Cleared Traditional

K212783 - ProstatID (FDA 510(k) Clearance)

Jul 2022
Decision
310d
Days
Class 2
Risk

K212783 is an FDA 510(k) clearance for the ProstatID. This device is classified as a Radiological Computer Assisted Detection/diagnosis Software For Lesions Suspicious For Cancer (Class II - Special Controls, product code QDQ).

Submitted by Scanmed, LLC (Omaha, US). The FDA issued a Cleared decision on July 8, 2022, 310 days after receiving the submission on September 1, 2021.

This device falls under the Radiology FDA review panel. Regulated under 21 CFR 892.2090. 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..

Submission Details

510(k) Number K212783 FDA.gov
FDA Decision Cleared Substantially Equivalent - Traditional 510(k) (SESE)
Date Received September 01, 2021
Decision Date July 08, 2022
Days to Decision 310 days
Submission Type Traditional
Review Panel Radiology (RA)
Summary Summary PDF

Device Classification

Product Code QDQ - Radiological Computer Assisted Detection/diagnosis Software For Lesions Suspicious For Cancer
Device Class Class II - Special Controls
CFR Regulation 21 CFR 892.2090
Definition 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.

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