Intraoperative tumor identification (extension/margins/metastases) via receptor-specific targeting is one of the ultimate promises of fluorescence-guided surgery. The translation of fluorescent tracers that enable tumor visualization forms a critical component in the realization of this approach. Ex vivo assessment of surgical specimens after topical tracer application could help provide an intermediate step between preclinical evaluation and first-in-human trials. Here, the suitability of the c-Met receptor as a potential surgical target in oral cavity cancer was explored via topical ex vivo application of the fluorescent tracer EMI-137. Freshly excised tumor specimens obtained from ten patients with squamous cell carcinoma of the tongue were incubated with EMI-137 and imaged with a clinical-grade Cy5 prototype fluorescence camera. In-house developed image processing software allowed video-rate assessment of the tumor-to-background ratio (TBR). Fluorescence imaging results were related to standard pathological evaluation and c-MET immunohistochemistry. After incubation with EMI-137, 9/10 tumors were fluorescently illuminated. Immunohistochemistry revealed c-Met expression in all ten specimens. Non-visualization could be linked to a more deeply situated lesion. Tumor assessment was improved via video representation of the TBR (median TBR: 2.5 (range 1.8–3.1)). Ex vivo evaluation of tumor specimens suggests that c-Met is a possible candidate for fluorescence-guided surgery in oral cavity cancer.

The aim of this study is to prove that facial surface electromyography (sEMG) conveys sufficient information to predict 3D lip shapes. High sEMG predictive accuracy implies we could train a neural control model for activation of biomechanical models by simultaneously recording sEMG signals and their associated motions. With a stereo camera set-up, we recorded 3D lip shapes and simultaneously performed sEMG measurements of the facial muscles, applying principal component analysis (PCA) and a modified general regression neural network (GRNN) to link the sEMG measurements to 3D lip shapes. To test reproducibility, we conducted our experiment on five volunteers, evaluating several sEMG features and window lengths in unipolar and bipolar configurations in search of the optimal settings for facial sEMG. The errors of the two methods were comparable. We managed to predict 3D lip shapes with a mean accuracy of 2.76 mm when using the PCA method and 2.78 mm when using modified GRNN. Whereas performance improved with shorter window lengths, feature type and configuration had little influence.

Oral cancer surgery has a negative influence on the quality of life (QOL). As a result of the complex physiology involved in oral functions, estimation of surgical effects on functionality remains difficult. We present a user-friendly biomechanical simulation of tongue surgery, including closure with suturing and scar formation, followed by an automated adaptation of a finite element (FE) model to the shape of the tongue. Different configurations of our FE model were evaluated and compared to a well-established FE model. We showed that the post-operative impairment as predicted by our model was qualitatively comparable to a patient case for five different tongue maneuvers.