Impact of Time-of-Flight PET on Whole-Body Oncologic Studies: A Human Observer Lesion Detection and Localization Study
Open accessAbstract
UNLABELLED: Phantom studies have shown improved lesion detection performance with time-of-flight (TOF) PET. In this study, we evaluate the benefit of fully 3-dimensional, TOF PET in clinical whole-body oncology using human observers to localize and detect lesions in realistic patient anatomic backgrounds. Our hypothesis is that with TOF imaging we achieve improved lesion detection and localization for clinically challenging tasks, with a bigger impact in large patients. METHODS: One hundred patient studies with normal (18)F-FDG uptake were chosen. Spheres (diameter, 10 mm) were imaged in air at variable locations in the scanner field of view corresponding to lung and liver locations within each patient. Sphere data were corrected for attenuation and merged with patient data to produce fused list-mode data files with lesions added to normal-uptake scans. All list files were reconstructed with full corrections and with or without the TOF kernel using a list-mode iterative algorithm. The images were presented to readers to localize and report the presence or absence of a lesion and their confidence level. The interpretation results were then analyzed to calculate the probability of correct localization and detection, and the area under the localized receiver operating characteristic (LROC) curve. The results were analyzed as a function of scan time per bed position, patient body mass index (BMI < 26 and BMI ≥ 26), and type of imaging (TOF and non-TOF). RESULTS: Our results showed that longer scan times led to an improved area under the LROC curve for all patient sizes. With TOF imaging, there was a bigger increase in the area under the LROC curve for larger patients (BMI ≥ 26). Finally, we saw smaller differences in the area under the LROC curve for large and small patients when longer scan times were combined with TOF imaging. CONCLUSION: A combination of longer scan time (3 min in this study) and TOF imaging provides the best performance for imaging large patients or a low-uptake lesion in small or large patients. This imaging protocol also provides similar performance for all patient sizes for lesions in the same organ type with similar relative uptake, indicating an ability to provide a uniform clinical diagnosis in most oncologic lesion detection tasks.
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Surti et al. showed that TOF reconstruction improves detection rates of simulated liver and lung lesions by human readers, with improvement pronounced in heavy patients with BMI ≥26 kg/m2.
“Surti et al. showed that TOF reconstruction improves detection rates of simulated liver and lung lesions by human readers. This improvement was pronounced in heavy patients with BMI ≥ 26 kg/m2 [159].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [159]
The same group further demonstrated that TOF improved lesion detection, especially in low-contrast lesions.
“The same group further demonstrated that TOF improved lesion detection, especially in low-contrast lesions [160].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [160]
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References 19 · Cited by 104
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- [1]Surti S Kuhn A Werner ME Perkins AE Kolthammer J Karp JS Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities J Nucl Med 2007 48 3 471 480 17332626
- [2]Jakoby BW Bercier Y Conti M Performance Investigation of a Time-of-Flight PET/CT Scanner Paper presented at: 2008 IEEE Nuclear Science Symposium and Medical Imaging Conference 2008 Dresden, Germany
- [4]Budinger TF Time-of-Flight Positron Emission Tomography - Status Relative to Conventional PET J Nucl Med 1983 24 1 73 76 6336778
- [5]Tomitani T Image-Reconstruction and Noise Evaluation in Photon Time-of-Flight Assisted Positron Emission Tomography IEEE Trans Nucl Sci 1981 28 6 4582 4589
- [6]Surti S Karp JS Popescu LA Daube-Witherspoon ME Werner M Investigation of time-of-flight benefit for fully 3-D PET IEEE Trans Med Imag 2006 25 5 529 538 16689258
- [7]Conti M Bendriem B Casey M First experimental results of time-of-flight reconstruction on an LSO PET scanner Phys Med Biol 2005 50 19 4507 4526 16177486
- [9]Karp JS Surti S Daube-Witherspoon ME Muehllehner G Benefit of Time-of-Flight in PET: Experimental and Clinical Results J Nucl Med 2008 49 3 462 470 18287269 PMC2639717
- [10]Lois C Jakoby BW Long MJ An Assessment of the Impact of Incorporating Time-of-Flight Information into Clinical PET/CT Imaging J Nucl Med 2010 51 237 245 20080882 PMC2818518
- [11]Surti S Karp JS Experimental evaluation of a simple lesion detection task with time-of-flight PET Phys Med Biol 2009 54 2 373 384 19098351 PMC2662381
- [12]Kadrmas DJ Casey ME Conti M Jakoby BW Lois C Townsend DW Impact of Time-of-Flight on PET Tumor Detection J Nucl Med 2009 50 8 1315 1323 19617317 PMC2786272
- [13]El Fakhri G Santos PA Badawi RD Holdsworth CH Van den Abbeele AD Kijewski MF Impact of acquisition geometry, image processing, and patient size on lesion detection in whole-body FDG-PET J Nucl Med 2007 48 1951 1960 18006613
- [14]El Fakhri G Surti S Trott CM Scheuermann J Karp JS Improvement in Lesion Detection with Whole – Body Oncologic TOF - PET J Nucl Med 2011 in press PMC3088884 21321265
- [15]Popescu LM Iterative image reconstruction using geometrically ordered subsets with list-mode data Paper presented at: 2004 IEEE Nuclear Science Symposium and Medical Imaging Conference 2004 Rome, Italy
- [16]Watson CC Extension of Single Scatter Simulation to Scatter Correction of Time-of-Flight PET IEEE Trans Nucl Sci 2007 54 5 1679 1686
- [17]Werner ME Surti S Karp JS Implementation and Evaluation of a 3D PET Single Scatter Simulation with TOF Modeling Paper presented at: 2006 IEEE Nuclear Science Symposium and Medical Imaging Conference 2006 San Diego, CA
- [18]Swensson RG Unified measurement of observer performance in detecting and localizing target objects on images Med Phys 1996 23 10 1709 1725 8946368
- [19]Hochberg Y Tamhane AC Multiple Comparison Procedures Hoboken, NJ John Wiley & Sons 1987
- Authors
- Surti, S., Scheuermann, J., El Fakhri, G., Daube-Witherspoon, M. E., Lim, R., Abi-Hatem, N., Moussallem, E., Benard, F., Mankoff, D., & Karp, J. S.
- Affiliations
- University of Pennsylvania (US)
- Harvard University (US)
- University of Washington (US)
- Venue
- Journal of Nuclear Medicine
- Publisher
- Society of Nuclear Medicine
- Published
- 2011-04-15
- Volume
- 52
- Issue
- 5
- Pages
- 712-719
- ISSN
- 0161-5505 (ISSN-L)
- 2159-662X
- PMC
- PMC3104282
- OpenAlex
- W2101305905
- Cited by
- 104
- References
- 19
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 4 · 2023: 1 · 2022: 4 · 2021: 8 · 2020: 4 · 2019: 3 · 2018: 7 · 2017: 9 · 2016: 16 · 2015: 10 · 2014: 12 · 2013: 10 · 2012: 9
- FWCI
- 8.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Nuclear Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- University of Pennsylvania
- National Institutes of Health
- National Cancer Institute (R01CA113941)
- National Institute of Biomedical Imaging and Bioengineering (R01EB009056)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced X-ray and CT Imaging
- Keywords
- time-of-flight PET, whole-body PET, lesion detection, lesion localization, 18F-FDG, list-mode reconstruction, scan time, body mass index
- MeSH terms
- Humans, Image Processing, Computer-Assisted, Liver Neoplasms, Lung Neoplasms, ROC Curve, Time Factors, Fluorodeoxyglucose F18, Positron-Emission Tomography, Body Size, Whole Body Imaging
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