Improvement in sampling and modulation of multiplexing with temporal shuttering of adaptable apertures in a brain-dedicated multi-pinhole SPECT system

Correction of multiplexing artefacts in multi-pinhole SPECT through temporal shuttering, de-multiplexing of projections, and alternating reconstruction

Objective.Single-photon emission computed tomography (SPECT) with pinhole collimators can provide high-resolution imaging, but is often limited by low sensitivity. Acquiring projections simultaneously through multiple pinholes affords both high resolution and high sensitivity. However, the overlap of projections from different pinholes on detectors, known as multiplexing, has been shown to cause artefacts which degrade reconstructed images.Approach.Multiplexed projection sets were considered here using an analytic simulation model of AdaptiSPECT-C-a brain-dedicated multi-pinhole SPECT system. AdaptiSPECT-C has fully adaptable aperture shutters, so can acquire projections with a combination of multiplexed and non-multiplexed frames using temporal shuttering. Two strategies for reducing multiplex artefacts were considered: an algorithm to de-multiplex projections, and an alternating reconstruction strategy for projections acquired with a combination of multiplexed and non-multiplexed frames. Geometric and anthropomorphic digital phantoms were used to assess a number of metrics.Main results.Both de-multiplexing strategies showed a significant reduction in image artefacts and improved fidelity, image uniformity, contrast recovery and activity recovery (AR). In all cases, the two de-multiplexing strategies resulted in superior metrics to those from images acquired with only mux-free frames. The de-multiplexing algorithm provided reduced image noise and superior uniformity, whereas the alternating strategy improved contrast and AR.Significance.The use of these de-multiplexing algorithms means that multi-pinhole SPECT systems can acquire projections with more multiplexing without degradation of images.

Mesh modeling of system geometry and anatomy phantoms for realistic GATE simulations and their inclusion in SPECT reconstruction

Objective.Monte-Carlo simulation studies have been essential for advancing various developments in single photon emission computed tomography (SPECT) imaging, such as system design and accurate image reconstruction. Among the simulation software available, Geant4 application for tomographic emission (GATE) is one of the most used simulation toolkits in nuclear medicine, which allows building systems and attenuation phantom geometries based on the combination of idealized volumes. However, these idealized volumes are inadequate for modeling free-form shape components of such geometries. Recent GATE versions alleviate these major limitations by allowing users to import triangulated surface meshes.Approach.In this study, we describe our mesh-based simulations of a next-generation multi-pinhole SPECT system dedicated to clinical brain imaging, called AdaptiSPECT-C. To simulate realistic imaging data, we incorporated in our simulation the XCAT phantom, which provides an advanced anatomical description of the human body. An additional challenge with the AdaptiSPECT-C geometry is that the default voxelized XCAT attenuation phantom was not usable in our simulation due to intersection of objects of dissimilar materials caused by overlap of the air containing regions of the XCAT beyond the surface of the phantom and the components of the imaging system.Main results.We validated our mesh-based modeling against the one constructed by idealized volumes for a simplified single vertex configuration of AdaptiSPECT-C through simulated projection data of123I-activity distributions. We resolved the overlap conflict by creating and incorporating a mesh-based attenuation phantom following a volume hierarchy. We then evaluated our reconstructions with attenuation and scatter correction for projections obtained from simulation consisting of mesh-based modeling of the system and the attenuation phantom for brain imaging. Our approach demonstrated similar performance as the reference scheme simulated in air for uniform and clinical-like123I-IMP brain perfusion source distributions.Significance.This work enables the simulation of complex SPECT acquisitions and reconstructions for emulating realistic imaging data close to those of actual patients.

Cerebral SPECT imaging with different acquisition schemes using varying levels of multiplexing versus sensitivity in an adaptive multi-pinhole brain-dedicated scanner

Application of multi-pinhole collimator in pinhole-based SPECT increases detection sensitivity. The presence of multiplexing in projection images due to the usage of multiple pinholes can further improve the sensitivity at the cost of adding data ambiguity. We are developing a next-generation adaptive brain-dedicated SPECT system -AdaptiSPECT-C. The AdaptiSPECT-C can adapt the multiplexing level and system sensitivity using adaptable pinhole modules. In this study, we investigated the performance of 4 data acquisition schemes with different multiplexing levels and sensitivities on cerebral SPECT imaging. Schemes #1, #2, and #3 have <1%, 67%, and 31% overall multiplexing, respectively, while the 4th scheme without multiplexing is considered as ground truth. The ground-truth and schemes #1-3 have 1.0, 1.7, 5.1, and 4.0 times higher sensitivity, respectively, compared to a dual-headed parallel-hole SPECT system at matched spatial resolution. A customized XCAT brain perfusion digital phantom emulating the distribution of I-123 N-isopropyl iodoamphetamine (IMP) in a 99th percentile size male was used for simulations. Data acquisition for each scheme was performed at two count levels (low-count and high-count relative to the recommended clinical count level). The normalized root-mean-square error (NRMSE) for schemes #1, #2, and #3 with the low-count (high-count) scenario showed 11%, 4%, and 5% (10%, 5%, and 6%) deviation, respectively, from that of the multiplex-free ground truth. For both the low-count and high-count scenarios, scheme #1 resulted in the least accurate activity ratio (AR) for almost all the analyzed gray-matter brain regions. Further schemes #2 or #3 led to the most accurate AR values with both low-count and high-count scenarios for all the analyzed gray-matter regions. It was thus observed that even with this large head size which leads to significant multiplexing levels, the higher sensitivity from multiplexing could to some extent mitigate the data ambiguity and be translated into reconstructed images of higher quality.