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Data from Single Photon Emission Computed Tomography (SPECT) studies are blurred by inevitable physical phenomena occurring during data acquisition. These errors may be compensated by means of reconstruction algorithms which take into account accurate physical models of the data acquisition procedure. Unfortunately, this approach involves high memory requirements as well as a high computational burden which cannot be afforded by the computer systems of SPECT acquisition devices. In this work the possibility of accessing High Performance Computing and Networking (HPCN) resources through a World Wide Web interface for the advanced reconstruction of SPECT data in a clinical environment was investigated. An iterative algorithm with an accurate model of the variable system response was ported on the Multiple Instruction Multiple Data (MIMD) parallel architecture of a Cray T3D massively parallel computer. The system was accessible even from low cost PC-based workstations through standard TCP/IP networking. A speedup factor of 148 was predicted by the benchmarks run on the Cray T3D. A complete brain study of 30 (64 x 64) slices was reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s which corresponds to an actual speed-up factor of 135. The technique was extended to a more accurate 3D modeling of the system response for a true 3D reconstruction of SPECT data; the reconstruction time of the same data set with this more accurate model was 5 min. This work demonstrates the possibility of exploiting remote HPCN resources from hospital sites by means of low cost workstations using standard communication protocols and an user-friendly WWW interface without particular problems for routine use.

It is well known that the quantitative potential of emission computed tomography (ECT) relies on the ability to compensate for resolution, attenuation and scatter effects. Reconstruction algorithms which are able to take these effects into account are highly demanding in terms of computing resources. The reported work aimed to investigate the use of a parallel high-performance computing platform for ECT reconstruction taking into account an accurate model of the acquisition of single-photon emission tomographic (SPET) data. An iterative algorithm with an accurate model of the variable system response was ported on the MIMD (Multiple Instruction Multiple Data) parallel architecture of a 64-node Cray T3D massively parallel computer. The system was organized to make it easily accessible even from low-cost PC-based workstations through standard TCP/IP networking. A complete brain study of 30 (64x64) slices could be reconstructed from a set of 90 (64x64) projections with ten iterations of the conjugate gradients algorithm in 9 s, corresponding to an actual speed-up factor of 135. This work demonstrated the possibility of exploiting remote high-performance computing and networking resources from hospital sites by means of low-cost workstations using standard communication protocols without particular problems for routine use. The achievable speed-up factors allow the assessment of the clinical benefit of advanced reconstruction techniques which require a heavy computational burden for the compensation effects such as variable spatial resolution, scatter and attenuation. The possibility of using the same software on the same hardware platform with data acquired in different laboratories with various kinds of SPET instrumentation is appealing for software quality control and for the evaluation of the clinical impact of the reconstruction methods.

A brain phantom is described that is characterized by a high anatomical definition and by the possibility of varying the internal contrast with the use of a single radioactive solution. The experimental work was done with a single-photon emission computerized tomographic (SPET) rotating camera. The phantom was used to study the contrast recovery of both the filtered back-projection and an iterative reconstruction algorithm. Moreover, it was also used to find a cross-calibration factor between activity concentrations in the SPET slices and an external reference.