K964778 · Health Images, Inc. · LNH · Feb 24, 1997 · Radiology
Device Facts
Record ID
K964778
Device Name
HI-STAR MRI IMAGING SYSTEM
Applicant
Health Images, Inc.
Product Code
LNH · Radiology
Decision Date
Feb 24, 1997
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.1000
Device Class
Class 2
Indications for Use
The HI STAR system is indicated for use as a general purpose MR imager that produces transverse, sagittal, coronal, and oblique cross-sectional images of internal structures of the human body, head, and extremities. Contrast in these images reflect the intrinsic properties of the hydrogen proton, proton density, T1, and T2, and the extrinsic parameters of the applied imaging sequences. The indications for the HI STAR do not differ significantly from the predicate, or legally marketed devices.
Device Story
HI STAR is a 0.6T superconducting whole-body MRI system. It uses pulsed radio frequency energy and magnetic gradient fields to generate proton echo signals from human tissue. Signals are converted via Fourier transform into 2D/3D images. Operated by trained personnel in fixed or mobile clinical settings. Includes various RF coils (body, head, extremity, surface) for specific anatomical coverage. Supports multiple pulse sequences (Spin Echo, FSE, MRA, IRIS, FatSat). Post-processing includes window/level, rotation, zoom, pan, and HI-Q noise reduction. Output images assist clinicians in diagnostic assessment of internal structures. Benefits include non-invasive visualization of anatomy without ionizing radiation.
Clinical Evidence
Bench testing only. Performance validated against NEMA and AAPM standards for signal-to-noise ratio, image uniformity, slice thickness, resolution, and geometric distortion. Safety parameters (static field, SAR, acoustic noise) verified against IEC 601-2-33 and NEMA MS-4. Sample images obtained from employee volunteers to demonstrate image quality; no adverse reactions reported.
Technological Characteristics
0.6T superconducting magnet with passive/active shimming. Quadrature transmit/receive body coils and various receive-only surface coils. Pulse sequences: Spin Echo, Field Echo, Turbo Field Echo, Multi-spin Echo, Inversion Recovery, MRA, FSE, IRIS, FatSat, Magnetization Transfer. Reconstruction via Fourier transform. Installation: fixed or mobile. Connectivity: variable display matrix up to 1024x1024. Standards: IEC 601-2-33, NEMA MS-1, MS-2, MS-4, MS-6, AAPM-28.
Indications for Use
Indicated for patients requiring cross-sectional imaging of the head, body, and extremities to visualize internal structures based on hydrogen proton density, T1, and T2 tissue characteristics.
Regulatory Classification
Identification
A magnetic resonance diagnostic device is intended for general diagnostic use to present images which reflect the spatial distribution and/or magnetic resonance spectra which reflect frequency and distribution of nuclei exhibiting nuclear magnetic resonance. Other physical parameters derived from the images and/or spectra may also be produced. The device includes hydrogen-1 (proton) imaging, sodium-23 imaging, hydrogen-1 spectroscopy, phosphorus-31 spectroscopy, and chemical shift imaging (preserving simultaneous frequency and spatial information).
Special Controls
*Classification.* Class II (special controls). A magnetic resonance imaging disposable kit intended for use with a magnetic resonance diagnostic device only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.
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K964778
FEB 24 1997
# Attachment H
## 510 (k) Summary / Safety and Effectiveness
1. 510 (k) Summary, Safety and Effectiveness
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510 (k) Summary, Safety and Effectiveness
Health Images
HI STAR MRI Device
The following information is in accordance with 21 CFR 807.92
## Submitter's Name, Address, Telephone Number, Contact Person, Preparation Date
Health Images, Inc.
8601 Dunwoody Place
Building 200
Atlanta, GA 30350
(770) 642-9869 ext. 2057
Richard Halbach, Dir. of Clinical Research & Regulatory Affairs
November 25, 1996
## Name of the Device and Classification Name/Number
HI STAR, Magnetic Resonance Imager.
The FDA has reclassified these devices, 90LNH, to Class II.
## Predicate Devices
| Manufacturer | Commercial Name | Description |
| --- | --- | --- |
| Health Images | HI-Standard | 0.6T whole body MRI imager, superconducting magnet |
| Health Images | HI-Standard/Calibre IRIS sequence | 0.6T whole body MRI imager, superconducting magnet, IRIS Silicone Specific Sequence |
| Health Images | HI STAR | 0.6T whole boy MRI imager, superconducting magnet |
| Elscint | Gyrex 2T Prestige | Spectral Fat Suppression, FSE |
| Philips | Gyroscan NT, 1T | Spectral Fat Suppression |
## Description of the Device
The Health Images HI STAR is a proton (H-1) Magnetic Resonance Imaging device. The HI STAR has been designed to produce transverse, sagittal, coronal, and oblique section images of the head, body and extremities of the human body. Contrast in these images is produced primarily by T1, T2, and proton density tissue characteristics. This imager employs conventional MRI imaging techniques in which the application of a combination of pulsed radio frequency energy and magnetic gradient fields is applied to the body to generate MR proton echo signals. These multidimensionally coded signals are converted by Fourier transform into 2D and 3D image sets.
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510 (k) Summary, Safety and Effectiveness
Health Images
HI STAR MRI Device
## Device Characteristics
| Parameter | Example |
| --- | --- |
| Type of magnet | Superconducting, passive/active shim |
| Static field strength | 0.6T |
| Type of RF coils | Transmit/Receive - quadrature Body |
| | Receive - quadrature Head, MRA, Neck, Spine, Wrist |
| | Receive - linear Bilateral TMJ, Volume Extremity, Bilateral Breast, Shoulder |
| | General Purpose Surface (body & extremity) 29.2 cm x 15.2 cm (11.5 x 6.0 inch) |
| | 19.0 cm x 19.0 cm (7.5 x 7.5 inch) |
| | 12.7 cm x 12.7 cm (5.0 x 5.0 inch) |
| | 6.4 cm x 6.4 cm (2.5 x 2.5 inch) |
| Data acquisition modes | Single slice, Multi-slice, Multi-angle oblique, 3D Volume, Physiologic Gating |
| Pulse Sequences | Spin Echo, Field Echo, Turbo Field Echo, Multi-spin Echo, Inversion Recovery, MRA, FSE |
| Additional Contrast Techniques | IRIS (Silicone Specific), FatSat, Magnetization Transfer |
| Reconstruction Technique | Fourier transform |
| Type of installation: | Mobile, Fixed |
| Slice selection method: | Selective Gradient, 3D phase encode |
| Display Matrix | Variable up to 1024 x 1024 |
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510 (k) Summary, Safety and Effectiveness
Health Images
HI STAR MRI Device
| Acquisition Matrix | In plane 64 - 512, increment of 8 |
| --- | --- |
| Number of slices, | 2D, 1 - 256 slices, increment of 1 |
| Range and Increment | 3D, 12 - 256 increment of 2 |
| Post processing | Window and level
Rotate image
Mirror image
Zoom image
Pan image
Add and Subtract images
HI-Q image processing noise reduction function |
| Slice orientation | Transverse, Sagittal, Coronal, Single and multiple oblique |
| Interslice spacing, minimum, maximum, | From Contiguous up to 320 mm, increment of 0.5 mm |
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510 (k) Summary, Safety and Effectiveness
Health Images
HI STAR MRI Device
# Intended Uses
The HI STAR system is indicated for use as a general purpose MR imager that produces transverse, sagittal, coronal, and oblique cross-sectional images of internal structures of the human body, head, and extremities. Contrast in these images reflect the intrinsic properties of the hydrogen proton, proton density, T1, and T2, and the extrinsic parameters of the applied imaging sequences. The indications for the HI STAR do not differ significantly from the predicate, or legally marketed devices.
## Safety Parameters
| Parameter | FDA Limit | HI STAR | Test Standard |
| --- | --- | --- | --- |
| Maximum Static Magnetic Field | ≤ 2 tesla | 0.6T | Manufacturer |
| Rate of Magnetic Field Strength change | ≤ 20 T/second | < 20 T/s | IEC 601-2-33 |
| SAR | < 1.5 W/kg, averaged over whole body (First Controlled Operating Level) | < 1.5 W/kg | IEC 601-2-33 |
| | 1.5 ≤ SAR < 4.0 W/kg, averaged over whole body (Second Controlled Operating Level) | 1.5 ≤ SAR < 4.0 W/kg | IEC 601-2-33 |
| Acoustic Noise Levels | < 105 dB (A weighted average over 1 hour) | < 92 dBA | NEMA MS-4 |
## Imaging Performance Parameters
| Parameter | Data | Standard |
| --- | --- | --- |
| Specification Volume | Head 25.6 cm DSV
Body 48 cm DSV | Manufacturer |
| Signal-to-noise Ratio | | |
| Body Coil | 103 | NEMA MS-1 |
| Head Coil | 62 | NEMA MS-1 |
| MRA Coil | 50 | NEMA MS-6 |
| Wrist Coil | 117 | NEMA MS-6 |
| Neck Coil | 108 | NEMA MS-6 |
| Spine Coil | 62 | NEMA MS-6 |
| Breast Coil | 100 | NEMA MS-6 |
| Bilateral TMJ Coil | 133 | NEMA MS-6 |
| Extremity Coil | 49 | NEMA MS-6 |
| Shoulder Coil | 108 | NEMA MS-6 |
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510 (k) Summary, Safety and Effectiveness
Health Images
HI STAR MRI Device
| Parameter | Data | Standard |
| --- | --- | --- |
| General Purpose
Surface Coils | | NEMA MS-6 |
| 29.2 cm x 15.2 cm
(11.5 x 6.0 inch) | 95 | |
| 19.0 cm x 19.0 cm
(7.5 x 7.5 inch) | 98 | |
| 12.7 cm x 12.7 cm
(5.0 x 5.0 inch) | 80 | |
| 6.4 cm x 6.4 cm
(2.5 x 2.5 inch) | 133 | |
| Image Uniformity
Body Coil | 12%, Specification Volume 48 cm
NEMA MS-2 | |
| Head Coil | 6%, Specification Volume 25.6 cm
NEMA MS-2 | |
| Slice Thickness, Separation | 10% of specified | AAPM-28 |
| Resolution | Body
1.5 mm
Head
1 mm
AAPM-28 | |
| Geometric Distortion | Body
< 5%
@ 31 cm
Head
< 5%
@ 15.5 cm | NEMA #2 |
Sample images included with this submission were obtained on R &D systems at Health Images, Inc. using employee volunteers. Each volunteer signed a consent form. There were no adverse reactions noted on any of the participants.
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Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
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Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
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What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
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Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
