The VIDA|vision software provides reproducible CT values for pulmonary tissue, which is essential for providing quantitative support for diagnosis and follow up examinations. VIDA|vision can be used to support the physician in the diagnosis and documentation of pulmonary tissue images (e.g., abnormalities) from CT thoracic datasets. Three-D segmentation and isolation of sub-compartments, volumetric analysis, density evaluations, low density cluster analysis and reporting tools are combined with a dedicated workflow. The VIDA vision software package is also intended to be a real-time interactive evaluation in space and time for CT volume data sets that provides the reconstruction of two dimensional images into a three-dimensional image format.

Device Description

VIDA|vision is a self-contained image analysis software package. This real-time interactive evaluation in space and time of CT volume datasets provides the reconstruction of two-dimensional images into a three-dimensional image format.

VIDA|vision can be used to support the physician in the diagnosis, treatment planning, and documentation of chest diseases, including lung cancer, asthma, COPD, interstitial lung disease and other lung abnormalities e.g. when examining the pulmonary and thoracic tissue (i.e. lung parenchyma) in CT thoracic datasets.

Evaluation (3D segmentation & isolation of sub-compartments, volumetric analysis, density evaluations, and low density cluster analysis), editing, and reporting tools are combined with a dedicated workflow.

VIDA|vision is designed to analyze pulmonary CT slice data and display analysis results. Each voxel of the scan is measured by Hounsfield units (HU), a measurement of x-ray attenuation that is applied to each volume element in three dimensional space ("voxel"). The HU are utilized to distinguish between air, water, tissue and bone, such distinction is common in the industry.

VIDA|vision provides computed tomography (CT) viewing, airway analysis, and parenchymal density analysis in one application. VIDA|vision provides imaging of bronchial airways that can be used to assess therapy effectiveness and treatment plan based on CT scan data. VIDA|vision reconstructs multiple cross-section images from CT data into a computer model displaying complex bronchial branches.

VIDA|vision provides quantitative measurements and tabulates quantitative properties. VIDA|vision focuses on what is visible to the eye and applies volumetric methods that might otherwise be too tedious to use. The software does not perform any function which cannot be accomplished by a trained user utilizing manual tracing methods; the intent of the software is to save time and automate potential error prone manual tasks.

VIDA|vision has functions for loading, analyzing, and saving datasets, and will generate screen displays, computations and aggregate statistics. VIDA|vision data output may be exported in pdf format or to a csv file.

AI/ML Overview

The provided document is a 510(k) Premarket Notification from the FDA to VIDA Diagnostics Inc. for their device, VIDA|vision. The document primarily focuses on demonstrating substantial equivalence to a predicate device, not on presenting detailed performance metrics and acceptance criteria from a clinical or non-clinical study for a specific AI function.

Specifically, the document states:

"No human clinical testing was required to support a substantial equivalence finding."
"Lung and lobe segmentation performance was tested against the predicate performance to demonstrate substantial equivalence." However, it does not provide the specific acceptance criteria or detailed results of this performance testing.

Therefore, many of the requested details about acceptance criteria and the study that proves the device meets them (such as specific performance metrics, sample sizes, expert qualifications, and ground truth methodologies) are not available in the provided text. The document focuses on regulatory compliance and comparison to a predicate, rather than a detailed performance study with quantifiable results.

Based on the information available:

1. A table of acceptance criteria and the reported device performance:

Acceptance Criteria: Not explicitly stated in terms of specific numerical thresholds for AI performance (e.g., specific accuracy, sensitivity, specificity values). The general acceptance criterion appears to be "demonstrate substantial equivalence" to the predicate device in terms of lung and lobe segmentation performance.
Reported Device Performance: No specific numerical performance metrics (e.g., accuracy, DICE score) are provided. It only states that "Results of testing demonstrate that the device has met all product specifications and user needs within its intended use." for lung and lobe segmentation.

2. Sample size used for the test set and the data provenance:

Sample Size: Not specified.
Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not specified.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

Not specified.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

No MRMC study is mentioned or summarized in the document. The statement "No human clinical testing was required" implies such a study assessing human reader improvement with AI assistance was not performed or submitted for this clearance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

It states that "Lung and lobe segmentation performance was tested against the predicate performance." This implies a standalone technical performance evaluation was done for the segmentation algorithm, but no specific metrics or methodology are provided to describe "standalone performance" in detail.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

Not specified in the provided text.

8. The sample size for the training set:

Not specified.

9. How the ground truth for the training set was established:

Not specified.

In summary, the provided FDA 510(k) clearance letter and summary primarily address regulatory aspects, device description, and comparison to a predicate device, rather than detailed technical study results with specific performance metrics for the deep learning algorithm. The mention of "deep learning-based segmentation algorithms" is a key difference from the predicate, but the specific validation of these algorithms in terms of detailed performance data is not included in this summary document.

Summary

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VIDA Diagnostics Inc. % Alex Morris Director, Quality and Regulatory 2500 Crosspark Road, W250 BioVentures Center CORALVILLE IA 52241

August 7, 2020

Re: K200990

Trade/Device Name: VIDA|vision Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK Dated: May 19, 2020 Received: May 20, 2020

Dear Alex Morris:

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/cfpmp/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 devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see

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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 medical devices and radiation-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) K200990

Device Name VIDA|vision

Indications for Use (Describe)

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)

CONTINUE ON A SEPARATE PAGE IF NEEDED.

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Section 5 – 510(k) Summary

K200990

Submitter:	VIDA Diagnostics, Inc.500 Crosspark Rd.W250 BioVentures CenterCoralville, IA 52241 USA
Date Prepared:	July 25, 2020
Contact Person:	Alex Morris, Director, Quality and RegulatoryVIDA Diagnostics, Inc.2500 Crosspark Rd.W250 BioVentures CenterCoralville, IA 52241 USACell Phone: (647) 470.4363Office Phone: (855) 900.8432Email: amorris@vidalung.ai
Submission Date:	May 19, 2020
Trade Name:	VIDA vision
RegulationDescription:	Computed tomography x-ray system
Common Name:	Medical Imaging Software for Computed Tomography Devices
Regulation:	21 CFR 892.1750
Product Code:	JAK
Regulatory Class:	Class II
Predicate Device:	Pulmonary Workstation 2 (PW2) by VIDA Diagnostics Inc.Regulation: 21 CFR 892.1750Product Code: JAKRegulatory Class: Class IIRegulation Description: Computed tomography x-ray systemSubmission Number: K083227

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Description of Device:

Indications for Use Statement:

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The VIDA|vision software provides reproducible CT values for pulmonary tissue, which is essential for providing quantitative support for diagnosis and follow up examinations. VIDA|vision can be used to support the physician in the diagnosis and documentation of pulmonary tissue images (e.g., abnormalities) from CT thoracic datasets. Three-D segmentation and isolation of sub-compartments, volumetric analysis, density evaluations, low density cluster analysis and reporting tools are combined with a dedicated workflow. The VIDA|vision software package is also intended to be a real-time interactive evaluation in space and time for CT volume data sets that provides the reconstruction of two dimensional images into a three-dimensional image format.

Comparison to Predicate:

The focus of this submission is to introduce deep learning-based segmentation algorithms to the proposed software to automatically segment lung regions.

	510(k) Submitter	Predicate	Differences
Manufacturer	VIDA Diagnostics, Inc.	VIDA Diagnostics, Inc.
Trade Name	VIDA vision (formerly VIDAPulmonary Workstation 2(PW2))	VIDA PulmonaryWorkstation 2 (PW2)
510(k) Number	K200990	K083227
Product Code	JAK	JAK	n/a
RegulationNumber	21 CFR 892.1750	21 CFR 892.1750	n/a
RegulationName	System, X-Ray, Tomography,Computed	System, X-Ray,Tomography, Computed	n/a
IntendedUse/Indicationsfor Use	The VIDA vision softwareprovides reproducible CTvalues for pulmonary tissue,which is essential forproviding quantitativesupport for diagnosis andfollow up examinations.VIDA vision can be used to	The VIDA PulmonaryWorkstation 2 (PW2)software providesreproducible CT values forpulmonary tissue, which isessential for providingquantitative support fordiagnosis and follow upexaminations. The PW2 can	n/a
	support the physician in thediagnosis anddocumentation ofpulmonary tissue images(e.g., abnormalities) from CTthoracic datasets. Three-Dsegmentation and isolationof sub-compartments,volumetric analysis, densityevaluations, low densitycluster analysis andreporting tools arecombined with a dedicatedworkflow. The VIDA visionsoftware package is alsointended to be a real-timeinteractive evaluation inspace and time for CTvolume data sets thatprovides the reconstructionof two dimensional imagesinto a three-dimensionalimage format.	be used to support thephysician in the diagnosisand documentation ofpulmonary tissue images(e.g., abnormalities) fromCT thoracic datasets.Three-D segmentation andisolation ofsub-compartments,volumetric analysis, densityevaluations, low densitycluster analysis andreporting tools arecombined with a dedicatedworkflow. The VIDAPulmonary Workstation 2(PW2) software package isalso intended to be areal-time interactiveevaluation in space andtime for CT volume datasets that provides thereconstruction of twodimensional images into athree-dimensional imageformat.
Image SourceModalities	СТ	СТ	n/a
DICOMConformance	Yes	Yes	n/a
ComparativeReview	2D, 3D	2D, 3D	n/a
3D Lungmapping	yes	yes	n/a
3Dmeasurements	VolumeEffective Diameter	VolumeEffective Diameter	n/a
2D	Line and ROI tools with	Line and ROI tools with	n/a
measurements	statisticsDiameter 2DArea	statisticsDiameter 2DArea
Densitymeasurements	Minimum, maximum andaverage HU	Minimum, maximum andaverage HU	n/a
Deployment	Standalone computer/distributed	Standalone computer	Subject deviceoffersdistributedconfiguration inaddition tostandalone,unlike thepredicate device
OS	Windows	Linux	transitionedfrom Linux toWindows.
User Interface	yes - w/ limitedmodifications	yes	limitedmodifications toimprove theuser experienceandaccommodatenewfunctionalityand a neweroperatingsystem.
Algorithm	Each voxel of the scan ismeasured by Hounsfieldunits (HU), a measurementof x-ray attenuation that isapplied to each volumeelement in threedimensional space ("voxel").The HU are utilized todistinguish between air,water, tissue and bone, such	Each voxel of the scan ismeasured by Hounsfieldunits (HU), a measurementof x-ray attenuation that isapplied to each volumeelement in threedimensional space ("voxel").The HU are utilized todistinguish between air,water, tissue and bone,	Unlike thepredicatedevice, thesubject deviceprovides deeplearning-derivedsegmentation.
	distinction is common in theindustry.A non-adaptive deeplearning-based algorithm isapplied to the CT imagingdata to automaticallysegment lung regions.	such distinction is commonin the industry.
Workflow	Automated contouringAutomated measurementsManual CorrectionDistinct user workflows:Airway Mapping and LungVolume Analysis	Automated contouringAutomated measurementsManual Correction	Subject deviceoffersfunctionality tosupport distinctuser workflows,unlike predicate.
Graphic UserInterface	Yes	Yes	n/a
Interactive 3DVisualization	Yes	Yes	n/a
Input/Output	Users can browse, select,and load CT scan files. Userscan save and load analyses,export via reporting tools.CT scan files can beorganized by user-definedprojects, and tracked byusage. User can generate areport that displaysquantitative data items thatcan be saved. DICOM infodisplayed. Data importthrough DICOM query/retrieve available.	Users can browse, select,and load CT scan files. Userscan save and load analyses,export via reporting tools.CT scan files can beorganized by user-definedprojects, and tracked byusage. User can generate areport that displaysquantitative data items thatcan be saved. DICOM infodisplayed.	Unlike thepredicatedevice, thesubject devicesupports DICOMquery/retrievedataimportation.
			predicate, thesubject deviceprovides pathplanning toairwaysegments.Unlike thepredicate, thesubject deviceincludes pathplanning to aregion ofinterest in thelung tissue.
User editing	yes	yes	n/a
Reports	yes - csv and pdf formatconfigurable for specific usecases	yes - csv only	Unlike thepredicate, thesubject deviceofferspre-existingmetrics andvisualizationspackaged forspecific usecases
Scan qualityassessment	Scan protocol isassessed forcompatibility withsoftware incompatibility issuesflagged duringimport and on report Scanner calibrationassessment Warning issued forout-of-rangeair/bloodmeasurements	Scan protocol isassessed for PW2compatibility incompatibilityissues flagged duringimport and onreport Scanner calibrationassessment Warning issued forout-of-rangeair/bloodmeasurements	n/a

Table 1 - Comparison of Characteristics

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Clinical Testing:

No human clinical testing was required to support a substantial equivalence finding.

Non-clinical testing:

The device labeling contains instructions for use and any necessary precautions and warnings to support the safe and effective use of the device. Known hazards were identified and mitigated in accordance with the ISO 14971 standard. Verification and validation activities were performed in accordance with FDA QSR and the IEC 62304 standard. Testing consisted of unit, regression, performance, and integrated system testing. Lung and lobe segmentation performance was tested against the predicate performance to demonstrate substantial equivalence. Results of testing demonstrate that the device has met all product specifications and user needs within its intended use.

Consensus Standards:

ISO 14971:2007 Medical devices -- Application of risk management to medical devices.
IEC 62304:2006Amd2015 Medical device software -- Software lifecycle processes. .
NEMA PS 3.1--3.20 (2016) Digital Imaging and Communication in Medicine (DICOM) Set ●
ISO 15223-1:2016 Medical devices -- Symbols to be used with medical device labels,
labelling and information to be supplied -- Part 1: General requirements. ●

Statement of Substantial Equivalence:

The subject device, VIDA|vision, is substantially equivalent to the predicate device. Differences do not raise new issues about the safety and effectiveness of the software.

Regulation Number and Section

§ 892.1750 Computed tomography x-ray system.

(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.