Clinical impact of time-of-flight and point response modeling in PET reconstructions: a lesion detection study
Open accessAbstract
Time-of-flight (TOF) and point spread function (PSF) modeling have been shown to improve PET reconstructions, but the impact on physicians in the clinical setting has not been thoroughly investigated. A lesion detection and localization study was performed using simulated lesions in real patient images. Four reconstruction schemes were considered: ordinary Poisson OSEM (OP) alone and combined with TOF, PSF, and TOF + PSF. The images were presented to physicians experienced in reading PET images, and the performance of each was quantified using localization receiver operating characteristic. Numerical observers (non-prewhitening and Hotelling) were used to identify optimal reconstruction parameters, and observer SNR was compared to the performance of the physicians. The numerical models showed good agreement with human performance, and best performance was achieved by both when using TOF + PSF. These findings suggest a large potential benefit of TOF + PSF for oncology PET studies, especially in the detection of small, low-intensity, focal disease in larger patients.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
PSF compensation can increase the SNR and subjectively rated image quality.
“PSF compensation can also increase the SNR [157,158] and thereby the subjectively rated image quality [157,161,162].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [161]
The Discussion states that PSF modeling can increase numerical-observer SNR in certain tasks when the algorithm has sufficiently converged. The Results report improved physician lesion-detection performance with PSF, but the physicians rated confidence in lesion decisions, not subjective image quality; the paper does not establish that SNR gains thereby improve subjective image-quality ratings. (LLM, conf=0.87)
Experimental — accuracy not yet measuredSchaefferkoetter et al. observed an improvement in lesion detection rates with PSF limited mainly to the lung, while detection rates achieved with TOF extended to the liver and lung.
“This is illustrated by the observation of Schaefferkoetter et al. of an improvement in lesion detection rates with PSF limited mainly to the lung, while the detection rates achieved with TOF extended to the liver and lung [161].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [161]
The Results report improved overall lesion-localization performance with both PSF and TOF, with greater improvement from TOF, and present liver and lung results in Figure 6. The text does not establish the claimed anatomical distinction—that PSF’s improvement was mainly limited to the lung while TOF’s extended to both liver and lung (Results; page not available). (LLM, conf=0.77)
Experimental — accuracy not yet measuredInvestigations with an anthropomorphic phantom or simulated liver and lung lesions have shown that TOF and PSF can have a supplementary effect on increasing lesion detection rates.
“Investigations with an anthropomorphic phantom or with simulated liver and lung lesions have shown that TOF and PSF can have a supplementary effect on increasing lesion detection rates [161,163].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [161]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Erlandsson, K., Buvat, I., Pretorius, P. H., Thomas, B. A., & Hutton, B. F. (2012) · Physics in Medicine and Biology · doi:10.1088/0031-9155/57/21/r119 · Cited by 731 · see citing works
Benefit of Time-of-Flight in PET: Experimental and Clinical Results
Karp, J. S., Surti, S., Daube-Witherspoon, M. E., & Muehllehner, G. (2008) · Journal of Nuclear Medicine · doi:10.2967/jnumed.107.044834 · Cited by 585 · see citing works
Model observers for assessment of image quality.
Barrett, H. H., Yao, J., Rolland, J. P., & Myers, K. J. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.21.9758 · Cited by 542 · see citing works
Fully 3-D PET reconstruction with system matrix derived from point source measurements
Panin, V. Y., Kehren, F., Michel, C., & Casey, M. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.876171 · Cited by 536 · see citing works
Self-citationAbbey, C. K., & Barrett, H. H. (2001) · Journal of the Optical Society of America A · doi:10.1364/josaa.18.000473 · Cited by 326 · see citing works
Unified measurement of observer performance in detecting and localizing target objects on images
Swensson, R. G. (1996) · Medical Physics · doi:10.1118/1.597758 · Cited by 286 · see citing works
Time-of-flight positron emission tomography: status relative to conventional PET.
Budinger, T. F. (1983) · PubMed · Cited by 278 · see citing works
Impact of Time-of-Flight on PET Tumor Detection
Kadrmas, D. J., Casey, M. E., Conti, M., Jakoby, B. W., Lois, C., & Townsend, D. W. (2009) · Journal of Nuclear Medicine · doi:10.2967/jnumed.109.063016 · Cited by 277 · see citing works
Self-citationEffect of random background inhomogeneity on observer detection performance
Rolland, J. P., & Barrett, H. H. (1992) · Journal of the Optical Society of America A · doi:10.1364/josaa.9.000649 · Cited by 273 · see citing works
An Assessment of the Impact of Incorporating Time-of-Flight Information into Clinical PET/CT Imaging
Lois, C., Jakoby, B., Long, M. J., Hübner, K. F., Barker, D. W., Casey, M., Conti, M., Panin, V., Kadrmas, D. J., & Townsend, D. W. (2010) · Journal of Nuclear Medicine · doi:10.2967/jnumed.109.068098 · Cited by 263 · see citing works
Self-citationEffect of noise correlation on detectability of disk signals in medical imaging
Myers, K. J., Barrett, H. H., Borgstrom, M. C., Patton, D. D., & Seeley, G. W. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.001752 · Cited by 205 · see citing works
Improvement in Lesion Detection with Whole-Body Oncologic Time-of-Flight PET
Fakhri, G. E., Surti, S., Trott, C. M., Scheuermann, J. S., & Karp, J. S. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.110.080382 · Cited by 199 · see citing works
Tong, S., Alessio, A. M., & Kinahan, P. E. (2010) · Physics in Medicine and Biology · doi:10.1088/0031-9155/55/5/013 · Cited by 188 · see citing works
First experimental results of time-of-flight reconstruction on an LSO PET scanner
Conti, M., Bendriem, B., Casey, M., Chen, M., Kehren, F., Michel, C. J., & Panin, V. (2005) · Physics in Medicine and Biology · doi:10.1088/0031-9155/50/19/006 · Cited by 164 · see citing works
Self-citationChannelized hotelling and human observer correlation for lesion detection in hepatic SPECT imaging.
Gifford, H. C., King, M. A., de Vries, D. J., & Soares, E. J. (2000) · PubMed · Cited by 162 · see citing works
Predicting human performance by a channelized Hotelling observer model
Yao, J., & Barrett, H. H. (1992) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.130899 · Cited by 124 · see citing works
A comparison of human and model observers in multislice LROC studies
Gifford, H. C., King, M. A., Pretorius, P. H., & Wells, R. G. (2005) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2004.839362 · Cited by 110 · see citing works
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. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.110.086678 · Cited by 104 · see citing works
Bias in iterative reconstruction of low-statistics PET data: benefits of a resolution model
Walker, M. D., Asselin, M.-C., Julyan, P. J., Feldmann, M., Talbot, P. S., Jones, T., & Matthews, J. C. (2011) · Physics in Medicine and Biology · doi:10.1088/0031-9155/56/4/004 · Cited by 102 · see citing works
Experimental evaluation of a simple lesion detection task with time-of-flight PET
Surti, S., & Karp, J. S. (2008) · Physics in Medicine and Biology · doi:10.1088/0031-9155/54/2/013 · Cited by 87 · see citing works
Preserving Poisson characteristics of PET data with weighted OSEM reconstruction
Michel, C. J., Sibomana, M., Boi, A., Bernard, X., Lonneux, M., Defrise, M., Comtat, C., Kinahan, P. E., & Townsend, D. W. (2002) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.1998.774398 · Cited by 81 · see citing works
Self-citationEvaluation of Multiclass Model Observers in PET LROC Studies
Gifford, H. C., Kinahan, P. E., Lartizien, C., & King, M. A. (2007) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2006.889163 · Cited by 53 · see citing works
Performance investigation of a time-of-flight PET/CT scanner
Jakoby, B., Bercier, Y., Conti, M., Casey, M. E., Gremillion, T., Hayden, C., Bendriem, B., & Townsend, D. W. (2008) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2008.4774221 · Cited by 49 · see citing works
Self-citationEffect of Scan Time on Oncologic Lesion Detection in Whole-Body PET
Kadrmas, D. J., Oktay, M. B., Casey, M. E., & Hamill, J. J. (2012) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2012.2197414 · Cited by 44 · see citing works
Self-citationEvaluation of noise properties in PSF-based PET image reconstruction
Tong, S., Alessio, A. M., & Kinahan, P. E. (2009) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2009.5401574 · Cited by 16 · see citing works
Armstrong, I. S., Williams, H. A., & Matthews, J. C. (2011) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2011.6153797 · Cited by 7 · see citing works
Impact of resolution modeling on accuracy and precision of lesion contrast measurements
Daube-Witherspoon, M. E., Matej, S., Werner, M. E., Surti, S., & Karp, J. S. (2011) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2011.6153842 · Cited by 6 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Tomitani T Tanaka E 1980 Noise Characteristics of Positron CT Using Time of Flight Third Symposium on Physical and Technical Aspects of Transmission and Emission Computed Tomography 92 93
Cited by
Sorted by citations
Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls
Rahmim, A., Qi, J., & Sossi, V. (2013) · Medical Physics · doi:10.1118/1.4800806 · Cited by 354 · see citing works
Impact of Image Reconstruction Settings on Texture Features in 18F-FDG PET
Yan, J., Lim, J., Loi, H. Y., Khor, L. K., Sinha, A. K., Quek, S. T., Tham, I. W. K., & Townsend, D. W. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.156927 · Cited by 242 · see citing works
Self-citationShiri, I., Rahmim, A., Ghafarian, P., Geramifar, P., Abdollahi, H., & Bitarafan‐Rajabi, A. (2017) · European Radiology · doi:10.1007/s00330-017-4859-z · Cited by 205 · see citing works
PET quantification: strategies for partial volume correction
Bettinardi, V., Castiglioni, I., De Bernardi, E., & Gilardi, M. C. (2014) · Clinical and Translational Imaging · doi:10.1007/s40336-014-0066-y · Cited by 105 · see citing works
Point-spread function reconstructed PET images of sub-centimeter lesions are not quantitative
Munk, O. L., Tolbod, L. P., Hansen, S. B., & Bogsrud, T. V. (2017) · EJNMMI Physics · doi:10.1186/s40658-016-0169-9 · Cited by 84 · see citing works
Armstrong, I. S., Kelly, M. D., Williams, H. A., & Matthews, J. C. (2014) · EJNMMI Physics · doi:10.1186/s40658-014-0099-3 · Cited by 80 · see citing works
New PET technologies – embracing progress and pushing the limits
Aide, N., Lasnon, C., Kesner, A., Levin, C. S., Buvat, I., Iagaru, A., Hermann, K., Badawi, R. D., Cherry, S. R., Bradley, K. M., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05390-4 · Cited by 73 · see citing works
Minimum lesion detectability as a measure of PET system performance
Adler, S., Seidel, J., Choyke, P. L., Knopp, M. V., Binzel, K., Zhang, J., Barker, C. S., Conant, S., & Maass‐Moreno, R. (2017) · EJNMMI Physics · doi:10.1186/s40658-017-0179-2 · Cited by 66 · see citing works
Advances in PET/CT Technology: An Update
Aide, N., Lasnon, C., Desmonts, C., Armstrong, I. S., Walker, M. D., & McGowan, D. R. (2021) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2021.10.005 · Cited by 55 · see citing works
Noise propagation in resolution modeled PET imaging and its impact on detectability
Rahmim, A., & Tang, J. (2013) · Physics in Medicine and Biology · doi:10.1088/0031-9155/58/19/6945 · Cited by 55 · see citing works
Daube-Witherspoon, M. E., Surti, S., Perkins, A. E., & Karp, J. S. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.127035 · Cited by 56 · see citing works
Optimization of reconstruction and quantification of motion-corrected coronary PET-CT
Doris, M. K., Otaki, Y., Krishnan, S. K., Kwieciński, J., Rubeaux, M., Alessio, A. M., Pan, T., Cadet, S. J., Dey, D., Dweck, M. R., et al. (2018) · Journal of Nuclear Cardiology · doi:10.1007/s12350-018-1317-5 · Cited by 54 · see citing works
Rogasch, J. M., Hofheinz, F., Lougovski, A., Furth, C., Ruf, J., Großer, O. S., Mohnike, K., Hass, P., Walke, M., Amthauer, H., et al. (2014) · EJNMMI Physics · doi:10.1186/2197-7364-1-12 · Cited by 53 · see citing works
Deep learning–based time-of-flight (ToF) image enhancement of non-ToF PET scans
Mehranian, A., Wollenweber, S. D., Walker, M. D., Bradley, K. M., Fielding, P. A., Huellner, M. W., Kotasidis, F. A., Su, K., Johnsen, R., Jansen, F. P., et al. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05824-7 · Cited by 53 · see citing works
Influences on PET Quantification and Interpretation
Rogasch, J. M. M., Hofheinz, F., van Heek, L., Voltin, C.-A., Boellaard, R., & Kobe, C. (2022) · Diagnostics · doi:10.3390/diagnostics12020451 · Cited by 50 · see citing works
Koopman, D., van Dalen, J. A., Lagerweij, M. C. M., Arkies, H., de Boer, J., Oostdijk, A. H. J., Slump, C. H., & Jager, P. L. (2015) · Journal of Nuclear Medicine Technology · doi:10.2967/jnmt.114.147215 · Cited by 48 · see citing works
Positron Emission Tomography-Magnetic Resonance Imaging: Technical Review
Muzic, R. F., & DiFilippo, F. P. (2014) · Seminars in Roentgenology · doi:10.1053/j.ro.2014.10.001 · Cited by 48 · see citing works
Rogasch, J. M., Steffen, I. G., Hofheinz, F., Großer, O. S., Furth, C., Mohnike, K., Hass, P., Walke, M., Apostolova, I., & Amthauer, H. (2015) · EJNMMI Research · doi:10.1186/s13550-015-0111-5 · Cited by 43 · see citing works
Wangerin, K. A., Ahn, S., Wollenweber, S. D., Ross, S. G., Kinahan, P. E., & Manjeshwar, R. M. (2016) · Journal of medical imaging · doi:10.1117/1.jmi.4.1.011002 · Cited by 43 · see citing works
Hori, Y., Hirano, Y., Koshino, K., Moriguchi, T., Iguchi, S., Yamamoto, A., Enmi, J., Kawashima, H., Zeniya, T., Morita, N., et al. (2014) · Physics in Medicine and Biology · doi:10.1088/0031-9155/59/18/5593 · Cited by 32 · see citing works
Self-citationKoopman, D., van Osch, J. A. C., Jager, P. L., Tenbergen, C. J. A., Knollema, S., Slump, C. H., & van Dalen, J. A. (2016) · EJNMMI Physics · doi:10.1186/s40658-016-0158-z · Cited by 31 · see citing works
Yu, Z., Rahman, M. A., Laforest, R. A., Schindler, T. H., Gropler, R. J., Wahl, R. L., Siegel, B. A., & Jha, A. K. (2023) · Medical Physics · doi:10.1002/mp.16407 · Cited by 31 · see citing works
Reducing Radiation Exposure to Paediatric Patients Undergoing [18F]FDG-PET/CT Imaging
Kertész, H., Beyer, T., London, K., Saleh, H., Chung, D. K. V., Rausch, I., Cal-González, J., Kitsos, T., & Kench, P. L. (2021) · Molecular Imaging and Biology · doi:10.1007/s11307-021-01601-4 · Cited by 31 · see citing works
Resolution modeling enhances PET imaging
Alessio, A. M., Rahmim, A., & Orton, C. G. (2013) · Medical Physics · doi:10.1118/1.4821088 · Cited by 29 · see citing works
A phantom design for assessment of detectability in PET imaging
Wollenweber, S. D., Alessio, A. M., & Kinahan, P. E. (2016) · Medical Physics · doi:10.1118/1.4960365 · Cited by 27 · see citing works
Visualization, imaging and new preclinical diagnostics in radiation oncology
Cyran, C. C., Paprottka, P. M., Eisenblätter, M., Clevert, D., Rist, C., Nikolaou, K., Lauber, K., Wenz, F. K., Hausmann, D., Reiser, M. F., et al. (2014) · Radiation Oncology · doi:10.1186/1748-717x-9-3 · Cited by 27 · see citing works
Pitfalls on PET/CT Due to Artifacts and Instrumentation
Tsai, Y., & Liu, C. (2021) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2021.06.015 · Cited by 24 · see citing works
Efficient visual-search model observers for PET
Gifford, H. C. (2014) · British Journal of Radiology · doi:10.1259/bjr.20140017 · Cited by 24 · see citing works
Riegler, G., Karanikas, G., Rausch, I., Hirtl, A., El‐Rabadi, K., Marik, W., Pivec, C., Weber, M., Prosch, H., & Mayerhoefer, M. E. (2017) · European Journal of Radiology · doi:10.1016/j.ejrad.2017.02.023 · Cited by 23 · see citing works
Ketabi, A., Ghafarian, P., Mosleh‐Shirazi, M. A., Mahdavi, S. R., Rahmim, A., & Ay, M. R. (2018) · European Radiology · doi:10.1007/s00330-018-5754-y · Cited by 24 · see citing works
Shang, K., Cui, B., Ma, J., Shuai, D., Liang, Z., Jansen, F. P., Zhou, Y., Lu, J., & Zhao, G. (2017) · European Journal of Radiology · doi:10.1016/j.ejrad.2017.05.029 · Cited by 21 · see citing works
Sheikhbahaei, S., Marcus, C. V., Wray, R., Rahmim, A., Lodge, M. A., & Subramaniam, R. M. (2015) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000000445 · Cited by 20 · see citing works
Recent Advances in Hybrid Molecular Imaging Systems
Lee, J. S., & Kim, J. (2014) · Seminars in Musculoskeletal Radiology · doi:10.1055/s-0034-1371014 · Cited by 20 · see citing works
Improving PET spatial resolution and detectability for prostate cancer imaging
Bal, H., Guérin, L., Casey, M. E., Conti, M., Eriksson, L., Michel, C. J., Fanti, S., Pettinato, C., Adler, S., & Choyke, P. L. (2014) · Physics in Medicine and Biology · doi:10.1088/0031-9155/59/15/4411 · Cited by 20 · see citing works
Self-citationMoving the goalposts while scoring―the dilemma posed by new PET technologies
Rogasch, J. M. M., Boellaard, R., Pike, L., Borchmann, P., Johnson, P., Wolf, J., Barrington, S. F., & Kobe, C. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05403-2 · Cited by 20 · see citing works
Koopman, D., van Dalen, J. A., Arkies, H., Oostdijk, A. H. J., Francken, A. B., Bart, J., Slump, C. H., Knollema, S., & Jager, P. L. (2018) · EJNMMI Research · doi:10.1186/s13550-018-0359-7 · Cited by 19 · see citing works
Mehranian, A., Kotasidis, F. A., & Zaidi, H. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/3/1309 · Cited by 17 · see citing works
Schaefferkoetter, J. D., Ouyang, J., Rakvongthai, Y., Nappi, C., & Fakhri, G. E. (2014) · Medical Physics · doi:10.1118/1.4875725 · Cited by 16 · see citing works
Self-citationArmstrong, I. S., James, J. M., Williams, H. A., Kelly, M. D., & Matthews, J. C. (2015) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000000305 · Cited by 15 · see citing works
Shekari, M., Ghafarian, P., Ahangari, S., & Ay, M. R. (2017) · Nuclear Science and Techniques · doi:10.1007/s41365-017-0308-6 · Cited by 12 · see citing works
Armstrong, I. S., Thomson, K. E., Rowley, L. M., & McGowan, D. R. (2017) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000000682 · Cited by 13 · see citing works
Karakatsanis, N. A., Zein, S. A., & Nehmeh, S. A. (2018) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2018.8824514 · Cited by 11 · see citing works
New prospects for PET in prostate cancer imaging: a physicist's viewpoint
Conti, M. (2014) · EJNMMI Physics · doi:10.1186/2197-7364-1-11 · Cited by 11 · see citing works
Dose Reduction in Brain [18F]FDG PET/MRI: Give It Half a Chance
Soret, M., Piekarski, E., Yeni, N., Giron, A., Maisonobe, J.-A., Khalifé, M., Zaslavsky, C., Bertaux, M., Habert, M., & Kas, A. (2019) · Molecular Imaging and Biology · doi:10.1007/s11307-019-01398-3 · Cited by 11 · see citing works
Hou, X., Ma, H., Esquinas, P. L., Uribe, C., Tolhurst, S., Bénard, F., Liu, D. M., Rahmim, A., & Celler, A. M. (2020) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aba8b5 · Cited by 11 · see citing works
Optimized Bayes variational regularization prior for 3D PET images
Rapisarda, E., Presotto, L., Bernardi, E. D., Gilardi, M. C., & Bettinardi, V. (2014) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2014.05.004 · Cited by 8 · see citing works
Rezaei, S., Ghafarian, P., Jha, A. K., Rahmim, A., Sarkar, S., & Ay, M. R. (2019) · Physica Medica · doi:10.1016/j.ejmp.2019.10.031 · Cited by 8 · see citing works
Rezaei, S., Ghafarian, P., Karam, M. B., Uribe, C., Rahmim, A., Sarkar, S., & Ay, M. R. (2020) · Japanese Journal of Radiology · doi:10.1007/s11604-019-00914-3 · Cited by 8 · see citing works
Lu, S., Zhang, P., Li, C., Sun, J., Liu, W., & Zhang, P. (2021) · BMC Medical Imaging · doi:10.1186/s12880-021-00683-4 · Cited by 7 · see citing works
Applications of both time of flight and point spread function in brain PET image reconstruction
Shao, X., Shao, X., Wang, X., & Wang, Y. (2015) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000000459 · Cited by 8 · see citing works
Zhang, X., Peng, Q., Zhou, J., Huber, J. S., Moses, W. W., & Qi, J. (2018) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aab0f3 · Cited by 8 · see citing works
Machado, M. A. D., Menezes, V. O. M. D. O., Namías, M., Vieira, N. S., Queiroz, C. C., Matheoud, R., Alessio, A. M., & Oliveira, M. L. (2018) · Journal of Nuclear Medicine Technology · doi:10.2967/jnmt.118.213405 · Cited by 8 · see citing works
Sharifpour, R., Ghafarian, P., Rahmim, A., & Ay, M. R. (2017) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000000732 · Cited by 7 · see citing works
Cattaneo, G. M., Bettinardi, V., Mapelli, P., & Picchio, M. (2016) · Physica Medica · doi:10.1016/j.ejmp.2016.02.013 · Cited by 7 · see citing works
Point Spread Function Reconstruction for Integrated 18F-FET PET/MRI in Patients With Glioma
Rogasch, J. M. M., Albers, J., Steinkrüger, F. L. G. A., Lukas, M., Wedel, F., Amthauer, H., & Furth, C. (2018) · Clinical Nuclear Medicine · doi:10.1097/rlu.0000000000002423 · Cited by 7 · see citing works
Deep learning-based time-of-flight (ToF) enhancement of non-ToF PET scans for different radiotracers
Mehranian, A., Wollenweber, S. D., Bradley, K. M., Fielding, P. A., Huellner, M. W., Iagaru, A. H., Dedja, M., Colwell, T., Kotasidis, F. A., Johnsen, R., et al. (2025) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-025-07119-z · Cited by 6 · see citing works
Jung-Soo, K., Park, C., Seok-Hwan, Y., Lee, J.-A., Kim, T., & Yang, H.-J. (2021) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000001368 · Cited by 6 · see citing works
Performance simulation of a compact PET insert for simultaneous PET/MR breast imaging
Liang, Y., & Peng, H. (2014) · Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · doi:10.1016/j.nima.2014.03.009 · Cited by 5 · see citing works
Karakatsanis, N. A., Mehranian, A., Lodge, M. A., Casey, M., Rahmim, A., & Zaidi, H. (2015) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2015.7582185 · Cited by 5 · see citing works
Self-citationNumerical observer for atherosclerotic plaque classification in spectral computed tomography
Lorsakul, A., Fakhri, G. E., Worstell, W. A., Ouyang, J., Rakvongthai, Y., Laine, A. F., & Li, Q. (2016) · Journal of medical imaging · doi:10.1117/1.jmi.3.3.035501 · Cited by 5 · see citing works
Girard, A., François, M., Chaboub, N., Reste, P. L., Devillers, A., Saint‐Jalmes, H., Jeune, F. L., & Palard-Novello, X. (2021) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims-21-742 · Cited by 5 · see citing works
Reconstruction of uptake patterns in PET : The influence of regularizing prior
Bernardi, E. D., Fallanca, F., Gianolli, L., Gilardi, M. C., & Bettinardi, V. (2017) · Medical Physics · doi:10.1002/mp.12205 · Cited by 4 · see citing works
Cistaro, A., Quartuccio, N., Vesco, S., Pagani, M., Fania, P., Donati, L. F., Nobili, F. M., Duca, S., Carrara, G., & Valentini, M. C. (2012) · Ophthalmology · doi:10.1016/j.ophtha.2012.02.047 · Cited by 3 · see citing works
Mohymen, A. A., Farag, H. I., Reda, S., Monem, A. S., & Ali, S. A. (2025) · Applied Radiation and Isotopes · doi:10.1016/j.apradiso.2025.111761 · Cited by 2 · see citing works
Kalantari, F., Sen, A. K., & Gifford, H. C. (2014) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2044423 · Cited by 2 · see citing works
The Impact of Point Spread Function Modeling on Scan Duration in PET Imaging
Ahangari, S., Ghafarian, P., Shekari, M., Ghadiri, H., Karam, M. B., & Ay, M. R. (2015) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 2 · see citing works
Fukai, S., Daisaki, H., Shimada, N., Ishiyama, M., Umeda, T., Yamashita, K., Miyaji, N., Takiguchi, T., Kawakami, H., & Terauchi, T. (2022) · Biomedical engineering and physics express · doi:10.1088/2057-1976/aca90d · Cited by 2 · see citing works
Sanghera, B., Wood, K., Sonoda, L. I., Gogbashian, A., Lowe, G. J., Nunes, A. F., Stirling, J., Shepherd, C., Beynon, G., & Wong, W. L. (2016) · Molecular Imaging and Radionuclide Therapy · doi:10.4274/mirt.18189 · Cited by 2 · see citing works
Wang, X., Yang, B., Adams, M. P., Gao, X., Karakatsanis, N. A., & Tang, J. (2018) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aad8f9 · Cited by 2 · see citing works
Wakabayashi, Y., Kashikura, K., Takahashi, Y., Yabe, H., Ichikawa, A., Yamamoto, S., Ishii, A., & Doi, K. (2016) · Europe PMC (PubMed Central) · doi:10.7508/aojnmb.2016.04.007 · Cited by 1 · see citing works
[PET] 6. Overview of Clinical Applications of Artificial Intelligence in PET
Emura, R. (2023) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.2023-2212 · Cited by 1 · see citing works
Objective Task-Based Evaluation of Quantitative Medical Imaging Methods
Liu, Y., Xia, H., Obuchowski, N. A., Laforest, R. A., Rahmim, A., Siegel, B. A., & Jha, A. K. (2025) · PET Clinics · doi:10.1016/j.cpet.2025.07.006 · Cited by 1 · see citing works
Huang, K., Feng, Y., Liang, W., & Li, L. (2021) · BMC Medical Imaging · doi:10.1186/s12880-021-00699-w
Antić, V., & Haglund, J. (2016) · RAD Conference Proceedings. · doi:10.21175/radproc.2016.29
A PET/CT Phantom for Evaluating The PET Image Quality of Micro-Lesion and CT Performance ParametersPreprint
Lu, S., Zhang, P., Li, C., Sun, J., Liu, W., & Zhang, P. (2020) · Research Square · doi:10.21203/rs.3.rs-108386/v1
Holm, S., Mawlawi, O. R., & Beyer, T. (2017) · Imaging in medical diagnosis and therapy · doi:10.1201/9781315374383-18
Sossi, V., & Walker, M. D. (2016) · Imaging in medical diagnosis and therapy · doi:10.1201/b19052-11
Alamdari, M. O., Ghafarian, P., Rahmim, A., Karam, M. B., & Ay, M. R. (2023) · Nuclear Science and Techniques · doi:10.1007/s41365-023-01321-0
New Imaging Technologies and Software in Nuclear Cardiology
Gülbiçim, H., & Yusuf, A. R. (2024) · Nuclear Medicine Seminars · doi:10.4274/nts.galenos.2024.0001
Mohamed, A. A., Farag, H. I., Reda, S., Soltan, A., & Ali, S. A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4812783
Fukai, S., Daisaki, H., Onda, R., 志賀真奈美, Yoshida, H., Motegi, K., Shimada, N., Takatsu, K., Nakagawa, M., & Terauchi, T. (2026) · Physical and Engineering Sciences in Medicine · doi:10.1007/s13246-026-01742-2
- Authors
- Schaefferkoetter, J., Casey, M., Townsend, D., & El Fakhri, G.
- Affiliations
- University of Tennessee Medical Center (US)
- Siemens Healthcare (United States) (US)
- Agency for Science, Technology and Research (SG)
- Venue
- Physics in Medicine and Biology
- Publisher
- IOP Publishing
- Published
- 2013-02-13
- Volume
- 58
- Issue
- 5
- Pages
- 1465-1478
- ISSN
- 0031-9155 (ISSN-L)
- 1361-6560
- PMC
- PMC3616316
- OpenAlex
- W1998484751
- Cited by
- 85
- References
- 27
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 10 · 2020: 3 · 2019: 3 · 2018: 9 · 2017: 10 · 2016: 10 · 2015: 8 · 2014: 15 · 2013: 3 · 2012: 1
- FWCI
- 9.31
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Physics in Medicine and Biology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01HL110241)
- National Cancer Institute (R01CA165221)
- 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, point spread function modeling, PET image reconstruction, lesion detection, lesion localization, observer performance, Hotelling observer
- MeSH terms
- Humans, Image Processing, Computer-Assisted, Models, Theoretical, Neoplasms, Time Factors, Observer Variation, Positron-Emission Tomography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review