Eugenio Martinelli

An investigation on electronic nose diagnosis of lung cancer

The use of gas sensor arrays as medical diagnosis instruments has been proposed several years ago. Since then, the idea has been proven for a limited number of diseases. The case of lung cancer is particularly interesting because it is supported by studies that have shown the correlation between the composition of breath and the disease. However, it is known that many other diseases can alter the breath composition, so for lung cancer diagnosis it is necessary not only to detect generic alterations but those specifically consequent to cancer. In this paper an experiment, performed in the bronchoscopy unit of a large hospital, aimed at discriminating between lung cancer, diverse lung diseases and reference controls is illustrated. Results show not only a satisfactory identification rate of lung cancer subjects but also a non-negligible sensitivity to breath modification induced by other affections. Furthermore, the effects of some compounds frequently found in the breath of lung cancer subjects have also been studied. Results indicate that breath samples of control individuals drift towards the lung cancer group when added with either single or mixtures of these alleged cancer-related compounds.

Diagnostic Performance of an Electronic Nose, Fractional Exhaled Nitric Oxide, and Lung Function Testing in Asthma

BACKGROUND Analysis of exhaled breath by biosensors discriminates between patients with asthma and healthy subjects. An electronic nose consists of a chemical sensor array for the detection of volatile organic compounds (VOCs) and an algorithm for pattern recognition. We compared the diagnostic performance of a prototype of an electronic nose with lung function tests and fractional exhaled nitric oxide (FENO) in patients with atopic asthma. METHODS A cross-sectional study was undertaken in 27 patients with intermittent and persistent mild asthma and in 24 healthy subjects. Two procedures for collecting exhaled breath were followed to study the differences between total and alveolar air. Seven patients with asthma and seven healthy subjects participated in a study with mass spectrometry (MS) fingerprinting as an independent technique for assessing between group discrimination. Classification was based on principal component analysis and a feed-forward neural network. RESULTS The best results were obtained when the electronic nose analysis was performed on alveolar air. Diagnostic performance for electronic nose, FENO, and lung function testing was 87.5%, 79.2%, and 70.8%, respectively. The combination of electronic nose and FENO had the highest diagnostic performance for asthma (95.8%). MS fingerprints of VOCs could discriminate between patients with asthma and healthy subjects. CONCLUSIONS The electronic nose has a high diagnostic performance that can be increased when combined with FENO. Large studies are now required to definitively establish the diagnostic performance of the electronic nose. Whether this integrated noninvasive approach will translate into an early diagnosis of asthma has to be clarified. TRIAL REGISTRATION EUDRACT https://eudralink.emea.europa.eu; Identifier: 2007-000890-51; and clinicaltrials.gov; Identifier: NCT00819676.

Solid-state gas sensors for breath analysis: A review

The analysis of volatile compounds is an efficient method to appraise information about the chemical composition of liquids and solids. This principle is applied to several practical applications, such as food analysis where many important features (e.g. freshness) can be directly inferred from the analysis of volatile compounds. The same approach can also be applied to a human body where the volatile compounds, collected from the skin, the breath or in the headspace of fluids, might contain information that could be used to diagnose several kinds of diseases. In particular, breath is widely studied and many diseases can be potentially detected from breath analysis. The most fascinating property of breath analysis is the non-invasiveness of the sample collection. Solid-state sensors are considered the natural complement to breath analysis, matching the non-invasiveness with typical sensor features such as low-cost, easiness of use, portability, and the integration with the information networks. Sensors based breath analysis is then expected to dramatically extend the diagnostic capabilities enabling the screening of large populations for the early diagnosis of pathologies. In the last years there has been an increased attention to the development of sensors specifically aimed to this purpose. These investigations involve both specific sensors designed to detect individual compounds and non-specific sensors, operated in array configurations, aimed at clustering subjects according to their health conditions. In this paper, the recent significant applications of these sensors to breath analysis are reviewed and discussed.

The evaluation of quality of post-harvest oranges and apples by means of an electronic nose

Abstract The measure of quality of post-harvest fruits is considered a promising application field for electronic nose technology such as the detection of defects. Among the possible defects present in fruits those due to post-harvest treatment are particularly important. Among them defects like mealiness (due to post-harvest over-ripening), skin damage (due to mechanical or temperature stresses), and infections affect strongly the perception of consumers. They have to be avoided in order to achieve high quality products. In this paper, the study of the variations of aroma of oranges, during the storage, and apples, due to the presence of mealiness and skin damage by means of a thickness shear mode quartz resonators- (TSMR) based electronic nose, is illustrated and discussed. Results have evidenced that the electronic nose has enough sensitivity and resolution to distinguish among the various classes and to correctly predict the amount of defects (for apples) and storage days (for oranges).

Comparison and integration of different electronic noses for freshness evaluation of cod-fish fillets

Abstract For the instrumental analysis of fish freshness, several different methods have been proposed based on different principles (such as mechanical, electrical, and optical). Although, it is well-known that the headspace composition changes greatly during the spoilage process, the difficulties in sampling and measuring the headspaces with traditional analytical chemistry techniques makes the practical implementation of this principle not viable. Recently, the advent of sensor array technology has given the possibility to reconsider the headspace variation for instrumental applications. In this paper the use of measurements of two electronic noses, based on different sensor technologies and sampling methodologies, to detect freshness of cod-fish fillets is illustrated and discussed. Over a period of 17 storage days, the two sensor systems have shown different resolution, while the combination of them achieves the best performances allowing an almost complete evaluation of the freshness of samples. Trimethylamine (TMA) and total volatile basic nitrogen, measured with conventional techniques, show a non-monotonic behaviour, that induces the possibility of large errors in freshness estimation, as shown by the electronic noses.

Counteraction of environmental disturbances of electronic nose data by independent component analysis

Abstract Electronic nose data are usually affected by several disturbances in part due to the non-idealities of sensors and in part due to the effects of the environment as far as the composition of the gaseous sample is concerned. In some practical applications, the sample cannot be completely insulated from the surrounding environment and its drift (due to temperature and relative humidity changes) may be so large to completely dim the intrinsic resolution of the sensor array. The problem could be solved at data analysis level making some assumptions on the nature of the disturbances. In this paper, the independent component analysis (ICA) method will be illustrated and used to segregate the environmental disturbances from the meaningful part of the data. The method is tested on a practical and simple experiment aimed at distinguishing two classes of fruits measured for 1 week at different room temperatures and relative humidity. The application of ICA results in a meaningful improvement of the classification. The application of ICA gives new insights in the comprehension of the working mechanisms of electronic nose systems. Connections between ICA and electronic nose will also be discussed in the paper.

Direct and two-stage data analysis procedures based on PCA, PLS-DA and ANN for ISE-based electronic tongue—Effect of supervised feature extraction

A novel strategy of data analysis for artificial taste and odour systems is presented in this work. It is demonstrated that using a supervised method also in feature extraction phase enhances fruit juice classification capability of sensor array developed at Warsaw University of Technology. Comparison of direct processing (raw data processed by Artificial Neural Network (ANN), raw data processed by Partial Least Squares-Discriminant Analysis (PLS-DA)) and two-stage processing (Principal Components Analysis (PCA) outputs processed by ANN, PLS-DA outputs processed by ANN) is presented. It is shown that considerable increase of classification capability occurred in the case of the new method proposed by the authors.

Identification of melanoma with a gas sensor array.

Background/purpose: The relationship between diseases and alterations of the airborne chemicals emitted from the body has been found in many different pathologies and in particular for various forms of cancer. Metabolism of cancer cells is greatly altered during their lifetime; then, modification of chemicals is supposed to be large around cancer tissues. Positive hints in this direction were provided, as an example, on studying the breath composition of lung cancer‐affected subjects. Besides the conventional analytical approaches, in recent years sensor arrays were also applied to these researches considering the chemical composition changes as those occurring in other applications such as for instance, those dealing with food quality measurements.

Electronic nose based investigation of the sensorial properties of peaches and nectarines

Abstract Quality of fruit is traditionally associated with the physical characteristics, such as surface colour, shape, and firmness. Although, it is well known that the aroma is also associated with the ripening processes, this feature never resulted in any practical instrumentation due to the complexity of the aroma analysis. Over the past years, electronic nose technology opened the possibility to exploit information on aroma to assess fruit ripening stage, and more generally, fruit quality. In order to match the instrumental analysis with the consumer requirements, a sensorial profile of the fruit is necessary. From the point of view of sensory analysis, fruits have not been extensively studied and a complete and detailed description of the aroma components is not well established. In this paper, an electronic nose and a sensory panel are considered together in order to study the sensorial properties of a number of peaches and nectarines. Fruits were divided into four classes; each composed of several cultivars. The research is aimed at evaluating the sensorial features typical of each class. This work represents a first attempt toward the definition of a sensorial profile for these fruits, and it can be considered a further proof of the fruitful interactions between natural olfaction and electronic nose.

Feature Extraction of chemical sensors in phase space

In this paper a sensor phase space is introduced and the analysis of trajectories in this space is proposed as a method to evaluate the sensor response. The phase space gives the opportunity to introduce a novel feature describing the area spanned by the trajectory during adsorption and/or desorption of chemicals from the sensor. A comparison with the usual features resulted in a better accuracy and a shortest measurement time.