Prostate cancer (PCa) is the most common cancer and the second cause of cancer death among men. Current screening for PCa has low specificity and high false positive rates, resulting in patients’ overtreatment. Researchers have worked on the development of non-invasive and accurate diagnostic tools through the analysis of biological materials. The most promising results published up to now were obtained relying on trained dogs’ smell. However, trained dogs are not suitable for the development of a large-scale diagnostic tool, due for instance to dogs’ training costs and lack of compliance with hospital protocols. This research investigated the possibility to transfer those results to an instrumental method based on urine odour characterization by Electronic nose (EN). The project consisted of the critical analysis of literary studies regarding the EN application to the diagnostic field and the definition of an optimized experimental protocol for urine sample preparation, analysis and subsequent data processing. Given the heterogeneity of procedures proposed in literature, this study focused on the standardization of the experimental protocol. Several experiments involving different procedures for the preparation and the analysis of odorous samples were performed, identifying the possibility of analysing urine headspaces heated at fixed temperature. 89 participants were involved in the study. In total, 130 urine samples divided in two olfactory classes (i.e. Healthy and Sick) were analysed. The dataset relevant to those analyses was critically investigated, highlighting differences between classes, and then processed by Principal Component Analysis to visualize the discrimination achieved. The EN proved able not only to distinguish between Healthy and Sick samples, but also to stage the PCa. The performance of the test was evaluated in terms of sensitivity, specificity and accuracy. Values above 80% and 70% were achieved respectively for the healthy/sick classification and the PCa staging. These results must be considered extremely innovative, because no scientific publication up to now reports the possibility of staging PCa through a non-invasive and cheap analyses.
Il cancro prostatico (PCa) è il più diffuso tra gli uomini e la seconda causa di morte legata al cancro. La bassa specificità (30%) e l’elevato tasso di falsi positivi dello screening attuale comportano un eccessivo trattamento dei pazienti e incentivano l’interesse nello sviluppo di uno strumento diagnostico non invasivo e più accurato. I risultati più promettenti pubblicati fino ad ora sono stati ottenuti da cani addestrati attraverso l’analisi dell’odore delle urine. Tuttavia, i cani addestrati non sono adeguati per lo sviluppo di uno strumento diagnostico di larga scala, ad esempio per la non conformità con i protocolli ospedalieri. Pertanto, questa ricerca ha valutato la possibilità di definire un metodo strumentale basato sulla caratterizzazione dell’odore delle urine con il naso elettronico (EN). Le attività principali di questo studio sono state l’analisi critica degli studi di letteratura riguardanti l’applicazione del EN in campo diagnostico e la definizione di un protocollo sperimentale ottimizzato. Alla luce dell’eterogeneità delle procedure proposte in letteratura, questo studio si è focalizzato sulla standardizzazione del protocollo sperimentale. Differenti procedure sono state considerate per la preparazione e l’analisi dello spazio di testa delle urine, identificando la possibilità di analizzare spazi di testa ottenuti per riscaldamento del campione. In totale, sono stati analizzati 130 campioni forniti da 89 partecipanti e raggruppati in due classi olfattive (i.e. Sani e Malati). I dati ottenuti sono stati criticamente analizzati, evidenziando le differenze tra le classi, e processati con Analisi delle componenti principali (PCA) per visualizzare la discriminazione ottenuta. Il EN ha dimostrato la capacità di distinguere tra soggetti sani e malati e di operare una stadiazione della malattia. Specificità, sensitività e accuratezza superiori a 80% e 70% sono state ottenute rispettivamente per la diagnosi e la stadiazione del PCa. Questi risultati devono essere considerati altamente innovativi, in quanto nessuna pubblicazione scientifica riporta la possibilità di operare una stadiazione del cancro con un’analisi non invasiva ed economica.
Potentialities of the electronic nose as diagnostic tool for early prostate cancer detection
BAX, CARMEN
2016/2017
Abstract
Prostate cancer (PCa) is the most common cancer and the second cause of cancer death among men. Current screening for PCa has low specificity and high false positive rates, resulting in patients’ overtreatment. Researchers have worked on the development of non-invasive and accurate diagnostic tools through the analysis of biological materials. The most promising results published up to now were obtained relying on trained dogs’ smell. However, trained dogs are not suitable for the development of a large-scale diagnostic tool, due for instance to dogs’ training costs and lack of compliance with hospital protocols. This research investigated the possibility to transfer those results to an instrumental method based on urine odour characterization by Electronic nose (EN). The project consisted of the critical analysis of literary studies regarding the EN application to the diagnostic field and the definition of an optimized experimental protocol for urine sample preparation, analysis and subsequent data processing. Given the heterogeneity of procedures proposed in literature, this study focused on the standardization of the experimental protocol. Several experiments involving different procedures for the preparation and the analysis of odorous samples were performed, identifying the possibility of analysing urine headspaces heated at fixed temperature. 89 participants were involved in the study. In total, 130 urine samples divided in two olfactory classes (i.e. Healthy and Sick) were analysed. The dataset relevant to those analyses was critically investigated, highlighting differences between classes, and then processed by Principal Component Analysis to visualize the discrimination achieved. The EN proved able not only to distinguish between Healthy and Sick samples, but also to stage the PCa. The performance of the test was evaluated in terms of sensitivity, specificity and accuracy. Values above 80% and 70% were achieved respectively for the healthy/sick classification and the PCa staging. These results must be considered extremely innovative, because no scientific publication up to now reports the possibility of staging PCa through a non-invasive and cheap analyses.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/134982