Background: Beam hardening and scattering artifacts from high-density objects such as dental implants adversely affect the image quality and subsequently the detection of fenestration or dehiscence around dental implants. Objective: This study aimed to assess the efficacy of metal artifact reduction (MAR) algorithm of two cone-beam computed tomography (CBCT) systems for detection of peri-implant fenestration and dehiscence. Material and Methods: In this experimental study, thirty-six titanium implants were placed in bone blocks of bovine ribs. Fenestration and dehiscence were created in the buccal bone around implants. CBCT images were obtained using Cranex 3D and ProMax 3D CBCT systems with and without MAR algorithm. Two experienced radiologists observed the images. Data were analyzed using SPSS software. The Kappa coefficient of agreement, the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy of different imaging modalities were calculated and analyzed. Results: In both CBCT systems, the use of MAR algorithm decreased the area under the ROC curve and subsequently the diagnostic accuracy for the detection of fenestration and dehiscence. The sensitivity, specificity and accuracy of both CBCT systems were higher in absence of the MAR algorithm. The specificity of ProMax 3D for detection of fenestration was equal with/without the MAR algorithm. Conclusion: Although CBCT is suitable for detection of peri-implant defects, the application of the MAR algorithm does not enhance the detection of peri-implant fenestration and dehiscence.
Background: Early detection of peri-implant bone defects is highly important because these defects eventually lead to gingival recession, bone loss and implant failure. Objective: This study aimed to assess and compare the efficacy of periapical radiography and three CBCT systems for the detection of peri-implant dehiscence defects. Material and Methods: In this vitro study, 124 titanium implants were placed in bovine ribs. The bone pieces were then mounted in boxes in the form of mandible and red dental wax was used to simulate the soft tissue. Crestal bone defects with 2, 3, and 4 mm depth were created in the ribs using a round bur. Periapical and CBCT images were then obtained. Images were investigated by two oral and maxillofacial radiologists twice with a two-week interval. The results were analyzed using chi-square, Kappa coefficient, Cochrane’s Q and McNemar tests as well as the receiver operating characteristic (ROC) curve. Results: The two observers showed good agreement in detection of sound and defective samples on periapical radiographs and CBCT scans. The level of agreement was low in detection of two samples with 2 mm defects on CBCT scans taken with Planmeca and NewTom 3G systems at the time of second assessment. NewTom 3G had the highest sensitivity (68.9%, 74.2% and 86.3%, respectively) and specificity (100% for all three) compared to other systems for detection of 2, 3 and 4 mm crestal bone defects. Conclusion: The inter-observer agreement increased with increase in depth of defects. NewTom 3G had the highest accuracy for detection of crestal bone defects.
UNSTRUCTURED This study aimed to assess the efficacy of metal artifact reduction (MAR) algorithm of two cone-beam computed tomography (CBCT) systems for detection of peri-implant fenestration and dehiscence. Thirty-six titanium implants were placed in bone blocks of bovine ribs. Fenestration and dehiscence were created in the buccal bone around implants using a round bur. The bone blocks were then mounted in a wax rim to simulate the mandible. CBCT images were obtained using Cranex 3D and ProMax 3D CBCT systems with and without MAR algorithm before and after creation of defects. Two experienced radiologists observed the images twice with a 2-week interval. Data were analyzed using SPSS software version 22.The Kappa coefficient of agreement, the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, accuracy of different imaging modalities were calculated and analyzed. According to the kappa statistics, the intra- and inter-observer agreements were higher for images without the MAR algorithm compared with those with the MAR algorithm. In both CBCT systems, use of MAR algorithm decreased the area under the ROC curve and subsequently the diagnostic accuracy for detection of fenestration and dehiscence. The sensitivity, specificity and accuracy of both CBCT systems were higher in absence of the MAR algorithm. The specificity of ProMax 3D for detection of fenestration was equal with/without the MAR algorithm. Although CBCT is suitable for detection of peri-implant defects, application of the MAR algorithm does not enhance the detection of peri-implant fenestration and dehiscence.
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