Aswin Mathews

Image reconstruction and system modeling techniques for virtual-pinhole PET insert systems

Virtual-pinhole PET (VP-PET) imaging is a new technology in which one or more high-resolution detector modules are integrated into a conventional PET scanner with lower resolution detectors. It can locally enhance the spatial resolution and contrast recovery near the add-on detectors, and depending on the configuration, may also increase the sensitivity of the system. This novel scanner geometry makes the reconstruction problem more challenging compared to the reconstruction of data from a stand-alone PET scanner, as new techniques are needed to model and account for the non-standard acquisition. In this paper, we present a general framework for fully 3D modeling of an arbitrary VP-PET insert system. The model components are incorporated into a statistical reconstruction algorithm to estimate an image from the multi-resolution data. For validation, we apply the proposed model and reconstruction approach to one of our custom-built VP-PET systems-a half-ring insert device integrated into a clinical PET/CT scanner. Details regarding the most important implementation issues are provided. We show that the proposed data model is consistent with the measured data, and that our approach can lead to reconstructions with improved spatial resolution and lesion detectability.

An image reconstruction framework for arbitrary positron emission tomography geometries

We are investigating a variety of custom system geometries for different PET applications. These geometries have detectors of varying sizes, and detection efficiency, placed at different locations in 3D space. To evaluate the performance of these unconventional geometries require the development of a general purpose reconstruction framework that is easy to adapt to any geometry. This enables investigation of optimal application-specific PET systems.

Investigation of breast cancer detectability using PET insert with whole-body and zoom-in imaging capability

Traditional whole-body PET scanner is limited in resolution due to large detector crystal size, finite positron range and non-collinearity of annihilation photons. Our lab has developed a prototype half ring insert PET system that can improve resolution and radionuclide contrast recovery by using (1) smaller size of the detector crystals (2) virtual pinhole PET geometry obtained by placing the insert close to the imaging subject. This design allows for zooming-in to an area of interest while still maintaining the scanners whole-body imaging capability. To find the limits of the image resolution and contrast recovery, we performed a set of Monte Carlo simulations for a clinical PET system with and without half ring insert. The reconstructed images show the improvement in image resolution, with 3 mm diameter tumors resolvable with insert at a contrast ratio of 9∶1, compared to scanner without insert where smallest tumors resolvable was 6 mm.

A simultaneous beta and coincidence-gamma imaging system for plant leaves

Positron emitting isotopes, such as (11)C, (13)N, and (18)F, can be used to label molecules. The tracers, such as (11)CO2, are delivered to plants to study their biological processes, particularly metabolism and photosynthesis, which may contribute to the development of plants that have a higher yield of crops and biomass. Measurements and resulting images from PET scanners are not quantitative in young plant structures or in plant leaves due to poor positron annihilation in thin objects. To address this problem we have designed, assembled, modeled, and tested a nuclear imaging system (simultaneous beta-gamma imager). The imager can simultaneously detect positrons ([Formula: see text]) and coincidence-gamma rays (γ). The imaging system employs two planar detectors; one is a regular gamma detector which has a LYSO crystal array, and the other is a phoswich detector which has an additional BC-404 plastic scintillator for beta detection. A forward model for positrons is proposed along with a joint image reconstruction formulation to utilize the beta and coincidence-gamma measurements for estimating radioactivity distribution in plant leaves. The joint reconstruction algorithm first reconstructs beta and gamma images independently to estimate the thickness component of the beta forward model and afterward jointly estimates the radioactivity distribution in the object. We have validated the physics model and reconstruction framework through a phantom imaging study and imaging a tomato leaf that has absorbed (11)CO2. The results demonstrate that the simultaneously acquired beta and coincidence-gamma data, combined with our proposed joint reconstruction algorithm, improved the quantitative accuracy of estimating radioactivity distribution in thin objects such as leaves. We used the structural similarity (SSIM) index for comparing the leaf images from the simultaneous beta-gamma imager with the ground truth image. The jointly reconstructed images yield SSIM indices of 0.69 and 0.63, whereas the separately reconstructed beta alone and gamma alone images had indices of 0.33 and 0.52, respectively.

A generalized reconstruction framework for unconventional PET systems.

PURPOSE Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels. METHODS The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation-maximization. System geometry can be specified using a simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddons algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features. RESULTS Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries. CONCLUSIONS This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations.

Preliminary results from a portable PET probe system with fast image reconstruction

We are developing a Point-Of-Care PET (POC-PET) imaging system platform that consists of one or more movable probe detectors in coincidence with a detector-array behind a patient. The probes are hand movable so that the operator can control the probe trajectory freely to achieve optimal coverage and sensitivity for patient-specific imaging tasks. This platform does not require a conventional full ring geometry, and as such it can be built portable and low cost for bed-side or intraoperative imaging. We developed a prototype that consists of a compact high resolution MPPC detector probe and a half ring of conventional detectors. The probe detector has 20×20 crystals of 0.74×0.74×3.0 mm3 each, in 0.8 mm pitches, read out by a MPPC array. The probe is fixed to a Microscribe device, which tracks the location and orientation of the probe in 3D space as it moves. A fully 3D list-mode TOF (Time-Of-Flight) image reconstruction algorithm has been developed to incorporate the dynamically changing geometry information acquired from the Microscribe. The algorithm is implemented on GPU to achieve fast reconstruction in the order of seconds, under practical count rate situations. Further Monte Carlo simulations show that the resolvability of 4 mm rods under practical contrast ratio could be achieved if the scanning trajectory is well designed.