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Session: Poster session I
Session starts: Thursday 24 January, 15:00

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Farzin Ghane Golmohamadi ()
Khalid Daoudi ()
Robert Takes ()
Ilse van Engen-vanGrunsven ()
Chris de Korte ()

Abstract:
The metastatic status of regional lymph nodes (LNs) is a significant prognostic factor in head and neck cancer patients. Therefore, in these patients, neck dissections are often part of the treatment and the presence of cancer cells is determined through pathological examination. However, this procedure is associated with significant morbidity. More accurate assessment of the metastatic status of the regional lymph nodes would allow for more selective treatment. In this study, we investigated the feasibility of a fast method to identify metastatic lymph nodes ex vivo based on photoacoustic (PA) and high-frequency ultrasound (US) imaging for patients suffering from head and neck cancer. First, we collected freshly dissected LNs from the pathology department, and subsequently, we performed 2D PA and US imaging in random cross-section through the LNs using a PA imaging system with laser wavelength ranging from 670-980nm. Subsequently, we carried out conventional histopathological analysis on the LNs. We select a region of interest (ROI) for each PA and US image and then proceed to quantitative analysis (QA) [1, 2]. The mean and variance were extracted from 2D PA and US images, and next the slope, intercept and midband obtained from the 2D PA spectral analysis was determined. Results showed two distinctive sets of values for the reactive and metastatic LNs (Mann–Whitney U-test, p<0.05) for all QA parameters. Furthermore, we implemented logistic regression to classify LNs as metastatic or reactive for each QA parameter. Our preliminary results reveal that PA and US imaging have potential to facilitate differentiation between reactive and metastatic LNs based on absorption and tissue microstructure. This work shows that ultrasound and photoacoustic spectral imaging can be a promising tool in assisting surgeons to preoperative diagnosis. [1] Xu, G., et al. (2014). "The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis." Radiology 271(1): 248-254. [2] Wang, T., et al. (2013). "Characterization of ovarian tissue based on quantitative analysis of photoacoustic microscopy images." Biomedical optics express 4(12): 2763-2768.