# K233998: TRAQinform IQ

- Pathway: 510(k) (Traditional)
- Applicant: Aiq Global, Inc.
- Decided: Sep 5, 2024 after 262 days
- Product code: LLZ (System, Image Processing, Radiological)
- Device class: 2
- Regulation: 21 CFR 892.2050
- Recalls of this device: none
- Data: FDA decisions to Oct 25, 2026; recalls to Oct 12, 2026

## Lineage
Longest line of descent: 9 generations back to K950279 (1995). 40 ancestors in all.
No later device cites it as a predicate yet.
0 of 41 devices in its family (counting itself) have a Class I recall.

## Predicates on the family tree (from the FDA summary)
- K173444: Quantitative Total Extensible Imaging (QTxI), Aiq Solutions, Inc. (2018) Summary page 7.

## Indications for use
TRAQinform IQ is a software only device that provides a quantitative TRAQinform Report on lesions identified as Regions of Interest (ROI) in PET/CT DICOM compliant imaging data acquired, interpreted, and reported on per local practice prior to device use. Clinicians responsible for patient care and for ordering TRAQinform Reports as an adjunct to locally reported image interpretation do not interact directly with the device. Clinicians responsible for local image interpretation do not interact with the device and generate their reporting before and independently of the TRAQinform Report. The TRAQinform Report is generated by the device manufacturer and signed by a U.S. board certified physician responsible for supervising central report generation and qualified to practice nuclear radiology/medicine. The TRAQinform Report is for use by trained medical professionals including but not limited to oncologists, nuclear radiologists/physicians, medical imaging technologists, dosimetrists, and physicists. TRAQinform IQ software contains the following functionalities: • Automated matching of ROI between previously performed CT and PET/CT DICOM 3.0 volumetric medical images. • In order to perform automated matching of ROI and quantitative analysis of previously performed CT and PET/CT DICOM 3.0 volumetric medical images, the software initially performs the following functions: ▪ Machine learning skeletal and anatomic structure segmentation. ▪ Threshold-based ROI identification and contouring. • Automated quantitative analysis to assess previously performed CT and PET/CT DICOM 3.0 volumetric medical images, including: change in total volume and density of each identified ROI, and change in Fludeoxyglucose F18 (FDG) tracer uptake of each identified ROI among images. • Generation of images of the anatomy combined with spatial and quantitative information, including computed classification of quantitative FDG ROI changes. For multi-timepoint quantitative analysis, recommended use is in adult patients 22 years and older with partial or whole-body PET/CT acquired following administration of FDG per approved drug prescribing information and with the second FDG administration separated from the first by a period not to exceed 12 months. For single-timepoint quantitative analysis, recommended use is in adult patients 22 years and older with partial or whole-body PET/CT following administration of FDG, a PSMA targeted PET drug, or a SSTR-targeted PET drug per approved drug prescribing information. Discrepancies between TRAQinform IQ and local PET/CT reporting have been investigated and use of TRAQinform IQ has not been established for binary patient level progression or non-progression decisions without multidisciplinary review. Discrepancies between TRAQinform IQ and local PET/CT reporting that could impact patient care should therefore prompt consultation with subject matter experts (for example, in tumor board), with a patient-centered focus on discrepant imaging regions and with blinded or otherwise neutral adjudication regarding interpretation/classification source. TRAQinform IQ is not intended to diagnose any disease, replace the diagnostic procedures for interpretation of CT or PET/CT images, recommend any specific treatment, nor is it intended to replace the skill and judgment of a qualified medical professional.

Source page: https://510kreport.com/device/K233998
Methodology: https://510kreport.com/methodology