"The Feasibility of a Multimodal Spectroscopy Analysis to Detect Urothelial Cancer in Urine"
"The Feasibility of a Multimodal Spectroscopy Analysis to Detect Urothelial Cancer in Urine"
To facilitate the follow-up of urothelial tumors and also make them more tolerable and less invasive for patients, there is a minimally invasive and easy to perform examination which is urinary cytology on 3 samples. This test is extremely specific, over 90% chance of cancer if it is positive and is performed by expert cytopathologists, but it is burdened by a very low sensitivity, which is especially acute in the case of low grade tumors. This makes it an extremely useful test in case of positivity, but of little use if negative or doubtful, not being able to consider it reliable.
To overcome this problem, our study aims to bring an approach based on a physical principle, that is spectroscopy, which is fast non-invasive and does not require the use of additional substances or contrast media in the diagnosis of urothelial neoplasms in samples of urine.
In our experience, multimodal optical fiber spectroscopy has proved extremely valid in discriminating healthy urothelial tissue from tumor ex vivo, as well as providing important information on the degree of urothelial neoplasia, with accuracy rates higher than 80%, for which developed the idea of a technique based on multimodal spectroscopy.
If our method proves valid, it could improve the follow up and management of patients with urothelial cancer, being able to support normal cytology and provide further support to the cytopathologist, as well as simplify the diagnosis.
CASES Inclusion criteria
Patients over the age of 18 who are known for urological interventions for the following pathologies will be considered for enrollment in the group of cases:
The exclusion criteria will be:
CHECKS Inclusion criteria
Patients over the age of 18 who are known for urological interventions for the following pathologies will be considered for enrollment in the control group:
The exclusion criteria will be:
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silvia.benemei@unifi.it