Abstract
The goal of this R01 application is to develop state-of-the-art, open-source software for image-based analysis of
skeletal kinematics. Worldwide, over 250 million people are affected by musculoskeletal disorders, including
arthritis, trauma, osteoporosis, and spine pathology, a number that is projected to increase as the population
ages. The in-depth understanding of normal joint function and the changes associated with aging, injury and
disease requires the ability to quantitatively measure skeletal kinematics. The current state-of-the art for
quantifying skeletal kinematics – especially the complex motion at the joint surface, called arthrokinematics – is
image-based object tracking performed with datasets from biplane videoradiography (BVR), and static and
dynamic computed tomography (3DCT and 4DCT, respectively). Regardless of the imaging modality, image-
based skeletal tracking involves image segmentation and bone model generation, bone image registration,
coordinate system selection, and data presentation. Software and computing infrastructure are critical for
accuracy and efficiency. The lack of “industry-standard” software or templates for workflow are major obstacles
to progress in the field. Laboratories use their own combination of commercial, public-domain, and custom-
written code. The current individualized implementation model is inefficient, duplicates effort, and impedes
collaboration, and, importantly, the sharing of software and technical advances. Recent focus workshops and
surveys demonstrate clear interest in better solutions. Accordingly, based on our longstanding expertise in
image-based tracking, we will develop an open source program for image-based skeletal motion tracking capable
of accepting as input all of the commonly used imaging modalities (videoradiography, 3DCT, and 4DCT). Our
long-term objective is to build a world-wide user base of collaborators and contributors to foster innovation and
inquiry in musculoskeletal research. In our first Aim we will partner with Kitware, Inc. an experienced and
successful open-source software development company, to refine and enhance Autoscoper, and integrate it into
the 3D Slicer platform to yield SlicerAutoscoperM (SAM). Autoscoper is an existing BVR software program
developed at Brown University to semi-automatically align skeletal structures (bones and implants) to x-ray
videos. SAM will be refined with input from the project’s co-investigators and an established core user base. In
Aim 2 we will determine the agreement and accuracy of SAM by comparing its outputs to those of obtained using
legacy methods, using data from existing studies performed in four independent laboratories. Finally, in Aim 3
we will use a synthetic model to evaluate the accuracy of SAM in round-robin testing in four labs (Brown,
Cleveland Clinic, Mayo Clinic, and Queens Universiyt) using image data from 3DCT, 4DCT and BVR. The work
outlined in this proposal will yield a state-of-the-art, open-source software solution that will accept datasets from
multiple imaging modalities. SAM will simplify and improve image-based skeletal tracking, facilitate the sharing
of novel analysis algorithms, methodologies, and data, and hasten the translation to clinical implementation.