An emission-based technique for obtaining attenuation correction data for myocardial SPECT studies

Attenuation correction in emission tomography using the emission data--A review

The problem of attenuation correction (AC) for quantitative positron emission tomography (PET) had been considered solved to a large extent after the commercial availability of devices combining PET with computed tomography (CT) in 2001; single photon emission computed tomography (SPECT) has seen a similar development. However, stimulated in particular by technical advances toward clinical systems combining PET and magnetic resonance imaging (MRI), research interest in alternative approaches for PET AC has grown substantially in the last years. In this comprehensive literature review, the authors first present theoretical results with relevance to simultaneous reconstruction of attenuation and activity. The authors then look back at the early history of this research area especially in PET; since this history is closely interwoven with that of similar approaches in SPECT, these will also be covered. We then review algorithmic advances in PET, including analytic and iterative algorithms. The analytic approaches are either based on the Helgason-Ludwig data consistency conditions of the Radon transform, or generalizations of John's partial differential equation; with respect to iterative methods, we discuss maximum likelihood reconstruction of attenuation and activity (MLAA), the maximum likelihood attenuation correction factors (MLACF) algorithm, and their offspring. The description of methods is followed by a structured account of applications for simultaneous reconstruction techniques: this discussion covers organ-specific applications, applications specific to PET/MRI, applications using supplemental transmission information, and motion-aware applications. After briefly summarizing SPECT applications, we consider recent developments using emission data other than unscattered photons. In summary, developments using time-of-flight (TOF) PET emission data for AC have shown promising advances and open a wide range of applications. These techniques may both remedy deficiencies of purely MRI-based AC approaches in PET/MRI and improve standalone PET imaging.

Attenuation correction for lung SPECT: evidence of need and validation of an attenuation map derived from the emission data

PURPOSE

The aim of our study was to investigate the importance of attenuation correction (AC) in reconstructed and reprojected images on lung SPECT studies.

METHODS

Simulation studies were undertaken to evaluate the influence of AC on defect-to-normal ratios (D/N), to demonstrate the influence of errors in the correction map values and to detect lung boundaries used for AC. The use of a synthetic map (SM) for AC of the clinical data was also evaluated and the results compared with those obtained with data derived from CT (CTM). Additionally, the role of AC in reprojected SPECT data was assessed and level of noise on the 'planar-like' images was measured.

RESULTS

Phantom studies showed that AC markedly affects the D/N ratio. However, variations in micro values typical of those found in clinical studies resulted in relatively small changes in results. Eroded and dilated conditions did not cause any significant effect on D/N. The level of noise in the reprojected images is reduced in comparison with real planar data. Clinical SPECT/CT data reconstructed with AC using CTM and SM showed an excellent correlation between the two methods.

CONCLUSION

AC improves D/N in lung SPECT studies, thus potentially enhancing the diagnostic capability of the method. The use of a synthetic map for AC is feasible, avoiding the need for an additional procedure and the increased radiation dose involved. Planar-like images generated from reprojected SPECT data are well matched to normal planar images provided AC is performed and attenuation included in the reprojection.

An EM algorithm for estimating SPECT emission and transmission parameters from emissions data only

A maximum-likelihood (ML) expectation-maximization (EM) algorithm (called EM-IntraSPECT) is presented for simultaneously estimating single photon emission computed tomography (SPECT) emission and attenuation parameters from emission data alone. The algorithm uses the activity within the patient as transmission tomography sources, with which attenuation coefficients can be estimated. For this initial study, EM-IntraSPECT was tested on computer-simulated attenuation and emission maps representing a simplified human thorax as well as on SPECT data obtained from a physical phantom. Two evaluations were performed. First, to corroborate the idea of reconstructing attenuation parameters from emission data, attenuation parameters (mu) were estimated with the emission intensities (lambda) fixed at their true values. Accurate reconstructions of attenuation parameters were obtained. Second, emission parameters lambda and attenuation parameters mu were simultaneously estimated from the emission data alone. In this case there was crosstalk between estimates of lambda and mu and final estimates of lambda and mu depended on initial values. Estimates degraded significantly as the support extended out farther from the body, and an explanation for this is proposed. In the EM-IntraSPECT reconstructed attenuation images, the lungs, spine, and soft tissue were readily distinguished and had approximately correct shapes and sizes. As compared with standard EM reconstruction assuming a fix uniform attenuation map, EM-IntraSPECT provided more uniform estimates of cardiac activity in the physical phantom study and in the simulation study with tight support, but less uniform estimates with a broad support. The new EM algorithm derived here has additional applications, including reconstructing emission and transmission projection data under a unified statistical model.

Attenuation and scatter compensation in myocardial perfusion SPECT

Nonuniform attenuation, Compton scatter, and limited, spatially varying resolution degrade both the qualitative and quantitative nature of myocardial perfusion SPECT. Physicians must recognize and understand the effects of these factors on myocardial perfusion SPECT for optimal interpretation and use of this important imaging technique. Recent developments in the design and implementation of compensation algorithms and transmission-based imaging promise to provide clinically realistic solutions to these effects and provide the framework for truly quantitative imaging. This achievement should improve the diagnostic accuracy and cost-effectiveness of myocardial perfusion SPECT.

Clinical review of attenuation-corrected cardiac SPECT

Rather than the introduction of a heralded technologic advancement in cardiac SPECT imaging challenging the accuracy of PET perfusion imaging, the commercial introduction of attenuation correction has been met with at least as many negative as positive reports. Some studies have reported significant improvements in specificity or specificity and sensitivity, especially for high-risk patterns of coronary artery disease; others have reported no improvement or a decrease in accuracy resulting from the introduction of troublesome artifacts. Although this review has attempted to emphasize the positive aspects of attenuation-corrected cardiac SPECT perfusion imaging and the potential for improved patient care it may provide, several negative reports continue to appear. Still there has been sufficient positive data reported to suggest that with fully developed, accurate, and robust correction methods, significant gains in SPECT assessments of the presence and extent of CHD, patient risk, and myocardial viability can be anticipated. Ultimately attenuation correction for cardiac SPECT should have a positive impact on the management of patients with coronary artery disease with important savings in lives and health care dollars.

Segmentation of the body and lungs from Compton scatter and photopeak window data in SPECT: a Monte-Carlo investigation

In SPECT imaging of the chest, nonuniform attenuation correction requires use of a patient specific attenuation (mu) map. Such a map can be obtained by estimating the regions of (1) the lungs and (2) the soft tissues and bones, and then assigning an appropriate value of attenuation coefficient (mu) to each region. The authors proposed a method to segment such regions from the Compton scatter and photopeak window SPECT slices of Tc-99m Sestamibi studies. The Compton scatter slices are used to segment the body outline and to estimate the regions of the lungs. Locations of the back bone and sternum are estimated from the photopeak window slices to assist in the segmentation. To investigate the accuracy of using Compton scatter slices in estimating the regions of the body and the lungs, a Monte-Carlo SPECT simulation of an anthropomorphic phantom with an activity distribution and noise characteristics similar to patient data was conducted. Energy windows of various widths were simulated for use in locating a suitable Compton scatter window for imaging, The effects of attenuation correction using a mu map based on segmentation were also studied. The results demonstrated for the activity and mu maps studied herein that: (1) reasonable contrast could be obtained from Compton scatter data for the segmentation of the lung regions, (2) true positive rates of 99% and 89% for determining the body and lung regions, respectively, with total error rates of 4% and 29%, could be achieved, (3) usage of a mu map based on segmentation for attenuation correction improved relative quantification over filtered backprojection, (4) variations in the assigned mu value of 40% smaller or 40% larger in the lung regions had an insignificant impact on the results of relative quantification, (5) a wide energy window away from the photopeak window for recording scattered events could benefit both the segmentation of the lung regions and the attenuation correction of the activity in the myocardium region, and (6) usage of a smaller than true mu value in the lung regions of an assigned mu map might benefit attenuation correction for absolute quantification.