Systematic and Distributed Time-of-Flight List Mode PET Reconstruction

Wang, W.; Hu, Zhiqiang; Gualtieri, E.; Parma, Michael J.; Walsh, E.S.; Sebok, David; Hsieh, Yu-Lung; Tung, Chi-hua; Song, Xiyun; Griesmer, Jerome; Kolthammer, Jeffrey; Popescu, Lucreţiu M.; Werner, Matthew E.; Karp, Joel S.; Gagnon, Daniel

doi:10.1109/nssmic.2006.354229

Cited by 75 publications

(59 citation statements)

References 8 publications

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“…A fully 3D list-mode iterative reconstruction algorithm is computationally intensive and has proven to be challenging to implement for clinical purposes (26). Using a 10-node (dual central-processingunit) computer cluster, the image processing with this algorithm proceeds in parallel with data acquisition and is typically completed for clinical whole-body (multibed) studies 10-30 min after the end of the acquisition, depending on the number of counts collected.…”

Section: Data Corrections and Reconstructionmentioning

confidence: 99%

“…In the last decade there have been notable developments in list-mode reconstruction methods (20)(21)(22) and, more recently, inclusion of both TOF and other physical effects in the system model (23)(24)(25). Although list-mode reconstruction is a computationally intensive method, fast computers and parallelization make a practical implementation feasible today (26).…”

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confidence: 99%

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Benefit of Time-of-Flight in PET: Experimental and Clinical Results

Surti²,

et al. 2008

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Significant improvements have made it possible to add the technology of time-of-flight (TOF) to improve PET, particularly for oncology applications. The goals of this work were to investigate the benefits of TOF in experimental phantoms and to determine how these benefits translate into improved performance for patient imaging. Methods: In this study we used a fully 3-dimensional scanner with the scintillator lutetium-yttrium oxyorthosilicate and a system timing resolution of ;600 ps. The data are acquired in list-mode and reconstructed with a maximum-likelihood expectation maximization algorithm; the system model includes the TOF kernel and corrections for attenuation, detector normalization, randoms, and scatter. The scatter correction is an extension of the model-based singlescatter simulation to include the time domain. Phantom measurements to study the benefit of TOF include 27-cm-and 35-cm-diameter distributions with spheres ranging in size from 10 to 37 mm. To assess the benefit of TOF PET for clinical imaging, patient studies are quantitatively analyzed. Results: The lesion phantom studies demonstrate the improved contrast of the smallest spheres with TOF compared with non-TOF and also confirm the faster convergence of contrast with TOF. These gains are evident from visual inspection of the images as well as a quantitative evaluation of contrast recovery of the spheres and noise in the background. The gains with TOF are higher for larger objects. These results correlate with patient studies in which lesions are seen more clearly and with higher uptake at comparable noise for TOF than with non-TOF. Conclusion: TOF leads to a better contrast-versus-noise trade-off than non-TOF but one that is difficult to quantify in terms of a simple sensitivity gain improvement: A single gain factor for TOF improvement does not include the increased rate of convergence with TOF nor does it consider that TOF may converge to a different contrast than non-TOF. The experimental phantom results agree with those of prior simulations and help explain the improved image quality with TOF for patient oncology studies. There has been considerable advancement of the technology and instrumentation in PET over the last 30 y since the first tomography ring systems were developed. Significant improvements have been made in detectors, hardware, and image processing that impact both image quality and accuracy of quantification. Some of the major achievements include (a) the development and incorporation of new scintillators and detector configurations for higher spatial resolution and sensitivity, (b) the evolution from 2-dimensional (2D) systems with septa to 3-dimensional (3D) systems with larger axial fields of view for improved sensitivity, (c) the transition from analytic filtered-backprojection reconstruction algorithms to fully 3D iterative techniques with data corrections included in the system model for improved image quality and quantification, and (d) the combination of a CT scanner with the PET instrument for both attenuation ...

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Section: Data Corrections and Reconstructionmentioning

confidence: 99%

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confidence: 99%

Benefit of Time-of-Flight in PET: Experimental and Clinical Results

Surti²,

et al. 2008

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“…This method is currently implemented in the Gemini TF PET system (Philips) for correction of scatter and random coincidences (4,5). Care should thus be taken when imaging low-90 Y specific activity with this lutetium yttrium oxyorthosilicate-based system (6).…”

Section: James H Thrallmentioning

confidence: 99%

The Impact of Image Reconstruction Bias on PET/CT ⁹⁰Y Dosimetry After Radioembolization

Walrand¹,

Hesse²,

Lhommel³

et al. 2015

J Nucl Med

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TO THE EDITOR:The survey finding by Karantanis et al. (1) of perceived greater "overinterpretation" than "underintepretation" of 18 F-FDG PET/CT studies in oncology on the part of referring physicians is supported by data from a prior report in The Journal of Nuclear Medicine by Biggi et al. (2). This work showed a better failure-free survival (FFS) rate in patients with Hodgkin disease and positive interim PET scans interpreted locally than in patients judged to have positive scans by a central reading group. The FFS rates for patients with negative scans were identical between local and central interpreters. Therefore, the discrepancy in the FFS rates in patients with positive interim scans can be accounted for only by overinterpretation, that is, false-positive interpretations, on the part of the local interpreters.In fairness to local interpreters, there is more pressure on them clinically than on central interpreters whose opinions are not used in caring for the patients. There is arguably more pressure when it is known that a result will be used to guide further decisions on treatment.My own impression of this is that because of the relative consequences, many interpreting physicians are more worried about missing a cancer than having a false-positive result. A missed cancer can progress to the detriment of the patient and with liability risk to the interpreting physician, whereas overcalls are often never discovered because therapy goes forward with apparent success and everyone is happy. From this standpoint, the data from Biggi et al. are unique and eye-opening because outcomes were tracked over time, revealing the impact of overinterpretation, which does not come without medical and financial costs. If we are to use the results of PET/CT in oncology to guide risk-adapted therapy, the interpretations must be accurate.In the context of international telemedicine, we have seen a similar phenomenon with pathology interpretations. In one case of a lesion falsely diagnosed as cancer, we asked the originating pathologist about his interpretation. He was quite candid and said the patient was a VIP. He was not sure of the diagnosis and had no local expert to consult. He reasoned that if he called the lesion benign, and it turned out to be cancer, his position would be in jeopardy. On the other hand, if he called the lesion cancer, the treatment was certain to be successful and all parties would be satisfied with the outcome.Equally interesting is the observation of Hicks (3) in the accompanying perspective. Hicks notes that he has seen cases in which he has made a positive finding only to be overruled by a negative biopsy result but with disease becoming manifest later in the same area. He posits the likelihood of pathologic sampling errors but with the surgeon left thinking the PET scan was a false-positive.An article by Haseebuddin (4) in the same issue of JNM as Biggi's report sheds important light on Hick's observation. Haseebuddin's work provides data on FFS in patients with prostate cancer studied with 1...

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“…Apart from this modification to the algorithm, PET data were reconstructed following the scanner's standard whole-body list-mode OSEM protocol as described by Wang et al (23), with 3 iterations on a 75 · 75 blob slice grid and a relaxation parameter l 5 0:9 and resampled after reconstruction to a 144 · 144 rectangular slice grid with isotropic 4-mm voxels.…”

Section: Pet-constrained Reconstructionmentioning

confidence: 99%

Fat-Constrained ¹⁸F-FDG PET Reconstruction in Hybrid PET/MR Imaging

Prevrhal

Heinzer²,

Wülker

et al. 2014

J Nucl Med

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Fusion of information from PET and MR imaging can increase the diagnostic value of both modalities. This work sought to improve 18 F FDG PET image quality by using MR Dixon fat-constrained images to constrain PET image reconstruction to low-fat regions, with the working hypothesis that fatty tissue metabolism is low in glucose consumption. Methods: A novel constrained PET reconstruction algorithm was implemented via a modification of the system matrix in list-mode timeof-flight ordered-subsets expectation maximization reconstruction, similar to the way time-of-flight weighting is incorporated. To demonstrate its use in PET/MR imaging, we modeled a constraint based on fat/water-separating Dixon MR images that shift activity away from regions of fat tissue during PET image reconstruction. PET and MR imaging scans of a modified National Electrical Manufacturers Association/ International Electrotechnical Commission body phantom simulating body fat/water composition and in vivo experiments on 2 oncology patients were performed on a commercial time-of-flight PET/MR imaging system. Results: Fat-constrained PET reconstruction visibly and quantitatively increased resolution and contrast between high-uptake and fatty-tissue regions without significantly affecting the images in nonfat regions. Conclusion: The incorporation of MR tissue information, such as fat, in image reconstruction can improve the quality of PET images. The combination of a variety of potential other MR tissue characteristics with PET represents a further justification for merging MR data with PET data in hybrid systems. PET/ MR is rapidly emerging as a promising new hybrid imaging modality. Among several differentiating features when compared with PET/CT, the combination of PET with MR imaging can potentially benefit from reduced radiation for the patient and predominantly from the wider range of tissue characteristics generated by appropriate MR imaging sequences and their multiparametric combinations (1). MR provides anatomic imaging with better soft-tissue depiction and more dedicated tissue contrast than CTand furthermore offers insight into a variety of aspects of human physiology with the potential to image metabolic processes and physiologic function (2-4), complementing metabolic and molecular information afforded by PET for better assessment of the underlying physiopathology (5). Beyond these diagnostic aspects, in the hybrid setting with PET, MR data are also used to estimate tissuedependent photon attenuation and scatter to improve the quantitative accuracy of PET images (6-8). The MR-based motion correction of PET reconstruction to improve PET image quality is also supported (9,10).Spatial resolution and quantification accuracy in PET imaging are limited by the low detector spatial resolution and poor photon counting statistics. Early developments in PET reconstruction techniques have addressed this limitation by modeling the underlying photon generation statistics and taking advantage of the physics of coincidence detection to find an app...

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Systematic and Distributed Time-of-Flight List Mode PET Reconstruction

Cited by 75 publications

References 8 publications

Benefit of Time-of-Flight in PET: Experimental and Clinical Results

Benefit of Time-of-Flight in PET: Experimental and Clinical Results

The Impact of Image Reconstruction Bias on PET/CT ⁹⁰Y Dosimetry After Radioembolization

Fat-Constrained ¹⁸F-FDG PET Reconstruction in Hybrid PET/MR Imaging

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Systematic and Distributed Time-of-Flight List Mode PET Reconstruction

Cited by 75 publications

References 8 publications

Benefit of Time-of-Flight in PET: Experimental and Clinical Results

Benefit of Time-of-Flight in PET: Experimental and Clinical Results

The Impact of Image Reconstruction Bias on PET/CT 90Y Dosimetry After Radioembolization

Fat-Constrained 18F-FDG PET Reconstruction in Hybrid PET/MR Imaging

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Product

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The Impact of Image Reconstruction Bias on PET/CT ⁹⁰Y Dosimetry After Radioembolization

Fat-Constrained ¹⁸F-FDG PET Reconstruction in Hybrid PET/MR Imaging