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This study retrospectively included patients who underwent prostate magnetic resonance imaging (MRI) and subsequent ultrasound-guided prostate biopsy at Peking University First Hospital from January 2019 to December 2023, and prospectively enrolls patients from January 2024 to December 2029. Clinical information such as age, PSA levels, PI-RADS scores, and digital rectal examination findings are collected. A well-performing artificial intelligence model is employed to measure prostate volume, transitional zone volume, and lesion volume using MRI images. Furthermore, prostate-specific antigen density (PSAD), transitional zone-based prostate-specific antigen density (TZ-PSAD) and lesion-based prostate-specific antigen density (lesion-PSAD) are calculated using prostate volume, transitional zone volume and lesion volume. Utilizing the aforementioned data, machine learning predictive models for clinically-significant prostate cancer (csPCa) are developed and validated.
This study retrospectively included patients who underwent prostate magnetic resonance imaging (MRI) and subsequent ultrasound-guided prostate biopsy at Peking University First Hospital from January 2019 to December 2023, and prospectively enrolls patients from January 2024 to December 2029. Clinical information such as age, PSA levels, PI-RADS scores, and digital rectal examination findings are collected. A well-performing artificial intelligence model is employed to measure prostate volume, transitional zone volume, and lesion volume using MRI images. Furthermore, prostate-specific antigen density (PSAD), transitional zone-based prostate-specific antigen density (TZ-PSAD) and lesion-based prostate-specific antigen density (lesion-PSAD) are calculated using prostate volume, transitional zone volume and lesion volume. Utilizing the aforementioned data, machine learning predictive models for clinically-significant prostate cancer (csPCa) are developed and validated
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| cohort 1 | Cohort 1 comprises patients who underwent prostate magnetic resonance imaging (MRI) at Peking University First Hospital between January 2024 and December 2029, followed by an ultrasound-guided prostate biopsy. |
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| Measure | Description | Time Frame |
|---|---|---|
| Biopsy pathology results | The pathology report will include the ISUP grade; if it is greater than or equal to 2, it is considered csPCa (clinically significant prostate cancer), otherwise, it is classified as non-csPCa. | 1week after biopsy |
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Inclusion Criteria:
Exclusion Criteria:
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Patients who underwent prostate magnetic resonance imaging (MRI) at Peking University First Hospital between January 2024 and December 2029, followed by an ultrasound-guided prostate biopsy.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yi LIU | Contact | +8613611035261 | liuyipkuhsc@163.com | |
| Yi LIU | Contact | liuyipkuhsc@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Yi LIU | Dept. of Urology, Peking University First Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Peking University First Hospital | Recruiting | Beijing | 100034 | China |
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| ID | Term |
|---|---|
| D011471 | Prostatic Neoplasms |
| ID | Term |
|---|---|
| D005834 | Genital Neoplasms, Male |
| D014565 | Urogenital Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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| D005832 |
| Genital Diseases, Male |
| D000091662 | Genital Diseases |
| D000091642 | Urogenital Diseases |
| D011469 | Prostatic Diseases |
| D052801 | Male Urogenital Diseases |