K-numberK243651
Device nameVersaViewer
ApplicantGE Medical Systems SCS
Product codeLLZ
Device classClass II
Decision dateApr 21, 2025
DecisionSubstantially Equivalent
Regulation892.2050
AI Summary extracted from FDA summary PDF · never regenerated
Intended use

VersaViewer is a medical imaging software application that processes and analyzes 2D, 3D, and 4D medical images from multiple imaging modalities (CT, MR, PET, NM, ultrasound, etc.). It provides radiologists and clinicians with customizable layouts, measurement tools, segmentation capabilities, and rendering options to assist in diagnosis. The software is designed for use by trained healthcare professionals and is not intended for digital mammography image display for diagnosis.

Technological characteristics

VersaViewer supports expanded modality coverage compared to the predicate Volume Viewer Plus (adding SCPT, US, CR, DX, RF, XA, MR PJN, CT GSI, and breast tomosynthesis for presentation). It includes a new multi-oblique tool providing three adjustable orthogonal views, segmentation tools with Smart Brush and Threshold Brush functionality, and an optional One View feature with deep learning-based automated segmentation for six body parts (lung, liver, bone, aorta, heart, body). Core rendering modes (axial, coronal, sagittal, oblique, 3D, volume rendering, MIP, minIP, average) and export capabilities remain substantially equivalent.

Test standards cited

The device complies with NEMA PS 3.1 - 3.20 (2023) Digital Imaging and Communications in Medicine (DICOM) Set (Radiology) standard. It was designed and manufactured under Quality System Regulations of 21 CFR 820 and ISO 13485.

Substantial equivalence argument

VersaViewer employs the same fundamental scientific technology as its predicate devices. The expanded modality support has been successfully verified and validated with no new safety or effectiveness issues identified. The new multi-oblique tool and segmentation tools produce results obtainable by combinations of existing predicate functions and improve workflow without adding or removing diagnostic information. The deep learning segmentation algorithm was validated against retrospective CT exams representative of clinical use scenarios and passed acceptance criteria. All design control testing, risk analysis, and verification activities completed under GE HealthCare's quality system found no new hazards or unexpected adverse effects compared to predicates.

Extracted by AI from the official FDA summary PDF →
Source

View the full FDA submission: accessdata.fda.gov

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