Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images
Abstract A novel classification system, termed the Sivan classification, was developed to enhance the diagnosis of jaw lesions by utilizing visual volumetric analysis of three-dimensional Cone Beam Computed Tomography (CBCT) images. This classification groups lesions into ten categories, primarily d...
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-83974-4 |
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| author | Sivan Sathish |
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| author_sort | Sivan Sathish |
| collection | DOAJ |
| description | Abstract A novel classification system, termed the Sivan classification, was developed to enhance the diagnosis of jaw lesions by utilizing visual volumetric analysis of three-dimensional Cone Beam Computed Tomography (CBCT) images. This classification groups lesions into ten categories, primarily divided into hypovolumetric, hypervolumetric, and normovolumetric groups. To validate this system, 10 raters—comprising 5 general dentists and 5 oral radiology specialists—assessed the CBCT images and diagnosed the lesions using the Sivan classification. Eight raters repeated the process after one month to assess consistency. The overall agreement between raters, quantified using kappa statistics, was 0.82, indicating excellent consistency. Hypervolumetric and normovolumetric lesions demonstrated the highest agreement (kappa 0.84 and 0.82, respectively), while hypovolumetric lesions showed substantial agreement (kappa 0.77). Pairwise interrater agreement ranged from 76 to 93%, with kappa values between 0.75 and 0.87. Intrarater reliability was equally strong, with kappa values between 0.79 and 0.89.These results suggest that the Sivan classification provides a robust and reliable framework for diagnosing jaw lesions using CBCT volumetric analysis, surpassing traditional diagnostic methods in accuracy and consistency. |
| format | Article |
| id | doaj-art-92e3f23549d2432c87947be62239d754 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-92e3f23549d2432c87947be62239d7542025-01-05T12:27:08ZengNature PortfolioScientific Reports2045-23222024-12-0114111110.1038/s41598-024-83974-4Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic imagesSivan Sathish0Department of Oral Medicine and Radiology, Teerthanker Mahaveer Dental College and Research CentreAbstract A novel classification system, termed the Sivan classification, was developed to enhance the diagnosis of jaw lesions by utilizing visual volumetric analysis of three-dimensional Cone Beam Computed Tomography (CBCT) images. This classification groups lesions into ten categories, primarily divided into hypovolumetric, hypervolumetric, and normovolumetric groups. To validate this system, 10 raters—comprising 5 general dentists and 5 oral radiology specialists—assessed the CBCT images and diagnosed the lesions using the Sivan classification. Eight raters repeated the process after one month to assess consistency. The overall agreement between raters, quantified using kappa statistics, was 0.82, indicating excellent consistency. Hypervolumetric and normovolumetric lesions demonstrated the highest agreement (kappa 0.84 and 0.82, respectively), while hypovolumetric lesions showed substantial agreement (kappa 0.77). Pairwise interrater agreement ranged from 76 to 93%, with kappa values between 0.75 and 0.87. Intrarater reliability was equally strong, with kappa values between 0.79 and 0.89.These results suggest that the Sivan classification provides a robust and reliable framework for diagnosing jaw lesions using CBCT volumetric analysis, surpassing traditional diagnostic methods in accuracy and consistency.https://doi.org/10.1038/s41598-024-83974-4Jaw neoplasmsCone-beam computed tomographyClassification |
| spellingShingle | Sivan Sathish Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images Scientific Reports Jaw neoplasms Cone-beam computed tomography Classification |
| title | Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images |
| title_full | Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images |
| title_fullStr | Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images |
| title_full_unstemmed | Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images |
| title_short | Sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3-dimensional cone-beam computed tomographic images |
| title_sort | sivan classification system for diagnosis of jaw lesions based on visual volumetric analysis of 3 dimensional cone beam computed tomographic images |
| topic | Jaw neoplasms Cone-beam computed tomography Classification |
| url | https://doi.org/10.1038/s41598-024-83974-4 |
| work_keys_str_mv | AT sivansathish sivanclassificationsystemfordiagnosisofjawlesionsbasedonvisualvolumetricanalysisof3dimensionalconebeamcomputedtomographicimages |