A spectroscopic imaging device to study brain activation, without any scan nor contact, is under construction. The entire
instrument will be assembled in a unique setup and will use light emitted by picosecond laser diodes, a frontal light
distributor and a time-gated intensified camera. The instrument is controlled by an FPGA based module which generates
the pulse sequences for laser diodes and for the photocathode of the micro-channel-plate intensifier, and for the trigger of
the CCD camera. A time resolved 3D simulation study, using the Finite Element Method, was performed in order to
evaluate the proposed method for brain activation imaging. It is based on the widely used Brainweb digital brain
phantom, where the tissues of the whole head were distributed into 10 classes, for which optical absorption and
scattering coefficients were determined accordingly to the literature. Simulation data were calibrated thanks to timeresolved
experiments and results will be presented with special attention on the sensitivity and accuracy for detection of
optical absorption changes due to brain activation.
Spatially-resolved bimodal spectroscopy (multiple AutoFluorescence AF excitation and Diffuse Reflectance DR), was
used in vivo to discriminate various healthy and precancerous skin stages in a pre-clinical model (UV-irradiated mouse):
Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A specific data preprocessing scheme was
applied to intensity spectra (filtering, spectral correction and intensity normalization), and several sets of spectral
characteristics were automatically extracted and selected based on their discrimination power, statistically tested for
every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was
performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic
performance of each method. Diagnostic performance was studied and assessed in terms of Sensibility (Se) and
Specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibres distances and of the
numbers of principal components, such that: Se and Sp ≈ 100% when discriminating CH vs. others; Sp ≈ 100% and Se >
95% when discriminating Healthy vs. AH or D; Sp ≈ 74% and Se ≈ 63% for AH vs. D.
Histopathological analysis and in vivo optical spectroscopy were used to discriminate several histological stages of UV-irradiated mouse skin. At different times throughout the 30-week irradiation, autofluorescence (AF) and diffuse reflectance (DR) spectra were acquired in a bimodal approach. Then skin was sampled and processed to be classified, according to morphological criteria, into four histological categories: normal, and three types of hyperplasia (compensatory, atypical, and dysplastic). After extracting spectral characteristics, principal component analysis (data reduction) and the k-nearest neighbor classifying method were applied to compare diagnostic performances of monoexcitation AF (based on each of the seven excitation wavelengths: 360, 368, 390, 400, 410, 420, and 430 nm), multiexcitation AF (combining the seven excitation wavelengths), DR, and bimodal spectroscopies. Visible wavelengths are the most sensitive ones to discriminate compensatory from precancerous (atypical and dysplastic) states. Multiexcitation AF provides an average 6-percentage-point increased sensitivity compared to the best scores obtained with monoexcitation AF for all pairs of tissue categories. Bimodality results in a 4-percentage-point increase of specificity when discriminating the three types of hyperplasia. Thus, bimodal spectroscopy appears to be a promising tool to discriminate benign from precancerous stages; clinical investigations should be carried out to confirm these results.
Skin cancer full resection implies an evaluation of safety margins around the visible tumour. For melanomas such
margins are proportional to tumour's thickness also known as "Breslow Index". In order to see if Diffuse Reflectance
Spectroscopy (DRS) could be used to non-invasively evaluate Breslow Index, an in vitro study as well as numerical
simulations were performed. Bilayered phantoms were made : a lower layer mimicking dermis underneath an absorbing
layer mimicking a melanoma. Five groups of phantoms each having a specific top layer's thickness were made : 2, 3, 4, 5
or 6 mm. For wavelengths longer than 600 nm, Diffuse Reflectance spectra were significantly different (p<0.05) for each
thickness at every Collecting to Excitation Fibre Separations (CEFS) : 271, 536, 834, 1076 and 1341 &mgr;m. Monte Carlo
simulations were performed to check if DRS could detect smaller (i.e. 0.5 mm) thickness variations. Both experimental
and numerical results showed the DR signal intensity linearly (R2>0.9) decreases as CEFS increases. The thicker the
melanic layer was the smaller the slope (absolute value) was. These in vitro results will help setting up a clinical trial to
non invasively evaluate Breslow Index : the bandwidth should be the NIR one (wavelengths longer than 600 nm) and
CEFS should be shorter than 1 mm. Calibration will have to be made in order to relate slope to Breslow Index.
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