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The DeepSight NeedleVue LC1 Ultrasound System is intended for use in Abdominal, Pediatric, Small Organ, Peripheral Vascular, Fetal, Urological, and Musculoskeletal Conventional and Superficial Imaging. This device is indicated for Prescription Use Only and by qualified healthcare professionals (HCPs). The DeepSight NeedleVue LC1 ultrasound system is intended to be used by qualified and trained physicians or sonographers with at least basic ultrasound knowledge. The operator must have read and understood the user manual. The DeepSight NeedleVue LC1 ultrasound system is intended to be used in medical practices and clinical environments including healthcare facilities, hospitals and clinics.

The DeepSight NeedleVue LC1 Ultrasound System is a general-purpose diagnostic ultrasound system that is mounted on a movable cart and has a mobile console that provides digital acquisition, processing, and display capabilities. The subject device has three major functional blocks that are consistent across ultrasound systems including the predicate:

• A front end, which includes a single curved (a.k.a. convex) array transducer and analog signal processing functions. This transducer transmits acoustic energy into the body and receives the resulting reflections, and performs the signal processing functions on them required to produce an ultrasound image (e.g., analog to digital conversion, noise filtering);
• A back end, which includes a user interface, memory, and export via USB. The user interfaces include a computer keyboard, standard ultrasound parameter controls, an LCD touch screen, acoustic output display and an LCD image display. The touch screen is divided into a display area and a user interaction area, and allows for patient data entry, transmit voltage adjustment, transducer/preset selection, depth and focus adjustment, annotation, freeze, image and clip capture, and measurements.
• Power systems which generate, regulate and supply the required voltages to the system parts.

The provided FDA 510(k) Clearance Letter for the DeepSight NeedleVue LC1 Ultrasound System does not contain acceptance criteria for device performance nor does it describe a study to prove the device meets such criteria.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (GE Healthcare Logiq E9 Ultrasound System) based on:

• Intended Use and Indications for Use: Showing similarities in target patient populations and anatomical regions.
• Technological Characteristics: Comparing functional blocks, power sources, beamforming, controls, and display.
• Performance Testing (Non-clinical): Verifying compliance with relevant FDA guidance documents and recognized international standards for software, electromagnetic compatibility, thermal/mechanical/electrical safety, acoustic output, acoustic power, and reprocessing.

Therefore, it is not possible to provide the requested information based on the input document.

Here's why and what information is missing:

1. Acceptance Criteria and Reported Device Performance: The document lists various standards and guidance documents that the device's non-clinical performance testing complied with. However, it does not explicitly state specific acceptance criteria (e.g., image resolution in millimeters, signal-to-noise ratio in dB, penetration depth) for the DeepSight NeedleVue LC1 Ultrasound System and does not report quantitative data on how the device performed against any such criteria. It only states that the device was "found to have a safety and effectiveness profile that is similar to the predicate device."

2. Sample Size, Data Provenance, and Ground Truth for a Test Set (Clinical Study): The document explicitly states: "Clinical data was not required for this submission." This means there was no clinical study conducted to evaluate the device's performance in a real-world setting with patient data. Consequently, there is no information regarding:

   • Sample size used for a test set.
   • Data provenance (country, retrospective/prospective).
   • Number of experts or their qualifications.
   • Adjudication method.
   • Type of ground truth used.

3. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Since no clinical study was performed, an MRMC study comparing human readers with and without AI assistance was not conducted. The DeepSight NeedleVue LC1 is described as a general-purpose diagnostic ultrasound system, with no mention of AI features that would necessitate such a study.

4. Standalone Performance Study (Algorithm Only): The document describes the DeepSight NeedleVue LC1 as a general-purpose ultrasound system. While it mentions software testing, it does not describe an "algorithm only (standalone)" performance study in the context of diagnostic accuracy, as it's not an AI/CADe (Computer-Aided Detection) device in the sense that it provides an interpretation or analysis beyond standard imaging. The software testing mentioned relates to compliance with software life cycle processes, cybersecurity, and off-the-shelf software use.

5. Training Set Information: As no clinical study was reported and the device is a general-purpose ultrasound system (not an AI/ML-based diagnostic algorithm requiring a training set for diagnostic outcome prediction), there is no information about a training set, its sample size, or how its ground truth was established.

In summary, the provided document details a 510(k) clearance process based on substantial equivalence and compliance with non-clinical performance standards and guidance. It does not include information on clinical acceptance criteria or a study that specifically measures the device's performance against such criteria using patient data, as such a study was not required for this submission.

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The B-Scan module is used for imaging the internal structure of the eye, including the opaque media and posterior pathology, for the purpose of diagnosing pathological or traumatic conditions in the eye. The probe is intended to be used on both adult and pediatric patients that require imaging of the eye.

The B-Scan device is designed as an ultrasound B-Scan, which uses pulsed echo ultrasound to image the structure of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulse signals and provides a graphic display of returning pulse echoes to indicate the various structures.

All of the critical functions of the B-Scan are calculated in the same manner as in the predicate device, B-Scan Plus. The software algorithms for clinically critical functions remain the same as in the predicate device. However, the user interface and the workflow of B-Scan have enhancement to support cybersecurity implementation.

Both the subject device and predicate device are compatible with the Connect Software (K070943, K123349) and 4Sight (K152573). The software improvements in Connect were focused on enhancing features that optimize integration with the personal computer's processing, data storage, display, and printing capabilities.

The energy source for the B-Scan is USB power as in the predicate device, B-Scan Plus.

The software utilized on both the Connect and 4Sight platforms is fundamentally identical in core clinical functions, including image scanning, rendering, IOL calculations, data storage, and report formatting. Additionally, the key features within the B-Scan module do not differ significantly between the two systems, nor do they make an impact on the established clinical workflow.

Track 1 is being followed for this 510(k) submission.

Here's a breakdown of the acceptance criteria and the study details for the B-Scan Ultrasonic Imaging System, based on the provided FDA 510(k) clearance letter:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating pre-defined "acceptance criteria" for a novel device performance. However, we can infer acceptance criteria from the comparison table (Table 2) and the performance data section, where the subject device's performance is either "Same" or "SE" (Substantially Equivalent) to the predicate, or explicitly lists performance metrics.

For quantitative metrics, the "acceptance criteria" for the subject device can be interpreted as performing comparably or within acceptable limits relative to the predicate device, or meeting specific new specifications.

2. Sample Size Used for the Test Set and Data Provenance

The document does not explicitly state a sample size for patients or images used in any clinical or test set. The performance data mostly refers to bench testing and validation against standards.

• The only mention of a "sample" related to performance is "average time recorded across 5 probes" for the image preview time. This refers to hardware units, not patient data.
• Data Provenance: Not applicable, as no external data set or clinical study on patients is described beyond bench tests. The focus is on device specifications and in-house validation.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Not applicable. The submission does not describe a study involving expert readers establishing ground truth for a test set of images for diagnostic performance evaluation. The "Performance" section outlines bench tests and compliance with recognized standards.

4. Adjudication Method for the Test Set

Not applicable. Since there's no mention of a clinical test set requiring human expert review to establish ground truth, there is no adjudication method described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. The document does not describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it quantify improvement in human readers with AI assistance. The device is purely an imaging system, and there is no mention of AI assistance for image interpretation.

6. Standalone (Algorithm Only Without Human-in-the-loop Performance)

The device described is an "B-Scan Ultrasonic Imaging System," which is a diagnostic tool that produces images for human interpretation. It does not contain an AI algorithm for standalone diagnostic performance. Its performance is related to image acquisition parameters, accuracy of measurements, and adherence to safety/design standards.

7. Type of Ground Truth Used

For the quantitative performance claims (e.g., Clinical Accuracy Line/Area), the ground truth was established by physical measurements against known standards or calibrated references during bench testing ("Physical Accuracy and Range Test"). For other aspects, the ground truth is adherence to technical specifications, safety standards, and validated manufacturing/reprocessing procedures.

8. Sample Size for the Training Set

Not applicable. This device is an ultrasound imaging system, not an AI-driven diagnostic algorithm that requires a "training set" of data in the typical machine learning sense. The software aspects mentioned are primarily for device control, image rendering, data storage, and report formatting, enhanced for cybersecurity and usability – not for learning from data to perform a diagnostic task.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no training set mentioned for an AI algorithm.

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Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz), ultrasound attenuation and Velacur Determined Fat Fraction (VDFF). The Velacur Determined Fat Fraction combines ultrasound attenuation and backscatter coefficient measurements. The device is indicated to non-invasively determine liver tissue stiffness, attenuation, and Velacur Determined Fat Fraction. VDFF is not intended to be used in pediatric patients. These are meant to be used in conjunction with other clinical indicators in order to aid in clinical management of patients with liver diseases, including hepatic steatosis.

The device is intended to be used in a clinical setting and by trained medical professionals.

The device that is the subject of this submission is the substantially equivalent to that cleared under K233977, Velacur.

Velacur ONE is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam and Velacur Determined Fat Fraction is a combination of measured ultrasound attenuation and backscatter.

The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies 40, 50, and 60 Hz causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation.

Software and hardware changes were made to the device. The intended use of the device is unchanged. The user interface was updated to a more modern platform with the same workflow and outputs. The hardware components have been consolidated, combining the functionality of the computing unit and control unit. The activation unit has been designed to include more voice coils which are distributed throughout the unit. The power output and performance of the activation unit is unchanged.

The provided FDA 510(k) clearance letter and summary for Velacur ONE (LI-1100) focuses on substantiating equivalence to a predicate device (Velacur K233977) through bench testing and human factors testing. It explicitly states that "No clinical or animal testing was performed" for this specific submission, meaning there is no mention of a study involving human or animal subjects to prove the device's performance against clinical acceptance criteria.

Therefore, many of the requested details related to clinical study design, such as sample size for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, and ground truth types, cannot be extracted from this document as these types of studies were not conducted for the Velacur ONE (LI-1100) submission.

The information provided primarily relates to the bench testing validation of the algorithms, which is a different type of validation than a clinical study.

Here's an analysis of the available information:

1. Table of Acceptance Criteria and Reported Device Performance (Bench Testing)

The document refers to "acceptance criteria" within the context of bench testing against phantoms and comparison to the predicate device.

2. Sample Size and Data Provenance

• Test Set Sample Size:
  • Elasticity: 6 Homogeneous phantoms.
  • Attenuation: 6 attenuation phantoms.
  • VDFF: 6 different phantoms.
  • Note: These are phantoms, not patient data.
• Data Provenance: The data is from bench testing using phantoms, not clinical data from patients. Therefore, there is no country of origin or retrospective/prospective classification.

3. Number of Experts and Qualifications for Ground Truth

• Not applicable for this submission. Ground truth for bench testing is established by the known properties of the phantoms (e.g., CIRS values, labeled backscatter and attenuation). There is no mention of experts involved in establishing ground truth for the bench tests.

4. Adjudication Method for the Test Set

• Not applicable for this submission. As there's no clinical test set requiring human interpretation, no adjudication method is mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC study was done. The document explicitly states "No clinical or animal testing was performed."

6. Standalone Performance (Algorithm Only without Human-in-the-Loop)

• The performance data provided (bias, precision, correlation coefficients for elasticity, attenuation, and VDFF) appears to be standalone algorithm performance as measured on phantoms. The stated purpose of these tests is to validate the algorithms. While "User holds the probe against the skin, and software... is shown on the device display to indicate when the location is acceptable," the actual measurement and calculation of stiffness, attenuation, and VDFF are algorithmic. The performance metrics listed directly reflect the algorithm's output against the known phantom values.

7. Type of Ground Truth Used

• Phantom Properties: The ground truth for the bench testing was derived from the known and labeled properties of the reference phantoms (e.g., CIRS values for stiffness, labeled backscatter and attenuation for VDFF, and expected attenuation values).

8. Sample Size for the Training Set

• Not mentioned or applicable for this submission. This submission is a 510(k) for a modified device (Velacur ONE) claiming substantial equivalence to a predicate (Velacur). The focus is on verifying that the changes to the device (hardware consolidation, updated UI, new activation unit) do not negatively impact performance compared to the predicate, and that the algorithms maintain their validated performance. Details about the original training of the algorithms (which would have occurred for the predicate device's clearance) are not part of this specific document.

9. How the Ground Truth for the Training Set Was Established

• Not mentioned or applicable for this submission. Similar to point 8, this information would pertain to the original development and validation of the predicate device's algorithms, not this specific 510(k) for a modified device.

The study proves the device meets the acceptance criteria through extensive bench testing on phantoms, demonstrating that the modified Velacur ONE systems performs equivalently to its predicate (Velacur) and within pre-defined numerical tolerances for accuracy and precision when measuring phantom properties. This approach is common for 510(k) submissions of modified devices where clinical performance has already been established for the predicate.

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The Accuro 3S is a diagnostic ultrasound imaging system for use by qualified and trained healthcare professionals. Accuro 3S is intended to be used in a hospital or medical clinic environment at the point of care.

Accuro 3S supports B-mode imaging and a SpineNav-AI™ image processing software. Accuro 3S clinical applications include: musculoskeletal conventional and superficial, and guidance for needle or catheter placement. A typical examination using Accuro 3S is guidance of neuraxial anesthesia.

The Accuro® 3S is an ultrasound imaging device intended for use by qualified and trained healthcare professionals in hospital or medical clinic environments. The device offers B-mode imaging and a SpineNav-AI™ image processing software.

The Accuro 3S is a portable system with a small footprint that can be easily maneuvered within the intended use environment and at the point of care. The device features a touchscreen interface and articulated monitor arm to optimize viewing angle. An integrated battery pack allows the system to operate without wall power. Accuro 3S interfaces with healthcare IT networks to implement DICOM-based patient and image archival workflows, with image storage in an external PACS. The device utilizes a Dual-Array™ convex probe.

SpineNav-AI is an automated software tool that utilizes machine learning technologies to facilitate workflows associated with musculoskeletal imaging assessments of the lumbar spine.

The Accuro 3S Dual-Array probe comprises a side-by-side convex transducer array design. Each convex array has identical specifications: 64 elements, 3.5 – 4.0 MHz nominal center frequency, 480-micron pitch, and 50 mm radius of curvature.

Here's a breakdown of the acceptance criteria and the study that proves the Accuro 3S device meets them, based on the provided FDA 510(k) clearance letter.

Important Note: The provided document is an FDA 510(k) clearance letter, not a detailed study report. Therefore, some information, especially regarding the specifics of the AI study design (e.g., adjudication method beyond concensus, full statistical analysis of MRMC), is inferred or not explicitly stated in the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

Note on Acceptance Criteria: The document states that "success criteria for each anatomical annotation produced with SpineNav-AI were derived via a preliminary survey with intended users." For the Epidural Region Indicator's accuracy, specific numerical acceptance criteria are not explicitly stated in the same manner as the per-frame and per-sequence detection rates. The reported values are presented as the results of the evaluation against the radiologist panel ground truth.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size (Test Set): 120 sequences and 10,080 image frames obtained from a total of 81 individuals.
• Data Provenance:
  • Country of origin: Not explicitly stated, but collected at "seven (7) geographically diverse sites," implying multi-site collection.
  • Retrospective or Prospective: Not explicitly stated, but the description of "test dataset comprising a diverse range of demographic variables" and being "collected at seven (7) geographically diverse sites" suggests data collected specifically for this validation, making it likely prospective or a carefully curated retrospective collection. The phrase "completely distinct from the test dataset used for validation" for the training data further supports the idea of a dedicated test set.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Number of Experts: Three board-certified radiologists.
• Qualifications: "Board certified radiologists." No specific years of experience or subspecialty are detailed beyond board certification.

4. Adjudication Method for the Test Set

• Adjudication Method: The ground truth for anatomical labels was "established from a panel of three board certified radiologists." This strongly implies a consensus method where the three radiologists collectively determined the ground truth. The specific nature of how disagreements were resolved (e.g., majority vote, discussion-based consensus, or presence of a tie-breaker) is not explicitly detailed but falls under a consensus approach. It is not a 2+1 or 3+1 setup, but rather a direct panel consensus.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No, an MRMC comparative effectiveness study was not explicitly stated as having been done. The study focuses on the standalone performance of the AI against expert ground truth. Assistance to human readers is not mentioned as part of the validation design.
• Effect size of improvement: Not applicable, as an MRMC study comparing human readers with and without AI assistance was not described.

6. Standalone (Algorithm Only) Performance Study

• Was a standalone study done? Yes. The "AI Summary of Tests" section exclusively describes the performance of the SpineNav-AI™ software tool against ground truth established by experts, without human intervention or interaction. Metrics like per-frame accuracy, per-sequence detection success rate, and DICE scores are typical for standalone algorithm performance evaluation.

7. Type of Ground Truth Used

• Type of Ground Truth: Expert Concensus. The ground truth for anatomical labels was "established from a panel of three board certified radiologists." This means the truth was defined by the agreement of multiple human experts.

8. Sample Size for the Training Set

• Sample Size (Training Set): 25,536 images from 147 subjects.

9. How Ground Truth for the Training Set Was Established

• How Ground Truth Was Established: The document states that the training data and test data are "completely distinct." While it explicitly mentions how ground truth was established for the test set (panel of three board-certified radiologists), it does not explicitly state how the ground truth for the training set was established. It is a common practice for training data ground truth to also be established by experts, potentially with varying levels of expert involvement or adjudication compared to a highly scrutinized test set, but this specific detail is not provided in the submitted text.

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EchoGuide is a vascular ultrasound imaging device meant to aid in identification of the cannulation site on the skin of mature arteriovenous fistulas/grafts (AVFs/AVGs) in adult patients by appropriately trained healthcare providers in clinical settings. This device is not meant to replace the current standard of care cannulation methods.

EchoGuide is a 3D automated ultrasound solution designed to provide the benefits of ultrasound for arteriovenous fistula/graft cannulation without the need for extensive training. EchoGuide uses a three-dimensional probe to acquire live coronal plane images, in addition to automating imaging settings, to allow users to quickly assess the position, trajectory, and size of an arteriovenous fistula/graft. Users can then mark the position and trajectory of the access on the patient's skin before removing the probe and proceeding with cannulation.

The EchoGuide probe houses a 2D array on a track. The piezoelectric material in the transducer is used as an ultrasound source to transmit sound waves into the body. Sound waves are reflected back to the transducer and converted to electrical signals that are processed. The transducer is a 52 mm linear (192 element) motorized probe capable of capturing a volume of data. The motorized probe collects a series of 2D images to capture a volume. Through image analysis and processing, the volumes are sliced to create live coronal plane renderings.

The ultrasound system has a laptop form factor, with a bottom touch screen for user interaction and an additional top screen for display. The ultrasound system includes a transmitter and receiver, are all self-contained within the case. The ultrasound system interfaces with the probe through a port on the right side of the system.

The EchoGuide user interface defaults to a conventional 2D ultrasound image when the system powers on. Users can switch between this view, and the live coronal imaging via controls on the bottom screen of the ultrasound. Users can freeze the imaging and capture a snapshot of the fistula/graft as well. The snapshot displays a static view of the fistula/graft in the coronal and transverse planes.

EchoGuide is intended to be used in a clinical setting at the point of hemodialysis care.

This document primarily focuses on the FDA 510(k) clearance process for "EchoGuide (Version 1)" and its substantial equivalence to predicate devices, rather than a detailed report of a study proving the device meets specific performance acceptance criteria for an AI algorithm. The provided text touches on non-clinical and clinical testing but does not provide the granular details required to answer all parts of your request, particularly regarding specific performance metrics (e.g., sensitivity, specificity, accuracy), expert qualification for ground truth, and the specifics of AI-assisted human reader studies.

Here's an analysis based on the information provided, highlighting what can be discerned and what is missing:

Acceptance Criteria and Device Performance for EchoGuide (Version 1)

The provided FDA 510(k) clearance letter and summary primarily discuss the substantial equivalence of the EchoGuide device to existing predicate devices, focusing on its intended use, technological characteristics, and conformance to general safety and performance standards for imaging devices. It does not explicitly state acceptance criteria in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy for identifying cannulation sites) for an AI component.

The document mentions "imaging accuracy and quality" as confirmed by a clinical study, but without providing the quantitative acceptance criteria or the reported performance values against these criteria.

Missing Information:

• A specific table of acceptance criteria for AI-driven performance metrics (e.g., a specific target sensitivity or accuracy).
• Reported device performance values against these specific AI-driven criteria. The text only vaguely states "confirms the imaging accuracy and quality of EchoGuide for in vivo use."

Study Details (Based on available information):

1. Table of Acceptance Criteria and Reported Device Performance:

As noted above, this level of detail is not provided in the given FDA 510(k) document. The document focuses on showing substantial equivalence and conformance to general device standards.

2. Sample Size and Data Provenance for Test Set:

• Sample Size: The document states, "Data from a non-significant risk observational study was used to confirm in vivo imaging adequacy of EchoGuide for the exam of hemodialysis accesses." It further specifies that "Images were collected on upper arm arteriovenous fistulae." However, the exact sample size (number of patients or images) for this "test set" is not specified.
• Data Provenance: The study was described as a "prospective, single arm, non-randomized, observational study." The country of origin is not explicitly stated, but given the FDA clearance, it's highly likely to be US data or data suitable for US regulatory submission.

3. Number and Qualifications of Experts for Ground Truth:

• The document does not provide any information on the number of experts used to establish ground truth or their specific qualifications (e.g., "Radiologist with X years of experience").
• It mentions the device is "meant to aid in identification of the cannulation site...by appropriately trained healthcare providers in clinical settings," but doesn't detail how the 'true' cannulation sites were established for the study.

4. Adjudication Method:

• The document does not provide any information on the adjudication method used for establishing ground truth (e.g., 2+1, 3+1 consensus).

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance. The focus is on the device's imaging quality for in vivo use.
• Therefore, there is no information on the effect size of how much human readers improve with AI vs. without AI assistance.

6. Standalone (Algorithm-Only) Performance:

• The device is described as an "ultrasound solution designed to provide the benefits of ultrasound for arteriovenous fistula/graft cannulation" and automates "imaging settings" to allow users to "assess the position, trajectory, and size." It also states, "EchoGuide is a vascular ultrasound imaging device meant to aid in identification of the cannulation site...by appropriately trained healthcare providers."
• This phrasing suggests that the device (likely including algorithmic processing for image presentation and perhaps automated measurements/guidance, but without explicit AI claims) is intended to be used by a human operator to assist in a task. It is not presented as a standalone diagnostic algorithm that outputs a decision on its own.
• The document does not explicitly describe a standalone ("algorithm-only") performance study in terms of metrics like sensitivity, specificity, or AUC as one might see for a diagnostic AI. The "imaging accuracy and quality" mentioned is likely related to the visual representation and utility for a human user.

7. Type of Ground Truth Used:

• The document refers to a "non-significant risk observational study" where "Images were collected on upper arm arteriovenous fistulae." The study's primary objective was "data collection." It confirms "in vivo imaging adequacy."
• The nature of the ground truth is not explicitly stated beyond being related to "in vivo imaging adequacy" for "hemodialysis accesses." For specific "identification of the cannulation site," ground truth could potentially involve:
  • Expert consensus (e.g., radiologists/sonographers outlining the vessel)
  • Pathology (unlikely for this application)
  • Outcomes data (e.g., successful cannulation rates after using the device, but this is usually a separate clinical utility study)
  • Perhaps direct measurements or annotations from images performed by clinicians in the study.
• The specific method for establishing the 'true' cannulation site or vessel parameters is not detailed.

8. Sample Size for Training Set:

• The document describes a clinical evaluation/validation study, but it does not provide information on the sample size of any training set used for the development of the EchoGuide's algorithms (if it uses machine learning/AI models). This information is typically found in design validation documentation, not necessarily in the public 510(k) summary focused on substantial equivalence.

9. How Ground Truth for Training Set Was Established:

• Since information on a training set is not provided, there is no information on how ground truth for such a set would have been established.

Summary of Missing Information Critical for Full Response:

The provided document, being a 510(k) clearance letter and summary, primarily focuses on demonstrating substantial equivalence to predicate devices and adherence to general performance standards, rather than providing a detailed clinical study report for an AI-driven device with specific performance metrics against pre-defined acceptance criteria. Therefore, many of the specific details requested regarding AI performance studies, sample sizes, expert qualifications, and ground truth establishment are not present in this particular type of FDA document.

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The Liverscan C is intended to provide shear wave speed measurements and estimates of tissue stiffness as well as ultrasound coefficient of attenuation (MAP: Mobile Attenuation Parameter) in internal structures of the body. The shear wave speed and stiffness measurements may be used as an aid to clinical management of adult patients with liver disease.

The Liverscan C is indicated for non-invasive measurement in the liver of 50 Hz shear wave speed and estimates of stiffness as well as determining a 3.5MHz ultrasound coefficient of attenuation (MAP: Mobile Attenuation Parameter).

The shear wave speed and stiffness, and MAP may be used as an aid to diagnosis and monitoring of adult patients with liver disease, as part of an overall assessment of the liver.

This device is designed to be used in a doctor's office to measure the stiffness and ultrasonic attenuation of the liver in patients with liver disease. It does so in a painless and completely noninvasive manner.

The Liverscan C is intended to provide shear wave speed measurements and estimates of tissue stiffness as well as ultrasound coefficient of attenuation (MAP: Mobile Attenuation Parameter) in internal structures of the body. The shear wave speed and stiffness measurements may be used as an aid to clinical management of adult patients with liver disease.

The Liverscan C is indicated for non-invasive measurement in the liver of 50 Hz shear wave speed and estimates of stiffness as well as determining a 3.5MHz ultrasound coefficient of attenuation (MAP: Mobile Attenuation Parameter).

The shear wave speed and stiffness, and MAP may be used as an aid to diagnosis and monitoring of adult patients with liver disease, as part of an overall assessment of the liver.

The provided document is a 510(k) Premarket Notification from the FDA, asserting that the "Portable Liver Elastography Ultrasound Diagnostic System (Liverscan C)" is substantially equivalent to a legally marketed predicate device.

Crucially, this document focuses on demonstrating substantial equivalence through non-clinical testing and comparison to a predicate device, rather than presenting a clinical study of the device's performance against defined acceptance criteria for diagnostic accuracy.

Therefore, I cannot extract information related to acceptance criteria for diagnostic accuracy and a study proving the device meets those criteria, as an independent clinical study demonstrating diagnostic performance was not performed, or at least not provided in this document for the purpose of the 510(k) submission.

Specifically, section 10, "Clinical Tests Performed," explicitly states: "No clinical test data was used to support the decision of substantial equivalence."

The "acceptance criteria" discussed in the document relate to engineering and safety standards (e.g., IEC standards for electrical safety, EMC, usability, software, biocompatibility, and performance) and functional tests, which the device did meet. However, these are not diagnostic performance metrics.

For completeness, I can describe what the document does provide regarding "acceptance criteria" and "device performance" in terms of engineering and regulatory compliance:

Summary of "Acceptance Criteria" and "Device Performance" as presented in the 510(k) document (focused on substantial equivalence, not diagnostic accuracy):

The document defines "acceptance criteria" in terms of compliance with various international standards for medical devices and successful completion of bench tests. The "device performance" is reported as meeting these standards and demonstrating substantial equivalence to a predicate device.

Missing Information: Due to the nature of a 510(k) submission focused on substantial equivalence through non-clinical testing, the document does not contain any information regarding:

• A table of diagnostic performance acceptance criteria (e.g., sensitivity, specificity, accuracy for a specific liver condition).
• Sample size used for a clinical test set for diagnostic accuracy.
• Data provenance for a clinical test set.
• Number of experts used to establish ground truth for a clinical test set.
• Qualifications of experts for establishing ground truth for a clinical test set.
• Adjudication method for a clinical test set.
• Multi-Reader Multi-Case (MRMC) comparative effectiveness study.
• Effect size of human readers improving with AI vs. without AI assistance.
• Standalone (algorithm only) diagnostic performance.
• Type of clinical ground truth used (e.g., pathology, outcomes data).
• Sample size for a clinical training set (as no clinical AI algorithm study is detailed).
• How ground truth for a clinical training set was established.

Therefore, I cannot populate the table and answer the requested questions as they pertain to clinical diagnostic performance, because the provided text explicitly states that no clinical test data was used for this 510(k) submission. The "study that proves the device meets the acceptance criteria" in this context refers to bench testing against engineering and safety standards to demonstrate substantial equivalence, not a clinical validation of diagnostic accuracy.

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The SpineUs™ system is a software-based, tracked, ultrasound imaging system and accessories, intended for diagnostic imaging. It is indicated for diagnostic ultrasound imaging in the following applications: musculoskeletal (conventional, superficial). The system is intended for use by trained chiropractors and radiologists in a hospital or medical clinic.

The SpineUs™ system is intended for assisting trained chiropractors and radiologists in acquiring, viewing, and measuring ultrasound images of the spine in both clinic and hospital settings. The SpineUs™ system is intended to be used as an adjunct to conventional imaging method that allows trained chiropractors and radiologists to measure spine-related anatomical components on images (e.g., intervertebral angles and spine curvature). The system also allows the review and management of patient measurement data. Clinical judgment of anatomy and experience are required to properly use the SpineUs™ system.

Patient management decisions should not be made based solely on the results of the SpineUs™ computer application. The user shall retain the ultimate responsibility of ascertaining the measurements based on standard practices and clinical judgement.

The SpineUs™ System is a diagnostic ultrasound system, which consists of the FDA cleared Clarius Ultrasound Scanner C3 HD3 (K213436), a consumer PC, a tracking system with OptiTrack cameras connected to a POE switch and active LED markers, and the SpineUs™ computer application.

The SpineUs™ computer application, installed in the consumer PC, processes the ultrasound imaging data received from the Clarius Ultrasound Scanner and the tracking data received from the tracking system. The SpineUs™ computer application allows the operator to view ultrasound images of the spine, segment the ultrasound images using artificial intelligence, generate and visualize 3D reconstructions of the surface of the spine in real-time, measure spine-related anatomical components (e.g., intervertebral angles and spine curvature), review and manage patient measurement data, and generate and export printable reports.

The SpineUs™ system comprises the following:
Transducer / Scanner: Clarius Ultrasound Scanner, model C3 HD3 (K213436)
Software: SpineUs™ computer application
Tracking system: Motive Software, OptiTrack Cameras, SpineUs™ Active LED Markers, Power over Ethernet (PoE) switch
Accessories: USB-C charging cables, USB-C charging block, Wall mounted camera holders/covers, Tracker Reference (includes belt), Consumer PC

Here's a breakdown of the acceptance criteria and study details for the SpineUs™ System, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance (Segmentation AI)

2. Sample Size Used for the Test Set and Data Provenance

• Test Set Sample Size: 31 patients for both Non-Clinical and Clinical Performance Testing.
• Data Provenance: The data used in the Testing Datasets was obtained from clinical sites that are independent from those included in the Development dataset. While the specific countries are not mentioned, the gender, age, BMI, and ethnicity demographics suggest a diverse patient population, likely from multiple regions. The data is retrospective, as it involves recorded ultrasound sequences that were subsequently analyzed.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Number of Experts: At least two clinical experts for the Segmentation AI outputs.
• Qualifications of Experts: Described as "trained clinical experts." No further specific qualifications (e.g., years of experience, specialty) are provided in the document for the test set ground truth.

4. Adjudication Method for the Test Set

• "At least two clinical experts" annotated the Segmentation AI outputs.
• "All annotations were reviewed by a separate annotator." This suggests a form of 2+1 or similar adjudication, where two experts make initial annotations, and a third (or a different "separate annotator") reviews them, potentially resolving disagreements or confirming consistency.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study was explicitly mentioned for AI-assisted versus without AI assistance.
• The clinical performance testing involved "three different observers measuring scoliosis angle on the SpineUs™ system images and X-ray images of the same patients." This was a comparison between the SpineUs™ system measurements and X-ray measurements, essentially using X-ray as a reference standard, not a comparison of human readers with and without AI assistance on the ultrasound images. Therefore, no effect size of human readers improving with AI vs. without AI assistance is provided.

6. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance)

• Yes, standalone performance testing was done for the Segmentation AI.
• The section "Standalone Segmentation AI performance testing" explicitly states its purpose was "to assess the ability of the Segmentation AI to delineate between bone surfaces and background on ultrasound images from a recorded ultrasound sequence." The Non-Clinical Performance Testing summary directly reports the AI's performance on its own outputs against the established ground truth.

7. Type of Ground Truth Used

• Expert Consensus: For the Segmentation AI in both development and testing, image-level annotations were performed by trained clinical experts to label bone surface structures. These annotations, reviewed by a separate annotator, served as the ground truth for pixel-based metrics.
• X-ray Measurements: For the clinical performance testing assessing scoliosis angle, X-ray images of the same patients were used as the reference standard for comparison with SpineUs™ system measurements.

8. Sample Size for the Training Set

• Training Set Sample Size (Development Data): 81 ultrasound image sequences from 45 patients, totaling 17,684 images.

9. How the Ground Truth for the Training Set Was Established

• Expert Consensus with CT Confirmation: Image-level annotations were performed on a per-frame basis by a team of trained clinical experts, who labeled bone surface structures.
• Radiological Confirmation: "When available, corresponding thoracic CT imaging served as a ground truth to assist in the annotation process." This indicates that CT scans were used as a definitive reference to guide and confirm the expert annotations where possible.
• Adjudication: "All annotations were reviewed by a separate annotator." This ensures consistency and quality of the ground truth labels.

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Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz), ultrasound attenuation and Velacur Determined Fat Fraction (VDFF). The Velacur Determined Fat Fraction combines ultrasound attenuation and backscatter coefficient measurements. The device is indicated to non-invasively determine liver tissue stiffness, attenuation, and Velacur Determined Fat Fraction. VDFF is not intended to be used in pediatric patients. These are meant to be used in conjunction with other clinical indicators in order to aid in clinical management of patients with liver diseases, including hepatic steatosis.

The device is intended to be used in a clinical setting and by trained medical professionals.

Velacur is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the orqan of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam.

The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies 40, 50, and 60 Hz causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation.

Minor hardware and software changes were made to the organ guide (cleared in K223287) was also extended to add more optional overlays on top of the liver overlay to help with optimizing the scan and training users to obtain adequate images. The significant change is the addition of a new output measure for Velacur, an ultrasound derived fat fraction (VDFF).

Here's a breakdown of the acceptance criteria and study details for the Velacur device, as described in the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The document describes two separate machine learning algorithms: the Velacur Determined Fat Fraction (VDFF) algorithm, the Organ Guide Extension, and the Wave Quality Guide. Each has its own acceptance criteria and performance metrics.

2. Sample Size Used for the Test Set and Data Provenance

• Velacur Determined Fat Fraction (VDFF):

  • Test Set Sample Size: 70 new patients
  • Data Provenance: From 3 separate sites (with different Velacur operators). Implied to be prospective, as it's separate from the training data. The document states "Data was collected from sites across the US and Canada" for training, and "Evaluation data was collected... from separate patients, sites and collected by different users than the data used for training in order to ensure data independence," suggesting a similar geographical distribution for the test set. Retrospective/prospective not explicitly stated for this particular validation cohort, but the nature of MRI scans for ground truth implies it would be collected alongside the Velacur scans.

• Organ Guide Extension:

  • Test Set Sample Size: More than 800 images from 21 patients.
  • Data Provenance: "Evaluation data was collected from volunteers and patients with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. All patients were recruited from hepatology clinics." Data was collected from sites across the US and Canada (implied to be similar for evaluation as for training). Data for evaluation was explicitly stated to be from "separate patients, sites and collected by different users than the data used for training," indicating an independent, possibly prospective collection for evaluation.

• Wave Quality Guide:

  • Test Set Sample Size: More than 4,000 images from 36 patients.
  • Data Provenance: "Evaluation data was collected from volunteers and patients with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. All patients were recruited from hepatology clinics." Data was collected from sites across the US and Canada (implied to be similar for evaluation as for training). Data for evaluation was explicitly stated to be from "separate patients, sites and collected by different users than the data used for training," indicating an independent, possibly prospective collection for evaluation.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Velacur Determined Fat Fraction (VDFF):

  • Number of Experts: Not specified.
  • Qualifications of Experts: Not specified. The MRI scans were "assessed to create the final measurement," implying expert interpretation without explicitly stating the number or qualifications.

• Organ Guide Extension:

  • Number of Experts: Not specified.
  • Qualifications of Experts: "experts in the field of sonography and/or ultrasound elastography." No specific experience level (e.g., years) is provided.

• Wave Quality Guide:

  • Number of Experts: Not specified.
  • Qualifications of Experts: "experts in the field of ultrasound elastography." No specific experience level (e.g., years) is provided.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (such as 2+1 or 3+1) for establishing ground truth for any of the algorithms. It generally states that ground truth was established by experts or through MRI-PDFF assessment, implying a single assessment per case or a consensus without detailing the process.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not reported in this document. The studies focus on the standalone performance of the AI algorithms.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, standalone performance studies were done for all three components:

• Velacur Determined Fat Fraction (VDFF): The reported correlation coefficient and AUC are measures of the algorithm's direct performance against a ground truth (MRI-PDFF).
• Organ Guide Extension: The Dice Coefficient and pixel accuracy measure the algorithm's ability to segment organs directly.
• Wave Quality Guide: The Dice Coefficient, sensitivity, and specificity measure the algorithm's direct ability to identify good quality waves.

7. The Type of Ground Truth Used

• Velacur Determined Fat Fraction (VDFF): MRI Proton Density Fat Fraction (MRI-PDFF). This is considered a highly accurate quantitative measure for liver fat.
• Organ Guide Extension: Manual image segmentation by experts.
• Wave Quality Guide: Manual image segmentation by experts.

8. The Sample Size for the Training Set

• Velacur Determined Fat Fraction (VDFF): 112 patients from 4 sites (used for parameter fitting/training).
• Organ Guide Extension: More than 5,000 patient images.
• Wave Quality Guide: More than 15,000 patient images from 100+ patients.

9. How the Ground Truth for the Training Set Was Established

• Velacur Determined Fat Fraction (VDFF): MRI-PDFF scans were assessed to create the final measurement.
• Organ Guide Extension: Manual image segmentation by experts in the field of sonography and/or ultrasound elastography.
• Wave Quality Guide: Manual image segmentation by experts in the field of ultrasound elastography.

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The SC1 Ultrasound Imaging System (Model: SC1) is intended for diagnostic ultrasound echo imaging, measurement, and analysis of the human body for general clinical applications including musculoskeletal (MSK), vascular, small parts (breast, thyroid) through B mode. Flow detection is possible using PWD (Power Doppler) mode.

SC1 is a transportable ultrasound system intended for use in environments where healthcare is provided by healthcare professionals.

The SC1 Handheld ultrasound imaging system, Model: SC1, is a general purpose, software-controlled, diagnostic ultrasound system that uses pulsed-echo technology (B Mode (Power Doppler); Frequency: 5 - 13 MHz; module: linear; depth max: 10 cm) to transmit ultrasound images via wired communication to a mobile device that utilizes the Android operating system. Its function is to acquire ultrasound data and to display the data in operation.

The SC1 Handheld ultrasound imaging system is a portable, general-purpose, software-controlled, hand-held diagnostic ultrasound system that consists of (i) the battery-operated, SC1L (Linear type Ultrasound Probe) that communicates wired with Android mobile device, (ii) the software that runs as an app on the mobile device, (iii) batteries, charger (Cradle), cable, power cord, and magnetizers (option), (iv) the instructions for use manual.

The SC1 App software can be downloaded to an Android mobile device and utilizes an icon touch-based user interface. The software enables ultrasound image review, controls for depth, gain, linear measurement.

The SC1 App software allows the user to image in real time and review freeze-frame images on the screen in a B-Mode and PD-Mode, 2-dimensional scan format.

SC1 Handheld ultrasound system is only intended for acquisition and real time diagnosis. SC1 Handheld ultrasound system (SC1 probe and SC1 app) provides functions on patient data (entering new patient information, editing patient data saving, storing, or transferring patient information). It is possible to connect to the PACS DICOM network (hospital network) to get the list of exams and export recorded exams. However, there is no option to export patient data via a USB cable.

Physician who is responsible for interpreting ultrasound images must be available in the room to provide diagnosis in real time.

SC1 Handheld ultrasound imaging system utilizes pulsed-echo technology to determine the depth and location of tissue interfaces, and to measure the duration of an acoustic pulse from the transmitter to the tissue interface and back to the receiver. Ultrasound waves are emitted from the transducer, propagate through tissues, and return to the transducer as reflected echoes. The returned echoes are then converted into electrical impulses by transducer crystals and further processed in order to form the ultrasound image presented on the screen.

The device components are not supplied sterile and do not require sterilization prior to use.

The provided text is a 510(k) summary for the FCU Co., Ltd. SC1 Handheld Ultrasound Imaging system (Model: SC1). While it details the device, its intended use, comparison to predicate devices, and various non-clinical tests conducted (electrical safety, EMC, software validation, biocompatibility), it explicitly states that "No clinical studies were considered necessary and performed."

Therefore, based on the provided document, the device's acceptance criteria related to clinical performance and the study proving it meets those criteria cannot be described as no such studies were conducted or reported in this 510(k) summary.

However, I can extract information regarding the non-clinical performance and the general acceptance criteria inferred from regulatory compliance.

Based on the provided 510(k) summary, here's what can be inferred about acceptance criteria (primarily non-clinical) and the "study" (non-clinical testing) conducted:

Since no clinical studies were performed, the "study that proves the device meets the acceptance criteria" refers to the non-clinical performance testing and regulatory compliance activities.

1. Table of Acceptance Criteria and Reported Device Performance (Non-Clinical)

2. Sample size used for the test set and the data provenance:

• Test Set (Non-Clinical): Not applicable in the traditional sense of a clinical test set. The "test set" for non-clinical performance refers to the physical device and its software being subjected to various engineering and lab-based tests. The document does not specify the number of individual devices or software builds tested, but implies that "the proposed device" (singular, referring to the model) underwent these tests.
• Data Provenance: The tests were conducted to demonstrate compliance with international standards (IEC, ISO, ANSI/UL) and FDA guidances. The manufacturing and testing entity is FCU Co., Ltd., based in Daejeon, Republic of Korea. The testing would be prospective in the sense that the device was actively tested to demonstrate compliance, not retrospectively analyzed from patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. As no clinical studies were performed, there was no clinical "ground truth" to establish through expert review for a test set. Ground truth for non-clinical tests is based on physical measurements, software validation protocols, and adherence to engineering specifications and regulatory standards by qualified testing personnel.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not Applicable. This is a concept related to clinical image interpretation by multiple readers. For non-clinical validation, "adjudication" typically refers to engineering review, quality assurance checks, and regulatory body assessment, not a specific consensus method for data labeling.

5. 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, a MRMC comparative effectiveness study was explicitly NOT done. The document states: "No clinical studies were considered necessary and performed." This device is an imaging system, not an AI-assisted diagnostic tool in the sense of providing automated interpretations.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not Applicable in the context of an AI algorithm. This device is an ultrasound imaging system. Its "performance" is about image acquisition, display, and measurement capabilities, not an AI algorithm making diagnostic decisions. When it refers to "software validation," it's about the functionality, safety, and reliability of the operational software, not an AI model's diagnostic accuracy.

7. The type of ground truth used:

• For non-clinical performance: The "ground truth" is adherence to established engineering specifications, published international standards (e.g., IEC for electrical safety, ISO for biocompatibility), and regulatory guidance documents. This is determined through physical measurements, simulated environments, and compliance testing.
• For clinical performance: None. No clinical ground truth was established, as no clinical studies were performed.

8. The sample size for the training set:

• Not applicable. This device is an ultrasound imaging system, not an AI model trained on a dataset. The software enables image review and control, not AI inference.

9. How the ground truth for the training set was established:

• Not applicable. See point 8.

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The ACUSON SC2000 Diagnostic Ultrasound 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: Cardiac, Neo-natal and Fetal Cardiac, Pediatric, Transesophageal, Adult Cephalic, Peripheral Vessel, Abdominal, Intraoperative Abdominal, Musculo-skeletal Conventional, and Musculo-skeletal Superficial applications. The system also provides the ability to measure anatomical structures 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 SC2000 Diagnostic Ultrasound System is a multi-purpose diagnostic ultrasound system with proprietary software and accessories. The function of the ACUSON SC2000 Diagnostic Ultrasound System 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, measurements, calculations, analysis of the human body and fluid flow, etc.

The provided document is a 510(k) summary for the ACUSON SC2000 Diagnostic Ultrasound System. It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it explicitly states that no clinical data was required or conducted to support substantial equivalence for this device.

Therefore, I cannot provide a table of acceptance criteria and reported device performance based on the provided text, nor can I answer questions about sample sizes, data provenance, expert adjudication, MRMC studies, standalone performance, or ground truth details, as these clinical study elements were not performed.

The document focuses on non-clinical data to demonstrate safety and performance, primarily through compliance with voluntary standards and compatibility testing with existing catheters.

Here's a breakdown of what can be extracted from the document regarding the device's validation:

1. Table of Acceptance Criteria and Reported Device Performance: Not applicable as no clinical study with explicit acceptance criteria for device performance (e.g., sensitivity, specificity, accuracy) was conducted or reported in this 510(k) summary. The document focuses on showing compliance with performance standards for ultrasound systems generally and compatibility with specific catheters.

2. Sample size used for the test set and the data provenance: Not applicable. No clinical test set data from patients was presented.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No clinical test set requiring expert ground truth was performed.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. No clinical test set requiring adjudication was performed.

5. 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: Not applicable. This device is an ultrasound system and there is no mention of AI assistance or human reader studies.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This device is an ultrasound system, not an algorithm-only device. Performance evaluations focused on the system's ability to generate ultrasound images and facilitate measurements, as well as its compatibility with certain catheters.

7. The type of ground truth used: Not applicable. No clinical ground truth (e.g., pathology, outcomes data, expert consensus) was used as no clinical study was conducted.

8. The sample size for the training set: Not applicable. This document does not describe the development or training of an AI algorithm, but rather the clearance of an ultrasound system.

9. How the ground truth for the training set was established: Not applicable.

Summary of Device Validation based on the Provided Text:

The ACUSON SC2000 Diagnostic Ultrasound System's substantial equivalence to its predicate device (ACUSON SC2000 Diagnostic Ultrasound System v6.1 (VC11) K211726) is supported by non-clinical data.

• Rationale for No Clinical Data: "The proposed ACUSON SC2000 Diagnostic Ultrasound System did not require clinical studies to support substantial equivalence." (Page 9)
• Non-clinical Data Focus: The submission primarily demonstrates that:
  • The device complies with various voluntary standards related to medical electrical equipment, ultrasound field characterization, biological evaluation of medical devices, usability, risk management, software lifecycle process, and quality management systems (listed on pages 8-9).
  • The ACUSON SC2000 Diagnostic Ultrasound System v6.5 (VC15) is compatible with the AcuNav Crystal Ultrasound Catheter (K233270) and SoundStar Crystal Ultrasound Catheter (K240050), and the SwiftLink Plus Connector. This compatibility testing demonstrates that the system performs as intended with these accessory devices.
• Conclusion: "The non-clinical testing data support the safety of the device and demonstrate that the ACUSON SC2000 Diagnostic Ultrasound System is compatible with the AcuNav Crystal Ultrasound Catheter and the SoundStar Crystal Ultrasound Catheter and the system performs as intended in the specified use conditions. Therefore, it is the opinion of Siemens Medical Solutions USA, Inc. that the ACUSON SC2000 Diagnostic Ultrasound Systems are as safe and effective with substantially equivalent performance as the predicate device." (Page 9)

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