(92 days)
Yes
The document explicitly states that the device utilizes "machine learning algorithms trained on medical images."
No.
The device is described as image processing software that aids medical professionals in measurements and assessments for diagnosis, but it does not directly treat or provide therapy to a patient.
Yes
Explanation: The "Intended Use / Indications for Use" section states that the software is "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... and, the presence or absence of radiographic knee OA based on Kellgren & Lawrence Grading". It also explicitly states, "The Knee OsteoArthritis Labeling Assistant (KOALA) software provides metric measurements of the joint space width and indicators for presence of radiographic features of osteoarthritis (OA)". These functions are all part of the diagnostic process for knee osteoarthritis.
Yes
The device description explicitly states it is "software" and operates in a Linux environment, compatible with Docker. It processes existing medical images and does not include or control any hardware.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze samples taken from the human body. The description clearly states that IB Lab KOALA is a radiological image processing software that analyzes X-ray images of the knee. It does not interact with the patient directly or analyze biological samples like blood, urine, or tissue.
- The intended use is for analyzing medical images. The primary function is to process and analyze radiographic images to aid in the assessment of knee osteoarthritis. This falls under the category of medical image analysis software, not IVD.
The device's function is to process and interpret medical images, which is distinct from the analysis of biological samples that defines an IVD.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device.
Intended Use / Indications for Use
IB Lab KOALA 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 OARSI criteria for these parameters; and, the presence or absence of radiographic knee OA based on Kellgren & Lawrence Grading, 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, orthopedics, physicians and medical technicians.
Product codes
LLZ, JAK
Device Description
The Knee OsteoArthritis Labeling Assistant (KOALA) software provides metric measurements of the ioint space width and indicators for presence of radiographic features of osteoarthritis (OA) on posterior-anterior-posterior (PA/AP) knee X-ray images. The outputs aid clinical professionals who are interested in the analysis of knee OA in adult patients, either suffering from knee OA or having an elevated risk of developing the disease.
Outputs are summarized in a KOALA report that can be viewed on any FDA approved DICOM viewer workstation. KOALA operates in a Linux environment and can be deployed to be compatible with any operating system supporting the third-party software Docker. The integration environment has to support KOALA data input and output requirements. The device does not interact with the patient directly, nor does it control any life-sustaining devices.
Mentions image processing
Yes
Mentions AI, DNN, or ML
The predicate and subject software utilize computer vision and machine learning algorithms trained on medical images.
Input Imaging Modality
computed (CR) or directly digital (DX) images
Anatomical Site
Joint (knee)
Indicated Patient Age Range
Adult patients
Intended User / Care Setting
trained professionals including, but not limited to, radiologists, orthopedics, physicians and medical technicians.
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
The company performed standalone clinical performance validation on a dataset of images from a large longitudinal US study, Osteoarthritis Initiative (OAI) study. This dataset contained a total of 6597 radiographs, representing 1149 individuals for which ground truth grading for Kellgren Lawrence grades, as well as osteophyte, sclerosis and joint space narrowing grades according to the OARSI (Osteoarthritis Research Society International) guidelines, was established by three physicians following adjudication procedures for discrepancies.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Software verification and validation testing was completed for the subject device. The software functioned as intended and all results observed were as expected.
The company performed standalone clinical performance validation on a dataset of images from a large longitudinal US study, Osteoarthritis Initiative (OAI) study. This dataset contained a total of 6597 radiographs, representing 1149 individuals.
The quality of the joint space width (JSW) measurements was quantified by orthogonal linear regression against reference measurements. The performance of the indicators was assessed by calculating its accuracy matrix) aqainst the reference standard and calculating sensitivity and specificity.
The status indicator outputs of KOALA performed as follows:
Kellgren-Lawrence status (KL >= 2): Sensitivity 0.87 (0.84, 0.9), Specificity 0.83 (0.8, 0.86)
Joint Space Narrowing Status (JSN OARSI grade > 0): Sensitivity 0.83 (0.8, 0.86), Specificity 0.8 (0.76, 0.83)
Osteophytosis status (Ost OARSI grade > 0): Sensitivity 0.86 (0.81, 0.9), Specificity 0.79 (0.76, 0.83)
Sclerosis status (Scl OARSI grade > 0): Sensitivity 0.82 (0.8, 0.87), Specificity 0.8 (0.76, 0.83)
In addition, the accuracy of the joint space width measurements was compared to equivalent measurements also provided as part of the outputs from the longitudinal study mentioned above, using orthogonal linear regressions.
Medial: Slope 1.02 (0.99 ; 1.05), Intercept [mm] -0.08 (-0.22 ; 0.03)
Lateral: Slope 0.97 (0.93 ; 1.00), Intercept [mm] 0.08 (-0.15 ; 0.30)
The analysis supports good agreement between the two sets of measurements.
In summary, performance validation data establish that KOALA is an effective image processing device that provides reliable measurements and accurate indicators for presence/absence of radiographic features relevant for the diagnosis and classification of osteoarthritis. Thus, the device performs as intended and is substantially equivalent to the predicate device.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Kellgren-Lawrence status (KL >= 2): Sensitivity 0.87 (0.84, 0.9), Specificity 0.83 (0.8, 0.86)
Joint Space Narrowing Status (JSN OARSI grade > 0): Sensitivity 0.83 (0.8, 0.86), Specificity 0.8 (0.76, 0.83)
Osteophytosis status (Ost OARSI grade > 0): Sensitivity 0.86 (0.81, 0.9), Specificity 0.79 (0.76, 0.83)
Sclerosis status (Scl OARSI grade > 0): Sensitivity 0.82 (0.8, 0.87), Specificity 0.8 (0.76, 0.83)
Predicate Device(s)
Reference Device(s)
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 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).
0
November 5, 2019
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 features the letters 'FDA' in a blue square, followed by the words 'U.S. FOOD & DRUG ADMINISTRATION' in blue text.
IB Lab GmbH % John J. Smith, M.D., J.D. Regulatory Counsel Hogan Lovells US LLP Columbia Square 555 Thirteenth Street, NW WASHINGTON DC 20004
Re: K192109
Trade/Device Name: KOALA Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ, JAK Dated: October 11, 2019 Received: October 11, 2019
Dear Dr. Smith:
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 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
2
Indications for Use
510(k) Number (if known) K192109
Device Name KOALA
Indications for Use (Describe)
IB Lab KOALA is a radiological fully-automated image processing software 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 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, orthopedics, physicians and medical technicians.
| Type of Use (Select one or both, as applicable) |
|---|
| ------------------------------------------------- |
× | Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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3
Submitter
IB Lab GmbH Hietzinger Hauptstrasse 50/10 1130 Vienna, Austria Phone: +43 1 9051206 Contact Person: Dr. Richard Ljuhar Date Prepared: October 11, 2019
Name of Device: KOALA Classification Name: Picture archiving and communications system (21 C.F.R. 892.2050) Regulatory Class: Class II Product Code: LLZ/892.2050, JAK/892.1750
Predicate Device: Ortho Kinematics, Inc.'s VMA™ System version 3.0 (K172327)
Reference Device: Zebra Medical Vision Ltd.'s HealthCCS (K172983)
Device Description
The Knee OsteoArthritis Labeling Assistant (KOALA) software provides metric measurements of the ioint space width and indicators for presence of radiographic features of osteoarthritis (OA) on posterior-anterior-posterior (PA/AP) knee X-ray images. The outputs aid clinical professionals who are interested in the analysis of knee OA in adult patients, either suffering from knee OA or having an elevated risk of developing the disease.
Outputs are summarized in a KOALA report that can be viewed on any FDA approved DICOM viewer workstation. KOALA operates in a Linux environment and can be deployed to be compatible with any operating system supporting the third-party software Docker. The integration environment has to support KOALA data input and output requirements. The device does not interact with the patient directly, nor does it control any life-sustaining devices.
Intended Use / Indications for Use
IB Lab KOALA 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 OARSI criteria for these parameters; and, the presence or absence of radiographic knee OA based on Kellgren & Lawrence Grading, 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, orthopedics, physicians and medical technicians.
4
Summary of Technological Characteristics
The following technological similarities and differences exist between the subject and predicate devices. The predicate and subject software utilize computer vision and machine learning algorithms trained on medical images. The machine-learning algorithms allow for high accuracy in the detection and measurement of OA related symptoms visible on knee radiographs.
| Feature | IB Lab's KOALA Software
(Subject Device) | Ortho Kinematics,
Inc.'s VMA System
(K172327, Predicate
Device) | Zebra Medical Vision Ltd.'s
HealthCCS Software
(K172983, Reference Device) |
|---------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------|----------------------------------------------------------------------------------|
| Classification
Name and
Product Code | System, Image Processing,
Radiological (LLZ) | System, Image
Processing, Radiological
(LLZ) | Computed Tomography X-Ray
System (JAK) |
| Runs on Server | Yes | Yes | Yes |
| Image Input | DICOM compliant images
collected in other devices in
either digitally computed (CR) or
directly digital (DX) formats | DICOM compliant
images inputted from
cleared PACS | DICOM |
| Anatomical Area | Joint (knee) | Spine | Heart (coronary artery) |
| Image
Processing | Knee detection;
Landmark detection;
Joint space detection | Semi-automated
vertebral body
templating and tracking | Calcification location marking |
| Measurements | Yes | Yes | Yes |
| Grading based
on
measurements | Yes, cutoffs on grades | No | Yes |
| Human
Intervention for
interpretation | Required | Required | Required |
| Intended User | Trained professionals | Physicians and clinical
professionals | Health care professionals |
A table comparing the key features of the subject and predicate devices is provided below.
Performance Data
Software verification and validation testing was completed for the subject device. The software functioned as intended and all results observed were as expected.
The company performed standalone clinical performance validation on a dataset of images from a large longitudinal US study, Osteoarthritis Initiative (OAI) study. This dataset contained a total of 6597 radiographs, representing 1149 individuals for which ground truth grading for Kellgren
5
Lawrence grades, as well as osteophyte, sclerosis and joint space narrowing grades according to the OARSI (Osteoarthritis Research Society International) guidelines, was established by three physicians following adjudication procedures for discrepancies.
The quality of the joint space width (JSW) measurements was quantified by orthogonal linear regression against reference measurements. The performance of the indicators was assessed by calculating its accuracy matrix) aqainst the reference standard and calculating sensitivity and specificity.
The status indicator outputs of KOALA performed as follows
| Status Indicator | Sensitivity
(95% CI) | Specificity
(95% CI) |
|-------------------------------------------------------|-------------------------|-------------------------|
| Kellgren-Lawrence status
(KL ≥ 2) | 0.87
(0.84, 0.9) | 0.83
(0.8, 0.86) |
| Joint Space Narrowing Status
(JSN OARSI grade > 0) | 0.83
(0.8, 0.86) | 0.8
(0.76, 0.83) |
| Osteophytosis status
(Ost OARSI grade > 0 ) | 0.86
(0.81, 0.9) | 0.79
(0.76, 0.83) |
| Sclerosis status
(Scl OARSI grade > 0 ) | 0.82
(0.8, 0.87) | 0.8
(0.76, 0.83) |
In addition, the accuracy of the joint space width measurements was compared to equivalent measurements also provided as part of the outputs from the longitudinal study mentioned above, using orthogonal linear regressions.
| | Slope | Intercept
[mm] |
|---------|-----------------------|-------------------------|
| Medial | 1.02
(0.99 ; 1.05) | -0.08
(-0.22 ; 0.03) |
| Lateral | 0.97
(0.93 ; 1.00) | 0.08
(-0.15 ; 0.30) |
The analysis supports good agreement between the two sets of measurements.
In summary, performance validation data establish that KOALA is an effective image processing device that provides reliable measurements and accurate indicators for presence/absence of radiographic features relevant for the diagnosis and classification of osteoarthritis. Thus, the device performs as intended and is substantially equivalent to the predicate device.
Conclusions
KOALA is as safe and effective as the predicate device. The subject device has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences between subject and predicate device in indications 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 demonstrate that the device performs as intended. Thus, KOALA is substantially equivalent.