(16 days)
Lung CAR I.1 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the lung derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of lung lesions (e.g. nodules). The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting either a single or double seed point followed by interactive fine-tuning the boundaries of the ROI. Lung CAR 1.1 provides quantative information for measurement of lesion volume and other measured characteristics over time allowing the user to review and track any changes in the physician-indicated nodules or lesions.
Lung CAR 1.1 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the nonenhanced view.
Lung CAR™ (Computer Assisted Reader) 1.1 is a software tool designed to assist radiologists and other clinicians in the evaluation of nodules and other lesions in the lug. The software allows the user to select Regions of Interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of nodules and other lesions, and measurement of nodule characteristics such as size and volume. The further features of Lung CAR™ 1.1 as compared to the cleared device are a series of filters, the results of which are presented in a Joint Reader filter view (enhanced and non-enhanced data viewed simultaneously). These filters are an edge enhancement filter, noise removal filters and a sphericity filter. The sphericity filter enhances structures of images with spherical elements within certain Hounsfield Unit (HU) ranges that are defined by the user. This enhancement can aid the user when looking at a highlighted area (sphere) as a potential spherical nodule.
Given the provided documentation, I can extract information related to the device description, intended use, and comparison to predicate devices, but there is no information about acceptance criteria or a specific study that proves the device meets acceptance criteria. The text focuses on establishing substantial equivalence to existing predicate devices for regulatory approval, rather than detailing a performance study with acceptance criteria.
The document is a 510(k) summary of safety and effectiveness for Medicsight Lung CAR™ Release 1.1. It states that "Test data are provided to validate the performance of the system and its substantial equivalence to the predicate devices." However, these "test data" are not described in this summary.
Therefore, I cannot fulfill all parts of your request. I will report on what is available and indicate where information is missing.
Here's a breakdown of the available information and what is missing:
1. A table of acceptance criteria and the reported device performance:
- Missing. The document does not provide a table of acceptance criteria or reported device performance metrics against specific criteria. It asserts substantial equivalence based on functional features and intended use.
2. Sample size used for the test set and the data provenance:
- Missing. The document mentions "Test data are provided to validate the performance," but does not specify the sample size of the test set, the country of origin of the data, or whether it was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Missing. This information is not present in the provided text.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Missing. This information is not present.
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:
- Missing. The document does not describe an MRMC study or any quantitative improvement in human reader performance with the device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The device is described as "designed to assist radiologists and other clinicians," indicating it's a human-in-the-loop system, not a standalone algorithm for diagnosis. No standalone performance study details are provided.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Missing. The document does not specify how ground truth was established for any test data.
8. The sample size for the training set:
- Missing. No information on a training set is provided.
9. How the ground truth for the training set was established:
- Missing. No information on a training set or its ground truth establishment is provided.
Summary of available information:
- Device Name: Lung CAR™ Release 1.1
- Manufacturer: Medicsight PLC.
- Intended Use: PC-based, stand-alone, non-invasive, image analysis software for display and visualization of 2D and 3D medical image data of the lung from CT scans, to assist clinicians in evaluating lung lesions (e.g., nodules). It allows manual or semi-automatic Region of Interest (ROI) extraction and provides quantitative information for measurement of lesion volume and other characteristics for tracking changes over time. It also contains additional imaging tools for enhancement.
- Predicate Devices:
- Conclusion of document: "Lung CAR 1.1 does not raise any new potential safety risks and is equivalent in performance to existing legally marketed devices. Lung CAR 1.1 is therefore substantially equivalent with respect to safety and effectiveness to the predicate devices."
The document functions as a regulatory submission (510(k) summary) aiming to establish substantial equivalence for market clearance, rather than a detailed scientific study report. Therefore, detailed performance metrics, study designs, sample sizes, and ground truth methodologies are not typically included in this type of summary.
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Image /page/0/Picture/0 description: The image shows a stylized eye with a white ring around the iris. The background is black, which contrasts with the white ring and the detailed texture of the iris. The iris has a lighter spot, possibly a reflection, adding depth to the image. The overall design is simple yet striking, focusing on the eye as a central element.
JUL 2 2 2004
Appendix E
510(k) SUMMARY OF SAFETY AND EFFECTIVENESS
This summary of safety and effectiveness information is being submitted in accordance with the requirements of 21 CFR 807.92( c ). ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Submitted by: | |
|---|---|
| Name: | Medicsight PLC. |
| Address: | 46 Berkeley SquareLondon W1J 5ATUK |
| Telephone: | 44 (0) 207 598 4070 |
| Facsimile: | 44 (0) 207 598 4071 |
| Contact: | Carol MacDonald, RA QA Director |
| Date of summary: | 1st July 2004 |
Device Information:
| Trade Name: | Lung CAR™ Release 1.1 |
|---|---|
| Common Name: | Medical imaging software for CT scanners |
| Classification Name: | Computed Tomography X-Ray System, Accessory |
| Regulation Number: | 892.1750 |
Predicate Devices:
Medicsight Lung CAR 1.1 is substantially equivalent to the following devices:
| Manufacturer | Device | 510(k) No. |
|---|---|---|
| MEDICSIGHT | MEDICLUNG 1.0 | K033412 |
| SIEMENS | LUNGCARE CT (with extended functionality NEV) | K033374 |
| GE | ADVANCED LUNG ANALYSIS | K013381 |
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Image /page/1/Picture/0 description: The image shows a black and white graphic of an eye. The eye is surrounded by a partial ring, resembling the letter 'C'. The eye itself has a visible pupil and iris, with some texture suggesting detail. The overall image has a stark contrast between the black background and the white elements of the eye and ring.
Device Description:
Lung CAR™ (Computer Assisted Reader) 1.1 is a software tool designed to assist radiologists and other clinicians in the evaluation of nodules and other lesions in the lug. The software allows the user to select Regions of Interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of nodules and other lesions, and measurement of nodule characteristics such as size and volume. The further features of Lung CAR™ 1.1 as compared to the cleared device are a series of filters, the results of which are presented in a Joint Reader filter view (enhanced and non-enhanced data viewed simultaneously). These filters are an edge enhancement filter, noise removal filters and a sphericity filter. The sphericity filter enhances structures of images with spherical elements within certain Hounsfield Unit (HU) ranges that are defined by the user. This enhancement can aid the user when looking at a highlighted area (sphere) as a potential spherical nodule.
Intended Use:
Lung CAR I.1 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the lung derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of lung lesions (e.g. nodules). The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting either a single or double seed point followed by interactive fine-tuning the boundaries of the ROI. Lung CAR I.1 provides quantative information for measurement of lesion volume and other measured characteristics over time allowing the user to review and track any changes in the physician-indicated nodules or lesions.
Lung CAR 1.1 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the nonenhanced view.
Comparison to Predicate Device:
As in the predicate devices, MedicLung 1.0, GE ALA and Siemens LungCare CT NEV, Lung CAR1.1 assists users in assessing CT images for the identification and evaluation of nodules and other lesions in the colon.
Test data are provided to validate the performance of the system and its substantial equivalence to the predicate devices. The functional features and the intended use of Lung CAR 1.1 are substantially equivalent to the predicate devices. The modifications to the original device did not introduce any new potential safety risks.
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Image /page/2/Picture/0 description: The image shows a stylized logo featuring an eye within a partial circle. The eye is detailed with a pupil and iris, suggesting a realistic representation. The partial circle surrounds the eye, creating a 'C' shape that frames the eye. The logo has a simple, monochrome color scheme, with the eye and 'C' shape appearing in white against a black background.
Safety:
A comprehensive hazard analysis was carried out on Lung CAR 1.1, which concluded that any residual risks were as low as reasonably practicable and judged as acceptable when weighed against the intended benefits of use of the system.
Conclusion:
Lung CAR 1.1 does not raise any new potential safety risks and is equivalent in performance to existing legally marketed devices. Lung CAR 1.1 is therefore substantially equivalent with respect to safety and effectiveness to the predicate devices.
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DEPARTMENT OF HEALTH & HUMAN SERVICES
Image /page/3/Picture/1 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo consists of a stylized abstract design resembling an eagle or bird-like figure. The text "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" is arranged in a circular fashion around the emblem.
Public Health Service
MAR 1 1 2009
Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
Ms. Carol MacDonald Regulatory & Quality Director Medicsight 46 Berkeley Square London W1J5AT UNITED KINGDOM
Re: K041807 Trade/Device Name: Medicsight Lung 1.1 Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: OEB Dated: July 1, 2004 Received: July 6, 2004
Dear Ms. MacDonald:
This letter corrects our substantially equivalent letter of July 22, 2004.
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. 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.
If vour device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to such 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.
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Page 2
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; good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
This letter will allow you to begin marketing your device as described in your Section 510(k) premarket notification. The FDA finding os substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Office of Compliance at one of the following numbers, based on the regulation number at the top of this letter.
| 21 CFR 876.xxx | (Gastroenterology/Renal/Urology) | (240) 276-0115 |
|---|---|---|
| 21 CFR 884.xxx | (Obstetrics/Gynecology) | (240) 276-0115 |
| 21 CFR 892.xxx | (Radiology) | (240) 276-0120 |
| Other | (240) 276-0100 |
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding postmarket surveillance, please contact CDRH's Office of Surveillance and Biometrics' (OSB's) Division of Postmarket Surveillance at 240-276-3474. For questions regarding the reporting of device adverse events (Medical Device Reporting (MDR)), please contact the Division of Surveillance Systems at 240-276-3464. You may obtain other general information on your responsibilities under the Act from the Division of Small Manufactures, International and Consumer Assistance at its toll-free number (800) 638-2041 or (240) 276-3150 or at its Internet address http://www.fda.gov/cdrh/industry.suppot/index.html.
Sincerely yours,
Huld Leun
Lucinda M. Macias
Janin M. Morris Acting Director, Division of Reproductive. Abdominal, and Radiological Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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APPENDIX A
Page _ of _
510(k) Number (if known): _KD41807
Medicsight Lung CAR 1.1 Device Name:
Indications for Use:
Lung CAR I.1 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the lung derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of lung lesions (e.g. nodules). The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting either a single or double seed point followed by interactive fine-tuning the boundaries of the ROI. Lung CAR 1.1 provides quantative information for measurement of lesion volume and other measured characteristics over time allowing the user to review and track any changes in the physician-indicated nodules or lesions.
Lung CAR 1.1 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the nonenhanced view.
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE OF NEEDED)
Device Evaluation (ODE) Concurrence of
Prescription Use
(Division Sign-Off)
Division of Reproductive, Abdominal,
and Radiological Devices 4041807
K1OOLI Alba
§ 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).