QP-Prostate is a medical imaging software that supports radiologists in the detection of clinically significant prostate cancer. It provides automatic lesion detection and risk scoring (High and Moderate) for the presence of csPCa. It also provides quantitative information, including prostate volume and dimensions, Apparent Diffusion Coefficient (ADC) map, computed high b-value and perfusion metrics (K trans, K ep, V e).
The information is compiled by the radiologist in a prostate structured report template based on PI-RADS guidelines.
Information source: Vendor
Last updated: Jan. 30, 2024

General Information

Product name QP-Prostate
Company Quibim
Subspeciality Abdomen
Modality MR
Disease targeted Prostate Cancer
Key-features Lesion detection, prostate segmentation, PI-RADS 2.1 structured report
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps)

Technical Specifications

Data characteristics
Population Male adult population. Exclusion: patients with endorectal coil, radical prostatectomy or hip prosthesis.
Input T2w, DWI sequence, DCE (not needed for lesion detection)
Input format DICOM
Output Lesion detection overlay, prostate segmentation overlay, quantitative information (ADC, high b-value, Ktrans, Kep, Ve), structured report based on PI-RADS 2.1
Output format DICOM SC
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased
Deployment Cloud-based
Trigger for analysis Automatically, right after the image acquisition
Processing time 1 - 10 minutes


Certified, Class IIb , MDR
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE) Medical imaging processing application intended for image processing and analysis of prostate MRI indicated for adult patients


Market presence
On market since CE/UKCA 10-2022. 510(k) clearance since 12-2020.
Distribution channels Philips Healthcare
Countries present (clinical, non-research use) 10
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Subscription
Based on Number of analyses


Peer reviewed papers on performance

  • Automated prostate multi-regional segmentation in magnetic resonance using fully convolutional neural networks (read)

Non-peer reviewed papers on performance
Other relevant papers

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