Influence of size of field of view (FOV), position within the FOV, and scanning mode on the detection of root fracture and observer's perception of artifacts in CBCT images.

Objective: To assess the influence of field of view (FOV) size, scanning position within the FOV and scanning mode on the detection of root fracture and artifact perception.

Methods: Forty single-rooted premolars restored with NiCr and AgPd posts were divided into two groups: fractured and sound. All teeth were scanned using four CBCT scanning protocols varying FOV sizes (80 × 80 mm and 50 × 55 mm) and scanning modes (Standard and High Definition).

Influence of tooth position within the field of view on the intensity of cone-beam computed tomographic imaging artifacts when assessing teeth restored with various intracanal materials.

Purpose: This study aimed to quantify the influence of tooth position within the field-of-view (FOV) on cone-beam computed tomography (CBCT) imaging artifacts' intensity when assessing teeth restored with various intracanal materials.

Materials And Methods: Seventy single-rooted teeth were divided into 7 groups (10 teeth per group): NiCr post (NC), AgPd post (AP), metal core fiberglass post (MCFG), fiberglass post (FG), anatomical fiberglass post (AFG), fiberglass post cemented with core build-up cement (FGCo), and anatomical fiberglass post cemented with core build-up cement (AFGCo). All posts were cemented using a regular dual-curing resin cement (Allcem), except FGCo and AFGCo which were cemented with a core build-up dual-curing resin cement (AllcemCore).

Quantitative assessment of image artifacts from root filling materials on CBCT scans made using several exposure parameters.

Purpose: To quantify artifacts from different root filling materials in cone-beam computed tomography (CBCT) images acquired using different exposure parameters.

Materials And Methods: Fifteen single-rooted teeth were scanned using 8 different exposure protocols with 3 different filling materials and once without filling material as a control group. Artifact quantification was performed by a trained observer who made measurements in the central axial slice of all acquired images in a fixed region of interest using ImageJ.