Blind Deblurring Reconstruction Technique with Applications in PET Imaging

We developed an empirical PET model taking into account system blurring and a blind iterative reconstruction scheme that estimates both the actual image and the point spread function of the system. Reconstruction images of high quality can be acquired by using the proposed reconstruction technique for both synthetic and experimental data. In the synthetic data study, the algorithm reduces image blurring and preserves the edges without introducing extra artifacts. The localized measurement shows that the performance of the reconstruction image improved by up to 100%. In experimental data studies, the contrast and quality of reconstruction is substantially improved. The proposed method shows promise in tumor localization and quantification

90Y PET/CT quantitative accuracy and image quality

Purpose: To optimize 90Y-PET/CT image reconstruction for quantitative accuracy and optimal image quality.Methods: PET/CT scans of a NEMA IEC phantom (3GBq 90YCl2, sphere uptake ratio of ~7) were acquired on 4 GE (BGO:DSTE, DST & LYSO:DRX, D690) and 1 Siemens (LSO:mCT) scanners in 3D list mode with 30 min/bed; replayed to 20, 15, 10 min/bed. Iterative reconstruction parameters explored were SUB × IT (3 – 80) and post-reconstruction filters: transaxial: 5 – 25 mm cutoff & z-axis (GE only): std vs. heavy. The effects of PSF modeling and TOF correction were evaluated for D690 and mCT. VOIs were drawn inside spheres and in adjacent background regions. The accuracy of sphere activity concentration (AC in kBq/mL) and contrast to noise ratio (CNR) was calculated as function of SUB × IT. Reconstructed PET images were also evaluated qualitatively for sphere detectability and artifacts.Results: AC converged to 70 – 90% accuracy for 37 mm sphere and further degraded for smaller spheres. Spheres at max CNR might not reach AC convergence yet. Smaller spheres have slower convergence but reach CNR max together with other spheres. Scan duration did not strongly affect sphere convergence but shorter scans increased noise and reduced detectability; 13 mm spheres were not visible going from 30 to 15 min/bed. Heavy z-axis (GE) and transaxial filter with 10 – 15 mm cutoff helped suppress noise and increase sphere detectability at the expense of accuracy. Images with PSF+TOF corrections had higher sphere detectability and converged faster. Hot cluster artifacts 5 – 7 times the background were seen in some cases with SUB × IT near convergence and lower filtration.Conclusion: Accurate 90Y AC was not achieved even at convergence and noise is a major concern. 90YPET/CT reconstruction parameters are different than those for 18F and benefit substantially from PSF+TOF corrections. Optimum image quality and accurate AC may not be simultaneously achievable.----------------------------------------Cite this article as: Siman W, Mawlawi O, Kappadath SC. 90Y PET/CT quantitative accuracy and image quality. Int J Cancer Ther Oncol 2014; 2(2):020235. DOI: 10.14319/ijcto.0202.3

Dose volume histogram‐based optimization of image reconstruction parameters for quantitative 90Y‐PET imaging

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147185/1/mp13269.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147185/2/mp13269_am.pd

Toward a standard for the evaluation of PET-Auto-Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation

Purpose: The aim of this paper is to define the requirements and describe the design and implementation of a standard benchmark tool for evaluation and validation of PET-auto-segmentation (PET-AS) algorithms. This work follows the recommendations of Task Group 211 (TG211) appointed by the American Association of Physicists in Medicine (AAPM).Methods: The recommendations published in the AAPM TG211 report were used to derive a set of required features and to guide the design and structure of a benchmarking software tool. These items included the selection of appropriate representative data and reference contours obtained from established approaches and the description of available metrics. The benchmark was designed in a way that it could be extendable by inclusion of bespoke segmentation methods, while maintaining its main purpose of being a standard testing platform for newly developed PET-AS methods. An example of implementation of the proposed framework, named PETASset, was built. In this work, a selection of PET-AS methods representing common approaches to PET image segmentation was evaluated within PETASset for the purpose of testing and demonstrating the capabilities of the software as a benchmark platform.Results: A selection of clinical, physical, and simulated phantom data, including "best estimates" reference contours from macroscopic specimens, simulation template, and CT scans was built into the PETASset application database. Specific metrics such as Dice Similarity Coefficient (DSC), Positive Predictive Value (PPV), and Sensitivity (S), were included to allow the user to compare the results of any given PET-AS algorithm to the reference contours. In addition, a tool to generate structured reports on the evaluation of the performance of PET-AS algorithms against the reference contours was built. The variation of the metric agreement values with the reference contours across the PET-AS methods evaluated for demonstration were between 0.51 and 0.83, 0.44 and 0.86, and 0.61 and 1.00 for DSC, PPV, and the S metric, respectively. Examples of agreement limits were provided to show how the software could be used to evaluate a new algorithm against the existing state-of-the art.Conclusions: PETASset provides a platform that allows standardizing the evaluation and comparison of different PET-AS methods on a wide range of PET datasets. The developed platform will be available to users willing to evaluate their PET-AS methods and contribute with more evaluation datasets. </p

Imaging Long-Term Fate of Intramyocardially Implanted Mesenchymal Stem Cells in a Porcine Myocardial Infarction Model

The long-term fate of stem cells after intramyocardial delivery is unknown. We used noninvasive, repetitive PET/CT imaging with [18F]FEAU to monitor the long-term (up to 5 months) spatial-temporal dynamics of MSCs retrovirally transduced with the sr39HSV1-tk gene (sr39HSV1-tk-MSC) and implanted intramyocardially in pigs with induced acute myocardial infarction. Repetitive [18F]FEAU PET/CT revealed a biphasic pattern of sr39HSV1-tk-MSC dynamics; cell proliferation peaked at 33–35 days after injection, in periinfarct regions and the major cardiac lymphatic vessels and lymph nodes. The sr39HSV1-tk-MSC–associated [18F]FEAU signals gradually decreased thereafter. Cardiac lymphography studies using PG-Gd-NIRF813 contrast for MRI and near-infrared fluorescence imaging showed rapid clearance of the contrast from the site of intramyocardial injection through the subepicardial lymphatic network into the lymphatic vessels and periaortic lymph nodes. Immunohistochemical analysis of cardiac tissue obtained at 35 and 150 days demonstrated several types of sr39HSV1-tk expressing cells, including fibro-myoblasts, lymphovascular cells, and microvascular and arterial endothelium. In summary, this study demonstrated the feasibility and sensitivity of [18F]FEAU PET/CT imaging for long-term, in-vivo monitoring (up to 5 months) of the fate of intramyocardially injected sr39HSV1-tk-MSC cells. Intramyocardially transplanted MSCs appear to integrate into the lymphatic endothelium and may help improve myocardial lymphatic system function after MI

90Y PET/CT quantitative accuracy and image quality

Purpose: To optimize 90Y-PET/CT image reconstruction for quantitative accuracy and optimal image quality.Methods: PET/CT scans of a NEMA IEC phantom (3GBq 90YCl2, sphere uptake ratio of ~7) were acquired on 4 GE (BGO:DSTE, DST &amp; LYSO:DRX, D690) and 1 Siemens (LSO:mCT) scanners in 3D list mode with 30 min/bed; replayed to 20, 15, 10 min/bed. Iterative reconstruction parameters explored were SUB × IT (3 – 80) and post-reconstruction filters: transaxial: 5 – 25 mm cutoff &amp; z-axis (GE only): std vs. heavy. The effects of PSF modeling and TOF correction were evaluated for D690 and mCT. VOIs were drawn inside spheres and in adjacent background regions. The accuracy of sphere activity concentration (AC in kBq/mL) and contrast to noise ratio (CNR) was calculated as function of SUB × IT. Reconstructed PET images were also evaluated qualitatively for sphere detectability and artifacts.Results: AC converged to 70 – 90% accuracy for 37 mm sphere and further degraded for smaller spheres. Spheres at max CNR might not reach AC convergence yet. Smaller spheres have slower convergence but reach CNR max together with other spheres. Scan duration did not strongly affect sphere convergence but shorter scans increased noise and reduced detectability; 13 mm spheres were not visible going from 30 to 15 min/bed. Heavy z-axis (GE) and transaxial filter with 10 – 15 mm cutoff helped suppress noise and increase sphere detectability at the expense of accuracy. Images with PSF+TOF corrections had higher sphere detectability and converged faster. Hot cluster artifacts 5 – 7 times the background were seen in some cases with SUB × IT near convergence and lower filtration.Conclusion: Accurate 90Y AC was not achieved even at convergence and noise is a major concern. 90YPET/CT reconstruction parameters are different than those for 18F and benefit substantially from PSF+TOF corrections. Optimum image quality and accurate AC may not be simultaneously achievable.----------------------------------------Cite this article as: Siman W, Mawlawi O, Kappadath SC. 90Y PET/CT quantitative accuracy and image quality. Int J Cancer Ther Oncol 2014; 2(2):020235. DOI: 10.14319/ijcto.0202.35</p

Effects of alterations in positron emission tomography imaging parameters on radiomics features.

Radiomics studies require large patient cohorts, which often include patients imaged using different imaging protocols. We aimed to determine the impact of variability in imaging protocol parameters and interscanner variability using a phantom that produced feature values similar to those of patients. Positron emission tomography (PET) scans of a Hoffman brain phantom were acquired on GE Discovery 710, Siemens mCT, and Philips Vereos scanners. A standard-protocol scan was acquired on each machine, and then each parameter that could be changed was altered individually. The phantom was contoured with 10 regions of interest (ROIs). Values for 45 features with 2 different preprocessing techniques were extracted for each image. To determine the impact of each parameter on the reliability of each radiomics feature, the intraclass correlation coefficient (ICC) was calculated with the ROIs as the subjects and the parameter values as the raters. For interscanner comparisons, we compared the standard deviation of each radiomics feature value from the standard-protocol images to the standard deviation of the same radiomics feature from PET scans of 224 patients with non-small cell lung cancer. When the pixel size was resampled prior to feature extraction, all features had good reliability (ICC > 0.75) for the field of view and matrix size. The time per bed position had excellent reliability (ICC > 0.9) on all features. When the filter cutoff was restricted to values below 6 mm, all features had good reliability. Similarly, when subsets and iterations were restricted to reasonable values used in clinics, almost all features had good reliability. The average ratio of the standard deviation of features on the phantom scans to that of the NSCLC patient scans was 0.73 using fixed-bin-width preprocessing and 0.92 using 64-level preprocessing. Most radiomics feature values had at least good reliability when imaging protocol parameters were within clinically used ranges. However, interscanner variability was about equal to interpatient variability; therefore, caution must be used when combining patients scanned on equipment from different vendors in radiomics data sets