This is a prospective clinical study recruiting 510 men at risk of PCa to undergo urine, blood, AI-assisted ultrasound and AI-assisted MRI investigations to stratify risk of clinically significant PCa (csPCa). (sample size calculation in section 5)
All recruited patients will undergo investigations including urine for spermine, blood for miRNA, TRUS, and MRI prostate. Patients with high suspicion of csPCa in any one step (urine, blood, ultrasound, OR MRI) will be offered an image-guided prostate biopsy. This will be followed by machine learning techniques to find the best combination in predicting csPCa.
Study Type
OBSERVATIONAL
Enrollment
510
All recruited patients will undergo investigations including urine for spermine, blood for miRNA, TRUS, and MRI prostate. Patients with high suspicion of Clinically significant prostate cancer in any one step (urine, blood, ultrasound, OR MRI) will be offered an image-guided prostate biopsy.
Prince of Wales Hospital, Chinese University of Hong Kong
Hong Kong, Hong Kong
RECRUITINGDiagnosis of clinically significant Prostate cancer (csPCa); • csPCa is diagnosis of ISUP Grade group ≥2 prostate cancer in at least 1 biopsy core
Assessed by by machine learning algorithms utilizing clinical parameters, novel biomarkers and AI-assisted imaging
Time frame: Through study completion, an average of 1 year
Diagnosis of any grade of prostate cancer
Assessed by prostate biopsy
Time frame: Through study completion, an average of 1 year
Proportion of men with diagnosis of clinically insignificant prostate cancer
Assessed by prostate biopsy
Time frame: Through study completion, an average of 1 year
Prostate biopsies that can be avoided
Assessed by using different machine learning algorithms
Time frame: Through study completion, an average of 1 year
The concordance of AI-assisted TRUS & MRI diagnosis and biopsy outcomes
Assessed by using different machine learning algorithms and prostate biopsy result
Time frame: Through study completion, an average of 1 year
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