Rapidly increasing utilization of X-ray computed tomography (CT) has heightened concerns about the collective radiation exposure to the population as a whole, and about potential risks to patients undergoing recurrent imaging for chronic conditions or persistent complaints. These concerns have motivated a great deal of attention to practical radiation-dose-reduction strategies. Current dose reduction approaches, such as iterative reconstruction or improved detector technology, each offer only moderate dose reductions up to 30- 40% below the prior state of the art. We will pursue more-than-incremental improvements in radiation dose by changing the current paradigm of CT data acquisition and image reconstruction: a reduced number of X-ray projections will be acquired, in an angularly subselected pattern associated with random-appearing or incoherent artifacts which will then be removed by compressed-sensing (CS) reconstruction algorithms. Several groups have shown the potential of CS to reconstruct undersampled CT data in simulations, but no practical means of incoherent undersampling has yet been demonstrated in the challenging physical environment of a rapidly rotating CT gantry. In this project, we will develop and evaluate novel approaches for rapid and incoherent interruption of the X-ray source on the CT gantry which, when combined with our sparsity-based CS reconstruction algorithms, will enable reconstruction of high-quality images from a markedly reduced number of projections. In particular, we will investigate a novel moving multihole collimator design which will block X-rays directed towards different subsets of detectors at different gantry angles. We have already shown these approaches to be capable of order-of-magnitude dose reductions in preliminary simulations in both phantoms and human subjects, but in order to evaluate our methods in actual practice, we will work closely with Siemens Medical Solutions, who will dedicate an experimental test bay at their CT plant in Forchheim to develop a practical test system as a prelude to functional clinical scanner prototypes. Successful completion of the aims of this study will lay the groundwork for a paradigm-changing approach to CT data acquisition and reconstruction, enabling heretofore inaccessible dose reductions.
Specific Aims are as follows: 1. Validate the dose-reduction potential of incoherent interrupted-beam acquisition and sparse reconstruction using realistic simulations carefully designed to incorporate the physics of the modified acquisition process. 2. Evaluate achievable dose reduction with preserved image quality using retrospective undersampling of clinical scan data (using the model from Aim 1), and compare with gold-standard dose reduction methods. 3. Develop a test system for interrupted-beam CT acquisition in collaboration with our industry partner, and evaluate performance in phantoms.
In this project, we will evaluate the feasibility of a new paradigm for X-ray computed tomography (CT) which will enable dramatic reductions in radiation exposure while preserving diagnostic image quality. Rather than gathering X-ray projections continuously as the CT gantry rotates around the patient, we will develop new technology to interrupt the X-ray beam at rapid intervals (thereby reducing radiation dose), and will apply advanced 'compressed sensing' algorithms to eliminate resulting image errors. This approach will be tested not only in realistic simulations, but also, for the first time, in actual practice, through collaborations with an industry partner who will modify a state-of-the-art clinicl CT scanner for this purpose.
