INTRODUCTION: The aim of this study was to assess 2 cone-beam computed tomographic systems on the detection of artificially induced vertical root fractures (VRFs) and artifact intensity using birooted teeth restored with different intracanal materials. METHODS: The sample consisted of 20 extracted birooted premolars. Root fracture was induced in half of the sample. Seven intracanal material combinations were used in each tooth, 1 at a time: unrestored, gutta-percha, a buccal root with gutta-percha and a lingual root with a fiberglass post, a buccal root with gutta-percha and a lingual root with a metal core fiberglass post, fiberglass posts, metal core fiberglass posts, and NiCr posts. Cone-beam computed tomographic scans were acquired using CS 9000 3D (Carestream Dental Rochester, NY) and OP300 (Instrumentarium Dental Inc, Tuusula, Finland) units. Exposure parameters were fixed at 90 kV and 8 mA. The voxel size and field of view were set at 0.085 mm and 5 × 5 cm for OP300 and 0.076 mm and 5 × 3.75 cm for CS 9000, respectively. Two observers assessed all images using a 5-point confidence scale for VRF detection and a 4-point score for artifact interference. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve were compared using 2-way analysis of variance and the Tukey test (α = 0.05). Artifact interference was evaluated by descriptive statistics and the chi-square test. RESULTS: There were significant differences between scanners (P > .05) and among the different intracanal material groups (OP300) (P < .05) for specificity. When a metal post was present in both roots, severe artifact interference was observed in all images. CONCLUSIONS: CS 9000 3D presented better performance than OP300 on VRF detection of endodontically treated teeth. Unrestored teeth and teeth filled with fiberglass posts were considered the groups with the lowest artifact interference and the highest VRF detection results.
INTRODUCTION: The aim of this study was to assess 2 cone-beam computed tomographic systems on the detection of artificially induced vertical root fractures (VRFs) and artifact intensity using birooted teeth restored with different intracanal materials. METHODS: The sample consisted of 20 extracted birooted premolars. Root fracture was induced in half of the sample. Seven intracanal material combinations were used in each tooth, 1 at a time: unrestored, gutta-percha, a buccal root with gutta-percha and a lingual root with a fiberglass post, a buccal root with gutta-percha and a lingual root with a metal core fiberglass post, fiberglass posts, metal core fiberglass posts, and NiCr posts. Cone-beam computed tomographic scans were acquired using CS 9000 3D (Carestream Dental Rochester, NY) and OP300 (Instrumentarium Dental Inc, Tuusula, Finland) units. Exposure parameters were fixed at 90 kV and 8 mA. The voxel size and field of view were set at 0.085 mm and 5 × 5 cm for OP300 and 0.076 mm and 5 × 3.75 cm for CS 9000, respectively. Two observers assessed all images using a 5-point confidence scale for VRF detection and a 4-point score for artifact interference. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve were compared using 2-way analysis of variance and the Tukey test (α = 0.05). Artifact interference was evaluated by descriptive statistics and the chi-square test. RESULTS: There were significant differences between scanners (P > .05) and among the different intracanal material groups (OP300) (P < .05) for specificity. When a metal post was present in both roots, severe artifact interference was observed in all images. CONCLUSIONS:CS 9000 3D presented better performance than OP300 on VRF detection of endodontically treated teeth. Unrestored teeth and teeth filled with fiberglass posts were considered the groups with the lowest artifact interference and the highest VRF detection results.
Authors: Amanda P Candemil; Benjamin Salmon; Karla F Vasconcelos; Anne C Oenning; Reinhilde Jacobs; Deborah Q Freitas; Francisco Haiter-Neto; Francesca Mangione; Matheus L Oliveira Journal: Sci Rep Date: 2021-09-27 Impact factor: 4.379