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Image-guided surgery, prosthetic-based virtual planning, 3D printing, and CAD/CAM technology are changing head and neck ablative and reconstructive surgical oncology. Due to quality-of-life improvement, dental implant rehabilitation could be considered in every patient treated with curative intent. Accurate implant placement is mandatory for prosthesis long-term stability and success in oncologic patients. We present a prospective study, with a novel workflow, comprising 11 patients reconstructed with free flaps and 56 osseointegrated implants placed in bone flaps or remnant jaws (iliac crest, fibula, radial forearm, anterolateral thigh). Starting from CT data and jaw plaster model scanning, virtual dental prosthesis was designed. Then prosthetically driven dental implacement was also virtually planned and transferred to the patient by means of intraoperative infrared optical navigation (first four patients), and a combination of conventional static teeth supported 3D-printed acrylic guide stent, intraoperative dynamic navigation, and augmented reality for final intraoperative verification (last 7 patients). Coronal, apical, and angular deviation between virtual surgical planning and final guided intraoperative position was measured on each implant. There is a clear learning curve for surgeons when applying guided methods. Initial only-navigated cases achieved low accuracy but were comparable to non-guided freehand positioning due to jig registration instability. Subsequent dynamic navigation cases combining highly stable acrylic static guides as reference and registration markers result in the highest accuracy with a 1-1.5-mm deviation at the insertion point. Smartphone-based augmented reality visualization is a valuable tool for intraoperative visualization and final verification, although it is still a difficult technique for guiding surgery. A fixed screw-retained ideal dental prosthesis was achieved in every case as virtually planned. Implant placement, the final step in free flap oncological reconstruction, could be accurately planned and placed with image-guided surgery, 3D printing, and CAD/CAM technology. The learning curve could be overcome with preclinical laboratory training, but virtually designed and 3D-printed tracer registration stability is crucial for accurate and predictable results. Applying these concepts to our difficult oncologic patient subgroup with deep anatomic alterations ended in comparable results as those reported in non-oncologic patients.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8833256 | PMC |
http://dx.doi.org/10.3389/fonc.2021.754943 | DOI Listing |
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