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FlightPlan for Embolization is a post processing software package that helps the analysis of 3D X-ray angiography images. Its output is intended to be used by physicians as an adjunct means to help visualize vasculature during the planning phase of embolization procedures. FlightPlan for Embolization is not intended to be used during therapy delivery.

The output includes segmented vasculature, and selective display of proximal vessels from a reference point determined by the user. User-defined data from the 3D X-ray angiography images may be exported for use during the guidance phase of the procedure. The injection points should be confirmed independently of FlightPlan for Embolization prior to therapy delivery.

FlightPlan for Embolization is a post-processing, software-only application using 3D X-ray angiography images (CBCT) as input. It helps clinicians visualize vasculature to aid in the planning of endovascular embolization procedures throughout the body.

A new option, called AI Segmentation, was developed from the modifications to the predicate device, GE HealthCare's FlightPlan for Embolization [K193261]. It includes two new algorithms. This Al Segmentation option is what triggered this 510(k) submission.

The software process 3D X-ray angiography images (CBCT) acquired from GE HealthCare's interventional X-ray system [K181403], operates on GEHC's Advantage Workstation (AW) [K110834] platform and AW Server (AWS) [K081985] platform, and is an extension to the GE HealthCare's Volume Viewer application [K041521].

FlightPlan for Embolization is intended to be used during the planning phase of embolization procedures.

The primary features/functions of the proposed software are:

• Semi-automatic segmentation of vasculature from a starting point determined by the user, when AI Segmentation option is not activated;
• Automatic segmentation of vasculature powered by a deep-learning algorithm, when Al Segmentation option is activated;
• Automatic definition of the root point powered by a deep-learning algorithm, when AI Segmentation option is activated;
• Selective display (Live Tracking) of proximal vessels from a point determined by the user's cursor;
• Ability to segment part of the selected vasculature;
• Ability to mark points of interest (POI) to store cursor position(s);
• Save results and optionally export them to other applications such as GEHC's Vision Applications ● [K092639] for 3D road-mapping.

Here's a breakdown of the acceptance criteria and the study details for the GE Medical Systems SCS's FlightPlan for Embolization device, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

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

• Test Set Sample Size: 207 contrast-injected CBCT scans, each from a unique patient.
• Data Provenance: The scans were acquired during the planning of embolization procedures from GE HealthCare's interventional X-ray system. The text indicates that these were from "clinical sites" and were "representative of the intended population" but does not specify countries of origin. The study appears to be retrospective, using existing scans.

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

• Vessel Extraction: 3 board-certified radiologists.
• Root Definition: 1 GEHC advanced application specialist.

3. Adjudication Method for the Test Set:

• Vessel Extraction: Consensus of 3 board-certified radiologists. (Implies a qualitative agreement, not a specific quantitative method like 2+1).
• Root Definition: The acceptable area was manually defined by the annotator (the GEHC advanced application specialist).

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

• No, an MRMC comparative effectiveness study was not explicitly described in terms of human readers improving with AI vs. without AI assistance. The non-clinical testing focused on the algorithms' performance against ground truth and the clinical assessment used a Likert scale to evaluate the proposed device with the AI option, rather than a direct comparison of human reader performance with and without AI.

5. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• Yes, a standalone performance evaluation was conducted for both the vessel extraction and root definition algorithms. The reported success rates of 93.7% and 95.2% are measures of the algorithms' performance against established ground truth without a human in the loop for the primary performance metrics.

6. The Type of Ground Truth Used:

• Vessel Extraction: Expert consensus (3 board-certified radiologists).
• Root Definition: Manual definition by an expert (GEHC advanced application specialist), defining an "acceptable area."

7. The Sample Size for the Training Set:

• The document states that "contrast injected CBCT scans acquired from GE HealthCare's interventional X-ray system [K181403] were used for designing and qualifying the algorithms." However, it does not specify the sample size for the training set. It only mentions that a test set of 207 scans was "reserved, segregated, and used to evaluate both algorithms."

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

• The document does not explicitly state how the ground truth for the training set was established. It only details the ground truth establishment for the test set.

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FlightPlan for Liver is a post processing software package that helps the analysis of 3D X-ray angiography images of the liver. Its output is intended as an adjunct means to help visualize vasculature and identify arteries leading to the vicinity of hypervascular lesions in the liver. This adjunct information may be used by physicians to aid them in their evaluation of hepatic arterial anatomy during the planning phase of embolization procedures.

FlightPlan for Liver with the Parenchyma Analysis option is a post-processing, software-only application using 3D X-ray angiography images (CBCT) as input. It helps physicians visualize and analyze vasculature to aid in the planning of endovascular embolization procedures in the liver. It was developed from modifications to the predicate device, GE's FlightPlan for Liver [K121200], including the addition of 2 new algorithms supporting the Parenchyma Analysis option. The Parenchyma Analysis option is what triggered this 510k. The subject device also includes a feature, Live Tracking, that was cleared in the reference device, GE's FlightPlan for Embolization. The software operates on GE's Advantage Workstation [K110834] platform and AW Server [K081985] platform and is an extension to the GE's Volume Viewer application [K041521].

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

1. Table of Acceptance Criteria and Reported Device Performance

The document states that "The test results of both of the algorithms met their predefined acceptance criteria" for the deep learning-based Liver Segmentation algorithm and the non-deep learning Virtual Parenchyma Visualization (VPV) algorithm. However, the specific quantitative acceptance criteria and their corresponding reported performance values are not explicitly detailed in the provided text.

The clinical assessment also "demonstrated that the proposed device FlightPlan for Liver with the Parenchyma Analysis option met its predefined acceptance criteria," but again, the specifics are not provided.

Therefore, a table cannot be fully constructed without this missing information.

Missing Information:

• Specific quantitative acceptance criteria for Liver Segmentation algorithm (e.g., Dice score, IoU, boundary distance).
• Specific quantitative reported performance for Liver Segmentation algorithm.
• Specific quantitative acceptance criteria for VPV algorithm (e.g., accuracy of distal liver region estimation).
• Specific quantitative reported performance for VPV algorithm.
• Specific quantitative or qualitative acceptance criteria for the clinical assessment using the 5-point Likert scale.

2. Sample Sizes and Data Provenance

For the Deep Learning Liver Segmentation Algorithm:

• Test Set Sample Size: Not explicitly stated, but derived from a "database of contrast injected CBCT liver acquisitions."
• Data Provenance: Clinical sites in the USA and France. The data was prospective (implied by "clinical sites") and for the purpose of training and testing.

For the Non-Deep Learning Virtual Parenchyma Visualization (VPV) Algorithm:

• Test Set Sample Size: "a test set of proximal CBCT acquisitions." The exact number is not provided.
• Data Provenance: From the USA and France.

For the Clinical Testing:

• Test Set Sample Size: "A sample of 3D X-ray angiography image pairs." The exact number is not provided.
• Data Provenance: From France and the USA.

3. Number of Experts and Qualifications for Ground Truth

For the Deep Learning Liver Segmentation Algorithm:

• Number of Experts: Not specified.
• Qualifications: Not specified. The ground truth method itself (how segmentation was established for training and testing) is not fully detailed beyond using existing "contrast injected CBCT liver acquisitions."

For the Non-Deep Learning Virtual Parenchyma Visualization (VPV) Algorithm:

• Number of Experts: Not specified.
• Qualifications: Not specified.
• Ground Truth Basis: "selective contrast injected CBCT exams from same patients." It's implied that these were expert-interpreted or based on a recognized clinical standard, but the specific expert involvement is not detailed.

For the Clinical Testing:

• Number of Experts: Not specified.
• Qualifications: "interventional radiologists." No experience level (e.g., years of experience) is provided.

4. Adjudication Method for the Test Set

The document does not explicitly mention an adjudication method (like 2+1 or 3+1 consensus) for any of the test sets.

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

• The document describes a "Clinical Testing" section where "interventional radiologists using a 5-point Likert scale" assessed image pairs. This suggests a reader study.
• However, it does not explicitly state that it was an MRMC comparative effectiveness study comparing human readers with AI assistance vs. without AI assistance. The study assessed whether the device "met its predefined acceptance criteria and helps physicians visualize and analyze... and aids in the planning..." which seems to be an evaluation of the device's utility rather than a direct comparison of reader performance with and without the AI.
• Therefore, no effect size of human readers improving with AI vs. without AI assistance is reported.

6. Standalone (Algorithm Only) Performance

• Yes, standalone performance was done for both new algorithms.
  • The "deep learning-based Liver Segmentation algorithm" was evaluated, although specific performance metrics are not given.
  • The "non-deep learning Virtual Parenchyma Visualization algorithm's performance was evaluated [...] compared to selective contrast injected CBCT exams from same patients used as the ground truth."
• This indicates that the algorithms themselves were tested for their inherent performance.

7. Type of Ground Truth Used

For the Deep Learning Liver Segmentation Algorithm:

• Based on "contrast injected CBCT liver acquisitions." The precise method for establishing the "correct" segmentation (e.g., manual expert tracing, pathology, outcome data) is not detailed. It's implicitly clinical data.

For the Virtual Parenchyma Visualization (VPV) Algorithm:

• "selective contrast injected CBCT exams from same patients used as the ground truth." This implies a gold standard of directly observed, selective angiography, which is a clinical reference.

For the Clinical Testing:

• The "ground truth" here is the perception and evaluation of interventional radiologists using a 5-point Likert scale regarding the device's utility ("helps physicians visualize," "aids in the planning"). This is a form of expert consensus/subjective assessment of utility.

8. Sample Size for the Training Set

For the Deep Learning Liver Segmentation Algorithm:

• "a database of contrast injected CBCT liver acquisitions from clinical sites in the USA and France was used for the training and testing." The exact sample size for training is not specified, only that a database was used.

For the Virtual Parenchyma Visualization (VPV) Algorithm:

• The VPV algorithm is described as "non-deep learning," so it would not have a traditional "training set" in the same way a deep learning model would. It likely relies on predefined anatomical/physiological models or rules.

9. How Ground Truth for the Training Set Was Established

For the Deep Learning Liver Segmentation Algorithm:

• The document states "a database of contrast injected CBCT liver acquisitions [...] was used for the training." However, it does not explicitly detail how the ground truth labels (i.e., the correct liver segmentations) were established for these training images. This is a critical piece of information for a deep learning model. It's usually through expert manual annotation for segmentation tasks.

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FlightPlan for Embolization is a post processing software package that helps the analysis of 3D X-ray angiography images. Its output is intended to be used by physicians as an adjunct means to help visualize vasculature during the planning phase of embolization procedures. FlightPlan for Embolization is not intended to be used during therapy delivery.

The output includes segmented vasculature, and selective display of proximal vessel and distal vessels from a reference point determined by the user. User-defined data from the 3D X-ray angiography images may be exported for use during the guidance phase of the procedure. The injection points should be confirmed independently of FlightPlan for Embolization prior to therapy delivery.

FlightPlan for Embolization is a post processing software application which operates on the Advantage Workstation (AW) [K110834] platform and AW Server [K081985] platform. It is an extension to the Volume Viewer application [K041521] modified from FlightPlan for Liver (K121200) and is designed for processing 3D X-ray angiography images to help visualize vasculature

The primary features of the software are: semi-automatic segmentation of vascular tree from a starting point determined by the user; selective display (Live Tracking) of proximal vessel and distal vessels from a point determined by the user's cursor; ability to segment part of the vasculature; ability to mark points of interest (POI) to store cursor position; save results and export to other applications such as Vision Applications [K092639] for 3D road-mapping.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for FlightPlan for Embolization:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list quantitative acceptance criteria in a dedicated section for "acceptance criteria." However, it describes validation activities that implicitly define the performance considered acceptable. Based on the "Summary of Non-Clinical Tests" and "Summary of Clinical Tests," the following can be inferred:

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

• Non-Clinical Test Set:

  • Sample Size: A "database of XACT exams." The specific number of cases is not provided.
  • Data Provenance: Not explicitly stated, but clinical scenarios are considered "representative" and include "consideration of acquisition parameters, image quality and anatomy." It can be inferred that these are existing clinical data, likely retrospective.

• Clinical Test Set:

  • Sample Size: "A sample of 3D X-ray angiography images representative of clinical practice." The specific number of cases is not provided.
  • Data Provenance: Not explicitly stated, but described as "representative of clinical practice" and "most common anatomic regions where embolization procedures are performed." It can be inferred that these are retrospective clinical cases.

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

• Clinical Test Set:
  • Number of Experts: Four
  • Qualifications: "board certified interventional radiologists." No information on years of experience is provided.

4. Adjudication Method for the Test Set

• Clinical Test Set: The document states that the assessment was done "using a 5-point Likert scale." This implies an individual scoring system by each radiologist, but it does not specify an adjudication method (e.g., 2+1, 3+1 consensus). It sounds like individual assessments were performed and then aggregated or analyzed.

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

• No, an MRMC comparative effectiveness study was not explicitly stated to have been done in the traditional sense of comparing human readers with AI vs. without AI assistance.
  • The clinical study described is an assessment of the device's helpfulness by radiologists, rather than a comparative study measuring improvement in diagnostic accuracy or efficiency for humans using the AI vs. not using it. The statement "demonstrated that the proposed device (FlightPlan for Embolization) helps physicians" is an outcome of an assessment, not a quantitative effect size from an MRMC study comparing assisted vs. unassisted performance.

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

• Yes, a form of standalone performance was assessed in the "Summary of Non-Clinical Tests." The "Engineering...validated FlightPlan for Embolization algorithms' capability to automatically segment and selectively display vascular structures..." using a database of XACT exams. This implies an evaluation of the algorithm's output against some reference (likely manual segmentations or ground truth established by experts) without direct human interaction at the time of assessment.

7. The Type of Ground Truth Used

• Non-Clinical Test Set: The ground truth for the non-clinical validation of segmentation and display capabilities is implicitly based on expert-defined correct segmentations or "satisfactory quality" as determined by engineering validation. The document does not explicitly state "expert consensus" or "pathology" for this.
• Clinical Test Set: The ground truth for the clinical assessment relies on the judgment of "four board certified interventional radiologists" using a 5-point Likert scale to determine if the device "helps physicians." This is a form of expert assessment/opinion as ground truth regarding the device's utility/helpfulness.

8. The Sample Size for the Training Set

• Not provided. The document does not disclose information about the training data used for the FlightPlan for Embolization algorithms.

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

• Not provided. Since the training set details are not mentioned, how its ground truth was established is also not available in this document.

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The FLIGHT 60 Ventilator is intended to provide continuous or intermittent mechanical ventilation support for the care of individuals who require mechanical ventilation. Specifically, the FLIGHT 60 is applicable for adult and pediatic (i.e., infant, child and adolescent) patients, greater than or equal to 5kg (11 1bs).

The FLIGHT 60 Ventilator is a restricted medical device intended for use by qualified, trained personnel under the direction of a physician; it is sutable for use in hospital, sub-acute, emergency room, and home care environments, as well as for transport and emergency response applications.

The FLIGHT 60 Ventilator is an electrically powered, microprocessor controlled ventilator with the following types of ventilatory support: A/CMV Volume or Pressure Control, SIMV Volume or Pressure Control, Pressure Support & SPONT mode with Pressure Support. It can be pressure or time triggered; volume or pressure limited; time, pressure or flow cycled. Manual inflation is possible, and an emergency intake valve allows the patient to pull ambient air into the breathing circuit in the event of a complete loss of supply gas pressure. The FLIGHT 60 may be powered by external power (100 - 240 VACS or 12 - 15 VDC) or by its two internal Li Ion rechargeable batteries. The electrical system is comprised of three primary boards: the Main board (motherboard) which holds the majority of the electronics including the main CPU and the display CPU, the Power board, which holds the power subsystems, and internal communication functions, and the Communication board, which holds internal communication and external communication connectors. The main component of the pneumatic system is an electrically controlled compressor (pump). This compressor provides a compressed gas source so no external air compressor is needed. Additionally, the exhalation valve is activated by an electrically controlled proportional solenoid that provides a built in PEEP.

The provided text is a 510(k) summary for the FLIGHT 60 Ventilator, focusing on a modification to its compressor. Here's a breakdown of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The document describes the performance data in narrative form rather than a direct table of acceptance criteria vs. performance. However, it indicates that the device "met the predetermined acceptance criteria" for all tests.

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

The document does not specify a "sample size" in terms of number of patients or clinical cases for a test set. The testing described is primarily non-clinical performance testing of a medical device (ventilator). The "test set" consists of the physical device undergoing various engineering and performance evaluations.

• Sample Size: Not applicable in the context of clinical patient data. The "sample" is presumably one or more units of the revised FLIGHT 60 Ventilator.
• Data Provenance: The data provenance is from laboratory and engineering testing conducted by the manufacturer, Flight Medical Innovations Ltd., as part of the design and verification activities. The country origin is not explicitly stated for the testing itself, but the manufacturer is based in Israel (Petach Tikva). The submission is to the US FDA. This is retrospective in the sense that the testing has already been completed for the submission.

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

This section is not applicable as the described testing is non-clinical performance and engineering validation. "Ground truth" in this context refers to established engineering specifications, performance standards (e.g., IEC, ISO), and comparisons to predicate device measurements, not expert clinical diagnoses. Therefore, there were no clinical experts establishing "ground truth" for the test set.

4. Adjudication Method for the Test Set

The concept of an "adjudication method" (like 2+1 or 3+1) is typically relevant for clinical studies where expert consensus is needed to establish ground truth from ambiguous cases (e.g., in medical imaging interpretation). Since the described testing is non-clinical performance validation, an adjudication method was not used. The performance was directly measured against predetermined engineering specifications and international standards.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document describes non-clinical performance testing for a ventilator, not a study involving human readers interpreting cases.

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

This concept is typically applied to AI/ML devices. The FLIGHT 60 Ventilator is a hardware-based medical device with microprocessor control, not an AI algorithm. Therefore, the concept of "standalone (algorithm only)" performance is not applicable in this context. The performance described is the standalone performance of the mechanical ventilator itself, which inherently involves its internal software/firmware control without a "human-in-the-loop" in the sense of an assist/no-assist comparison.

7. The Type of Ground Truth Used

The "ground truth" used for this device validation is based on:

• Established engineering specifications: Predefined performance parameters for the ventilator.
• International standards: Compliance with standards like IEC 60601-1, ISO 80601-2-12, and IEC 60601-1-2.
• Predicate device performance: Comparative measurements against the predicate FLIGHT 60 (K130171) and Trilogy 100 (K083526) to demonstrate substantial equivalence, particularly for waveform characteristics.

8. The Sample Size for the Training Set

Not applicable. The FLIGHT 60 Ventilator is a hardware medical device with embedded software, not a machine learning model that requires a "training set."

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

Not applicable. As a hardware medical device, there is no "training set" or corresponding ground truth establishment process in the context of machine learning.

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The FLIGHT 60 Ventilator is intended to provide continuous or intermittent mechanical ventilation support for the care of individuals who require mechanical ventilation. Specifically, the FLIGHT 60 is applicable for adult and pediatric (i.e., infant, child and adolescent) patients, greater than or equal to 5kg (11 lbs).

The FLIGHT 60 Ventilator is a restricted medical device intended for use by qualified, trained personnel under the direction of a physician; it is suitable for use in hospital, sub-acute, emergency room, and home care environments, as well as for transport and emergency response applications.

The FLIGHT 60 Ventilator is an electrically powered, microprocessor controlled ventilator with the following types of ventilatory support: ACMV Volume, Pressure or PRVC, SIMV Volume, Pressure or PRVC, PSV/SPONT mode with Pressure Support and Volume Guarantee, Bi-Level (APRV). It can be pressure, flow or time triggered; volume or pressure limited; time, pressure or flow cycled. Manual inflation is possible, and an emergency intake valve allows the patient to pull ambient air into the breathing circuit in the event of a complete loss of supply gas pressure.

The FLIGHT 60 may be powered by external power (100 - 240 VACS or 12 - 15 VDC) or by its two internal Li Ion rechargeable batteries, which power the ventilator for up to 12 hours when fully charged.

The electrical system is comprised of three primary boards: the Main board (motherboard) which holds the majority of the electronics including the main CPU and the display CPU, the Power board, which holds the power subsystem and internal communication functions, and the Communication board, which holds internal communication and external communication connectors.

The main component of the pneumatic system is an electrically controlled compressor (pump). This compressor provides a compressed gas source so no external air compressor is needed. Additionally, the exhalation valve is activated by an electrically controlled proportional solenoid that provides built in PEEP.

A comprehensive alarm system is built-in to alert the user to violations of set safety limits. The alarm system alerts the care giver by activating the audible alarm, screen display and the LED indicator.

Here's an analysis of the acceptance criteria and study information for the FLIGHT 60 Ventilator, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document primarily focuses on establishing substantial equivalence to predicate devices and adherence to medical device standards. It does not present specific quantitative acceptance criteria alongside corresponding performance metrics in a direct table format for the FLIGHT 60 Ventilator itself. Instead, it makes a general statement about meeting "applicable device specification" and compliance with recognized standards.

However, we can infer the "acceptance criteria" through the mentioned standards and the general statement about meeting design verification criteria. The "reported device performance" is essentially the statement of compliance.

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

The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective) for the performance data. The "Performance Data" section merely states: "FLIGHT 60 Ventilator meets all applicable device specification... Verification of compliance with recognized standard has been made to support use of the device for its intended use and in its intended environment." This suggests testing was conducted, but the specifics of the test set are not detailed.

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

The document does not mention the use of experts to establish ground truth for a test set. This type of evaluation is common for diagnostic/AI devices, but for a ventilator, performance is typically assessed against engineering specifications and international standards, often through bench testing and simulated use, rather than requiring expert interpretation of results.

4. Adjudication Method for the Test Set

Since the document does not describe a study involving a "test set" in the context of expert review or clinical outcomes requiring adjudication, there is no mention of an adjudication method.

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

No, the document does not describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. This type of study is more relevant for diagnostic imaging devices where human readers interpret medical images, and the performance of AI-assisted reading is compared to unassisted reading. The FLIGHT 60 Ventilator is a treatment device, not a diagnostic one in that context.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The concept of "standalone performance" typically applies to AI algorithms that provide a diagnostic or predictive output without human intervention. The FLIGHT 60 Ventilator is a physical medical device. Its "performance" is inherently standalone in that it functions independently according to its design and specifications. There's no AI algorithm in the sense of a diagnostic one being evaluated for standalone performance here. The document states it is "microprocessor controlled" but doesn't imply an AI component requiring this type of assessment.

7. The Type of Ground Truth Used

For medical devices like ventilators, the "ground truth" for performance evaluation is typically established through:

• Engineering specifications and design requirements: The device's output (e.g., delivered volume, pressure, flow) is measured and compared against its programmed settings and acceptable tolerances.
• International standards conformance: Performance is assessed against the requirements of relevant ISO and IEC standards (as listed), which define acceptable ranges and behaviors for medical electrical equipment and specific device types.
• Simulated physiological models: Ventilator performance can be tested using lung simulators that mimic various patient conditions.

The document explicitly states that "Verification and validation activities were conducted to establish the performance characteristics of the FLIGHT 60 Ventilator" and that "All testing demonstrated that the FLIGHT 60 Ventilator met required design verification criteria and has acceptable performance when used in accordance with its labeling." This indicates that the ground truth was based on pre-defined engineering standards and specified performance parameters.

8. The Sample Size for the Training Set

The document does not mention a "training set." This term is specific to the development and evaluation of machine learning or artificial intelligence algorithms. The FLIGHT 60 Ventilator is a microprocessor-controlled device, but the context provided does not indicate it uses a machine learning model that would require a distinct training set for its core functionality.

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

As no "training set" for a machine learning algorithm is discussed, there is no information on how its ground truth might have been established.

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FlightPlan for Liver is a post processing software package that helps the analysis of 3D X-ray images of the liver arterial tree. Its output is intended as an adjunct means to help identify arteries leading to the vicinity of hypervascular lesions in the liver. This adjunct information may be used by physicians to aid them in their evaluation of hepatic arterial anatomy during embolization procedures.

FlightPlan for Liver is a post-processing software application for use with interventional fluoroscopy procedures, using 3D rotational angiography images as input. It operates on the AW VolumeShare 4 [K052995] and AW VolumeShare 5 [K110834] platform. It is an extension to the Volume Viewer application [K041521] utilizing the rich set of the 3D processing features of Volume Viewer. FlightPlan for Liver delivers post-processing features that will aid physicians in their analysis of 3D X-ray images of the liver arterial tree. Additionally FlightPlan for Liver includes an algorithm to highlight the potential vessel(s) in the vicinity of a target.

Here's an analysis of the provided text regarding the acceptance criteria and study for the FlightPlan for Liver device:

Acceptance Criteria and Device Performance

There is no explicit table of acceptance criteria or reported device performance metrics (e.g., sensitivity, specificity, AUC) in the provided document. The submission focuses on demonstrating substantial equivalence to a predicate device and confirming that the software functions as required and fulfills user needs.

The "Performance testing" mentioned is described as "computing time of algorithm on several data," implying it's a speed or efficiency metric rather than a diagnostic performance metric. The "Verification confirms that the Design Output meets the Design Input (Product Specifications) requirements" and "Validation confirms that the product fulfills the user needs and the intended use under simulated use conditions," but specific, quantifiable acceptance criteria are not detailed.

The "Summary of Clinical Tests" states that the study "demonstrate[d] the safety and effectiveness of FlightPlan for Liver" and compared its output "to a reference reading established by two senior interventional oncologists." However, the exact metrics used for comparison and the "acceptance criteria" for those metrics are not provided. The key takeaway is that the clinical data was not intended to support a claim of improved clinical outcomes.

Study Details

Here's what can be extracted about the study that proves the device meets the (unspecified quantitative) acceptance criteria:

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

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

• Test Set Size: 44 subjects, representing a total of 66 tumors.
• Data Provenance: Retrospective study. The country of origin is not explicitly stated, but given the submitter's address (Buc, FRANCE) and the GE Healthcare global nature, it could be either European or multinational, but this is speculative.

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

• Number of Experts: Two.
• Qualifications: "Senior interventional oncologists." Specific experience (e.g., years) is not provided.

4. Adjudication method for the test set

• The ground truth was established by a "reference reading established by two senior interventional oncologists." While it states the two established the reference, it doesn't specify if this was by consensus, independent reads with adjudication, or another method. The phrasing "a reference reading established by two" suggests a single, agreed-upon ground truth, likely consensus or 2-reader agreement if initial reads differed.

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 multi-reader, multi-case (MRMC) comparative effectiveness study comparing human readers with AI assistance vs. without AI assistance was not done. The study specifically states that the clinical data "was not designed nor intended to support a claim of an improvement in clinical outcomes of such procedures, and no such claim is being made." The study focused on comparing the device's output to an expert reference, not on human performance improvement.

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

• Yes, the clinical study appears to evaluate the algorithm's standalone performance compared to a "reference reading." The "output of FlightPlan for Liver was compared to a reference reading," indicating the algorithm's direct output was assessed. No mention is made of human interaction or interpretation of the algorithm's output as part of this comparison.

7. The type of ground truth used

• Type of Ground Truth: Expert consensus/reference reading. Specifically, "a reference reading established by two senior interventional oncologists."

8. The sample size for the training set

• The document does not mention the sample size for the training set. It only describes the clinical study as a "retrospective study" used for verification and validation, implying it was a test set. There's no information about the data used to train the "algorithm to highlight the potential vessel(s)."

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

• This information is not provided since the document does not detail the training set or its ground truth establishment.

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The FLIGHT 60 Ventilator is intended to provide continuous or intermittent mechanical ventilation support for the care of individuals who require mechanical ventilation. Specifically, the FLIGHT 60 is applicable for adult and pediatric (i.e., infant, child and adolescent) patients, greater than or equal to 5kg (11 lbs).

The FLIGHT 60 Ventilator is a restricted medical device intended for use by qualified, trained personnel under the direction of a physician; it is suitable for use in hospital, sub-acute, emergency room, and home care environments, as well as for transport and emergency response applications.

The FLIGHT 60 Ventilator is an electrically powered, microprocessor controlled ventilator with the following types of ventilatory support: A/CMV Volume or Pressure Control, SIMV Volume or Pressure Control, Pressure Support & SPONT mode with Pressure Support. It can be pressure or time triggered; volume or pressure limited; time, pressure or flow cycled. Manual inflation is possible, and an emergency intake valve allows the patient to pull ambient air into the breathing circuit in the event of a complete loss of supply gas pressure.

The FLIGHT 60 may be powered by external power (100 - 240 VACS or 12 - 15 VDC) or by its two internal Li Ion rechargeable batteries, which power the ventilator for up to 12 hours when fully charged.

The electrical system is comprised of three primary boards: the Main board (motherboard) which holds the majority of the electronics including the main CPU and the display CPU, the Power board, which holds the power subsystems, and internal communication functions, and the Communication board, which holds internal communication and external communication connectors.

The main component of the pneumatic system is an electrically controlled compressor (pump). This compressor provides a compressed gas source so no external air compressor is needed. Additionally, the exhalation valve is activated by an electrically controlled proportional solenoid that provides a built in PEEP.

A comprehensive alarm system is built-in to alert the user to violations of set safety limits. The alarm system alerts the care giver by activating the audible alarm, screen display and the LED indicator.

Here's an analysis of the provided text regarding the FLIGHT 60 Ventilator, focusing on acceptance criteria and supporting studies.

Important Note: The provided document is a 510(k) summary for a medical device (a ventilator). Unlike AI/ML-driven devices, traditional medical devices like ventilators do not typically have "acceptance criteria" in the same way an AI algorithm has performance metrics (e.g., sensitivity, specificity, AUC). Instead, they meet performance specifications and recognized standards to ensure safety and effectiveness. The "study" here refers to the verification and validation (V&V) testing.

Therefore, many of the requested categories (sample size for test/training, number of experts, adjudication methods, MRMC studies, standalone performance, ground truth types) are not applicable in the context of a ventilator's regulatory submission. This information is primarily relevant for AI/ML devices that make diagnostic or prognostic predictions.

1. Table of Acceptance Criteria and Reported Device Performance

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

This information is not applicable as this is a physical medical device (ventilator), not a diagnostic algorithm. The "test set" for a ventilator would involve rigorous engineering and safety testing under various simulated and real-world conditions, rather than a dataset of patient information. The document refers to "performance testing" and "verification of compliance," which implies testing of the physical device's functionality and adherence to safety standards.

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

This information is not applicable. The "ground truth" for a ventilator's performance is objective physical measurements and safety standards (e.g., gas flow rates, pressure delivery, alarm functionality, battery life, power consumption). This does not involve expert consensus on medical images or diagnoses. Experts (e.g., engineers, clinicians) would be involved in designing the specifications and evaluating test results, but not in establishing a "ground truth" that is then compared against an algorithm's output.

4. Adjudication Method for the Test Set

This information is not applicable. Adjudication methods (like 2+1 or 3+1) are used to resolve discrepancies in expert interpretations, typically for establishing ground truth in diagnostic studies. For a ventilator, performance is objectively measured against specifications and standards, not subject to subjective adjudication in this way.

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

This information is not applicable. MRMC studies are designed to assess the impact of an AI system on human reader performance, usually in image interpretation. This ventilator is a life-support device, not a diagnostic imaging aid. The "comparison" mentioned in the document is between the new FLIGHT 60 and its predicate devices to demonstrate substantial equivalence, not an assessment of human reader performance with or without AI assistance.

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

This information is not applicable. The FLIGHT 60 is a ventilator, a standalone medical device that performs a mechanical function. It's not an algorithm that makes diagnostic predictions. Its performance is its own operation, and it's designed to be used with human oversight, but not as an "AI-only" component.

7. The Type of Ground Truth Used

The "ground truth" for a ventilator's performance is typically defined by:

• Engineering specifications: Precise measurements of gas delivery, pressure, oxygen concentration, flow rates, alarm thresholds, battery duration, power consumption, etc.
• Recognized national and international standards: Adherence to standards like ISO 80601-2-12 for critical care ventilators, or specific electrical safety standards.
• Biocompatibility testing: Ensuring materials are safe for patient contact.
• Electromagnetic compatibility (EMC) testing: Ensuring it doesn't interfere with or get interfered by other devices.
• Environmental testing: Performance under varying temperatures, humidity, and vibration.

It is not based on expert consensus, pathology, or outcomes data in the way an AI diagnostic device would be.

8. The Sample Size for the Training Set

This information is not applicable. Ventilators do not have "training sets" in the context of machine learning. Their functionality is programmed and engineered, not "learned" from data.

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

This information is not applicable. As there is no "training set" for a ventilator in the AI/ML sense, there's no ground truth to establish for it. The ventilator's operational parameters are based on scientific and medical principles, engineering design, and regulatory standards.

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The FLIGHT 60 Ventilator is intended to provide continuous or intermittent mechanical ventilation support for the care of individuals who require mechanical ventilation. Specifically, the FLIGHT 60 is applicable for adult and pediatric (i.e., infant, child and adolescent) patients, greater than or equal to 10kg (22 lbs). The Flight 60 Ventilator is a restricted medical device intended for use by qualified, trained personnel under the direction of a physician; it is suitable for use in hospital, sub-acute, emergency room, and home care environments, as well as for transport and emergency response applications.

The Flight 60 Ventilator is an electrically powered, microprocessor controlled ventilator with the following types of ventilatory support: A/CMV Volume or Pressure Control. SIMV Volume or Pressure Control. Pressure Support & SPONT mode with Pressure Support. It can be pressure or time triggered volume or pressure limited; time, pressure or flow cycled. Manual inflation is possible, and an emergency intake valve allows the patient to pull ambient air into the breathing circuit in the event of a complete loss of supply gas pressure. The Flight 60 may be powered by external power (100 - 240 VACS or 12 -15 VDC) or by its two internal Li Ion rechargeable batteries, which power the ventilator for up to 12 hours when fully charged. The electrical system is comprised of three primary boards the Main board (motherboard) which holds the majority of the electronics including the main CPU and the display CPU, the Power board, which holds the power subsystems, and internal communication functions, and the Communication board, which holds internal communication and external communication connectors. The main component of the pneumatic system is an electrically controlled compressor (pump). This compressor provides a compressed gas source so no external air compressor is needed. Additionally, the exhalation valve is activated by an electrically controlled proportional solenoid that provides a built in PEEP. A comprehensive alarm system is built in to alert the user to violations of set safety limits. The alarm system alerts the care giver by activating the audible alarm, screen display and the LED indicator.

This document is a 510(k) summary for the Flight 60 Ventilator, focusing on its substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a specific study proving the device meets those criteria. Therefore, much of the requested information regarding acceptance criteria, study design, and performance metrics for a specific algorithm or AI is not present.

However, based on the provided text, here's what can be extracted and inferred:

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

The document states: "The Flight 60 Ventilator meets all applicable device specification requirements for performance testing as identified in the FDA reviewer guidance for ventilators. Verification of compliance with recognized standards has been made to support safe use of the device for its intended use and in its intended environment." It also mentions a usability/human factors study.

While specific numerical acceptance criteria or performance metrics are not given, the overall acceptance criterion can be inferred as "meeting all applicable device specification requirements and recognized standards."

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

The document mentions a "usability/human factors study" and refers to "users" being requested to use the ventilator.

• Sample size: Not specified.
• Data provenance: Not specified, but the applicant is "Flight Medical Innovations Ltd. 13 Hamelacha Street North Industrial Park Lod 71520, Israel," so presumably, the study was conducted there or relevant to their market. The study seems prospective in nature ("First users were requested to use the ventilator...").

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)

This information is not provided because the "study" mentioned is a usability/human factors study, not a clinical study evaluating diagnostic accuracy or a similar measure that would require expert-established ground truth. The "ground truth" for a usability study would be user feedback and observed interactions.

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

Not applicable, as this was a usability study focused on user experience, not a clinical trial with adjudicated outcomes from experts.

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. The Flight 60 Ventilator is a hardware device, not an AI or imaging diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is irrelevant to this submission.

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

Not applicable, as this is a hardware medical device (ventilator).

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

For the usability/human factors study, the "ground truth" would be the subjective and objective feedback from the users regarding ease of use, and potentially observed performance during simulated tasks. For the overall device performance, the "ground truth" is compliance with recognized standards and device specifications, which would be verified through engineering and performance testing. There's no clinical "ground truth" in the sense of pathology or outcomes data presented here for efficacy.

8. The sample size for the training set

Not applicable. This is a hardware device, not an AI model.

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

Not applicable, as this is a hardware device, not an AI model requiring a training set with established ground truth.

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The FLIGHT 60 Ventilator is intended to provide continuous or intermittent mechanical ventilation support for the care of individuals who require mechanical ventilation. Specifically, the FLIGHT 60 is applicable for adult and pediatric (i.e., infant, child and adolescent) patients, greater than or equal to 10kg (22 lbs).

The FLIGHT 60 Ventilator is a restricted medical device intended for use by qualified, trained personnel under the direction of a physician; it is suitable for use in hospital, sub-acute, emergency room, and home care environments, as well as for transport and emergency response applications.

The FLIGHT 60 Ventilator is an electrically powered, microprocessor controlled ventilator with the following types of ventilatory support: A/CMV Volume or Pressure Control, SIMV Volume or Pressure Control, Pressure Support & SPONT mode with Pressure Support. It can be pressure or time triggered; volume or pressure limited; time, pressure or flow cycled. Manual inflation is possible, and an emergency intake valve allows the patient to pull ambient air into the breathing circuit in the event of a complete loss of supply gas pressure. The FLIGHT 60 may be powered by external power (100 - 240 VACS or 12 - 15 VDC) or by its two internal Li Ion rechargeable batteries, which power the ventilator for up to 12 hours when fully charged.

The electrical system is comprised of three primary boards: the Main board (motherboard) which holds the majority of the electronics including the main CPU and the display CPU, the Power board, which holds the power subsystems, and internal communication functions, and the Communication board, which holds internal communication and external communication connectors. The main component of the pneumatic system is an electrically controlled compressor (pump). This compressor provides a compressed gas source so no external air compressor is needed. Additionally, the exhalation valve is activated by an electrically controlled proportional solenoid that provides a built in PEEP.

A comprehensive alarm system is built-in to alert the user to violations of set safety limits. The alarm system alerts the care giver by activating the audible alarm, screen display and the LED indicator.

The provided text is a 510(k) summary for the FLIGHT 60 Ventilator. While it discusses the device's intended use, classification, predicate devices, and general performance statements, it does not contain specific acceptance criteria or the details of a study that proves the device meets those criteria.

The relevant section, "Performance Data," states: "The FLIGHT 60 Ventilator meets all applicable device specification requirements for performance testing as identified in the FDA reviewer guidance for ventilators. Verification of compliance with recognized standards has been made to support safe use of the device for its intended use and in its intended environment."

This statement confirms that testing was conducted and standards were met, but it does not provide the specific data requested in your prompt regarding acceptance criteria, sample sizes, ground truth establishment, or comparative effectiveness studies.

Therefore, I cannot populate the table or answer the specific questions because the information is not present in the provided text.

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The Flight Dental Systems A-Series Operative Units are intended to supply power und serve as a base for dental devices and accessories. The use intended is in the treatment of dental patients in the dental clinic/office environment. The units are for use only by trained dentists, dental hygienists, dental technicians and dental assistants.

The Flight A-Series Dental Operative Unit is a dental operating system. The device includes a patient chair, dentist's element, utility center and a floor box. The unit may also include a cuspidor, an assistant's element and a dental operating light. The doctor's element may be mounted on the patient chair or on a mobile cart. The unit is used to position the patient in a comfortable position and to provide the power to the dentist's instruments including dental handpieces.

This document describes the Flight Dental Systems A-Series Dental Operative Unit, cleared under K070196. This device is a dental operating system comprising a patient chair, dentist's element, utility center, and floor box, intended to supply power and serve as a base for dental devices and accessories in a dental clinic/office environment.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (Sirona C8+ Dental Operative unit - K983242) rather than defining explicit, quantitative acceptance criteria for de novo performance. The acceptance criteria are implicitly met by demonstrating conformance to relevant standards and direct equivalence to the predicate.

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

• Sample Size for Test Set: The submission states that "Bench testing has been performed on a sample that is in all respects the same as the device to be marketed." This indicates a single device sample (or a very small number representing the manufactured article) was used for physical bench testing.
• Data Provenance: The bench testing was performed against local GB standards in China. Additional independent laboratory testing was performed by Intertek Testing of Mississauga, Ontario, Canada. This is prospective testing of the device itself.

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

• This submission does not involve clinical data or expert evaluations for establishing ground truth in the context of image interpretation or diagnostic performance. Instead, ground truth is established by the compliance of the device with recognized international and national standards as assessed by engineering and testing professionals at the designated testing laboratories. Therefore, the "experts" are the qualified personnel at the testing facilities (e.g., Intertek Testing) who conducted the specified tests and verified compliance. Their specific qualifications are not detailed beyond their affiliation with the testing labs.

4. Adjudication Method for the Test Set:

• Not applicable. The testing described is objective bench testing against engineering standards, not subjective evaluation requiring adjudication among multiple human assessments.

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

• No, a MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic imaging devices or AI-assisted devices that impact human clinical decision-making. This device is a physical dental operative unit.

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

• Not applicable. This device is a physical medical device, not an algorithm or software-only device. Its performance is inherent in its physical and electrical characteristics conforming to safety and performance standards.

7. Type of Ground Truth Used:

• The "ground truth" used for this submission is conformance to established engineering and safety standards (e.g., ISO, UL, CSA, GB standards), combined with direct comparison of technological characteristics to a legally marketed predicate device.

8. Sample Size for the Training Set:

• Not applicable. This device does not involve machine learning or AI, and therefore does not have a "training set."

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

• Not applicable, as there is no training set.

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