Background
Evaluate imaging photoplethysmography (iPPG) as a novel noninvasive technique to assess flap perfusion in head and neck free flap reconstructive (FFR) surgeries.

Methods
Intraoperative iPPG was performed in 17 patients undergoing FFR surgery. Imaging consisted of a 30-s video from which perfusion maps were extracted, providing detailed information about blood flow and pulsatility in the flap microvasculature. During each procedure, iPPG acquisitions were acquired representing distinct perfusion conditions of the flap (fully perfused/ischemic/reperfused). When possible, postoperative measurements were performed to assess flap recovery during the critical time period (3 days) and long-term follow-up (30 days).

Results
Perfusion maps, displaying iPPG amplitude and delay times, correlated strongly (p < 0.001) with the perfusion status of the tissue. One case of postoperative thrombosis, leading to flap failure, was identified with iPPG. After surgical revision in this case, flap perfusion was restored and confirmed by iPPG. Postoperative follow-up imaging allowed for objective visualization of flap recovery short term (3 days) and up to 30 days after the surgical procedure.

Conclusions
This study shows that iPPG is suitable for objective and noninvasive assessment of flap perfusion in head and neck FFR surgery. In addition, postoperative monitoring shows potential for assessing flap perfusion in patients with increased risk of postoperative complications.@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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