of patients with bicuspid aortic valve, while further assessing differences between patients with repaired coarctation, patients with unrepaired coarctation and patients without coarctation. METHODS This is a single-centre retrospective study that included patients with available cardiovascular magnetic resonance imaging data and native bicuspid aortic valve diagnosis ( n = 525). A statistical shape analysis was performed on patients with a 3-dimensional magnetic imaging resonance (MRI) dataset ( n = 108), deriving 3-dimensional aortic reconstructions and computing a mean aortic shape (template) for the whole population as well as for the 3 subgroups of interest (no coarctation, repaired coarctation and unrepaired coarctation). Shape deformations (modes) were computed and correlated with demographic variables, 2-dimensional MRI measurements and volumetric and functional data. RESULTS Overall, the results showed that patients with coarctation tended towards a more Gothic arch architecture, with decreased ascending and increased descending aorta diameters, with the unrepaired-aortic coarctation subgroup exhibiting more ascending aorta dilation. Careful assessment of patients with repaired coarctation only revealed that a more Gothic arch, increased descending aorta dimensions and ascending aorta dilation were associated with reduced ejection fraction ( P ≤ 0.04), increased end-diastolic volume ( P ≤ 0.04) and increased ventricular mass ( P ≤ 0.02), with arch morphology distinguishing patients with and without recoarctation ( P = 0.05). CONCLUSIONS A statistical shape modelling framework was applied to a bicuspid aortic valve population revealing nuanced differences in arch morphology and demonstrating that morphological features, not immediately described by conventional measurements, can indicate those shape phenotypes associated with compromised function and thus possibly warranting closer follow-up.

Bone fragility is a concern for aged and diseased bone. Measuring bone toughness and understanding fracture properties of the bone are critical for predicting fracture risk associated with age and disease and for preclinical testing of therapies. A reference point indentation technique (BioDent) has recently been developed to determine bone's resistance to fracture in a minimally invasive way by measuring the indentation distance increase (IDI) between the first and last indentations over cyclic indentations in the same position. In this study, we investigate the relationship between fracture toughness KC and reference point indentation parameters (i.e. IDI, total indentation distance (TID) and creep indentation distance (CID)) in bones from 38 mice from six types (C57Bl/6, Balb, oim/oim, oim/+, Phospho1−/− and Phospho1 wild type counterpart). These mice bone are models of healthy and diseased bone spanning a range of fracture toughness from very brittle (oim/oim) to ductile (Phospho1−/−). Left femora were dissected, notched and tested in 3-point bending until complete failure. Contralateral femora were dissected and indented in 10 sites of their anterior and posterior shaft surface over 10 indentation cycles. IDI, TID and CID were measured. Results from this study suggest that reference point indentation parameters are not indicative of stress intensity fracture toughness in mouse bone. In particular, the IDI values at the anterior mid-diaphysis across mouse types overlapped, making it difficult to discern differences between mouse types, despite having extreme differences in stress intensity based toughness measures. When more locations of indentation were considered, the normalised IDIs could distinguish between mouse types. Future studies should investigate the relationship of the reference point indentation parameters for mouse bone in other material properties of the bone tissue in order to determine their use for measuring bone quality.