Validation testing: 168 samples from 14 exams (12 patients)
3 (expert cardiac sonographers)
Cardiac chamber measurements
—
—
Pearson correlation coefficient of 0.81 or higher
—
—
Validation testing: 90 images from 45 exams across 5 institutions
3 (examiners)
Cardiac volume measurements
—
—
Pearson correlation coefficient of 0.87 or higher
—
—
Validation testing: 64 volumes from 32 exams across 5 institutions
3 (examiners)
Cardiac clinical measurements
—
—
89.6% success rate
—
—
Validation testing: 392 images from 32 patients across 5 institutions
3 (expert cardiac sonographers)
Indications for Use
The ACUSON Sequoia and Sequoia Select ultrasound imaging systems are intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Fetal, Abdominal, Pediatric, Neonatal Cephalic, Small Parts, OB/GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic, structures), Cardiac, Adult Cephalic, Musculoskeletal and Peripheral Vascular applications. The system supports the Ultrasonically-Derived Fat Fraction (UDFF) measurement tool to report an index that can be useful as an aid to a physician managing adult patients with hepatic steatosis. The system also provides the ability to measure anatomical structures for fetal, abdominal, pediatric, small organ, cardiac, transrectal, transvaginal, peripheral vessel, musculoskeletal and calculation packages that provide information to the clinician that may be used adjunctively with other medical data obtained by a physician for clinical diagnosis purposes. The ACUSON Origin ultrasound imaging system is intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Abdominal, Pediatric, OB/ GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic structures), Cardiac, Transesophageal, Intracardiac, Vascular, Adult Cephalic, and Peripheral Vascular applications. The catheter is intended for intracardiac and intra-luminal visualization of cardiac and great vessel anatomy and physiology as well as visualization of other devices in the heart of adult and pediatric patients. The catheter is intended for imaging guidance only, not treatment delivery, during cardiac interventional percutaneous procedures.
Device Story
Mobile, software-controlled diagnostic ultrasound systems; transmit/receive ultrasound echo data; display in B-Mode, M-Mode, Doppler (PW, CW, Color, Tissue, Amplitude), 3D/4D, and elastography. Used in clinical settings by trained healthcare professionals (sonographers, physicians). Systems integrate AI-based cardiac imaging and analysis packages (AI Assist, AI Measure, 2D HeartAI, 4D HeartAI) to support blood flow, valve, and anatomical feature assessment. Output includes real-time images, physiological signals, and quantitative measurements (e.g., UDFF, anatomical calculations). Clinicians use outputs adjunctively with other medical data for diagnosis and interventional guidance. Benefits include improved diagnostic visualization, automated measurement efficiency, and standardized cardiac assessment.
Clinical Evidence
No clinical studies were required. Bench testing only. Performance of AI algorithms (AI Assist, 2D HeartAI, 4D HeartAI, AI Measure) validated using independent datasets from multiple institutions. Metrics include success rates (e.g., 99.3% for AI Assist), Pearson correlation coefficients (e.g., 0.81-0.87 for HeartAI), and Bland-Altman bias analysis. Datasets included diverse patient demographics (BMI, age, gender) and standardized protocols.
Technological Characteristics
Mobile ultrasound system; 1.0-18 MHz frequency range; 23.8" HDR display; 13.3" touch screen. Patient contact materials tested to ISO 10993-1. Connectivity includes DICOM, DICOM SR, and wireless. Software includes AI/ML-based cardiac analysis. Safety standards: IEC 62359, AAMI ES60601-1, IEC 60601-1-2, IEC 60601-2-18, IEC 60601-2-37, ISO 14971.
Indications for Use
Indicated for fetal, abdominal, pediatric, neonatal cephalic, small parts, OB/GYN, cardiac, adult cephalic, musculoskeletal, peripheral vascular, transrectal, transvaginal, transesophageal, and intracardiac imaging in adult and pediatric patients. Used by trained healthcare professionals for diagnostic imaging and guidance during cardiac interventional percutaneous procedures.
Regulatory Classification
Identification
An ultrasonic pulsed doppler imaging system is a device that combines the features of continuous wave doppler-effect technology with pulsed-echo effect technology and is intended to determine stationary body tissue characteristics, such as depth or location of tissue interfaces or dynamic tissue characteristics such as velocity of blood or tissue motion. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.
{0}------------------------------------------------
October 30, 2023
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which 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.
Siemens Medical Solutions USA, Inc. % Sulgue Choi Regulatory Affairs Manager 22010 South East 51st Street ISSAQUAH WA 98029
#### Re: K232145
Trade/Device Name: ACUSON Sequoia Diagnostic Ultrasound System, ACUSON Sequoia Select Diagnostic Ultrasound System, ACUSON Origin Diagnostic Ultrasound System Regulation Number: 21 CFR 892.1550 Regulation Name: Ultrasonic Pulsed Doppler Imaging System Regulatory Class: Class II Product Code: IYN, IYO, ITX, OIJ, QIH Dated: July 18, 2023 Received: September 19, 2023
#### Dear Sulgue Choi:
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.
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).
{1}------------------------------------------------
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 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 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-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 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.
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-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,
# Yanna S. Kang -S
Yanna Kang, Ph.D. Assistant Director Mammography and Ultrasound Team DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
{2}------------------------------------------------
## Indications for Use
#### 510(k) Number (if known)
## K232145
#### Device Name
ACUSON Sequoia Diagnostic Ultrasound System, ACUSON Sequoia Select Diagnostic Ultrasound System ACUSON Origin Diagnostic Ultrasound System
Indications for Use (Describe) ACUSON Sequoia and ACUSON Sequoia Select
The ACUSON Sequoia and Sequoia Select ultrasound imaging systems are intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Fetal, Abdominal, Pediatric, Neonatal Cephalic, Small Parts, OB/GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic, structures), Cardiac, Adult Cephalic, Musculoskeletal and Peripheral Vascular applications.
The system supports the Ultrasonically-Derived Fat Fraction (UDFF) measurement tool to report an index that can be useful as an aid to a physician managing adult patients with hepatic steatosis.
The system also provides the ability to measure anatomical structures for fetal, abdominal, pediatric, small organ, cardiac, transrectal, transvaginal, peripheral vessel, musculoskeletal and calculation packages that provide information to the clinician that may be used adjunctively with other medical data obtained by a physician for clinical diagnosis purposes.
#### ACUSON Origin
The ACUSON Origin ultrasound imaging system is intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Abdominal, Pediatric, OB/ GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic structures), Cardiac, Transesophageal, Intracardiac, Vascular, Adult Cephalic, and Peripheral Vascular applications.
The catheter is intended for intracardiac and intra-luminal visualization of cardiac and great vessel anatomy and physiology as well as visualization of other devices in the heart of adult and pediatric patients. The catheter is intended for imaging guidance only, not treatment delivery, during cardiac interventional percutaneous procedures.
Operating Modes 2D-mode · 2D-mode · 2D-mode with Harmonics Imaging · 2D-mode with Harmonics Imaging for Contrast Agent Imaging 3D/4D Volume Imaging Color flow Doppler · Color (velocity) · Power (energy) Doppler • Pulsed Wave Doppler · Pulsed Wave Doppler Tissue Imaging · High Pulsed Repetition Frequency Pulsed Wave Doppler · Steerable Continuous Wave Doppler for imaging transducers · Continuous Wave Doppler for non-imaging transducers
M-mode
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| • M-mode with Harmonics Imaging |
|---------------------------------|
| • Anatomical M-Mode |
| Elastography |
| • Strain Imaging |
| • Shear Wave Elastography |
Combined Modes
| 2D-mode with color |
|--------------------------------|
| 2D-mode with Doppler |
| 2D-mode with color and Doppler |
| 2D-mode with M-mode |
| 2D-mode with M-mode and Color |
| 2D-mode with Elastography |
| 3D/4D Volume Imaging with colo |
*Type of Use (Select one or both, as applicable)*
| <span style="font-family: Arial, sans-serif;">☑</span> Prescription Use (Part 21 CFR 801 Subpart D) | ☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
|-----------------------------------------------------------------------------------------------------|-----------------------------------------------|
|-----------------------------------------------------------------------------------------------------|-----------------------------------------------|
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#### K232145 510(k) Summary September 28, 2023 Date: 1. Sponsor: Siemens Medical Solutions USA, Inc. Ultrasound Division 22010 South East 51st Street Issaquah, Washington 98029 Contact Person: Sulgue Choi Tel: (425) 281-9898 2. Device Name: ACUSON Sequoia Diagnostic Ultrasound System ACUSON Sequoia Select Diagnostic Ultrasound System ACUSON Origin Diagnostic Ultrasound System Common Name: Diagnostic Ultrasound System with Accessories Classification: Regulatory Class: Review Category: Tier II Classification Panel: Radiology Ultrasonic Pulsed Doppler Imaging 892.1550 90-IYN System Ultrasonic Pulsed Echo Imaging 892.1560 90-IYO System 892.1570 Diagnostic Ultrasound Transducer 90-ITX Biopsy Needle Guide Kit 892.1560 90-OlJ Automated Radiological Image 892.2050 90-QIH Processing Software Siemens Medical Solutions USA, Inc. Manufacturing Site: 22010 South East 51st Street, Issaquah, Washington 98029, UNITED STATES
#### 3. Leqally Marketed Predicate Devices
The ACUSON Sequoia, Sequoia Select, and Origin Diagnostic Ultrasound Systems are multi-purpose, diagnostic ultrasound systems with accessories and proprietary software,
{5}------------------------------------------------
and are substantially equivalent to the company's own products- the ACUSON Sequoia and Sequoia Select (K223735) which is the primary predicate device and the ACUSON SC2000 (K211726) as the reference device.
## 4. Device Description
The ACUSON Sequoia, Sequoia Select, and Origin Diagnostic Ultrasound Systems are multi-purpose, mobile, software-controlled, diagnostic ultrasound systems with an onscreen display of thermal and mechanical indices related to potential bio-effect mechanisms. The ultrasound system function is to transmit and receive ultrasound echo data and display it in B-Mode, M-Mode, Pulsed (PW) Doppler Mode, Continuous (CW) Doppler Mode, Color Doppler Mode, Color M Mode, Doppler Tissue Mode, Amplitude Doppler Mode, a combination of modes. Panoramic Imaging. Contrast agent Imaging. Virtual Touch Strain Imaging (except Origin), Virtual Touch - pSWE Imaging, Virtual Touch - SWE Imaging, Custom Tissue Imaging, 3D/4D Volume Imaging or Harmonic Imaging on a Display and provide cardiac anatomical and quantitative function software applications.
## 5. Intended Use/Indications for Use
ACUSON Sequoia and ACUSON Sequoia Select
The ACUSON Sequoia and Sequoia Select ultrasound imaging systems are intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Fetal, Abdominal. Pediatric, Neonatal Cephalic, Small Parts, OB/GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic structures), Cardiac, Pelvic, Vascular, Adult Cephalic, Musculoskeletal and Peripheral Vascular applications.
The system supports the Ultrasonically-Derived Fat Fraction (UDFF) measurement tool to report an index that can be useful as an aid to a physician managing adult patients with hepatic steatosis.
The system also provides the ability to measure anatomical structures for fetal. abdominal, pediatric, small organ, cardiac, transvaginal, peripheral vessel, musculoskeletal and calculation packages that provide information to the clinician that may be used adjunctively with other medical data obtained by a physician for clinical diaqnosis purposes.
## ACUSON Origin
The ACUSON Origin ultrasound imaging system is intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Abdominal, Pediatric, OB/GYN (useful for
{6}------------------------------------------------
visualization of the ovaries, follicles, uterus and other pelvic structures), Cardiac, Transesophageal, Intracardiac, Vascular, Adult Cephalic, and Peripheral Vascular applications.
The catheter is intended for intracardiac and intra-luminal visualization of cardiac and great vessel anatomy and physiology as well as visualization of other devices in the heart of adult and pediatric patients. The catheter is intended for imaging guidance only, not treatment delivery, during cardiac interventional percutaneous procedures.
#### Operating Modes
2D-mode
- . 2D-mode
- . 2D-mode with Harmonics Imaging
- . 2D-mode with Harmonics Imaging for Contrast Agent Imaging
3D/4D Volume Imaging
Color flow Doppler
- Color (velocity) ●
- . Power (energy)
Doppler
- Pulsed Wave Doppler ●
- . Pulsed Wave Doppler Tissue Imaging
- . High Pulsed Repetition Frequency Pulsed Wave Doppler
- . Steerable Continuous Wave Doppler for imaging transducers
- . Continuous Wave Doppler for non-imaging transducers
M-mode
- M-mode with Harmonics Imaging
- . Anatomical M-Mode
Elastography
- Strain Imaqing ●
- . Shear Wave Elastography
Combined Modes 2D-mode with color 2D-mode with Doppler 2D-mode with color and Doppler 2D-mode with M-mode 2D-mode with M-mode and Color 2D-mode with Elastography 3D/4D Volume Imaging with color
#### 6. Substantially Equivalent Devices and Summary of Technological Characteristics
The modified ACUSON Sequoia, Sequoia Select, and Origin Ultrasound Systems are based on the same system configuration as the company's own currently cleared
{7}------------------------------------------------
ACUSON Sequoia and Sequoia Select (K223735) with regard to the intended use and technological characteristics. The ACUSON Sequoia, Sequoia Select, and Origin will have different software and transducer options for different markets. The ACUSON Sequoia, Sequoia Select, and Origin will offer an optional cardiac imaging and analysis package with new transducers and software applications with Artificial Intelligent algorithms. The ACUSON Sequoia, Sequoia Select, and Origin will offer four (4) new software applications (Al Measure, Al Assist, 2D HeartAl, 4D Heart4) containing Machine Learning that are specifically intended to support cardiac imaging for blood flow, valves and anatomical features and modifies the Indications for Use. The modified ultrasound systems under this review and the predicate ultrasound systems function in the same manner as all diagnostic ultrasound systems and transducers.
The submission devices include following changes from predicate devices:
ACUSON Sequoia and Sequoia Select
- The addition of the Z6T transducer which is substantially equivalent to the Z6Ms . transducer previously cleared on ACUSON SC2000 (K211726).
- . The modified ACUSON Sequoia and Sequoia Select Ultrasound System includes the expansion of the 'transesophageal' clinical application which was already cleared on ACUSON SC2000 (K211726).
- . Also this Traditional 510(k) includes additional new or improved imaging features and image quality improvement: Cardiac Volume Imaging Feature, Al Measure, Al 2D Heart, Stress Echo, and Wide FOV which were cleared on the predicate device. ACUSON Sequoia and Sequoia Select(K223735) and SC2000 (K211726) to enable an improved customer experience.
## ACUSON Origin
- The addition of the Z6T transducer which is substantially equivalent to the Z6Ms ● transducer previously cleared on ACUSON SC2000 (K211726).
- . The addition of the 5Z1 transducer which is substantially equivalent to the 4Z1c transducer previously cleared on ACUSON SC2000 (K211726).
- . The addition of the AcuNav Lumos 4D ICE catheter which is substantially equivalent to the AcuNav Volume catheter previously cleared on ACUSON SC2000 (K211726).
- . The modified ACUSON Origin Ultrasound System includes the expansion of the 'transesophageal' and 'intracardiac' clinical application which was already cleared on ACUSON SC2000 (K211726).
- Also this Traditional 510(k) includes additional new or improved imaging features ● and image quality improvement: Cardiac Volume Imaging Feature, Al Assist, Al Measure, 2D Heart^, Stress Echo, 4D Heart^', and Wide FOV which were cleared on the predicate device, ACUSON Sequoia and Sequoia Select (K223735) and SC2000 (K211726) to enable an improved customer experience.
{8}------------------------------------------------
All other hardware and software features of the ACUSON Sequoia, Select, and Origin Diagnostic Ultrasound devices remain unchanged. The foundation of the ACUSON Sequoia, Sequoia Select, and Origin (this submission) is the ACUSON Sequoia and Sequoia Select (K223735) with features and transducers integrated with the ACUSON Sequoia and Sequoia Select (K223735) hardware and the ACUSON Sequoia, Sequoia Select, and Origin (this submission) reuse software developed for Sequoia and Sequoia Select (K223735) mainly as well as Z6T transducer, 5Z1 transducer, and Lumos 4D ICE catheter from ACUSON SC2000 (K211726).
The submission device is substantially equivalent to the predicate devices with regards to both intended use and technological characteristics.
| Feature / Characteristic | ACUSON<br>Sequoia<br>This<br>Submission | ACUSON<br>Sequoia<br>Select<br>This<br>Submission | ACUSON<br>Origin<br>This<br>Submission | ACUSON<br>Sequoia &<br>Sequoia<br>Select<br>K# 223735<br>Predicate<br>device | ACUSON<br>SC2000<br>K# 211726<br>Predicate<br>device |
|--------------------------------------------------------|-----------------------------------------|---------------------------------------------------|----------------------------------------|------------------------------------------------------------------------------|------------------------------------------------------|
| <b>Indications for Use:</b> | | | | | |
| Fetal | √ | √ | √ | √ | √ |
| Abdominal | √ | √ | √ | √ | √ |
| Pediatric | √ | √ | √ | √ | √ |
| Small Organ | √ | √ | -- | √ | √ |
| OB/GYN | √ | √ | √ | √ | √ |
| Cardiac | √ | √ | √ | √ | √ |
| Transesophageal | -- | -- | √ | -- | √ |
| Intracardiac | -- | -- | -- | -- | -- |
| Transrectal | √ | √ | √ | √ | √ |
| Transvaginal | √ | √ | -- | √ | √ |
| Peripheral vessel | √ | √ | √ | √ | √ |
| Musculo-skeletal<br>(conventional) | √ | √ | -- | √ | √ |
| Musculo-skeletal<br>(superficial) | √ | √ | √ | √ | √ |
| Neonatal cephalic | √ | √ | -- | √ | √ |
| Adult cephalic | √ | √ | √ | √ | √ |
| <b>Frequencies<br/>Supported:</b> | (1.0MHZ~18MHz) | (1.0MHZ~18MHz) | (1.0MHZ~18 MHz) | (1.0MHZ~18 MHz) | (1.7MHZ~10MHz) |
| <b>Modes:</b> | | | | | |
| B | √ | √ | √ | √ | √ |
| Feature / Characteristic | ACUSON<br>Sequoia<br>This<br>Submission | ACUSON<br>Sequoia<br>Select<br>This<br>Submission | ACUSON<br>Origin<br>This<br>Submission | ACUSON<br>Sequoia &<br>Sequoia<br>Select<br>K# 223735<br>Predicate<br>device | ACUSON<br>SC2000<br>K# 211726<br>Predicate<br>device |
| M | √ | √ | √ | √ | √ |
| PWD (Pulsed<br>Wave Doppler) | √ | √ | √ | √ | √ |
| CWD (Continuous<br>Wave Doppler) | √ | √ | √ | √ | √ |
| PW DTI (Doppler<br>Tissue Image) | √ | √ | √ | √ | √ |
| Color Doppler | √ | √ | √ | √ | √ |
| Power Doppler | √ | √ | √ | √ | √ |
| Combined<br>(BMDC) | √ | √ | √ | √ | √ |
| Features: | | | | | |
| Harmonic imaging | √ | √ | √ | √ | √ |
| Panoramic<br>imaging | √ | √ | √ | √ | √ |
| Color Panoramic<br>imaging | √ | √ | √ | √ | √ |
| Auto TEQ | √ | √ | √ | √ | √ |
| Cardiac Imaging<br>physiological<br>signal display | √ | √ | √ | √ | √ |
| Auto OB (eSie OB) | (Auto OB) | (Auto OB) | (Auto OB) | (eSie OB) | (eSie OB) |
| Compounding | √ | √ | √ | √ | √ |
| Contrast imaging | √ | √ | √ | √ | √ |
| Clarify | √ | √ | √ | √ | √ |
| Virtual Touch -<br>Strain | √ | -- | -- | √ | -- |
| Auto Calcs (eSie<br>Calcs) | (Auto Calcs) | (Auto Calcs) | (Auto Calcs) | (eSie Calcs) | (eie Calcs) |
| Speed of Sound | √ | √ | √ | √ | -- |
| Fusion | √ | √ | -- | √ | -- |
| Virtual Touch -<br>pSWE | √ | -- | -- | √ | -- |
| Virtual Touch<br>Auto pSWE | √ | -- | -- | √ | -- |
| Feature / Characteristic | ACUSON<br>Sequoia<br>This<br>Submission | ACUSON<br>Sequoia<br>Select<br>This<br>Submission | ACUSON<br>Origin<br>This<br>Submission | ACUSON<br>Sequoia &<br>Sequoia<br>Select<br>K# 223735<br>Predicate<br>device | ACUSON<br>SC2000<br>K# 211726<br>Predicate<br>device |
| Virtual Touch –<br>SWE | √ | √ | -- | √ | √ |
| UltraArt | √ | √ | √ | √ | -- |
| Modality Compare | √ | √ | √ | √ | -- |
| HD Zoom (Write<br>Zoom) | √ | √ | √ | √ | -- |
| Workflow<br>Protocols | √ | √ | √ | √ | √ |
| InFocus | √ | √ | √ | √ | -- |
| Flash sequencing | √ | √ | √ | √ | √ |
| Gesture control | √ | √ | √ | √ | -- |
| TeamViewer | √ | √ | √ | √ | √ |
| Motion Stabilized<br>Persistence | √ | √ | √ | √ | √ |
| DICOM | √ | √ | √ | √ | √ |
| DICOM SR | √ | √ | √ | √ | √ |
| Slow Flow Color<br>Doppler State | √ | √ | √ | √ | √ |
| Dynamic<br>MultiHertz | √ | √ | √ | √ | √ |
| 3D/4D Volume<br>Imaging Mode | √ | √ | -- | √ | √ |
| UDFF<br>(Ultrasonically-<br>Derived Fat<br>Fraction) | √ | √ | -- | √ | -- |
| Auto IMT | √ | √ | √ | √ | √ |
| Auto Doppler<br>(eSieDoppler) | √<br>(Auto<br>Doppler) | √<br>(Auto Doppler) | √<br>(Auto<br>Doppler) | √<br>(eSieDoppler) | √<br>(eSieDoppler) |
| Virtual workstation | √ | √ | √ | √ | -- |
| Velocity Variance<br>Mapping | √ | √ | √ | √ | √<br>(Color doppler map) |
| Feature / Characteristic | ACUSON<br>Sequoia<br>This<br>Submission | ACUSON<br>Sequoia<br>Select<br>This<br>Submission | ACUSON<br>Origin<br>This<br>Submission | ACUSON<br>Sequoia &<br>Sequoia<br>Select<br>K# 223735<br>Predicate<br>device | ACUSON<br>SC2000<br>K# 211726<br>Predicate<br>device |
| Cardiac Volume<br>Imaging Feature | √ | √ | √ | -- | √ |
| AI Assist | √ | √ | √ | -- | -- |
| AI Measure | √ | √ | √ | -- | √<br>(eSie Measure) |
| 2D HeartAI | √ | √ | √ | -- | √<br>(Velocity<br>Variance<br>Mapping, eSie<br>LH) |
| 4D HeartAI | -- | -- | √ | -- | √<br>(eSie LH, eSie<br>LVA, eSie RH +<br>GLS) |
| Stress Echo | √ | √ | √ | -- | √ |
| Wide FOV | √ | √ | √ | -- | -- |
| Wireless | √ | √ | √ | √ | √ |
| Monitor: 23.8" Dual<br>Layer High Dynamic<br>Range FPD | √ | √ | √ | √ | √ |
| Touch Screen: 13.3"<br>adjustable Touch<br>Screen | √ | √ | √ | √ | -- |
| Output Display<br>Standard (Track 3) | √ | √ | √ | √ | √ |
| Patient Contact<br>Materials | Tested to<br>ISO 10993-1 | Tested to ISO<br>10993-1 | Tested to ISO<br>10993-1 | Tested to ISO<br>10993-1 | Tested to<br>ISO 10993-1 |
| UL 60601-1 Certified | √ | √ | √ | √ | √ |
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{10}------------------------------------------------
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## 7. Nonclinical Data
The subject devices have been evaluated for acoustic output, biocompatibility, cleaning and disinfection effectiveness as well as thermal, electrical, electromagnetic and mechanical safety and have been found to conform to applicable medical device safety standards. The systems comply with the following voluntary standards:
- IEC 62359: Edition 2.1 2017-09, Ultrasonics Field characterization Test . methods for the determination of thermal and mechanical indices related to
{12}------------------------------------------------
medical diagnostic ultrasonic fields / Combines IEC 62359 (2010-10) and AMD 1 (2017-09)
- . AAMI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012 and A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment - Part 1: General requirements for basic safety and essential performance (IEC 60601-1:2005)
- IEC 60601-1:2005/A1(2012), Medical electric equipment Part 1: General ■ requirements for basic safety and essential performance / This document and its separate amendments continue to be valid together with the consolidated version
- IEC 60601-1-2 Edition 4.0 2014-02, Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral Standard: Electromagnetic disturbances - Requirements and tests
- I IEC 60601-2-18: Edition 3.0 2009-08, Medical electrical equipment - Part 2-18: Particular requirements for the basic safety and essential performance of endoscopic equipment
- . IEC 60601-2-37 Edition 2.1 2015. Medical electrical equipment - Part 2-37: Particular requirements for the basic safety and essential performance of ultrasonic medical diagnostic and monitoring equipment
- 트 ISO 10993-1 Fifth edition 2018-08, Biological evaluation of medical devices -Part 1: Evaluation and testing within a risk management process
- . IEC 60601-1-6:2010+A1:2013+A2:2020 Medical Electrical Equipment Part 1-6, General Requirements for Basic Safety and Essential Performance- Collateral standard: Usability
- . ANSI AAMI ISO 14971: Medical devices- Applications of risk management to medical devices, 2019
Al Summary of Testing
#### Al Assist:
- Summary of test statistics or other test results including acceptance criteria or l other information supporting the appropriateness of the characterized performance
{13}------------------------------------------------
- -Al Assist provides Color Box and Doppler Gate placement for 12 Cardiac Views and 1-4 anatomy locations in each view, for a total of 42 supported placements.
- -Aggregating test results over all cardiac views and placement locations, the algorithm is successful 99.3% of the time. Successful placement means that no adjustment or only minor adjustment needs to be made by the user.
- As tested on datasets from different scanning views, the algorithm success is 92% or higher for any placement location.
- 트 The number of individual patients' images were collected from
- For Al Assist validation testing, image data was collected from 12 patients.
- . The number of samples, if different from above, and the relationship between the two
- For Al Assist validation testing, for each patient, data was collected for 12 cardiac views using either the 5V1 or the 5Z1 transducer. For two patients, additional data was collected for 12 cardiac views using the 8V3 transducer. 16 frames of data evenly spaced over 1 second are collected for each case.
- -This gives a total of 168 samples from 14 exams(12 patients). 72 samples use 5V1, 72 samples use 5Z1 and 24 samples use 8V3.
- I Demographic distribution including Gender, Age, Ethnicity
- Age: 18 81 -
- Gender: Female: 17%, Male; 83% -
- Ethnicity/Country: US -
- BMI: 17.7 30.9 -
- 58% Normal (BMI <= 25 kg/m2) 42% Overweight / Obese (BMI > 25 kg/m2)
- Information about clinical subaroups and confounders present in the dataset 트
- -Test dataset include all 12 standard cardiac views supported with up to 4 anatomy areas supported by the Al Assist feature.
- Information about equipment and protocols used to collect images
- The Origin platform was used to collect all data. The data collection was performed by a cardiac sonographer who scanned 12 cardiac views included in an Adult Echocardiogram examination.
{14}------------------------------------------------
- Information about how the reference standard was derived from the dataset . (i.e., the "truthing" process)
- For Al Assist verification of algorithms on the platform, expert cardiac । sonographers provided "truth" by scoring the results of the AI Assist algorithm to assess success (no adjustment or minor adjustment needed) or failure (major adjustment needed). Three sonographers scored the results for each placement made by the algorithm.
- I Description of how independence of test data from training data was ensured
- -Testing was performed on patient data completely independent from the data used in the model development processes. The patients were not associated with the sites where model development training data was collected.
#### 2D HeartAl
- . Summary of test statistics or other test results including acceptance criteria or other information supporting the appropriateness of the characterized performance
- The accuracy of the 2D Heart^ as measured by comparison of 2D Heart^l with user edits compared to a reference standard ground truth on a dataset from five different institutions has a Pearson correlation coefficient of 0.81 or higher with a minimal bias by Bland Altman of less than 5.2. For subjects with a Normal BMI the performance of the Al Algorithm was 0.84 or higher. For subjects with a BMI > 25 (Obese) performance was greater than 0.82.
- . The number of individual patients' images were collected from
- The image dataset was collected from 45 exams from 5 institutions including different transducers (5V1, 5Z1), different views (Apical 2, 3, 4 chamber views) with frame rates greater than 17fps. Contrast was used in 12 exams.
- 트 The number of samples, if different from above, and the relationship between the two
- -There were 90 images extracted from the 45 exams.
- Demographic distribution including Gender, Age, Ethnicity .
{15}------------------------------------------------
- -Age: Adults 42-74 years
- Gender: Female; 24%, Male; 76% -
- Ethnicity/Country: US, Mexico -
- -BMI: 18 - 36
29% Normal (BMI <= 25 kg/m2) 71% Overweight + Obese (BMI > 25 kg/m2)
- Information about clinical subgroups and confounders present in the dataset 트
- During testing of the Al algorithm, we have included images from subjects with Normal and High BMI.
- 트 Information about equipment and protocols used to collect images
- -The dataset consists of exams from across five institutions, two different probes (5V1, 5Z1) and different Origin Systems. The data collection protocol was standardized across all data collection sites.
- 트 Information about how the reference standard was derived from the dataset (i.e., the "truthing" process)
- -For all datasets, three examiners perfomed all manual contouring and measurements. Variability was assessed by intraclass correlation (ICC), interreader variability was computed by using Pearson correlation and agreement (Bland-Altman). Reference standard for each measurement was established by calculating the mean value from the three examiners.
- 트 Description of how independence of test data from training data was ensured
- To ensure that the testing dataset is not mixed with the training data, we used datasets from different clinical sites for testing as compared to the clinical sites for training.
#### 4D HeartAl
- 트 Summary of test statistics or other test results including acceptance criteria or other information supporting the appropriateness of the characterized performance
- The accuracy of the Al algorithm as measured by comparison of Al Algorithm with user edits compared to a reference standard ground truth on a dataset
{16}------------------------------------------------
from five different institutions has a Pearson correlation coefficient of 0.87 or higher with a minimal bias by Bland Altman of less than 13.3. For subjects with a Normal BMI the performance of the Al Algorithm was 0.98 or higher. For subjects with a BMI > 25 (Obese) performance was greater than 0.81.
- 트 The number of individual patients' images were collected from
- The image dataset was collected from 32 patients from 5 institutions including different transducers (5Z1 (17 TTE), 6ZT (15 TEE)), Volume rates were > 13.4vps.
- The number of samples, if different from above, and the relationship between the ■ two
- -There were 64 volumes were extracted from the 32 exams.
- Demographic distribution including Gender, Age, Ethnicity
- Age: Adults 28-77 years -
- Gender: 68% Male, 32% Female -
- Ethnicity/Country: US, Mexico -
- BMI 21 34 -
15% Normal (BMI <= 25 kg/m2) 85% Overweight + Obese (BMI > 25 kg/m2)
- 트 Information about clinical subgroups and confounders present in the dataset:
- -During testing of the Al algorithm, we have included images from subjects with Normal and High BMI.
- Information about equipment and protocols used to collect images: I
- -The dataset was collected from across five institutions in the US and Mexico, two different probes (5Z1, 6ZT) and different Sequoia CV Systems. The data collection protocol was standardized across all data collection sites.
- 트 Information about how the reference standard was derived from the dataset (i.e., the "truthing" process)
- For all datasets, three examiners performed all manual contouring and measurements. Variability was assessed by intraclass correlation (ICC), inter-
{17}------------------------------------------------
reader variability was computed by using Pearson correlation and agreement (Bland-Altman). Reference standard for each measurement was established by calculating the mean value from the three examiners.
- Description of how independence of test data from training data was ensured ı
- To ensure that the testing dataset is not mixed with the training data, we used datasets from different clinical sites for testing as compared to the clinical sites for training.
#### Al Measure
- . Summary of test statistics or other test results including acceptance criteria or other information supporting the appropriateness of the characterized performance
- Al Measure covers a set of semi-automated cardiac measurements for -Doppler, BMode and M-mode acquisitions.
- । Aqgregating algorithm performance over all modes showed the Al algorithm was successful 89.6% based on acceptance of measurements as Pass or Pass with/Edit.
- As tested on datasets from different aquisition modes, the algorithm sucess is -88.1% or higher
- I The number of individual patients' images were collected from
- -The dataset was collected from 32 individual patients from 5 institutions
- 트 The number of samples, if different from above, and the relationship between the two
- -Overall 1354 samples were taken 392 images from 32 individual patients.
- 트 Demographic distribution including Gender, Age, Ethnicity
- Age: 4 79 years -
- Gender: Female; 44%, Male; 51%, Unknown; 5% -
- Ethnicity/Country: US, Mexico -
- BMI: 14 41.2 -
- 49% Normal (BMI <= 25 kg/m2)
- 51% Overweight + Obese (BMI > 25 kg/m2)
{18}------------------------------------------------
- . Information about clinical subgroups and confounders present in the dataset
- Test dataset includes all 15 measurement views from 3 acquisition modes (B--Mode, Doppler, M-Mode).
- 트 Information about equipment and protocols used to collect images
- The dataset consists of exams from across five institutions, five probes (5V1, -5Z1, 8V3, 10V4, Z6T) and different Sequoia CV Systems. The data collection protocol was standardized across all data collection sites.
- 트 Information about how the reference standard was derived from the dataset (i.e., the "truthing" process)
- For Al Measure verification of algorithms on the platform, expert cardiac sonographers provided "truth" by scoring the results of the Al Measure algorithm to assess success (measurements were deemed clinically acceptable). At least three sonographers scored the results for each measurement made by the algorithm.
- . Description of how independence of test data from training data was ensured
- -To ensure that the testing dataset is not mixed with the training data, we used datasets from different clinical sites for testing as compared to the clinical sites for training.
#### 8. Clinical Data
Since the ACUSON Sequoia, Sequoia Select and Origin Diagnostic Ultrasound Systems use the same technology and principles as existing devices, clinical studies were not required to support substantial equivalence.
## 9. Summary
Intended uses and other key features are consistent with traditional clinical practice and FDA quidelines. The design and development process of the manufacturer conforms to 21 CFR 820 Quality System Regulation and ISO 13485:2016 quality system standards. The product is designed to conform to applicable medical device safety standards and compliance is verified through independent evaluation with ongoing factory surveillance. Diagnostic ultrasound system has accumulated a long history of safe and effective performance. Therefore, it is the opinion of Siemens Medical Solutions USA, Inc. that the ACUSON Sequoia. Sequoia Select and Origin systems are substantially equivalent with respect to safety and effectiveness to devices currently cleared for market.
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Learn the FDA Browser
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.