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.

Introduction HR-pQCT is increasingly used to assess bone quality, fracture risk and anti-fracture interventions. The contribution of the operator has not been adequately accounted in measurement precision. Operators acquire a 2D projection (“scout view image”) and define the region to be scanned by positioning a “reference line” on a standard anatomical landmark. In this study, we (i) evaluated the contribution of positioning variability to in vivo measurement precision, (ii) measured intra- and inter-operator positioning variability, and (iii) tested if custom training software led to superior reproducibility in new operators compared to experienced operators. Methods To evaluate the operator in vivo measurement precision we compared precision errors calculated in 64 co-registered and non-co-registered scan-rescan images. To quantify operator variability, we developed software that simulates the positioning process of the scanner’s software. Eight experienced operators positioned reference lines on scout view images designed to test intra- and inter-operator reproducibility. Finally, we developed modules for training and evaluation of reference line positioning. We enrolled 6 new operators to participate in a common training, followed by the same reproducibility experiments performed by the experienced group. Results In vivo precision errors were up to three-fold greater (Tt.BMD and Ct.Th) when variability in scan positioning was included. Inter-operator precision errors were significantly greater than short-term intra-operator precision (p<0.001). New trained operators achieved comparable intra-operator reproducibility to experienced operators, and lower inter-operator reproducibility (p<0.001). Precision errors were significantly greater for the radius than for the tibia. Conclusion Operator reference line positioning contributes significantly to in vivo measurement precision and is significantly greater for multi-operator datasets. Inter-operator variability can be significantly reduced using a systematic training platform, now available online (http://webapps.radiology.ucsf.edu/refline/).

In multicenter studies and longitudinal studies that use two or more different quantitative computed tomography (QCT) imaging systems, anthropomorphic standardization phantoms (ASPs) are used to correct inter-scanner differences and allow pooling of data. In this study, in vivo imaging of 20 women on two imaging systems was used to evaluate inter-scanner differences in hip integral BMD (iBMD), trabecular BMD (tBMD), cortical BMD (cBMD), femoral neck yield moment (Mt) and yield force (Fy), and finite-element derived strength of the femur under stance (FEstance) and fall (FEfall) loading. Six different ASPs were used to derive inter-scanner correction equations. Significant (p < 0.05) inter-scanner differences were detected in all measurements except My and FEfall, and no ASP-based correction was able to reduce inter-scanner variability to corresponding levels of intra-scanner precision. Inter-scanner variability was considerably higher than intra-scanner precision, even in cases where the mean inter-scanner difference was statistically insignificant. A significant (p < 0.01) effect of body size on inter-scanner differences in BMD was detected, demonstrating a need to address the effects of body size on QCT measurements. The results of this study show that significant inter-scanner differences in QCT-based measurements of BMD and bone strength can remain even when using an ASP.

Abstract:Osteoarthritis is a degenerative disease affecting bones and cartilage especially in the human knee. In this context, cartilage thickness is an indicator for knee cartilage health. Thickness measurements are performed on medical images acquired in-vivo. Currently, there is no standard method agreed upon that defines a distance measure in articular cartilage. In this work, we present a comparison of different methods commonly used in literature. These methods are based on nearest neighbors, surface normal vectors, local thickness and potential field lines. All approaches were applied to manual segmentations of tibia and lateral and medial tibial cartilage performed by experienced raters. The underlying data were contrast agent-enhanced cone-beam C-arm CT reconstructions of one healthy subject's knee. The subject was scanned three times, once in supine position and two times in a standing weight-bearing position. A comparison of the resulting thickness maps shows similar distributions and high correlation coefficients between the approaches above 0.90. The nearest neighbor method results on average in the lowest cartilage thickness values, while the local thickness approach assigns the highest values. We showed that the different methods agree in their thickness distribution. The results will be used for a future evaluation of cartilage change under weight-bearing conditions.

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Development of novel implants in orthopaedic trauma surgery is based on limited datasets of cadaver trials or artificial bone models. A method has been developed whereby implants can be constructed in an evidence based method founded on a large anatomic database consisting of more than 2.000 datasets of bones extracted from CT scans. The aim of this study was the development and clinical application of an anatomically pre-contoured plate for the treatment of distal fibular fractures based on the anatomical database.48 Caucasian and Asian bone models (left and right) from the database were used for the preliminary optimization process and validation of the fibula plate. The implant was constructed to fit bilaterally in a lateral position of the fibula. Then a biomechanical comparison of the designed implant to the current gold standard in the treatment of distal fibular fractures (locking 1/3 tubular plate) was conducted. Finally, a clinical surveillance study to evaluate the grade of implant fit achieved was performed. The results showed that with a virtual anatomic database it was possible to design a fibula plate with an optimized fit for a large proportion of the population. Biomechanical testing showed the novel fibula plate to be superior to 1/3 tubular plates in 4-point bending tests. The clinical application showed a very high degree of primary implant fit. Only in a small minority of cases further intra-operative implant bending was necessary. Therefore, the goal to develop an implant for the treatment of distal fibular fractures based on the evidence of a large anatomical database could be attained. Biomechanical testing showed good results regarding the stability and the clinical application confirmed the high grade of anatomical fit.

Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments in science. Although attitudes are increasingly favorable, data reuse remains difficult due to lack of infrastructures, standards, and policies. The FAIR (findable, accessible, interoperable, reusable) principles aim to provide recommendations to increase data reuse. Because of the broad interpretation of the FAIR principles, maturity indicators are necessary to determine the FAIRness of a dataset. In this work, we propose a reproducible computational workflow to assess data FAIRness in the life sciences. Our implementation follows principles and guidelines recommended by the maturity indicator authoring group and integrates concepts from the literature. In addition, we propose a FAIR balloon plot to summarize and compare dataset FAIRness. We evaluated the feasibility of our method on three real use cases where researchers looked for six datasets to answer their scientific questions. We retrieved information from repositories (ArrayExpress, Gene Expression Omnibus, eNanoMapper, caNanoLab, NanoCommons and ChEMBL), a registry of repositories, and a searchable resource (Google Dataset Search) via application program interfaces (API) wherever possible. With our analysis, we found that the six datasets met the majority of the criteria defined by the maturity indicators, and we showed areas where improvements can easily be reached. We suggest that use of standard schema for metadata and the presence of specific attributes in registries of repositories could increase FAIRness of datasets.

Introduction High-resolution peripheral quantitative computed tomography (HR-pQCT) measures of bone do not account for anatomic variability in bone length: a 1-cm volume is acquired at a fixed offset from an anatomic landmark. Our goal was to evaluate HR-pQCT measurement variability introduced by imaging fixed vs. proportional volumes and to propose a standard protocol for relative anatomic positioning. Methods Double-length (2-cm) scans were acquired in 30 adults. We compared measurements from 1-cm subvolumes located at the default fixed offset, and the average %-of-length offset. The average position corresponded to 4.0% ± 1.1 mm for radius, and 7.2% ± 2.2 mm for tibia. We calculated the RMS difference in bone parameters and T-Scores to determine the measurement variability related to differences in limb length. We used anthropometric ratios to estimate the mean limb length for published HR-pQCT reference data, and then calculated mean %-of-length offsets. Results Variability between fixed vs. relative scan positions was highest in the radius, and for cortical bone in general (RMS difference Ct.Th = 19.5%), while individuals had T-score differentials as high as +3.0 SD (radius Ct.BMD). We estimated that average scan position for published HR-pQCT reference data corresponded to 4.0% at the radius, and 7.3% at tibia. Conclusion Variability in limb length introduces significant bias to HR-pQCT measures, confounding cross-sectional analyses and limiting the clinical application for individual assessment of skeletal status. We propose to standardize scan positioning using 4.0% and 7.3% of total bone length for the distal radius and tibia, respectively.