[Methods and materials used for construction of anatomic models].
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A simple anatomic model for studying the scintigraphic appearance of various skeletal structures is described. The technique makes use of the fact that technitium pyrophosphate uptake in bone occurs by chemisorption to the surface of crystals in the bone matrix. By soaking clean bones in solutions of technetium pyrophosphate they can be rendered radioactive and subsequently studied by various imaging techniques.
Some clinical applications, such as surgical planning, require volumetric models of anatomical structures represented as a set of tetrahedra. A practical method of constructing anatomical models from medical images is presented. The method starts with a set of contours segmented from the medical images by a clinician and produces a model that has high fidelity with the contours. Unlike most modeling methods, the contours are not restricted to lie on parallel planes. The main steps are a 3D Delaunay tetrahedralization, culling of non-object tetrahedra, and refinement of the tetrahedral mesh. The result is a high-quality set of tetrahedra whose surface points are guaranteed to match the original contours. The key is to use the distance map and bit volume structures that were created along with the contours. The method is demonstrated on computed tomography, MRI and 3D ultrasound data. Models of 170,000 tetrahedra are constructed on a standard workstation in approximately 10s. A comparison with related methods is also provided.
An anatomical model for teaching the practical aspects of routine oral surgery in a clinical or laboratory environment, is described. Replaceable sections allow the model to be rapidly re-used so that successive students may practise procedures such as incisions, flap reflection, bone removal, tooth removal, apicectomy and suturing. Keeping the cost per procedure to a minimum was considered to be of fundamental importance and this has been achieved through the use of 'factory produced' replacement parts.
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Comparative musculoskeletal modeling represents a tool to understand better how motor system parameters are fine-tuned for specific behaviors. Frog jumping is a behavior in which the physical properties of the body and musculotendon actuators may have evolved specifically to extend the limits of performance. Little is known about how the joints of the frog contribute to and limit jumping performance. To address these issues, we developed a skeletal model of the frog Rana pipiens that contained realistic bones, joints and body-segment properties. We performed forward dynamic simulations of jumping to determine the minimal number of joint degrees of freedom required to produce maximal-distance jumps and to produce jumps of varied take-off angles. The forward dynamics of the models was driven with joint torque patterns determined from inverse dynamic analysis of jumping in experimental frogs. When the joints were constrained to rotate in the extension-flexion plane, the simulations produced short jumps with a fixed angle of take-off. We found that, to produce maximal-distance jumping, the skeletal system of the frog must minimally include a gimbal joint at the hip (three rotational degrees of freedom), a universal Hooke's joint at the knee (two rotational degrees of freedom) and pin joints at the ankle, tarsometatarsal, metatarsophalangeal and iliosacral joints (one rotational degree of freedom). One of the knee degrees of freedom represented a unique kinematic mechanism (internal rotation about the long axis of the tibiofibula) and played a crucial role in bringing the feet under the body so that maximal jump distances could be attained. Finally, the out-of-plane degrees of freedom were found to be essential to enable the frog to alter the angle of take-off and thereby permit flexible neuromotor control. The results of this study form a foundation upon which additional model subsystems (e.g. musculotendon and neural) can be added to test the integrative action of the neuromusculoskeletal system during frog jumping.
INTRODUCTION: The use of computer-generated 3-dimensional (3-D) anatomical models to teach anatomy has proliferated. However, there is little evidence that these models are educationally effective. The purpose of this study was to test the educational effectiveness of a computer-generated 3-D model of the middle and inner ear. METHODS: We reconstructed a fully interactive model of the middle and inner ear from a magnetic resonance imaging scan of a human cadaver ear. To test the model's educational usefulness, we conducted a randomised controlled study in which 28 medical students completed a Web-based tutorial on ear anatomy that included the interactive model, while a control group of 29 students took the tutorial without exposure to the model. At the end of the tutorials, both groups were asked a series of 15 quiz questions to evaluate their knowledge of 3-D relationships within the ear. RESULTS: The intervention group's mean score on the quiz was 83%, while that of the control group was 65%. This difference in means was highly significant (P < 0.001). DISCUSSION: Our findings stand in contrast to the handful of previous randomised controlled trials that evaluated the effects of computer-generated 3-D anatomical models on learning. The equivocal and negative results of these previous studies may be due to the limitations of these studies (such as small sample size) as well as the limitations of the models that were studied (such as a lack of full interactivity). Given our positive results, we believe that further research is warranted concerning the educational effectiveness of computer-generated anatomical models.
Anatomical spatial concepts are indispensable in educational and clinical discourse, yet a system for representing these concepts has not been proposed. Guided by explicit principles and definitions of the Digital Anatomist Foundational Model, we developed an ontology of spaces, surfaces, lines and points that are associated with anatomical structures. Ontologies for Anatomical Structure and Anatomical Spatial Entity were instantiated for the thorax, abdomen, pelvis and perineum. Representing the concepts in--part of--hierarchies as well, provided formative evaluation of the classification. We invite empirical evaluation of the Foundational Model through its use for educational and clinical applications.
Anatomical data and models for the human shoulder musculo-skeletal system are developed with the intent of quantifying physiological subcomponents of a model-based multi-axis prosthetic limb control scheme which has heretofore been implemented empirically. Part I presents the controller formulation, the surface descriptions of the muscles (and bones), and the centroidal trajectory data of the muscles. The data partially quantify the muscle modelling components of the controller, and set the stage for the analysis of the force-to-moment anatomical conversion factors of Part II.
A framework for modeling and predicting anatomical deformations is presented, and tested on simulated images. Although a variety of deformations can be modeled in this framework, emphasis is placed on surgical planning, and particularly on modeling and predicting changes of anatomy between preoperative and intraoperative positions, as well as on deformations induced by tumor growth. Two methods are examined. The first is purely shape-based and utilizes the principal modes of co-variation between anatomy and deformation in order to statistically represent deformability. When a patient's anatomy is available, it is used in conjunction with the statistical model to predict the way in which the anatomy will/can deform. The second method is related, and it uses the statistical model in conjunction with a biomechanical model of anatomical deformation. It examines the principal modes of co-variation between shape and forces, with the latter driving the biomechanical model, and thus predicting deformation. Results are shown on simulated images, demonstrating that systematic deformations, such as those resulting from change in position or from tumor growth, can be estimated very well using these models. Estimation accuracy will depend on the application, and particularly on how systematic a deformation of interest is.
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Clinical procedures have traditionally been taught at the bedside, in the morgue and in the animal lab. Augmented Reality (AR) technology (the merging of virtual reality and real objects or patients) provides a new method for teaching clinical and surgical procedures. Improved patient safety is a major advantage. We describe a system which employs AR technology to teach endotracheal intubation, using the Visible Human datasets, as well as MR images from live patient volunteers.
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