Image-to-patient registration in navigated mandibular surgery is complex due to the mobile nature of the mandible compared with other craniofacial bones. As a result, surgical navigation is rarely employed in the mandibular region. This systematic review provides an overview of the different registration methods that are used for surgical navigation of the mandible. A systematic search was performed in the MEDLINE Ovid, Scopus, and Embase databases on March 25, 2021. Search terms included synonyms for mandibular surgery, surgical navigation, and registration methods. Articles about navigated mandibular surgery, where the registration method was explicitly mentioned, were included. The database search yielded a total of 2952 articles, from which 81 articles remained for analysis. Four main registration methods were identified: point registration, surface registration, hybrid registration, and computer vision-based registration. The mobility of the mandible is accounted for by either keeping the mandible in a fixed position during preoperative imaging and surgery, or by tracking the mandibular movements. Although different registration methods are available for navigated mandibular surgery, there is always a trade-off between accuracy, registration time, usability, and invasiveness. Future studies should focus on testing the different methods in larger patient studies and should report the registration accuracy.

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Purpose: To utilize navigated mandibular (reconstructive) surgery, accurate registration of the preoperative CT scan with the actual patient in the operating room (OR) is required. In this phantom study, the feasibility of a noninvasive hybrid registration method is assessed. This method consists of a point registration with anatomic landmarks for initialization and a surface registration using the bare mandibular bone surface for optimization. Methods: Three mandible phantoms with reference notches on two osteotomy planes were 3D printed. An electromagnetic tracking system in combination with 3D Slicer software was used for navigation. Different configurations, i.e., different surface point areas and number and configuration of surface points, were tested with a dentate phantom (A) in a metal-free environment. To simulate the intraoperative environment and different anatomies, the registration procedure was also performed with an OR bed using the dentate phantom and two (partially) edentulous phantoms with atypical anatomy (B and C). The accuracy of the registration was calculated using the notches on the osteotomy planes and was expressed as the target registration error (TRE). TRE values of less than 2.0 mm were considered as clinically acceptable. Results: In all experiments, the mean TRE was less than 2.0 mm. No differences were found using different surface point areas or number or configurations of surface points. Registration accuracy in the simulated intraoperative setting was—mean (SD)—0.96 (0.22), 0.93 (0.26), and 1.50 (0.28) mm for phantom A, phantom B, and phantom C. Conclusion: Hybrid registration is a noninvasive method that requires only a small area of the bare mandibular bone surface to obtain high accuracy in phantom setting. Future studies should test this method in clinical setting during actual surgery.

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Background and Objectives: There is a clinical need to assess the resection margins of tongue cancer specimens, intraoperatively. In the current ex vivo study, we evaluated the feasibility of hyperspectral diffuse reflectance imaging (HSI) for distinguishing tumor from the healthy tongue tissue. Study Design/Materials and Methods: Fresh surgical specimens (n = 14) of squamous cell carcinoma of the tongue were scanned with two hyperspectral cameras that cover the visible and near-infrared spectrum (400–1,700 nm). Each pixel of the hyperspectral image represents a measure of the diffuse optical reflectance. A neural network was used for tissue-type prediction of the hyperspectral images of the visual and near-infrared data sets separately as well as both data sets combined. Results: HSI was able to distinguish tumor from muscle with a good accuracy. The diagnostic performance of both wavelength ranges (sensitivity/specificity of visual and near-infrared were 84%/80% and 77%/77%, respectively) appears to be comparable and there is no additional benefit of combining the two wavelength ranges (sensitivity and specificity were 83%/76%). Conclusions: HSI has a strong potential for intra-operative assessment of tumor resection margins of squamous cell carcinoma of the tongue. This may optimize surgery, as the entire resection surface can be scanned in a single run and the results can be readily available. Lasers Surg. Med.@en

This ex-vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy tissue, with the aim to develop a technology that can assess resection margins for the presence of tumor cells during oral cavity cancer surgery. Diffuse reflectance spectra were acquired on fresh surgical specimens from 28 patients with oral cavity squamous cell carcinoma. The spectra (400 to 1600 nm) were detected after illuminating tissue with a source fiber at 0.3-, 0.7-, 1.0-, and 2.0-mm distances from a detection fiber, obtaining spectral information from different sampling depths. The spectra were correlated with histopathology. A total of 76 spectra were obtained from tumor tissue and 110 spectra from healthy muscle tissue. The first- and second-order derivatives of the spectra were calculated and a classification algorithm was developed using fivefold cross validation with a linear support vector machine. The best results were obtained by the reflectance measured with a 1-mm source-detector distance (sensitivity, specificity, and accuracy are 89%, 82%, and 86%, respectively). DRS can accurately discriminate tumor from healthy tissue in an ex-vivo setting using a 1-mm source-detector distance. Accurate validation methods are warranted for larger sampling depths to allow for guidance during oral cavity cancer excision.

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