A trained canine olfactory system can detect prostate cancer specific volatile organic compounds in urine samples with high estimated sensitivity and specificity. Further studies are needed to investigate the potential predictive value of this procedure to identify prostate cancer.

The electronic nose is able to provide useful information through the analysis of the volatile organic compounds in body fluids, such as exhaled breath, urine and blood. This paper focuses on the review of electronic nose studies and applications in the specific field of medical diagnostics based on the analysis of the gaseous headspace of human urine, in order to provide a broad overview of the state of the art and thus enhance future developments in this field. The research in this field is rather recent and still in progress, and there are several aspects that need to be investigated more into depth, not only to develop and improve specific electronic noses for different diseases, but also with the aim to discover and analyse the connections between specific diseases and the body fluids odour. Further research is needed to improve the results obtained up to now; the development of new sensors and data processing methods should lead to greater diagnostic accuracy thus making the electronic nose an effective tool for early detection of different kinds of diseases, ranging from infections to tumours or exposure to toxic agents.

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Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86–0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80–0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80–0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84–0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa.

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This is a multicentre evaluation of prospective databases in men with phi result and MRI-guided targeted and systematic prostate biopsy performed. The additional value of phi to pre-biopsy MRI Prostate Imaging Reporting & Data System(PIRADS) version 2 score was evaluated with multivariate analyses and Cstatistics(AUC). The proportion of unnecessary biopsies that can be avoided are estimated for csPCa(ISUP group !2 PCa).RESULTS: Among the whole cohort of 2014 men without prior PCa diagnosis, 1183 men had pre-biopsy phi results available. The median(interquartile range) age, PSA, Prostate volume(PV), MRI lesion size, highest PIRADS score, targeted and systematic biopsy cores were 67(62-71), 8.0(5.8-11.0)ng/mL, 50.0(36.9-68.0)ml, 11(7-15)mm, 4(3-4), 3(3-4) cores and 12(12-18) cores respectively. Abnormal digital rectal exam(DRE) and Prior negative biopsy was seen in in 20.8% and 36.6% men respectively. PCa and csPCa was diagnosed in 51.3%(607/1183) and 35.3%(417/1181) men. csPCa was diagnosed in 4.7%, 15.5%, 40.1% and 74.2% of PIRADS 2, 3, 4 and 5 lesions respectively. In multivariate analyses, independent predictors for csPCa detection (odd ratio OR, 95%CI) included age(1.06,1.03-1.08), phi(1.04,1.03-1.04), PV(0.97, 0.96-0.98), and PIRADS score(reference PIRADS 2) [PIRADS 3 (3.3, PIRADS 4(8.2, PIRADS 5(21.6,]. AUC of predictors for csPCa were shown in the Table . Using a 5-factor risk score for csPCa in men with PIRADS score 2 or 3, 36.9%(90% sensitivity) and 19.4%(95% sensitivity) biopsies could be avoided. Decision curve analyses showed the 5-factor risk score achieving the best net clinical benefit.CONCLUSIONS: Adding phi test to men with MRI prostate performed improved csPCa prediction, and further reduced unnecessary biopsies using multivariable risk models especially in PIRADS 2 and 3 lesions. The observed benefits were superior to adding PSA density to MRI prostate.