{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:43:38Z","timestamp":1789994618406,"version":"4.0.1"},"reference-count":45,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":["physicamedica.com","clinicalkey.jp","clinicalkey.com","clinicalkey.es","clinicalkey.fr","clinicalkey.com.au","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Physica Medica"],"published-print":{"date-parts":[[2019,3]]},"DOI":"10.1016\/j.ejmp.2019.03.005","type":"journal-article","created":{"date-parts":[[2019,3,16]],"date-time":"2019-03-16T06:52:17Z","timestamp":1552719137000},"page":"117-126","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":21,"special_numbering":"C","title":["Impact of acquisition count statistics reduction and SUV discretization on PET radiomic features in pediatric 18F-FDG-PET\/MRI examinations"],"prefix":"10.1016","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0794-2888","authenticated-orcid":false,"given":"Marco","family":"Branchini","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandra","family":"Zorz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pietro","family":"Zucchetta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Bettinelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"De Monte","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diego","family":"Cecchin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8647-911X","authenticated-orcid":false,"given":"Marta","family":"Paiusco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0005","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.radonc.2011.06.030","article-title":"Diagnostic and staging impact of radiotherapy planning FDG-PET-CT in non-small-cell lung cancer","volume":"101","author":"Lin","year":"2011","journal-title":"Radiother Oncol"},{"issue":"1","key":"10.1016\/j.ejmp.2019.03.005_b0010","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1148\/radiol.14131732","article-title":"Simultaneous whole-body PET\/MR imaging in comparison to PET\/CT in pediatric oncology: initial results","volume":"273","author":"Sch\u00e4fer","year":"2014","journal-title":"Radiology"},{"issue":"8","key":"10.1016\/j.ejmp.2019.03.005_b0015","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1001\/jamapediatrics.2013.311","article-title":"The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk","volume":"167","author":"Miglioretti","year":"2013","journal-title":"JAMA Pediatr"},{"key":"10.1016\/j.ejmp.2019.03.005_b0020","series-title":"Health risks from exposures to low levels of ionizing radiation","author":"BEIR VII PHASE II","year":"2006"},{"key":"10.1016\/j.ejmp.2019.03.005_b0025","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.ejmp.2017.05.071","article-title":"Beyond imaging: the promise of radiomics","volume":"38","author":"Avanzo","year":"2017","journal-title":"Phys Med"},{"issue":"6","key":"10.1016\/j.ejmp.2019.03.005_b0030","doi-asserted-by":"crossref","first-page":"1162","DOI":"10.1016\/j.patcog.2008.08.011","article-title":"Exploring feature-based approaches in PET images for predicting cancer treatment outcomes","volume":"42","author":"El Naqa","year":"2009","journal-title":"Pattern Recognit"},{"issue":"6","key":"10.1016\/j.ejmp.2019.03.005_b0035","doi-asserted-by":"crossref","first-page":"891","DOI":"10.2967\/jnumed.113.127340","article-title":"Textural parameters of tumor heterogeneity in 18F-FDG PET\/CT for therapy response assessment and prognosis in patients with locally advanced rectal cancer","volume":"55","author":"Bundschuh","year":"2014","journal-title":"J Nucl Med"},{"issue":"10","key":"10.1016\/j.ejmp.2019.03.005_b0040","doi-asserted-by":"crossref","first-page":"1703","DOI":"10.2967\/jnumed.112.119289","article-title":"Textural features of pretreatment 18F-FDG PET\/CT images: prognostic significance in patients with advanced T-stage oropharyngeal squamous cell carcinoma","volume":"54","author":"Cheng","year":"2013","journal-title":"J Nucl Med"},{"issue":"4","key":"10.1016\/j.ejmp.2019.03.005_b0045","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0094017","article-title":"Relationship between tumor heterogeneity measured on FDG-PET\/CT and pathological prognostic factors in invasive breast cancer","volume":"9","author":"Soussan","year":"2014","journal-title":"PLoS One"},{"issue":"6","key":"10.1016\/j.ejmp.2019.03.005_b0050","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1053\/j.semnuclmed.2018.07.003","article-title":"Novel quantitative PET techniques for clinical decision support in oncology","volume":"48","author":"Zaidi","year":"2018","journal-title":"Semin Nucl Med"},{"issue":"4","key":"10.1016\/j.ejmp.2019.03.005_b0055","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1016\/j.ijrobp.2018.05.053","article-title":"Repeatability and reproducibility of radiomic features: a systematic review","volume":"102","author":"Traverso","year":"2018","journal-title":"Int J Radiat Oncol Biol Phys"},{"issue":"5","key":"10.1016\/j.ejmp.2019.03.005_b0060","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1007\/s11307-016-0940-2","article-title":"Repeatability of radiomic features in non-small-cell lung cancer [(18)F]FDG-PET\/CT studies: impact of reconstruction and delineation","volume":"18","author":"van Velden","year":"2016","journal-title":"Mol Imaging Biol"},{"issue":"11","key":"10.1016\/j.ejmp.2019.03.005_b0065","doi-asserted-by":"crossref","first-page":"1667","DOI":"10.2967\/jnumed.115.156927","article-title":"Impact of image reconstruction settings on texture features in 18F-FDG PET","volume":"56","author":"Yan","year":"2015","journal-title":"J Nucl Med"},{"key":"10.1016\/j.ejmp.2019.03.005_b0070","doi-asserted-by":"crossref","first-page":"11075","DOI":"10.1038\/srep11075","article-title":"The effect of SUV discretization in quantitative FDG-PET radiomics: the need for standardized methodology in tumor texture analysis","volume":"5","author":"Leijenaar","year":"2015","journal-title":"Sci Rep"},{"key":"10.1016\/j.ejmp.2019.03.005_b0075","doi-asserted-by":"crossref","first-page":"406","DOI":"10.2967\/jnumed.116.180919","article-title":"Reliability of PET\/CT shape and heterogeneity features in functional and morphologic components of non-small cell lung cancer tumors: a repeatability analysis in a prospective multicenter cohort","volume":"58","author":"Desseroit","year":"2017","journal-title":"J Nucl Med"},{"issue":"11","key":"10.1016\/j.ejmp.2019.03.005_b0080","doi-asserted-by":"crossref","first-page":"1642","DOI":"10.2967\/jnumed.115.163469","article-title":"Tumor texture analysis in PET: where do we stand?","volume":"56","author":"Buvat","year":"2015","journal-title":"J Nucl Med"},{"key":"10.1016\/j.ejmp.2019.03.005_b0085","unstructured":"Zwanenburg A, Leger S, Valli\u00e8res M, L\u00f6ck S. Image biomarker standardisation initiative. arXiv preprint arXiv:1612.07003, 2016."},{"key":"10.1016\/j.ejmp.2019.03.005_b0090","doi-asserted-by":"crossref","first-page":"43356","DOI":"10.1038\/srep43356","article-title":"Associations between tumor vascularity, vascular endothelial growth factor expression and PET\/MRI radiomic signatures in primary clear-cell-renal-cell-carcinoma: proof-of-concept study","volume":"7","author":"Yin","year":"2017","journal-title":"Sci Rep"},{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0095","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.tranon.2016.01.008","article-title":"Radiomics analysis on FLT-PET\/MRI for characterization of early treatment response in renal cell carcinoma: a proof-of-concept study","volume":"9","author":"Antunes","year":"2016","journal-title":"Transl Oncol"},{"issue":"13","key":"10.1016\/j.ejmp.2019.03.005_b0100","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.1007\/s00259-016-3503-5","article-title":"Defining optimal tracer activities in pediatric oncologic whole-body 18F-FDG-PET\/MRI","volume":"43","author":"Gatidis","year":"2016","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"1095","key":"10.1016\/j.ejmp.2019.03.005_b0105","doi-asserted-by":"crossref","first-page":"20180438","DOI":"10.1259\/bjr.20180438","article-title":"Quantitative analysis of image metrics for reduced and standard dose pediatric (18)F-FDG PET\/MRI examinations","volume":"92","author":"Zucchetta","year":"2019","journal-title":"Br J Radiol"},{"issue":"29","key":"10.1016\/j.ejmp.2019.03.005_b0110","doi-asserted-by":"crossref","first-page":"20734","DOI":"10.18632\/oncotarget.25070","article-title":"Selected PET radiomic features remain the same","volume":"9","author":"Tsujikawa","year":"2018","journal-title":"Oncotarget"},{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0115","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1007\/s00259-014-2961-x","article-title":"Association of nuclear medicine (EANM).FDG PET\/CT: EANM procedure guidelines for tumour imaging: version 2.0, Vols","volume":"42","author":"Boellaard","year":"2015","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"7","key":"10.1016\/j.ejmp.2019.03.005_b0120","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.2967\/jnumed.110.086579","article-title":"Evaluation of optimal acquisition duration or injected activity for pediatric 18F-FDG PET\/CT","volume":"52","author":"Alessio","year":"2011","journal-title":"J Nucl Med"},{"issue":"3","key":"10.1016\/j.ejmp.2019.03.005_b0125","doi-asserted-by":"crossref","first-page":"414","DOI":"10.2967\/jnumed.113.129858","article-title":"Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis","volume":"55","author":"Orlhac","year":"2014","journal-title":"J Nucl Med"},{"issue":"1","key":"10.1016\/j.ejmp.2019.03.005_b0130","doi-asserted-by":"crossref","first-page":"38","DOI":"10.2967\/jnumed.114.144055","article-title":"18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort","volume":"56","author":"Hatt","year":"2015","journal-title":"J Nucl Med"},{"issue":"3","key":"10.1016\/j.ejmp.2019.03.005_b0135","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1118\/1.4908210","article-title":"IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics","volume":"42","author":"Zhang","year":"2015","journal-title":"Med Phys"},{"issue":"9","key":"10.1016\/j.ejmp.2019.03.005_b0140","doi-asserted-by":"crossref","first-page":"2805","DOI":"10.1007\/s00330-015-3681-8","article-title":"The precision of textural analysis in (18)F-FDG-PET scans of oesophageal cancer","volume":"25","author":"Doumou","year":"2015","journal-title":"Eur Radiol"},{"key":"10.1016\/j.ejmp.2019.03.005_b0145","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.ejmp.2018.05.024","article-title":"PET textural features stability and pattern discrimination power for radiomics analysis: an \u201cad-hoc\u201d phantoms study","volume":"50","author":"Presotto","year":"2018","journal-title":"Phys Med"},{"issue":"5","key":"10.1016\/j.ejmp.2019.03.005_b0150","doi-asserted-by":"crossref","first-page":"693","DOI":"10.2967\/jnumed.111.099127","article-title":"Reproducibility of tumor uptake heterogeneity characterization through textural feature analysis in 18F-FDG PET","volume":"53","author":"Tixier","year":"2012","journal-title":"J Nucl Med"},{"issue":"12","key":"10.1016\/j.ejmp.2019.03.005_b0155","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0145063","article-title":"18F-FDG PET-derived textural indices reflect tissue-specific uptake pattern in non-small cell lung cancer","volume":"10","author":"Orlhac","year":"2015","journal-title":"PLoS One"},{"issue":"6","key":"10.1016\/j.ejmp.2019.03.005_b0160","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1007\/s11307-016-0973-6","article-title":"Robustness of radiomic features in [(11)C]choline and [(18)F]FDG PET\/CT imaging of nasopharyngeal carcinoma: impact of segmentation and discretization. Vols","volume":"18","author":"Lu","year":"2016","journal-title":"Mol Imaging Biol"},{"issue":"7","key":"10.1016\/j.ejmp.2019.03.005_b0165","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.3109\/0284186X.2013.812798","article-title":"Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability","volume":"52","author":"Leijenaar","year":"2013","journal-title":"Acta Oncol"},{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0170","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0057105","article-title":"Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images","volume":"8","author":"Bagci","year":"2013","journal-title":"PLoS One"},{"key":"10.1016\/j.ejmp.2019.03.005_b0175","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1007\/s12149-018-1260-1","article-title":"(18)F-FDG PET\/CT metabolic tumor parameters and radiomics features in aggressive non-Hodgkin's lymphoma as predictors of treatment outcome and survival","volume":"32","author":"Parvez","year":"2018","journal-title":"Ann Nucl Med"},{"issue":"12","key":"10.1016\/j.ejmp.2019.03.005_b0180","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1097\/RLU.0000000000001375","article-title":"Intratumoral heterogeneity of pretreatment 18F-FDG PET images predict disease progression in patients with nasal type extranodal natural killer\/T-cell lymphoma","volume":"41","author":"Ko","year":"2016","journal-title":"Clin Nucl Med"},{"issue":"9","key":"10.1016\/j.ejmp.2019.03.005_b0185","doi-asserted-by":"crossref","first-page":"4608","DOI":"10.1002\/mp.12349","article-title":"Association between textural and morphological tumor indices on baseline PET-CT and early metabolic response on interim PET-CT in bulky malignant lymphomas","volume":"44","author":"Ben Bouall\u00e8gue","year":"2017","journal-title":"Med Phys"},{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0190","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1002\/mp.12041","article-title":"Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data","volume":"44","author":"Beichel","year":"2017","journal-title":"Med Phys"},{"key":"10.1016\/j.ejmp.2019.03.005_b0195","article-title":"Optimized feature extraction for radiomics analysis of (18)F-FDG-PET imaging","author":"Papp","year":"2018","journal-title":"J Nucl Med"},{"issue":"11","key":"10.1016\/j.ejmp.2019.03.005_b0200","doi-asserted-by":"crossref","first-page":"4498","DOI":"10.1007\/s00330-017-4859-z","article-title":"The impact of image reconstruction settings on 18F-FDG PET radiomic features: multi-scanner phantom and patient studies","volume":"27","author":"Shiri","year":"2017","journal-title":"Eur Radiol"},{"key":"10.1016\/j.ejmp.2019.03.005_b0205","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.ejmp.2018.05.013","article-title":"Quantifying the robustness of [(18)F]FDG-PET\/CT radiomic features with respect to tumor delineation in head and neck and pancreatic cancer patients","volume":"49","author":"Belli","year":"2018","journal-title":"Phys Med"},{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0210","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.radonc.2018.06.028","article-title":"Comparison of SUVmax and SUVpeak based segmentation to determine primary lung tumour volume on FDG PET-CT correlated with pathology data","volume":"129","author":"Mercieca","year":"2018","journal-title":"Radiother Oncol"},{"issue":"2","key":"10.1016\/j.ejmp.2019.03.005_b0215","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1148\/radiol.14132807","article-title":"Repeatability of metabolically active tumor volume measurements with FDG PET\/CT in advanced gastrointestinal malignancies: a multicenter study","volume":"273","author":"Frings","year":"2014","journal-title":"Radiology"},{"issue":"1","key":"10.1016\/j.ejmp.2019.03.005_b0220","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s00259-016-3427-0","article-title":"Characterization of PET\/CT images using texture analysis: the past, the present\u2026 any future?","volume":"44","author":"Hatt","year":"2017","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"1","key":"10.1016\/j.ejmp.2019.03.005_b0225","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1038\/s41598-017-00665-z","article-title":"Delta-radiomics features for the prediction of patient outcomes in non\u2013small cell lung cancer","volume":"7","author":"Fave","year":"2017","journal-title":"Sci Rep"}],"container-title":["Physica Medica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1120179719300481?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1120179719300481?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T21:35:03Z","timestamp":1573680903000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1120179719300481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3]]},"references-count":45,"alternative-id":["S1120179719300481"],"URL":"https:\/\/doi.org\/10.1016\/j.ejmp.2019.03.005","relation":{},"ISSN":["1120-1797"],"issn-type":[{"value":"1120-1797","type":"print"}],"subject":[],"published":{"date-parts":[[2019,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Impact of acquisition count statistics reduction and SUV discretization on PET radiomic features in pediatric 18F-FDG-PET\/MRI examinations","name":"articletitle","label":"Article Title"},{"value":"Physica Medica","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejmp.2019.03.005","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}]}}