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BackgroundStatistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. ObjectiveTo solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. MethodsThe VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. ResultsTo illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. ConclusionsThe VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.

Background: The cornea plays a role in the refractive power of the eye, and when its natural curvature and thickness are compromised by diseases such as keratoconus or high myopia, this results in loss of visual acuity. Intracorneal rings (ICRs) were developed as a treatment option to restore the natural corneal curvature by implanting rings into tunnels cut within the corneal stroma. However, selecting and placing the appropriate ring can be difficult, and predicting refractive outcomes is challenging. Objective: The purpose of this study was to better understand the design parameters of the rings that determine postoperative refractive and mechanical outcomes. Methods: We developed an automated finite element simulation pipeline for ICR implantation and tested 300 variations of 20 ICRs. Results: The outcome of ICR was dominated by the vertical size of the ring; 84% of the change in corneal curvature can be attributed to the vertical size of the ring, while only 13% were attributed to the detailed cross-sectional shape of the ring. However, the cross-sectional shape of the ring is limited to the change in axial length and contact pressure between the ring and the cornea. The horizontal dimension of the ring plays only a minor role in the postoperative outcome. Conclusion: These results support Keraring's approach to ring scaling, in which only the vertical dimension of the ring is changed, while the horizontal dimension remains constant. Numerical models help to understand ICR outcomes, design implants, and personalize empirical nomograms to achieve more successful postoperative outcomes. [ABSTRACT FROM AUTHOR]

In surgical refractive interventions over-correction or under-correction still occur in 10-15 % of cases. Improved outcomes could be achieved by incorporating patient-specific corneal biomechanics into surgical planning. As a first step, this study mechanically characterizes and numerically simulates corneal lenticules harvested during a refractive intervention called Corneal Lenticule Extraction for Advanced Refractive Correction (CLEAR). These human corneal lenticules were mechanically tested in uniaxial extension in nasal-temporal and 45 deg orientations. An HGO material model that accounts for the unique collagen arrangement of the human cornea was developed and used to identify the material parameters using a finite element model of the experimental setup. The material parameters that best represent the experimental force/displacement were obtained by parameter estimation using Bayesian optimization. The uniaxial experiments performed on 3 patients did not show distinctive differences in orientation. The estimated material parameters fit well with the experimental data, representing a promising material model. In the future, Brillouin measurements will be performed on the CLEAR patients before lenticule extraction so that material parameters can be estimated in vivo, providing the surgeon with a patient specific-surgical planning tool.

Dynamic deformation events induced by osmosis or photochemical stiffening substantially influence geometrical and mechanical assessments in post-mortem corneas, therefore need to be carefully monitored in experimental settings. In this study, we employed optical coherence elastography (OCE) to quantify dynamic deformation processes at high resolution in freshly enucleated porcine corneas. Osmotic effects were studied by immerging n = 9 eyes in preservation media of three different tonicities. Dynamic processes underlying corneal cross-linking (CXL) were studied by subjecting n = 6 eyes to standard Dresden treatment, while three control groups were used. The entire procedures were performed under an OCE setup during up to 80 min, acquiring a volumetric scan every 20 s. Changes in OCE-derived axial deformations were incrementally calculated between consecutive scans. Preservation conditions had a strong influence on the observed strain patterns, which were consistent with the tonicity of the medium (swelling in hypotonic, deswelling in hypertonic environment). In the CXL group, we observed deswelling of the anterior stroma 10 min after starting the UV irradiation, which was not observed in any control group (p = 0.007). The presented results proved OCE to be a valuable technique to quantify subtle dynamic biomechanical alterations in the cornea resulting from CXL and preservation solutions. [ABSTRACT FROM AUTHOR]

The massive amount of human biological, imaging, and clinical data produced by multiple and diverse sources necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell-signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels, as well as their orchestration and links, are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof-of-concept study cases. Personalized simulations of the actual anatomy of a patient have been conducted. The hypermodel has also been applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin-based clinical decision support system and as the core of future in silico trial platforms, although additional retrospective adaptation and validation are necessary. [ABSTRACT FROM AUTHOR]