This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Background: Atrial fibrillation (AF) is an electrophysiological condition that increases the risk of stroke and mortality and diminishes the quality of life for aging populations. The best current method to evaluate the progression of AF and monitor the success of interventions is via an invasive intracardiac catheter-based electrical mapping procedure. Dr. Marrouche and the CARMA team have published recent findings indicating that the MRI image acquisition methods they have developed may provide a non-invasivie means to evaluate clinical characteristics of the tissue substrate that supports AF, as well as methods to detect changes in atrial tissue that result from ablation therapy. Rationale: The overarching technical goal of this DBP is to support the screening, management, treatment, and maintenance of people with atrial fibrillation with a range of computational tools. These tools will be useful for all stages of the disease and its treatment, will be simple and efficient to use, and will integrate all the tasks required for patient specific management into a single workflow. Questions: The entire basis for pre-ablation evaluation of fibrosis is based on segmentation and quantification of subtle features of delayed enhancement MRI, a process that will require innovative image processing and analysis to achieve. The CARMA team already makes daily use of Seg3D and drives many of the features that it contains. There is a pressing need for still more capabilities so that steps requiring considerable manual evaluation and specific medical experience can become at least semi-automated. Although Seg3D has streamlined the processing time, each case requires a file conversion, which introduces delays and increased chances of error. Design &Methods: The rationale and procedural goals of this DBP are as follows: (1) To develop software tools for the registration and segmentation of images from AF patients to be applied across all segments of the use of MRI in the management of AF patients;(2) To develop and validate algorithms and associated software for the quantitative analysis of pre-ablation fibrosis and post-ablation edema and scar;(3) To create compensation approaches for errors in position from heart and respiratory motion and their impact on MR images for use in real-time imaging of the heart during MRI guided ablation; and (4) To develop and evaluate integrated visualization schemes and software for use in real-time MRI guided AF ablation.