DeepHealth ProstateAI
Quantib B.V. is listed for DeepHealth ProstateAI (K253682). The FDA list gives April 29, 2026 as the date of the final decision. The lead panel is Radiology, and the database link on the FDA list is the 510(k) pathway. openFDA describes product code QDQ as “Radiological Computer Assisted Detection/Diagnosis Software For Lesions Suspicious For Cancer”: A radiological computer assisted detection and diagnostic software for suspected lesions is an image processing device intended to aid in the detection, localization, and characterization of lesions suspicious for cancer on acquired medical images (e.g., mammography , MR, CT, ultrasound, radiography). The device detects, identifies and characterizes lesions suspicious for cancer based on features or information extracted from the images, and may provide information about the presence, location, and characteristics of the lesion to the user. Primary diagnostic and patient management decisions are made by the clinical user. openFDA records this submission’s decision description as “Substantially Equivalent.” This paragraph is assembled only from those public fields. It is not an FDA review, not a determination of safety or effectiveness, and not medical advice. Official record: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMN/pmn.cfm?ID=K253682
- Date of final decision
- April 29, 2026
- Company on the FDA list
- Quantib B.V.
- Lead panel
- Radiology
- Primary product code
- QDQ
- openFDA device name for the code
- Radiological Computer Assisted Detection/Diagnosis Software For Lesions Suspicious For Cancer
- Device class
- 2
- Regulation number
- 892.2090
- openFDA decision description
- Substantially Equivalent
- openFDA decision code
- SESE
- Statement or summary label
- Summary
Product-code text from openFDA
A radiological computer assisted detection and diagnostic software for suspected lesions is an image processing device intended to aid in the detection, localization, and characterization of lesions suspicious for cancer on acquired medical images (e.g., mammography , MR, CT, ultrasound, radiography). The device detects, identifies and characterizes lesions suspicious for cancer based on features or information extracted from the images, and may provide information about the presence, location, and characteristics of the lesion to the user. Primary diagnostic and patient management decisions are made by the clinical user.