Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with aEvolve Imaging (FOV Extension)
K253584 · Canon Medical Systems Corporation · OWB · Mar 10, 2026 · Radiology
Device Facts
Record ID
K253584
Device Name
Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with aEvolve Imaging (FOV Extension)
Applicant
Canon Medical Systems Corporation
Product Code
OWB · Radiology
Decision Date
Mar 10, 2026
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.1650
Device Class
Class 2
Attributes
AI/ML
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Real-time fluoroscopic image noise reduction
Artificial Intelligence Denoising (AID) and Multi Frequency Processing (MFP)
Equivalent to or better than predicate device (SNRF) in noise and SNR properties; absence of unexpected distortions; kurtosis closer to 3 than predicate; superior LCD performance (p < 0.05); superior CNR (p < 0.05)
Noise and SNR properties equivalent to or better than predicate; NPS smooth and free of distortions; kurtosis significantly closer to 3 than predicate; LCD statistically significantly better (p < 0.05); CNR significantly better (p < 0.05)
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—
Bench testing using anthropomorphic chest phantom and PMMA slab phantom datasets.
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Indications for Use
This device is a digital radiography/fluoroscopy system used in a diagnostic and interventional angiography configuration. The system is indicated for use in diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen and lower extremities. αEvolve Imaging is an imaging chain intended for adults, with Artificial Intelligence Denoising (AID) designed to reduce noise in real-time fluoroscopic images and signal enhancement algorithm, Multi Frequency Processing (MFP).
Device Story
Interventional X-ray system with floor-mounted C-arm (optional ceiling-mounted for bi-plane); includes patient table, X-ray generator, and digital detectors. Inputs: real-time fluoroscopic X-ray signals. Processing: αEvolve Imaging chain utilizes Artificial Intelligence Denoising (AID) for noise reduction and Multi-Frequency Processing (MFP) for signal enhancement. Output: enhanced fluoroscopic images displayed to clinicians. Used in interventional suites by physicians to guide diagnostic and angiographic procedures. Output assists in visualization of blood vessels, potentially improving procedural accuracy and patient outcomes. Modification expands FOV support to 12-inch, 10-inch, and 3-inch modes.
Clinical Evidence
Bench testing only. No clinical data. Performance evaluated using anthropomorphic chest phantoms and PMMA slab phantoms. Metrics included Noise Power Spectrum (NPS), Modulation Transfer Function (MTF), Noise Equivalent Quanta (NEQ), Low Contrast Detectability (LCD), and Contrast-to-Noise Ratio (CNR). Subject device demonstrated statistically significant improvements (p < 0.05) in LCD and CNR compared to the predicate, with equivalent or improved noise/SNR properties across tested FOV modes.
Technological Characteristics
Interventional X-ray system; floor/ceiling-mounted C-arm; X-ray high-voltage generator; digital detectors. Imaging chain: AI-based denoising (AID) and Multi-Frequency Processing (MFP). Conforms to IEC 60601-1, IEC 60601-2-43, and 21 CFR 1020. Supports 12-inch, 10-inch, 8-inch, 6-inch, and 3-inch FOV. Software-based image processing.
Indications for Use
Indicated for adult patients undergoing diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen, and lower extremities using digital radiography/fluoroscopy.
Regulatory Classification
Identification
An image-intensified fluoroscopic x-ray system is a device intended to visualize anatomical structures by converting a pattern of x-radiation into a visible image through electronic amplification. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.
Special Controls
*Classification.* Class II (special controls). An anthrogram tray or radiology dental tray intended for use with an image-intensified fluoroscopic x-ray system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9. In addition, when intended as an accessory to the device described in paragraph (a) of this section, the fluoroscopic compression device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.
Predicate Devices
Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (K251602)
Submission Summary (Full Text)
{0}
FDA U.S. FOOD & DRUG ADMINISTRATION
March 10, 2026
Canon Medical Systems Corporation
% Jonathan Toy
Manager, Regulatory Affairs
Canon Medical Systems, USA
2441 Michelle Drive
TUSTIN, CA 92780
Re: K253584
Trade/Device Name: Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with aEvolve Imaging (FOV Extension)
Regulation Number: 21 CFR 892.1650
Regulation Name: Image-Intensified Fluoroscopic X-Ray System
Regulatory Class: Class II
Product Code: OWB
Dated: November 17, 2025
Received: March 2, 2026
Dear Jonathan Toy:
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
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K253584 - Jonathan Toy
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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 13484 clause 8.3 (Nonconforming product), and ISO 13485 clause 8.5 (Corrective and 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 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 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-
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K253584 - Jonathan Toy
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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,

Lu Jiang, Ph.D.
Assistant Director
Diagnostic X-Ray Systems Team
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. | K258534 | ? |
| Please provide the device trade name(s). | | ? |
| Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension) | | |
| Please provide your Indications for Use below. | | ? |
| This device is a digital radiography/fluoroscopy system used in a diagnostic and interventional angiography configuration. The system is indicated for use in diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen and lower extremities.
αEvolve Imaging is an imaging chain intended for adults, with Artificial Intelligence Denoising (AID) designed to reduce noise in real-time fluoroscopic images and signal enhancement algorithm, Multi Frequency Processing (MFP). | | |
| 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) | ? |
{4}
Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 510(k) SUMMARY
This summary of 510(k) substantial equivalence information is being submitted in accordance with the requirements of Safe Medical Device Act 1990 and 21 CFR § 807.92
1. SUBMITTER'S NAME
Canon Medical Systems Corporation
1385 Shimoishigami
Otawara-Shi, Tochigi 324-8550, Japan
2. OFFICIAL CORRESPONDENT
Junichiro Araoka
Senior Manager, Quality Assurance Department
3. CONTACT PERSON, U.S. AGENT and ADDRESS
Contact Person
Jonathan Toy
Manager, Regulatory Affairs
Canon Medical Systems USA
2441 Michelle Drive, Tustin, CA 92780
Phone: (562) 709-0291
Fax: (714) 730-1310
jtoy@us.medical.canon
Official Correspondent/U.S. Agent
Orlando Tadeo, Jr.
Director, Regulatory Affairs
Canon Medical Systems USA
2441 Michelle Drive, Tustin, CA 92780
Phone: (714) 483-1551
Fax: (714) 730-1310
otadeo@us.medical.canon
4. MANUFACTURING SITE
Canon Medical Systems Corporation (CMSC)
1385 Shimoishigami
Otawara-shi, Tochigi 324-8550, Japan
5. ESTABLISHMENT REGISTRATION
9614698
6. DATE PREPARED
November 17, 2025
7. TRADE NAME(S)
Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension)
8. COMMON NAME
Interventional Fluoroscopic X-ray System
9. CLASSIFICATION PANEL
Radiology
Page 1 of 7
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Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 10. DEVICE CLASSIFICATION
a) Classification Name: Image-Intensified Fluoroscopic X-ray System
b) Regulation Number: 21 CFR 892.1650
c) Regulation Class: Class II
# 11. PRODUCT CODE
OWB
# 12. PERFORMANCE STANDARD
This device conforms to applicable Performance Standards for Ionizing Radiation Emitting Products [21 CFR Subchapter J, Federal Diagnostic X-ray Equipment Standard].
# 13. PREDICATE DEVICE
| Trade Name | Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging |
| --- | --- |
| Marketed by | Canon Medical Systems USA, Inc. |
| 510(k) Number | K251602 |
| Clearance Date | October 10, 2025 |
| Common Name | Interventional Fluoroscopic X-ray System |
| Classification Name | Image-Intensified Fluoroscopic X-ray System |
| Regulation Number | 21 CFR 892.1650 |
| Regulation Class | Class II |
| Product Code | OWB |
# 14. REASON FOR SUBMISSION
Modification of a cleared device
# 15. SUBMISSION TYPE
Traditional 510(k)
# 16. DEVICE DESCRIPTION
The Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension), is an interventional X-ray system with a floor mounted C-arm as its main configuration. An optional ceiling mounted C-arm is available to provide a bi-plane configuration where required. Additional units include a patient table, X-ray high-voltage generator and a digital radiography system. The C-arms can be configured with designated X-ray detectors and supporting hardware (e.g. X-ray tube and diagnostic X-ray beam limiting device). With Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension), the αEvolve Imaging feature now supports 12-inch, 10-inch, and 3-inch fields of view (FOV) for imaging in adult patients. The αEvolve imaging chain incorporates Artificial Intelligence Denoising (AID) for real-time fluoroscopic noise reduction, as well as Multi-Frequency Processing (MFP), a signal enhancement algorithm.
Page 2 of 7
{6}
Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 17. INDICATIONS FOR USE
This device is a digital radiography/fluoroscopy system used in a diagnostic and interventional angiography configuration. The system is indicated for use in diagnostic and angiographic procedures for blood vessels in the heart, brain, abdomen and lower extremities.
αEvolve Imaging is an imaging chain intended for adults, with Artificial Intelligence Denoising (AID) designed to reduce noise in real-time fluoroscopic images and signal enhancement algorithm, Multi Frequency Processing (MFP).
# 18. SUBSTANTIAL EQUIVALENCE
The Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension) is substantially equivalent to the Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging, which received premarket clearance under K251602, marketed by Canon Medical Systems. The intended use of the Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension) is the same as that of the predicate device. A comparison of the technological characteristics between the subject and the predicate device is included below.
| | Predicate Device | Subject Device |
| --- | --- | --- |
| Device Name, Model Number | Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging | Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6 with αEvolve Imaging (FOV Extension) |
| 510(k) Number | K251602 | This submission |
| FOV of αEvolve Imaging | 8-inch, 6-inch (non-binning) | 12-inch, 10inch (binning)
8-inch, 6-inch (non-binning)
3-inch (hi-def, non-binning) |
# 19. SAFETY
The device is designed and manufactured under the Quality System Regulations as outlined in 21 CFR § 820 and ISO 13485 Standards. This device is in conformance with the applicable parts of the IEC60601-1 standards, its collateral standards and particular standards; IEC 60601-2-43, IEC60601-2-28, and IEC TR 60601-4-2. All requirements of the Federal Diagnostic Equipment Standard, as outlined in 21 CFR §1020, that apply to this device, are met.
# LIST OF APPLICABLE STANDARDS
- IEC 60601-1:2005+A1:2012+A2:2020
- IEC 60601-1-2:2014 + A1:2020
- IEC 60601-1-3:2008+A1:2013+A2:2021
- IEC 60601-1-6:2010+A1:2013+A2:2020
- IEC 60601-2-28:2017
- IEC 60601-2-43:2010+A1:2017+A2:2019
- IEC 62304:2006+A1:2015
- IEC 62366-1:2015 + A1:2020
- IEC 81001-5-1:2021
- ISO 17664-2:2021
- IEC TR 60601-4-2:201
Page 3 of 7
{7}
Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 20. TESTING
# Performance Testing – Bench
## Image Quality Evaluations
Image quality assessments were performed, utilizing phantom and clinical datasets, to evaluate the image quality of the artificial intelligence denoising (AID) algorithm compared to the predicate device, super noise reduction filter (SNRF). The following image quality performance tests were conducted:
## Binning Mode Bench Test Results
1. Change in Image Level, Noise Magnitude and Signal-to-Noise Ratio (SNR)
- AID and SNRF image sequences of an anthropomorphic chest phantom were acquired at various settings to evaluate image-level similarity using the Two One-Sided Test (TOST), and to assess noise magnitude and SNR using a one-sided Student's t-test. Results demonstrated that noise and SNR properties of the subject device were equivalent to or better than those of the predicate device in this bench test.
2. Noise Power Spectrum
- The noise power spectrum (NPS) of fluoroscopic images was evaluated using a PMMA slab phantom, comparing the subject and predicate IP chains. NPS was measured in accordance with IEC 62220-1-1:2015, with success defined as the absence of unexpected distortions (e.g., spikes). Both NPS curves were smooth and free of unexpected distortions. Relative to the predicate IP chain, the subject IP chain exhibited a flatter NPS curve, with lower noise at spatial frequencies below approximately 0.6 cycles/mm and slightly higher noise above that range.
3. Noise Texture via Kurtosis
- Noise texture was evaluated using kurtosis as a statistical marker with a PMMA slab phantom across four acquisition conditions, utilizing the same dataset used in the Noise Power Spectrum analysis. Success was defined as the subject IP chain's kurtosis being significantly closer to 3 than the predicate (p < 0.05) in most test cases. The subject IP chain consistently met this criterion, indicating a more Gaussian-like noise distribution, while the predicate exhibited higher kurtosis, reflecting a heavier-tailed noise distribution.
4. Modulation Transfer Function (MTF)
- Spatial resolution was assessed by measuring the modulation transfer function (MTF) of fluoroscopic images in accordance with IEC 62220-1-1:2015.
Frame-by-frame measurements were averaged to obtain the final normalized MTF curve, with error bars indicating the standard deviation across frames. The test was deemed successful if the MTF curve showed reduced over-enhancement and no unexpected distortions. Both MTF curves were smooth and free of unexpected distortions. The predicate chain exhibited a higher MTF peak, indicating stronger edge enhancement, while the subject IP chain applied more moderate enhancement.
Page 4 of 7
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Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 5. Noise Equivalent Quanta
- Noise Equivalent Quanta (NEQ) was evaluated using previously obtained Noise Power Spectrum (NPS) and Modulation Transfer Function (MTF) data. Success was defined as the subject image processing (IP) chain demonstrating higher NEQ in the low to mid spatial frequency range compared to the predicate IP chain. The results showed that the subject IP chain consistently outperformed the predicate in the $0 - 0.5\mathrm{lp / mm}$ range.
# 6. Low Contrast Detectability
- Low contrast detectability (LCD) was evaluated for the subject IP chain compared with the predicate using a PMMA slab phantom across four acquisition conditions, utilizing the same dataset used in the Noise Power Spectrum analysis. Custom software measured LCD across various ROI sizes to assess performance at different spatial scales. The test was considered successful if the subject IP chain performed significantly better than the predicate $(p < 0.05)$ , or if no statistically significant difference was observed in most test cases. Across all conditions, the subject IP chain consistently demonstrated lower percent contrast values than the predicate, indicating superior LCD performance, with improvements statistically significant in all cases $(p < 0.05)$ .
# 7. Contrast-to-Noise Ratio of a High Contrast Object
- This test measured the contrast-to-noise ratio (CNR) in high-contrast regions using a guide wire placed on an anthropomorphic chest phantom containing contrast-enhanced vessels. CNR was measured at the guidewire tip and vessel on a frame-by-frame basis, and results were compared between the subject and predicate IP chains. The test was considered successful if the subject IP chain performed significantly better than the predicate $(p < 0.05)$ , or if no statistically significant difference was observed in most test cases. Results showed that the subject IP chain significantly outperformed the predicate in all cases $(p < 0.05)$ , indicating a consistent and statistically significant improvement in CNR for high-contrast objects.
# Hi-Def Mode Bench Test Results
# 1. Change in Image Level, Noise Magnitude and Signal-to-Noise Ratio (SNR)
- AID and SNRF image sequences of an anthropomorphic chest phantom, at various PMMA thicknesses, were acquired at various settings to evaluate image-level similarity using the Two One-Sided Test (TOST), and to assess noise magnitude and SNR using a one-sided Student's t-test. Results demonstrated that noise and SNR properties of the subject device were better than those of the predicate device in this bench test.
{9}
Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 2. Noise Power Spectrum
- The noise power spectrum (NPS) of fluoroscopic images was evaluated using a PMMA slab phantom, comparing the subject and predicate IP chains. NPS was measured in accordance with IEC 62220-1-1:2015, with success defined as the absence of unexpected distortions (e.g., spikes) and a reduction in noise at high spatial frequencies. Both NPS curves were smooth and free of unexpected distortions. Relative to the predicate IP chain, the subject IP chain exhibited lower noise at spatial frequencies at mid and high frequencies above 2 cycles/mm.
# 3. Noise Texture via Kurtosis
- Noise texture was evaluated using kurtosis as a statistical marker with a PMMA slab phantom across four acquisition conditions, utilizing the same dataset used in the Noise Power Spectrum analysis. Success was defined as the subject IP chain's kurtosis being significantly closer to 3 than the predicate $(p < 0.05)$ in most test cases. The subject IP chain consistently met this criterion, indicating a more Gaussian-like noise texture and statistically lower kurtosis than the predicate.
# 4. Modulation Transfer Function (MTF)
- Spatial resolution was assessed by measuring the modulation transfer function (MTF) of fluoroscopic images in accordance with IEC 62220-1-1:2015.
Frame-by-frame measurements were averaged to obtain the final normalized MTF curve, with error bars indicating the standard deviation across frames. The test is considered acceptable if the Noise Equivalent Quanta (NEQ) in Test 5: Noise Equivalent Quanta is maintained or improved in the higher spatial frequency range. Both MTF curves were smooth and free of unexpected distortions, and the subject IP chain demonstrated lower spatial resolution than the predicate chain.
# 5. Noise Equivalent Quanta
- Noise Equivalent Quanta (NEQ) was evaluated using previously obtained Noise Power Spectrum (NPS) and Modulation Transfer Function (MTF) data. Success was defined as the subject IP chain exhibiting higher NEQ in the mid to high spatial frequency range compared with the predicate IP chain. Results demonstrated that the subject IP chain consistently outperformed the predicate in mid and high frequencies.
# 6. Low Contrast Detectability
- Low contrast detectability (LCD) was evaluated for the subject IP chain compared with the predicate using a PMMA slab phantom across four acquisition conditions, utilizing the same dataset used in the Noise Power Spectrum analysis. Custom software measured LCD across various ROI sizes to assess performance at different spatial scales. The test was considered successful if the subject IP chain performed significantly better than the predicate $(p < 0.05)$ . The results were considered acceptable, as the subject IP chain outperformed the predicate in the majority of ROI sizes (3 out of 4).
{10}
Canon
CANON MEDICAL SYSTEMS USA, INC.
Made For life
# 7. Contrast-to-Noise Ratio of a High Contrast Object
- This test measured the contrast-to-noise ratio (CNR) in high-contrast regions using a guide wire placed on an anthropomorphic chest phantom containing contrast-enhanced vessels. CNR was measured at the guidewire tip and vessel on a frame-by-frame basis, and results were compared between the subject and predicate IP chains. The test was considered successful if the subject IP chain performed significantly better than the predicate $(p < 0.05)$ in most test cases. Results showed that the subject IP chain significantly outperformed the predicate in all cases, indicating a consistent and statistically significant improvement in CNR for high-contrast objects.
Risk analysis and verification/validation testing conducted through bench testing demonstrate that the established specifications for the device have been met. Testing of the modified system was conducted in accordance with the applicable standards published by the International Electromechanical Commission (IEC) for Medical Devices and XR Systems.
Software Documentation for a Basic Documentation Level, per the FDA guidance document, "Content of Premarket Submissions for Device Software Functions" issued on June 14, 2023, was determined appropriate. This documentation includes justification for the Basic Documentation Level determination as well as testing which demonstrates that the verification and validation requirements have been met.
Cybersecurity documentation followed FDA cybersecurity premarket guidance document "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions" issued on September 27, 2023.
Additionally, the design controls used for this device included risk management and all known risks were mitigated to an acceptable level.
# 21. CONCLUSION
The Alphenix, INFX-8000V/B, INFX-8000V/5, V9.6 with αEvolve Imaging (FOV Extension), performs in a manner similar to and is intended for the same use as the predicate device, as indicated in the product labeling. Based upon this information, conformance to standards, successful completion of software validation, application of risk management, and design controls, it is concluded that the subject device has demonstrated substantial equivalence to the predicate device and is as safe and effective for its intended use.
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Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
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.