real-time-dynamic-navigation-system-for-precise-quad-zygomatic

Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla

Zygomatic implants (ZIs) are an ideal way to address cases of a severely atrophic edentulous maxilla and maxilla defects because they replace extensive ...

National Center for Stomatology, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology

To identify potentially pathogenic mutations for tooth agenesis by whole-exome sequencing.

Novel mutations identified in patients with tooth agenesis by whole-exome sequencing.

Cone-beam computed tomography (CBCT) and conventional multislice CT (MSCT) are both used in zygomatic implant navigation surgery but the superiority of one technique versus the other remains unclear.

Comparative accuracy of cone-beam CT and conventional multislice computed tomography for real-time navigation in zygomatic implant surgery.

The traditional way to treat maxillary edentulous Cawood and Howell Class 4 (CH4) patients who exhibit the knife-edge ridge form of edentulous jaws that are adequate in height and inadequate in width is extensive autologous bone grafting for conventional implant placement.

A single-arm clinical trial investigating the feasibility of the zygomatic implant quad approach for Cawood and Howell Class 4 edentulous maxilla: An option for immediate loading.

Article	Year
Novel mutations identified in patients with tooth agenesis by whole-exome sequencing. Oral diseases\| PubMed ID: 30417976	2019
Comparative accuracy of cone-beam CT and conventional multislice computed tomography for real-time navigation in zygomatic implant surgery. Clinical implant dentistry and related research\| PubMed ID: 33112508	2020
A single-arm clinical trial investigating the feasibility of the zygomatic implant quad approach for Cawood and Howell Class 4 edentulous maxilla: An option for immediate loading. Clinical implant dentistry and related research\| PubMed ID: 34580991	2021

Yihan Shen

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