Accelerated EM reconstruction in total-body PET: potential for improving tumour detectability

Meikle, Steven R.; Hutton, BF; Bailey, Dale L.; Hooper, Patrick K.; Fulham, Michael

doi:10.1088/0031-9155/39/10/012

Cited by 64 publications

(13 citation statements)

References 15 publications

(10 reference statements)

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“…Consequently, the reconstruction problem is solved iteratively, meaning the image estimate is progressively updated towards an improved solution. Initially, the computation cost hindered iterative reconstruction’s clinical use, but advances in computation speed and the development of efficient algorithms have permitted widespread clinical use of iterative image reconstruction methods [6,29-31]. …”

Section: D Pet Image Reconstructionmentioning

confidence: 99%

Image reconstruction for PET/CT scanners: past achievements and future challenges

Shan

Alessio

Kinahan

2010

Imaging in Medicine

109

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PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. Keywordsanalytic reconstruction; fully 3D imaging; iterative reconstruction; maximum-likelihood expectation-maximization method; PET PET is a medical imaging modality with proven clinical value for the detection, staging and monitoring of a wide variety of diseases. This technique requires the injection of a radiotracer, which is then monitored externally to generate PET data [1,2]. Through different algorithms, PET data can be reconstructed into the spatial distribution of a radiotracer. PET imaging provides noninvasive, quantitative information of biological processes, and such functional information can be combined with anatomical information from CT scans. The integration of PET and CT on modern PET/CT scanners provides a synergy of the two imaging modalities, and can lead to improved disease diagnosis and treatment monitoring [3,4].Considering that PET imaging is limited by high levels of noise and relatively poor spatial resolution, numerous research efforts have been devoted to the development and improvement of PET image reconstruction methods since the introduction of PET in the 1970s. This article provides a brief introduction to tomographic reconstruction and an overview of the commonly used methods for PET. We start with the problem formulation and then introduce data correction methods. We then proceed with reconstruction methods

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Section: D Pet Image Reconstructionmentioning

confidence: 99%

Image reconstruction for PET/CT scanners: past achievements and future challenges

Shan

Alessio

Kinahan

2010

Imaging in Medicine

109

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“…The result is a reduction in the number of iterations by a factor approximately equal to the number of subsets employed. 30 An example of the impact of attenuation correction using OSEM on reconstructed slices is given in Figure 5. This figure shows FBP and OSEM reconstructed slices, as well as the attenuation maps used in reconstruction, for Tc-99m acquisitions of activity in the Data Spectrum Anthropomorphic Phantom.…”

Section: Backproject Ratios For Allmentioning

confidence: 99%

An Overview of Attenuation and Scatter Correction of Planar and SPECT Data for Dosimetry Studies

King

Farncombe²

2003

Cancer Biotherapy and Radiopharmaceuticals

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A number of factors impact the accuracy of activity quantitation in planar and single photon emission computed tomographic (SPECT) imaging. Two important such factors are attenuation and scattering in the medium containing the activity. The first removes photons which otherwise would have been included in the images, and the second adds events to the images from photons which would not have otherwise been imaged. A number of methods have been developed to compensate for these biases to activity quantitation. This review will briefly introduce planar quantitation which is commonly used for dosimeter purposes, and then present a slightly more detailed overview of SPECT quantitation which is arguably more accurate. It will conclude by cautioning users of commercial reconstruction software to validate it for quantitation before using it for dosimetric purposes.

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“…When , (5) is the maximum-likelihood expectation-maximization (MLEM) algorithm [27]. For other values, a rule of thumb [28] equates one OSEM iteration with iterations of MLEM, although this rule can break down if is large. Our initial data partitioning was 16 subsets of eight angular projections apiece.…”

Section: A Osem With No Drcmentioning

confidence: 99%

LROC analysis of detector-response compensation in SPECT

Gifford

King

Wells

et al. 2000

IEEE Trans. Med. Imaging

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Localization ROC (LROC) observer studies examined whether detector response compensation (DRC) in ordered-subset, expectation-maximization (OSEM) reconstructions helps in the detection and localization of hot tumors. Simulated gallium (Ga-67) images of the thoracic region were used in the study. The projection data modeled the acquisition of attenuated 93- and 185-keV photons with a medium-energy parallel-hole collimator, but scatter was not modeled. Images were reconstructed with five strategies: 1) OSEM with no DRC; 2) OSEM preceded by restoration filtering; 3) OSEM with iterative DRC; 4) OSEM with an ideal DRC; and 5) filtered backprojection (FBP) with no DRC. All strategies included attenuation correction. There were four LROC studies conducted. In a study using a single tumor activity, the ideal DRC offered the best performance, followed by iterative DRC, restoration filtering, OSEM with no DRC, and FBP. Statistical significance at the 5% level was found between all pairs of strategies except for restoration filtering and OSEM with no DRC. A similar ranking was found for a more realistic study using multiple tumor activities. Additional studies considered the effects of OSEM iteration number and tumor activity on the detection improvement that iterative DRC offered with respect to OSEM with no DRC.

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Accelerated EM reconstruction in total-body PET: potential for improving tumour detectability

Cited by 64 publications

References 15 publications

Image reconstruction for PET/CT scanners: past achievements and future challenges

Image reconstruction for PET/CT scanners: past achievements and future challenges

An Overview of Attenuation and Scatter Correction of Planar and SPECT Data for Dosimetry Studies

LROC analysis of detector-response compensation in SPECT

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