Cardiac single-photon emission tomography: is attenuation correction enough?

Comparison of attenuation, dual-energy-window, and model-based scatter correction of low-count SPECT to 82Rb PET/CT quantified myocardial perfusion scores

BACKGROUND

New reconstruction algorithms allow reduction in acquisition times or the amount of injected radioactivity. We examined the impact of different corrections on low-count clinical SPECT myocardial perfusion images (MPI) and compared to (82)Rb PET/CT. We compared no corrections (NC) to attenuation correction (AC) with and without scatter correction by either a dual-energy-window (AC-DEW) or model-based (AC-ESSE) approach. All reconstructions included resolution recovery.

METHODS

56 patients were imaged using a standard rest/stress Tc-99m-tetrofosmin MPI SPECT/CT protocol with an additional half-time acquisition. A (82)Rb-rest/stress PET/CT MPI was acquired within 4 weeks. Reconstruction methods were compared using summed rest/stress/difference scores from an objective algorithm (SRS/SSS/SDS).

RESULTS

The SRS and SSS for NC were significantly (P < .01) higher than for AC, but well correlated (r ≥ 0.87). The correlation in SRS/SSS among AC, AC-DEW, and AC-ESSE was excellent (r ≥ 0.98). AC-ESSE and AC-DEW had higher SRS (P ≤ .05) than AC, but the SDS values were not significantly different. Concordance with PET normal/abnormal classification was 76% for NC and ≥85% for the AC methods.

CONCLUSION

AC significantly improves the accuracy of low-count myocardial perfusion SPECT half-time imaging for the detection of disease compared to NC. Compared to PET, there was no significant difference among AC, AC-DEW, and AC-ESSE.

Iterative image reconstruction for positron emission tomography based on a detector response function estimated from point source measurements

The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed positron emission tomography (PET) images. For efficient computation in reconstruction, the system model in PET can be factored into a product of a geometric projection matrix and sinogram blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. Direct measurement of a sinogram blurring matrix is difficult in practice because of the requirement of a collimated source. In this work, we propose a method to estimate the 2D blurring kernels from uncollimated point source measurements. Since the resulting sinogram blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo (MC) simulation, and hence provide a more accurate system model. Another advantage of the proposed method over MC simulation is that it can easily be applied to data that have undergone a transformation to reduce the data size (e.g., Fourier rebinning). Point source measurements were acquired with high count statistics in a relatively fine grid inside the microPET II scanner using a high-precision 2D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner and explicitly models the detector block structure. The resulting sinogram blurring matrix is incorporated into a maximum a posteriori (MAP) image reconstruction algorithm. The proposed method has been validated using a 3 x 3 line phantom, an ultra-micro resolution phantom and a (22)Na point source superimposed on a warm background. The results of the proposed method show improvements in both resolution and contrast ratio when compared with the MAP reconstruction with a MC-based sinogram blurring matrix, and one without a detector response model. The reconstruction time is unaffected by the new method since the blurring component takes a relatively small part of the overall reconstruction time. The proposed method can be applied to other PET scanners for human and animal imaging.

Reconstruction algorithm for single photon emission computed tomography and its numerical implementation

The modern imaging techniques of positron emission tomography and of single photon emission computed tomography are not only two of the most important tools for studying the functional characteristics of the brain, but they now also play a vital role in several areas of clinical medicine, including neurology, oncology and cardiology. The basic mathematical problems associated with these techniques are the construction of the inverse of the Radon transform and of the inverse of the so-called attenuated Radon transform, respectively. An exact formula for the inverse Radon transform is well known, whereas that for the inverse attenuated Radon transform was obtained only recently by R. Novikov. The latter formula was constructed by using a method introduced earlier by R. Novikov and the first author in connection with a novel derivation of the inverse Radon transform. Here, we first show that the appropriate use of that earlier result yields immediately an analytic formula for the inverse attenuated Radon transform. We then present an algorithm for the numerical implementation of this analytic formula, based on approximating the given data in terms of cubic splines. Several numerical tests are presented which suggest that our algorithm is capable of producing accurate reconstruction for realistic phantoms such as the well-known Shepp-Logan phantom.

Effect of errors in the system matrix on maximum a posteriori image reconstruction

Statistically based iterative image reconstruction methods have been developed for emission tomography. One important component in iterative image reconstruction is the system matrix, which defines the mapping from the image space to the data space. Several groups have demonstrated that an accurate system matrix can improve image quality in both single photon emission computed tomography (SPECT) and positron emission tomography (PET). While iterative methods are amenable to arbitrary and complicated system models, the true system response is never known exactly. In practice, one also has to sacrifice the accuracy of the system model because of limited computing and imaging resources. This paper analyses the effect of errors in the system matrix on iterative image reconstruction methods that are based on the maximum a posteriori principle. We derived an analytical expression for calculating artefacts in a reconstructed image that are caused by errors in the system matrix using the first-order Taylor series approximation. The theoretical expression is used to determine the required minimum accuracy of the system matrix in emission tomography. Computer simulations show that the theoretical results work reasonably well in low-noise situations.

Attenuation correction for single photon emission computed tomography myocardial perfusion imaging

The specificity of cardiac single photon emission computed tomography (SPECT) perfusion imaging is significantly affected by internal photon absorption. Commonly referred to as anterior wall breast and inferior wall diaphragm attenuation artifacts, even when following characteristic patterns in women and men, the reduced activity produced can be difficult to differentiate from real perfusion defects. Unfortunately, wide variations in body habitus result in unpredictable variations in tissue attenuation and the specificity of uncorrected SPECT is unacceptably low in many laboratories. This manuscript reviews recent developments in attenuation correction methods for cardiac SPECT. Several commercial methods are now available, and although the initial success using these methods varied widely, as these methods have been improved successful clinical reports are appearing with increasing frequency. Recent developments have yielded more robust validated methods and significant clinical advantages have been achieved in the diagnostic evaluation of coronary heart disease (sensitivity as well as specificity) and myocardial viability. As these methods continue to mature, further advances should be anticipated.

Combined corrections for attenuation, depth-dependent blur, and motion in cardiac SPECT: a multicenter trial

BACKGROUND

The diagnostic accuracy of cardiac single photon emission computed tomography (SPECT) is limited by image-degrading factors, such as heart or subject motion, depth-dependent blurring caused by the collimator, and photon scatter and attenuation. We developed correction approaches for motion, depth-dependent blur, and attenuation and performed a multicenter validation.

METHODS AND RESULTS

Motion was corrected both transversely and axially with a cross-correlation technique. Depth-dependent blurring was corrected by first back-projecting each projection and then applying a depth-dependent Wiener filter row by row. Attenuation was corrected with an iterative, nonuniform Chang algorithm, based on a transmission scan-generated attenuation map. We validated these approaches in 112 subjects, including 36 women (20 healthy volunteers, 8 angiographically normal patients, and 8 patients with coronary artery disease [CAD] found by means of angiography) and 76 men (23 healthy volunteers, 10 angiographically normal patients, and 43 patients with CAD found by means of angiography). Either technetium 99m or thallium 201 was used for emission; either gadolinium 153 or Tc-99m was used for transmission. Images were reconstructed and blindly interpreted with a 5-point scale for receiver operating characteristic analysis in 2 ways: motion correction plus a Butterworth filter, and combined motion and blur and attenuation corrections. The interpretation by means of consensus was for the overall presence of CAD and vascular territory. The receiver operating characteristic curves for overall presence and each of the 3 main coronary arteries were all shifted upward and to the left and had larger areas under the curve, for combined corrections compared with motion correction and Butterworth. Sensitivity/specificity for motion correction and Butterworth were 84/69, 64/71, 32/94, and 71/81 overall for the left anterior descending, the right coronary artery, and circumflex territories, respectively, compared with 88/92, 77/93, 50/97, and 74/95, respectively, for the combined corrections.

CONCLUSIONS

The proposed combined corrections for motion, depth-dependent blur, and attenuation significantly improve diagnostic accuracy, when compared with motion correction alone.