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Clinical problems of computer-guided implant surgery

Overview of attention for article published in Maxillofacial Plastic and Reconstructive Surgery, March 2016
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Title
Clinical problems of computer-guided implant surgery
Published in
Maxillofacial Plastic and Reconstructive Surgery, March 2016
DOI 10.1186/s40902-016-0063-3
Pubmed ID
Authors

Seong-Yong Moon, Kyoung-Rok Lee, Su-Gwan Kim, Mee-Kyoung Son

Abstract

The utilization of a cone-beam computed tomography (CT)-assisted surgical template allows for predictable results because implant placement plans can be performed in the actual surgery. In order to assess the accuracy of the CT-guided surgery, angular errors and shoulder/apex distance errors were evaluated by data fusion from before and after the placement. Computer-guided implant surgery was performed in five patients with 19 implants. In order to analyze differences of the implant fixture body between preoperative planned implant and postoperative placed implant, angular error and distance errors were evaluated. The mean angular errors between the preoperative planned and postoperative placed implant was 3.84° ± 1.49°; the mean distance errors between the planned and placed implants were 0.45 ± 0.48 mm horizontally and 0.63 ± 0.51 mm vertically at the implant neck and 0.70 ± 0.63 mm horizontally and 0.64 ± 0.57 mm vertically at the implant apex for all 19 implants. It is important to be able to utilize these methods in actual clinical settings by improving the various problems, including the considerations of patient mouth opening limitations, surgical guide preparation, and fixation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 27%
Student > Postgraduate 9 14%
Student > Doctoral Student 8 13%
Student > Bachelor 5 8%
Researcher 4 6%
Other 7 11%
Unknown 14 22%
Readers by discipline Count As %
Medicine and Dentistry 44 69%
Nursing and Health Professions 2 3%
Agricultural and Biological Sciences 1 2%
Unspecified 1 2%
Unknown 16 25%