K201836 · Canon Medical Systems Corporation · JAK · Jan 12, 2021 · Radiology
Device Facts
Record ID
K201836
Device Name
Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i
Applicant
Canon Medical Systems Corporation
Product Code
JAK · Radiology
Decision Date
Jan 12, 2021
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.1750
Device Class
Class 2
Attributes
AI/ML
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
CT Image Noise Reduction
Deep Convolutional Network
—
Up to 82.9% dose reduction relative to FBP; 15% improved low contrast detectability; 29% noise reduction at the same dose.
—
—
—
—
Indications for Use
This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head. The Aquilion Lightning has the capability to provide volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician. AiCE (Advanced Intelligent Clear-IQ Engine) is a noise reduction that improves image quality and reduces image noise by employing Deep Convolutional Network methods for abdomen,pelvis, lung, cardiac, extremities, head and inner ear applications.
Device Story
80-row multi-slice helical CT scanner; consists of gantry, couch, and console. Inputs: X-ray projection data. Transformation: Reconstruction of cross-sectional volume data using AiCE-i (Advanced Intelligent Clear-IQ Engine). AiCE-i utilizes Deep Convolutional Neural Network (DCNN) methods to differentiate structure from noise, reducing image noise and improving image quality. Used in clinical settings by trained physicians. Output: High-quality CT images displayed on console. Clinical impact: Enables dose reduction (up to 82.9% vs FBP) and improved low-contrast detectability (15% vs AIDR 3D) while maintaining diagnostic image quality. Benefits patient via reduced radiation exposure and clearer diagnostic visualization.
Clinical Evidence
Bench testing only. No clinical data. Performance evaluated using phantoms to assess CNR, CT number accuracy, uniformity, SSP, MTF, noise power spectra, and low-contrast detectability. Results demonstrated up to 82.9% dose reduction relative to FBP, 15% improved low-contrast detectability, and 29% noise reduction compared to AIDR 3D.
Indicated for whole body, including head, cross-sectional volume acquisition and display. Used by trained physicians for specialized studies. AiCE noise reduction indicated for abdomen, pelvis, lung, cardiac, extremities, head, and inner ear applications.
Regulatory Classification
Identification
A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.
Aquilion Prime SP (TSX-303B/8) V10.2 with AiCE-i (K192832)
Submission Summary (Full Text)
{0}------------------------------------------------
January 12, 2021
Image /page/0/Picture/1 description: The image contains the logos of the Department of Health & Human Services and the U.S. Food & Drug Administration (FDA). The Department of Health & Human Services logo is on the left, featuring a stylized symbol. To the right is the FDA logo, with the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" and "ADMINISTRATION" in blue text.
Canon Medical Systems Corporation % Orlando Tadeo, Jr. Sr. Manager, Regulatory Affairs Canon Medical Systems USA, Inc. 2441 Michelle Drive TUSTIN CA 92780
Re: K201836
Trade/Device Name: Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK Dated: December 9, 2020 Received: December 10, 2020
Dear Mr. Tadeo:
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 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.
For
Thalia T. Mills, Ph.D. 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}------------------------------------------------
# Indications for Use
510(k) Number (if known)
#### K201836
Device Name
Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i.
#### Indications for Use (Describe)
This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head.
The Aquilion Lightning has the capability to provide volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician.
AiCE (Advanced Intelligent Clear-IQ Engine) is a noise reduction that improves image quality and reduces image noise by employing Deep Convolutional Network methods for abdomen,pelvis, lung, cardiac, extremities, head and inner ear applications.
X 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 PRAStaff(@fda.hhs.gov
"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}------------------------------------------------
# Made For life
K201836
## 510(k) SUMMARY
1.
## SUBMITTER'S NAME: Canon Medical Systems Corporation 1385 Shimoishigami Otawara-Shi, Tochigi-ken, Japan 324-8550
## 2. OFFICIAL CORRESPONDENT: Fumiaki Teshima Senior Manager, Quality Assurance Department
## 3. ESTABLISHMENT REGISTRATION: 9614698
## 4. CONTACT PERSON:
Orlando Tadeo, Jr. Sr. Manager, Regulatory Affairs Canon Medical Systems USA, Inc 2441 Michelle Drive Tustin, CA 92780 (714) 669-7459
## 5. Date Prepared:
June 30, 2020
## 6. TRADE NAME(S):
Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i
## 7. COMMON NAME:
System, X-ray, Computed Tomography
## 8. DEVICE CLASSIFICATION:
a) Classification Name: Computed Tomography X-ray system b) Regulation Number: 892.1750 c) Regulatory Class: Class II
## 9. PRODUCT CODE / DESCRIPTION:
JAK – System, Computed Tomography
PHONE: 800-421-1968 2441 Michelle Drive, Tustin, CA 92780
{4}------------------------------------------------
#### 10. PREDICATE DEVICE:
| Product | Marketed by | Regulation<br>Number | Regulation<br>Name | Product Code | 510(k)<br>Number | Clearance Date |
|------------------------------------------------------------------------------|----------------------------------|----------------------|----------------------------------------|---------------------------------------------------|------------------|-------------------|
| Aquilion Lightning,<br>TSX-036A/1, V8.4<br>(Primary Predicate<br>Device) | Canon<br>Medical<br>Systems, USA | 21 CFR<br>892.1750 | Computed<br>Tomography<br>X-ray System | JAK:<br>System, X-ray,<br>Tomography,<br>Computed | K170019 | February 2, 2017 |
| Aquilion Prime SP<br>(TSX-303B/8) V10.2<br>with AiCE-i<br>(Reference Device) | Canon<br>Medical<br>Systems, USA | 21 CFR<br>892.1750 | Computed<br>Tomography<br>X-ray System | JAK:<br>System, X-ray,<br>Tomography,<br>Computed | K192832 | February 21, 2020 |
#### 11. REASON FOR SUBMISSION:
Modification of a cleared device
## 12. DEVICE DESCRIPTION:
Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i. The Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i is an 80-row CT system that is a whole body, multi-slice helical CT scanner, consisting of a gantry, couch and console used for data processing and display. This device captures cross sectional volume data sets used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician. This system is based upon the technology and materials of previously marketed Canon CT systems. In addition, the subject device incorporates the latest reconstruction technology, AiCE-i (Advanced intelligent Clear-IQ Engine - integrated), intended to reduce image noise and improve image quality by utilizing Deep Convolutional Network (DCNN) methods. This reconstruction algorithm is predicated on AiCE reconstruction algorithm previously 510(k) cleared per K192832 on the Canon CT scanner Aquilion Prime SP (TSX-303B/8) V10.2 with AiCE-i, which serves as a reference predicate for this submission. The DCNN methods can more fully explore the statistical properties of the signal and noise. By learning to differentiate structure from noise, the algorithm produces fast, high quality CT reconstruction for every patient.
#### 13. INDICATIONS FOR USE:
This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head.
The Aquilion Lightning has the capability to provide volume sets. These volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician.
AiCE (Advanced Intelligent Clear-IQ Engine) is a noise reduction algorithm that improves image quality and reduces image noise by employing Deep Convolutional Network methods for abdomen,pelvis, lung, cardiac, extremities, head and inner ear applications.
{5}------------------------------------------------
## 14. SUBSTANTIAL EQUIVALENCE:
The Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i, is substantially equivalent to the Aquillion Lightning (TSX-036A/1) V8.4, which received premarket clearance under K170019 and is marketed by Canon Medical Systems USA. The intended use of the Aquilion Lightning is the same as that of the predicate device. The changes made to the subject device include the addition of AiCE-i (Advanced intelligent Clear-IQ Engine-integrated), a reconstruction algorithm that utilizes Deep Convolutional Neural Network methods to reduce image noise and improve image quality, previously cleared under K192832. A comparison of the technological characteristics between the subject and the predicate device is included below.
| Item | Aquilion Lightning (TSX-036A/7) V10.2<br>with AiCE-i | Aquilion Lightning (TSX-036A/1) V8.4 |
|-------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------|
| 510(k) Clearance<br>Number | N/A | K170019 |
| Anatomical Region | AIDR 3D (Whole Body) | AIDR 3D (Whole Body) |
| Noise Reduction<br>Processing | AiCE (Abdomen and Pelvis, Chest,<br>Cardiac, Extremities, Brain, Inner ear)<br>AIDR 3D<br>AIDR 3D Enhanced<br>Quantum Denoising Smoothing (QDS)<br>AiCE | AIDR 3D<br>AIDR 3D Enhanced<br>Quantum Denoising Smoothing (QDS) |
| Processing<br>capability | Console CKCN-020C<br><br>Reconstruction processing system<br>(AiCE-i: CSAL-001A) | Console CKCN-020C<br><br>Reconstruction processing system<br>(N/A) |
| Image Quality<br>Claim | - Improved Quantitative high contrast<br>Spatial Resolution over AIDR 3D with<br>reduced noise<br>- Improved Quantitative Dose Reduction<br>over FBP<br>- Better Low-contrast Detectability than<br>AIDR 3D for abdomen at the same<br>dose<br>-Noise appearance/texture similar to<br>filtered backprojection | -N/A |
| Operating System | Microsoft Windows 10 | Microsoft Windows 10 |
## 15. 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 following standards IEC60601-1, IEC60601-1-9, IEC60601-1-2, IEC60601-1-3, IEC60601-1-6, IEC60601-2-28, IEC60601-2-44, IEC60825-1, IEC62304, IEC62366, NEMA XR-25, NEMA XR-26 and NEMA XR-29. Additionally, this device complies with all applicable requirements of the radiation safety performance standards, as outlined in 21 CFR §1010 and §1020.
{6}------------------------------------------------
This device conforms to applicable Performance Standards for Ionizing Radiation Emitting Products [21 CFR, Subchapter J, Part 1020]
#### 16. TESTING
Risk analysis and verification/validation activities conducted through bench testing demonstrate that the established specifications for the device have been met.
## Image Quality Evaluation
CT image quality metrics were performed, utilizing phantoms, to assess Contrast-to-Noise Ratios (CNR), CT Number Accuracy, Uniformity, Slice Sensitivity Profile (SSP), Modulation Transfer Function (MTF)-Wire, Standard Deviation of Noise (SD), Noise Power Spectra (NPS), Low Contrast Detectability (LCD). It was concluded that the AiCE-i images are substantially equivalent to the predicate device as demonstrated by the results of the above testing.
#### Quantitative Spatial Resolution
A phantom study was conducted to compare spatial resolution performance between AiCE, filtered backprojection and AIDR 3D. It was determined that there is double the high contrast spatial resolution versus AIDR 3D for body (AiCE Body Sharp).
#### Quantitative Body LCD, Noise Improvement and Dose Reduction
A dose reduction study was conducted using AiCE and based on the results, a dose reduction claim of up to 82.9%, relative to FBP, is supported as well as 15% improved low contrast detectability and noise reduction of 29% at the same dose for body compared to AIDR 3D.
Software Documentation for a Moderate Level of Concern, per the FDA guidance document, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices Document" issued on May 11, 2005, is included as part of this submission. This documentation includes justification for the Moderate Level of Concern determination as well as testing which demonstrates that the verification and validation requirements for the modifications described above have been met.
It was determined that representative clinical images were not necessary to demonstrate substantial equivalence of the subject device.
Cybersecurity documentation, per the FDA cybersecurity premarket guidance document "Content of Premarket Submissions for Management of Cybersecurity in Medical Devices" issued on October 2, 2014, is also included as part of this submission.
Additionally, testing of the subject device was conducted in accordance with the applicable standards published by the International Electrotechnical Commission (IEC) for Medical Devices and CT Systems.
## 17. CONCLUSION
The Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i is substantially equivalent to Aquilion Lightning (TSX-036A/1) V8.4, which was cleared via Pre-Market Notification 510(k), K170019. The
{7}------------------------------------------------
Aquilion Lightning (TSX-036A/7) V10.2 with AiCE-i, performs in a manner similar to and is intended for the same use as the predicate device, as indicated in product labeling. Based upon this information, conformance to standards, successful completion of software validation, application of risk management and design controls and the performance data presented in this submission it is concluded that the subject device has demonstrated substantial equivalence to the predicate device and is safe and effective for its intended use.
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
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.