{"doi":"10.1016/j.ijom.2020.07.027","title":"Semi-automatic magnetic resonance imaging based orbital fat volumetry: reliability and correlation with computed tomography","abstract":null,"journal":"International Journal of Oral and Maxillofacial Surgery","year":2021,"id":638166,"datarank":0.3596842909197557,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.0,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"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":1657362,"name":"B. Degrieck","orcid":null,"position":1,"is_corresponding":false},{"id":1657363,"name":"K. Orhan","orcid":null,"position":2,"is_corresponding":false},{"id":1657364,"name":"J. Deferm","orcid":"0000-0002-6545-7648","position":3,"is_corresponding":false},{"id":1657365,"name":"C. Politis","orcid":"0000-0003-4772-9897","position":4,"is_corresponding":false},{"id":1657366,"name":"E. Shaheen","orcid":null,"position":5,"is_corresponding":false},{"id":1570997,"name":"R. Jacobs","orcid":"0000-0002-3461-0363","position":6,"is_corresponding":false},{"id":1657361,"name":"R. Willaert","orcid":"0000-0003-1610-6988","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Semi-automatic magnetic resonance imaging based orbital fat volumetry: reliability and correlation with computed tomography","abstract":"Post-processing analysis can provide valuable information for diagnosis and planning of orbital disorders. This cross-sectional study aims to evaluate the reliability of semi-automatic, orbital fat volumetry using magnetic resonance imaging (MRI). Two observers assessed the orbital fat volume using a standard MRI protocol (3T, T1w sequence) in 12 orbits diagnosed with Graves' orbitopathy (GO) and 10 healthy control orbits. MRI and computed tomography (CT) based analysis were compared. Intra-observer variability was good (intraclass correlation coefficient (ICC) 0.88; 95% confidence interval (CI) [0.70, 0.95]) and interobserver agreement was moderate (ICC 0.55; 95% CI [-0.09, 0.81]), which corresponds to a mean percentage difference of 1.3% and 17.9% of the total orbital fat volume. Mean differences between MRI and CT measurements were, respectively, 1.1 cm<sup>3</sup> (P= 0.064, 95% CI [-0.20, 2.43]) and 1.4 cm<sup>3</sup> (P=0.016, 95% CI [0.21, 2.56]) for the control and the GO group. MRI volumetry was strongly correlated with CT (Pearson's r= 0.7, P<0.001). We conclude that orbital fat volumetry is feasible with a semi-automatic segmentation procedure and standard MRI protocol. Correlation with CT volumetry is good, but considerable bias may derive from observer variability and these errors should be taken into account for the purpose of volumetric analysis. Better definition of error sources may increase measurement accuracy.","is_dataset_classified":null,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"32814653","pmcid":null,"openalex_id":"https://openalex.org/W3049125416","authors":[],"funders":[],"total_grants":0,"fwci":0.9306,"citation_percentile":0.73974564,"influential_citations":0,"citation_trend":[{"year":2022,"count":2},{"year":2023,"count":5},{"year":2025,"count":2},{"year":2026,"count":1}],"oa_status":"bronze","license":"https://www.elsevier.com/legal/tdmrep-license","oa_locations":[{"url":"http://www.ijoms.com/article/S0901502720302885/pdf","host_type":"journal"},{"url":"http://www.ijoms.com/article/S0901502720302885/pdf","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0901502720302885?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0901502720302885?httpAccept=text/plain","host_type":"publisher"},{"url":"https://doi.org/10.1016/j.ijom.2020.07.027","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/32814653","host_type":"repository"},{"url":"https://lirias.kuleuven.be/handle/123456789/659242","host_type":"repository"}],"fields_of_study":["Ophthalmology and Eye Disorders","Advanced Differential Geometry Research","Cerebral Venous Sinus Thrombosis","Cross-Sectional Studies","Graves Ophthalmopathy","Humans","Magnetic Resonance Imaging","Observer Variation","Orbit","Reproducibility of Results","Tomography, X-Ray Computed"],"mesh_terms":["Cross-Sectional Studies","Humans","Magnetic Resonance Imaging","Orbit","Tomography, X-Ray Computed","Reproducibility of Results","Observer Variation","Graves Ophthalmopathy"],"keywords":["Intraclass correlation","Medicine","Magnetic resonance imaging","Confidence interval","Nuclear medicine","Computed tomography","Correlation","Radiology","Mathematics","Internal medicine","Orbit","computer-assisted image processing","Graves’ Orbitopathy"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T20:13:46.306672Z","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":[]}