Photobiomodulation by a new optical fiber device: analysis of the in vitro impact on proliferation/migration of keratinocytes and squamous cell carcinomas cells stressed by X-rays.

Photobiomodulation-based (PBM-based) therapies show promising results in mucositis and dermatitis treatment by stimulating wound healing mechanisms such as cell proliferation and migration. The aim of the present study is to investigate the in vitro effects of CareMin650 on the proliferation and migration of two different types of cells, namely cancer and non-cancer cells, with or without X-ray radiation. Study design used PBM through a combination of 0-3-6 J/cm2 doses-with or without X-ray radiation-on the proliferation and migration capabilities of a keratinocyte cell line (HaCaT) and a squamous cell carcinoma line (SCC61). PBM is delivered by a new woven optical fiber device, namely CareMin650 prototype (light emission by LEDs (light-emitting diodes), peak at 660 nm, irradiance of 21.6 mW/cm2). The effectiveness of PBM to increase HaCaT proliferation and migration (with or without X-ray radiation) supports the capability of PBM to favor wound healing. It also highlights that PBM does not provide any anti-radiation effect to previously X-rays radiated SCC (p < 0.001). Such data supports the beneficial effect of PBM delivered by an optical fiber device to heal wounds, without promoting cancer development.

Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy.

Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clustering method is proposed to discriminate glioma margin. This is obtained from spectroscopic fluorescent measurements acquired with a recently introduced intraoperative set up. We describe a data-driven selection of best spectral features and show how this improves results of margin prediction from healthy tissue by comparison with the standard biomarker-based prediction. This pilot study based on 10 patients and 50 samples shows promising results with a best performance of 77% of accuracy in healthy tissue prediction from margin tissue.

Repetitive motion compensation for real time intraoperative video processing.

In this paper, we present a motion compensation algorithm dedicated to video processing during neurosurgery. After craniotomy, the brain surface undergoes a repetitive motion due to the cardiac pulsation. This motion as well as potential video camera motion prevent accurate video analysis. We propose a dedicated motion model where the brain deformation is described using a linear basis learned from a few initial frames of the video. As opposed to other works using linear basis for the flow, the camera motion is explicitly accounted in the transformation model. Despite the nonlinear nature of our model, all the motion parameters are robustly estimated all at once, using only one singular value decomposition (SVD), making our procedure computationally efficient. A Lagrangian specification of the flow field ensures the stability of the method. Experiments on in vivo data are presented to evaluate the capacity of the method to cope with occlusion or camera motion. The method we propose satisfies the intraoperative constraints: it is robust to surgical tools occlusions, it works in real time, and it is able to handle large camera viewpoint changes.

Intraoperative quantitative functional brain mapping using an RGB camera.

Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. However, it still lacks robustness to be used as a clinical standard. In particular, new biomarkers of brain functionality with improved sensitivity and specificity are needed. We present a method for the computation of hemodynamics-based functional brain maps using an RGB camera and a white light source. We measure the quantitative oxy and deoxyhemoglobin concentration changes in the human brain cortex with the modified Beer-Lambert law and Monte Carlo simulations. A functional model has been implemented to evaluate the functional brain areas following neuronal activation by physiological stimuli. The results show a good correlation between the computed quantitative functional maps and the brain areas localized by electrical brain stimulation (EBS). We demonstrate that an RGB camera combined with a quantitative modeling of brain hemodynamics biomarkers can evaluate in a robust way the functional areas during neurosurgery and serve as a tool of choice to complement EBS.

Nonlinear relation between concentration and fluorescence emission of protoporphyrin IX in calibrated phantoms.

5-ALA-induced protoporphyrin IX (PpIX) has shown its relevance in medical assisting techniques, notably in the detection of glioma (brain tumors). Validation of instruments on phantoms is mandatory and a standardization procedure has recently been proposed. This procedure yields phantoms recipes to realize a linear relationship between PpIX concentration and fluorescence emission intensity. The present study puts forward phantoms where this linear relationship cannot be used. We propose a model that considers two states of PpIX, corresponding to two different aggregates of PpIX, with fluorescence spectra peaking at 634 and 620 nm, respectively. We characterize the influence of these two states on PpIX fluorescence emission spectra in phantoms with steady concentration of PpIX and various microenvironment parameters (surfactant, Intralipid or bovine blood concentration, and pH). We show that, with fixed PpIX concentration, a modification of the microenvironment induces a variation of the emitted spectrum, notably a shift in its central wavelength. We show that this modification reveals a variation of proportions of the two states. This establishes phantom microenvironment regimes where the usual single state model is biased while a linear combination of the two spectra enables accurate recovering of any measured spectra.