To evaluate the possibility to properly discriminate between healthy bladder tissue and BCa with a multimodal fiber optic spectroscopy (MFOS) technique, in order to possibly introduce a more objective way to detect BCa, thus reducing inter-observer variability and maybe to determine urothelial carcinoma stage and grade with a comparable accuracy, specificity and sensibility of the current gold standard histopathological analysis

Observational single center study on human biological samples to evaluate the possibility to discriminate between healthy and tumor tissue on urothelial bladder samples. Aim of the study is to provide a fast, reliable and label free aid/alternative to current histopathology

Inclusion Criteria:

• willingness to participate,
• legal age,
• full capacity to sign informed consent
• eligibility for each surgical operation according to the best clinical practice and the urological guidelines

Exclusion Criteria:

• concomitant use of Hexaminolevulinate (Hexvix®)
• concomitant ongoing UTIs,
• concomitant bladder stone presence,
• recent catheterization or persistent bladder catheterization at time of surgery,
• concomitant presence of other pelvic cancer (both prostate, urethral, uterine),
• previous chemotherapy or radiotherapy of the pelvis,
• patient refusal at informed consent.

Patients are enrolled at hospitalization in our Urology Ward for surgical operation. Patients in surgical note for TURBT for bladder cancer or for Trans-Urethral Resection of Prostate (TURP) for Benign Prostatic Hyperplasia (BPH) are prospectively enrolled.

Age, history of bladder cancer, smoke habit and anamnesis are recorded before surgery. During time of bladder or prostate resection, freshly excised cold cup biopsies of both bladder cancer or healthy bladder mucosa are taken and sent for inspection through label-free multimodal fiber optic spectroscopy (MFOS) within 30 minutes.

Specimens are sent to standard histopathological analysis. MFOS data are then compared to current gold standard methodology in order to develop a classification algorithm based on the spectral information provided by each technique.