Accuracy evaluation of cone beam computed tomography applied to measure peri-implant bone thickness in living patients: an ex vivo and in vivo experiment

Lan, Yanhua; Huang, Xiaoyuan; Fan, Mingxing; Yu, Huazhen; Xie, Zhijian; Zhou, Yiqun

doi:10.1007/s00784-022-04590-y

Cited by 2 publications

(2 citation statements)

References 42 publications

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“…28 It consists of 5-domains: risk of bias, indirectness, inconsistency, imprecision, and publication bias. Particularly, for imprecision a conservative threshold of ±0.2 mm for soft-tissue thickness 29 and ±0.5 mm for bone thickness 30 was used to establish minimum important differences. Judgments across domains can be summarized into four levels of confidence for each relative treatment effect corresponding to very low, low, moderate, and high GRADE assessments.…”

Section: Data Synthesismentioning

confidence: 99%

The feasibility of ultrasonography for the measurement of periodontal and peri‐implant phenotype: A systematic review and meta‐analysis

Fan

Sáenz-Ravello

Schiegnitz

et al. 2023

Clin Implant Dent Rel Res

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BackgroundScreening ultrasonography was proposed for monitoring periodontal soft tissues in the early 1960s, owing to its nonionizing, real‐time, and cost‐effective properties. Studies have provided convincing preliminary evidence for the use of ultrasound (US) in implant dentistry.PurposeTo assess the feasibility of ultrasonography (US) for measuring the buccal thickness of periodontal and peri‐implant tissues. The secondary objective was to evaluate the reliability of US measurements compared to classic techniques, such as CBCT and directly measurements.Materials and MethodsAn electronic literature search was conducted by three independent reviewers through February 2023. The inclusion criteria were articles investigating at least five patients/cadavers with US measurements in periodontal or peri‐implant buccal tissues. Compliance with methodological reporting standards and risk of bias was assessed using EULAR and QUADAS‐C tools, respectively. Random‐effects meta‐analysis was conducted, using Bland–Altman analysis. Certainty of the evidence was assessed using GRADE.ResultsThe final selection included 12 studies examining 458 patients and 13 cadavers, with a total of 226 implants, 1958 teeth and 60 edentulous sites. The body of evidence was assessed as partially compliant with methodological reporting standards for US studies and had an unclear to high risk of bias. Meta‐analysis of five comparative studies showed no evidence of clinically significant bias between US and direct measurements (very low certainty), and between US and CBCT (very low certainty) for soft‐tissue thickness. Likewise, for bone thickness, there is no evidence of clinically significant bias between US and CBCT (low certainty).ConclusionsCompared to the CBCT and direct measurements, ultrasonography might be a reliable approach for monitoring on periodontal and peri‐implant phenotype. However, there is uncertainty about estimates of the actual effect, so further standardized and larger sample size of clinical research is needed.

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Section: Data Synthesismentioning

confidence: 99%

The feasibility of ultrasonography for the measurement of periodontal and peri‐implant phenotype: A systematic review and meta‐analysis

Fan

Sáenz-Ravello

Schiegnitz

et al. 2023

Clin Implant Dent Rel Res

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“…In recent years, with the rapid progress of medical and health care, dental implant technology has become the first choice for patients to restore missing teeth [1] . Bone preservation around implants is essential for their initial stability and longterm survival [2] , and methods for assessing bone mass include both invasive and noninvasive [3] . In clinical practice, the detection of bone height around implants relies on imaging examinations.…”

Section: Introductionmentioning

confidence: 99%

A one-stage deep learning architecture for the detection of key points in peri-implant alveolar bone

Guo,

Lv,

Niu

et al. 2023

Third International Conference on Signal Image Processing and Communication (ICSIPC 2023)

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Detecting the key points of the peri-implant alveolar bone is the most crucial step in automatic clinical diagnosis. To achieve keypoint detection accurately and efficiently, we propose an end-to-end convolutional neural network-based method for detecting key points of the peri-implant alveolar bone. The method uses a High-Resolution Network (HRNet) for feature extraction and regards type and identity labels as different attributes and achieves single-stage pose estimation via Attribute-Disentangled Heatmap (ADH) prediction. ADH is end-to-end trainable and presents better robustness to accumulated errors in two-stage models. It jointly optimizes keypoint type and identity prediction in a unified model, hence enjoying better efficiency and compactness. We compared the proposed method with the state-of-the-art keypoint methods ResNet-50, Mask-RCNN, and Hourglass, and the experimental results show the superiority of our method. The mean Average Precision (mAP) value achieves 85.6% in mAP, which outperforms all the compared methods.

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Accuracy evaluation of cone beam computed tomography applied to measure peri-implant bone thickness in living patients: an ex vivo and in vivo experiment

Cited by 2 publications

References 42 publications

The feasibility of ultrasonography for the measurement of periodontal and peri‐implant phenotype: A systematic review and meta‐analysis

The feasibility of ultrasonography for the measurement of periodontal and peri‐implant phenotype: A systematic review and meta‐analysis

A one-stage deep learning architecture for the detection of key points in peri-implant alveolar bone

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