SignificanceCerebrospinal fluid (CSF) rhinorrhea (leakage of brain fluid from the nose) can be difficult to identify and currently requires invasive procedures, such as intrathecal fluorescein, which requires a lumbar drain placement. Fluorescein is also known to have rare but significant side effects including seizures and death. As the number of endonasal skull base cases increases, the number of CSF leaks has also increased for which an alternative diagnostic method would be highly advantageous to patients.AimWe aim to develop an instrument to identify CSF leaks based on water absorption in the shortwave infrared (SWIR) without the need of intrathecal contrast agents. This device needed to be adapted to the anatomy of the human nasal cavity while maintaining low weight and ergonomic characteristics of current surgical instruments.ApproachAbsorption spectra of CSF and artificial CSF were obtained to characterize the absorption peaks that could be targeted with SWIR light. Different illumination systems were tested and refined prior to adapting them into a portable endoscope for testing in 3D-printed models and cadavers for feasibility.ResultsWe identified CSF to have an identical absorption profile as water. In our testing, a narrowband laser source at 1480 nm proved superior to using a broad 1450 nm LED. Using a SWIR enabling endoscope set up, we tested the ability to detect artificial CSF in a cadaver model.ConclusionsAn endoscopic system based on SWIR narrowband imaging can provide an alternative in the future to invasive methods of CSF leak detection.
Chronic-rhinosinusitis (CRS) is one of the most common conditions affecting ~14.2% (29.2-million) of US adults leading to estimated 18-22 million-physician office visits. It causes significant physical symptoms, negatively affects the quality-of-life and can substantially impair daily functioning. Various factors including microorganisms, allergies, and other inflammatory triggers play role in CRS. Lack of a universal marker and acknowledged difficulty in establishing the causes for the condition contributes to the poor treatment strategies and outcomes associated with CRS. Utilizing panel of sensitive markers associated with inflammatory responses in the nasal area can provide clinicians valuable information about the disease at the molecular level. The present study aims at identifying spectrochemical markers associated with the onset of CRS using data-driven Raman imaging. By combining high-resolution Raman imaging and machine learning we have developed a novel approach to obtain an integrated insight. Our findings are suggestive of differential changes in the biochemical composition of nasal tissues with CRS onset. A regression-based framework has been developed to link the inflammation score with spectral features. Support vector machine has been employed to explore the feasibility of classification. Successful recognition of these markers in nasal tissues will be helpful not only in designing automated diagnosis platforms but can also be used for identifying novel treatment strategies. Findings of this study will also serve as the foundation of our future research work on evaluating the applicability of nasal lavage for a minimally invasive method for objective CRS diagnosis.
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