Manual vs threshold-based segmentations including patients with pneumonia and COVID-19
>1 (expert radiologist)
Low Attenuation Area (LAA) quantification
—
—
PCC: 0.99
—
—
Manual vs threshold-based segmentations including healthy and diseased patients
>1 (expert radiologist)
Lung segmentation
Deep learning model
—
PCC: 0.977-0.992; DICE: 0.98-0.99
—
—
One internal and two external datasets
>1 (expert radiologist)
Indications for Use
ClariPulmo is a non-invasive image analysis software for use with CT images which is intended to support the quantification of lung CT images. The software is designed to support the physician in the diagnosis and documentation of pulmonary tissue images (e.g., abnormalities) from the CT thoracic datasets. (The software is not intended for the diagnosis of pneumonia or COVID-19). The software provides automation of the lungs and quantification of low-attenuation areas within the segmented lungs by using predefined Hounsfield unit thresholds. The software displays by color the segmented lungs and analysis results. ClariPulmo provides optional denoising and kernel normalization functions for improved quantification of lung CT images in cases when CT images were taken at low-dose conditions or with sharp reconstruction kernels.
Device Story
ClariPulmo is a standalone software application for lung CT image analysis. It takes thoracic CT datasets as input. The device uses a pre-trained deep learning model for automatic lung segmentation. It quantifies low-attenuation areas (LAA) and high-attenuation areas (HAA) using predefined Hounsfield unit thresholds. Optional U-Net based algorithms perform kernel normalization (sharp to smooth kernel) and denoising (low-dose to enhanced quality) to improve quantification. The software displays segmented lungs and analysis results via color overlays, tables, and charts. It is used by physicians in clinical settings to support diagnosis and documentation of pulmonary tissue abnormalities. The output assists clinicians in quantifying lung tissue density, which can aid in assessing lung conditions. It does not perform automated diagnosis of pneumonia or COVID-19.
Clinical Evidence
No clinical data. Non-clinical performance testing included bench testing of HAA/LAA analysis and AI-based segmentation/denoising/normalization. HAA analysis showed PCC 0.980–0.983; LAA analysis showed PCC 0.99. AI-based lung segmentation demonstrated PCC 0.977–0.992 and DICE coefficients 0.98–0.99 across various subgroups (normal/LAA/HAA, scanner types, kernels, low-dose).
Technological Characteristics
Standalone software for CT image processing. Uses deep learning (U-Net architecture) for segmentation, denoising, and kernel normalization. Operates on thoracic CT datasets. Complies with DICOM (NEMA-PS 3.1-3.20) and ISO 14971 risk management standards.
Indications for Use
Indicated for adult patients receiving lung CT to support quantification of lung CT images, including segmentation and analysis of low-attenuation and high-attenuation areas. Not indicated for diagnosis of pneumonia or COVID-19.
Regulatory Classification
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.
Special Controls
*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).
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April 6, 2022
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which consists of the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" in blue, and then the word "ADMINISTRATION" in a smaller font size below that.
ClariPi Inc. % Harry Park President ClariPi Detroit Office 1645 Park Creek Ct. Rochester Hills DETROIT MI 48309
Re: K203783
Trade/Device Name: ClariPulmo Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: March 31, 2022 Received: March 31, 2022
Dear Mr. Park:
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
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requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (OS) 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,
Laurel Burk, Ph.D Assistant Director Diagnostic X-ray Systems Team Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K203783
Device Name ClariPulmo
Indications for Use (Describe)
ClariPulmo is a non-invasive image analysis software for use with CT images which is
intended to support the quantification of lung CT images. The software is designed to support the physician in the diagnosis and documentation of pulmonary tissue images (e.g., abnormalities) from the CT thoracic datasets. (The software is not intended for the diagnosis of preumonia or COVID-19). The software provides automation of the lungs and quantification of low-attenuation areas within the segmented lungs by using predefined Hounsfield unit thresholds. The software displays by color the segmented lungs and analysis results. ClariPulmo provides optional denoising and kernel normalization functions for improved quantification of lung CT images in cases when CT images were taken at low-dose conditions or with sharp reconstruction kernels.
| 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/1 description: The image shows the logo for "Clariπ Medical Imaging Solutions". The word "Clari" is in bold black font, followed by a blue pi symbol. Below the word "Clariπ" is the text "MEDICAL IMAGING SOLUTIONS" in a smaller, thinner font. The logo is simple and professional, and it is likely used to represent a company that provides medical imaging solutions.
This 510(k) Summary is being submitted in accordance with the requirements of as required by section 807.92(c).
- SUBMITTER .
ClariPi Inc. 2F~4F, 11, Ihwajang-1 gil, Jongno-gu Seoul, Republic of Korea [03088]
Tel: +82-2-741-3014 Fax: +82-2-743-3014 Email: claripi@claripi.com
Contact person: Mr. Harry Park, ClariPi USA Date Prepared: April 6, 2022
- II. DEVICE
Device Name: ClariPulmo Common or Usual Name: Radiological Image Processing Software Regulation Name: "Medical Image Management and Processing System" Regulation Number: 21 CFR 892.2050 Regulatory Class: II K-Number: K203783 Product Code: LLZ
### III. PREDICATE DEVICE
The following table shows the predicate devices of the proposed ClariPulmo:
| Device Classification<br>Name | System, Image processing, Radiological<br>(Predicate device) | | |
|--------------------------------|------------------------------------------------------------------------|--|--|
| 510(k) Number | K103480 | | |
| Device Name | THORACIC VCAR | | |
| Applicant | GE MEDICAL SYSTEMS, LLC<br>3000 N GRANDVIEW<br>Waukesha, WI 53188, USA | | |
| Regulation Number | 892.2050 | | |
| Classification Product<br>Code | LLZ | | |
| Date Received | 11/26/2010 | | |
| Decision Date | 03/07/2011 | | |
| 510k Review Panel | Radiology | | |
The proposed ClariPulmo and its predicate devices. THORACIC VCAR (K103480) is substantially equivalent regarding its intended use, clinical indications, and principle of operation.
Further to the predicate device, ClariPi has identified the following currently marketed devices as reference devices of proposed ClariPulmo:
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Image /page/4/Picture/1 description: The image shows the logo for ClariPi Medical Imaging Solutions. The word "Clari" is written in bold, black letters. To the right of "Clari" is a blue symbol that resembles the mathematical symbol pi. Below the word "Clari" is the phrase "MEDICAL IMAGING SOLUTIONS" in smaller, black letters.
| Device<br>Classification<br>Name | System, X-Ray,<br>Tomography,<br>Computed<br>(Reference<br>Device) | System, X-Ray,<br>Tomography,<br>Computed<br>(Reference<br>Device) | System, Image<br>processing,<br>Radiological<br>(Reference<br>Device) |
|------------------------------------|----------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|
| 510(k) Number | K141069 | K200990 | K183460 |
| Device Name | Imbio CT Lung<br>Density Analysis<br>Software | VIDA vision<br>(formerly VIDA<br>Pulmonary<br>Workstation 2<br>(PW2)) | ClariCT.AI |
| Applicant | IMBIO LLC<br>227 COLFAX AVE<br>NSUITE 144<br>Minneapolis, MN 5<br>5405 USA | VIDA Diagnostics,<br>Inc. 500 Crosspark<br>Rd. W250<br>BioVentures Center<br>Coralville, IA 52241<br>USA | ClariPi Inc.<br>3F, 70-15,<br>Ihwajang-gil,<br>Jongno-gu, Seoul,<br>Republic of Korea<br>03088 |
| Regulation<br>Number | 892.1750 | 892.1750 | 892.2050 |
| Classification<br>Product Code | JAK | JAK | LLZ |
| Date Received | 04/24/2014 | 04/15/2020 | 12/13/2018 |
| Decision Date | 09/17/2014 | 08/07/2020 | 06/13/2019 |
| Decision | Substantially<br>Equivalent (SE) | Substantially<br>Equivalent (SE) | Substantially<br>Equivalent (SE) |
| Regulation<br>Medical<br>Specialty | Radiology | Radiology | Radiology |
The Imbio CT Lung Density Analysis Software (K141069), VIDA|vision (formerly VIDA Pulmonary Workstation 2 (PW2)) (K200990) and ClariCT.Al (K183460) are reference devices for additional technologies and support the addition application functionalities and enhanced capabilities.
## IV. DEVICE DESCRIPTION
ClariPulmo is a standalone software application analyzing lung CT images that can be used to support the physician in the quantification of lung CT image when examining pulmonary tissues.
ClariPulmo provides two main and optional functions:
- LAA Analysis provides quantitative measurement of pulmonary tissue image with low . attenuation areas (LAA). LAA are measured by counting those voxels with low attenuation values under the user-predefined thresholds within the segmented lungs. This feature supports the physician in quantifying lung tissue image with low attenuation area.
- HAA Analysis provides quantitative measurement of pulmonary tissue image with high attenuation areas (HAA). HAA are measured by counting those voxels with high attenuation
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Image /page/5/Picture/1 description: The image shows the logo for ClariPi Medical Imaging Solutions. The word "Clari" is in black, followed by a blue pi symbol. Below the word "Clari" is the text "MEDICAL IMAGING SOLUTIONS" in a smaller font size.
values using the user-predefined thresholds within the seamented lungs. This feature supports the physician in quantifying lung tissue image with high attenuation area.
- Lungs are automatically segmented using a pre-trained deep learning model.
- The optional Kernel Normalization function provides an image-to-image translation from a sharp kernel image to a smooth kernel image for improved quantification of lung CT images. The Kernel Normalization algorithm was constructed based on the U-Net architecture.
- The optional Denoising function provides an image-to-image translation from a noisy lowdose image to a noise-reduced enhanced quality image of LDCT for improved quantification of lung LDCT images. The Denoising algorithm was constructed based on the U-Net architecture.
The ClariPulmo software provides summary reports for measurement results that contains color overlay images for the lungs tissues as well as table and charts displaying analysis results.
## V. INDICATIONS FOR USE
ClariPulmo is a non-invasive image analysis software for use with CT images which is intended to support the quantification of lung CT images. The software is designed to support the physician in the diagnosis and documentation of pulmonary tissue images (e.g., abnormalities) from the CT thoracic datasets. (The software is not intended for the diagnosis of pneumonia or COVID-19). The software provides automated segmentation of the lungs and quantification of low-attenuation and high-attenuation areas within the segmented lungs by using predefined Hounsfield unit thresholds. The software displays by color the segmented lungs and analysis results. ClariPulmo provides optional denoising and kernel normalization functions for improved quantification of lung CT images in cases when CT images were taken at low-dose conditions or with sharp reconstruction kernels.
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Image /page/6/Picture/1 description: The image shows the logo for ClariPi Medical Imaging Solutions. The logo features the word "Clari" in bold, black letters, followed by a stylized blue pi symbol. Below the word "ClariPi" is the text "MEDICAL IMAGING SOLUTIONS" in a smaller, sans-serif font.
# vi. INTENDED POPULATION
The device is intended for adult patients receiving lung CT.
## VII. SUBSTANTIAL EQUIVALENCE TABLE
| Feature | ClariPulmo<br>(Subject<br>Device) | Thoracic<br>VCAR<br>K103480<br>(Predicate<br>Device) | Imbio CT<br>Lung Density<br>Analysis<br>Software<br>K141069<br>(Reference<br>Device) | VIDA vision<br>(formerly VIDA<br>Pulmonary<br>Workstation 2<br>(PW2))<br>K200990<br>(Reference<br>Device) | ClariCT.AI<br>K183460<br>(Reference<br>Device) |
|---------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------|
| Algorithm | Deep<br>learning | unknown | Image post-<br>processing<br>algorithm | Self-contained<br>image<br>analysis | Deep<br>learning |
| Modality | CT | CT | CT | CT | CT |
| Type of scan | Thoracic<br>CT | Thoracic<br>CT | Thoracic CT | Thoracic CT | Head,<br>heart, chest<br>and<br>abdomen<br>CT |
| DICOM standard | Yes | Yes | Yes | Yes | Yes |
| Automatic segmentation<br>of both the left and right<br>lungs and airways | Yes | Yes | Yes | Yes | Not relevant |
| Lung volume analysis<br>support: Both, Left, and<br>Right Lungs | Yes | Yes | Yes | Yes | Not relevant |
| Low attenuation analysis | Yes<br>Lung<br>density<br>result<br>quantificati<br>on with HU<br>density<br>range,<br>volume<br>measurem<br>ent, lung<br>density<br>index and<br>Perc15<br>measurem<br>ent | Yes<br>Lung<br>density<br>result<br>quantificati<br>on with HU<br>density<br>range,<br>volume<br>measurem<br>ent | Yes<br>Lung density<br>result<br>quantification<br>with HU<br>density<br>range,<br>volume<br>measurement<br>, lung density<br>index and<br>PercX (where<br>"X"<br>corresponds<br>to the desired<br>percentile)<br>calculated in<br>the<br>Inspiration<br>Assessment | Yes<br>Lung density<br>result<br>quantification<br>with HU<br>density range,<br>volume<br>measurement,<br>lung density<br>index and<br>Perc15<br>measurement | Not relevant |
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Image /page/7/Picture/1 description: The image is a logo for a company called "ClariPi MEDICAL IMAGING SOLUTIONS". The word "Clari" is in black, and the "Pi" is in blue. Underneath the word "ClariPi" is the phrase "MEDICAL IMAGING SOLUTIONS".
| High attenuation analysis | | | | | |
|------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|---------|--------------|
| | Yes<br>Lung<br>density<br>result<br>quantificati<br>on with HU<br>density<br>range and<br>volume<br>measurem<br>ent based<br>on selected<br>HU ranges<br>set by user | Yes<br>Lung<br>density<br>result<br>quantificati<br>on with HU<br>density<br>range and<br>volume<br>measurem<br>ent based<br>on selected<br>HU ranges<br>set by user | Not<br>supported | unknown | Not relevant |
| Adjustable density<br>thresholds for refining<br>and optimizing HU range | Yes | Yes | Not<br>supported | Yes | Not relevant |
| Viewer displays lung<br>density in color<br>according to Hounsfield<br>Unit (HU) range. | Yes | Yes | Yes | Yes | Not relevant |
| Viewer displays density<br>graph/histogram of the<br>classified lung voxels'<br>relative frequencies | Yes | Unknown | Yes | Yes | Not relevant |
| Report includes overlay<br>of density quantification<br>results and density graph<br>histogram | Yes | Unknown | Yes | Yes | Not relevant |
| Low-dose CT support | Yes | Not<br>supported | Yes | Yes | Yes |
## VIII. PERFORMANCE TESTING
Non-clinical performance testing has been performed on ClariPulmo (the subject device) to support the safety and effectiveness of the features including the HAA and LAA analysis, Al-based lung seqmentation, Al-based kernel normalization and denoising.
The HAA analysis showed excellent agreement (PCC: 0.980 – 0.983) with expert-established seqmentations of user-defined high attenuation areas. The test dataset used for manual vs threshold-based segmentations included patients with pneumonia and COVID-19.
The LAA analysis showed excellent agreement (PCC: 0.99) with expert-established segmentations of user-defined low attenuation areas. The test dataset used for manual vs threshold-based segmentations included both health and diseased patients.
The Al-based lung segmentation demonstrated excellent agreements with that by expert radiologist's imageJ based segmentation for one internal and two external datasets showing PCC of 0.977-0.992 and DICE coefficients of 0.98~0.99 with statistical significance across normal/LAA/HAA patients, CT scanner, reconstructed kernel and low-dose subgroups . The submitted performance testing data demonstrates compliance with the following International and FDA-recognized consensus standards and FDA guidance document:
- ISO 14971 Medical devices Application of risk management to medical devices. ●
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Image /page/8/Picture/1 description: The image shows the logo for "Clariπ MEDICAL IMAGING SOLUTIONS". The word "Clari" is in black, and the pi symbol is in blue. Below the word "Clariπ" is the text "MEDICAL IMAGING SOLUTIONS" in a smaller font.
- NEMA-PS 3.1- PS 3.20 Digital Imaging and Communications in Medicine (DICOM). ●
- Guidance for the Content of Premarket Submissions for Software Contained in Medical ● Devices issued May 11, 2005.
- Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices issued September 6, 2017.
- . The subject device, was tested in accordance with the internal Verification and Validation processes of ClariPi Inc. Verification and Validation tests have been performed to address intended use, the technological characteristics claims, requirement specifications, and the risk management results.
The test results in this 510(k), demonstrate that ClariPulmo:
- complies with the aforementional and FDA-recognized consensus standards and .
- . FDA quidance document, and
- . meets the acceptance criteria and is adequate for its intended use.
Therefore, ClariPulmo, is substantially equivalent to the currently marketed predicate device, in terms of safety and effectiveness.
#### Clinical Testing:
ClariPulmo does not require clinical studies to demonstrate substantial equivalence to the predicate device.
### IX. CONCLUSIONS
Verification and Validation activities required to establish the safety and effectiveness of ClariPulmo were performed. Testing involved system level tests, performance tests, and safety testing from risk analysis. Testing performed, demonstrated the subject device meets pre-defined functionality requirements.
The subject device and predicate device are substantially equivalent in the areas of technical characteristics, general function, and intended use does not raise any new potential risks and is equivalent in performance to existing legally marketed devices. Nonclinical tests demonstrate that the subject device is as safe and therefore substantially equivalent to the predicate device.
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In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.