Olfactory cleft opacity and CT score are predictive factors of smell recovery after surgery in nasal polyposis.

OBJECTIVES: To assess subjective improvement of olfactory function following endoscopic sinus surgery (ESS) in chronic rhinosinusitis associated with nasal polyps (CRSwNP) and to analyse factors of recovery with the European Test of Olfactory Capabilities (ETOC). METHODS: We carried out a prospective study of 30 patients with CRSwNP from November 2011 to April 2013. The ETOC was filled the day before surgery and in the short term follow-up. Sixteen suprathreshold odorants with a detection task and a forced choice verbal identification task were tested. RESULTS: The mean composite score (MCS) improved at 3 and 6 months. The preoperative MCS was correlated to the Lund-Mackay score and to the olfactory cleft opacification on preoperative computed tomography (CT) scan. Multivariate linear regression modelling of patients with preoperative anosmia showed that the olfactory recovery at 3 months was predicted by the preoperative Lund-Mackay score and the age, and at 6 months by the preoperative Lund-Mackay score. CONCLUSION: With a convenient psychophysical test, we showed that olfactory cleft opacification and CT scan score could be predictive factors of olfaction disorder severity and improvement after ESS in CRSwNP. These results need to be strengthened in the long term with a larger panel of patients.

Quantization effects in digitally behaving circuit implementations of Kohonen networks.

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.