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The Signa CVMR system is a whole body scanner designed for shorter scan times. The Signa CVMR system is indicated for use as a diagnostic imaging device to produce transverse, sagittal, coronal and oblique images of the internal structures of the head or body. The images produced by the Signa CVMR system reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.

The Signa CVMR System is a modification to the Signa Horizon MR Systems which utilize a superconducting magnet to acquire 2D single-slice and multi-slice, and 3D volume images. In addition to the wide variety of pulse sequences provided to the Signa Horizon operator, such as inversion recovery, spin echo, gradient echo, gradient recalled, and steady state, and free precession acquisitions, the Signa CVMR operator has the ability for shorter scan times due to expanded gradient capabilities. Imaging options such as cardiac gating, peripheral gating, flow compensation and fat/water suppression are provided to suppress artifacts due to physiological motion and improve image quality.

The provided text describes a 510(k) premarket notification for the GE Signa CVMR Magnetic Resonance System. However, it does not contain a detailed study proving the device meets specific acceptance criteria in the manner typically seen for autonomous AI/ML devices. Instead, the submission focuses on demonstrating substantial equivalence to a predicate device and compliance with general safety and performance standards.

Here's an analysis based on the provided text, addressing the requested points where information is available:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or a direct performance table. The "performance" assessment is framed in terms of compliance with established medical device standards and comparison to a predicate device.

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

Not applicable. This submission doesn't describe a clinical study of "test set" data for evaluating an algorithm's performance. The evaluation is focused on engineering and safety standards, and comparative equivalence to an existing device.

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

Not applicable. See point 2.

4. Adjudication Method for the Test Set

Not applicable. See point 2.

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 document describes a traditional medical imaging device (MR system) and not an AI/ML diagnostic algorithm. Therefore, an MRMC study related to AI assistance is not relevant to this submission.

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

Not applicable. This is not an AI/ML algorithm.

7. The Type of Ground Truth Used

Not applicable in the context of AI/ML evaluation. The "ground truth" for this device's safety and effectiveness relies on:

• Engineering and electrical safety standards (NEMA, IEC).
• Demonstrated performance characteristics inherent to MR technology (e.g., ability to acquire T1/T2 weighted images, proton density).
• Clinical acceptance of the predicate device (Signa Horizon System) for its diagnostic capabilities when interpreted by trained physicians.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML algorithm, so there is no "training set."

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

Not applicable. See point 8.

Summary of the Study (as described in the document):

The "study" described in this 510(k) submission is primarily a technical and regulatory evaluation to demonstrate substantial equivalence to a previously cleared predicate device, the Signa Horizon System.

• Objective: To show that the Signa CVMR System is as safe and effective as the predicate device and does not raise new questions of safety and effectiveness.
• Methodology:
  • Comparison with Predicate: The Signa CVMR System was compared to the Signa Horizon Systems, with the primary difference identified as a modified Body/Gradient coil allowing for expanded gradient capabilities and shorter scan times. The submission asserts that no new indications for use or potential hazards are introduced.
  • Compliance with Standards: The device was evaluated against:
    • Appropriate NEMA performance standards.
    • IEC 601-1 International medical equipment safety standard.
    • IEC 601-2-33 Particular requirements for the safety of magnetic resonance equipment for medical diagnosis.
• Conclusion: GE concluded that the Signa CVMR System is substantially equivalent to the Signa Horizon MR Systems. The FDA, based on this submission, concurred with the substantial equivalence finding.

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Diffusion Weighted EPI imaging produces magnetic resonance (MR) images whose contrast is dependent on the local diffusion coefficient of water. Diffusion Weighted EPI can be useful in visualizing the apparent loss of diffusion (mobility) by water molecules in brain tissues affected by acute stroke. Diffusion Weighted EPI is more accurate than conventional MRI pulse sequence (ie Fast FLAIR and Fast Spin Echo) in identifying the occurrence of acute stroke.

The Diffusion Weighted EPI Imaging Option provides an additional imaging option to the Echo Planar Imaging pulse sequence. The DW-EPI option is a single shot EPI pulse designed to create images that differentiates tissues with restricted diffusion from tissues with normal diffusion.

Here's a summary of the acceptance criteria and study information for the GE Medical Systems Diffusion Weighted EPI Imaging Option based on the provided text:

Important Note: The provided document is a 510(k) summary for a medical device submitted in 1997. At that time, the regulatory requirements for showing performance and clinical benefit were significantly different (and generally less stringent) than today's standards for AI/ML devices. Therefore, much of the information typically expected for a modern AI device's acceptance criteria and study data (e.g., detailed performance metrics like sensitivity/specificity, specific ground truth methods for clinical endpoints, robust training/test set details, MRMC studies) is not present in this document. The focus of this submission is primarily on demonstrating substantial equivalence to a predicate device and basic safety.

Acceptance Criteria and Device Performance

Study Details

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

   • Test Set Sample Size: Not explicitly stated. The "Summary of Studies" section only mentions "Evaluation testing confirmed accuracy statements in the User Manual." It does not provide details on patient cohorts, case numbers, or specific performance metrics from a test set.
   • Data Provenance: Not specified.

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

   • Not specified. The document does not detail how "accuracy statements" were confirmed, nor does it refer to specific clinical ground truth established by experts for performance evaluation beyond general statements about its utility in identifying acute stroke. The primary "ground truth" for regulatory approval appears to be equivalence to the predicate device.

3. Adjudication method for the test set:

   • Not specified.

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 MRMC comparative effectiveness study is reported. The device is an "imaging option" (a pulse sequence), not an AI-based interpretation tool designed to assist human readers, in the modern sense. The claim is that the imaging sequence itself is "more accurate than conventional MRI pulse sequence" in identifying acute stroke, not that it improves human reader performance through AI assistance.

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

   • This is not an "algorithm-only" or AI device in the contemporary sense. It's an MR imaging pulse sequence. Its "performance" is inherent in the image contrast and information it provides. The study primarily focuses on safety and functional performance of the imaging sequence itself, not on an algorithm's diagnostic output.

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

   • Not explicitly stated for clinical accuracy. The document mentions "accuracy statements in the User Manual" were confirmed, but the basis for these statements (e.g., against pathology, clinical follow-up, or expert consensus) is not detailed. For the regulatory submission, the primary "ground truth" was the predicate device and its established safety and performance.

7. The sample size for the training set:

   • Not applicable as this is an MR imaging pulse sequence, not an AI/ML algorithm that requires a training set in the current understanding. Its development likely involved engineering, physics, and empirical testing for image quality and contrast, rather than data-driven machine learning.

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

   • Not applicable for the same reason as #7.

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The Indications for Use for the Signa Profile 9 Inch Diameter Coil and Kinematic Positioner Options expands the capability of the Signa Profile System. The Kinematic Positioner accommodates and improves imaging of the knee and surrounding structures. The 9 inch Coil is intended for imaging of the cervical spine, shoulder, knee and surrounding structures.

Profile 9 Inch Coil consists of a linear solenoid coil. The lt is a split two part design that has a base and a removable top to facilitate patient positioning. It is designed for use with a vertical magnetic field MR imaging system.

The Kinematic Positioner provides support for the legs for MR scanning. It has two usages. One is for a scan when the scanned leg is fixed, and the other is while the scanned leg is moving down.

The provided text describes a 510(k) premarket notification for the GE Signa Profile 9 Inch Coil and Kinematic Positioner Options. It focuses on demonstrating substantial equivalence to a predicate device rather than providing detailed performance studies with acceptance criteria in the manner one might expect for a novel AI device.

Here's an analysis based on the information provided:

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

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 does not specify a "test set" in the context of clinical data or image samples for performance evaluation. The evaluation appears to be based on engineering and laboratory testing against NEMA and IEC standards, and direct comparison of specifications with 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. The evaluation described is for physical medical devices (MRI coil and positioner) against technical standards, not for an AI algorithm requiring expert ground truth for interpretation.

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

Not applicable. There is no mention of a human expert adjudication process for image interpretation or diagnosis.

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 submission concerns hardware components (an MRI coil and a positioner), not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study comparing human reader performance with and without AI assistance is irrelevant to this device.

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

Not applicable. This is not an algorithm.

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

Not applicable. The "ground truth" here would be measurements and tests against established engineering and safety standards (NEMA, IEC) and the specifications of the predicate device.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device.

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

Not applicable. This is not an AI/machine learning device.

Summary of the Study:

The "study" described in this 510(k) summary is primarily an engineering and regulatory compliance exercise. GE Medical Systems evaluated the Signa Profile 9 Inch Coil and Kinematic Positioner Options against:

• NEMA performance standards: To ensure the coil performs adequately from a technical imaging perspective. Specific NEMA standards (e.g., for RF coils) would have been used.
• International safety standards IEC 601-1 and IEC 601-2-33: To ensure electrical and mechanical safety of the medical devices.
• Manufacturer's stated specifications: To confirm manufacturing quality and functionality.
• Comparison to a predicate device: The Signa Profile Extremity Coil (for the 9-inch coil) and the existing Signa Profile System (for both options). This comparison focused on identifying similarities and differences and demonstrating that any differences do not raise new safety or effectiveness concerns.

The conclusion is that these options are substantially equivalent to currently marketed devices and do not introduce new hazards, allowing them to expand the capabilities of the Signa Profile System for imaging various anatomical regions like the cervical spine, shoulder, and knee.

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The Signa Contour 2 System is indicated for use as a diagnostic imaging device to produce transverse, sagittal, coronal and oblique images of the internal structures of the head or body. The images produced reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.

The Signa Contour 2 System utilizes a superconducting magnet to acquire 2D single-slice and multi-slice, and 3D volume images. A wide variety of pulse sequences is provided to the operator, including inversion recovery, spin echo, gradient recalled, and steady state, free precession acquisitions. Imaging options such as cardiac gating, peripheral gating, flow compensation and fathwater suppression are provided to suppress artifacts due to physiological motion and improve image quality. The system can be used as a stationary or mobile system.

The provided text is for a 510(k) premarket notification for a medical device, the "Signa Contour 2 Magnetic Resonance System." This type of submission is for demonstrating substantial equivalence to a predicate device, not for proving clinical efficacy or diagnostic performance in the same way a new drug or a novel AI-driven diagnostic device would.

Therefore, the document does not contain the detailed information required to answer your questions regarding acceptance criteria, device performance, ground truth, expert involvement, or sample sizes for clinical studies. The summary focuses on comparing the new device's technical specifications and safety standards to a previously cleared product.

Here's why each of your requested points cannot be addressed with the provided text:

1. A table of acceptance criteria and the reported device performance: The document states the device "was evaluated to the appropriate NEMA performance standards as well as the IEC 601-1 International medical equipment safety standard." However, it does not list specific imaging performance metrics (e.g., resolution, signal-to-noise ratio, diagnostic accuracy for specific conditions) as acceptance criteria or report actual performance values against those criteria.
2. Sample size used for the test set and the data provenance: There is no mention of a "test set" in the context of diagnostic performance or clinical outcomes. The evaluation was primarily against technical and safety standards.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: As no clinical "test set" for diagnostic performance is described, there's no mention of experts establishing ground truth for such a set. The device is for image acquisition, and interpretation is done by a "trained physician," but this is a general statement about usage, not a study design detail.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable, as no clinical test set for diagnostic performance is described.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This device is an MRI scanner, not an AI-driven image analysis tool. There's no mention of AI or assistance to human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is an MRI scanner, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The device's evaluation was against technical and safety standards, not clinical diagnostic accuracy with a "ground truth."
8. The sample size for the training set: Not applicable. There is no mention of a training set as this is not an AI algorithm being validated.
9. How the ground truth for the training set was established: Not applicable.

In summary, the provided document from a 1997 510(k) submission for an MRI scanner focuses on demonstrating technical and safety equivalence to a predicate device. It does not contain the type of clinical study design and performance data typically associated with the evaluation of diagnostic efficacy or AI-driven medical devices.

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The Signa Horizon Cx System is indicated for use as a diagnostic imaging device to produce transverse, sagital, coronal and oblique images of the internal structures of the head or body. The images produced by the Signa Horizon Cx System reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.

The Signa Horizon Cx System utilizes a superconducting maanet to acquire 2D single-slice and multi-slice, and 3D volume images. A wide variety of pulse sequences is provided to the operator, including inversion recovery, spin echo, gradient echo, gradient recalled, and steady state, free precession acquisitions. Imaging options such as cardiac gating, peripheral gating, flow compensation and fat/water suppression are provided to suppress artifacts due to physiological motion and improve image quality. The system can be used as a stationary or mobile svstem.

The provided document does not contain information about acceptance criteria, device performance, or a study proving that the device meets specific acceptance criteria in the manner described by the prompt's request for detailed study design elements (sample size, ground truth, expert consensus, etc.).

This document is a 510(k) Summary of Safety and Effectiveness for the Signa Horizon Cx Magnetic Resonance System. Its purpose is to demonstrate substantial equivalence to a predicate device, not to detail performance against a set of acceptance criteria based on clinical outcomes or diagnostic accuracy.

Here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated in terms of diagnostic accuracy or clinical utility. The document focuses on equivalence to NEMA performance standards and IEC safety standards.
• Reported Device Performance: No specific performance metrics like sensitivity, specificity, or inter-reader variability are provided. The "performance" mentioned refers to compliance with established engineering and safety standards.

2. Sample size used for the test set and the data provenance: Not applicable. This document does not describe a clinical study with a test set of patient data.

3. 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 for a test set is described.

4. Adjudication method for the test set: Not applicable.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done: No, an MRMC study is not mentioned. The comparison is between the new device and a predicate device in terms of design and compliance with standards.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is an MR imaging system, not an AI algorithm.

7. The type of ground truth used: Not applicable.

8. The sample size for the training set: Not applicable.

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

Summary of Information from the Document:

The document states:

• The Signa Horizon Cx System was "evaluated to the appropriate NEMA performance standards as well as the IEC 601-1 International medical equipment safety standard."
• It is "comparable to the Signa Horizon MR Systems."
• "The Signa Horizon Cx does not include any new indications for use, nor does use of this device result in any new potential hazards."
• The comparison with the predicate device focuses on physical and technical characteristics: the new magnets are 2 tons lighter, have a lower cryogen boil-off rate, and are 68 cm shorter. The software and electronics are "substantially equivalent" to the currently marketed Signa Horizon System.

Conclusion based on the provided text:

This document demonstrates substantial equivalence to a predicate device based on engineering and safety standards, not through clinical performance studies against specific acceptance criteria for diagnostic accuracy or clinical outcomes. Therefore, the detailed information requested regarding study design and performance metrics is not available in this document.

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SmartPreo IA option enables breath hold studies and trigger acquisition based on timing related to the arrival of a user injected exogenous contrast agent bolus.

The SmartPrep IA Option is an optional imaging technique that results in a scan acquisition being triggered off of the arrival of a user injected bolus of contrast agent at a prescribed volume of interest.

This document, a 510(k) summary for the GE Medical Systems SmartPrep IA, primarily focuses on demonstrating substantial equivalence to a predicate device and outlining safety standards. It does not contain the detailed information necessary to fully answer your request regarding acceptance criteria and a study proving those criteria are met for a device that involves performance metrics like sensitivity, specificity, or human reader improvement.

Here's a breakdown of why and what information is available:

Missing Information and Why:

The provided text describes a modification to an existing MR system (SmartPrep IA Option) that optimizes the timing of scan acquisition based on contrast agent arrival. This is a functional and safety-centric submission for a medical imaging technique, not a diagnostic AI device requiring performance metrics like sensitivity, specificity, or human reader studies.

Therefore, the following cannot be extracted from the provided text:

• A table of acceptance criteria and the reported device performance: This document confirms functionality and safety, not diagnostic performance metrics.
• Sample sized used for the test set and the data provenance: Not applicable to a functional/safety evaluation of this nature.
• Number of experts used to establish the ground truth... and their qualifications: Not applicable.
• Adjudication method: Not applicable.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not applicable. This is not an AI diagnostic assistant.
• Standalone (algorithm-only) performance: Not applicable. While it's an "option" (software), its performance is in optimizing image acquisition, not interpreting images.
• Type of ground truth used: Not applicable.
• Sample size for the training set: Not applicable.
• How the ground truth for the training set was established: Not applicable.

Information Available from the Document:

1. Device Description: The SmartPrep IA Option is an optional imaging technique that triggers scan acquisition based on the arrival of a user-injected bolus of contrast agent at a prescribed volume of interest.
2. Indications for Use: Enables breath-hold studies and triggers acquisition based on timing related to the arrival of a user-injected exogenous contrast agent bolus.
3. Summary of Studies: The SmartPrep IA Option was evaluated to the IEC 601-2-33 International medical equipment safety standard for Magnetic Resonance Systems.
4. Conclusions: Evaluation testing confirmed the functionality of the software. The option does not result in any new potential hazards.

In summary, this document is a regulatory submission for a software feature improving MR scan acquisition, not a diagnostic AI device requiring performance validation against clinical endpoints or human reader studies.

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The Signa SP System optional accessories are indicated for use as follows:

• The Scan Plane Pointer facilitates localization of the scanning planes. .
• . The side entry patient support access feature and the Patient Imaging Chair allows multiple patient positions enabling imaging exams of dynamic joints (such as knees and shoulders) and loaded spine studies.
• . The use of MR Imaging during interventional procedures using common devices such as fine needles and suction.

The Signa SP System employs an open magnet configuration which helps to reduce patient anxiety. increases patient positioning options and allows easy access to the patient. The Scan Plane Pointer accessory is useful in acquiring MR images relative to the physical orientation of the patient. The images may then be displayed to the operator and on a screen at table side.

The provided text describes a 510(k) summary for the GE Signa SP Magnetic Resonance System with optional accessories. It focuses on demonstrating substantial equivalence to a predicate device and safety and effectiveness, rather than providing a detailed study that proves the device meets specific acceptance criteria in the way a clinical study for a new diagnostic or therapeutic device would.

Therefore, much of the requested information cannot be directly extracted from the provided text because it describes regulatory submission for accessory features, not a performance study for a novel algorithm or diagnostic tool.

However, I can extract what is present and indicate what is not.

Here's an attempt to answer based on the provided text:

Acceptance Criteria and Study for GE Signa SP Magnetic Resonance System - Optional Accessories

The document describes a regulatory submission for optional accessories to an existing Magnetic Resonance (MR) system, focusing on its safety and effectiveness and substantial equivalence to a predicate device. It does not present a clinical study with detailed performance metrics and acceptance criteria as would be typical for a new diagnostic algorithm. Instead, it refers to compliance with industry standards and internal evaluation.

1. Table of Acceptance Criteria and Reported Device Performance

Regarding the study that "proves" the device meets acceptance criteria:

The document states: "The Signa SP optional accessories was evaluated to the appropriate NEMA performance standards as well as the IEC 601-1 International medical equipment safety standard. Evaluation testing confirmed accuracy statements in the User Manual." This indicates internal testing and compliance checks rather than a formal clinical study designed to meet specific performance endpoints for a diagnostic.

Here are answers to the specific questions, where applicable based on the provided text:

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

• Sample size: Not specified. The "evaluation testing" mentioned likely refers to engineering and performance verification tests of the accessory hardware, not a data set of patient cases.
• Data provenance: Not applicable in the context of diagnostic data. The evaluation would be on the performance of the hardware itself.

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. This is not a study requiring expert-established ground truth for diagnostic accuracy.

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

• Not applicable. This is not a study requiring adjudication of diagnostic outcomes.

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 is not an AI-assisted diagnostic device; it describes hardware accessories for an MR system.

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

• Not applicable. This is not an algorithm, but hardware accessories.

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

• Not applicable for a diagnostic performance ground truth. For hardware, "ground truth" would be established by engineering specifications, calibration standards, and physical measurements.

8. The sample size for the training set

• Not applicable. This is not a machine learning model.

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

• Not applicable. This is not a machine learning model.

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