In an attempt to overcome the subjectiveness of clinical observation in the diagnosis of cutaneous melanoma, a computerized method is proposed. Reflectance images of 237 pigmented lesions (67 melanomas and 170 non-melanomas) were analysed using a telespectrophotometric technique. This device consists of a CCD camera with 17 interference filters. Images were acquired at selected wavelengths, from 420 to 1040 nm. Morphological and reflectance related parameters were extracted from the wavelength-dependent images of the lesions. The most significant features in the comparison between benign and malignant lesions were: lesion dimension (P < 10(-8) at 578 nm); mean value (P < 10(-7) at 940 nm) and standard deviation (P < 10(-4) at 904 nm) of lesion reflectance; lesion roundness (P < 10(-5) at 461 nm); and border irregularity (P < 10(-4) at 461 nm). Based on these parameters, a discriminant function between the two populations of lesions (naevi and melanomas) was obtained. By using the results of the analysis of the recruited lesions as 'training data', discriminant functions enabled the assignment of a score, or a 'risk probability', to each studied lesion. By imposing a sensitivity of 80% (a figure that mimics the diagnostic capability of an experienced clinician), entering or not entering the lesion dimension as input data in the discriminant analysis led to a specificity of 51% or 46% respectively. The high number of false-positive cases, which is a consequence of the selection criteria of the lesions, is, at present, the major limitation of the current technique. Nevertheless, our results suggest that an imaging-based computer-assisted device could be capable of discriminating malignant lesions mainly by evaluation of reflectance, especially in the infrared region, and shape properties. The dimension of a lesion should not be essential in the diagnosis of melanoma and, in our opinion, small melanomas should be recognized by a computer system as well as they are on clinical grounds.

The proposed technique allows to produce a stable and reproducible phantom, with accurately predictable optical properties, easy to make and to handle. This phantom is a useful tool for numerous applications involving light interaction with biologic tissue.

Cytokines may influence brain activities especially during stressful conditions, and elevated levels of IL-6 and C-reactive protein have been pointed out in subjects with Major Depression. If pro-inflammatory cytokines play a causative role in major depressive disorders, one would expect that antidepressants may down-regulate these cytokines or interfere with their actions, leading to improvement of depressive symptoms. Accumulating evidence has been published that antidepressants modulate cytokine production and this is particularly true for Tricyclics and Selective serotonin reuptake inhibitors (SSRIs), but the influence of newer antidepressants acting on both serotonin (5-HT) and norepinephrine (NE) such as venlafaxine, duloxetine and mirtazapine on cytokine levels has not been extensively studied. However, both pre-clinical and clinical studies examined in this review have demonstrated that newer serotonin-noradrenalin antidepressants can inhibit the production and/or release of pro-inflammatory cytokines and stimulate the production of anti-inflammatory cytokines, suggesting that reductions in inflammation might contribute to treatment response. Moreover, the results of the present review support the notion that the serotonin-noradrenalin antidepressants venlafaxine and mirtazapine may influence cytokine secretion in patients affected by MD, restoring the equilibrium between their physiological and pathological levels and leading to recovery. To date, no studies have evaluated the effect of duloxetine, the newest serotonin-noradrenalin antidepressant, on cytokine levels and therefore this should be evaluated in future studies.

The propagation of light emitted by a linear light diffuser in a cylindrical hollow organ was investigated by means of the Monte Carlo (MC) method. The height and radius of the cavity, scattering (mu(s)) (or reduced scattering, mu'(s)) and absorption (mu(a)) coefficients, anisotropy (g), and refractive indices of the media involved (n1, n2) are required as input data by the MC code, as are characteristics of the light diffuser (length, delivered power and emission profile). Results of our MC model were tested by measuring the light fluence rate in a tissue-simulating phantom (mu(a) = 0.5 cm(-1), mu(s) = 23 cm(-1) and g = 0.75) irradiated at 633 nm with a cylindrical diffuser. Since geometric and optical parameters determine the behaviour of light propagation in tissue, MC simulations with different sets of input parameters were carried out to provide qualitative as well as quantitative data useful in planning photodynamic therapy. Data are reported on light penetration and fluence rate build-up at mu(a) and mu'(s) values ranging between 0.1 and 5 cm(-1) and 2.5 and 50 cm(-1), respectively. Furthermore, results suggest that a shift and spread could occur in the isofluence curves along the symmetry axis, which depend on the diameter of the treated lumen as well as on the emission profile of the light diffuser. Using our data it is possible to estimate how inaccuracy in knowledge of the optical coefficients can affect (i.e. usually by increasing) the light dose scheduled at a certain depth into tissue.

Our preliminary results suggested that image analysis performed on hue and saturation-derived and red green and blue-derived data could better discriminate melanoma from nevi than separately using the two color representation models.