| K-number | K251484 |
| Device name | CT:VQ |
| Applicant | 4Dmedical Limited |
| Product code | JAK |
| Device class | Class II |
| Decision date | Aug 28, 2025 |
| Decision | Substantially Equivalent |
| Regulation | 892.1750 |
CT:VQ is a software tool that analyzes paired inspiratory/expiratory chest CT scans to measure and visualize regional ventilation and perfusion in the lungs. It provides DICOM images and quantitative data to help radiologists, pulmonologists, and nuclear medicine physicians assess lung function and respiratory conditions in adult patients for clinical decision support without using contrast agents.
CT:VQ processes non-contrast paired chest CTs to derive ventilation and perfusion measures from lung tissue displacement, lung volume change, and Hounsfield Units. Unlike the primary predicate (CT:V, which measures only ventilation from non-contrast CTs), CT:VQ adds perfusion quantification. Unlike the secondary predicate (CSBP-001A, which requires contrast-enhanced dynamic CT), CT:VQ achieves both measurements from a single non-contrast acquisition.
ANSI AAMI ISO14971:2019 (risk management), ISO62304:2006/Amendment 1:2016 (software life cycle), IEC62304-1:2016 (health software safety), IEEE 11073-40101/40102:2020 (cybersecurity), ISO14155:2020 (clinical investigation), ISO20417:2021 (labeling), and FDA guidance documents on device software and cybersecurity.
CT:VQ is substantially equivalent because it shares the same regulatory classification (Class II, product code JAK), intended users (thoracic specialists), and patient population (adults) as the predicates. Functionally, it combines ventilation capability from the primary predicate (CT:V) with perfusion capability from the secondary predicate (CSBP-001A). Clinical studies demonstrated strong correlation with SPECT nuclear imaging and pulmonary function tests, showing CT:VQ outputs are interpretable and clinically actionable with a safety/effectiveness profile similar to the primary predicate, while providing contrast-free perfusion assessment.
View the full FDA submission: accessdata.fda.gov