(86 days)
Not Found
No
The description explicitly states the algorithm is based on "Non-Local Means filtering," which is a traditional image processing technique, not an AI/ML method. There is no mention of training data or models typically associated with AI/ML.
No.
This device is image processing software intended to improve the quality of medical images for diagnostic purposes, not to directly treat a medical condition or ailment.
No
The device is described as image processing software intended to enhance the quality of PET images (noise reduction, sharpening, resolution improvement) for radiologists and nuclear medicine physicians. It clarifies that "no new feature is introduced that did not exist in the PET data." Its purpose is to present existing information more clearly, not to provide a diagnosis itself.
Yes
The device is explicitly described as "medical image enhancement software, i.e., a Software as a Medical Device (SaMD)" and its function is solely image processing and enhancement of existing medical images. There is no mention of any accompanying hardware component that is part of the device itself.
Based on the provided information, Claritas iPET is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: In Vitro Diagnostics are devices intended for use in the examination of specimens derived from the human body in order to provide information for diagnostic, monitoring, or compatibility purposes. This typically involves analyzing biological samples like blood, urine, or tissue.
- Claritas iPET's Function: Claritas iPET is an image processing software that enhances medical images (PET, CT, MRI). It operates on image data obtained from the patient, not on biological specimens. Its purpose is to improve the visual quality of these images for interpretation by medical professionals.
Therefore, Claritas iPET falls under the category of medical image processing software, not In Vitro Diagnostics.
N/A
Intended Use / Indications for Use
Claritas iPET is an image processing software intended for use by radiologists and nuclear medicine physicians for noise reduction, sharpening, and resolution improvement of PET images (including PET/CT and PET/MRI) obtained with any kind of radionuclides, e.g. fluorodeoxyglucose (FDG). Enhanced images will be saved in DICOM files and exist in conjunction with original images.
Product codes (comma separated list FDA assigned to the subject device)
LLZ
Device Description
Claritas iPET v1.0 Image Enhancement System is a medical image enhancement software, i.e., a Software as a Medical Device (SaMD), that can be used to increase image quality by implementation of an image processing and image fusion algorithm.
Claritas iPET can be used to enhance Positron Emission Tomography (PET) images with optional simultaneous Magnetic Resonance Imaging (MRI) or Computerized Tomography (CT) scans of the same subject. Claritas iPET takes as input DICOM [Digital Imaging and Communications in Medicine] files of PET, MRI, and CT images, and produces an enhanced image of the same file. The objective is to enhance the DICOM files that are obscured and not clearly visible, to be more visible, sharper, and clearer through the Claritas iPET image enhancement process. Claritas iPET is intended to be used by radiologists and nuclear medicine physicians in hospitals, radiology centres and clinics, as well as by medical universities and research intuitions.
The image improvement includes noise reduction, sharpening of organ boundaries, and achieving super-resolution. With the help of Claritas iPET software, high quality PET scans can be produced. The Claritas iPET algorithm computes the fusion of functional (from PET) and anatomic (from MR or CT) information, and is based on Non-Local Means filtering. The goal of the software is to process and visualize the content of DICOM files storing 3D voxel arrays, i.e. a uniformly spaced sequence of slices of a PET scan. The processing algorithm may also input another 3D voxel array storing the density values obtained by a CT or MRI scan. The PET and CT/MR volumes should at least partially overlap to exploit the additional anatomic information. The CT or MR volume is expected to have a higher resolution than the PET volume in order for effective improvement. The sharpness. style and the detail of the visualization can be controlled by the user and can be compared to the visualization of the raw image data. During this process, no new feature is introduced that did not exist in the PET data, just the existing features are emphasized if they are also supported by the anatomy or suppressed if they are in the noise region and are not supported by the anatomy.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes (The predicate device implements an algorithm based on a trained convolutional network (CNN))
Input Imaging Modality
PET, PET/CT, PET/MRI
Anatomical Site
Not Found
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Radiologists and nuclear medicine physicians in hospitals, radiology centres and clinics, as well as by medical universities and research intuitions.
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
First option (Real human PET scans):
The dataset consisted of real full body human PET scans. A long scan was executed and accepted as ground truth. The PET scanning time was decomposed into uniform frames. Reconstruction process was executed for subsets of the original frames. Comparison was performed for the case when additional CT/MRI information was utilized by the Claritas iPET software.
Second option (Zubal mathematical phantom):
The Zubal mathematical phantom was used as the ground truth. Measured data were generated by adding multiplicative (Poisson) noise to the ground truth data.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Study type: Performance testing based on RMSE and SNR calculations.
Sample size: Not specified numerically beyond "real full body human PET scans" in option 1.
AUC: Not specified.
MRMC: Not specified.
Standalone performance: No, the performance is reported as comparison before and after processing as well as comparison against ground truth.
Key results:
- For real human PET scans (long scans considered as ground truth):
- RMSE decreased by at least 10%.
- SNR increased by at least 20%.
- For low dosage or short time scans, RMSE decreased by 50% and SNR increased by 4-5 times.
- All tests passed.
- For Zubal mathematical phantom:
- For high dosage and longer scans, 10-20% improvement in RMSE and SNR.
- Improvement grows rapidly for low dosage or short scans.
- This test passed.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Root Mean Square Error (RMSE), Signal to Noise Ratio (SNR)
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
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
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health and Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
Claritas HealthTech Pte. Ltd. % Devika Dutt COO 20A Tanjong Pagar Road Singapore, 088443 Singapore
Re: K213140
Trade/Device Name: Claritas iPET Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: September 24, 2021 Received: September 27, 2021
Dear Devika Dutt:
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
1
devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device 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.
Thalia T. Mills, PhD 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
| DEPARTMENT OF HEALTH AND HUMAN SERVICES | Form Approved: OMB No. 0910-0120 | |
|---|---|---|
| Food and Drug Administration | Expiration Date: 06/30/2023 | |
| Indications for Use | See PRA Statement below. | |
| 510(k) Number (if known) | K213140 | |
| Device Name | Claritas iPET | |
| Indications for Use (Describe) | Claritas iPET is an image processing software intended for use by radiologists and nuclear medicine physicians for noise reduction, sharpening, and resolution improvement of PET images (including PET/CT and PET/MRI) obtained with any kind of radionuclides, e.g. fluorodeoxyglucose (FDG). Enhanced images will be saved in DICOM files and exist in conjunction with original images. | |
| 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) |
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the
time to review instructions, search existing data sources, gather and maintain the data needed and complete
and review the collection of information. Send comments regarding this burden estimate or any other aspect
of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services
Food and Drug Administration
Office of Chief Information Officer
Paperwork Reduction Act (PRA) Staff
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of
information unless it displays a currently valid OMB number."
3
510(k) Summary
The following information is provided in accordance with 21 CFR 807.92 for the Premarket 510(k) Summary:
| Company: | Claritas HealthTech Pte. Ltd.
20A Tanjong Pagar Road
Singapore, Singapore 088443 |
|------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Contact: | Devika Dutt
COO
Claritas HealthTech Pte Ltd
20A Tanjong Pagar Road
Singapore, Singapore 088443
Telephone: (65) 9795-1921
d.d@claritasco.com |
| Date Summary Prepared: | September 23, 2021 |
5.1 Submitter Information
5.2 Name of the Device
| Trade Name: | Claritas iPET | |
|---|---|---|
| Model Number: | V1.0 | |
| Common Name: | Image Enhancement System | |
| Device: | System, Image Processing, Radiological | |
| Regulation Name: | Medical Imaging Management and Processing System | |
| Review Panel: | Radiology | |
| Regulation Number: | 21 CFR 892.2050 | |
| Device Class: | Class II | |
| Product Code: | LLZ |
5.3 Equivalence Claimed to Predicate Device
The Claritas iPET device is equivalent to the SubtlePET (K182336) device, manufactured by Subtle Medical, Inc.
4
| Trade Name: | SubtlePET |
|---|---|
| Manufacturer: | Subtle Medical, Inc., 880 Santa Cruz Ave, Suite 200Menlo Park, CA 94025 |
| Regulation Number: | 21 CFR 892.2050 |
| Regulation Name: | Picture archiving and communications system |
| Device Class: | Class II |
| Product Code: | LLZ |
| 510(k) Number: | K182336 |
5.4 Predicate Device Information
5.5 Indications for Use
510(k) Clearance Date:
Claritas iPET is an image processing software intended for use by radiologists and nuclear medicine physicians for noise reduction, sharpening, and resolution improvement of PET images (including PET/CT and PET/MRI) obtained with any kind of radionuclides, e.g. fluorodeoxyglucose (FDG). Enhanced images will be saved in DICOM files and exist in conjunction with original images.
November 30, 2018
5.6 Device Description
Claritas iPET v1.0 Image Enhancement System is a medical image enhancement software, i.e., a Software as a Medical Device (SaMD), that can be used to increase image quality by implementation of an image processing and image fusion algorithm.
Claritas iPET can be used to enhance Positron Emission Tomography (PET) images with optional simultaneous Magnetic Resonance Imaging (MRI) or Computerized Tomography (CT) scans of the same subject. Claritas iPET takes as input DICOM [Digital Imaging and Communications in Medicine] files of PET, MRI, and CT images, and produces an enhanced image of the same file. The objective is to enhance the DICOM files that are obscured and not clearly visible, to be more visible, sharper, and clearer through the Claritas iPET image enhancement process. Claritas iPET is intended to be used by radiologists and nuclear medicine physicians in hospitals, radiology centres and clinics, as well as by medical universities and research intuitions.
The image improvement includes noise reduction, sharpening of organ boundaries, and achieving super-resolution. With the help of Claritas iPET software, high quality PET scans can be produced. The Claritas iPET algorithm computes the fusion of functional (from PET) and anatomic (from MR or CT) information, and is based on Non-Local Means filtering. The goal of the software is to process and visualize the content of DICOM files storing 3D voxel arrays, i.e. a uniformly spaced sequence of slices of a PET scan. The processing algorithm may also input another 3D voxel array storing the density values obtained by a CT or MRI scan. The PET and CT/MR volumes should at least partially overlap to exploit the additional anatomic information. The CT or MR volume is expected to have a higher resolution than the
5
PET volume in order for effective improvement. The sharpness. style and the detail of the visualization can be controlled by the user and can be compared to the visualization of the raw image data. During this process, no new feature is introduced that did not exist in the PET data, just the existing features are emphasized if they are also supported by the anatomy or suppressed if they are in the noise region and are not supported by the anatomy.
5.7 Substantial Equivalence Comparison of Technological Characteristics
The predicate device, SublePET and the subject device, Claritas iPET have similar technological characteristics. Both devices implement an image enhancement algorithm as the core of their image enhancement software. The predicate device implements an algorithm based on a trained convolutional network (CNN) and the subject device implements an algorithm based on 3D non-local means using a guide from a different 3D scan. The algorithms implemented in both devices enhance the image and reduce noise. Both devices predict the voxel value as a weighted sum of the values in the neighbourhood. The difference between the two devices is that the predicate device, SubtlePET finds the weights with a trained CNN, while the subject device, Claritas iPET finds the weights using the statistical analysis of the PET data and the data of additional modalities (MRI / CT). Verification and Validation testing and Performance testing for the subject device have been done on static and dynamic PET, PET/MR and PET/CT scans, and the test results confirm that the subject device is as safe and effective as the predicate device, hence the differences in the technological characteristics do not raise new risks related to the safety and effectiveness.
The table below shows the similarities and differences between the technological characteristics of the two devices.
| Characteristics | Predicate Device | Subject Device |
|---|---|---|
| SubtlePET [K182336] | Claritas iPET [K213140] | |
| Device Class | Class II | Class II |
| Product Code | LLZ | LLZ |
| Intended Use | Image enhancement system which | |
| is an image processing software | ||
| for image enhancement of PET | ||
| images including PET/CT and | ||
| PET/MRI | Same | |
| Indications for | ||
| Use | SubtlePET is an image processing | |
| software intended for use by | ||
| radiologists and nuclear | ||
| medicine physicians for transfer, | ||
| storage, and noise reduction of | ||
| fluorodeoxyglucose (FDG) and | ||
| amyloid PET images (including | ||
| PET/CT and PET/MRI). | Claritas iPET is an image | |
| processing software intended for | ||
| use by radiologists and nuclear | ||
| medicine physicians for noise | ||
| reduction, sharpening, and | ||
| resolution improvement of PET | ||
| images (including PET/CT and | ||
| PET/MRI) obtained with any kind | ||
| of radionuclides, e.g. | ||
| fluorodeoxyglucose (FDG). | ||
| Enhanced images will be saved in | ||
| Characteristics | Predicate Device | Subject Device |
| SubtlePET [K182336] | Claritas iPET [K213140] | |
| DICOM files and exist in | ||
| conjunction with original images. | ||
| Physical | ||
| Characteristics | Software package that operates | |
| on a virtual machine (VM) | Software package that operates on a | |
| virtual machine (VM) or deployed | ||
| on a local computer. | ||
| Computer | Virtual machine host-compatible | |
| system | Virtual machine host-compatible | |
| system or local computer. | ||
| Image | ||
| Processing | ||
| Enhancement | ||
| Location | Onsite on the facility VM | |
| and/or offsite on the cloud VM, | ||
| depending on the site's | ||
| configuration | Same in case of the PACS integrated | |
| version. The stand-alone version | ||
| runs on the client computer. | ||
| DICOM | ||
| standard | ||
| Compliance | The software processes DICOM | |
| compliant image data | Same | |
| Operating | ||
| System | CentOS 7 Linux | Windows/Linux |
| Modalities | Multi-modality; specifically | |
| processes PET, PET/CT and | ||
| PET/MR images | Same | |
| User Interface | None - enhanced images are | |
| viewed on existing PACS | ||
| workstations | None - when integrated into existing | |
| PACS workstations, viewed on | ||
| existing PACS workstation. |
A user interface for stand-alone
version visualizing 2D slices and 3D
rendering for demo and research
purposes. |
| Protocols | Standard scanner protocols | Same |
| Core
Technology | Image Enhancement Algorithm | Same |
| Image
Enhancement
Algorithm
Description | The software employs a
convolutional neural network-
based method in a pixel's
neighborhood to generate the
value for each pixel. Using a
residual learning approach, the
software predicts the noise
components and structural
components. The software
separates these components,
which enhances the structure
while simultaneously reducing the
noise. | The image enhancement algorithm
is a modification of the non-local
means algorithm where the filtering
weights can be obtained from
higher resolution and lower noise
voxel arrays obtained with other
modalities, i.e. CT or MR. The
resolution of the target is at least
the maximum of the combined
modalities, but may be higher. |
| Image
acquisition | The acquisition remains the same,
i.e. the image processing can be
generated from multiple
modalities and with predefined or
specific acquisition protocol | The acquisition remains the
same. |
| Characteristics | Predicate Device | Subject Device |
| | SubtlePET [K182336] | Claritas iPET [K213140] |
| | settings. | |
| Workflow | The product acts as a DICOM | Same in case of the PACS integrated |
| | node that receives DICOM 3.0 | version. |
| | digital medical image data from | |
| | the modality or another DICOM | The stand-alone version can input |
| | source, processes the data and | the slices of the PET, MR or CT |
| | then forwards the enhanced study | scans as DICOM files, interactively |
| | to the selected destination. This | visualizes the input and the output |
| | destination can be any DICOM | data, and saves the enhanced |
| | node, typically either the PACS | volume in DICOM files. |
| | system or a specific workstation. | |
5.8 Technological Characteristics Comparison Table
6
7
Summary of Technological Characteristics Comparison Table
As per the table above the two devices are technologically similar and have similar indications of use. Verification, validation, and performance testing demonstrates the differences in the algorithm implemented by the subject and predicate, do not raise new questions of safety and effectiveness.
5.9 Performance Testing
Claritas iPET has been developed under the Quality System Regulations of ISO 13485. The design has been verified and validated according to the software development plan which follows IEC 62304:2006 and ISO 14971:2019 requirements.
Safety and performance have been evaluated and verified in accordance with the software specification to ensure the performance meets the specified requirements and the requirement of the FDA guidance document, titled, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices". Testing included design traceability confirming all requirement tracing is complete from design inputs and verification/validation and that all risk controls are implemented. Design validation testing simulated intended use to confirm that the end-to-end functionality of the Claritas iPET meets the design requirements.
Claritas iPET is an image processing software which reduces the noise without blurring organ boundaries and compromising the true signal. The accuracy of the processing and the reduction of the noise can be quantified by the Root Mean Square Error (RMSE) and the Signal to Noise Ratio (SNR) calculated before and after processing the data with iPET. Both measures need the ground truth of the analysed data.
In order to obtain the ground truth, we consider two different options:
- In the first option, we enhanced real full body human PET scans. We executed a long scan ● and accepted the reconstructed results as ground truth. The PET scanning time is decomposed to uniform frames and the reconstruction process has been executed for subsets of the original frames demonstrating that the reconstruction quality can be maintained even for reduced scanning time and/or dosage if the Claritas iPET software is executed. The comparison is repeated for the case when the additional CT/MRI information is also utilized by the Claritas iPET software. We have concluded that the RMSE has been decrease by at least 10% and the SNR has been increased by at least 20%. However, for low dosage or
8
short time scans, the improvement can be significantly higher, the RMSE is decreased by 50% and the SNR can be increased by 4-5 times. All tests have passed.
- In the second option, we took the Zubal mathematical phantom, and considered it as the ground truth. The measured data are then generated by adding multiplicative, i.e. Poisson noise to the ground truth data. The noisy images are processed with the iPET software and the results are compared to the ground truth. The conclusions are similar to those of the measured scans. For high dosage and longer scans, we can expect 10-20% improvement in RMSE and SNR, which grows rapidly for low dosage or short scans. This test has passed.
5.10 Safety and Effectiveness
Based on the Claritas iPET software performance test results and incorporated risk minimisation methods in design, Claritas HealthTech Pte. Ltd. concludes that this device is substantially equivalent to the predicate device.
5.11 Substantial Equivalence Conclusion
Claritas iPET is an image enhancement software which has similar intended use and indications for use as the predicate device. The difference is that the predicate device sets the filtering weights using a pre-trained net, while Claritas iPET applies multi-channel non-local means filtering. The two devices have similar technological characteristics: both predicate device and subject device use image enhancement algorithms as their core technology. Performance test results and incorporated risk minimization methods demonstrate that Claritas iPET is as safe and effective as the predicate device. This 510(k) submission includes information on the Claritas iPET technological characteristics, as well as performance data and verification and validation activities demonstrating that Claritas iPET is substantially equivalent to the predicate device, and does not raise different questions of safety and effectiveness.