Accurate system modeling in tomographic image reconstruction has been shown to reduce the spatial variance of resolution and improve quantitative accuracy. System modeling can be improved through analytic calculations, Monte Carlo simulations, and physical measurements. The purpose of this work is to improve clinical fully-3-D reconstruction without substantially increasing computation time. We present a practical method for measuring the detector blurring component of a whole-body positron emission tomography (PET) system to form an approximate system model for use with fully-3-D reconstruction. We employ Monte Carlo simulations to show that a non-collimated point source is acceptable for modeling the radial blurring present in a PET tomograph and we justify the use of a Na22 point source for collecting these measurements. We measure the system response on a whole-body scanner, simplify it to a 2-D function, and incorporate a parameterized version of this response into a modified fully-3-D OSEM algorithm. Empirical testing of the signal versus noise benefits reveal roughly a 15% improvement in spatial resolution and 10% improvement in contrast at matched image noise levels. Convergence analysis demonstrates improved resolution and contrast versus noise properties can be achieved with the proposed method with similar computation time as the conventional approach. Comparison of the measured spatially variant and invariant reconstruction revealed similar performance with conventional image metrics. Edge artifacts, which are a common artifact of resolution-modeled reconstruction methods, were less apparent in the spatially variant method than in the invariant method. With the proposed and other resolution-modeled reconstruction methods, edge artifacts need to be studied in more detail to determine the optimal tradeoff of resolution/contrast enhancement and edge fidelity.

Purpose: The goal of this work was to investigate the effects of MRI surface coils on attenuationcorrected PET emission data. The authors studied the cases where either an MRI or a CT scan would be used to provide PET attenuation correction (AC). Combined MR/PET scanners that use the MRI for PET AC (MR-AC) face the challenge of absent surface coils in MR images and thus cannot directly account for attenuation in the coils. Combining MR and PET images could be achieved by transporting the subject on a stereotactically registered table between independent MRI and PET scanners. In this case, conventional PET CT-AC methods could be used. A challenge here is that high atomic number materials within MR coils cause artifacts in CT images and CT based AC is typically not validated for coil materials. Methods: The authors evaluated PET artifacts when MR coils were absent from AC data (MR-AC), or when coil attenuation was measured by CT scanning (CT-AC). They scanned PET phantoms with MR surface coils on a clinical PET/CT system and used CT-AC to reconstruct PET data. The authors then omitted the coil from the CT-AC image to mimic the MR-AC scenario. Images were acquired using cylinder and anthropomorphic phantoms. They evaluated and compared the following five scenarios: (1) A uniform cylinder phantom and head coil scanned and reconstructed using CT-AC; (2) similar emission data (with head coil present) were reconstructed without the head coil in the AC data; (3) the same cylinder scanned without the head coil present (reference scan); (4) a PET torso phantom with a full MR torso coil present in both PET and CT; (5) only half of the separable torso coil present in the PET/CT acquisition. The authors also performed analytic simulations of the first three scenarios. Results: Streak artifacts were present in CT images containing MR surface coils due to metal components. These artifacts persisted after the CT images were converted for PET AC. The artifacts were significantly reduced when half of the separable coil was removed during the scan. CT scans tended to over-estimate the linear attenuation coefficient (l) of the metal components when using conventional methods for converting from CT number to l(511 keV). Artifacts were visible outside the phantom in some of the PET emission images, corresponding to the MRI coil geometry. However, only subtle artifacts were apparent in the emission images inside the phantoms. On the other hand, the PET emission image quantitative accuracy was significantly affected: the activity was underestimated by 19% when AC did not include the head coil, and overestimated by 28% when the CT-AC included the head coil. Conclusions: The presence of MR coils during PET or PET/CT scanning can cause subtle artifacts and potentially important quantification errors. Alternative CT techniques that mitigate artifacts should be used to improve AC accuracy. When possible, removing segments of an MR coil prior to the PET/CT exam is recommended. Further, MR coils could be redesigned to reduce artifacts by rear...

In dual-modality PET/CT systems, the CT scan provides the attenuation map for PET attenuation correction. The current clinical practice of obtaining a single helical CT scan provides only a snapshot of the respiratory cycle, whereas PET occurs over multiple respiratory cycles. Misalignment of the attenuation map and emission image because of respiratory motion causes errors in the attenuation correction factors and artifacts in the attenuationcorrected PET image. To rectify this problem, we evaluated the use of cine CT, which acquires multiple low-dose CT images during a respiratory cycle. We evaluated the average and the intensity-maximum image of cine CT for cardiac PET attenuation correction. Methods: Cine CT data and cardiac PET data were acquired from a cardiac phantom and from multiple patient studies. The conventional helical CT, cine CT, and PET data of an axially translating phantom were evaluated with and without respiratory motion. For the patient studies, we acquired 2 cine CT studies for each PET acquisition in a rest-stress 13 N-ammonia protocol. Three readers visually evaluated the alignment of 74 attenuation image sets versus the corresponding emission image and determined whether the alignment provided acceptable or unacceptable attenuation-corrected PET images. Results: In the phantom study, the attenuation correction from helical CT caused a major artifactual defect in the lateral wall on the PET image. The attenuation correction from the average and from the intensity-maximum cine CT images reduced the defect by 20% and 60%, respectively. In the patient studies, 77% of the cases using the average of the cine CT images had acceptable alignment and 88% of the cases using the intensity maximum of the cine CT images had acceptable alignment. Conclusion: Cine CT offers an alternative to helical CT for compensating for respiratory motion in the attenuation correction of cardiac PET studies. Phantom studies suggest that the average and the intensity maximum of the cine CT images can reduce potential respirationinduced misalignment errors in attenuation correction. Patient studies reveal that cine CT provides acceptable alignment in most cases and suggest that the intensity-maximum cine image offers a more robust alternative to the average cine image. PET combined with CT in an integrated PET/CT scanner offers a single-study, noninvasive technique for the diagnosis of coronary artery disease. The integrated modalities provide distinct and complementary information: PET offers functional measurement of myocardial perfusion and metabolism, whereas contrast-enhanced CT angiography offers structural assessment of coronary anatomy and atherosclerotic burden (1,2).A limitation with cardiac PET on a PET/CT system is that the PET attenuation map formed from a helical CT acquisition represents a snapshot of the respiratory cycle, whereas the PET image is acquired over multiple respirations. The potential attenuation and emission misalignment dramatically reduces the accuracy of attenuation correction, leading...

Noise equivalent count rate (NECR) and image noise are two different but related metrics that have been used to predict and assess image quality, respectively. The aim of this study is to investigate, using patient studies, the relationships between injected dose (ID), body mass index (BMI) and scanner type on NECR and image noise measurements in PET imaging. Two groups of 90 patients each were imaged on a GE DSTE and a DRX PET/CT scanner, respectively. The patients in each group were divided into nine subgroups according to three BMI (20-24.9, 25-29.9, 30-45 kg m(-2)) and three ID (296-444, 444-555, 555-740 MBq) ranges, resulting in ten patients/subgroup. All PET data were acquired in 3D mode and reconstructed using the VuePoint HD® fully 3D OSEM algorithm (2 iterations, 21(DRX) or 20 (DSTE) subsets). NECR and image noise measurements for bed positions covering the liver were calculated for each patient. NECR was calculated from the trues, randoms and scatter events recorded in the DICOM header of each patient study, while image noise was determined as the standard deviation of 50 non-neighboring voxels in the liver of each patient. A t-test compared the NECR and image noise for different scanners but with the same BMI and ID. An ANOVA test on the other hand was used to compare the results of patients with different BMI but the same ID and scanner type as well as different ID but the same BMI and scanner type. As expected the t-test showed a significant difference in NECR between the two scanners for all BMI and ID subgroups. However, contrary to what is expected no such findings were observed for image noise measurement. The ANOVA results showed a statistically significant difference in both NECR and image noise among the different BMI for each ID and scanner subgroup. However, there was no statistically significant difference in NECR and image noise across different ID for each BMI and scanner subgroup. Although the GE DRX PET/CT scanner has better count rate performance than the GE DSTE PET/CT scanner, this improvement does not translate to a lower image noise when using OSEM reconstruction. Our results show that patients with larger BMI consistently generate poorer image quality. Dose reduction from>555 to 296-444 MBq has minimal impact on image quality independent of the scanner used. A reduction in ID decreases patient and technologist exposure and can potentially reduce the overall cost of the study.

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