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510(k) Data Aggregation
(99 days)
ACUSON Sequoia Diagnostic Ultrasound System; ACUSON Sequoia Select Diagnostic Ultrasound System; ACUSON
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, Transesophageal, 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 and pediatric 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 and Origin ICE 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, 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.
The system also provides the ability to measure anatomical structures for fetal, abdominal, pediatric, cardiac, peripheral vessel, 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 Sequoia, Sequoia Select, Origin, and Origin ICE Diagnostic Ultrasound Systems (software version VC10) are multi-purpose, mobile, software-controlled, diagnostic ultrasound systems with an on-screen display of thermal and mechanical indices related to potential bio- effect mechanisms. The function of these ultrasound systems is to transmit, receive, process ultrasound echo data (distance and intensities information about body tissue) in various modes of operation and display it as ultrasound imaging, anatomical and quantitative measurements, calculations, analysis of the human body and fluid flow, etc. These ultrasound systems use a variety of transducers to provide imaging in all standard acquisition modes and also have comprehensive networking and DICOM capabilities.
The provided FDA 510(k) clearance letter and summary discuss the ACUSON Sequoia, Sequoia Select, Origin, and Origin ICE Diagnostic Ultrasound Systems. This document indicates a submission for software feature enhancements and workflow improvements, including an "AI Measure and AI Assist workflow efficiency feature" and "Liver Elastography optimization."
Here's an analysis of the acceptance criteria and the study information provided:
Acceptance Criteria and Reported Device Performance
The submission focuses on enhancements to existing cleared devices rather than a de novo AI device. Therefore, the "acceptance criteria" discussed are primarily related to the performance of the Liver Elastography optimization using phantom testing.
Acceptance Criteria | Reported Device Performance |
---|---|
Liver Elastography Optimization: The system's performance in measuring stiffness within calibrated elasticity phantoms for pSWE, Auto pSWE, and 2D SWE modes must meet manufacturer's accuracy and variability criteria. | The verification results for Liver Elastography optimization using calibrated elasticity phantoms met the acceptance criteria for accuracy and variability. Specific numerical values for accuracy and variability are not provided in this document. |
Software Feature Enhancements and Workflow Improvements (including AI Measure and AI Assist): The modifications should not raise new or different questions of safety and effectiveness, and the features should continue to meet their intended use. | "All pre-determined acceptance criteria were met." The document states that the modifications do not raise new or different questions of safety and effectiveness, and the devices continue to meet their intended use. Specific performance metrics for the AI Measure and AI Assist features themselves are not detailed as quantitative acceptance criteria in this document. |
General Device Safety and Effectiveness: Compliance with relevant medical device standards (e.g., IEC 60601 series, ISO 10993-1, IEC 62304, ISO 13485) and FDA guidance. | The device complies with a comprehensive list of international and FDA standards, and non-clinical verification testing addressed system-level requirements, design specifications, and risk control measures. |
Study Details for Liver Elastography Optimization (SWE Performance Testing)
The primary study mentioned in the document for performance evaluation is related to the Liver Elastography optimization.
-
Sample Size Used for the Test Set and the Data Provenance:
- Test Set: Calibrated elasticity phantoms. The specific number of phantoms used is not stated beyond "calibrated elasticity phantoms."
- Data Provenance: Not explicitly stated, but implies laboratory testing using commercially available or manufacturer-certified phantoms. Transducers listed were DAX, 5C1, 9C2, 4V1, and 10L4.
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Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of those Experts:
- Ground Truth Establishment: The ground truth for the test set (phantom stiffness) was established by the phantom manufacturer, as they were "calibrated elasticity phantoms certified by the phantom manufacturer."
- Number/Qualifications of Experts: The document does not specify the number or qualifications of experts involved in the phantom's certification process or in the actual testing of the Siemens device. The testing appears to be objective, relying on the calibrated properties of the phantoms.
-
Adjudication Method for the Test Set:
- Adjudication Method: Not applicable. Phantom testing typically relies on quantitative measurements against known phantom properties, not human adjudication of results.
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If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
- MRMC Study: No, an MRMC comparative effectiveness study was not conducted according to this document. The submission focuses on technical enhancements and phantom validation for elastography, and system safety/effectiveness.
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If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Standalone Performance: The "SWE Performance Testing" with phantoms could be considered a form of standalone performance assessment as it evaluates the device's measurement capabilities against a known standard. However, the AI Measure and AI Assist features are described as "workflow efficiency features" where measurements are "automatically launched" after classification, implying an interaction with a human user rather than a fully standalone diagnostic output. No specific standalone performance metrics for the AI Measure/Assist components are provided.
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The Type of Ground Truth Used:
- Ground Truth: For the elastography testing, the ground truth was the known stiffness values of the calibrated elasticity phantoms.
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The Sample Size for the Training Set:
- Training Set Sample Size: The document does not provide information about a training set size for the AI Measure and AI Assist features or the elastography optimization. This type of 510(k) submission typically focuses on validation and verification of changes to an already cleared product, rather than detailing the initial development or training data for AI algorithms.
-
How the Ground Truth for the Training Set Was Established:
- Training Set Ground Truth: Not applicable, as information on a specific training set is not provided in this document.
Summary regarding AI components:
While the document mentions "AI Measure" and "AI Assist" as workflow efficiency features (e.g., launching relevant measurements after cardiac view classification), it does not provide detailed performance metrics, test set sizes, ground truth establishment, or clinical study information specifically for these AI components. The 510(k) emphasizes that these are "software feature enhancements and workflow improvements" that, along with other changes, do not raise new questions of safety and effectiveness, leading to substantial equivalence with the predicate device. The only detailed "performance testing" described is for the Liver Elastography optimization using phantoms. This suggests that the AI features themselves might have been validated through internal software verification and validation activities that are not detailed in this public summary, or their impact on diagnostic performance was considered incremental and not requiring specific clinical comparative studies for this particular submission.
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(88 days)
ACUSON Sequoia Diagnostic Ultrasound System; ACUSON Sequoia Select Diagnostic Ultrasound System; ACUSON
ACUSON Sequoia and 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, Transesophageal, 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 and pediatric 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 diagnosis purposes.
ACUSON Origin and Origin ICE
The ACUSON Origin and Origin ICE 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. 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.
The system also provides the ability to measure anatomical structures for fetal, abdominal, pediatric, cardiac, peripheral vessel, 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 Sequoia, Sequoia Select, Origin and Origin ICE Diagnostic Ultrasound Systems are multi-purpose, mobile, software-controlled, diagnostic ultrasound systems with an on-screen display of thermal and mechanical indices related to potential bioeffect 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 lmaging or Harmonic Imaging on a Display and provide cardiac anatomical and quantitative function software applications.
This document describes the acceptance criteria and study that proves the device called ACUSON Sequoia Diagnostic Ultrasound System from Siemens Medical Solutions USA, Inc. meets the acceptance criteria.
1. Table of Acceptance Criteria and Reported Device Performance
The submission details two AI features: "AI Abdomen" and "Trace AI."
AI Abdomen
Feature/Metric | Acceptance Criterion | Reported Device Performance |
---|---|---|
View Classification | Not explicitly stated as a numerical criterion, but the overall expectation is a high accuracy and usefulness. The summary indicates a focus on specific view types. | Achieved a success rate of 77.8% for view classification when aggregated across all 17 view types. When eliminating CBD and pancreas sagittal from the aggregated results, the accuracy increased to 82.5%. |
Semi-automated Measurements | Individual Equivalence Coefficient (IEC) below a prespecified success criterion of 0.25. (This indicates that the algorithm's measurements are very close to the ground truth, likely meaning a low difference/high agreement). | The IEC fell below the prespecified success criterion of 0.25 for all 12 measurements, with and without users editing the landmark locations. |
Trace AI
Feature/Metric | Acceptance Criterion | Reported Device Performance |
---|---|---|
DICE Coefficient for Orifice-type Structures | The 90th percentile shall have a minimum DICE coefficient of at least 80% with 90% confidence. (DICE coefficient is a measure of similarity between two images or segmentations, with 1 being perfect overlap and 0 being no overlap). | The lower 90% confidence bound for the 90th percentile is 0.95, which is greater than the requirement of 0.8, therefore, the test passes. |
2. Sample Size Used for the Test Set and Data Provenance
AI Abdomen:
- Sample Size: 105 exams from individual patients, resulting in 1,785 images extracted (15 B-Mode images per view and per transducer).
- Data Provenance: Retrospective, collected from 3 institutions in the United States.
Trace AI:
- Sample Size: 10 different adult patients, from which 24 volumes were extracted.
- Data Provenance: Retrospective, collected from three institutions in the US, Mexico, and Germany.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
AI Abdomen:
- Number of Experts: Three clinical users.
- Qualifications: All registered Clinical Sonographers with ARDMS accreditation (or equivalent), each with at least 3 years of clinical experience.
Trace AI:
- Number of Experts: Three clinical users.
- Qualifications: All registered Clinical Sonographers with ARDMS accreditation (or equivalent), each with at least 3 years of clinical experience.
4. Adjudication Method for the Test Set
AI Abdomen:
- For view classification, the ground truth was associated with each image at the time of imaging using a system protocol, implying a single determination at the point of acquisition.
- For semi-automated measurements, ground truth measurements were provided by three clinical users. The document does not explicitly describe an adjudication method (like 2+1 or 3+1 consensus) for these measurements, but the acceptance criterion of Individual Equivalence Coefficient (IEC) suggests a comparison of the algorithm's results against these expert measurements.
Trace AI:
- Ground truth measurements were provided by three clinical users. Each sonographer independently refined the initial circle provided by Trace AI to annotate the underlying orifice structure. They could only see their own annotations. The contour created by sonographers (Ground Truth) was then compared with the contour detected by Trace AI (Detection Truth). This implies a comparison against each expert's delineation, potentially implying an aggregation or statistical analysis of agreement rather than a formal consensus adjudication before comparison with the AI.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- No MRMC comparative effectiveness study was explicitly mentioned in the provided text, and therefore, no effect size of human readers' improvement with AI vs. without AI assistance can be determined from this information. The studies described are performance evaluations of the AI algorithms themselves against ground truth.
6. Standalone (Algorithm Only) Performance Study
- Yes, the studies described for both "AI Abdomen" and "Trace AI" are standalone performance evaluations of the algorithms. They assess the algorithms' accuracy in view classification, semi-automated measurements, and segmentation (DICE coefficient) against established ground truth without a human-in-the-loop component for the performance measurement. The "AI Abdomen" notes testing "with and without users editing the landmark locations" for measurements, implying that the algorithm's initial measurement (standalone) was evaluated. "Trace AI" describes experts refining initial circles given by Trace AI, and then comparing the expert-refined contour to the contour detected by Trace AI algorithm, further confirming a standalone evaluation of the algorithm's output.
7. Type of Ground Truth Used
AI Abdomen:
- View Classification: Ground truth view labels were associated with each image at the time of imaging using a system protocol. This suggests a form of expert labeling or pre-categorization at the point of data capture.
- Semi-automated Measurements: Expert consensus (or at least independent expert measurements) provided by three registered Clinical Sonographers.
Trace AI:
- Expert consensus/independent expert annotations: Ground truth measurements (delineations of orifice structures) were provided by three registered Clinical Sonographers independently.
8. Sample Size for the Training Set
- The document does not explicitly state the sample size for the training set for either AI Abdomen or Trace AI. It only focuses on the test set and ensures its independence from the training data.
9. How the Ground Truth for the Training Set Was Established
- The document does not explicitly state how the ground truth for the training set was established. It only mentions that the testing dataset was from different clinical sites than those used for training, to ensure independence.
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(130 days)
ACUSON Sequoia Diagnostic Ultrasound System, ACUSON Sequoia Select Diagnostic Ultrasound System, ACUSON
ACUSON Sequoia and 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, Transesophageal, 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 and pediatric 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 diagnosis purposes.
ACUSON Origin and Origin ICE
The ACUSON Origin and Origin ICE 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: 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.
The system also provides the ability to measure anatomical structures for fetal, abdominal, pediatric, cardiac, peripheral vessel, 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 Sequoia, Sequoia Select, Origin and Origin ICE Diagnostic Ultrasound Systems are multi-purpose, mobile, software-controlled, diagnostic ultrasound systems with an on-screen display of thermal and mechanical indices related to potential bioeffect 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.
Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided text, specifically for the expansion of the Ultrasonically-Derived Fat Fraction (UDFF) measurement tool to pediatrics:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria | Reported Device Performance |
---|---|
Clinical Accuracy: AUROC > 0.80 for correlation with MRI-PDFF | AUROC ≥ 0.87 |
Clinical Reliability: Test-retest Intraclass Correlation Coefficient (ICC) > 0.75 | ICC ≥ 0.97 |
Exam Time: Under 60 seconds | Exam time less than 60 seconds |
2. Sample Size Used for the Test Set and Data Provenance
- Number of individual patients: 105 patients.
- 40 patients scanned with the DAX transducer.
- 27 patients with the 5C1 transducer.
- 38 patients with the 9C2 transducer.
- Number of samples: 525 measurements (Five UDFF measurements were obtained per patient).
- Data Provenance: Data were collected from two institutions in the US and France. The studies tested UDFF in children during clinically indicated MRI procedures.
3. Number of Experts Used to Establish Ground Truth and Qualifications
The document does not explicitly state the number of experts used to establish ground truth or their specific qualifications (e.g., radiologist with X years of experience). It only states that "MRI PDFF was used as the reference standard." The interpretation and establishment of ground truth from MRI-PDFF would typically involve qualified medical professionals, but this detail is not provided.
4. Adjudication Method for the Test Set
The document does not specify an adjudication method like 2+1 or 3+1. The reference standard used was MRI-PDFF, which is a quantitative measure and therefore may not have required such an adjudication process.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study directly comparing human readers with and without AI assistance was not reported. The study focused on the performance of the UDFF tool itself against a reference standard.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Yes, the testing described appears to be for the standalone performance of the UDFF algorithm. The criteria and results focus on the measurements generated by the UDFF tool (AUROC, ICC, exam time) in comparison to the MRI-PDFF reference standard. While the tool is intended to "aid a physician," the performance metrics presented demonstrate the algorithm's capability independent of direct human interaction in the evaluation setup.
7. The Type of Ground Truth Used
The ground truth used was MRI-PDFF (Magnetic Resonance Imaging Proton Density Fat Fraction). Steatosis was defined as MRI-PDFF greater than 5%.
8. The Sample Size for the Training Set
The document explicitly states that the UDFF algorithm remained unchanged and was not retrained for these studies. Therefore, no specific training set sample size for this expansion is provided, as the existing algorithm developed for adults was applied to the pediatric population.
9. How the Ground Truth for the Training Set Was Established
Since the UDFF algorithm was not retrained and remained unchanged, the document does not describe how the ground truth for its original training set was established. It only clarifies that the data from these pediatric studies were considered "test data to evaluate the performance of UDFF in children using MRI PDFF."
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(103 days)
ACUSON Sequoia Diagnostic Ultrasound System, ACUSON Sequoia Select Diagnostic Ultrasound System, ACUSON
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.
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.
The provided FDA 510(k) summary describes the Siemens ACUSON Sequoia, ACUSON Sequoia Select, and ACUSON Origin Diagnostic Ultrasound Systems, focusing on new software applications (AI Measure, AI Assist, 2D HeartAI, 4D HeartAI) that incorporate Machine Learning algorithms for cardiac imaging.
The document includes summaries of validation testing for each of these AI features.
1. Table of Acceptance Criteria and Reported Device Performance
AI Feature | Acceptance Criteria / Performance Metric | Reported Device Performance |
---|---|---|
AI Assist | Overall Success Rate: Percentage of placements requiring no adjustment or only minor adjustment by the user. | 99.3% overall successful placement across all cardiac views and placement locations. For any single placement location, success is 92% or higher. |
2D HeartAI | Pearson Correlation Coefficient: With user edits compared to reference standard ground truth. | 0.81 or higher |
Bland-Altman Bias: With user edits compared to reference standard ground truth. | less than 5.2 (minimal bias) | |
Performance for Normal BMI subjects ( 25 kg/m2): Pearson Correlation Coefficient. | greater than 0.82 | |
4D HeartAI | Pearson Correlation Coefficient: With user edits compared to reference standard ground truth. | 0.87 or higher |
Bland-Altman Bias: With user edits compared to reference standard ground truth. | less than 13.3 (minimal bias) | |
Performance for Normal BMI subjects ( 25 kg/m2): Pearson Correlation Coefficient. | greater than 0.81 | |
AI Measure | Overall Success Rate: Percentage of measurements deemed clinically acceptable (Pass or Pass with/Edit). | 89.6% overall successful performance. For any single acquisition mode, success is 88.1% or higher. |
2. Sample Sizes Used for the Test Set and Data Provenance
AI Feature | Test Set Sample Size (Patients/Exams/Samples) | Data Provenance |
---|---|---|
AI Assist | 12 patients; 14 exams (12 patients, with 2 having additional data); 168 samples (16 frames x 12 cardiac views x 14 exams). | US; Retrospective (collected by a cardiac sonographer who scanned 12 cardiac views included in an Adult Echocardiogram examination). |
2D HeartAI | 45 exams; 90 images extracted. | US, Mexico; From 5 different institutions; Retrospective. |
4D HeartAI | 32 patients; 64 volumes extracted. | US, Mexico; From 5 different institutions; Retrospective (for 5Z1 (17 TTE) and 6ZT (15 TEE) transducers, with Volume rates > 13.4vps). |
AI Measure | 32 individual patients; 1354 samples (from 392 images). | US, Mexico; From 5 institutions; Retrospective (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). |
3. Number of Experts and Qualifications for Ground Truth
AI Feature | Number of Experts | Qualifications |
---|---|---|
AI Assist | 3 sonographers | Expert cardiac sonographers (implied by context). |
2D HeartAI | 3 examiners | "Examiners" performed all manual contouring and measurements. No specific years of experience mentioned, but expertise is implied for establishing reference standard. |
4D HeartAI | 3 examiners | "Examiners" performed all manual contouring and measurements. No specific years of experience mentioned, but expertise is implied for establishing reference standard. |
AI Measure | At least 3 sonographers | Expert cardiac sonographers (implied by context). |
4. Adjudication Method for the Test Set
AI Feature | Adjudication Method |
---|---|
AI Assist | Consensus-based scoring: Three sonographers scored the results for each placement made by the algorithm. Success was defined as "no adjustment or minor adjustment needed," while "failure" meant a "major adjustment needed." This implies a form of expert consensus without explicit mention of conflict resolution, but rather individual scoring that collectively determined the success rate. |
2D HeartAI | Mean value from multiple examiners: Three examiners performed all manual contouring and measurements. Reference standard for each measurement was established by calculating the mean value from the three examiners. Variability was assessed by intraclass correlation (ICC) and inter-reader variability by Pearson correlation and Bland-Altman. This is a form of 3-expert consensus by averaging. |
4D HeartAI | Mean value from multiple examiners: Identical to 2D HeartAI. Three examiners performed all manual contouring and measurements. Reference standard for each measurement was established by calculating the mean value from the three examiners. Variability was assessed by intraclass correlation (ICC) and inter-reader variability by Pearson correlation and Bland-Altman. This is a form of 3-expert consensus by averaging. |
AI Measure | Consensus-based scoring: At least three sonographers scored the results for each measurement made by the algorithm to assess success ("measurements were deemed clinically acceptable"). Similar to AI Assist, this implies a form of expert consensus without explicit mention of conflict resolution. |
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study to measure the effect size of human readers improving with AI vs. without AI assistance. The studies performed focus on the standalone performance of the AI algorithms, often with user edits being factored in, but not a direct comparison of human performance with and without AI.
6. Standalone Performance Study
Yes, standalone performance studies were done for each AI feature:
- AI Assist: Evaluated the algorithm's ability to successfully place Color Box and Doppler Gate based on expert sonographer scoring of its output (99.3% success). This is a standalone assessment of the algorithm's initial placement accuracy.
- 2D HeartAI: Evaluated the accuracy of the 2D HeartAI "as measured by comparison of 2D HeartAI with user edits compared to a reference standard ground truth." While user edits are mentioned, the reported correlation coefficient and bias (0.81 or higher, bias
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(55 days)
ACUSON Sequoia Diagnostic Ultrasound System, ACUSON Sequoia Select Diagnostic Ultrasound System
The ACUSON Sequoia and Sequoia Select 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: Fetal, Abdominal, Pediatric, Neonatal Cephalic, Small Parts, OB/GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic structures), Cardiac, Pelvic, Vascular, Musculosketal 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 Sequoia and Sequoia Select Diagnostic Ultrasound Systems are a multi-purpose mobile, software controlled, diagnostic ultrasound system with an on-screen display of thermal and mechanical indices related to potential bio-effect mechanisms. Its function is to transmit and receive ultrasound echo data and display it in B-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, Virtual Touch - pSWE Imaging, Virtual Touch - SWE Imaging, syngo Velocity Vector Imaging, Custom Tissue Imaging, 3D/4D Volume Imaging and Harmonic Imaging on a Display.
The provided text is a 510(k) summary for the Siemens ACUSON Sequoia and Sequoia Select Diagnostic Ultrasound Systems. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific acceptance criteria and a study proving the device meets those criteria, especially for new or AI-driven features.
The most relevant section about specific performance is regarding the Ultrasonically-Derived Fat Fraction (UDFF) measurement tool, which is described as reporting "an index that can be useful as an aid to a physician managing adult patients with hepatic steatosis" (Page 3, Page 6). The document states that the modified ACUSON Sequoia Ultrasound System includes "the expansion of the UDFF (Ultrasonically-Derived fat fraction) software features for 5C1 transducer which were already cleared on the ACUSON Sequoia (K221500)" (Page 7). This implies that the UDFF feature itself was previously cleared.
However, the 510(k) submission does not provide details about acceptance criteria or a study proving the device meets these criteria for the UDFF feature or any other feature in the format requested. In fact, it explicitly states:
"Since the ACUSON Sequoia and Sequoia Select Diagnostic Ultrasound Systems use the same technology and principles as existing devices, clinical studies were not required to support substantial equivalence." (Page 10)
This statement indicates that their substantial equivalence argument relies on the technological similarity to existing cleared devices, and thus a detailed clinical performance study (including acceptance criteria, sample sizes, expert ground truth, etc.) was not performed for this specific 510(k) submission.
Therefore, I cannot extract the requested information from the provided text. The document is a regulatory submission for a diagnostic ultrasound system based on substantial equivalence, not a clinical study report for a novel AI/software feature with detailed performance metrics.
To directly answer your request based on the provided text, many fields will be "Not Applicable" or "Not Provided."
Here's how the information would map to your request if it were available in the document:
Acceptance Criteria and Device Performance Study for Siemens ACUSON Sequoia and Sequoia Select Diagnostic Ultrasound Systems (as per provided document)
Given the nature of the provided 510(k) summary, which relies on substantial equivalence and states that clinical studies were not required, many of the requested details are not present.
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A table of acceptance criteria and the reported device performance
Feature/Criterion Acceptance Criteria (if stated) Reported Device Performance (if stated) Ultrasonically-Derived Fat Fraction (UDFF) measurement tool Not provided in this document "an index that can be useful as an aid to a physician managing adult patients with hepatic steatosis" (indicative only, no quantitative performance reported) General Device Performance Not provided in this document Relies on substantial equivalence to predicate device (K221500) Overall Conclusion Not provided for specific features in a quantitative manner, as clinical studies were not required for this submission. Not provided for specific features in a quantitative manner, as clinical studies were not required for this submission. -
Sample sizes used for the test set and the data provenance
- Test Set Sample Size: Not applicable / Not provided, as clinical studies were not required for this 510(k) based on substantial equivalence.
- Data Provenance: Not applicable / Not provided.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable / Not provided, as clinical studies were not required for this 510(k) based on substantial equivalence.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable / Not provided, as clinical studies were not required for this 510(k) based on substantial equivalence.
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If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
- No MRMC study was performed or reported in this document. The submission states, "clinical studies were not required to support substantial equivalence."
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No standalone performance study reported in this document. The submission states, "clinical studies were not required to support substantial equivalence."
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The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable / Not provided, as clinical studies were not required for this 510(k) based on substantial equivalence.
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The sample size for the training set
- Not applicable / Not provided. This document does not describe the development or training of an AI algorithm; rather, it describes a diagnostic ultrasound system relying on existing technology and a predicate device. The UDFF is a "software feature" that was "already cleared" on a previous device.
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How the ground truth for the training set was established
- Not applicable / Not provided, for the same reasons as above. The document does not detail the training of any new AI/software feature unique to this submission.
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