K091262 · Ziosoft, Inc. · LLZ · Jun 29, 2009 · Radiology
Device Facts
Record ID
K091262
Device Name
MR CARDIAC FUNCTION ANALYSIS
Applicant
Ziosoft, Inc.
Product Code
LLZ · Radiology
Decision Date
Jun 29, 2009
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
The MR Cardiac Function Analysis software option for use with Ziostation is intended for noninvasive post-processing of DICOM compliant cardiac MR images to semi-automatically calculate and display various functional parameters, such as left ventricular ejection fraction, end diastolic volume, end systolic volume, stroke volume, cardiac output, cardiac index, wall thickness, wall thickness ratio and regional wall motion display. These measurements can be used to assist the clinician in a cardiac evaluation.
Device Story
Software add-on for Ziostation image management system; processes ECG-gated cardiac MR images. Inputs: multi-phase DICOM cardiac MR data. Operation: semi-automatically extracts left ventricular parameters including ejection fraction, volumes (end diastolic/systolic, stroke), cardiac output/index, wall thickness/motion, and volume curves. Output: quantitative functional metrics and regional wall motion displays. Used in clinical settings by physicians/clinicians to assist in cardiac evaluation. Benefits: provides objective functional measurements to support clinical decision-making regarding cardiac pathology.
Clinical Evidence
No clinical data. Bench testing only; software integration testing, verification, and validation performed.
Technological Characteristics
Software-only device; no physical materials. Operates as an add-on to the Ziostation image management system. Processes DICOM-compliant cardiac MR images. Connectivity via Ziostation platform.
Indications for Use
Indicated for clinicians requiring noninvasive post-processing of DICOM-compliant cardiac MR images to calculate and display left ventricular functional parameters and wall motion for cardiac evaluation.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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K091262
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## 510(k) Summary
JUN 29 2009
This 510(k) summary is prepared in accordance with 21 CFR 807.92.
### General Information
#### Trade Name
#### MR Cardiac Function Analysis
Common Name Classification Name
Picture Archiving and Communications System (PACS) System, Image Processing, Radiological (21 CFR § 892.2050 - LLZ)
Applicant:
Ziosoft, Inc. 1000 Bridge Parkway, Ste. 100 Redwood City, CA 94065 Tel 650-413-1300 Fax 650-596-7319
#### Contact
Richard Ball Director, Regulatory and Quality Affairs
#### Intended Use
#### MR Cardiac Function Analysis
The MR Cardiac Function Analysis software option for use with Ziostation is intended for noninvasive post-processing of DICOM compliant cardiac MR images to semi-automatically calculate and display various functional parameters, such as left ventricular ejection fraction, end diastolic volume, end systolic volume, stroke volume, cardiac output, cardiac index, wall thickness, wall thickness ratio and regional wall motion display. These measurements can be used to assist the clinician in a cardiac evaluation.
#### Predicate Device
| Ziosoft tool | Manufacturer of<br>Predicate Device | Device Name | 510(k)<br>Number |
|---------------------------------|---------------------------------------|----------------------------------------------------------|------------------|
| MR Cardiac Function<br>Analysis | Medis Medical<br>Imaging Systems B.V. | MRI-FLOW Analytical Software<br>Package (a.k.a. QMassMR) | K994282 |
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#### Device Description
MR Cardiac Function Analysis is an add-on software package designed to be used with the basic Ziostation image management system to further aid clinicians in their analysis of anatomy and pathology. Universal functions such as data retrieval, storage, management, querying and listing, and output are handled by the basic Ziostation software. The additional capabilities provided by this new device are:
MR Cardiac Function Analysis software post-processes ECG-gated cardiac MR images and extracts the following left ventricular parameters from multi-phase data.
- · Left ventricular ejection fraction
- End diastolic volume
- End systolic volume
- Stroke volume
- Cardiac output
- Cardiac Index
- Wall thickness
- Wall thickness ratio
- Wall movement
- Volume Curve
- Peak Ejection Rate
- Peak Filling Rate
#### Materials
The MR Cardiac Function Analysis tool consists entirely of software. No materials are contained in this product.
#### Testing Summary
The MR Cardiac Function Analysis software package will successfully complete integration testing/verification testing prior to Beta validation. Software Beta testing/validation will be successfully completed prior to release. In addition, potential hazards have been addressed by the Ziosoft Risk Management process.
#### Summary of Substantial Equivalence
MR Cardiac Function Analysis is substantially equivalent in intended use and function to the predicate device and other devices already marketed in the US.
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Image /page/2/Picture/0 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo consists of a stylized caduceus symbol, which is a staff with two snakes coiled around it, and the words "DEPARTMENT OF HEALTH & HUMAN SERVICES • USA" arranged in a circular pattern around the symbol. The logo is black and white.
## DEPARTMENT OF HEALTH & HUMAN SERVICES
JUN 2 9 2009
Public Health Service
Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
Mr. Richard Ball Director, RA/OA Ziosoft, Inc. 1000 Bridge Parkway, Suite 100 REDWOOD CITY CA 94065
Re: K091262
Trade/Device Name: MR Cardiac Function Analysis Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: April 28, 2009 Received: April 29, 2009
#### Dear Mr. Ball:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration. Iisting of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical
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device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please go to http://www.fda.gov/AboutFDA/CentersOffices/CDRH/CDRHOffices/ucm115809.htm for the Center for Devices and Radiological Health's (CDRH's) Office of Compliance. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to http://www.fda.gov/cdrl/mdr/ for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (240) 276-3150 or at its Internet address http://www.fda.gov/cdrh/industry/support/index.html.
Sincerely yours,
Janine M. Morris Acting Director, Division of Reproductive, Abdominal, and Radiological Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known): KO91262
Device Name: __ MR Cardiac Function Analysis
Indications for Use:
MR Cardiac Function Analysis
The MR Cardiac Function Analysis software option for use with Ziostation is intended for noninvasive post-processing of DICOM compliant cardiac MR images to semi-automatically calculate and display various functional parameters, such as left ventricular ejection fraction, end diastolic volume, end systolic volume, stroke volume, cardiac output, cardiac index, wall thickness, wall thickness ratio and regional wall motion display. These measurements can be used to assist the clinician in a cardiac evaluation.
Prescription Use (Part 21 CFR 801 Subpart D)
AND/OR
Over-The-Counter Use (21 CFR 801 Subpart C)
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
| (Division Sign Off) | |
|---------------------------------------------------------------|---------|
| Division of Reproductive, Abdominal, and Radiological Devices | |
| 510(k) Number | R091262 |
Page ______ of ______510(k) Submission Ziosoft, Inc.
MR Cardiac Function Analysis for ZIOSTATION
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Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
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.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
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.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
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.
8. Chart view
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.
