Long-Term Evaluation of Recurrence after Photodynamic Therapy with Topical Methyl Aminolevulinate for Non-Melanoma Skin Cancer: a Hospital-Based Study

Introduction & Objectives: Several factors may influence the decision to pursue nonsurgical modalities for the treatment of non-melanoma skin cancer. Topical photodynamic therapy (PDT) is a non-invasive alternative treatment reported to have a high efficacy when using standardized protocols in Bowen’s disease (BD), superficial basal cell carcinoma (BCC) and in thin nodular BCC. However, long-term recurrence studies are lacking. The aim of this study was to evaluate the long-term efficacy of PDT with topical methylaminolevulinate (MAL) for the treatment of BD and BCC in a dermato-oncology department. Materials & Methods: All patients with the diagnosis of BD or BCC, treated with MAL-PDT from the years 2004 to 2008, were enrolled. Treatment protocol included two MAL-PDT sessions one week apart repeated at three months when incomplete response, using a red light dose of 37-40 J/cm2 and an exposure time of 8’20’’. Clinical records were retrospectively reviewed, and data regarding age, sex, tumour location, size, treatment outcomes and recurrence were registered. Descriptive analysis was performed using chi square tests, followed by survival analysis with the Kaplan-Meier and Cox regression models. Results: Sixty-eight patients (median age 71.0 years, P25;P75=30;92) with a total of 78 tumours (31 BD, 45 superficial BCC, 2 nodular BCC) and a median tumour size of 5 cm2 were treated. Overall, the median follow-up period was 43.5 months (P25;P75=0;100), and a total recurrence rate of 33.8% was observed (24.4 % for BCC vs. 45.2% for BD). Estimated recurrence rates for BCC and BD were 5.0% vs. 7.4% at 6 months, 23.4% vs. 27.9% at 12 months, and 30.0% vs. 72.4% at 60 months. Both age and diagnosis were independent prognostic factors for recurrence, with significantly higher estimated recurrence rates in patients with BD (p=0.0036) or younger than 58 years old (p=0.039). The risk of recurrence (hazard ratio) was 2.4 times higher in patients with BD compared to superficial BCC (95% CI:1.1-5.3; p=0.033), and 2.8 times higher in patients younger than 58 years old (95% CI:1.2-6.5; p=0.02). Conclusions: In the studied population, estimated recurrence rates are higher than those expected from available literature, possibly due to a longer follow-up period. To the authors’ knowledge there is only one other study with a similar follow-up period, regarding BCC solely. BD, as an in situ squamous cell carcinoma, has a higher tendency to recur than superficial BCC. Despite greater cosmesis, PDT might no be the best treatment option for young patients considering their higher risk of recurrence.

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Numerical Evaluation of Ventilation Performance in Children Day Care Centres

Modelling of ventilation is strongly dependent on the physical characteristics of the building of which precise evaluation is a complex and time consuming task. In the frame of a research project, two children day care centres (CDCC) have been selected in order to measure the envelope air permeability, the flow rate of mechanical ventilation systems and indoor and outdoor temperature. The data obtained was used as input to the computer code CONTAM for ventilation simulations. The results obtained were compared with direct measurements of ventilation flow from short term measurements with CO2 tracer gas and medium term measurements with perfluorocarbon tracer (PFT) gas decay method. After validation, in order to analyse the main parameters that affect ventilation, the model was used to predict the ventilation rates for a wide range of conditions. The purpose of this assessment was to find the best practices to improve natural ventilation. A simple analytical method to predict the ventilation flow rate of rooms is also presented. The method is based on the estimation of wind effect on the room through the evaluation of an average factor and on the assessment of relevant cross section of gaps and openings combined in series or in parallel. It is shown that it may be applied with acceptable accuracy for this type of buildings when ventilation is due essentially to wind action.