PurposeHyperspectral imaging shows promise for surgical applications to non-invasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable and so are unsuitable for surgical environments. We demonstrate the necessity for in situ white references and address this by proposing a novel, sterile, synthetic reference construction algorithm.ApproachThe use of references obtained at different distances and lighting conditions to the subject were examined. Spectral and color reconstructions were compared with standard measurements qualitatively and quantitatively, using ΔE and normalized RMSE, respectively. The algorithm forms a composite image from a video of a standard sterile ruler, whose imperfect reflectivity is compensated for. The reference is modeled as the product of independent spatial and spectral components, and a scalar factor accounting for gain, exposure, and light intensity. Evaluation of synthetic references against ideal but non-sterile references is performed using the same metrics alongside pixel-by-pixel errors. Finally, intraoperative integration is assessed though cadaveric experiments.ResultsImproper white balancing leads to increases in all quantitative and qualitative errors. Synthetic references achieve median pixel-by-pixel errors lower than 6.5% and produce similar reconstructions and errors to an ideal reference. The algorithm integrated well into surgical workflow, achieving median pixel-by-pixel errors of 4.77% while maintaining good spectral and color reconstruction.ConclusionsWe demonstrate the importance of in situ white referencing and present a novel synthetic referencing algorithm. This algorithm is suitable for surgery while maintaining the quality of classical data reconstruction.
Emerging optical imaging techniques such as hyperspectral imaging (HSI) provide a promising non-invasive solution for intraoperative tissue characterisation with the potential to provide rich tissue-differentiation information over the entire surgical field. Neuro-oncology surgery would especially benefit from detailed real-time in vivo tissue characterisation, improving the accuracy with which boundaries of safe surgical resection are delineated and thereby improving patient outcomes. Current systems are limited by challenges with processing the HSI data because of incomplete characterisation of the optical properties of tissue across the complete visible and near-infrared wavelength spectrum. In this study, we characterised the optical properties of various freshly-excised brain tumours and normal cadaveric human brain tissue using a dual-beam integrating sphere spectrophotometer and the inverse adding-doubling technique. We adapted an integrating sphere to analyse 2 mm-thick tissue samples measuring 4 – 7 mm in diameter and validated the experimental setup with a tissue-mimicking optical phantom. We investigated the different spectral signatures of freshly-excised tumour tissues including pituitary adenoma, meningioma and vestibular schwannoma and compared these to normal grey and white matter, pons, pituitary, dura and cranial nerve tissues across the wavelength range of 400 – 1800 nm. It was found that brain and tumour tissues could be differentiated by their optical properties but the freezing process did alter the tissues’ relative absorption and reduced scattering coefficients. In this work, we have demonstrated a method to characterise the optical properties of small human brain and tumour specimens that may be used as a reference dataset for developing optical imaging techniques.
In high-grade glioma surgery, tumor resection is often guided by intraoperative fluorescence imaging. 5-aminolevulinic acid-induced protoporphyrin IX (PpIX) provides fluorescent contrast between normal brain tissue and glioma tissue, thus achieving improved tumor delineation and prolonged patient survival compared with conventional white-light-guided resection. However, commercially available fluorescence imaging systems rely solely on visual assessment of fluorescence patterns by the surgeon, which makes the resection more subjective than necessary. We developed a wide-field spectrally resolved fluorescence imaging system utilizing a Generation II scientific CMOS camera and an improved computational model for the precise reconstruction of the PpIX concentration map. In our model, the tissue’s optical properties and illumination geometry, which distort the fluorescent emission spectra, are considered. We demonstrate that the CMOS-based system can detect low PpIX concentration at short camera exposure times, while providing high-pixel resolution wide-field images. We show that total variation regularization improves the contrast-to-noise ratio of the reconstructed quantitative concentration map by approximately twofold. Quantitative comparison between the estimated PpIX concentration and tumor histopathology was also investigated to further evaluate the system.
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