{"doi":"10.1088/0031-9155/53/11/002","title":"How many plans are needed in an IMRT multi-objective plan database?","abstract":null,"journal":"Physics in Medicine and Biology","year":2008,"id":681325,"datarank":0.6830815337400812,"base_score":4.553876891600541,"endowment":4.553876891600541,"self_citation_contribution":0.6830815337400812,"citation_network_contribution":0.0,"self_endowment_contribution":0.6830815337400812,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":94,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":888340,"name":"Thomas Bortfeld","orcid":"0000-0002-3883-0398","position":1,"is_corresponding":false},{"id":13375,"name":"David Craft","orcid":"0000-0003-3093-718X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"How many plans are needed in an IMRT multi-objective plan database?","abstract":"In multi-objective radiotherapy planning, we are interested in Pareto surfaces of dimensions 2 up to about 10 (for head and neck cases, the number of structures to trade off can be this large). A key question that has not been answered yet is: how many plans does it take to sufficiently represent a high-dimensional Pareto surface? In this paper, we present a method to answer this question, and we show that the number of points needed is modest: 75 plans always controlled the error to within 5%, and in all cases but one, N + 1 plans, where N is the number of objectives, was enough for <15% error. We introduce objective correlation matrices and principal component analysis (PCA) of the beamlet solutions as two methods to understand this. PCA reveals that the feasible beamlet solutions of a Pareto database lie in a narrow, small dimensional subregion of the full beamlet space, which helps explain why the number of plans needed to characterize the database is small.","is_dataset_classified":null,"base_score":4.553876891600541,"endowment":4.553876891600541,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"18451463","pmcid":null,"openalex_id":"https://openalex.org/W2122993411","authors":[],"funders":[{"funder_name":"NCI NIH HHS","grant_id":"1 R01 CA103904-01A1","title":null}],"total_grants":1,"fwci":8.6612,"citation_percentile":0.98035103,"influential_citations":0,"citation_trend":[{"year":2012,"count":11},{"year":2013,"count":8},{"year":2014,"count":4},{"year":2015,"count":4},{"year":2016,"count":5},{"year":2017,"count":4},{"year":2018,"count":5},{"year":2019,"count":4},{"year":2020,"count":3},{"year":2021,"count":5},{"year":2022,"count":5},{"year":2023,"count":6},{"year":2024,"count":2},{"year":2025,"count":4}],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://doi.org/10.1088/0031-9155/53/11/002","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/18451463","host_type":"repository"}],"fields_of_study":["Advanced Radiotherapy Techniques","Advanced Multi-Objective Optimization Algorithms","Optimal Experimental Design Methods","Computer Simulation","Dose-Response Relationship, Radiation","Humans","Radiotherapy Planning, Computer-Assisted"],"mesh_terms":["Computer Simulation","Dose-Response Relationship, Radiation","Humans","Radiotherapy Planning, Computer-Assisted"],"keywords":["Computer science","Plan (archaeology)","Pareto principle","Principal component analysis","Pareto optimal","Principal (computer security)","Database","Multi-objective optimization","Space (punctuation)","Key (lock)","Mathematical optimization","Data mining","Mathematics","Artificial intelligence","Machine learning"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Sustainable cities and communities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-17T17:32:48.505864Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}