CT-based Attenuation Correction Research Articles

Optimization of Number of Iterations as a Reconstruction Parameter in Bone SPECT Imaging Using a Novel Thoracic Spine Phantom.

The aim of this study was to optimize the number of iterations in bone SPECT imaging using a novel thoracic spine phantom (ISMM phantom). Methods: The quality and quantitative accuracy of bone SPECT images were evaluated by changing the number of iterations and the size of the hot spot in the phantom. True SUVs in the vertebra, tumor, and background parts were 9.8, 52.2, and 1.0, respectively. The phantom image was reconstructed using the ordered-subset expectation-maximization algorithm with CT-based attenuation correction, scatter correction, and resolution recovery; the number of ordered-subset expectation-maximization subsets was fixed at 10, with iterations ranging from 1 to 40. Full width at half maximum, percentage coefficient of variation, contrast ratio for the sphere and background (contrast), and recovery coefficient were evaluated as a function of the number of iterations for a given number of subsets (10) using the reconstructed images. In addition, SUVmax, SUVpeak, and SUVmean were calculated with various numbers of iterations for each sphere (13, 17, 22, and 28 mm) simulating a tumor. Results: Full width at half maximum decreased as the number of iterations was increased, and full width at half maximum converged uniformly when the number of iterations exceeded 10. The percentage coefficient of variation increased as the number of iterations was increased. Recovery coefficient decreased with decreasing sphere size. Contrast and all SUVs increased as the number of iterations was increased, and contrast and all SUVs converged uniformly when the number of iterations exceeded 5 and 10, respectively, for all sphere sizes. When the SUV was defined as the converged value for 10 iterations in the 28-mm sphere, the converged values of SUVmax, SUVpeak, and SUVmean were 75.1, 66.5, and 55.6, respectively. The relative error in the converged values for SUVmax, SUVpeak, and SUVmean were 43.8%, 27.3%, and 7.2% of the true value (52.2); all SUVs were overestimated. Conclusion: Using a thoracic spine phantom to evaluate the optimal reconstruction parameters in bone SPECT imaging, we determined the optimal number of iterations for 10 subsets to be 10.

CT-based attenuation correction of whole-body radiotherapy treatment positioning devices in PET/MRI hybrid imaging

Objective.To implement computed tomography (CT)-based attenuation maps of radiotherapy (RT) positioning hardware and radiofrequency (RF) coils to enable hybrid positron emission tomography/magnetic resonance imaging (PET/MRI)-based RT treatment planning. Materials and Methods. The RT positioning hardware consisted of a flat RT table overlay, coil holders for abdominal scans, coil holders for head and neck scans and an MRI compatible hip and leg immobilization device. CT images of each hardware element were acquired on a CT scanner. Based on the CT images, attenuation maps of the devices were created. Validation measurements were performed on a PET/MR scanner using a 68Ge phantom (48 MBq, 10 min scan time). Scans with each device in treatment position were performed. Then, reference scans containing only the phantom were taken. The scans were reconstructed online (at the PET/MRI scanner) and offline (via e7tools on a PC) using identical reconstruction parameters. Average reconstructed activity concentrations of the device and reference scans were compared. Results. The device attenuation maps were successfully implemented. The RT positioning devices caused an average decrease of reconstructed PET activity concentration in the range between −8.3 ± 2.1% (mean ± SD) (head and neck coil holder with coils) to −1.0 ± 0.5% (abdominal coil holder). With attenuation correction taking into account RT hardware, these values were reduced to −2.0 ± 1.2% and −0.6 ± 0.5%, respectively. The results of the offline and online reconstructions were nearly identical, with a difference of up to 0.2%. Conclusion. The decrease in reconstructed activity concentration caused by the RT positioning devices is clinically relevant and can successfully be corrected using CT-based attenuation maps. Both the offline and online reconstruction methods are viable options.

Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images

BackgroundAttenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.Materials and methodTwelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.ResultsThe mean whole-image PET uptake error was reduced from − 5.4% for Dixon-PET to − 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for SDA-PET.ConclusionAttenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.

PO-1745: PET/MRI for RT planning: CT-based attenuation correction of radiation treatment positioning devices

PO-1745: PET/MRI for RT planning: CT-based attenuation correction of radiation treatment positioning devices

Influence of a Headrest on Reconstruction and Attenuation Correction of Human Brain SPECT Images.

Previous reports suggest that a headrest significantly influences anterior and posterior cerebral blood flow. The present study aimed to clarify the influence of a headrest on reconstruction and attenuation correction (AC) of brain SPECT images. Methods: We evaluated the influence on cerebral blood flow in the anterior region (brain segments A + B), middle region (segments D + F), and posterior region (segment G) of the brain using filtered backprojection-AC based on the method of Chang (FBP-ChangAC), ordered-subset expectation maximization-ChangAC (OSEM-ChangAC), OSEM CT-based AC (OSEM-CTAC), and OSEM with no attenuation correction (OSEM-NoAC) with and without a headrest. The subjects were 17 healthy volunteers who underwent 99mTc-ECD SPECT. We compared the A + B/G and the D + F/G ratios of 99mTc-ECD SPECT images in each group. Results: For FBP-ChangAC, OSEM-ChangAC, and OSEM-NoAC, there were significant differences in A + B/G ratio between images obtained with a headrest and those obtained without. On the other hand, for OSEM-CTAC, there were no significant differences in A + B/G ratio regardless of whether a headrest was used. For FBP-ChangAC and OSEM-NoAC, there were significant differences in D + F/G ratio between images with a headrest and those without. For OSEM-CTAC and OSEM-ChangAC, there were no significant differences in D + F/G ratio regardless of whether a headrest was used. Conclusion: The influence of a headrest on image reconstruction and AC should be considered if FBP-ChangAC, OSEM-ChangAC, or OSEM-NoAC is used but not if OSEM-CTAC is used.

Feasibility of Multiparametric Positron Emission Tomography/Magnetic Resonance Imaging as a One-Stop Shop for Radiation Therapy Planning for Patients with Head and Neck Cancer

Multiparametric positron emission tomography (PET)/magnetic resonance imaging (MRI) as a one-stop shop for radiation therapy (RT) planning has great potential but is technically challenging. We studied the feasibility of performing multiparametric PET/MRI of patients with head and neck cancer (HNC) in RT treatment position. As a step toward planning RT based solely on PET/MRI, a deep learning approach was employed to generate synthetic computed tomography (sCT) from MRI. This was subsequently evaluated for dose calculation and PET attenuation correction (AC). Eleven patients, including 3 pilot patients referred for RT of HNC, underwent PET/MRI in treatment position after a routine fluorodeoxyglucose-PET/CT planning scan. The PET/MRI scan protocol included multiparametric imaging. A convolutional neural network was trained in a leave-one-out process to predict sCT from the Dixon MRI. The clinical CT-based dose plans were recalculated on sCT, and the plans were compared in terms of relative differences in mean, maximum, near-maximum, and near-minimum absorbed doses for different volumes of interest. Comparisons between PET with sCT-based AC and PET with CT-based AC were assessed based on the relative differences in mean and maximum standardized uptake values (SUVmean and SUVmax) from the PET-positive volumes. All 11 patients underwent PET/MRI in RT treatment position. Apart from the 3 pilots, full multiparametric imaging was completed in 45 minutes for 7 out of 8 patients. One patient terminated the examination after 30 minutes. With the exception of 1 patient with an inserted tracheostomy tube, all dosimetric parameters of the sCT-based dose plans were within ±1% of the CT-based dose plans. For PET, the mean difference was 0.4 ± 1.2% for SUVmean and -0.5 ± 1.0% for SUVmax. Performing multiparametric PET/MRI of patients with HNC in RT treatment position was clinically feasible. The sCT generation resulted in AC of PET and dose calculations sufficiently accurate for clinical use. These results are an important step toward using multiparametric PET/MRI as a one-stop shop for personalized RT planning.

Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies.

PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain PET scanners and hybrid PET/MRI, is challenging. Direct AC in image‐space, wherein PET images corrected for attenuation and scatter are synthesized from nonattenuation corrected PET (PET‐nonAC) images in an end‐to‐end fashion using deep learning approaches (DLAC) is evaluated for various radiotracers used in molecular neuroimaging studies. One hundred eighty brain PET scans acquired using 18F‐FDG, 18F‐DOPA, 18F‐Flortaucipir (targeting tau pathology), and 18F‐Flutemetamol (targeting amyloid pathology) radiotracers (40 + 5, training/validation + external test, subjects for each radiotracer) were included. The PET data were reconstructed using CT‐based AC (CTAC) to generate reference PET‐CTAC and without AC to produce PET‐nonAC images. A deep convolutional neural network was trained to generate PET attenuation corrected images (PET‐DLAC) from PET‐nonAC. The quantitative accuracy of this approach was investigated separately for each radiotracer considering the values obtained from PET‐CTAC images as reference. A segmented AC map (PET‐SegAC) containing soft‐tissue and background air was also included in the evaluation. Quantitative analysis of PET images demonstrated superior performance of the DLAC approach compared to SegAC technique for all tracers. Despite the relatively low quantitative bias observed when using the DLAC approach, this approach appears vulnerable to outliers, resulting in noticeable local pseudo uptake and false cold regions. Direct AC in image‐space using deep learning demonstrated quantitatively acceptable performance with less than 9% absolute SUV bias for the four different investigated neuroimaging radiotracers. However, this approach is vulnerable to outliers which result in large local quantitative bias.

Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data.

Attenuation correction (AC) is essential for quantitative PET imaging. In the absence of concurrent CT scanning, for instance on hybrid PET/MRI systems or dedicated brain PET scanners, an accurate approach for synthetic CT generation is highly desired. In this work, a novel framework is proposed wherein attenuation correction factors (ACF) are estimated from time-of-flight (TOF) PET emission data using deep learning. In this approach, referred to as called DL-EM), the different TOF sinogram bins pertinent to the same slice are fed into a multi-input channel deep convolutional network to estimate a single ACF sinogram associated with the same slice. The clinical evaluation of the proposed DL-EM approach consisted of 68 clinical brain TOF PET/CT studies, where CT-based attenuation correction (CTAC) served as reference. A two-tissue class consisting of background-air and soft-tissue segmentation of the TOF PET non-AC images (SEG) as a proxy of the technique used in the clinic was also included in the comparative evaluation. Qualitative and quantitative PET analysis was performed through SUV bias maps quantification in 63 different brain regions. The DL-EM approach resulted in 6.1±9.7% relative mean absolute error (RMAE) in bony structures compared to SEG AC method with RMAE of 16.1±8.2% (p-value <0.001). Considering the entire head region, DL-EM led to a root mean square error (RMSE) of 0.3±0.01 outperforming the SEG method with RMSE of 0.8±0.02 SUV (p-value <0.001). The region-wise analysis of brain PET studies revealed less than 7% absolute SUV bias for the DL-EM approach, whereas the SEG method resulted in more than 14% absolute SUV bias (p-value <0.05). Qualitative assessment and quantitative PET analysis demonstrated the superior performance of the DL-EM approach over the segmentation-based technique with clinically acceptable SUV bias. The results obtained using the DL-EM approach are comparable to state-of-the-art MRI-guided AC methods. Yet, this approach enables the extraction of interesting features about patient-specific attenuation which could be employed not only as a stand-alone AC approach but also as complementary/prior information in other AC algorithms.

Relationship between CT Numbers and Artifacts Obtained Using CT-based Attenuation Correction of PET/CT

The aim of this study was to clarify the artifacts that occurred in the non-activity signal with computed tomography (CT)-based attenuation correction (CTAC) error due to image misregistration. We used a cylindrical phantom containing a test tube with a diameter of 15 mm as the non-activity signal part. Positron emission tomography (PET) images were acquired for 30 minutes using the phantom with water in the non-activity signal part and 18F-fluoro-2-deoxy-d-glucose (18F-FDG) (5.3 kBq/ml) in the background area. CT scanning was performed by replacing the water with contrast agents at different dilutions to obtain arbitrary CT numbers (-1000 to 1000). The PET images were attenuation-corrected individually by the CT images in which the CT number of the non-activity signal part had changed. The relationship between the CT numbers and the CTAC artifact was determined by measuring the PET value in the non-activity signal part of the PET images and comparing Ci. As the CT number of the CT images increased, Ci of the artifact increased. The CT number and Ci had a correlation of y=1.48x+2.86×103 (R2 =0.99) when CTAC was performed in units of CT numbers above 0 for PET data of water (0 HU) and a correlation of y=3.15x+6.26×103 (R2 =0.97) when CTAC was performed in units of CT numbers below 0 for PET data of air (-1000 HU). Although the original CT image was air, the artifacts due to CTAC errors with different Hounsfield units showed larger changes. In particular, positive artifacts were recognized in the PET images after CTAC depending on the Hounsfield units. When the CT number was different from the original in CTAC, the PET value was different. CTAC should be performed with caution as there may be image misregistration.

Evaluating the effectiveness of a single CT method for attenuation correction in stress-rest myocardial perfusion imaging with thallium-201 chloride SPECT.

This study aimed to evaluate the effectiveness of a single computed tomography (CT) based attenuation correction method using thallium-201 chloride (201TlCl) in stress-rest myocardial perfusion imaging (MPI). The data of 106 patients who underwent MPI with single photon emission computed tomography (SPECT) using 201TlCl were retrospectively reviewed. MPI SPECT images were reconstructed using stress SPECT and stress CT (SIO), rest SPECT and rest CT (RIO), and rest SPECT and stress CT (RIA). The accuracy of alignment between the SPECT and CT images was evaluated with normalized cross-correlation (NCC) and visual examination. The summed rest score (SRS) was used to evaluate hypoperfusion at rest; washout rate (WO) was used to assess ischemia; and left ventricular ejection fraction (LVEF) was used to evaluate the left ventricle (LV) function. There was no significant difference in NCC and visual evaluation in all three dimensions. The SRS of both RIO and RIA (7.5 ± 7.7 and 7.7 ± 7.6, respectively) did not differ significantly. However, SRSs of RIO and RIA showed a strong correlation (r = 0.98). The WO was 39.0 ± 0.98% for both RIO and RIA, with a strong correlation between the two values (r = 1.00). LVEF was 61.1 ± 17.4% for RIO and 61.3 ± 17.4% for RIA, and a strong correlation was observed between the two values (r = 1.00). In conclusion, the single CT-based attenuation correction method with 201TlCl SPECT has an accuracy equivalent to that of the conventional two CT-based attenuation correction method.

ZTE MR-based attenuation correction in brain FDG-PET/MR: performance in patients with cognitive impairment.

One of the main challenges of integrated PET/MR is to achieve an accurate PET attenuation correction (AC), especially in brain acquisition. Here, we evaluated an AC method based on zero echo time (ZTE) MRI, comparing it with the single-atlas AC method and CT-based AC, set as reference. Fifty patients (70 ± 11 years old, 28 men) underwent FDG-PET/MR examination (SIGNA PET/MR 3.0 T, GE Healthcare) as part of the investigation of suspected dementia. They all had brain computed tomography (CT), 2-point LAVA-flex MRI (for atlas-based AC), and ZTE-MRI. Two AC methods were compared with CT-based AC (CTAC): one based on a single atlas, one based on ZTE segmentation. Impact on brain metabolism was evaluated using voxel and volumes of interest-based analyses. The impact of AC was also evaluated through comparisons between two subgroups of patients extracted from the whole population: 15 patients with mild cognitive impairment and normal metabolic pattern, and 22 others with metabolic pattern suggestive of Alzheimer disease, using SPM12 software. ZTE-AC yielded a lower bias (3.6 ± 3.2%) than the atlas method (4.5 ± 6.1%) and lowest interindividual (4.6% versus 6.8%) and inter-regional (1.4% versus 2.6%) variabilities. Atlas-AC resulted in metabolism overestimation in cortical regions near the vertex and cerebellum underestimation. ZTE-AC yielded a moderate metabolic underestimation mainly in the occipital cortex and cerebellum. Voxel-wise comparison between the two subgroups of patients showed that significant difference clusters had a slightly smaller size but similar locations with PET images corrected with ZTE-AC compared with those corrected with CT, whereas atlas-AC images showed a notable reduction of significant voxels. ZTE-AC performed better than atlas-AC in detecting pathologic areas in suspected neurodegenerative dementia. • The ZTE-based AC improved the accuracy of the metabolism quantification in PET compared with the atlas-AC method. • The overall uptake bias was 21% lower when using ZTE-based AC compared with the atlas-AC method. • ZTE-AC performed better than atlas-AC in detecting pathologic areas in suspected neurodegenerative dementia.

Impact of aging on semiquantitative uptake parameters in normal rated clinical baseline [123I]Ioflupane single photon emission computed tomography/computed tomography.

Studies investigating the age-related impact on dopamine transporter binding have previously omitted the use of attenuation correction by computed tomography (CT). We aimed to explore the impact of age and gender on dopamine transporter binding on [I]Ioflupane single photon emission CT (SPECT) imaging with simultaneously acquired CT. Three hundred forty-two patients with clinically uncertain parkinsonian syndrome underwent [I]-Ioflupane SPECT/CT with CT-based attenuation correction. Two nuclear medicine physicians independently performed a visual evaluation of all scans and only visibly normal scans were included for further analysis. Moreover, the results of a fully automatic semiquantitative evaluation method were recorded. Thereafter, the obtained [I]Ioflupane binding ratio and the hemispheric asymmetry index were correlated with age and sex. Patient age range was 41-80 years with a balanced distribution over decades. Of 342 patients, 133 (38.9%, 66 females, median age, 64 years) were considered visually normal by both observers on the SPECT/CT images. A significant inverse correlation between age and [I]Ioflupane binding ratios in the striata (R = -0.38; P < 0.001), putamina (R = -0.39; P < 0.001) and caudate nuclei (R = -0.3; P < 0.001) was demonstrated. Linear regression of all included subjects demonstrated an average decrease of 0.19 per decade in the striatal binding ratio (6.6%). No significant sex differences were found in striatal binding ratios (P = 0.86). Moreover, no significant correlation was observed between age and striatal asymmetry index (r = 0.12; P = 0.16). In the present largest single-center analysis investigating [I]Ioflupane SPECT/CT in patients with clinical uncertain parkinsonian syndrome, a dopamine transporter loss of 6.6% per decade in visually normal scans was recorded.

Clinical utility of the normal database of 123I-iodoamphetamine brain perfusion single photon emission computed tomography for statistical analysis using computed tomography-based attenuation correction: a multicenter study

We have established a common normal database (NDB) with applicability in multicenter settings for the statistical analysis of brain perfusion single photon emission computed tomography (SPECT) with triple energy window scatter correction, computed tomography-based attenuation correction (CTAC), and spatial resolution compensation. This study aimed to compare the CTAC normal database (CTAC-NDB) with conventional normal databases for the statistical analysis of 123I-iodoamphetamine (123I-IMP) brain perfusion SPECT at three institutions and to assess the clinical efficiency of CTAC-NDB. We recruited 45 patients (26 men and 19 women; mean age, 74.2 ± 3.9years; Mini-Mental State Examination score, 19.8 ± 6.1) with Alzheimer's disease (AD, n = 26), dementia with Lewy bodies (DLB, n = 9), and mild cognitive impairment (n = 10) from three institutions. Three-dimensional stereotactic surface projection (3D-SSP) technique was used to analyze data obtained from the 123I-IMP brain perfusion SPECT images compared with both CTAC-NDB and conventional NDB. We visually assessed each 3D-SSP z score map to determine the changes in specific findings, such as AD/DLB pattern. Furthermore, the stereotactic extraction estimation analysis software was used to measure the regional z score severity and extent as a semiquantitative assessment. In the visual assessment, all cases exhibited clearer findings with CTAC-NDB than with conventional NDB in the parietotemporal association cortex as well as in the inferior temporal, frontal, and lateral occipital cortices. Contrarily, the findings from the medial cerebral regions, including the precuneus and the posterior cingulate, became indistinct in 71% of the cases and remained unchanged in 25% of the cases. In the semiquantitative analysis, a similar tendency was observed in the mean z score in the three institutions included in the study. Using the CTAC-NDB, the findings in the vicinity of the cranium became increasingly clear, whereas those in the medial surface of the brain became less defined or remained unchanged. These findings were confirmed via a semiquantitative analysis. Moreover, similar changes in the reduction pattern were observed in the three institutions. Therefore, the new database with CTAC might be applicable in other institutions. Data collected in this study may serve as a CTAC-NDB.

Promise of Fully Integrated PET/MRI: Noninvasive Clinical Quantification of Cerebral Glucose Metabolism.

We describe a fully automated processing pipeline to support the noninvasive absolute quantification of the cerebral metabolic rate for glucose (CMRGlc) in a clinical setting. This pipeline takes advantage of “anatometabolic” information associated with fully integrated PET/MRI. Methods: Ten healthy volunteers (5 men and /5 women; 27 ± 7 y old; 70 ± 10 kg) underwent a test-retest 18F-FDG PET/MRI examination of the brain. The imaging protocol consisted of a 60-min PET list-mode acquisition with parallel MRI acquisitions, including 3-dimensional time-of-flight MR angiography, MRI navigators, and a T1-weighted MRI scan. State-of-the-art MRI-based attenuation correction was derived from T1-weighted MRI (pseudo-CT [pCT]). For validation purposes, a low-dose CT scan was also performed. Arterial blood samples were collected as the reference standard (arterial input function [AIF]). The developed pipeline allows the derivation of an image-derived input function (IDIF), which is subsequently used to create CMRGlc maps by means of a Patlak analysis. The pipeline also includes motion correction using the MRI navigator sequence as well as a novel partial-volume correction that accounts for background heterogeneity. Finally, CMRGlc maps are used to generate a normative database to facilitate the detection of metabolic abnormalities in future patient scans. To assess the performance of the developed pipeline, IDIFs extracted by both CT-based attenuation correction (CT-IDIF) and MRI-based attenuation correction (pCT-IDIF) were compared with the reference standard (AIF) using the absolute percentage difference between the areas under the curves as well as the absolute percentage difference in regional CMRGlc values. Results: The absolute percentage differences between the areas under the curves for CT-IDIF and pCT-IDIF were determined to be 1.4% ± 1.0% and 3.4% ± 2.6%, respectively. The absolute percentage difference in regional CMRGlc values based on CT-IDIF and pCT-IDIF differed by less than 6% from the reference values obtained from the AIF. Conclusion: By taking advantage of the capabilities of fully integrated PET/MRI, we developed a fully automated computational pipeline that allows the noninvasive determination of regional CMRGlc values in a clinical setting. This methodology might facilitate the proliferation of fully quantitative imaging into the clinical arena and, as a result, might contribute to improved diagnostic efficacy.

Continuous Repetitive Data Acquisition with 123I-FP-CIT SPECT: Effects of Rotation Speed and Rotation Time.

The aim of this study was to evaluate the effects of the acquisition rotation speed and the rotation time for continuous repetitive rotation acquisition (CRRA) on image quality and quantification in 123I-FP-CIT SPECT. Methods: An anthropomorphic striatal phantom filled with 123I solution was acquired with CRRA and the step-and-shoot (SS) mode. The following combinations of acquisition rotation speed and rotation time for CRRA were used: 0.50 rpm by 30 frames, 0.17 rpm by 10 frames, 0.10 rpm by 6 frames, and 0.05 rpm by 3 frames. SPECT images were reconstructed using ordered-subset expectation maximization with resolution recovery, scatter, and CT-based attenuation correction. Two kinds of image processing patterns-image reconstruction after the addition of projection data (the added-projection-data process) and image addition after data reconstruction (the added-reconstructed-image process)-were investigated in this study. The effects of the acquisition parameters and the image processes were evaluated by the full width at half maximum, percentage coefficient of variation (%CV), and specific binding ratio (SBR). Results: With full width at half maximum, there were no clear differences between CRRA images obtained with the various rotation speeds before rotation and the SS mode. Although the combination of a slow rotation speed and a short rotation time improved image uniformity compared with the SS mode, the %CV obtained by CRRA increased as the rotation speed increased. The %CVs were 11.9% ± 0.9% for 0.50 rpm by 30 frames, 6.9% ± 0.9% for 0.05 rpm by 3 frames, and 9.6% ± 0.5% for SS mode. SBRs obtained by CRRA with the added-projection-data process were equal to those obtained by SS mode. However, SBRs obtained with the added-reconstructed-image process were clearly decreased compared with the SS mode. Conclusion: The combination of rotation speed and rotation times affects the image quality and quantification of 123I-FP-CIT SPECT using CRRA. When CRRA is applied in 123I-FP-CIT SPECT, it is necessary to use added-projection-data processes and proper rotation speeds (e.g., 0.10-0.17 rpm rotation speed).

Impact of free-breathing CT on quantitative measurements of static and quiescent period-gated PET Images

Measurements of standardized uptake values (SUV) can vary due to many causes, including respiratory motion. Various methodologies have been introduced to correct for motion in PET, with quiescent-period-gated (QPG) PET being the most popular approach. QPG has been shown to improve PET image quantification compared to static-whole-body (SWB) PET. However, to achieve this improvement, QPG PET requires CT attenuation correction data that matches the QPG PET data. In this paper we investigated the effect of using free-breathing CT for attenuation correction of QPG PET on SUVmax and SUVpeak and compared the results to those of SWB PET. 34 lesions in 27 patients were included. All patients were injected with F-18 FDG. 4D-CT datasets representing all possible phases of respiration that could result from a free-breathing CT were acquired. The 4D-CT datasets were used for attenuation correction of the QPG and SWB PET data. Percentage change in the SUVmax and SUVpeak range was calculated for the reconstructions and compared between QPG and SWB PET. The mean percentage change in the lesion SUVmax and SUVpeak ranges were 19.1% (p = 0.0178) and 25.2% (p = 0.0002) higher for QPG compared to SWB, respectively. The maximum percent change in SUVmax and SUVpeak ranges were 58.5% and 59.0% for QPG, respectively compared to 46.1% and 45.3% for SWB, respectively. The highest SUVmax and SUVpeak measurements corresponded to the CT phase that matched the QPG phase. Utilizing free-breathing CT for attenuation correction can lead to large changes in quantification due to misalignment with PET data. This misalignment has a large quantitative impact on QPG PET as compared to SWB PET. When interpreting quantitative changes in lesions, it is critical to consider the influences of free-breathing CT-based attenuation correction.

A Quantitative Evaluation of Joint Activity and Attenuation Reconstruction in TOF PET/MR Brain Imaging.

Time-of-flight (TOF) PET data provide an effective means for attenuation correction (AC) when no (or incomplete or inaccurate) attenuation information is available. Since MR scanners provide little information on photon attenuation of different tissue types, AC in hybrid PET/MR scanners has always been challenging. In this contribution, we aim at validating the activity reconstructions of the maximum-likelihood ordered-subsets activity and attenuation (OSAA) reconstruction algorithm on a patient brain data set. We present a quantitative comparison of joint reconstructions with the current clinical gold standard-ordered-subsets expectation maximization-using CT-based AC in PET/CT, as well as the current state of the art in PET/MR, that is, zero time echo (ZTE)-based AC. Methods: The TOF PET emission data were initially used in a preprocessing stage to estimate crystal maps of efficiencies, timing offsets, and timing resolutions. Applying these additional corrections during reconstructions, OSAA, ZTE-based, and the vendor-provided atlas-based AC techniques were analyzed and compared with CT-based AC. In our initial study, we used the CT-based estimate of the expected scatter and later used the ZTE-based and OSAA attenuation estimates to compute the expected scatter contribution of the data during reconstructions. In all reconstructions, a maximum-likelihood scaling of the single-scatter simulation estimate to the emission data was used for scatter correction. The reconstruction results were analyzed in the 86 segmented regions of interest of the Hammers atlas. Results: Our quantitative analysis showed that, in practice, a tracer activity difference of +0.5% (±2.1%) and +0.1% (±2.3%) could be expected for the state-of-the-art ZTE-based and OSAA AC methods, respectively, in PET/MR compared with the clinical gold standard in PET/CT. Conclusion: Joint activity and attenuation estimation methods can provide an effective solution to the challenging AC problem for brain studies in hybrid TOF PET/MR scanners. With an accurate TOF-based (timing offsets and timing resolutions) calibration, and similar to the results of the state-of-the-art method in PET/MR, regional errors of joint TOF PET reconstructions are within a few percentage points.

Bone SPECT-based segmented attenuation correction for quantitative analysis of bone metastasis (B-SAC): comparison with CT-based attenuation correction

BackgroundEvidence has shown the clinical usefulness of measuring the metastatic tumor burden of bone for prognostic assessment especially in prostate cancer; quantitative evaluation by dedicated SPECT is difficult due to the lack of attenuation correction (AC) method.We developed a novel method for attenuation correction using bone SPECT emission data (bone SPECT-based segmented attenuation correction; B-SAC) where emission data were virtually segmented into three tissues (i.e., bone, soft tissue, and air). Then, the pixel values in SPECT were replaced by 50 for the virtual soft tissue, and − 1000 for the virtual air. The replaced pixel values for the virtual bone were based on the averaged CT values of the normal vertebrae (B-SACN) or the metastatic bones (B-SACM). Subsequently, the processed SPECT data (i.e., SPECT value) were supposed to realize CT data (i.e., CT value) that were used for B-SAC. The standardized uptake values (SUVs) of 112 metastatic bone tumors in 15 patients with prostate cancer were compared between CTAC with scatter correction (SC) and resolution recovery (RR) and the following reconstruction conditions: B-SACN (+)SC(+)RR(+), B-SACM (+)SC(+)RR(+), uniform AC(UAC)(+)SC(+)RR(+), AC(−)SC(+)RR(+), and no correction (NC).ResultsThe SUVs in the five reconstruction conditions were all correlated with those in CTAC(+)SC(+)RR(+) (p < 0.01), and the correlations between B-SACN or B-SACM and CTAC images were excellent (r > 0.94). Bland-Altman analysis showed that the mean SUV differences between CTAC (+)SC(+)RR(+) and the other five reconstructions were 0.85 ± 2.25 for B-SACN (+)SC(+)RR(+), 1.61 ± 2.36 for B-SACM (+)SC(+)RR(+), 1.54 ± 3.84 for UAC(+)SC(+)RR(+), − 3.12 ± 4.97 for AC(−)SC(+)RR(+), and − 5.96 ± 4.59 for NC. Compared to CTAC(+)SC(+)RR(+), B-SACN (+)SC(+)RR(+) showed a slight but constant overestimation (approximately 17%) of the metastatic tumor burden of bone when the same threshold of metabolic tumor volume was used.ConclusionsThe results of this preliminary study suggest the potential for B-SAC to improve the quantitation of bone metastases in bone SPECT when X-ray CT or transmission CT data are not available. Considering the small but unignorable differences of lesional SUVs between CTAC and B-SAC, SUVs obtained with the current version of B-SAC seem difficult to be directly compared with those obtained with CTAC.

Bias in PET Images of Solid Phantoms Due to CT-Based Attenuation Correction

The use of computed tomography (CT) images to correct for photon attenuation in positron emission tomography (PET) produces unbiased patient images, but it is not optimal for synthetic materials. For test objects made from epoxy, image bias and artifacts have been observed in well-calibrated PET/CT scanners. An epoxy used in commercially available sources was infused with long-lived 68Ge/68Ga nuclide and measured on several PET/CT scanners as well as on older PET scanners that measured attenuation with 511-keV photons. Bias in attenuation maps and PET images of phantoms was measured as imaging parameters and methods varied. Changes were made to the PET reconstruction to show the influence of CT-based attenuation correction. Additional attenuation measurements were made with a new epoxy intended for use in radiology and radiation treatment whose photonic properties mimic water. PET images of solid phantoms were biased by between 3% and 24% across variations in CT X-ray energy and scanner manufacturer. Modification of the reconstruction software reduced bias, but object-dependent changes were required to generate accurate attenuation maps. The water-mimicking epoxy formulation showed behavior similar to water in limited testing. For some solid phantoms, transformation of CT data to attenuation maps is a major source of PET image bias. The transformation can be modified to accommodate synthetic materials, but our data suggest that the problem may also be addressed by using epoxy formulations that are more compatible with PET/CT imaging.

Data-driven voluntary body motion detection and non-rigid event-by-event correction for static and dynamic PET

PET has the potential to perform absolute in vivo radiotracer quantitation. This potential can be compromised by voluntary body motion (BM), which degrades image resolution, alters apparent tracer uptakes, introduces CT-based attenuation correction mismatch artifacts and causes inaccurate parameter estimates in dynamic studies. Existing body motion correction (BMC) methods include frame-based image-registration (FIR) approaches and real-time motion tracking using external measurement devices. FIR does not correct for motion occurring within a pre-defined frame and the device-based method is generally not practical in routine clinical use, since it requires attaching a tracking device to the patient and additional device set up time. In this paper, we proposed a data-driven algorithm, centroid of distribution (COD), to detect BM. In this algorithm, the central coordinate of the time-of-flight (TOF) bin, which can be used as a reasonable surrogate for the annihilation point, is calculated for every event, and averaged over a certain time interval to generate a COD trace. We hypothesized that abrupt changes on the COD trace in lateral direction represent BMs. After detection, BM is estimated using non-rigid image registrations and corrected through list-mode reconstruction. The COD-based BMC approach was validated using a monkey study and was evaluated against FIR using four human and one dog studies with multiple tracers. The proposed approach successfully detected BMs and yielded superior correction results over conventional FIR approaches.