(277 days)
Deep Xray is a radiological fully automated image processing software device of either computed (CR) or directly digital (DX) images intended to aid medical professionals in the measurement of minimum joint space width; the assessment of the presence or absence of sclerosis, joint space narrowing, and osteophytes based on OARSI criteria for these parameters; and, the presence or absence of radiographic knee OA based on Kellgren & Lawrence Grading of standing, fixed-flexion radiographs of the knee.
It should not be used in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis.
The system is to be used by trained professionals including, but not limited to, radiologists, physicians and medical technicians.
Deep Xray is a standalone software device that utilizes artificial intelligence (AI) and computer vision algorithms to assist clinical professionals in analyzing and measuring radiographic abnormalities of knee osteoarthritis (OA) during review of posterior or anterior-posterior knee radiographs. DeepXray provides automated metric measurements of the joint space width and angular measurements of the femoral-tibial angle. DeepXray also performs assessments of knee osteoarthritis based on the Kellgren-Lawrence Grade (KL Grade), as well as individual radiographic features of osteoarthritis, including joint space narrowing, osteophyte and sclerosis based on the OARSI (Osteoarthritis Research Society International) grading criteria.
The output of DeepXray is rendered as a summary report and can be viewed on a web browser. Using this web interface, the user can verify the AI report side-by-side with the original radiograph using standard DICOM image tools and review each AI analysis result with the help of markup images overlaid with highlighted disease location or reference lines used for automated measurements. The web report also notifies the user for potential data quality issues. The clinical professionals can make modifications to the AI analysis results based on their professional judgement before saving and outputting the report.
Here's a breakdown of the acceptance criteria and the study details for the DeepXray device, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state "acceptance criteria" as a set of predefined thresholds that the device must meet in order to be cleared. Instead, it presents the performance metrics obtained during the clinical validation, implying that these results were deemed sufficient for substantial equivalence. I will present the reported performance, which served as the basis for clearance.
| DeepXray Output (Indication) | Performance Metric | Reported Result (95% C.I.) |
|---|---|---|
| Kellgren-Lawrence Grade (KL Grade ≥2) | Sensitivity | 0.87 (0.86/0.88) |
| Specificity | 0.84 (0.83/0.85) | |
| Joint Space Narrowing (OARSI Grade ≥1) | Sensitivity | 0.88 (0.87/0.89) |
| Specificity | 0.82 (0.81/0.83) | |
| Osteophyte (OARSI Grade ≥1) | Sensitivity | 0.86 (0.85/0.87) |
| Specificity | 0.80 (0.79/0.81) | |
| Sclerosis (Presence/Absence) | Sensitivity | 0.84 (0.83/0.85) |
| Specificity | 0.88 (0.87/0.89) | |
| Medial mJSW (mm) | Orthogonal linear regression (Slope) | 1.02 (1.00, 1.03) |
| Orthogonal linear regression (Intercept) | 0.04 (-0.03, 0.11) | |
| Lateral mJSW (mm) | Orthogonal linear regression (Slope) | 0.98 (0.95, 1.01) |
| Orthogonal linear regression (Intercept) | 0.06 (-0.10, 0.26) | |
| Femoral-Tibial Angle (degree°) | Orthogonal linear regression (Slope) | 0.97 (0.96, 0.99) |
| Orthogonal linear regression (Intercept) | -0.10 (-0.17, -0.04) |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size (Test Set):
- Patients: 1121
- DICOM Images: 6125 (after automatic quality control, 6114 DICOM images were analyzed for classification tasks and 5993/5904 for osteophyte/sclerosis, 4432/4377/4310 for mJSW/FTA)
- Knees: 11816 (11775 knees for classification tasks, 7748/7605/7546 for mJSW/FTA)
- Data Provenance: The data was derived from "one of the site of the Osteoarthritis Initiative (OAI), a multi-center longitudinal study." The OAI is a major public-private partnership focused on osteoarthritis. The text doesn't explicitly state the country of origin, but OAI data generally comes from multiple sites across the United States. It is a retrospective dataset.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document states that the ground truth for the clinical validation was "clinical professionals' labeling provided by the OAI study." The OAI study involved a rigorous process for establishing ground truth, typically involving expert radiologists. However, the exact number of experts and their specific qualifications for the OAI labeling are not explicitly detailed in this document. It generally refers to "clinical professionals."
4. Adjudication Method for the Test Set
The document does not explicitly describe an adjudication method (like 2+1 or 3+1 consensus) for establishing the ground truth of the OAI data used as the test set. It refers to "clinical professionals' labeling." OAI practices typically involve centralized reading by experienced radiologists, often with multiple readers and adjudication processes, but this specific detail is not present in this particular document.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance
No, a multi-reader multi-case (MRMC) comparative effectiveness study evaluating human readers with AI assistance versus without AI assistance was not described in this document. The study presented here is a standalone performance study of the DeepXray algorithm against existing ground truth.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, a standalone performance study of the algorithm only (without human-in-the-loop performance) was performed. The reported performance metrics (Sensitivity, Specificity, Slopes, Intercepts) are for the DeepXray device operating independently against the established ground truth.
7. The Type of Ground Truth Used
The ground truth used was expert consensus / clinical professionals' labeling obtained from the Osteoarthritis Initiative (OAI) study. This often combines radiological assessment with other clinical data in large research studies, but here it specifically refers to "clinical professionals' labeling" of radiographic findings and measurements.
8. The Sample Size for the Training Set
- Patients: 3387
- DICOM Images: 18406
- Knees: 35217
9. How the Ground Truth for the Training Set Was Established
The document states that the training data and testing data were both derived from the OAI study and that the performance data supports that the assessments and measurements are in "good agreement with clinical professionals' labeling provided by the OAI study." This implies that the ground truth for the training set was established through the same or a similar rigorous process of expert clinical professionals' labeling as the test set, within the OAI framework.
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Image /page/0/Picture/0 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 seal on the left and the FDA acronym along with the full name of the agency on the right. The FDA part of the logo is in blue, with the acronym in a square and the full name written out to the right of the square.
Alpha Intelligence Manifolds, Inc. % Qingzong Tseng Director 2F, No. 170, Zhonghe Rd., Zhonghe District New Taipei City, 235068 TAIWAN
Re: K223621
September 8, 2023
Trade/Device Name: DeepXray Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH Dated: August 14, 2023 Received: August 14, 2023
Dear Qingzong Tseng:
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.
Jessica Lamb
Jessica Lamb, PhD Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of 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) K223621
Device Name DeepXray
Indications for Use (Describe)
Deep Xray is a radiological fully automated image processing software device of either computed (CR) or directly digital (DX) images intended to aid medical professionals in the measurement of minimum joint space width; the assessment of the presence or absence of sclerosis, joint space narrowing, and osteophytes based on OARSI criteria for these parameters; and, the presence or absence of radiographic knee OA based on Kellgren & Lawrence Grading of standing, fixed-flexion radiographs of the knee.
It should not be used in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis.
The system is to be used by trained professionals including, but not limited to, radiologists, physicians and medical technicians.
| 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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Image /page/3/Picture/0 description: The image shows the logo for Alpha Intelligence Manifolds. The logo consists of a red geometric shape on the left, followed by the letters "AIM" in a dark gray color. Below the letters is the text "Alpha Intelligence Manifolds" in a smaller font size and a lighter gray color. The geometric shape appears to be an abstract representation of a house or building.
K223621 510(k) SUMMARY
DeepXrav Alpha Intelligence Manifolds, Inc.
| Applicant: | Alpha Intelligence Manifolds, Inc.2F, No.170, Zhonghe Road, Zhonghe District,New Taipei City, 235068,TaiwanTelephone: +882-2-2240-6570 |
|---|---|
| Date Prepared: | Aug 14, 2023 |
| Device Name: | DeepXray |
| Regulation Number: | 892.2050 |
| Regulation Name: | Medical Image Management and Processing System |
| Product Code: | QIH |
| Classification Name: | Automated Radiological Image Processing Software |
| Device Class: | Class II |
| Review Panel: | Radiology |
| Predicate Devices: | IB Lab GmbH's KOALA (K192109)Radiobotics ApS's RBknee (K203696) |
Device Description
Deep Xray is a standalone software device that utilizes artificial intelligence (AI) and computer vision algorithms to assist clinical professionals in analyzing and measuring radiographic abnormalities of knee osteoarthritis (OA) during review of posterior or anterior-posterior knee radiographs. DeepXray provides automated metric measurements of the joint space width and angular measurements of the femoral-tibial angle. DeepXray also performs assessments of knee osteoarthritis based on the Kellgren-Lawrence Grade (KL Grade), as well as individual radiographic features of osteoarthritis, including joint space narrowing, osteophyte and sclerosis based on the OARSI (Osteoarthritis Research Society International) grading criteria.
The output of DeepXray is rendered as a summary report and can be viewed on a web browser. Using this web interface, the user can verify the AI report side-by-side with the original radiograph
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Image /page/4/Picture/0 description: The image shows the logo for Alpha Intelligence Manifolds. The logo consists of a red geometric shape on the left, followed by the letters "AIM" in a dark gray sans-serif font. Below the letters is the full name of the company, "Alpha Intelligence Manifolds", in a smaller, lighter gray font. The geometric shape resembles a stylized house or building.
using standard DICOM image tools and review each AI analysis result with the help of markup images overlaid with highlighted disease location or reference lines used for automated measurements. The web report also notifies the user for potential data quality issues. The clinical professionals can make modifications to the AI analysis results based on their professional judgement before saving and outputting the report.
Intended Use / Indications for Use
Deep Xray is a radiological fully automated image processing software device of either computed (CR) or directly digital (DX) images intended to aid medical professionals in the measurement of minimum joint space width; the assessment of the presence of sclerosis, joint space narrowing, and osteophytes based on OARSI criteria for these parameters; and, the presence or absence of radiographic knee OA based on Kellgren & Lawrence Grading of standing, fixedflexion radiographs of the knee.
It should not be used in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis.
The system is to be used by trained professionals including, but not limited to, radiologists, orthopedists, physicians and medical technicians.
Comparison of Technological Characteristics
Deep Xray has the same technological characteristics as the predicate devices: KOALA (K192109) and RBknee (K203696). DeepXray and predicate devices all utilize computer vision (CV) as well as artificial intelligence (AI) algorithms trained on medical images to perform automated image processing tasks such as knee detection, landmark detection, and joint space detection. DeepXray and predicate devices all operate within Docker containers on a Linux server.
The only differences with predicate devices are that, instead of outputting the knee osteoarthritis analysis report as DICOM images, DeepXray output a web report providing quality warnings, markup images as well as an editing interface for the clinical professionals to modify any automated analysis results they considered inappropriate. In addition to the disease status (KL Grade, JSN, osteophyte, sclerosis) and minimum joint space width value (mJSW) reported by the predicate devices, DeepXray also reports the quantitative measurement of the Femoral-Tibial Angle.
In general, the technological characteristics of the DeepXray is directly comparable to the predicate devices, KOALA and RBknee. A table comparing the key features of the subject and predicate devices is provided below:
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| Feature | DeepXray(Subject Device) | KOALA(K192109,Predicate Device) | RBknee(K203696,Predicate Device) |
|---|---|---|---|
| Classification Nameand Product Code | Automated RadiologicalImage ProcessingSoftware (QIH) | System, ImageProcessing, Radiological(LLZ) | System, ImageProcessing, Radiological(LLZ) |
| Anatomical Area | Joint (knee) | Joint (knee) | Joint (knee) |
| Image Input | DICOM compliant imagesin either digitallycomputed (CR) or directlydigital (DX) formats | DICOM compliant imagesin either digitallycomputed (CR) or directlydigital (DX) formats | DICOM compliant imagesin either digitallycomputed (CR) or directlydigital (DX) formats |
| Image Processing | Knee detection;Landmark detection; Jointspace detection | Knee detection;Landmark detection; Jointspace detection | Knee detection;Landmark detection; Jointspace detection |
| Human Interventionfor interpretation | Required | Required | Required |
| Intended User | Trained professionals | Trained professionals | Trained professionals |
| Output Format | Web report with qualitywarning, markup imagesand editing interface | A single DICOM Image | Markup images andtextual report as staticDICOM images |
| Output Information | - Knee OA status:KL grade ≥2 or ≤1- JSN status:Absent/Present- Osteophyte status:Absent/Present- Sclerosis status:Absent/Present- Minimum Joint SpaceWidth- Femoral-Tibial Angle | - Knee OA status:KL grade ≥2 or ≤1- JSN status:Absent/Present- Osteophyte status:Absent/Present- Sclerosis status:Absent/Present- Minimum Joint SpaceWidth | - Knee OA status:KL grade ≥2 or <2- JSN status:Not present/Present- Osteophyte status:Not present/Present- Sclerosis status:Not present/Present- Minimum Joint SpaceWidth |
| Runs on Server | Yes | Yes | Yes |
| OperatingEnvironment | Linux/Docker | Linux/Docker | Linux/Docker |
Performance Data
DeepXray's clinical performance validation was performed on an indepen data from one of the Tve Chical sites of the Order Minister (OA), a multicana
logitudial studiser comprise of C. L. 25 martes are massices are massices consected and consence
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Image /page/6/Picture/0 description: The image contains the logo for Alpha Intelligence Manifolds (AIM). The logo consists of a red geometric shape resembling a stylized house or building, followed by the letters "AIM" in a dark gray sans-serif font. Below the letters, the full name "Alpha Intelligence Manifolds" is written in a smaller, lighter gray font.
The statistics of patient demography, image specifications as well as subgroups of radiographic findings are shown below:
| Items | Testing Dataset | Training Dataset |
|---|---|---|
| #Patients | 1121 | 3387 |
| Male | 499 (44.5%) | 1390 (41%) |
| Female | 622 (55.5%) | 1997 (59%) |
| Age > 60 | 601 (53.6%) | 1642 (48.5%) |
| Ethnicity | ||
| White | 937 (83.6%) | 2675 (79.0%) |
| Black or African American | 159 (14.2%) | 626 (18.5%) |
| Asian | 13 (1.2%) | 25 (0.8%) |
| Unknown or not reported | 12 (1.1%) | 61 (1.9%) |
| #DICOM | 6125 | 18406 |
| CR | 5783 (94.4%) | 11213 (60.9%) |
| DX | 342 (5.6%) | 3438 (18.7%) |
| RG | 0 (0%) | 3755 (20.4%) |
| Visiting Timepoint: | ||
| Baseline | 1121 (18.3%) | 3385 (18.4%) |
| 12 month | 1058 (17.3%) | 3158 (17.2%) |
| 24 month | 978 (16%) | 2999 (16.3%) |
| 36 month | 939 (15.3%) | 2877 (15.6%) |
| 48 month | 897 (14.6%) | 2757 (15.0%) |
| 72 month | 558 (9.1%) | 1602 (8.7%) |
| 96 month | 574 (9.4%) | 1628 (8.8%) |
| X-ray Manufacturer: | ||
| Agfa | 4671 (76.3%) | 3914 (21.3%) |
| Fujifilm | 1144 (18.7%) | 3030 (16.5%) |
| GE | 310 (5.1%) | 3450 (18.7%) |
| Konica-Minolta | 0 (0%) | 2055 (11.2%) |
| Philips | 0 (0%) | 66 (0.4%) |
| Siemens | 0 (0%) | 318 (1.7%) |
| Swissray | 0 (0%) | 3873 (21.0%) |
| Others (Not reported) | 0 (0%) | 1700 (9.2%) |
| #Knees: | 11816 | 35217 |
| KI < 1 | 6850 (58%) | 20536 (58.3%) |
| KL > 2 | 4966 (42%) | 14681 (41.7%) |
| JSN Absent | 6862 (58.1%) | 21089 (59.9%) |
| JSN Present | 4954 (41.9%) | 14128 (40.1%) |
| Osteophyte Absent | 8018 (69.4%) | 18997 (55.0%) |
| Osteophyte Present | 3538 (30.6%) | 15533 (45.0%) |
| Sclerosis Absent | 8520 (74.8%) | 25813 (75.6%) |
| Sclerosis Present | 2865 (25.2%) | 8336 (24.4%) |
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Image /page/7/Picture/0 description: The image shows the logo for Alpha Intelligence Manifolds (AIM). The logo consists of a red geometric shape resembling a stylized house or building, followed by the letters "AIM" in a dark gray sans-serif font. Below the logo is the full name of the company, "Alpha Intelligence Manifolds," also in a sans-serif font.
DeepXray's automatic quality control mechanism blocked 0.3% of test samples and did not give analysis results on those samples. Of the remaining test samples, the performance for the status indicators (expressed in Sensitivity/Specificity) of the radiographic findings are shown in the table below:
| DeepXrayOutput | Sample Number | Performance Metric | Result(95% C.I.) |
|---|---|---|---|
| Kellgren-LawrenceGrade | 11775 knees/6114 DICOM/1121 subjects | Sensitivity(KL Grade ≥2) | 0.87 (0.86/0.88) |
| Specificity(KL Grade ≥2) | 0.84 (0.83/0.85) | ||
| Joint SpaceNarrowing | 11775 knees/6114 DICOM/1121 subjects | Sensitivity(OARSI Grade ≥1) | 0.88 (0.87/0.89) |
| Specificity(OARSI Grade ≥1) | 0.82 (0.81/0.83) | ||
| Osteophyte | 11518 knees/5993 DICOM/1121 subjects | Sensitivity(OARSI Grade ≥1) | 0.86 (0.85/0.87) |
| Specificity(OARSI Grade ≥1) | 0.80 (0.79/0.81) | ||
| Sclerosis | 11348 knees/5904 DICOM/1119 subjects | Sensitivity(Presence/Absence) | 0.84 (0.83/0.85) |
| Specificity(Presence/Absence) | 0.88 (0.87/0.89) |
The performance of the measurements for the Joint Space Width (JSW) and the Femoral-Tibial Angle (FTA) by the DeepXray were quantified by orthogonal linear regression against reference measurements from the OAI study. The performance test results are summarized below:
| DeepXrayOutput | Sample Number | Orthogonal linear regression | Result (95% C.I.) |
|---|---|---|---|
| MedialmJSW (mm) | 7748 knees/4432 DICOM/862 subjects | Slope | 1.02 (1.00, 1.03) |
| MedialmJSW (mm) | 7748 knees/4432 DICOM/862 subjects | Intercept | 0.04 (-0.03, 0.11) |
| LateralmJSW (mm) | 7605 knees/4377 DICOM/861 subjects | Slope | 0.98 (0.95, 1.01) |
| LateralmJSW (mm) | 7605 knees/4377 DICOM/861 subjects | Intercept | 0.06 (-0.10, 0.26) |
| Femoral-Tibial Angle(degree°) | 7546 knees/4310 DICOM/854 subjects | Slope | 0.97 (0.96, 0.99) |
| Femoral-Tibial Angle(degree°) | 7546 knees/4310 DICOM/854 subjects | Intercept | -0.10 (-0.17, -0.04) |
The performance data support that the knee OA assessments and measurements given by DeepXray are in good agreement with clinical professionals' labeling provided by the OAL study.
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Image /page/8/Picture/0 description: The image contains the logo for Alpha Intelligence Manifolds. The logo consists of a red geometric shape resembling a stylized house or network node, followed by the letters "AIM" in a dark gray sans-serif font. Below the logo is the full name of the company, "Alpha Intelligence Manifolds," also in a dark gray sans-serif font, but smaller than the "AIM" letters.
Substantial Equivalence
DeepXray has the same intended use, similar indications, technological characteristics, and principles of operation as its predicate devices. The differences between DeepXray and its predicate devices do not alter the intended use of the device and do not raise new or different questions regarding its safety and effectiveness when used as labeled. Performance data demonstrates that DeepXray performs as intended. Thus, DeepXray is substantially equivalent to its predicate devices.
§ 892.2050 Medical image management and processing system.
(a)
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.(b)
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).