Company: QTIWW
Filing Date: 2025-11-03
Form Type: S-1
Source: 0001628280-25-048373
Chunk: 166

Company: QT IMAGING HOLDINGS, INC.
Filing Date: 2025-11-03
Form: S-1
Chunk 166
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 QT Breast Scanner (formerly, QT Ultrasound Breast Scanner) pursuant to AAMI ES60601-1:2005/(R)2012 and A1:2012 Medical electrical equipment, testing was conducted by Intertek, an independent testing laboratory, located in Menlo Park, CA. Intertek also conducted applicable testing pursuant to IEC 60601-1-6 Edition 3.1 2013-10-Medical electrical equipment Part 1-6 General requirements for safety—Collateral Standard: Usability. In addition, QT Ultrasound conducted, and Intertek witnessed, all applicable testing pertaining to the requirements for the safety of ultrasonic medical diagnostic and monitoring equipment and to demonstrate compliance with the “Acoustic Output Measurement Standard for Diagnostic Ultrasound Equipment”. This test on acoustic output was pursuant to IEC 60601-2-37 Edition 2.0.2007 Medical electrical equipment—Part 2-37: Particular requirements for the basic safety and essential performance of ultrasonic medical diagnostic and monitoring equipment. Finally, system verification testing was conducted to ensure that the QT Breast Scanner met all design and other requirements including but not limited to that no new issues of safety or effectiveness compared to the predicate device, SoftVue System manufactured by Delphinus Medical Technologies, were raised.

On June 6, 2017, the FDA, in response to the Company’s Section 510(K) Summary of Safety and Effectiveness premarket notification, determined that the QT Breast Scanner is substantially equivalent to the predicate device. Our use of the words “safe”, “safety”, “effectiveness”, and “efficacy” in relation to the QT Breast Scanner in this prospectus and all other documents related to the Company is limited to the context of the Section 510(K) Summary of Safety and Effectiveness that was reviewed and responded to by the FDA.

The Company's Cloud SaaS platform will serve as the unified delivery framework for upcoming artificial intelligence/machine learning algorithms developed by the Company. Leveraging DICOM-compatible architecture, the Company will integrate these modules through the cloud for quantitative feature extraction and diagnostic decision support. Built on advanced acoustic signal analysis and volumetric data fusion, the algorithms will be deployed in real time through the cloud infrastructure. This approach will ensure that future artificial intelligence-driven advancements, such as automated lesion segmentation, volumetric tissue characterization, and computer-aided diagnosis, can be securely delivered to all connected QT Breast Scanners without requiring on-premise updates. As biomarkers allow us