{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T12:11:41Z","timestamp":1788783101965,"version":"build-2803163510"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","physicamedica.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Physica Medica"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.ejmp.2026.105917","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T12:20:55Z","timestamp":1786018855000},"page":"105917","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A simple parameter to guide plan optimization for robotic pancreas SBRT"],"prefix":"10.1016","volume":"149","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9154-8482","authenticated-orcid":false,"given":"M.","family":"Zani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9820-6047","authenticated-orcid":false,"given":"T.","family":"Zoppi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R.","family":"Doro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Loi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L.","family":"Livi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Pallotta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6107-7915","authenticated-orcid":false,"given":"L.","family":"Masi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ejmp.2026.105917_b0005","doi-asserted-by":"crossref","first-page":"9420","DOI":"10.3748\/wjg.v21.i31.9420","article-title":"Robotic radiosurgery in pancreatic cancer: a systematic review","volume":"21","author":"Buwenge","year":"2015","journal-title":"World J Gastroenterol"},{"key":"10.1016\/j.ejmp.2026.105917_b0010","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.ijrobp.2016.10.030","article-title":"Stereotactic Body Radiation Therapy for locally Advanced Pancreatic Cancer: a Systematic Review and Pooled Analysis of 19 Trials","volume":"97","author":"Petrelli","year":"2017","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0015","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1016\/j.ijrobp.2011.02.048","article-title":"Incidence of changes in respiration-induced tumor motion and its relationship with respiratory surrogates during individual treatment fractions","volume":"82","author":"Malinowski","year":"2012","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0020","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.radonc.2014.03.002","article-title":"MRI-based tumor motion characterization and gating schemes for radiation therapy of pancreatic cancer","volume":"111","author":"Heerkens","year":"2014","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0025","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.radonc.2019.01.020","article-title":"Pancreatic cancer treated with SBRT: effect of anatomical interfraction variations on dose to organs at risk","volume":"134","author":"Loi","year":"2019","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0030","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.radonc.2019.09.016","article-title":"A model-based patient selection tool to identify who may be at risk of exceeding dose tolerances during pancreatic SBRT","volume":"141","author":"Magallon-Baro","year":"2019","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0035","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.radonc.2018.11.019","article-title":"Identification of patients with locally advanced pancreatic cancer benefitting from plan adaptation in MR-guided radiation therapy","volume":"132","author":"Bohoudi","year":"2019","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2026.111525","article-title":"Intra-fraction errors and inter-fraction deformation during pancreas SBRT: Analysis and predictability of dose variations for upper gastrointestinal organs","volume":"219","author":"Loi","year":"2026","journal-title":"Radiother Oncol"},{"issue":"2010","key":"10.1016\/j.ejmp.2026.105917_b0045","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1177\/153303461000900502","article-title":"The CyberKnife\u00ae robotic radiosurgery system in 2010","volume":"9","author":"Kilby","year":"2010","journal-title":"Technol Cancer Res Treat"},{"key":"10.1016\/j.ejmp.2026.105917_b0050","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.ejmp.2018.11.012","article-title":"CyberKnife MLC-based treatment planning for abdominal and pelvic SBRT: Analysis of multiple dosimetric parameters, overall scoring index and clinical scoring","volume":"56","author":"Masi","year":"2018","journal-title":"Phys Med"},{"key":"10.1016\/j.ejmp.2026.105917_b0055","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.phro.2022.07.005","article-title":"Technical feasibility of online adaptive stereotactic treatments in the abdomen on a robotic radiosurgery system","volume":"23","author":"Milder","year":"2022","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0060","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.ijrobp.2021.03.050","article-title":"Comparison of Daily Online Plan Adaptation strategies for a Cohort of Pancreatic Cancer patients Treated with SBRT: Plan adaptation strategies for pancreatic SBRT","volume":"111","author":"Magallon-Baro","year":"2021","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0065","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.ejmp.2020.02.009","article-title":"Performance assessment of a new optimization system for robotic SBRT MLC-based plans","volume":"71","author":"Calusi","year":"2020","journal-title":"Phys Med"},{"key":"10.1016\/j.ejmp.2026.105917_b0070","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1177\/1533033819851520","article-title":"Technical Assessment of an Automated Treatment Planning on Dose Escalation of Pancreas Stereotactic Body Radiotherapy","volume":"18","author":"Wang","year":"2019","journal-title":"Technol Cancer Res Treat"},{"key":"10.1016\/j.ejmp.2026.105917_b0075","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1002\/acm2.13025","article-title":"Automated treatment planning as a dose escalation strategy for stereotactic radiation therapy in pancreatic cancer","volume":"21","author":"Cilla","year":"2020","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0080","article-title":"An Interpretable Planning Bot for Pancreas Stereotactic Body Radiation Therapy","author":"Zhang","year":"2021","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0085","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1002\/acm2.13173","article-title":"Knowledge-based planning in robotic intracranial stereotactic radiosurgery treatments","volume":"22","author":"Yu","year":"2021","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejmp.2023.102606","article-title":"Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol","volume":"110","author":"Monticelli","year":"2023","journal-title":"Phys Med"},{"key":"10.1016\/j.ejmp.2026.105917_b0095","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1080\/0284186X.2018.1479068","article-title":"First fully automated planning solution for robotic radiosurgery\u2013comparison with automatically planned volumetric arc therapy for prostate cancer","volume":"57","author":"Rossi","year":"2018","journal-title":"Acta Oncol (Madr)"},{"key":"10.1016\/j.ejmp.2026.105917_b0100","doi-asserted-by":"crossref","first-page":"4139","DOI":"10.1002\/mp.14993","article-title":"Fully automated treatment planning for MLC-based robotic radiotherapy","volume":"48","author":"Schipaanboord","year":"2021","journal-title":"Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0105","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1120\/jacmp.v14i5.4333","article-title":"Improving plan quality and consistency by standardization of dose constraints in prostate cancer patients treated with cyberknife","volume":"14","author":"Descovich","year":"2013","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0110","doi-asserted-by":"crossref","first-page":"4036","DOI":"10.1118\/1.3596527","article-title":"Correlation and prediction uncertainties in the CyberKnife Synchrony respiratory tracking system","volume":"38","author":"Pepin","year":"2011","journal-title":"Med Phys"},{"issue":"2022","key":"10.1016\/j.ejmp.2026.105917_b0115","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.clon.2022.02.010","article-title":"Consensus on Normal Tissue Dose-volume Constraints for Oligometastatic, Primary Lung and Hepatocellular Carcinoma Stereotactic Ablative Radiotherapy","volume":"34","author":"Diez","year":"2022","journal-title":"Clin Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0120","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1177\/030089161109700415","article-title":"Geometry of volumes in radiotherapy planning. A new method for a quantitative assessment","volume":"97","author":"Tomatis","year":"2011","journal-title":"Tumori"},{"key":"10.1016\/j.ejmp.2026.105917_b0125","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1002\/mp.14667","article-title":"Robotic MLC-based plans: a study of plan complexity","volume":"48","author":"Masi","year":"2021","journal-title":"Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0130","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1118\/1.3276775","article-title":"A new metric for assessing IMRT modulation complexity and plan deliverability","volume":"37","author":"McNiven","year":"2010","journal-title":"Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0135","unstructured":"Tommaso Zoppi, Macaron Project, NextGenerationEU Programme, Italian DM737 \u2013 CUP B15F21005410003, MACARON Project Https:\/\/Github.Com\/Tommyippoz\/MACARON (n.d.)."},{"key":"10.1016\/j.ejmp.2026.105917_b0140","doi-asserted-by":"crossref","unstructured":"N. V Chawla, K.W. Bowyer, L.O. Hall, W.P. Kegelmeyer, SMOTE: Synthetic Minority Over-sampling Technique, 2002.","DOI":"10.1613\/jair.953"},{"key":"10.1016\/j.ejmp.2026.105917_b0145","doi-asserted-by":"crossref","unstructured":"J.R. Quinlan, Induction of Decision Trees, 1986.","DOI":"10.1023\/A:1022643204877"},{"key":"10.1016\/j.ejmp.2026.105917_b0150","doi-asserted-by":"crossref","unstructured":"N.R. Draper, H. Smith, Applied Regression Analysis, Wiley, 1998. doi: 10.1002\/9781118625590.","DOI":"10.1002\/9781118625590"},{"key":"10.1016\/j.ejmp.2026.105917_b0155","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/S0378-8733(01)00039-9","article-title":"Distance and cosine measures of niche overlap","volume":"23","author":"Sohn","year":"2001","journal-title":"Soc Networks"},{"key":"10.1016\/j.ejmp.2026.105917_b0160","doi-asserted-by":"crossref","first-page":"2611","DOI":"10.1002\/mp.12896","article-title":"Efficiently train and validate a RapidPlan model through APQM scoring","volume":"45","author":"Fusella","year":"2018","journal-title":"Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0165","doi-asserted-by":"crossref","unstructured":"A. Fogliata, P.-M. Wang, F. Belosi, A. Clivio, G. Nicolini, E. Vanetti, L. Cozzi, Assessment of a model based optimization engine for volumetric modulated arc therapy for patients with advanced hepatocellular cancer, 2014. http:\/\/www.ro-journal.com\/content\/9\/1\/236.","DOI":"10.1186\/s13014-014-0236-0"},{"key":"10.1016\/j.ejmp.2026.105917_b0170","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.radonc.2011.05.025","article-title":"Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma","volume":"102","author":"Petit","year":"2012","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0175","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.radonc.2014.07.009","article-title":"Improved robotic stereotactic body radiation therapy plan quality and planning efficacy for organ-confined prostate cancer utilizing overlap-volume histogram-driven planning methodology","volume":"112","author":"Wu","year":"2014","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0180","first-page":"6148","article-title":"Neural network dose models for knowledge-based planning in pancreatic SBRT:, me","volume":"44","author":"Campbell","year":"2017","journal-title":"Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0185","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ac0856","article-title":"Learning-based dose prediction for pancreatic stereotactic body radiation therapy using dual pyramid adversarial network","volume":"66","author":"Momin","year":"2021","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.ejmp.2026.105917_b0190","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1002\/acm2.13337","article-title":"Knowledge-based radiation treatment planning: a data-driven method survey","volume":"22","author":"Momin","year":"2021","journal-title":"J Appl Clin Med Phys"},{"key":"10.1016\/j.ejmp.2026.105917_b0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2024.110609","article-title":"Knowledge-based planning for fully automated radiation therapy treatment planning of 10 different cancer sites","volume":"202","author":"Chung","year":"2025","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ejmp.2026.105917_b0200","doi-asserted-by":"crossref","unstructured":"P. Cunningham, S.J. Delany, Underestimation Bias and Underfitting in Machine Learning, (2020). doi: 10.1007\/978-3-030-73959-1_2.","DOI":"10.1007\/978-3-030-73959-1_2"}],"container-title":["Physica Medica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1120179726002048?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1120179726002048?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T11:24:55Z","timestamp":1788780295000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1120179726002048"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":40,"alternative-id":["S1120179726002048"],"URL":"https:\/\/doi.org\/10.1016\/j.ejmp.2026.105917","relation":{},"ISSN":["1120-1797"],"issn-type":[{"value":"1120-1797","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A simple parameter to guide plan optimization for robotic pancreas SBRT","name":"articletitle","label":"Article Title"},{"value":"Physica Medica","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejmp.2026.105917","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"105917"}}