Artificial Intelligence Renal Assessment (AIRA) Version 1

{0} **FDA U.S. FOOD & DRUG** ADMINISTRATION September 15, 2026 Aramis Global AI Consultancies, LLC % John DeLucia Consultant John Delucia Consulting 34 Laurel Rd. Guilford, Connecticut 06437 Re: K261677 Trade/Device Name: Artificial Intelligence Renal Assessment (AIRA) Version 1 Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH Dated: August 15, 2026 Received: August 17, 2026 Dear John DeLucia: 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 (the 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 available 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. U.S. Food & Drug Administration 10903 New Hampshire Avenue Silver Spring, MD 20993 www.fda.gov {1} K261677 - John DeLucia Page 2 Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download). Your device is also subject to, among other requirements, the Quality Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13485 clause 8.3 (Nonconforming product), ISO 13485 clause 8.5.2 (Corrective action), and ISO 13485 clause 8.5.3 (Preventative action). Please note that regardless of whether a change requires premarket review, the QMSR requires device manufacturers to review and approve changes to device design and production (ISO 13485 clause 7.3 and ISO 13485 clause 7.5) and document changes and approvals in the Medical Device File (ISO 13485 clause 4.2.3). 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 (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the Quality Management System Regulation (QMSR) (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050. All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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-devices/medical-device-safety/medical-device-reporting-mdr-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/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the {2} K261677 - John DeLucia Page 3 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-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100). Sincerely, Jessica Lamb Assistant Director DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {3} | Indications for Use | | | | --- | --- | --- | | Please type in the marketing application/submission number, if it is known. This textbox will be left blank for original applications/submissions. | K261677 | ? | | Please provide the device trade name(s). | | ? | | Artificial Intelligence Renal Assessment (AIRA) Version 1 | | | | Please provide your Indications for Use below. | | ? | | Non-invasive processing of CT kidney images using automatic image segmentation and measurement of anatomical structures utilizing artificial intelligence/machine-learning algorithms.The system automatically calculates the renal parenchymal volume.AIRA is intended for adult patients who require volumetric measurement of the kidneys for further clinical assessment. | | | | Please select the types of uses (select one or both, as applicable). | Prescription Use (21 CFR 801 Subpart D)Over-The-Counter Use (21 CFR 801 Subpart C) | ? | | Please select the age group(s) for which the device(s) is to be used. | Neonates/Newborns (Birth to < 29 days old)Infants (29 days old to < 2 years old)Children (2 years old to < 12 years old)Adolescents (12 years old to < 22 years old)Adults (22 years old and greater) | ? | {4} K261677 # 510(K) Summary **Date Prepared:** August 8, 2026 **Submitter** Aramis Global AI Consultancies LLC Rahet Albal Business Centre Court Tower Building, Office #39 Dubai, UAE +91 9288045050 **Contact Person** John DeLucia John DeLucia Consulting 34Laurel Rd. Guilford, CT 06437 Email: johndelucia@comcast.net Phone: (603) 566-0146 **Submission Date:** May 21, 2026 **Trade Name:** Artificial Intelligence Renal Assessment (AIRA) Version 1 **Common Name:** Medical Imaging Software **Classification Name/Regulation** 21 CFR 892.2050 Medical image management and processing system **Product Code** QIH {5} ## Device Classification Class II ### Legally Marketed Devices to Which Substantial Equivalence is Claimed Artificial Intelligence Renal Assessment (AIRA) is substantially equivalent to the following legally marketed predicate device. | Device Name | Manufacturer | 510(k) # | Decision Date | | --- | --- | --- | --- | | Ceevra Reveal 3 | Ceevra Inc. | K222676 | 04/25/2023 | ### Device Description AIRA operates by using medical imaging data (CT scans) to analyze the size and shape of the kidney. It utilizes a deep learning algorithm to accurately estimate the renal parenchymal volume of the kidney. The output of the algorithm is a NumPy array that is used to generate a NIfTI file format, which is then used to calculate the kidney volumes. These values are then compiled into a PDF report that can be easily downloaded from our AIRA tool. The report provides the user with detailed information about their kidney size. Specifically, the report includes the volume of the left and right kidneys. In addition, volume masks are produced, that can be superimposed on the original DICOM gray scale image. An editor tool is also available, which can be used to modify the outputs where necessary and recalculate the volumes (this is optional). This information is compared to baseline measurements to detect any changes that may indicate early kidney swelling or volume loss. The tool is intended for use by medical professionals, such as radiologists, nephrologists, and urologists, who are trained in the interpretation of medical imaging data. ### Indications for Use Non-invasive processing of CT kidney images using automatic image segmentation and measurement of anatomical structures utilizing artificial intelligence/machine-learning algorithms. The system automatically calculates the renal parenchymal volume. {6} AIRA is intended for adult patients who require volumetric measurement of the kidneys for further clinical assessment. ## Summary of Indications for Use AIRA and the predicate device have the same indication for use. Both devices are intended for non-invasive processing of images using automatic image segmentation and measurement of anatomical structures utilizing artificial intelligence/machine-learning algorithms. AIRA is intended for adult patients who require volumetric measurement of the kidneys for further clinical assessment. ## Summary of Technological Characteristic AIRA and the predicate device have similar technological characteristics. Both utilize artificial intelligence/machine-learning algorithms to perform automatic image segmentation and measurement of anatomical structures. AIRA is different from the predicate in that it uses images from CT and MRI while the subject device utilizes CT images only. ## General Safety and Effectiveness Concerns The device labeling contains instructions for use and any necessary cautions and warnings to provide for safe and effective use of this device. Risk management is ensured via a risk analysis which is used to identify and mitigate potential hazards. Any potential hazards are controlled via software development, verification and validation testing. In addition, general controls of the FD&C Act, and special controls established for medical image management and processing system per 21 CFR 892.2050 are in place to further mitigate any safety and or effectiveness risks. ## Assessment of Non-Clinical Performance Data The AIRA Standalone Study was a retrospective study conducted to assess the performance of AIRA. A total of 119 computed tomography (CT) cases were retrospectively collected for use in this standalone study under the approved Aramis Protocol 66017 Data Collection Protocol. The cases were collected from 3 US sites at distinct geographic locations. The study analyses included 113 cases. The sample was enriched to have at least 25% of cases with atrophied kidneys. Ground truth volume and segmentation were established by 2 radiologists; no adjudication was required. AIRA: Version 1.0 was used to process all cases and provide segmentation and RPV for each kidney. Accuracy of AIRA was measured by the Dice {7} similarity coefficient (DSC) and the Hausdorff distance between AIRA and ground truth segmentation. The mean Dice Similarity Coefficient (DSC) between the AIRA mask and the larger Ground Truther mask was 0.9092 for the Right kidney (95% CI: 0.9032, 0.9148) and 0.9114 for the Left kidney (95% CI: 0.9035, 0.9179). The mean Hausdorff Distance (HD) between the AIRA mask and the larger Ground Truther mask was 9.9743 mm for the Right kidney (95% CI: 8.4073, 12.5967) and 9.9395 mm for the Left kidney (95% CI: 7.8926, 13.6073). Mean 95th Percentile HDs (HD95s) were 3.7734 mm (95% CI: 3.5544, 4.0104) and 3.9151 mm (95% CI: 3.4522, 4.6661) for the Right and Left kidneys, respectively. ### **Conclusion:** Based upon the information presented in this submission, it is concluded that AIRA is substantially equivalent to the named predicate device. The Summary of Substantial Equivalence Table below details the similarities and differences between the subject device and the predicate device Ceevra Reveal 3 (K222676 -Ceevra Inc.). {8} Table: Substantial Equivalence Table | Characteristics | Subject Device | Predicate | Similarities / Differences | | --- | --- | --- | --- | | Sponsor | Aramis LLP | Ceevra Inc. | | | Device Name | AIRA Renal Assessment | Ceevra Reveal 3 | NA | | 510(k) | K261677 | K222676 | NA | | Regulation No. | 21 CFR 892.2050 | 21 CFR 892.2050 | Subject Device Same as Predicate | | Regulation Description | Medical image management and processing system | Medical image management and processing system | Subject Device Same as Predicate | | Classification | Class II | Class II | Subject Device Same as Predicate | | Product Code | QIH | QIH | Subject Device Same as Predicate | | Indications for Use | Non-invasive processing of CT kidney images using automatic image segmentation and measurement of anatomical structures utilizing artificial intelligence/machine-learning algorithms. The system automatically calculates the renal parenchymal volume. AIRA is intended for adult patients who require volumetric measurement of the kidneys for further clinical assessment. | Ceevra Reveal 3 is intended as a medical imaging system that allows the processing, review, analysis, communication and media interchange of multi-dimensional digital images acquired from CT or MR imaging devices and that such processing may include the generation of preliminary segmentations of normal anatomy using software that employs machine learning and other computer vision algorithms. It is also intended as software for preoperative surgical planning, and as software for the intraoperative display of the multi- dimensional digital images. Ceevra Reveal 3 is designed for use by health | Subject Device Same as Predicate | {9} | | Subject Device | Predicate | Similarities / Differences | | --- | --- | --- | --- | | **Characteristics** | Aramis LLP | Ceevra Inc. | | | | | care professionals and is intended to assist the clinician who is responsible for making all final patient management decisions. The machine learning algorithms in use by Ceevra Reveal 3 are only for adult patients (22 and over). Three- dimensional images for patients under the age of 22 or of unknown age will be generated without the use of any machine learning algorithms | | | **Anatomical Site** | Kidney | Prostate, bladder neurovascular bundles, kidney, vein, arteries | Subject Device Same as Predicate | {10} | | Subject Device | Predicate | Similarities / Differences | | --- | --- | --- | --- | | Sponsor | Aramis LLP | Ceevra Inc. | | | Image Type and input | Computed Tomography / Complies with DICOM Standard CT Image | Computed Tomography / Ultrasound / Complies with DICOM Standard CT or MR Images | Subject Device Same as Predicate | | Principle of Operation/ Technology | CT image processing software application implementing artificial intelligence including non-adaptive machine learning algorithms trained with clinical and/or artificial data intended for non-invasive segmentation and measurements of CT data. | CT or MR medical imaging system that allows for generation of preliminary segmentations of normal anatomy using software that employs machine learning and other computer vision algorithms. | Subject Device Same as Predicate | | Medical Device Type | Software as a Medical Device (SaMD) | Software as a Medical Device (SaMD) | Subject Device Same as Predicate | | Operating System | Windows / Linux | Windows / MacOS /iOS/ Android | Subject device is Similar to Predicate. | {11} | | Subject Device | Predicate | Similarities / Differences | | --- | --- | --- | --- | | Sponsor | Aramis LLP | Ceevra, Inc. | | | Image analysis features | Interactive manipulation and 2D visualization | Interactive manipulation and 3D visualization | Subject Device Same as Predicate | | Quantitative analysis | Kidney Volume | Kidney Volume | Subject Device Same as Predicate | | Operating System | Web browser (Google Chrome) | Web browser (Google Chrome) and Android | Subject Device Same as Predicate | | Patient Population | Adults | Adults | Subject Device Same as Predicate | | Performance Testing* (Software measurement vs. Ground Truth) | **DCS:** Right kidney 0.9092 Left kidney 0.9114 | Kidney (from CT abdomen imaging) 0.89 DSC Kidney (from MR abdomen imaging) 0.87 DSC (Copied from 510k summary of K222676.) | Subject Device Similar as Predicate | * The subject device's performance testing dataset was different than the predicate's performance testing dataset.