EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies

From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors

Wahl, R. L., Jacene, H., Kasamon, Y., & Lodge, M. A. (2009) · Journal of Nuclear Medicine · doi:10.2967/jnumed.108.057307 · Cited by 3,777 · see citing works

FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0

Boellaard, R., Delgado-Bolton, R., Oyen, W. J. G., Giammarile, F., Tatsch, K., Eschner, W., Verzijlbergen, F. J., Barrington, S. F., Pike, L. C., Weber, W. A., et al. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-014-2961-x · Cited by 3,303 · see citing works

FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0

Boellaard, R., O’Doherty, M. J., Weber, W., Mottaghy, F. M., Lonsdale, M. N., Stroobants, S. G., Oyen, W. J. G., Kotzerke, J., Hoekstra, O. S., Pruim, J., et al. (2009) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-009-1297-4 · Cited by 1,329 · see citing works

Standards for PET Image Acquisition and Quantitative Data Analysis

Boellaard, R. (2009) · Journal of Nuclear Medicine · doi:10.2967/jnumed.108.057182 · Cited by 906 · see citing works

Performance Measurements of the Siemens mMR Integrated Whole-Body PET/MR Scanner

Delso, G., Fürst, S., Jakoby, B., Ladebeck, R., Ganter, C., Nekolla, S. G., Schwaiger, M., & Ziegler, S. I. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.092726 · Cited by 870 · 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

Characterization of PET/CT images using texture analysis: the past, the present… any future?

Hatt, M., Tixier, F., Pierce, L. A., Kinahan, P. E., Rest, C. C. L., & Visvikis, D. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3427-0 · Cited by 480 · see citing works

Simultaneous maximum a posteriori reconstruction of attenuation and activity distributions from emission sinograms

Nuyts, J. L., Dupont, P. J., Stroobants, S. G., Benninck, R., Mortelmans, L., & Suetens, P. (1999) · IEEE Transactions on Medical Imaging · doi:10.1109/42.774167 · Cited by 361 · see citing works

PET-CT–Based Auto-Contouring in Non–Small-Cell Lung Cancer Correlates With Pathology and Reduces Interobserver Variability in the Delineation of the Primary Tumor and Involved Nodal Volumes

van Baardwijk, A. A. W., Bosmans, G., Boersma, L. J., Buijsen, J., Wanders, S. L., Hochstenbag, M. M. H., van Suylen, R. J., Dekker, A. L. A. J., Oberije, C., Houben, R. M. A., et al. (2007) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2006.12.067 · Cited by 295 · see citing works

Combination of baseline metabolic tumour volume and early response on PET/CT improves progression-free survival prediction in DLBCL

Mikhaeel, N. G., Smith, D., Dunn, J., Phillips, M., Møller, H., Fields, P. A., Wrench, D., & Barrington, S. F. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3315-7 · Cited by 295 · see citing works

Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation

van Velden, F. H. P., Kramer, G. M., Frings, V., Nissen, I. A., Mulder, E. R., de Langen, A. J., Hoekstra, O. S., Smit, E. F., & Boellaard, R. (2016) · Molecular Imaging and Biology · doi:10.1007/s11307-016-0940-2 · Cited by 286 · see citing works

FDG PET for therapy monitoring in Hodgkin and non-Hodgkin lymphomas

Barrington, S. F., & Kluge, R. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3690-8 · Cited by 281 · see citing works

Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System

Teoh, E. J., McGowan, D. R., Macpherson, R. E., Bradley, K. M., & Gleeson, F. V. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.159301 · Cited by 265 · see citing works

PET/MR imaging of bone lesions—Implications for PET quantification from imperfect attenuation correction

Samarin, A., Burger, C., Wollenweber, S. D., Crook, D. W., Burger, I. A., Schmid, D. T., von Schulthess, G. K., & Kuhn, F. P. (2012) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-012-2113-0 · Cited by 251 · see citing works

NEMA NU 2-2012 performance studies for the SiPM-based ToF-PET component of the GE SIGNA PET/MR system

Grant, A. M., Deller, T. W., Khalighi, M. M., Maramraju, S. H., Delso, G., & Levin, C. S. (2016) · Medical Physics · doi:10.1118/1.4945416 · Cited by 246 · see citing works

Zero TE MR bone imaging in the head

Wiesinger, F., Sacolick, L. I., Menini, A., Kaushik, S. S., Ahn, S., Veit‐Haibach, P., Delso, G., & Shanbhag, D. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25545 · Cited by 241 · see citing works

Quantification, improvement, and harmonization of small lesion detection with state-of-the-art PET

van der Vos, C. S., Koopman, D., Rijnsdorp, S., Arends, A. J., Boellaard, R., van Dalen, J. A., Lubberink, M., Willemsen, A. T. M., & Visser, E. P. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3727-z · Cited by 206 · see citing works

A multicompartment body composition technique based on computerized tomography.

Chowdhury, B., Sjöström, L., Alpsten, M., Kostanty, J., Kvist, H., & Löfgren, R. (1994) · PubMed · Cited by 203 · see citing works

Evaluating tumor response with FDG PET: updates on PERCIST, comparison with EORTC criteria and clues to future developments

Pinker, K., Riedl, C. C., & Weber, W. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3687-3 · Cited by 172 · see citing works

Quantitative PET/CT Scanner Performance Characterization Based Upon the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network Oncology Clinical Simulator Phantom

Sunderland, J. J., & Christian, P. E. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.114.148056 · Cited by 144 · see citing works

Clinical Evaluation of Zero-Echo-Time MR Imaging for the Segmentation of the Skull

Delso, G., Wiesinger, F., Sacolick, L. I., Kaushik, S. S., Shanbhag, D., Hüllner, M. W., & Veit‐Haibach, P. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.114.149997 · Cited by 138 · see citing works

Variations in Clinical PET/CT Operations: Results of an International Survey of Active PET/CT Users

Beyer, T., Czernin, J., & Freudenberg, L. S. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.110.079624 · Cited by 136 · see citing works

Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients

Lasnon, C., Desmonts, C., Quak, E., Gervais, R., Dô, P., Dubos‐Arvis, C., & Aide, N. (2013) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-013-2391-1 · Cited by 126 · see citing works

Optimum Lean Body Formulation for Correction of Standardized Uptake Value in PET Imaging

Tahari, A. K., Chien, D. C., Azadi, J. R., & Wahl, R. L. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.136986 · Cited by 123 · see citing works

FDG PET/CT texture analysis for predicting the outcome of lung cancer treated by stereotactic body radiation therapy

Lovinfosse, P., Jánváry, Z. L., Coucke, P. A., Jodogne, S., Bernard, C., Hatt, M., Visvikis, D., Jansen, N., Duysinx, B., & Hustinx, R. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3314-8 · Cited by 112 · see citing works

Development of a nomogram combining clinical staging with 18F-FDG PET/CT image features in non-small-cell lung cancer stage I–III

Desseroit, M.-C., Visvikis, D., Tixier, F., Majdoub, M., Perdrisot, R., Guillevin, R., Rest, C. C. L., & Hatt, M. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3325-5 · Cited by 109 · see citing works

Impact of [18F]FDG PET imaging parameters on automatic tumour delineation: need for improved tumour delineation methodology

Cheebsumon, P., Yaqub, M. M., van Velden, F. H. P., Hoekstra, O. S., Lammertsma, A. A., & Boellaard, R. (2011) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-011-1899-5 · Cited by 108 · see citing works

Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients

Quak, E., Le Roux, P.-Y., Hofman, M. S., Robin, P., Bourhis, D., Callahan, J., Binns, D., Desmonts, C., Salaun, P.-Y., Hicks, R. J., et al. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-015-3128-0 · Cited by 107 · see citing works

Summary of the UPICT Protocol for 18F-FDG PET/CT Imaging in Oncology Clinical Trials

Graham, M. M., Wahl, R. L., Hoffman, J. M., Yap, J. T., Sunderland, J. J., Boellaard, R., Perlman, E. S., Kinahan, P. E., Christian, P. E., Hoekstra, O. S., et al. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.158402 · Cited by 103 · see citing works

Variations in PET/CT Methodology for Oncologic Imaging at U.S. Academic Medical Centers: An Imaging Response Assessment Team Survey

Graham, M. M., Badawi, R. D., & Wahl, R. L. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.109.074104 · Cited by 103 · see citing works

Evaluation of Atlas-Based Attenuation Correction for Integrated PET/MR in Human Brain: Application of a Head Atlas and Comparison to True CT-Based Attenuation Correction

Sekine, T., Buck, A., Delso, G., ter Voert, E. E. G. W., Huellner, M. W., Veit‐Haibach, P., & Warnock, G. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.159228 · Cited by 94 · see citing works

Does a novel penalized likelihood reconstruction of 18F-FDG PET-CT improve signal-to-background in colorectal liver metastases?

Parvizi, N., Franklin, J. M., McGowan, D. R., Teoh, E., Bradley, K. M., & Gleeson, F. V. (2015) · European Journal of Radiology · doi:10.1016/j.ejrad.2015.06.025 · Cited by 91 · see citing works

Sequential whole-body PET/MR scanner: concept, clinical use, and optimisation after two years in the clinic. The manufacturer’s perspective

Kalemis, A., Delattre, B. M. A., & Heinzer-Schweizer, S. (2012) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-012-0330-y · Cited by 88 · see citing works

Accurate PET/MR Quantification Using Time of Flight MLAA Image Reconstruction

Boellaard, R., Hofman, M. B. M., Hoekstra, O. S., & Lammertsma, A. A. (2014) · Molecular Imaging and Biology · doi:10.1007/s11307-013-0716-x · Cited by 87 · see citing works

Hybrid ZTE /Dixon MR ‐based attenuation correction for quantitative uptake estimation of pelvic lesions in PET / MRI

Leynes, A. P., Yang, J., Shanbhag, D., Kaushik, S. S., Seo, Y., Hope, T. A., Wiesinger, F., & Larson, P. E. Z. (2017) · Medical Physics · doi:10.1002/mp.12122 · Cited by 82 · see citing works

Mutatis Mutandis: Harmonize the Standard!

Boellaard, R. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.094763 · Cited by 78 · see citing works

Assessment of tumour size in PET/CT lung cancer studies: PET- and CT-based methods compared to pathology

Cheebsumon, P., Boellaard, R., Ruysscher, D. D., van Elmpt, W., van Baardwijk, A. A. W., Yaqub, M. M., Hoekstra, O. S., Comans, E. F. I., Lammertsma, A. A., & van Velden, F. H. P. (2012) · EJNMMI Research · doi:10.1186/2191-219x-2-56 · Cited by 75 · see citing works

Multicenter Harmonization of 89Zr PET/CT Performance

Makris, N. E., Boellaard, R., Visser, E. P., de Jong, J. R., Vanderlinden, B., Wierts, R., der Veen, B. J. D. W., Greuter, H. N. J. M., Vugts, D. J., van Dongen, G. A. M. S., et al. (2013) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.130112 · Cited by 69 · see citing works

Effects of Image Characteristics on Performance of Tumor Delineation Methods: A Test–Retest Assessment

Cheebsumon, P., van Velden, F. H. P., Yaqub, M. M., Frings, V., de Langen, A. J., Hoekstra, O. S., Lammertsma, A. A., & Boellaard, R. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.088914 · Cited by 68 · see citing works

Investigating the state-of-the-art in whole-body MR-based attenuation correction: an intra-individual, inter-system, inventory study on three clinical PET/MR systems

Beyer, T., Lassen, M. L., Boellaard, R., Delso, G., Yaqub, M., Sattler, B., & Quick, H. H. (2016) · Magnetic Resonance Materials in Physics, Biology and Medicine · doi:10.1007/s10334-015-0505-4 · Cited by 66 · see citing works

Impact of PET/CT image reconstruction methods and liver uptake normalization strategies on quantitative image analysis

Kuhnert, G., Boellaard, R., Sterzer, S., Kahraman, D., Scheffler, M., Wolf, J., Dietlein, M., Drzezga, A. E., & Kobe, C. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-015-3165-8 · Cited by 62 · see citing works

Quality control for quantitative multicenter whole-body PET/MR studies: A NEMA image quality phantom study with three current PET/MR systems

Boellaard, R., Rausch, I., Beyer, T., Delso, G., Yaqub, M., Quick, H. H., & Sattler, B. (2015) · Medical Physics · doi:10.1118/1.4930962 · Cited by 62 · see citing works

NEMA image quality phantom measurements and attenuation correction in integrated PET/MR hybrid imaging

Ziegler, S., Jakoby, B., Braun, H., Paulus, D. H., & Quick, H. H. (2015) · EJNMMI Physics · doi:10.1186/s40658-015-0122-3 · Cited by 60 · see citing works

SUVref: reducing reconstruction-dependent variation in PET SUV

Kelly, M. D., & Declerck, J. M. (2011) · EJNMMI Research · doi:10.1186/2191-219x-1-16 · Cited by 58 · see citing works

Staging the axilla in breast cancer patients with 18F-FDG PET: how small are the metastases that we can detect with new generation clinical PET systems?

Bellèvre, D., Blanc‐Fournier, C., Switsers, O., Dugué, A. E., Lévy, C., Allouache, D., Desmonts, C., Crouet, H., Guilloit, J., Grellard, J., et al. (2014) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-014-2689-7 · Cited by 58 · see citing works

Current Image Acquisition Options in PET/MR

Boellaard, R., & Quick, H. H. (2015) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2014.12.001 · Cited by 56 · see citing works

18F-FDG PET/CT heterogeneity quantification through textural features in the era of harmonisation programs: a focus on lung cancer

Lasnon, C., Majdoub, M., Lavigne, B., Dô, P., Madelaine, J., Visvikis, D., Hatt, M., & Aide, N. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3441-2 · Cited by 53 · see citing works

Lean body mass-based standardized uptake value, derived from a predictive equation, might be misleading in PET studies

Erselcan, T., Turgut, B., Doğan, D. Ö., & Özdemir, S. (2002) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-002-0974-3 · Cited by 44 · see citing works

Does PET SUV Harmonization Affect PERCIST Response Classification?

Quak, E., Roux, P. L., Lasnon, C., Robin, P., Hofman, M. S., Bourhis, D., Callahan, J., Binns, D., Desmonts, C., Salaün, P., et al. (2016) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.171983 · Cited by 41 · see citing works

Generating harmonized SUV within the EANM EARL accreditation program: software approach versus EARL-compliant reconstruction

Lasnon, C., Salomon, T., Desmonts, C., Dô, P., Oulkhouir, Y., Madelaine, J., & Aide, N. (2016) · Annals of Nuclear Medicine · doi:10.1007/s12149-016-1135-2 · Cited by 41 · see citing works

Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers

Burgos, N., Cardoso, M. J., Thielemans, K., Marc Modat, A., Dickson, J. C., Schott, J. M., Atkinson, D., Arridge, S., Hutton, B. F., & Sebastien Ourselin, A. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-015-3082-x · Cited by 37 · see citing works

Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs)

Lasnon, C., Enilorac, B., Popotte, H., & Aide, N. (2017) · EJNMMI Research · doi:10.1186/s13550-017-0279-y · Cited by 35 · see citing works

A Digital Reference Object to Analyze Calculation Accuracy of PET Standardized Uptake Value

Pierce, L. A., Elston, B. F., Clunie, D., Nelson, D. P., & Kinahan, P. E. (2015) · Radiology · doi:10.1148/radiol.2015141262 · Cited by 35 · see citing works

Variation of system performance, quality control standards and adherence to international FDG-PET/CT imaging guidelines

Bergmann, H., Geist, B. K., Schaffarich, M. P., Hirtl, A., Hacker, M., Beyer, T., & Rausch, I. (2014) · Nuklearmedizin - NuclearMedicine · doi:10.3413/nukmed-0665-14-05 · Cited by 33 · see citing works

Unterschiede in Systemeigenschaften, Qualitätsstandards und Berücksichtigung internationaler FDG-PET/CT-Bildgebungsrichtlinien

Rausch, I., Bergmann, H., Geist, B. K., Schaffarich, M. P., Hirtl, A., Hacker, M., & Beyer, T. (2014) · Nuklearmedizin - NuclearMedicine · Cited by 27 · see citing works

EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program

Lasnon, C., Quak, E., Roux, P. L., Robin, P., Hofman, M. S., Bourhis, D., Callahan, J., Binns, D., Desmonts, C., Salaün, P., et al. (2017) · EJNMMI Physics · doi:10.1186/s40658-017-0185-4 · Cited by 27 · see citing works

The importance of harmonizing interim positron emission tomography in non-Hodgkin lymphoma: focus on the Deauville criteria

Quak, E., Hovhannisyan, N., Lasnon, C., Fruchart, C., Vilque, J., Musafiri, D., & Aide, N. (2014) · Haematologica · doi:10.3324/haematol.2014.104125 · Cited by 25 · see citing works

Quantitative Evaluation of Atlas-based Attenuation Correction for Brain PET in an Integrated Time-of-Flight PET/MR Imaging System

Yang, J., Jian, Y., Jenkins, N. W., Behr, S. C., Hope, T. A., Larson, P. E. Z., Vigneron, D. B., & Seo, Y. (2017) · Radiology · doi:10.1148/radiol.2017161603 · Cited by 22 · see citing works

Methodological Aspects of Multicenter Studies with Quantitative PET

Boellaard, R. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-062-1_18 · Cited by 21 · see citing works

Comparison of SUVs Normalized by Lean Body Mass Determined by CT with Those Normalized by Lean Body Mass Estimated by Predictive Equations in Normal Tissues

Kim, W. H., Kim, C. G., & Kim, D. (2012) · Nuclear Medicine and Molecular Imaging · doi:10.1007/s13139-012-0146-8 · Cited by 20 · see citing works

Patient’s weight: a neglected cause of variability in SUV measurements? A survey from an EARL accredited PET centre in 513 patients

Lasnon, C., Houdu, B., Kammerer, E., Salomon, T., Devreese, J., Lebasnier, A., & Aide, N. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-015-3214-3 · Cited by 17 · see citing works

A Method to Improve the Semiquantification of 18F-FDG Uptake: Reliability of the Estimated Lean Body Mass Using the Conventional, Low-Dose CT from PET/CT

Decazes, P., Métivier, D., Rouquette, A., Talbot, J., & Kerrou, K. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.164913 · Cited by 16 · see citing works

Review of clinically accessible methods to determine lean body mass for normalization of standardized uptake values.

Devriese, J., Beels, L., Maes, A. F., Wiele, C. V. D., Gheysens, O. S., & Pottel, H. (2016) · PubMed · Cited by 11 · see citing works

CT synthesis in the head & neck region for PET/MR attenuation correction: an iterative multi-atlas approach

Burgos, N., Cardoso, M. J., Marc Modat, A., Punwani, S., Atkinson, D., Arridge, S., Hutton, B. F., & Sebastien Ourselin, A. (2015) · EJNMMI Physics · doi:10.1186/2197-7364-2-s1-a31 · Cited by 7 · see citing works

FDG PET/CT for assessing tumour response to immunotherapy

Aide, N., Hicks, R. J., Tourneau, C. L., Lheureux, S., Fanti, S., & Lopci, E. (2018) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-018-4171-4 · Cited by 263 · see citing works

Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization

Papadimitroulas, P., Brocki, L., Christopher Chung, N., Marchadour, W., Vermet, F., Gaubert, L., Eleftheriadis, V., Plachouris, D., Visvikis, D., Kagadis, G. C., et al. (2021) · Physica Medica · doi:10.1016/j.ejmp.2021.03.009 · Cited by 226 · see citing works

Quantification, improvement, and harmonization of small lesion detection with state-of-the-art PET

van der Vos, C. S., Koopman, D., Rijnsdorp, S., Arends, A. J., Boellaard, R., van Dalen, J. A., Lubberink, M., Willemsen, A. T. M., & Visser, E. P. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3727-z · Cited by 206 · see citing works

Harmonization strategies for multicenter radiomics investigations

Da‐ano, R., Visvikis, D., & Hatt, M. (2020) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aba798 · Cited by 161 · see citing works

PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group

Albert, N., Galldiks, N., Ellingson, B., van den Bent, M. J., Chang, S. M., Cicone, F., de Groot, J. D., Koh, E., Law, I., Rhun, É. L., et al. (2024) · The Lancet Oncology · doi:10.1016/s1470-2045(23)00525-9 · Cited by 126 · see citing works

Response assessment using 68Ga-PSMA ligand PET in patients undergoing 177Lu-PSMA radioligand therapy for metastatic castration-resistant prostate cancer

Grubmüller, B., Senn, D., Kramer, G., Baltzer, P., D’Andrea, D., Grubmüller, K. H., Mitterhauser, M., Eidherr, H., Haug, A. R., Wadsak, W., et al. (2018) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-018-4236-4 · Cited by 153 · see citing works

Strategies and technical challenges for imaging oligometastatic disease: Recommendations from the European Organisation for Research and Treatment of Cancer imaging group

deSouza, N. M., Liu, Y., Chiti, A., Oprea‐Lager, D. E., Gebhart, G., BEERS, B. E. V., Herrmann, K., & Lecouvet, F. E. (2018) · European Journal of Cancer · doi:10.1016/j.ejca.2017.12.012 · Cited by 138 · see citing works

18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma

Eertink, J. J., van de Brug, T., Wiegers, S. E., Zwezerijnen, G. J. C., Pfaehler, E. A. G., Lugtenburg, P. J., van der Holt, B., de Vet, H. C. W., Hoekstra, O. S., Boellaard, R., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05480-3 · Cited by 137 · see citing works

Review of Gallium-68 PSMA PET/CT Imaging in the Management of Prostate Cancer

Lenzo, N. P., Meyrick, D. P., & Turner, J. H. (2018) · Diagnostics · doi:10.3390/diagnostics8010016 · Cited by 136 · see citing works

Baseline metabolic tumor burden on FDG PET/CT scans predicts outcome in advanced NSCLC patients treated with immune checkpoint inhibitors

Seban, R., Mezquita, L., Berenbaum, A., Dercle, L., Botticella, A., Pechoux, C. L., Caramella, C., Deutsch, É., Grimaldi, S., Adam, J., et al. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04615-x · Cited by 135 · see citing works

First-in-Humans Study of the SSTR Antagonist ¹⁷⁷Lu-DOTA-LM3 for Peptide Receptor Radionuclide Therapy in Patients with Metastatic Neuroendocrine Neoplasms: Dosimetry, Safety, and Efficacy

Baum, R. P., Zhang, J., Schuchardt, C., Müller, D., & Mäcke, H. (2021) · Journal of Nuclear Medicine · doi:10.2967/jnumed.120.258889 · Cited by 127 · see citing works

SNMMI Procedure Standard/EANM Practice Guideline on Pediatric18F-FDG PET/CT for Oncology 1.0

Vali, R., Alessio, A. M., Balza, R., Borgwardt, L., Bar‐Sever, Z., Czachowski, M. R., Jehanno, N., Kurch, L., Pandit-Taskar, N. D., Parisi, M. T., et al. (2020) · Journal of Nuclear Medicine · doi:10.2967/jnumed.120.254110 · Cited by 125 · see citing works

Diagnostic Imaging in Vascular Graft Infection: A Systematic Review and Meta-Analysis

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Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon

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Procedural recommendations of cardiac PET/CT imaging: standardization in inflammatory-, infective-, infiltrative-, and innervation (4Is)-related cardiovascular diseases: a joint collaboration of the EACVI and the EANM

Slart, R. H. J. A., Glaudemans, A. W. J. M., Gheysens, O. S., Lubberink, M., Kero, T., Dweck, M. R., Habib, G., Gaemperli, O., Saraste, A., Gimelli, A., et al. (2020) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-020-05066-5 · Cited by 118 · see citing works

Radiomics: Data Are Also Images

Hatt, M., Rest, C. C. L., Tixier, F., Badic, B., Schick, U., & Visvikis, D. (2019) · Journal of Nuclear Medicine · doi:10.2967/jnumed.118.220582 · Cited by 117 · see citing works

Joint EANM/SNMMI/ANZSNM practice guidelines/procedure standards on recommended use of [18F]FDG PET/CT imaging during immunomodulatory treatments in patients with solid tumors version 1.0

Lopci, E., Hicks, R. J., Dimitrakopoulou‐Strauss, A., Dercle, L., Iravani, A., Seban, R., Sachpekidis, C., Humbert, O., Gheysens, O. S., Glaudemans, A. W. J. M., et al. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05780-2 · Cited by 116 · see citing works

Automated Segmentation of Baseline Metabolic Total Tumor Burden in Diffuse Large B-Cell Lymphoma: Which Method Is Most Successful? A Study on Behalf of the PETRA Consortium

Barrington, S. F., Zwezerijnen, G. J. C., de Vet, H. C. W., Heymans, M. W., Mikhaeel, N. G., Burggraaff, C. N., Eertink, J. J., Pike, L. C., Hoekstra, O. S., Zijlstra, J. M., et al. (2020) · Journal of Nuclear Medicine · doi:10.2967/jnumed.119.238923 · Cited by 112 · see citing works

Joint EANM-SNMMI guideline on the role of 2-[18F]FDG PET/CT in no special type breast cancer

Vaz, S. C., Woll, J. P. P., Cardoso, F., Groheux, D., Cook, G. J. R., Ulaner, G., Jacene, H., Rubio, I. T., Schoones, J., Peeters, M.-J. V., et al. (2024) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-024-06696-9 · Cited by 102 · see citing works

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

European Society of Radiology, deSouza, N. M., Achten, E., Alberich‐Bayarri, Á., Bamberg, F., Boellaard, R., Clémеnt, O., Fournier, L. S., Gallagher, F. A., Golay, X., et al. (2019) · Insights into Imaging · doi:10.1186/s13244-019-0764-0 · Cited by 108 · see citing works

Whole-Body Characterization of Estrogen Receptor Status in Metastatic Breast Cancer with 16α-18F-Fluoro-17β-Estradiol Positron Emission Tomography: Meta-Analysis and Recommendations for Integration into Clinical Applications

Kurland, B. F., Wiggins, J. R., Coche, A., Fontan, C., Bouvet, Y., Webner, P., Divgi, C. R., & Linden, H. M. (2020) · The Oncologist · doi:10.1634/theoncologist.2019-0967 · Cited by 102 · see citing works

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology

Duclos, V., Iep, A., Gomez, L., Goldfarb, L., & Besson, F. L. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22084159 · Cited by 95 · see citing works

Baseline 18F-FDG PET radiomic features as predictors of 2-year event-free survival in diffuse large B cell lymphomas treated with immunochemotherapy

Aide, N., Fruchart, C., Nganoa, C., Gac, A., & Lasnon, C. (2020) · European Radiology · doi:10.1007/s00330-020-06815-8 · Cited by 92 · see citing works

FDG-PET/CT for treatment response assessment in head and neck squamous cell carcinoma: a systematic review and meta-analysis of diagnostic performance

Helsen, N., WYNGAERT, T. V. D., Carp, L., & Stroobants, S. G. (2018) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-018-3978-3 · Cited by 90 · see citing works

Clinical insignificance of [18F]PSMA-1007 avid non-specific bone lesions: a retrospective evaluation

Arnfield, E. G., Thomas, P. A., Roberts, M. J., Pelecanos, A. M., Ramsay, S. C., Lin, C. Y., Latter, M. J., Garcia, P. L., & Pattison, D. A. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05456-3 · Cited by 87 · see citing works

Nuclear medicine and molecular imaging advances in the 21st century

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Integrating molecular nuclear imaging in clinical research to improve anticancer therapy

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Radiomics in PET/CT: Current Status and Future AI-Based Evolutions

Hatt, M., Rest, C. C. L., Antonorsi, N., Tixier, F., Tankyevych, O., Jaouen, V., Lucia, F., Bourbonne, V., Schick, U., Badic, B., et al. (2020) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2020.09.002 · Cited by 74 · 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

Imaging Inflammation in Atherosclerosis with CXCR4-Directed 68Ga-Pentixafor PET/CT: Correlation with 18F-FDG PET/CT

Kircher, M., Tran‐Gia, J., Kemmer, L., Zhang, X., Schirbel, A., Werner, R. A., Buck, A. K., Wester, H., Hacker, M., Lapa, C., et al. (2019) · Journal of Nuclear Medicine · doi:10.2967/jnumed.119.234484 · Cited by 72 · see citing works

Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor ligands: version 1.0

Albert, N. L., Preusser, M., Traub‐Weidinger, T., Tolboom, N., Law, I. G., Palmer, J. D., Guedj, É., Furtner, J., Fraioli, F., Huang, R. Y., et al. (2024) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-024-06783-x · Cited by 70 · see citing works

Response assessment using [68Ga]Ga‐PSMA ligand PET in patients undergoing systemic therapy for metastatic castration‐resistant prostate cancer

Grubmüller, B., Rasul, S., Baltzer, P., Fajković, H., D’Andrea, D., Berndl, F., Maj‐Hes, A., Grubmüller, K. H., Mitterhauser, M., Wadsak, W., et al. (2019) · The Prostate · doi:10.1002/pros.23919 · Cited by 69 · see citing works

EANM guideline on the role of 2-[18F]FDG PET/CT in diagnosis, staging, prognostic value, therapy assessment and restaging of ovarian cancer, endorsed by the American College of Nuclear Medicine (ACNM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI) and the International Atomic Energy Agency (IAEA)

Bolton, R. C. D., Aide, N., Colletti, P. M., Ferrero, A., Páez, D., Skanjeti, A., & Giammarile, F. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05450-9 · Cited by 69 · see citing works

Clinical Validity of 16α-[18F]Fluoro-17β-Estradiol Positron Emission Tomography/Computed Tomography to Assess Estrogen Receptor Status in Newly Diagnosed Metastatic Breast Cancer

van Geel, J., Boers, J., Elias, S. G., Glaudemans, A. W. J. M., de Vries, E. F. J., Hospers, G. A. P., van Kruchten, M., Kuip, E. J. M., Jager, A., van Oordt, C. W. M. D. H., et al. (2022) · Journal of Clinical Oncology · doi:10.1200/jco.22.00400 · Cited by 69 · see citing works

Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT

Weyts, K., Lasnon, C., Ciappuccini, R., Lequesne, J., Corroyer-Dulmont, A., Quak, E., Clarisse, B., Roussel, L., Bardet, S., & Jaudet, C. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05800-1 · Cited by 59 · see citing works

Radiomics Analysis for Clinical Decision Support in Nuclear Medicine

Ibrahim, A., Vallières, M., Woodruff, H. C., Primakov, S. P., Beheshti, M., Keek, S. A., Refaee, T., Sanduleanu, S., Walsh, S., Morin, O., et al. (2019) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2019.06.005 · Cited by 60 · see citing works

Lactate and Lactate Transporters as Key Players in the Maintenance of the Warburg Effect

Pereira‐Nunes, A., Afonso, J., Granja, S., & Baltazar, F. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-34025-4_3 · Cited by 61 · see citing works

18F-FDGPET/CT in fever of unknown origin and inflammation of unknown origin: a Chinese multi-center study

Wang, Q., Li, Y., Li, Y., Hua, F., Wang, Q.-S., Zhang, X.-L., Cheng, C., Wu, H., Yao, Z., Zhang, W., et al. (2018) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-018-4121-1 · Cited by 59 · see citing works

Twenty Years On: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group – ESOI Joint Paper

Fournier, L., de Geus-Oei, L. D., Regge, D., Oprea-Lager, D., D'Anastasi, M., Bidaut, L., Bäuerle, T., Lopci, E., Cappello, G., Lecouvet, F., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2021.800547 · Cited by 49 · see citing works

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

Vaz, S. C., Adam, J. A., Bolton, R. C. D., Véra, P., van Elmpt, W., Herrmann, K., Hicks, R. J., Lievens, Y. N., Santos, A., Schöder, H. M., et al. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05624-5 · Cited by 58 · see citing works

Applications of Artificial Intelligence in PSMA PET/CT for Prostate Cancer Imaging

Belal, S. L., Frantz, S., Minarik, D., Enqvist, O., Wikström, E., Edenbrandt, L., & Trägårdh, E. (2023) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2023.06.001 · Cited by 58 · 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

Language Analysis of Speakers with Dementia of the Alzheimer’s Type

Guinn, C. I., & Habash, A. (2012) · National Conference on Artificial Intelligence · 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

Abbreviated scan protocols to capture 18F-FDG kinetics for long axial FOV PET scanners

Viswanath, V., Sari, H., Pantel, A., Conti, M., Daube-Witherspoon, M., Mingels, C., Alberts, I., Eriksson, L., Shi, K., Rominger, A., et al. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05747-3 · Cited by 43 · see citing works

[18F]FDG PET/CT: EANM procedure guidelines for tumour imaging: version 3.0

Boellaard, R., Herrmann, K., Barrington, S. F., Cranston, I. C., Mottaghy, F. M., Hoekstra, C., Beyer, T., Pike, L., Willemsen, A., Graham, M. M., et al. (2025) · The EANM Journal · doi:10.1016/j.eanmj.2025.100006 · Cited by 43 · see citing works

Diagnostic and prognostic value of baseline FDG PET/CT skeletal textural features in diffuse large B cell lymphoma

Aide, N., Talbot, M., Fruchart, C., Damaj, G. L., & Lasnon, C. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3899-6 · Cited by 48 · see citing works

Evaluation of a Bayesian penalized likelihood reconstruction algorithm for low-count clinical 18F-FDG PET/CT

te Riet, J., Rijnsdorp, S., Roef, M. J., & Arends, A. J. (2019) · EJNMMI Physics · doi:10.1186/s40658-019-0262-y · Cited by 46 · see citing works

Reinventing Radiation Therapy with Machine Learning and Imaging Bio-markers (Radiomics): state-of-the-art, challenges and perspectives.

Dercle, L., Henry, T., Carré, A., Paragios, N., Deutsch, É., & Robert, C. (2020) · Methods · doi:10.1016/j.ymeth.2020.07.003 · Cited by 39 · see citing works

Assessing immune organs on 18F-FDG PET/CT imaging for therapy monitoring of immune checkpoint inhibitors: inter-observer variability, prognostic value and evolution during the treatment course of melanoma patients

Prigent, K., Lasnon, C., Ezine, E., Janson, M., Coudrais, N., Joly, E., Césaire, L., Stefan, A., Depontville, M., & Aide, N. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-020-05103-3 · Cited by 46 · see citing works

Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type

Guo, R., Hu, X., Song, H., Xu, P., Xu, H., Rominger, A., Lin, X., Menze, B. H., Li, B., & Shi, K. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05232-3 · Cited by 45 · see citing works

Proposal for a Quantitative 18F-FDG PET/CT Metabolic Parameter to Assess the Intensity of Bone Involvement in Multiple Myeloma

Takahashi, M. E. S., Mosci, C., de Souza, E. M., Brunetto, S. Q., Etchebehere, E., Santos, A. O., Camacho, M., MIRANDA, E. C. M., Lima, M., Amorim, B. J., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-52740-2 · Cited by 43 · see citing works

Accuracy of 18F-FDG PET/CT in Predicting Residual Disease After Neoadjuvant Chemoradiotherapy for Esophageal Cancer

Valkema, M. J., Noordman, B. J., Wijnhoven, B. P. L., Spaander, M. C. W., Biermann, K., Lagarde, S. M., Bennink, R. J., Schreurs, W. M. J., Roef, M. J., Hobbelink, M. G. G., et al. (2019) · Journal of Nuclear Medicine · doi:10.2967/jnumed.118.224196 · Cited by 42 · see citing works

Production of Ga-68 with a General Electric PETtrace cyclotron by liquid target

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Baseline PET radiomics outperform the IPI risk score for prediction of outcome in diffuse large B-cell lymphoma

Eertink, J. J., Zwezerijnen, G. J. C., Heymans, M. W., Pieplenbosch, S., Wiegers, S. E., Dührsen, U., Hüttmann, A., Kurch, L., Hanoun, C., Lugtenburg, P. J., et al. (2023) · Blood · doi:10.1182/blood.2022018558 · Cited by 39 · see citing works

Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan

Shekari, M., Verwer, E. E., Yaqub, M. M., Daamen, M., Buckley, C. J., Frisoni, G. B., Visser, P. J., Farrar, G., Barkhof, F., Gispert, J. D., et al. (2023) · EJNMMI Physics · doi:10.1186/s40658-023-00588-x · Cited by 39 · see citing works

Non-negative matrix factorisation improves Centiloid robustness in longitudinal studies

Bourgeat, P., Dóre, V., Doecke, J., Ames, D., Masters, C., Rowe, C., Fripp, J., & Villemagne, V. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117593 · Cited by 39 · see citing works

Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor

Zwezerijnen, G., Eertink, J. J., Ferrández, M. C., Wiegers, S., Burggraaff, C., Lugtenburg, P., Heymans, M., de Vet, H. D., Zijlstra, J., & Boellaard, R. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-022-05977-5 · Cited by 35 · see citing works

Impact of [18F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role

Safarian, A., Mirshahvalad, S. A., Nasrollahi, H., Jung, T., Pirich, C., Arabi, H., & Beheshti, M. (2025) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2025.02.006 · Cited by 38 · see citing works

Standardization of Small Animal Imaging—Current Status and Future Prospects

Mannheim, J. G., Kara, F., Doorduin, J., Fuchs, K., Reischl, G., Liang, S., Verhoye, M., Gremse, F., Mezzanotte, L., & Huisman, M. C. (2017) · Molecular Imaging and Biology · doi:10.1007/s11307-017-1126-2 · Cited by 40 · see citing works

All that glitters is not gold - new reconstruction methods using Deauville criteria for patient reporting

Barrington, S. F., Sulkin, T., Forbes, A., & Johnson, P. (2017) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-017-3893-z · Cited by 38 · see citing works

PET/CT variants and pitfalls in malignant melanoma

Aide, N., Iravani, A., Prigent, K., Kottler, D., Alipour, R., & Hicks, R. J. (2022) · Cancer Imaging · doi:10.1186/s40644-021-00440-4 · Cited by 38 · see citing works

β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3

Bourgeat, P., Doré, V., Burnham, S. C., Benzinger, T. L. S., Tosun, D., Li, S., Goyal, M. S., LaMontagne, P., Jin, L., Rowe, C. C., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119527 · Cited by 37 · see citing works

Impact of PET reconstruction protocols on quantification of lesions that fulfil the PERCIST lesion inclusion criteria

Devriese, J., Beels, L., Maes, A., de Wiele, C. V., & Pottel, H. (2018) · EJNMMI Physics · doi:10.1186/s40658-018-0235-6 · Cited by 37 · see citing works

Test–Retest Reproducibility of 18F-FDG PET/CT Uptake in Cancer Patients Within a Qualified and Calibrated Local Network

Kurland, B. F., Peterson, L. M., Shields, A. T., Lee, J. H., Byrd, D. W., Novakova-Jiresova, A., Muzi, M., Specht, J. M., Mankoff, D. A., Linden, H. M., et al. (2018) · Journal of Nuclear Medicine · doi:10.2967/jnumed.118.209544 · Cited by 36 · see citing works

18F-FDG-PET/CT-based treatment planning for definitive (chemo)radiotherapy in patients with head and neck squamous cell carcinoma improves regional control and survival

van den Bosch, S., Doornaert, P., Dijkema, T., Zwijnenburg, E. M., Verhoef, L. C. G., Hoeben, B. A. W., Kasperts, N., Smid, E. J., Terhaard, C. H. J., & Kaanders, J. H. A. M. (2019) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2019.07.025 · Cited by 36 · see citing works

[18F]FDG and [18F]FES PET/CT Imaging as a Biomarker for Therapy Effect in Patients with Metastatic ER+ Breast Cancer Undergoing Treatment with Rintodestrant

Iqbal, R., Yaqub, M. M., Bektas, H. O., Oprea‐Lager, D. E., de Vries, E. G. E., Glaudemans, A. W. J. M., Aftimos, P. G., Gebhart, G., Beelen, A. P., Schuit, R. C., et al. (2023) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-22-2720 · Cited by 36 · see citing works

Emerging role of 18F-FDG PET/CT in Castleman disease: a review

Koa, B., Borja, A. J., Aly, M., Padmanabhan, S., Tran, J., Zhang, V., Rojulpote, C., Pierson, S. K., Tamakloe, M.-A., Khor, J. S., et al. (2021) · Insights into Imaging · doi:10.1186/s13244-021-00963-1 · Cited by 35 · see citing works

Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience

Monaco, L., Gemelli, M., Gotuzzo, I., Bauckneht, M., Crivellaro, C., Genova, C., Cortinovis, D. L., Zullo, L., Ammoni, L. C., Bernasconi, D. P., et al. (2021) · Cancers · doi:10.3390/cancers13071634 · Cited by 35 · see citing works

The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer.

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EANM guidelines for PET-CT and PET-MR routine quality control

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A Systematic Review Into the Radiologic Features Predicting Local Recurrence After Stereotactic Ablative Body Radiotherapy (SABR) in Patients With Non-Small Cell Lung Cancer (NSCLC)

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Visual and volumetric parameters by 18F-FDG-PET/CT: a head to head comparison for the prediction of outcome in patients with multiple myeloma

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A Comparison of Two Hyperpolarized 129Xe MRI Ventilation Quantification Pipelines: The Effect of Signal to Noise Ratio

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The use of a proposed updated EARL harmonization of 18F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations

Ly, J., Minarik, D., Edenbrandt, L., Wollmer, P., & Trägårdh, E. (2019) · EJNMMI Research · doi:10.1186/s13550-019-0536-3 · Cited by 31 · see citing works

Quantitation of myocardial 99mTc-HMDP uptake with new SPECT/CT cadmium zinc telluride (CZT) camera in patients with transthyretin-related cardiac amyloidosis: Ready for clinical use?

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Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET

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A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation

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Feasibility of PET/CT system performance harmonisation for quantitative multicentre 89Zr studies

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Why harmonization is needed when using FDG PET/CT as a prognosticator: demonstration with EARL-compliant SUV as an independent prognostic factor in lung cancer

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Role of Fludeoxyglucose in Breast Cancer

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Does PET Reconstruction Method Affect Deauville Score in Lymphoma Patients?

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PET radiomics in lung cancer: advances and translational challenges

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Towards guidelines to harmonize textural features in PET: Haralick textural features vary with image noise, but exposure-invariant domains enable comparable PET radiomics

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Imaging of Invasive Fungal Infections- The Role of PET/CT

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Head-to-Head Comparison of 18F-PSMA-1007 Positron Emission Tomography/Computed Tomography and Multiparametric Magnetic Resonance Imaging with Whole-mount Histopathology as Reference in Localisation and Staging of Primary Prostate Cancer

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ESMO/ASCO Recommendations for a Global Curriculum in Medical Oncology Edition 2023

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Critical review of partial volume correction methods in PET and SPECT imaging: benefits, pitfalls, challenges, and future outlook

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ENETS consensus guidelines for synoptic reporting of molecular imaging studies

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Increased 18F-FDG signal recovery from small physiological structures in digital PET/CT and application to the pituitary gland

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EARL compliance measurements on the biograph vision Quadra PET/CT system with a long axial field of view

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18F-Fludeoxyglucose PET/Computed Tomography for Assessing Tumor Response to Immunotherapy and Detecting Immune-Related Side Effects

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Revisiting detection of in-transit metastases in melanoma patients using digital 18F-FDG PET/CT with small-voxel reconstruction

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Circulating Tumor DNA in Head and Neck Squamous Cell Carcinoma: Association with Metabolic Tumor Burden Determined with FDG-PET/CT

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Impact of solitary pulmonary nodule size on qualitative and quantitative assessment using 18F-fluorodeoxyglucose PET/CT: the SPUTNIK trial

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Usefulness of semi-automatic harmonization strategy of standardized uptake values for multicenter PET studies

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Multicenter study of quantitative PET system harmonization using NIST-traceable 68Ge/68Ga cross-calibration kit

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Tumor response evaluation in patients with malignant melanoma undergoing immune checkpoint inhibitor therapy and prognosis prediction using 18F-FDG PET/CT: multicenter study for comparison of EORTC, PERCIST, and imPERCIST

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Standardisation and harmonisation of quantitative oncology PET/CT studies

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Standardization and harmonization of quantitative PET/CT and SPECT/CT imaging: towards a universal quantitative language for precision nuclear medicine

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WE-AB-204-05: Harmonizing PET/CT Quantification in Multicenter Studies: A Case Study

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Evaluation of strategies towards harmonization of FDG PET/CT studies in multicentre trials: comparison of scanner validation phantoms and data analysis procedures

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Harmonization based on quantitative analysis of standardized uptake value variations across PET/CT scanners: a multicenter phantom study

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