Cleared Traditional

K210670 - BU-CAD (FDA 510(k) Clearance)

Dec 2021
Decision
291d
Days
Class 2
Risk

K210670 is an FDA 510(k) clearance for the BU-CAD. 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 Taihao Medical, Inc. (Taipei, TW). The FDA issued a Cleared decision on December 21, 2021, 291 days after receiving the submission on March 5, 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 K210670 FDA.gov
FDA Decision Cleared Substantially Equivalent - Traditional 510(k) (SESE)
Date Received March 05, 2021
Decision Date December 21, 2021
Days to Decision 291 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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