{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["51(3)"],"submitter":["Diaconu A"],"pubmed_abstract":["<h4>Objectives</h4>To propose and validate a reliable semi-automatic approach for three-dimensional (3D) analysis of the upper airway (UA) based on voxel-based registration (VBR).<h4>Methods</h4>Post-operative cone beam computed tomography (CBCT) scans of 10 orthognathic surgery patients were superimposed to the pre-operative CBCT scans by VBR using the anterior cranial base as reference. Anatomic landmarks were used to automatically cut the UA and calculate volumes and cross-sectional areas (CSA). The 3D analysis was performed by two observers twice, at an interval of two weeks. Intraclass correlations and Bland-Altman plots were used to quantify the measurement error and reliability of the method. The relative Dahlberg error was calculated and compared with a similar method based on landmark re-identification and manual measurements.<h4>Results</h4>Intraclass correlation coefficient (ICC) showed excellent intra- and inter-observer reliability (ICC ≥ 0.995). Bland-Altman plots showed good observer agreement, low bias and no systematic errors. The relative Dahlberg error ranged between 0.51 and 4.30% for volume and 0.24 and 2.90% for CSA. This was lower when compared with a similar, manual method. Voxel-based registration introduced 0.05-1.44% method error.<h4>Conclusions</h4>The proposed method was shown to have excellent reliability and high observer agreement. The method is feasible for longitudinal clinical trials on large cohorts due to being semi-automatic."],"journal":["Dento maxillo facial radiology"],"pagination":["20210253"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8925868"],"repository":["biostudies-literature"],"pubmed_title":["A semi-automatic approach for longitudinal 3D upper airway analysis using voxel-based registration."],"pmcid":["PMC8925868"],"pubmed_authors":["Diaconu A","Cattaneo PM","Holte MB","Pinholt EM"],"additional_accession":[]},"is_claimable":false,"name":"A semi-automatic approach for longitudinal 3D upper airway analysis using voxel-based registration.","description":"<h4>Objectives</h4>To propose and validate a reliable semi-automatic approach for three-dimensional (3D) analysis of the upper airway (UA) based on voxel-based registration (VBR).<h4>Methods</h4>Post-operative cone beam computed tomography (CBCT) scans of 10 orthognathic surgery patients were superimposed to the pre-operative CBCT scans by VBR using the anterior cranial base as reference. Anatomic landmarks were used to automatically cut the UA and calculate volumes and cross-sectional areas (CSA). The 3D analysis was performed by two observers twice, at an interval of two weeks. Intraclass correlations and Bland-Altman plots were used to quantify the measurement error and reliability of the method. The relative Dahlberg error was calculated and compared with a similar method based on landmark re-identification and manual measurements.<h4>Results</h4>Intraclass correlation coefficient (ICC) showed excellent intra- and inter-observer reliability (ICC ≥ 0.995). Bland-Altman plots showed good observer agreement, low bias and no systematic errors. The relative Dahlberg error ranged between 0.51 and 4.30% for volume and 0.24 and 2.90% for CSA. This was lower when compared with a similar, manual method. Voxel-based registration introduced 0.05-1.44% method error.<h4>Conclusions</h4>The proposed method was shown to have excellent reliability and high observer agreement. The method is feasible for longitudinal clinical trials on large cohorts due to being semi-automatic.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Mar","modification":"2025-04-04T08:52:54.704Z","creation":"2025-04-04T08:52:54.704Z"},"accession":"S-EPMC8925868","cross_references":{"pubmed":["34644181"],"doi":["10.1259/dmfr.20210253"]}}