EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program
Abstract Background This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SU...
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doaj-12fc27d0d4484e0daee5e736050967c52020-11-24T21:45:10ZengSpringerOpenEJNMMI Physics2197-73642017-05-014111310.1186/s40658-017-0185-4EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization programCharline Lasnon0Elske Quak1Pierre-Yves Le Roux2Philippe Robin3Michael S. Hofman4David Bourhis5Jason Callahan6David S. Binns7Cédric Desmonts8Pierre-Yves Salaun9Rodney J. Hicks10Nicolas Aide11Nuclear Medicine Department, François Baclesse Cancer CentreNuclear Medicine Department, François Baclesse Cancer CentreNuclear Medicine Department and EA 3878 IFR 148, University HospitalNuclear Medicine Department and EA 3878 IFR 148, University HospitalCancer Imaging, Peter Mac Callum Cancer InstituteNuclear Medicine Department and EA 3878 IFR 148, University HospitalCancer Imaging, Peter Mac Callum Cancer InstituteCancer Imaging, Peter Mac Callum Cancer InstituteNuclear Medicine Department, University HospitalNuclear Medicine Department and EA 3878 IFR 148, University HospitalCancer Imaging, Peter Mac Callum Cancer InstituteINSERM U1086 ANTICIPE, BioTICLA, Caen UniversityAbstract Background This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification. Materials and methods Baseline (PET1) and response assessment (PET2) scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL). Results Using OSEMPET1/OSEMPET2 (standard scenario), responders displayed a reduction of −57.5% ± 23.4 and −63.9% ± 22.4 for SULmax and SULpeak, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SULmax and SULpeak respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEMPET1/PSF ± TOFPET2 scenario reduced the apparent reduction in SUL in responding tumours (−39.7% ± 31.3 and −55.5% ± 26.3 for SULmax and SULpeak, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SULmax and SULpeak, respectively). Consequently, variation in reconstruction methodology (PSF ± TOFPET1/OSEMPET2 or OSEM PET1/PSF ± TOFPET2) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively. Conclusion PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.http://link.springer.com/article/10.1186/s40658-017-0185-4PET18F-FDGTherapy responsePERCISTEORTCHarmonization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Charline Lasnon Elske Quak Pierre-Yves Le Roux Philippe Robin Michael S. Hofman David Bourhis Jason Callahan David S. Binns Cédric Desmonts Pierre-Yves Salaun Rodney J. Hicks Nicolas Aide |
spellingShingle |
Charline Lasnon Elske Quak Pierre-Yves Le Roux Philippe Robin Michael S. Hofman David Bourhis Jason Callahan David S. Binns Cédric Desmonts Pierre-Yves Salaun Rodney J. Hicks Nicolas Aide EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program EJNMMI Physics PET 18F-FDG Therapy response PERCIST EORTC Harmonization |
author_facet |
Charline Lasnon Elske Quak Pierre-Yves Le Roux Philippe Robin Michael S. Hofman David Bourhis Jason Callahan David S. Binns Cédric Desmonts Pierre-Yves Salaun Rodney J. Hicks Nicolas Aide |
author_sort |
Charline Lasnon |
title |
EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program |
title_short |
EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program |
title_full |
EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program |
title_fullStr |
EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program |
title_full_unstemmed |
EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program |
title_sort |
eortc pet response criteria are more influenced by reconstruction inconsistencies than percist but both benefit from the earl harmonization program |
publisher |
SpringerOpen |
series |
EJNMMI Physics |
issn |
2197-7364 |
publishDate |
2017-05-01 |
description |
Abstract Background This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification. Materials and methods Baseline (PET1) and response assessment (PET2) scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL). Results Using OSEMPET1/OSEMPET2 (standard scenario), responders displayed a reduction of −57.5% ± 23.4 and −63.9% ± 22.4 for SULmax and SULpeak, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SULmax and SULpeak respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEMPET1/PSF ± TOFPET2 scenario reduced the apparent reduction in SUL in responding tumours (−39.7% ± 31.3 and −55.5% ± 26.3 for SULmax and SULpeak, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SULmax and SULpeak, respectively). Consequently, variation in reconstruction methodology (PSF ± TOFPET1/OSEMPET2 or OSEM PET1/PSF ± TOFPET2) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively. Conclusion PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either. |
topic |
PET 18F-FDG Therapy response PERCIST EORTC Harmonization |
url |
http://link.springer.com/article/10.1186/s40658-017-0185-4 |
work_keys_str_mv |
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