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The system is intended to be used by a trained/qualified healthcare professional in a hospital or clinical setting for ultrasound evaluation of fetal, abdominal, pediatric, small organ (thyroid, testes, breast), neonatal cephalic, musculoskeletal (conventional and superficial), cardiac (adult and pediatric), liver, peripheral vascular, trans-vaginal, trans-rectal, obstetrics/ gynecology applications in B-Mode(B, 2B, 4B), M-Mode, Anatomical M-mode, Color M, Color Flow Map (CFM), Power Doppler Imaging (PDI), Directional Power Doppler Imaging (DPDI), Pulsed Wave Doppler (PWD), Continuous Wave Doppler(CWD), 3D/4D, Elastography, Contrast Harmonic Imaging(CHI), S-Beam, Panoscope, Trapezoidal/Extended Sector Imaging, Tissue Doppler Imaging(TDD), Tissue Harmonic Imaging(THI), Macro Fidelity Imaging(MFI), ECG, Vector Space Flow (VS Flow), DICOM.

This system is a Track 3 device and the software used in Apogee C1, Apogee C2, Apogee C3, Apogee C5, Apogee K1, Apogee K2, Apogee K3, Apogee K5, Apogee U1, Apogee U2, Apogee U3, Apogee U5 Digital Color Ultrasound Imaging System is Ultrasound Software by SIUI and is based on the predicate device. The Document Level for the Ultrasound Software is Basic.

Here's a breakdown of the acceptance criteria and study information based on the provided text:

Important Note: The provided document is a 510(k) summary for an ultrasound system. It primarily focuses on demonstrating substantial equivalence to a predicate device based on technical characteristics, safety standards, and intended use. It explicitly states that clinical testing was not necessary to demonstrate substantial equivalence. Therefore, many of the requested items related to a clinical study (like test set sample size, expert qualifications, adjudication methods, MRMC studies, or standalone performance for an AI algorithm) are not applicable to this submission.

The document discusses non-clinical testing related to compliance with various international standards for medical electrical equipment, software, biocompatibility, and risk management. This type of testing ensures the device meets safety and performance criteria, but it's not a performance study in the sense of evaluating diagnostic accuracy against a ground truth for a specific clinical application.

1. Table of acceptance criteria and the reported device performance

Since this is a substantial equivalence claim for an ultrasound system, the acceptance criteria are primarily based on meeting safety standards and demonstrating comparable technical characteristics and intended use to the predicate device. There isn't a table of specific performance metrics for clinical accuracy as would be found in a study for an AI-powered diagnostic device.

• IEC 60601-1 (Basic safety & essential performance)
• IEC 60601-1-2 (EMC)
• IEC 60601-2-37 (Ultrasonic diagnostic & monitoring equipment)
• IEC 60601-2-25 (Electrocardiographs)
• ISO 14971 (Risk management)
• ISO 10993 (Biocompatibility parts 1, 5, 10, 23)
• IEC 62304 (Software life cycle)
• IEC 60601-1-6 (Usability)
• IEC 62366-1 (Usability engineering)
• ISO 15223-1 (Symbols for labels)
• ISO 13485 (Quality management systems)
• FDA Guidance for PMS for Software in Medical Devices
• Marketing Clearance of Diagnostic Ultrasound Systems and Transducers |
  | Software Document Level | Software documentation should meet the basic document level requirements, indicating proper development and verification processes. | "The Document Level for the Ultrasound Software is Basic." |

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable. The document explicitly states: "Clinical testing is not necessary for the Apogee C2... Digital Color Doppler Ultrasound Imaging System in order to demonstrate substantial equivalence to the predicate device." Therefore, there was no clinical test set in the traditional sense of a performance study to evaluate diagnostic accuracy. The "test set" for this submission refers to the physical device being tested against safety and performance standards, and comparison of its specifications to the predicate device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable. As explained above, no clinical test set requiring expert-established ground truth was part of this 510(k) submission.

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

• Not Applicable. No clinical test set with adjudication was part of this 510(k) submission.

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. This submission is for a general-purpose ultrasound imaging system, not an AI-assisted diagnostic tool. No MRMC study was conducted or reported.

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

• No. This submission is for an ultrasound imaging system. It states the software is "Ultrasound Software by SIUI" and is "based on the predicate device." It does not describe a standalone AI algorithm for diagnostic interpretation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Not Applicable. For the non-clinical testing performed (compliance with standards), the "ground truth" is adherence to the specifications of those standards (e.g., electrical safety limits, EMC performance, software lifecycle processes) and comparison of technical parameters to the predicate device. There was no clinical ground truth established for diagnostic performance.

8. The sample size for the training set

• Not Applicable. This submission does not describe an AI/machine learning model that would require a training set of patient data. The "software" referred to is the operating system and imaging processing software of the ultrasound machine, not a data-driven AI algorithm in the diagnostic sense implied by this question.

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

• Not Applicable. As no training set was used, no ground truth needed to be established for it.

Ask a specific question about this device

The system is intended to be used by a trained/qualified physician in a hospital or clinical setting for ultrasound evaluation of fetal, abdominal, pediatric, small organ (thyroid, testes, breast), neonatal cephalic, musculoskeletal (conventional and superficial), cardiac (adult and pediatric), peripheral vascular, trans-rectal, obstetrics/ gynecology and urology applications in B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, DPA, PWD, CWD, Combined (B, M, CFM, CPA, DPA, PWD, XBeam, Panoscope), and others (3D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, THI, MFI, ECG, VS Flow, Color M, DICOM).

The SIUI Apogee 1000 series (Apogee 1000/ Apogee 1000Neo/ Apogee 1000Lite/ Apogee 1000Exp/ Apogee 1000B/W/ Apogee 1 series (Apogee 1T/ Apogee 1T/ Apogee 1G) Digital Color Ultrasound Imaging System is capable of the following operating modes: B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, DPA, PWD, CWD, Combined(B, M, CFM, CPA, DPA, PWD, CWD, XBeam, Panoscope), and others (3D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, THI, TDI, DPA, MFI, ECG, VS Flow, Color M, DICOM). The system is designed for use in linear, convex, phased array scanning modes and supports linear, convex, phased array and endocavity (trans-vaginal and trans-rectal) transducers. The system has cine review, image zoom, measurements and calculations, image storage and review, printing and recording capabilities. This system is a Track 3 device and the software used in Apogee 1000 series / Apogee 1 series Digital Color Ultrasound Imaging System is Ultrasound Software by SIUI and is based on the predicate device. The Level of Concern for the Ultrasound Software is Moderate.

The provided document is a 510(k) summary for the SIUI Apogee 1000 series/Apogee 1 series Digital Color Doppler Ultrasound Imaging System. It describes the device, its intended use, and its comparison to a predicate device (SIUI Apogee 2300, K173000) to demonstrate substantial equivalence.

Based on the content, here's an analysis of the acceptance criteria and study information:

Description of Acceptance Criteria and Device Performance

The document does not explicitly state specific, quantifiable acceptance criteria (e.g., minimum sensitivity, specificity, or image quality metrics) for the device's performance. Instead, it relies on demonstrating substantial equivalence to a legally marketed predicate device (Apogee 2300, K173000) through compliance with recognized standards and a comparison of technological characteristics.

The "device performance" reported is the demonstration that the subject device (Apogee 1000 series/Apogee 1 series) is comparable to the predicate device in terms of:

• Intended Use: Both devices have the same intended use.
• Technological Characteristics: They share the same PC module, digital signal processing module, and ultrasound front-end module. The overall user interface is substantially unchanged.
• Functions: While some models of the subject device may lack the 4D imaging mode present in the predicate, they are similar in "other ultrasonic diagnostic functions, imaging modes, file storage management, compatible peripherals, measurement and calculation functions."
• Safety and Effectiveness: Non-clinical tests demonstrate that the subject device performs as well as, and is substantially equivalent with respect to safety and effectiveness of the predicate device.

Table of Acceptance Criteria and Reported Device Performance

Given the nature of the 510(k) submission for a diagnostic ultrasound system based on substantial equivalence, specific numerical acceptance criteria (like those for AI/CADe devices) are not typically presented in this format. The "acceptance criteria" here are implicitly meeting the regulatory requirements for substantial equivalence by demonstrating comparable technical characteristics and complying with relevant standards.

Study Details

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

   • The document describes non-clinical testing to demonstrate compliance with various international standards (e.g., electrical safety, EMC, software lifecycle, biological evaluation).
   • It does not mention a "test set" in the context of clinical image data or patient data. The evaluation is primarily based on engineering and performance standards applied to the device itself, rather than testing its diagnostic output against a specific dataset.
   • Data provenance is not applicable as this is not a study involving clinical data.

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

   • Not applicable. There is no mention of an external "test set" with ground truth established by experts. The "ground truth" implicitly comes from adherence to established engineering and medical device standards.

3. Adjudication method for the test set:

   • Not applicable. No "test set" or adjudication process described.

4. 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, an MRMC comparative effectiveness study was not done.
   • This submission is for a general-purpose ultrasound imaging system, not an AI/CADe (Computer-Aided Detection/Diagnosis) device designed to assist human readers or perform automated analysis. Therefore, the concept of "human readers improve with AI vs without AI assistance" is not relevant to this submission.

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

   • No, a standalone algorithm performance study was not done.
   • This device is an imaging system, not an algorithm, and is intended for use by a "trained/qualified physician" (human-in-the-loop).

6. The type of ground truth used:

   • For the non-clinical testing, the "ground truth" is implied by the technical specifications outlined in the international standards (e.g., electrical parameters, mechanical safety, software functionality, biocompatibility). It's not a clinical ground truth like pathology or patient outcomes.

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML device that requires a "training set."

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

   • Not applicable. No training set is mentioned.

Ask a specific question about this device

The system is intended to be used by a trained qualified physician in a hospital or clinical setting for ultrasound evaluation of fetal, abdominal, pediatric, small organ (thyroid, testes, breast), neonatal cephalic, musculoskeletal (conventional and superficial), cardiac (adult and pediatric), peripheral vascular, trans-rectal, obstetrics/ gynecology and urology applications in B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, CWD, CWD, Combined (B, M, CFM, CPA, DPA, PWD, CWD, XBeam, Panoscope), and others (3D/4D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, THI, MFI, ECG, VS Flow, Color M, DICOM).

The SIUI Apogee 6500/ Apogee 6300/ Apogee 6200 Digital Color Ultrasound Imaging System capable of the following operating modes: B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, DPA, PWD, CWD, Combined (B, M, CFM, CPA, DPA, PWD, CWD, XBeam, Panoscope), and others (3D/4D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, THI, MFI, ECG, VS Flow, Color M, DICOM).

The system is designed for use in linear, convex, phased array scanning modes and supports linear, convex, phased array and endocavity (trans-vaginal and trans-rectal) transducers. The system has cine review, image zoom, measurements and calculations, image storage and review, printing and recording capabilities.

This system is a Track 3 device and the software used in Apogee 6500 / Apogee 6300/Apogee 6200 Digital Color Ultrasound Imaging System is Ultrasound Software by SIUI and is based on the predicate device. The Level of Concern for the Ultrasound Software is Moderate.

The provided text is a 510(k) summary for the Apogee 6500, Apogee 6300, and Apogee 6200 Digital Color Doppler Ultrasound Imaging Systems. This document aims to demonstrate substantial equivalence to a legally marketed predicate device (Apogee 5500).

Based on the provided information, the device is an ultrasound imaging system, not an AI/ML-driven device, and therefore the majority of the requested information (acceptance criteria, specific study details for AI/ML performance, ground truth, expert adjudication, MRMC studies) is not applicable or not provided in this type of regulatory document.

Here's an breakdown of the available information in response to your request, and why some parts cannot be answered from this document:

1. A table of acceptance criteria and the reported device performance:

This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific performance metrics against pre-defined acceptance criteria for a novel AI/ML algorithm. The performance is assessed by comparison to the predicate device and compliance with relevant international standards.

• Acceptance Criteria (Implied for Substantial Equivalence): The device is substantially equivalent if it has the same intended use, similar technological characteristics, and does not raise new questions of safety or effectiveness compared to the predicate device.
• Reported Device Performance:
  • Intended Use: Same as the predicate device (Apogee 5500, K160853).
  • Technical Characteristics: Basic and key technical features (Operation Principle, Operation Controls, System Setup, Operation Modes, Measurement, Calculation and Report item Cine and File Management) are the same as the predicate.
  • Acoustic Power Levels: Meet FDA limits, same as the predicate device.
  • Materials of Probes: Same as the predicate device.
  • Probes: Similar probes as the predicate, with two new transducers (P5FC and V6LF) whose applications fall within the predicate's indications for use.
  • Safety and Efficacy: Differences between the new device and the predicate have no impact on safety or efficacy and do not raise new potential or increased safety risks. The new device is equivalent in performance to existing legally marketed devices.

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

• Not applicable / Not provided. As this is an ultrasound imaging system (not an AI/ML diagnostic algorithm), the performance is assessed through engineering tests, compliance with safety standards, and comparison of technical specifications to the predicate device. There is no "test set" in the context of image classification or detection algorithms with associated ground truth labels to be tested.

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

• Not applicable / Not provided. Ground truth establishment using expert review is relevant for AI/ML performance studies, which are not described in this 510(k) summary for an ultrasound imaging system.

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

• Not applicable / Not provided. Adjudication is relevant for resolving discrepancies in expert labeling of imaging data for AI/ML algorithm development/testing, which is not the subject of this document.

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. The document explicitly states: "Clinical testing is not necessary for the Apogee 6500/ Apogee 6300/ Apogee 6200 Digital Color Doppler Ultrasound Imaging System in order to demonstrate substantial equivalence to the predicate device." MRMC studies evaluating human reader performance with and without AI are not mentioned or required for this type of device clearance.

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

• Not applicable / Not provided in the context of diagnostic performance. This device is an imaging system, not a diagnostic algorithm. Its "performance" is assessed by its imaging capabilities, safety, and compliance with standards, not a standalone diagnostic accuracy.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Not applicable / Not provided. The concept of "ground truth" as used in AI development is not relevant to the substantial equivalence demonstration for this general-purpose ultrasound system. Its performance evaluation relies on engineering verification, compliance with safety standards (e.g., IEC 60601 series), and direct comparison of specifications and intended use to the predicate device.

8. The sample size for the training set:

• Not applicable / Not provided. This is not an AI/ML algorithm requiring a training set. The "software" mentioned (Ultrasound Software by SIUI) is based on the predicate device's software and its "Level of Concern" is Moderate, implying it was developed and validated through standard software engineering practices for medical devices (e.g., IEC 62304), not through machine learning training on a dataset.

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

• Not applicable / Not provided. As there is no AI/ML training set, the establishment of ground truth for such a set is not relevant.

In summary, this 510(k) pertains to a new generation of an existing ultrasound imaging system, demonstrating its substantial equivalence to a previously cleared model. The evaluation focuses on hardware, software (system-level, not AI/ML), safety standards, and technical specifications, rather than clinical performance metrics typically associated with AI/ML-driven diagnostic aids.

Ask a specific question about this device

The Apogee is a gas conserver intended as a delivery device for medical grade oxygen from a high-pressure oxygen cylinders. Apogee is an ambulatory device which allows patients to ambulate longer than they would with continuous flow regulator on the same cylinder. The Apogee is intended to be used in the hospital, healthcare facilities, or home care environments.

The proposed device, Apogee, senses each nostril independently through a bifurcated cannula and responds to the dynamic changes in nasal air-flow making a breath-to-breath determination of where to deliver the next bolus of oxygen: to the left, the right, or both nostrils. The Apogee Device is composed of the main components as detailed below: Control Unit, Control Board (Regulated Voltage Supply), Embedded Processor, User supplied Demand Cannula, The Apogee Bypass Cannula and Restrictor and Cylinder Tubing.

This document is an FDA 510(k) summary for the Apogee oxygen conserver. It describes the device, its intended use, and compares it to a predicate device (Inspired Technologies Model 350G). The information provided focuses on the device's design, technology, and non-clinical performance testing rather than clinical study results involving human patients or complex AI algorithms with specific performance metrics like sensitivity, specificity, or AUC.

Therefore, many of the requested elements for acceptance criteria and study details (like sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone AI performance, and training set details) are not applicable or not present in this type of regulatory document concerning a mechanical-electronic medical device like an oxygen conserver. The "performance data" section primarily refers to engineering and safety bench testing, not clinical performance studies with diagnostic accuracy targets for AI.

Here's a breakdown based on the provided document:

Acceptance Criteria and Device Performance for Apogee Oxygen Conserver

This 510(k) summary focuses on demonstrating substantial equivalence to a predicate device through engineering and safety testing. It does not contain specific "acceptance criteria" in the context of diagnostic performance (e.g., sensitivity, specificity, AUC) for an AI algorithm. Instead, the "acceptance criteria" are implied by compliance with recognized standards and comparable performance to the predicate device in bench tests.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a non-AI, mechanical-electronic device, the acceptance criteria are not typically expressed as diagnostic accuracy metrics. Instead, they relate to engineering specifications and performance in bench testing to ensure safety and effectiveness comparable to the predicate. The document highlights the following:

• Gas emission VOC
• Particulate Matter (PM2.5)
• Inorganic gases CO, CO2 and Ozone
• Toxicological Risk Assessment | Materials are safe for patient contact. |
  | Oxygen Bolus Delivery Equivalence
  (compared to predicate, volume and time) | Bench testing demonstrated that both devices (Apogee and predicate) delivered an equivalent amount of oxygen bolus to the patient in the same time. | Key functional performance matched the predicate. |
  | Trigger Sensitivity
  (compared to predicate) | Bench testing performed, details not quantified but implied comparable to predicate (-0.3 cmH2O for Apogee vs. +0.03 to -0.2 cmH2O for predicate). | Demonstrated a similar ability to sense patient inhalation. |
  | Volume Flow Performance | Bench testing performed. | Functional flow characteristics validated. |
  | Performance Pre- and Post-Cleaning | Bench testing performed. | Device maintains performance after cleaning. |
  | Breath Range Capability
  (e.g., up to 35 BPM for predicate) | Apogee: Up to 40 BPM | Apogee performs across a relevant physiological breath rate range, slightly better than predicate. |
  | Patient Oxygen Outlet Pressure
  (e.g., 19-25 psig for predicate) | Apogee: 19-30 psig | Comparable and within safe operating range. |
  | Water Ingress Protection
  (e.g., IPX1 for predicate) | Apogee: IP22 | Improved liquid ingress capability (IP22 for Apogee vs. IPX1 for predicate). No differences in safety or effectiveness found due to this improvement. |

Study Proving Device Meets Acceptance Criteria:

The study described is a series of non-clinical bench tests and compliance assessments against recognized industry standards, rather than a diagnostic accuracy or comparative effectiveness study involving human subjects or AI-assisted diagnostic tasks.

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

• Sample Size: Not specified in terms of patient data. The "test set" refers to physical units of the device tested in a lab setting. The number of units tested is not provided, but it would typically be a small number of engineering samples.
• Data Provenance: Not applicable in the context of patient data. This involves laboratory bench testing of physical device units, not patient data sets. The testing was presumably conducted by the manufacturer or contracted labs.

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

• Number of Experts: Not applicable. Ground truth for an oxygen conserver's performance in bench testing is based on engineering specifications, calibrated measurement equipment, and industry standards, not expert interpretation of medical images or clinical data.
• Qualifications of Experts: Not applicable. The "ground truth" for this device's performance is objective measurement against engineering specifications.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable. This is not a study where human interpretations are being adjudicated.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• MRMC Study: No. This type of study is typically performed for diagnostic devices (e.g., imaging AI) where human readers' performance is evaluated with and without an AI assist. This document concerns a therapeutic mechanical device.

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

• Standalone Performance: The "software" in this device controls the mechanical function (sensing breath and delivering oxygen bolus). Its "standalone performance" is implicitly assessed through the bench testing described (e.g., bolus delivery accuracy, trigger sensitivity). It's not a diagnostic algorithm with standalone performance metrics like sensitivity/specificity.

7. The Type of Ground Truth Used:

• Type of Ground Truth: The ground truth for this device's performance is based on engineering specifications, physical measurements from calibrated instruments, and compliance with recognized national and international standards for medical device safety and performance (e.g., AAMI ANSI ES 60601-1, IEC 60601-1-11, ISO 80601-2-67).

8. The Sample Size for the Training Set:

• Sample Size for Training Set: Not applicable. This is a non-AI mechanical device. The "software" mentioned is embedded control software, not a machine learning model that requires a training set in the conventional sense of AI development.

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

• Ground Truth for Training Set: Not applicable. As there's no machine learning training set, no such ground truth establishment occurred. The control logic for the device's functions (e.g., breath sensing, oxygen delivery) is derived from engineering design principles, physiological understanding, and validated algorithms for precise control, not from a data-driven training process.

Ask a specific question about this device

Diagnostic ultrasonic imaging for abdominal, pediatric, small organ, musculoskeletal, cardiac, peripheral vascular, transvaginal and trans-rectal applications in B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, PWD, CWD, Combined (B, M, CFM, CPA, PWD, CWD, XBeam, Panoscope, and others (3D, 4D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, MFI, ECG , VS Flow, Color M and DICOM).

The SIUI Apogee 2100/ Apogee 2300 is a Digital Ultrasound Imaging System capable of the following operating modes: B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, PWD, CWD, Combined (B, M, CFM, CPA, PWD, CWD, XBeam, Panoscope), others (3D, 4D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, MFI, ECG, VS Flow, Color M, DICOM). The system is designed for use in linear, convex, phased array and 3D scanning modes and supports linear, convex, phased array, 3D and endocavity (trans-vaginal and trans-rectal) transducers. The system has cine review, image zoom, measurements and calculations, image storage and review, printing and recording capabilities.

Here's a breakdown of the acceptance criteria and study information, based on the provided text, with a crucial caveat: The document describes a 510(k) submission for an ultrasound imaging system, which primarily focuses on demonstrating substantial equivalence to a predicate device, rather than proving a device meets specific clinical performance acceptance criteria through the types of studies you've listed (e.g., MRMC, standalone AI performance).

Therefore, many of your requested points about clinical studies, ground truth establishment, sample sizes for training/test sets, expert qualifications, and adjudication methods are not present in this type of regulatory document because they are not typically required for a 510(k) clearance of an ultrasound imaging system. The information provided heavily emphasizes hardware and software feature equivalence and safety standards.

Acceptance Criteria and Device Performance

The document doesn't explicitly state "acceptance criteria" in terms of clinical performance metrics like sensitivity, specificity, accuracy, or reader agreement. Instead, the acceptance criteria for this 510(k) submission are implied through demonstrating substantial equivalence to predicate devices in terms of:

1. Indications for Use: The new device's intended clinical applications must be substantially equivalent to or within the scope of the predicate devices.
2. Technological Characteristics: The new device's core technology, operating modes, and transducers must be substantially equivalent.
3. Safety and Effectiveness: Compliance with recognized medical device safety standards and acoustic output limits substituted for direct clinical evidence of safety and effectiveness for a new device.

Table of Acceptance Criteria and Reported Device Performance (as implied by the 510(k) process):

• Operating Modes: B-Mode (B, 2B, 4B), M-Mode, CFM, CPA, PWD, CWD, Combined (B, M, CFM, CPA, PWD, CWD, XBeam, Panoscope), others (3D, 4D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, MFI, ECG, VS Flow, Color M, DICOM).
• Comparison to Predicate: "All the Indications for Use of the Apogee 2100/ Apogee 2300 are included in the indications for use of predicate SIUI Apogee 1200." and "The Apogee 2100/ Apogee 2300 have three more imaging functions than the predicate SIUI Apogee 5500, namely VS Flow, Color M and DICOM." Additional new configurable transducers (L10LN, C6LN, U5LN) and 5 additional exams (Neonatal Cephalic, Trans-vaginal and Trans-rectal, Gynecology and Urology) are identical to Apogee 5500. |
  | 2. Technological Characteristics Equivalence | - Apogee 2100/2300 vs. Apogee 1200: "mainly have cosmetic changes," "same in their working principle and internal modules," "use the same PC module, digital signal processing module, and ultrasound front-end module." Control panel and display adjusted for ergonomics.
• Apogee 2100/2300 vs. Apogee 5500: "similar imaging modes," "similar diagnostic ultrasound applications," "similar technical parameters and hardware implementation principle" for transducers. |
  | 3. Safety (Acoustic Output & General Safety Standards Compliance) | - Tested per FDA Guidance (Sept 2008) for Diagnostic Ultrasound Systems and Transducers.
• Acoustic output measured and calculated per NEMA UD 2:2004.
• Conforms to IEC 60601-1, ISO10993-5, ISO 10993-10, and IEC 60601-1-2. |

Study Information (Based on the 510(k) document):

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

   • Test Set Sample Size: Not applicable/not provided. This document describes a 510(k) submission based on technical and performance equivalence and safety standards, not a clinical study with a specific test set of patient data with ground truth.
   • Data Provenance: Not applicable/not provided for a clinical test set. The submission relies on engineering tests, compliance with standards, and comparison to existing cleared devices.

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

   • Not applicable. No ground truth establishment by clinical experts is described for a test set of patient data.

3. Adjudication method for the test set:

   • Not applicable. No clinical test set requiring adjudication is described.

4. 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. An MRMC study was not done, as this is an ultrasound imaging system regulatory submission, not an AI diagnostic algorithm for which such studies are commonly required. The device itself is the imaging system, not an AI feature providing interpretive assistance.

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

   • Not applicable. This is not an AI algorithm. Its performance is inherent to its imaging capabilities, which are assessed against technical specifications and predicate device equivalence.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Not applicable for clinical ground truth. The "ground truth" in this context is adherence to engineering specifications, safety standards, and functional equivalence to predicate devices, verified through technical testing.

7. The sample size for the training set:

   • Not applicable. There is no mention of an algorithm being trained on a dataset.

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

   • Not applicable. No training set is mentioned.

In summary: The provided document is a 510(k) premarket notification for an ultrasound imaging system. The "study" referenced is largely a technical and engineering comparison study to predicate devices and a compliance assessment against recognized safety and performance standards. It does not involve a clinical study with patients, expert readers, or AI performance metrics as would be seen for a diagnostic AI device submission.

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The device is intended for use by a qualified physician for ultrasound evaluation of Fetal, Abdominal, Pediatric, Small Organ (Thyroid, Testes, Breast), Neonatal Cephalic, Musculoskeletal (Conventional and Superficial), Cardiac (Adult and Pediatric), Peripheral Vascular, Trans-rectal, Obstetrics/ Gynecology and Urology applications.

The SIUI Apogee 5500/ Apogee 5300 /Apogee 5800 is a Digital Ultrasound Imaging System capable of the following operating modes: B-Mode(B, 2B, 4B), M-Mode, CFM, CPA, PWD, CWD, Combined(B, M, CFM, CPA, PWD, CWD, XBeam, Panoscope), and other(3D, 4D, Trapezoidal /Extended Sector Imaging, Elastography, Anatomical M-mode, TDI, MFI, ECG).The system is designed for use in linear, convex, phased array and 3D scanning modes and supports linear, convex, phased array, 3D and endocavity (trans-vaginal and trans-rectal) transducers. The system has cine review, image zoom, measurements and calculations, image storage and review, printing and recording capabilities.

This document describes the premarket notification for the SIUI Apogee 5500, Apogee 5300, and Apogee 5800 Digital Color Doppler Ultrasound Imaging Systems. It focuses on demonstrating substantial equivalence to predicate devices rather than providing specific acceptance criteria and performance data for a novel AI device or software. Therefore, much of the requested information regarding acceptance criteria, sample sizes for test and training sets, expert qualifications, and adjudication methods is not directly available in the provided text.

Here is an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly those required to demonstrate substantial equivalence to previously cleared predicate devices, as per FDA's 510(k) pathway. The reported performance is primarily functional similarity and adherence to safety standards, rather than specific quantitative metrics.

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

The document does not explicitly mention a "test set" in the context of an AI/algorithm performance study. The evaluation appears to be based on engineering validation and verification testing of the ultrasound system's performance characteristics (e.g., acoustic output, image quality checks) and comparison to predicate devices, rather than a clinical study with a defined patient test set for an algorithm.

• Sample Size: Not specified for any performance testing beyond general system validation.
• Data Provenance: Not applicable from the provided text, as it doesn't describe a study with patient data for algorithm evaluation. The company (SIUI) is based in China.

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

This information is not provided because the submission is for an ultrasound imaging system, not an AI algorithm that would typically require expert-established ground truth on a test set of medical images. The "ground truth" for an ultrasound system typically relates to its physical performance characteristics, image quality, and diagnostic accuracy as determined by established medical principles and comparison to predicate devices.

4. Adjudication Method

Not applicable, as there is no mention of a study involving human reader interpretation or ground truth establishment that would require an adjudication method.

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

No. This type of study would be relevant for evaluating the impact of AI assistance on human reader performance, which is not the subject of this 510(k) submission.

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

No. This submission is for a full ultrasound imaging system, not a standalone AI algorithm. While the system incorporates "new imaging modes" such as XBeam, Panoscope, 3D, 4D, Elastography, etc., these are features of the imaging system itself, not separate AI algorithms. The document states these new modes "were tested and proved no impact on device safety and effectiveness," which implies technical validation rather than a standalone clinical performance study typically associated with AI.

7. Type of Ground Truth Used

The ground truth for the device's performance is implicitly based on:

• Engineering specifications and measurements: Adherence to established standards for acoustic output (NEMA UD 2), electrical safety (IEC 60601-1), and biocompatibility (ISO 10993-5, ISO 10993-10).
• Comparison to predicate devices: The "ground truth" for substantial equivalence is the validated performance and safety profile of the legally marketed predicate devices (SIUI Apogee 3800 and SIEMENS Acuson X700).
• Qualitative assessment: Clinical utility and image quality are likely assessed by medical professionals during internal validation, but no specific study details are provided.

8. Sample Size for the Training Set

Not applicable. This is not a submission for an AI algorithm that involves a training set.

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

Not applicable for the same reason as point 8.

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AMS Pelvic Floor Repair System is intended for use where the connective tissue has ruptured or for implantation to reinforce soft tissues where weakness exists in the urological, gynecological and gastroenterological anatomy. This includes but is not limited to the following procedures: pubourethral support, including urethral slings for the treatment of incontinence, vaginal wall prolapse repairs including anterior and posterior wall repairs, vaginal suspension, reconstruction of the pelvic floor and tissue repair.

The Apogee and Perigee Systems with IntePro Lite and InteXen LP are sterile, single use procedure kits that consist of stainless steel, curved needle passers and an implantable mesh assembly.

The provided text is a 510(k) summary statement and related FDA correspondence for a surgical mesh device. The document states that the device components were "tested for biocompatibility and performance requirements and found to be substantially equivalent to the predicate devices." However, it does not provide specific quantitative acceptance criteria or a detailed study description that proves the device meets those criteria.

Therefore, the requested information, which typically involves detailed performance metrics, sample sizes, expert involvement, and ground truth establishment, is not present in the provided text.

Here's a breakdown of why each point cannot be answered:

1. A table of acceptance criteria and the reported device performance: The document states "tested for biocompatibility and performance requirements and found to be substantially equivalent to the predicate devices." It does not provide a table with specific criteria (e.g., tensile strength, pore size, elasticity) or the numerical results from these tests.
2. Sample sized used for the test set and the data provenance: Not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned. The testing described is for biocompatibility and performance, not involving human interpretation of medical data where experts would establish ground truth.
4. Adjudication method for the test set: Not applicable for the type of testing described (biocompatibility and performance).
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 document is about a surgical mesh, not an AI-powered diagnostic or assistive tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is for a physical medical device.
7. The type of ground truth used: Not applicable in the context of the described physical device testing. The "ground truth" for material properties would be the established standards or values of the predicate device.
8. The sample size for the training set: Not applicable. This is not a machine learning device.
9. How the ground truth for the training set was established: Not applicable. This is not a machine learning device.

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The AMS Pelvic Floor Repair System is intended for use where the connective tissue has ruptured or for implantation to reinforce soft tissues where weakness exists in the urological, gynecological, and gastroenterological anatomy. This includes but is not limited to the following procedures: pubourethral support, including urethral slings, vaginal wall prolapse repairs including anterior and posterior wall repairs, vaginal suspension, reconstruction of the pelvic floor and tissue repair.

The Apogee and Perigee prolapse repair systems are part of the AMS Pelvic Floor Repair System family of devices. They consist of a permanently-implanted mesh assembly and non-implanted surgical instruments (needle passers) that are used as aids to place the mesh assembly in the pelvic floor.

This K081710 510(k) submission describes a modification to an existing surgical mesh device. The core of the submission revolves around demonstrating that the modified device (with a PC coating) is "substantially equivalent" to its predicate device (without the coating). This type of submission rarely includes detailed studies with acceptance criteria in the way a new device would. Instead, the "acceptance criteria" are implicitly met if the new device performs similarly enough to the predicate device.

Here's the breakdown of the information requested, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a 510(k) for a modified device, the "acceptance criteria" are not explicitly stated for clinical performance as they might be for a novel device. Instead, the study aimed to show "substantial equivalence" to a predicate device.

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

The provided text does not specify sample sizes for mechanical testing or biocompatibility studies. The studies were likely bench-top (mechanical) and potentially in-vitro/in-vivo (biocompatibility) tests.

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified, but generally, such tests are conducted in a laboratory setting, typically in the country of the manufacturer or a contracted testing facility. It's retrospective in the sense that the data is generated for the submission, not from a clinical trial.

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

This type of 510(k) submission, focused on material and mechanical equivalence for a modified surgical mesh, does not involve expert-established ground truth in the way a diagnostic AI device would. The "ground truth" for the mechanical tests would be the objective measurements themselves against established engineering standards or direct comparison to the predicate device's measured properties. For biocompatibility, it refers to standardized testing results.

4. Adjudication Method for the Test Set

Not applicable. This is not a study involving human interpretation or clinical outcomes requiring adjudication. The tests described are objective, physical, and biological assessments.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic imaging devices where human readers interpret medical images with and without AI assistance. This submission is for a surgical mesh, not a diagnostic device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Study was done

Not applicable. This submission is for a surgical mesh, which is a physical implant, not an algorithm or AI system.

7. The Type of Ground Truth Used

The "ground truth" for the tests mentioned (tensile, cycle, elongation, stiffness, dimensional characteristics, and biocompatibility) would be based on:

• Objective physical measurements: Using standardized testing methodologies and equipment to quantify mechanical properties and dimensions.
• Biocompatibility standards and assays: Results from validated in-vitro and potentially in-vivo tests comparing the new material's biological response to known standards or the predicate material.

8. The Sample Size for the Training Set

Not applicable. This submission is for a physical medical device (surgical mesh), not an AI algorithm, so there is no concept of a "training set."

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

Not applicable. No training set was used.

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The Apoqee™ Vault Suspension System is intended for use in vaginal vault suspension to treat pelvic organ prolapse.

The Apogee™ Vault Suspension System consists of needles and connectors used to pass a polypropylene mesh for support of the vaginal vault.

The provided text is a 510(k) Summary submission for the AMS Apogee™ Vault Suspension System. It primarily focuses on demonstrating substantial equivalence to predicate devices for regulatory approval, rather than detailing a specific study to prove the device meets pre-defined acceptance criteria with performance metrics.

Therefore, many of the requested sections (Table of acceptance criteria and reported device performance, sample size, data provenance, number of experts, adjudication method, MRMC study, effect size, standalone performance, type of ground truth for test set, training set details) cannot be fully populated from the provided text.

Here's an attempt to answer based only on the information available in the given text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or reported device performance metrics in numerical terms. Instead, it states: "The mesh used in the Apogee™ Vault Suspension System has been tested in accordance with FDA's Guidance for the Preparation of a Premarket Notification Application for a Surgical Mesh and has been shown to be equivalent to the listed predicate devices. In addition, the other components have demonstrated substantial equivalence to the predicate devices in terms of mechanical performance and biocompatibility."

This implies that the acceptance criteria revolved around demonstrating equivalence to predicate devices in the following areas:

2. Sample sized used for the test set and the data provenance

Not provided in the document. The text mentions "tested," but no details about the sample sizes or the nature (retrospective/prospective, country of origin) of the data, if any clinical data was involved. The testing appears to be primarily bench or material-based to demonstrate equivalence.

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

Not applicable. The provided text describes tests for material equivalence and mechanical performance, not diagnostic performance requiring expert interpretation or ground truth establishment in a clinical context.

4. Adjudication method for the test set

Not applicable. This concept applies to studies involving human interpretation or clinical endpoints, which are not detailed here.

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 is a medical device, not an AI or imaging diagnostic device where MRMC studies are typical.

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

Not applicable. This is a medical device, not an AI or imaging diagnostic algorithm.

7. The type of ground truth used

For the mesh, the ground truth was established by adherence to "FDA's Guidance for the Preparation of a Premarket Notification Application for a Surgical Mesh" and its comparison to the characteristics of the predicate devices. For other components, ground truth for mechanical performance and biocompatibility would be based on established engineering standards and biological safety assessments, again likely benchmarked against predicate devices. No specific "ground truth" in the clinical sense (e.g., pathology, outcomes data) is mentioned as being directly used in this summary.

8. The sample size for the training set

Not applicable. This is a medical device, not a machine learning model where a training set would be relevant.

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

Not applicable (as above).

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