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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-05-30

AUTHORS

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

ABSTRACT

BackgroundThis 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 methodsBaseline (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).ResultsUsing 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.ConclusionPERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either. More... »

PAGES

17

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    http://scigraph.springernature.com/pub.10.1186/s40658-017-0185-4

    DOI

    http://dx.doi.org/10.1186/s40658-017-0185-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1085715498

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28560574


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        "description": "BackgroundThis 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 methodsBaseline (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 \u00b1 TOF data (PSF \u00b1 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).ResultsUsing OSEMPET1/OSEMPET2 (standard scenario), responders displayed a reduction of \u221257.5%\u2009\u00b1\u200923.4 and \u221263.9%\u2009\u00b1\u200922.4 for SULmax and SULpeak, respectively, while progressing tumours had an increase of +63.4%\u2009\u00b1\u200926.5 and +60.7%\u2009\u00b1\u200919.6 for SULmax and SULpeak respectively. The use of PSF\u2009\u00b1\u2009TOF reconstruction impacted the classification of tumour response. For example, taking the OSEMPET1/PSF\u2009\u00b1\u2009TOFPET2 scenario reduced the apparent reduction in SUL in responding tumours (\u221239.7%\u2009\u00b1\u200931.3 and \u221255.5%\u2009\u00b1\u200926.3 for SULmax and SULpeak, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0%\u2009\u00b1\u200950.7 and +91.1%\u2009\u00b1\u200939.6 for SULmax and SULpeak, respectively).Consequently, variation in reconstruction methodology (PSF\u2009\u00b1\u2009TOFPET1/OSEMPET2 or OSEM PET1/PSF\u2009\u00b1\u2009TOFPET2) 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.ConclusionPERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.", 
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    22 schema:description BackgroundThis 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 methodsBaseline (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).ResultsUsing 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.ConclusionPERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.
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