(181 days)
Yes
The document explicitly states that "Artificial intelligence software as a medical device is the main technological principle" and that the software "uses artificial intelligence technology to analyze specific disease features".
No
The device is used to automatically detect diabetic retinopathy, which is a diagnostic function, not a therapeutic one.
Yes
The device is indicated for use by healthcare providers to "automatically detect more than mild diabetic retinopathy," which is a diagnostic function.
No
The device description explicitly states that the IDx-DR device consists of several component parts, including a camera attached to a computer, and servers hosted in a secure datacenter. While software is a critical component, the system includes hardware elements (camera, computer, servers) necessary for image acquisition, processing, and delivery of results.
Based on the provided information, no, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are medical devices intended for use in vitro for the examination of specimens, including blood, tissue, and urine, derived from the human body, solely or principally for the purpose of providing information concerning a physiological state, state of health, or disease or congenital abnormality.
- IDx-DR's Function: IDx-DR analyzes images of the retina (fundus images) taken directly from the patient's eye. It does not analyze biological specimens (blood, tissue, etc.) collected from the patient.
- Imaging Modality: The input is described as "Macula and disc centered color fundus images," which are images, not biological samples.
Therefore, IDx-DR falls under the category of a medical device that uses imaging and AI for diagnosis, but it is not an In Vitro Diagnostic device.
No
The letter mentions a protocol to mitigate risks from algorithm changes, referencing a guidance document, but does not state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
IDx-DR is indicated for use by healthcare providers to automatically detect more than mild diabetic retinopathy in adults diagnosed with diabetes who have not been previously diagnosed with diabetic retinopathy. IDx-DR is indicated for use with the Topcon NW400.
Product codes
PIB
Device Description
The IDx-DR device consists of several component parts. A camera is attached to a computer, where IDx-DR client is installed. Guided by the Client, users acquire two fundus images per eye to be dispatched to IDx-Service. IDx-Service is installed on a server hosted at a secure datacenter. From IDx-Service, images are transferred to IDx-DR Analysis. No information other than the fundus images is required to perform the analysis. IDx-DR Analysis, which runs on dedicated servers hosted in the same secure datacenter as IDx-Service, processes the fundus images and returns information on the exam quality and the presence or absence of mtmDR to IDx-Service. IDx-Service then transports the results to the IDx-DR Client that displays them to the user.
Component parts:
- IDx-DR Analysis: Software that analyzes the patient's images and determines exam quality and the presence/absence of diabetic retinopathy.
- IDx-DR Client: A software application component running on a computer, usually connected to the fundus camera, at the customer site. Using this software, the customer can transfer images to IDx-DR Analysis via IDx-Service and receive results back.
- IDx-Service: IDx-Service comprises a general exam analysis service delivery software package. IDx-Service contains a webserver front-end that securely handles incoming requests, a database that stores customer information, and a logging system that records information about each transaction through IDx-Service. IDx-Service is also primarily responsible for device cybersecurity.
Mentions image processing
IDx-DR Analysis, which runs on dedicated servers hosted in the same secure datacenter as IDx-Service, processes the fundus images and returns information on the exam quality and the presence or absence of mtmDR to IDx-Service.
Mentions AI, DNN, or ML
Artificial intelligence software as a medical device is the main technological principle for both the subject and predicate devices. The software as a medical device uses artificial intelligence technology to analyze specific disease features from fundus retinal images for diagnostic screening of diabetic retinopathy.
The IDx-DR artificial intelligence device design has the ability to perform analysis on the specific disease features that are important to a retina specialist for diagnostic screening of diabetic retinopathy.
Input Imaging Modality
Fundus images; Macula and disc centered color fundus images with 45° field of view, 2 per eye.
Anatomical Site
Retinal
Indicated Patient Age Range
Adults
Intended User / Care Setting
Healthcare providers
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Not Found
Summary of Performance Studies
The determination of substantial equivalence is not based on an assessment of clinical performance data. The device modifications do not affect clinical performance. Refer to DEN180001 for details about the pivotal clinical trial of the IDx-DR device.
Non-clinical Studies:
Software:
IDx-DR (software version 2) was identified as having a major level of concern as defined in the FDA guidance document Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices. The software documentation includes:
- Software/Firmware Description
- Device Hazard Analysis
- Software Requirement Specifications
- Architecture Design Chart
- Software Design Specifications
- Traceability
- Software Development Environment Description
- Revision Level History
- Unresolved Anomalies
- Cybersecurity
A comprehensive risk analysis was performed on IDx-DR with identification and detailed description of the hazards, their causes and severity, as well as acceptable methods for control of the identified hazards. A description of acceptable verification and validation activities, at the unit, integration, and system level, including test protocols with pass/fail criteria and a report of the results, was provided. The expected impact of various hardware features on performance was assessed and minimum specifications for acceptable images for analysis were specified.
The cybersecurity considerations of data confidentiality, data integrity, data availability, denial of service attacks, and malware were adequately addressed utilizing platform controls, application controls, and procedure controls, and evidence was provided for the intended performance of the controls. Risks related to failure of various software components and their potential impact on patient reports and operator failures were also adequately addressed in the risk analysis. This software documentation information provided sufficient evidence of safe and effective software performance.
A full characterization of the technical parameters of all of the components of the software, including a description of the algorithms that analyzes the patient's images to determine exam quality and the diagnostic screening of diabetic retinopathy, has been provided. IDx-DR requires one optic disc centered image and one macula centered image from a fundus camera with at least 22 pixels per degree on the retina. So, a 1000 pixel field of view diameter for a 45 degree field of view image.
Usability:
Usability validation testing was performed under simulated-use to assess the user interface (IDx-DR Client) of the subject device. The testing was performed in an environment equivalent to the intended use environment of IDx-DR with subjects that had no prior experience using the IDx-DR Client. The critical task for the IDx-DR system is the ability to capture four images of sufficient quality. The purpose of the usability validation test plan was to demonstrate that the intended image capture workflow and training methodology can successfully be used by the intended operators to capture four retinal images. The results of the usability validation study indicated that no existing critical tasks were impacted by the modification and no new critical tasks were introduced, and demonstrated that previously untrained camera operators can capture four retinal images of sufficient quality following the imaging protocol and using the indicated camera system and standardized training and operating materials.
Key Metrics
Not Found
Predicate Device(s)
Reference Device(s)
No reference devices were used in this submission.
Predetermined Change Control Plan (PCCP) - All Relevant Information
A protocol was provided to mitigate the risk of algorithm changes leading to changes in the device technical specifications, which would lead to changes in false positive or false negative results. These changes could significantly affect clinical functionality or performance specifications directly associated with the intended use of the device. The protocol specifies the level of change in device specifications that could significantly affect the safety or effectiveness of the device, triggering the requirement for a new 510(k) premarket notification submission before commercial introduction. The protocol incorporates a risk management approach and other approaches provided in the FDA guidance document Deciding When to Submit a 510(k) for a Software Change to an Existing Device: Guidance for Industry and FDA Staff in development, validation, and execution of the device changes.
§ 886.1100 Retinal diagnostic software device.
(a)
Identification. A retinal diagnostic software device is a prescription software device that incorporates an adaptive algorithm to evaluate ophthalmic images for diagnostic screening to identify retinal diseases or conditions.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Software verification and validation documentation, based on a comprehensive hazard analysis, must fulfill the following:
(i) Software documentation must provide a full characterization of technical parameters of the software, including algorithm(s).
(ii) Software documentation must describe the expected impact of applicable image acquisition hardware characteristics on performance and associated minimum specifications.
(iii) Software documentation must include a cybersecurity vulnerability and management process to assure software functionality.
(iv) Software documentation must include mitigation measures to manage failure of any subsystem components with respect to incorrect patient reports and operator failures.
(2) Clinical performance data supporting the indications for use must be provided, including the following:
(i) Clinical performance testing must evaluate sensitivity, specificity, positive predictive value, and negative predictive value for each endpoint reported for the indicated disease or condition across the range of available device outcomes.
(ii) Clinical performance testing must evaluate performance under anticipated conditions of use.
(iii) Statistical methods must include the following:
(A) Where multiple samples from the same patient are used, statistical analysis must not assume statistical independence without adequate justification.
(B) Statistical analysis must provide confidence intervals for each performance metric.
(iv) Clinical data must evaluate the variability in output performance due to both the user and the image acquisition device used.
(3) A training program with instructions on how to acquire and process quality images must be provided.
(4) Human factors validation testing that evaluates the effect of the training program on user performance must be provided.
(5) A protocol must be developed that describes the level of change in device technical specifications that could significantly affect the safety or effectiveness of the device.
(6) Labeling must include:
(i) Instructions for use, including a description of how to obtain quality images and how device performance is affected by user interaction and user training;
(ii) The type of imaging data used, what the device outputs to the user, and whether the output is qualitative or quantitative;
(iii) Warnings regarding image acquisition factors that affect image quality;
(iv) Warnings regarding interpretation of the provided outcomes, including:
(A) A warning that the device is not to be used to screen for the presence of diseases or conditions beyond its indicated uses;
(B) A warning that the device provides a screening diagnosis only and that it is critical that the patient be advised to receive followup care; and
(C) A warning that the device does not treat the screened disease;
(v) A summary of the clinical performance of the device for each output, with confidence intervals; and
(vi) A summary of the clinical performance testing conducted with the device, including a description of the patient population and clinical environment under which it was evaluated.
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June 10, 2021
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo is in blue and includes the letters "FDA" in a square, followed by the words "U.S. FOOD & DRUG ADMINISTRATION".
Digital Diagnostics Inc. Ashley Miller Regulatory Affairs Manager 2300 Oakdale Blvd. Coralville, Iowa 52241
Re: K203629
Trade/Device Name: IDx-DR Regulation Number: 21 CFR 886.1100 Regulation Name: Retinal Diagnostic Device Regulatory Class: Class II Product Code: PIB Dated: May 11, 2021 Received: May 11, 2021
Dear Ashley Miller:
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
1
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 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 (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,
Elvin Ng Assistant Director DHT1A: Division of Ophthalmic Devices OHT1: Office of Ophthalmic, Anesthesia, Respiratory, ENT and Dental Devices Office of Product Evaluation and Ouality Center for Devices and Radiological Health
Enclosure
2
Indications for Use
510(k) Number (if known) K203629
Device Name IDx-DR
Indications for Use (Describe)
IDx-DR is indicated for use by healthcare providers to automatically detect more than mild diabetic retinopathy in adults diagnosed with diabetes who have not been previously diagnosed with diabetic retinopathy. IDx-DR is indicated for use with the Topcon NW400.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| X Prescription Use (Part 21 CER 801 Subnart D) | Over-The-Counter Ise (21 CER 801 Submart C) |
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V. 510(k) Summary
I. Submitter
Digital Diagnostics Inc. 2300 Oakdale Blvd. Coralville, IA 52241 Phone: 319-248-5620
Contact Person: Ashley Miller Date Prepared: December 4, 2020
II. Device
Name of Device: IDx-DR Common or Usual Name: Diabetic Retinopathy Detection Device Classification Name: Retinal diagnostic software device Regulatory Class: II Regulation: 21 CFR 886.1100 Product Code: PIB
III. Predicate Device
IDx-DR, Diabetic Retinopathy Detection Device, DEN180001 This predicate has not been subject to a design-related recall.
No reference devices were used in this submission.
IV. Indications for Use
IDx-DR is indicated for use by healthcare providers to automatically detect more than mild diabetic retinopathy in adults diagnosed with diabetes who have not been previously diagnosed with diabetic retinopathy. IDx-DR is indicated for use with the Topcon NW400.
The Indications for Use statement is identical to the predicate device.
V. Device Description
The IDx-DR device consists of several component parts (see image below). A camera is attached to a computer, where IDx-DR client is installed. Guided by the Client, users acquire two fundus images per eye to be dispatched to IDx-Service. IDx-Service is installed on a server hosted at a secure datacenter. From IDx-Service, images are
4
transferred to IDx-DR Analysis. No information other than the fundus images is required to perform the analysis. IDx-DR Analysis, which runs on dedicated servers hosted in the same secure datacenter as IDx-Service, processes the fundus images and returns information on the exam quality and the presence or absence of mtmDR to IDx-Service. IDx-Service then transports the results to the IDx-DR Client that displays them to the user.
Image /page/4/Figure/3 description: The image shows a diagram of the IDx secure server system. The diagram shows the flow of data from the patient's camera to the IDx-DR client on the customer's computer. The data is then sent to the IDx web service on the IDx secure servers. Finally, the data is sent to the IDx-DR analysis on the IDx secure servers, and the results are sent back to the customer's computer.
Figure 1: IDx-DR Components
The component parts of IDx-DR illustrated above are summarized as follows:
- IDx-DR Analysis: Software that analyzes the patient's images and determines exam quality and the presence/absence of diabetic retinopathy.
- IDx-DR Client: A software application component running on a computer, usually connected to the fundus camera, at the customer site. Using this software, the customer can transfer images to IDx-DR Analysis via IDx-Service and receive results back.
- IDx-Service: IDx-Service comprises a general exam analysis service delivery software package. IDx-Service contains a webserver front-end that securely handles incoming requests, a database that stores customer information, and a logging system that records information about each transaction through IDx-Service. IDx-Service is also primarily responsible for device cybersecurity.
VI. Comparison of Technological Characteristics with the Predicate Device
IDx-DR, the subject device of this 510(k), has the same intended use and indications for use as the predicate IDx-DR device cleared under DEN180001.
Artificial intelligence software as a medical device is the main technological principle for both the subject and predicate devices. The software as a medical device uses artificial intelligence technology to analyze specific disease features from fundus retinal images for diagnostic screening of diabetic retinopathy. The subject and predicate devices are based on the same general technological elements:
5
- . Fundus camera to obtain retinal images
- IDx-DR Client installed on a computer to guide the user to acquire images using ● the fundus camera, transfer the images to IDx-DR Analysis via IDx-Service, and receive the results
- . IDx-DR Analysis to analyze the patient's images for exam quality and the presence/absence of diabetic retinopathy
- . IDx-Service to facilitate secure transfer of exam data from IDx-DR Client to IDx-DR Analysis and the results from IDx-DR Analysis back to IDx-DR Client
The major technological differences that exist between each component of the subject and predicate devices are described below.
IDx-Service
- The subject device allows of the submission of DICOM images
- . The subject device provides improved feedback to the client by distinguishing between the states "submission not found" and "submission not ready"
- . The subject device tracks image analysis statistics, such as analysis start and end
IDx-DR Client
- . The subject device does not require the user to "refresh" the user interface to display new exams
- . The subject device incorporates customer configuration options:
- Submission of DICOM images O
- O Output filename structure
- Highlight most recent exam о
- Masking of exam result on the user interface (the result is unchanged in о the final report)
- o Dark mode for viewing based on customer preference
- The subject device incorporates a guided workflow in IDx-DR Client to guide the . user through the image acquisition/submission and display step-by-step instructions directly on the user interface
- . The subject device incorporates local image retention
- . The subject device incorporates a training mode
- . The subject device in-exam image quality feedback and allows the user to resubmit images when applicable
6
IDx-DR Analysis
- . The subject device determines image fixations when the number of left and right eye images does not meet protocol requirements
Table 3 provides a comparison between the technical characteristics and indications for use of the subject and predicate devices.
| | Subject Device
IDx-DR | Predicate Device
IDx-DR, DEN180001 | Discussion |
|-----------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Component
Software
Versions | IDx-DR Client v3.2.0
IDx-DR Analysis v2.1.1
IDx-Service v1.1.2
See above for the major
technological differences
between each component
of the subject and
predicate device. | IDx-DR Client v2.0.1
IDx-DR Analysis v2.0.1
IDx-Service v1.0.0 | Substantially
Equivalent. The
changes described
above do not
significantly affect
the use of the
device, clinical
functionality, nor
performance of the
device as
supported by
software
verification and
validation testing. |
| Technological
Principle | Artificial intelligence
software as a medical
device. | Artificial intelligence
software as a medical
device. | Equivalent |
| Indications
for Use | For use by healthcare
providers to automatically
detect more than mild
diabetic retinopathy in
adults diagnosed with
diabetes who have not
been previously diagnosed
with diabetic retinopathy. | For use by healthcare
providers to automatically
detect more than mild
diabetic retinopathy in
adults diagnosed with
diabetes who have not
been previously diagnosed
with diabetic retinopathy. | Equivalent |
| Indicated
Camera | Topcon NW400 fundus
camera | Topcon NW400 fundus
camera | Equivalent |
| Inputs | Macula and disc centered
color fundus images with
45° field of view, 2 per
eye. | Macula and disc centered
color fundus images with
45° field of view, 2 per
eye. | Equivalent |
| Outputs | Detection of diabetic
retinopathy and referral
decision: | Detection of more than
mild diabetic retinopathy
(mtmDR) and referral
decision: | Equivalent |
| | mtmDR detected:
Refer to an eye care professional mtmDR not detected:
Rescreen in 12 months Insufficient image quality | mtmDR detected:
Refer to an eye care professional mtmDR not detected:
Rescreen in 12 months Insufficient image quality | |
| Architecture | User facing client software
transfers images to and
receives results from
analysis software through
a web server. | User facing client software
transfers images to and
receives results from
analysis software through
a web server. | Equivalent |
| Workflow | The graphical user
interface includes on-
screen prompts to guide
the user through the image
acquisition workflow one
image at a time and
submission of the exam. | Labeling (the Quick
Reference Guide) guides
the user through the image
acquisition workflow and
submission of the exam. | Substantially
Equivalent. The
labeling is being
incorporated
directly into the
user interface and
instructions are
displayed as the
user progress
through each step
for improved
interaction with
the device. The
overall workflow
and directions for
use do not change. |
Table 1: Comparison of the Subject and Predicate Device
7
Performance Data VII.
The following performance data were provided in support of the substantial equivalence determination.
A. Summary of Non-clinical Studies
Software
IDx-DR (software version 2) was identified as having a major level of concern as defined in the FDA guidance document Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices. The software documentation includes:
-
- Software/Firmware Description
-
- Device Hazard Analysis
8
-
- Software Requirement Specifications
-
- Architecture Design Chart
-
- Software Design Specifications
-
- Traceability
-
- Software Development Environment Description
-
- Revision Level History
-
- Unresolved Anomalies
-
- Cybersecurity
A comprehensive risk analysis was performed on IDx-DR with identification and detailed description of the hazards, their causes and severity, as well as acceptable methods for control of the identified hazards. A description of acceptable verification and validation activities, at the unit, integration, and system level, including test protocols with pass/fail criteria and a report of the results, was provided. The expected impact of various hardware features on performance was assessed and minimum specifications for acceptable images for analysis were specified.
The cybersecurity considerations of data confidentiality, data integrity, data availability, denial of service attacks, and malware were adequately addressed utilizing platform controls, application controls, and procedure controls, and evidence was provided for the intended performance of the controls. Risks related to failure of various software components and their potential impact on patient reports and operator failures were also adequately addressed in the risk analysis. This software documentation information provided sufficient evidence of safe and effective software performance.
A full characterization of the technical parameters of all of the components of the software, including a description of the algorithms that analyzes the patient's images to determine exam quality and the diagnostic screening of diabetic retinopathy, has been provided. IDx-DR requires one optic disc centered image and one macula centered image from a fundus camera with at least 22 pixels per degree on the retina. So, a 1000 pixel field of view diameter for a 45 degree field of view image.
The IDx-DR artificial intelligence device design has the ability to perform analysis on the specific disease features that are important to a retina specialist for diagnostic screening of diabetic retinopathy. Future algorithm improvements will be made under a consistent medically relevant framework. A protocol was provided to mitigate the risk of algorithm changes leading to changes in the device technical specifications, which would lead to changes in false positive or false negative results. These changes could significantly affect clinical functionality or performance specifications directly associated with the intended use of the device. The protocol specifies the level of change in device specifications that could significantly affect the safety or effectiveness of the device, triggering the requirement for a new 510(k) premarket notification submission before commercial introduction. The protocol incorporates a risk management approach and
9
other approaches provided in the FDA guidance document Deciding When to Submit a 510(k) for a Software Change to an Existing Device: Guidance for Industry and FDA Staff in development, validation, and execution of the device changes.
Usability
Usability validation testing was performed under simulated-use to assess the user interface (IDx-DR Client) of the subject device. The testing was performed in an environment equivalent to the intended use environment of IDx-DR with subjects that had no prior experience using the IDx-DR Client. The critical task for the IDx-DR system is the ability to capture four images of sufficient quality. The purpose of the usability validation test plan was to demonstrate that the intended image capture workflow and training methodology can successfully be used by the intended operators to capture four retinal images. The results of the usability validation study indicated that no existing critical tasks were impacted by the modification and no new critical tasks were introduced, and demonstrated that previously untrained camera operators can capture four retinal images of sufficient quality following the imaging protocol and using the indicated camera system and standardized training and operating materials.
B. Summary of Clinical Studies
The determination of substantial equivalence is not based on an assessment of clinical performance data. The device modifications do not affect clinical performance. Refer to DEN180001 for details about the pivotal clinical trial of the IDx-DR device.
VIII. Conclusions
IDx-DR is substantially equivalent to the predicate IDx-DR device cleared under DEN180001. The subject and predicate devices have the same indications for use, technological characteristics, and performance specifications.