Abstract
Purpose: Statistical shape modeling provides a powerful tool for describing and analyzing human anatomy. By linearly combining the variance of the shape of a population of a given anatomical entity, statistical shape models (SSMs) identify its main modes of variation and may approximate the total variance of that population to a selected threshold, while reducing its dimensionality. Even though SSMs have been used for over two decades, they lack in characterization of their goodness of prediction, in particular when defining whether these models are actually representative for a given population.Methods: The current paper presents, to the authors' knowledge, the most extent lower limb anatomy shape model considering the pelvis, femur, patella, tibia, fibula, talus, and calcaneum to date. The present study includes the segmented training shapes (n = 542) obtained from 271 lower limb CT scans. The different models were evaluated in terms of accuracy, compactness, generalizability as well as specificity.Results: The size of training samples needed in each model so that it can be considered population covering was estimated to approximate around 200 samples, based on the generalizability properties of the different models. Simultaneously differences in gender and patterns in left-right asymmetry were identified and characterized. Size was found to be the most pronounced sexual discriminator whereas intra-individual variations in asymmetry were most pronounced at the insertion site of muscles.Conclusion: For models aimed at population covering descriptive studies, the number of training samples required should amount a sizeable 200 samples. The geometric morphometric method for sex discrimination scored excellent, however, it did not largely outperformed traditional methods based on discrete measures.
Highlights
The increasing use of and ease of access to 3D and 4D imaging technologies has had a tremendous impact on understanding the complexity of human anatomy by enabling detailed non-invasive exploration of the human body
With improved modalities, such as Multi-Detector/Multi-Slice Computed Tomography (MD/MSCT) and Magnetic Resonance Imaging (MRI) to visualize and describe skeletal anatomy, a growing interest in the description of the anatomical variation has emerged and scientific findings have been reported in numerous areas including anthropology, evolutionary biology, forensics, implant design, anatomy, epidemiology, and last but not least clinics, for the distinction of physiological vs. pathological anatomical variation (Audenaert, 2014)
Each case was represented by its averaged symmetrical consensus as well as the remaining asymmetry component
Summary
The increasing use of and ease of access to 3D and 4D imaging technologies has had a tremendous impact on understanding the complexity of human anatomy by enabling detailed non-invasive exploration of the human body With improved modalities, such as Multi-Detector/Multi-Slice Computed Tomography (MD/MSCT) and Magnetic Resonance Imaging (MRI) to visualize and describe skeletal anatomy, a growing interest in the description of the anatomical variation has emerged and scientific findings have been reported in numerous areas including anthropology, evolutionary biology, forensics, implant design, anatomy, epidemiology, and last but not least clinics, for the distinction of physiological vs pathological anatomical variation (Audenaert, 2014). These techniques have the potential for accurate parameterization of complex data such as an individual’s morphology or the description of the distribution of anatomy in the population
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