K210053 · Dia Imaging Analysis, Ltd. · QIH · Feb 5, 2021 · Radiology
Device Facts
Record ID
K210053
Device Name
LVivo Software Application
Applicant
Dia Imaging Analysis, Ltd.
Product Code
QIH · Radiology
Decision Date
Feb 5, 2021
Decision
SESE
Submission Type
Special
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K210053 · Feb 5, 2021
LVivo Software Application
Dia Imaging Analysis, Ltd.
Routine transthoracic echocardiography examinations from ambulatory and hospitalized patients
The retrospective dataset was used to validate the performance of the LVivo Software Application (EF, SWM, and GLS analysis) by comparing results against established reference standards.
Ambulatory and hospitalized patients referred for routine transthoracic echocardiography; age >18, in sinus rhythm; excluded patients with LBBB.; Sample Size: 100 patients (96 examinations for EF analysis; 98 examinations for SWM and GLS analysis)
Not applicable for this study
Biplane EF correlation, sensitivity, specificity, and kappa for EF; sensitivity for SWM and GLS.
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Ejection Fraction
Neural network
biplane EF correlation >=80%
—
—
—
100 ambulatory and hospitalized patients referred for routine transthoracic echocardiography
—
Global Longitudinal Strain
Neural network
cutoff value < -17, Sensitivity>=75% compared to ref WSMI
—
—
—
98 examinations from a data set of 100 ambulatory and hospitalized patients
—
Segmental Wall Motion
Neural network
Sensitivity >=75%
—
—
—
98 examinations from a data set of 100 ambulatory and hospitalized patients
—
Indications for Use
LVivo platform is intended for non-invasive processing of ultrasound images to detect, measure, and calculate relevant medical parameters of structures and function of patients with suspected disease
Device Story
LVivo platform is a software system for automated analysis of echocardiographic DICOM movies; supports global/segmental left ventricle (LV) function evaluation (ejection fraction, wall motion, strain) from apical (4CH, 2CH, 3CH) and parasternal short axis (SAX) views; includes right ventricular (RV) function and bladder volume modules. Operates on Windows/Linux/Android platforms. Software processes ultrasound inputs to automatically select end-diastolic/end-systolic frames, calculate volumes via Simpson's method of discs, and present results. Clinicians use output to assess cardiac function and bladder volume; manual editing/confirmation capabilities provided. Benefits include automated, standardized, and efficient analysis of ultrasound examinations.
Clinical Evidence
Bench testing and retrospective analysis of 100 ambulatory/hospitalized patients (59% male, mean age 60.6 ±17.7). 96 exams used for EF analysis; 98 for SWM/GLS. Acceptance criteria: biplane EF correlation ≥80%; GLS sensitivity ≥75% (cutoff < -17); SWM sensitivity ≥75%. Results demonstrated performance similar or superior to the predicate device.
Technological Characteristics
Software-based automated radiological imaging processing. Supports DICOM input. Operates on Windows, Linux, and Android platforms. Utilizes neural network-based algorithms for image analysis. Features include automated frame selection, Simpson's method of discs for volume calculation, and manual editing tools.
Indications for Use
Indicated for patients with suspected disease requiring non-invasive ultrasound image processing for structural and functional measurements. Excludes patients with multiple premature beats or LBBB. Age >18.
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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February 5, 2021
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DiA Imaging Analysis Ltd. % Mr. George J. Hattub Senior Project Manager Medicsense USA 291 Hillside Avenue SOMERSET MA 02726
Re: K210053
Trade/Device Name: LVivo Software Application Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: OIH Dated: December 31, 2020 Received: January 8, 2021
Dear Mr. Hattub:
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. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
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 device-related adverse events) (21 CFR 803) for
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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
For
Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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## Indications for Use
510(k) Number (if known) K210053
Device Name LVivo Software Application
Indications for Use (Describe)
LVivo platform is intended for non-invasive processing of ultrasound images to detect, measure, and calculate relevant medical parameters of structures and function of patients with suspected disease.
| Type of Use (Select one or both, as applicable) | |
|-------------------------------------------------|--|
|-------------------------------------------------|--|
X Prescription Use (Part 21 CFR 801 Subpart D)
| Over-The-Counter Use (21 CFR 801 Subpart C)
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# 510(k) Summary
K210053
Pursuant to CFR 807.92, the following 510(k) Summary is provided:
| 1. (a) | Submitter Address: | George J. Hattub<br>Medicsense USA LLC<br>291 Hillside Avenue<br>Somerset, MA 02726<br>ghattub@comcast.net<br>https://www.upwork.com/freelancers/~0196e832ca4b82a2f3?viewMode=1 |
|--------|----------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 1. (b) | Manufacturer Address: | DiA Imaging Analysis Ltd<br>HaEnergia Street 77<br>Beer-Sheva, Israel 8470912 |
| | Mfg. Phone: | Tel.: +972 77 7648318 |
| | Contact Person: | Mrs. Michal Yaacobi |
| | Date: | January 27, 2021 |
| 2. | Device &<br>Classification<br>Name: | Automated Radiological Imaging Processing Software - classified as Class 2<br>QIH, Regulation Number 21 CFR 892.2050<br>LVivo Software Application |
| 3. | Predicate Device: | K200232 LVivo Software Application |
| 4. | Description: | The LVivo platform is a software system for automated analysis of<br>ultrasound examinations. Automated analysis of echocardiographic<br>examinations is done using DICOM movies. The LVivo platform supports<br>global and segmental evaluation of the left ventricle (LV) of the heart. The<br>global LV function is evaluated from two of the apical views: four-chamber<br>(4CH) and two-chamber (2CH) by ejection fraction (EF). The segmental LV<br>function is done from three apical views 4CH, 2CH and three chamber<br>(3CH) and supports wall motion evaluation and strain. The LVivo platform<br>supports also global and segmental evaluation of the LV from the<br>parasternal short axis (SAX) view. In addition to the LV analysis, the<br>cardiology toolbox includes a module for automated evaluation of the Right<br>Ventricular function. The LVivo platform includes one additional non-cardiac<br>module for the measurement of the bladder volume. |
| 5. | Intended Use: | LVivo platform is intended for non-invasive processing of ultrasound images<br>to detect, measure, and calculate relevant medical parameters of structures<br>and function of patients with suspected disease |
| 6. | Comparison of<br>Technological<br>Characteristics: | With respect to technology and intended use, DiA's LVivo Software<br>Application is substantially equivalent to its predicate device. Based upon<br>the outcomes from the risk analysis and Performance Testing Evaluation,<br>DiA believes that the modification of the predicate device does not raise<br>additional safety of efficacy concerns. The following comparison table<br>depicts the changes. |
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| | Submitted Device | Predicate Device |
|-------------------------------------------------------------------------|-------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Features/Characteristics | LVivo Software<br>Application | LVivo Software<br>Application |
| Product Code | same | QIH |
| Indication for Use | same | LVivo platform is<br>intended for non-<br>invasive processing of<br>ultrasound images to<br>detect, measure, and<br>calculate relevant<br>medical parameters of<br>structures and function<br>of patients with<br>suspected disease. |
| Modules | same | LVivo EF, LVivo SG,<br>LVivo SAX, LVivo RV &<br>LVivo Bladder |
| Automation | same | yes |
| Manual Adjustment | same | yes |
| Bi plane EF evaluation | same | yes |
| Simultaneous 2CH and<br>4CH evaluation | same | yes |
| Off-line EF evaluation<br>using DICOM clips of any<br>vendor | same | yes |
| Automated ED and ES<br>frames selection | same | yes |
| Dynamic left ventricular | same | yes |
| Manual editing by<br>user capability | same | yes |
| Visually confirm EF | same | yes |
| Automated rejection<br>of false results | same | yes |
| Volume calculation by<br>standard Simpson's<br>method of discs | same | yes |
| Volume curve<br>Presentation | same | yes |
| EF results presentation | same | yes |
| Enables presentation EF<br>results for different<br>cycle | same | yes |
| Algorithm | Modified in LVivo EF | yes |
| Calculation speed | same | yes |
| Capability or a part of a<br>bigger package (device)<br>for LV function | same | yes |
| Segmental Longitudinal<br>Strain Measure | same | yes |
| Global Longitudinal<br>Strain Measure | same | yes |
| Segmental wall motion<br>evaluation | same | yes |
| Operating System | same | Windows/Linux<br>(with Android<br>option for LVivo<br>EF |
| 510(k) # | Pending | K200232 |
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510k Notification: LVivo Software Application
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#### 7. Performance A summary of the Performance Evaluation, which was based upon well-Evaluation: established test methods, demonstrated conformity to the intended use.
A data set of 100 ambulatory and hospitalized patients referred for routine transthoracic echocardiography was previously collected according to GCP standards. The population was comprised of 59% male, mean age of 60.6 ±17.727. Inclusion criteria: age >18 in sinus rhythm without multiple premature beats. Patients with LBBB were excluded from the study. 27 patients had normal LV and 47 patients had coronary artery disease (CAD) function. Total of 96 examinations were used for the EF analysis (due to missing ref).
Acceptance criteria for EF analysis: biplane EF correlation >=80%, similar or better EF biplane results in terms of correlation, specificity, sensitivity, and kappa with respect to subject device.
For SWM and GLS analysis, a total of 98 examinations were used from the same data set (due to missing ref).
For GLS acceptance criteria: cutoff value < -17, Sensitivity>=75% compared to ref WSMI, similar or better results compared to subject device
For SWM acceptance criteria: Sensitivity >=75%, similar or better results compared to subject device
- 8. Conclusion: The Intended Use and the technological characteristics in the current device are the same as those in the predicate device, including the addition of the neural network, do not affect the safety and effectiveness of the device. The performance tests have been completed and successfully support the device performance. Therefore, DiA Imaging Analysis concludes the LVivo Software Application is substantially equivalent to the predicate device.
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.