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The ECHELON Synergy System is an imaging device and is intended to provide the physician with physiological and clinical information, obtained non-invasively and without the use of ionizing radiation. The MR system produces transverse, coronal, sagittal, oblique, and curved cross sectional images that display the internal structure of the head, body, or extremities. The images produced by the MR system reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spinlattice relaxation time (TI), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that can be useful in diagnosis determination.

Anatomical Region: Head, Body, Spine, Extremities
Nucleus excited: Proton

Diagnostic uses:

• · TI, T2, proton density weighted imaging
• · Diffusion weighted imaging
• · MR Angiography
• · Image processing
• · Spectroscopy
• · Whole Body

The ECHELON Synergy is a Magnetic Resonance Imaging System that utilizes a 1.5 Tesla superconducting magnet in a gantry design.

The provided document is a 510(k) summary for the FUJIFILM Healthcare Corporation's ECHELON Synergy MRI System. This document asserts substantial equivalence to a predicate device and primarily focuses on technical characteristics and adherence to standards rather than detailed performance studies with acceptance criteria for a diagnostic aid.

Here's an analysis of the acceptance criteria and study information derived from the document:

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

The document doesn't explicitly state quantitative acceptance criteria in terms of diagnostic performance metrics (e.g., sensitivity, specificity, AUC) because it's a 510(k) submission for an MRI system with an added coil, not a diagnostic algorithm. The acceptance criteria for the added Breast Coil 17 are implicitly tied to the performance and safety standards of the predicate device (ECHELON Synergy V10.0 K233687).

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

• Sample size for test set: Not explicitly stated as a number of cases or patients. The document mentions "Clinical image examples."
• Data provenance: Not explicitly stated (e.g., country of origin, retrospective or prospective). It only states that "Clinical images were collected and analyzed."

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

• Number of experts: One radiologist.
• Qualifications of experts: A "radiologist" validated the clinical images. No further details on experience level are provided.

4. Adjudication method for the test set:

• Adjudication method: None mentioned beyond a single radiologist's validation of image quality for clinical use.

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:

• MRMC study: No, an MRMC comparative effectiveness study was not explicitly mentioned or implied. This submission is for an MRI system with an added coil, not an AI-powered diagnostic algorithm.

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

• Standalone performance: Not applicable. This device is an MRI system, not a standalone AI algorithm. The performance evaluation focused on the technical aspects and image quality of the MRI machine and its new coil.

7. The type of ground truth used:

• Type of ground truth: Expert opinion (a single radiologist's validation of "acceptable image quality for clinical use"). This is tied to the demonstrative aspect of clinical image examples, rather than a definitive diagnostic truth for a disease state.

8. The sample size for the training set:

• Sample size for training set: Not applicable. This document is about a hardware modification (an added coil) to an existing MRI system. It does not involve machine learning models that require training sets in the conventional sense.

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

• How ground truth for training set was established: Not applicable, as there is no mention of a training set or machine learning model.

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The OASIS MRI System is an imaging device, and is intended to provide the physician with physiological and clinical information, obtained non-invasively and without the use of ionizing radiation. The MR system produces transverse, coronal, sagittal, oblique, and curved crosssectional images that display the internal structure of the head, body, or extremities. The images produced by the MR 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 diagnosis determination.

Anatomical Region: Head, Body, Spine, Extremities
Nucleus excited: Proton
Diagnostic uses: T1, T2, proton density weighted imaging
Diffusion weighted imaging
MR Angiography
Image processing
Spectroscopy
Whole Body

The OASIS MRI System is a Magnetic Resonance Imaging System that utilizes a 1.2 Tesla superconducting magnet in a gantry design. Magnetic Resonance imaging (MRI) is based on the fact that certain atomic nuclei have electromagnetic properties that cause them to act as small spinning bar magnets. The most ubiquitous of these nuclei is hydrogen, which makes it the primary nuclei currently used in magnetic resonance imaging. When placed in a static magnetic field, these nuclei assume a net orientation or alignment with the magnetic field, referred to as a net magnetization vector. The introduction of a short burst of radiofrequency (RF) excitation of a wavelength specific to the magnetic field strength and to the atomic nuclei under consideration can cause a re-orientation of the net magnetization vector. When the RF excitation is removed, the protons relax and return to their original vector. The rate of relaxation is exponential and varies with the character of the proton and its adjacent molecular environment. This re-orientation process is characterized by two exponential relaxation times, called T1 and T2. A RF emission or echo that can be measured accompanies these relaxation events.

The emissions are used to develop a representation of the relaxation events in a three dimensional matrix. Spatial localization is encoded into the RF excitation, applying appropriate magnetic field gradients in the x, y, and z directions, and changing the direction and strength of these gradients. Images depicting the spatial distribution of the NMR characteristics can be reconstructed by using image processing techniques similar to those used in computed tomography.

The provided document, a 510(k) Summary for the OASIS MRI System (K240571), describes the device and its equivalence to a predicate device (OASIS MRI System K211406). The acceptance criteria and performance study details are primarily focused on a new feature, DLR Rise.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria for DLR Rise. Instead, the acceptance is based on expert subjective evaluation of image quality metrics and clinical acceptability.

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The ECHELON Synergy System is an imaging device and is intended to provide the physician with physiological and clinical information, obtained non-invasively and without the use of ionizing radiation. The MR system produces transverse, coronal, sagittal, oblique, and curved cross-sectional images that display the internal structure of the head, body, or extremities. The images produced by the MR 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 diagnosis determination.

The ECHELON Synergy is a Magnetic Resonance Imaging System that utilizes a 1.5 Tesla superconducting magnet in a gantry design. The design was based on the ECHELON OVAL V6.0A MRI system. The ECHELON Synergy has been designed to enhance clinical utility as compared to the ECHELON OVAL V6.0A by taking advantage of open architecture.

The provided document, K223426, is a 510(k) premarket notification for the FUJIFILM Healthcare Corporation's ECHELON Synergy MRI system. This submission primarily focuses on demonstrating substantial equivalence to a predicate device (ECHELON OVAL V6.0A MRI system, K172110) rather than presenting a detailed performance study with explicit acceptance criteria for an AI/ML powered device as typically required for novel AI products.

However, the document mentions several new features powered by Machine Learning (ML), specifically Deep Learning Reconstruction (DLR), AutoClip, AutoPose Spine, AutoPose Shoulder, and AutoPose Knee. For DLR, some form of evaluation was performed. For AutoClip and AutoPose functions, performance comparisons were made against manual operations.

Based on the provided text, a comprehensive table of acceptance criteria and reported device performance, as one would expect for a dedicated AI/ML device approval, is not explicitly stated with numerical thresholds. The evaluations are largely qualitative or comparative to existing methods.

Below is an attempt to extract the closest information to your request, specifically focusing on the DLR, AutoClip, and AutoPose functions, as they are the only "AI/ML powered" components mentioned with specific evaluations.

1. Table of Acceptance Criteria and Reported Device Performance

As explicit numerical acceptance criteria are not provided for the AI/ML components, the table below consolidates the stated evaluative goals and findings from the "Summary of Clinical Testing" section.

• SNR: Equivalent or better in 81 out of 81 cases.
• Sharpness: Equivalent or better in 80 out of 81 cases.
• Lesion Conspicuity: Equivalent or better in 45 out of 45 cases (with pathology).
• Overall Image Quality: Equivalent or better in all cases.
  Motion Artifact Handling: Rated as better or equivalent image quality in all 3 image pairs with motion artifacts, indicating DLR did not significantly change their appearance.
  Shorter Scan Time Efficacy: DLR images with shorter scan times were rated "acceptable for routine examinations" in all 18 cases.
  Resolution Improvement: High-resolution DLR images were rated "better or equivalent" image quality in all cases compared to low-resolution conventional images. |
  | AutoClip | Performance Equivalence: Performance should be "substantially equivalent" to manual clipping. | Confirmed that the performance of AutoClip was "substantially equivalent to that of manual clipping." |
  | AutoPose (Spine, Shoulder, Knee) | Efficiency Improvement/Equivalence: Should reduce time and number of steps in slice positioning compared to manual, or at least show the "same time and number of steps." | Spine, Shoulder, and Knee:
• Many cases were able to reduce the time and number of steps in slice positioning compared to manual.
• Remaining cases showed the same time and number of steps as manual slice positioning. |

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

• Deep Learning Reconstruction (DLR):

  • Number of cases: 110 cases for DLR image quality evaluation (including 81 cases for SNR/sharpness/overall IQ, 45 cases with pathology for lesion conspicuity, 3 cases for motion artifacts, and 18 cases for shorter scan time evaluation). The exact breakdown per sub-analysis is specified.
  • Data Provenance: ECHELON OVAL, ECHELON Smart, and ECHELON Synergy MRI systems (all FUJIFILM Healthcare Corporation 1.5T MRI systems). Data acquired at "FUJIFILM Healthcare Corporation and clinical site."
  • Subject Type: Healthy volunteer and patient.
  • Anatomical Coverage: Head, Spine, Cardiac, Breast, Abdomen, Pelvis, Shoulder, Wrist, Knee, Ankle.

• AutoClip:

  • Number of cases: 40 cases.
  • Data Provenance: ECHELON Synergy MRI system (FUJIFILM Healthcare Corporation 1.5T MRI system). Data acquired at "FUJIFILM Healthcare Corporation."
  • Subject Type: Japanese healthy volunteers.
  • Anatomical Coverage: Brain (using 3D TOF, 3D Soft TOF scan sequences).

• AutoPose (Spine, Shoulder, Knee):

  • Number of cases: Spine (146 cases), Shoulder (48 cases), Knee (38 cases).
  • Data Provenance: ECHELON Synergy MRI system (FUJIFILM Healthcare Corporation 1.5T MRI system). Data acquired at "FUJIFILM Healthcare Corporation."
  • Subject Type: Japanese healthy volunteers.
  • Anatomical Coverage: Spine, Shoulder, Knee.

Note: The document does not explicitly state if the data was retrospective or prospective. Given the nature of performance testing within a company and potentially a clinical site, it could be a mix or internal prospective collection, but it's not specified. The country of origin for the "clinical site" data is also not explicitly stated beyond "Japanese healthy volunteers" for AutoClip/AutoPose, implying at least part of the data is from Japan for those features.

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

• Deep Learning Reconstruction (DLR):

  • Number of Experts: Three (3) US certified radiologists.
  • Qualifications: "US certified radiologists." No specific years of experience or subspecialty are provided, beyond their certification.

• AutoClip & AutoPose (Spine, Shoulder, Knee):

  • Number of Experts: Not specified as "experts" establishing ground truth, but rather "certified radiological technologists" performed the performance comparison/evaluation. The ground truth for performance was implicitly "manual operation" by these technologists. Their qualifications are listed as "certified radiological technologists."

4. Adjudication Method for the Test Set

• Deep Learning Reconstruction (DLR): The document states "Readers compared pairs of DLR images and conventional images (without DLR) for each case to evaluate image quality of DLR images." It does not specify an explicit adjudication method (e.g., 2+1, 3+1). It merely presents the results as derived from the collective evaluation of the three radiologists. It's unclear if consensus was required, or if individual ratings were aggregated.

• AutoClip & AutoPose: The evaluation was done by "certified radiological technologists" comparing against manual operation. No formal adjudication process is described.

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

• Deep Learning Reconstruction (DLR): A study involving multiple readers (3 US certified radiologists) and multiple cases (110 cases in total for DLR evaluation) was performed, which aligns with the spirit of an MRMC study. However, it's not explicitly labeled as such, and the methodology primarily focuses on qualitative comparison of image quality between DLR and conventional images rather than a comparative effectiveness study of human reader diagnostic performance with vs. without AI assistance for a specific diagnostic task.

  • Effect Size of Human Reader Improvement: This type of effect size (e.g., AUC uplift) is not reported. The study focused on assessing image quality attributes and acceptability for routine examinations from the DLR images themselves, as perceived by radiologists, not on how DLR assistance changes a radiologist's diagnostic accuracy or efficiency on a specific clinical task. The evaluation was primarily about the AI's impact on image characteristics, not human diagnostic performance.

• AutoClip & AutoPose: These evaluations were focused on the efficiency and equivalence of the automated process compared to manual operation, as assessed by technologists. They were not MRMC studies designed to measure impact on human readers' diagnostic effectiveness.

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

• The document implies a standalone assessment of the DLR output quality (SNR, sharpness, etc.) against conventional images, as rated by radiologists. The AutoClip and AutoPose functions are also inherently standalone algorithms that automate tasks, with their performance evaluated against manual methods. However, no formal "standalone performance study" with typical metrics like sensitivity, specificity, or AUC for a diagnostic task is presented for these AI/ML components in isolation. The evaluation focuses on product-level performance and usability.

7. The Type of Ground Truth Used

• Deep Learning Reconstruction (DLR): The ground truth for evaluation was expert consensus/opinion (or individual expert assessment) of the image quality attributes (SNR, sharpness, lesion conspicuity, overall image quality) when comparing DLR images to conventional images. The underlying "ground truth" for the cases themselves (e.g., presence of pathology) would presumably come from standard clinical diagnostic reports or other confirmed findings, but the DLR study's focus was on image quality as assessed by experts.

• AutoClip & AutoPose: The ground truth for these functions was the manual operation by certified radiological technologists. The evaluation aimed to determine if the automated function delivered equivalent or better performance (in terms of results and/or efficiency) compared to the human-performed task.

8. The Sample Size for the Training Set

• The document does not provide any details on the sample size used for the training set for DLR, AutoClip, or AutoPose. This information is typically proprietary and not included in 510(k) summaries unless specifically requested by the FDA or deemed critical for demonstrating substantial equivalence for a novel AI/ML device.

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

• Similar to the training set sample size, the document does not provide any details on how the ground truth for the training set was established for DLR, AutoClip, or AutoPose.

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The SCENARIA View system is indicated to acquire axial volumes of the whole body including the head. Images can be acquired in axial, helical, or dynamic modes. The SCENARIA View system can also be used for interventional needle guidance.

Volume datasets acquired by a SCENARIA View system can be post-processed in the SCENARIA View system to provide additional information. Post-processing capabilities of the SCENARIA View software include, multi-planar reconstruction (MPR), and volume rendering.

Volume datasets acquired by a SCENARIA View system can be transferred to external devices via a DICOM standard interface.

The Low Dose CT Lung Cancer Screening Option for the SCENARIA View system is indicated for using low dose CT for lung cancer screening. The screening must be conducted with the established program criteria and protocols that have been approved and published by a governmental body, a professional medical society, and/or Hitachi.

The SCENARIA View is a multi-slice computed tomography system that uses x-ray data to produce cross-sectional images of the body at various angles.

The SCENARIA View system uses 128-slice CT technology, where the X-ray tube and detector assemblies are mounted on a frame that rotates continuously around the patient using slip ring technology. The solid-state detector assembly design collects up to 64 slices of data simultaneously. The X-ray sub-system features a high frequency generator, X-ray tube, and collimation system that produces a fan beam X-ray output. The system can operate in a helical (spiral) scan mode where the patient table moves during scanning. As the X-ray tube/detector assembly rotates around the patient, data is collected at multiple angles.

The collected data is then reconstructed into cross-sectional images by a high-speed reconstruction sub-system. The images are displayed on a Computer Workstation, stored, printed, and archived as required. The workstation is based on current PC technology using the Windows™ operating system.

The SCENARIA View system consists of a Gantry, Operator's Workstation, Patient Table, High-Frequency X-ray Generator, and accessories.

The provided document is a 510(k) premarket notification for the FUJIFILM SCENARIA View Computed Tomography x-ray system. This submission primarily focuses on demonstrating substantial equivalence to a predicate device (SCENARIA View K200498) rather than presenting a performance study for a novel AI device with specific acceptance criteria.

The document states: "A clinical evaluation comparison was conducted with the SCENARIA View system and the predicate device (K200498) and found to be substantially equivalent as documented in Section 10 - Performance." However, Section 10 - Performance is not included in the provided document. Without this section, detailed acceptance criteria and reported performance metrics from a specific study are not available.

The only specific performance testing mentioned with some detail is related to a new feature: "FUJIFILM has conducted an evaluation to assess the effectiveness of the images reconstructed by using MCR and a summary of the results is contained in an explanatory document in the Specification section." Again, this "explanatory document in the Specification section" is not provided. Therefore, a complete answer regarding acceptance criteria and performance based on a study is not possible from the given text.

Based on the available information, here's what can be inferred and what is missing:

No Specific Acceptance Criteria or Performance Study for a Novel AI Device is Fully Described in the Provided Text.

The document is a 510(k) submission for a CT system, emphasizing substantial equivalence to a previous version of the same system (SCENARIA View K200498). The primary "study" mentioned is a clinical evaluation comparison to the predicate device and an evaluation of a new feature called Motion Compensate Reconstruction (MCR). While the document asserts these evaluations were conducted and support substantial equivalence, the details of the acceptance criteria and the results of these studies are not present.

The document indicates that comprehensive performance data for the CT system (Dose Profile, Noise, Mean CT number and Uniformity, Spatial Resolution, Tomographic Section Thickness and Sensitivity Profile, Tomographic Plane Location, and CT dose index) were evaluated and found to be unchanged or comparable to the predicate device. However, specific "acceptance criteria" and "reported device performance" in a tabular format are not provided for these metrics, nor are the studies detailing these.

Regarding the MCR feature: The document states that "FUJIFILM has conducted an evaluation to assess the effectiveness of the images reconstructed by using MCR and a summary of the results is contained in an explanatory document in the Specification section." This suggests a study was performed, but its details, acceptance criteria, and specific performance outcomes are not shared in the provided pages.

Based on what is explicitly stated or can be strongly inferred about the evaluation of the MCR feature (as this is the only new "feature" with an explicit "evaluation" mentioned), here's an attempt to answer the questions, highlighting the significant gaps in information:

1. Table of Acceptance Criteria and Reported Device Performance:

(Note: Without "Section 10 - Performance" and the "explanatory document in the Specification section," the actual acceptance criteria and detailed performance metrics are unavailable.)

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

• Sample Size (Test Set): Not specified in the provided document for the MCR evaluation or the clinical evaluation comparison.
• Data Provenance: Not specified for any evaluation or data used. It's unclear if the data was retrospective or prospective, or the country of origin.

3. Number of Experts and Qualifications for Ground Truth:

• Not specified. The document does not mention the use of experts to establish a ground truth for any evaluation, including the MCR feature.

4. Adjudication Method:

• Not specified. No information is given about how findings or image quality assessments were adjudicated.

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

• Not explicitly mentioned. The document primarily focuses on technical comparisons and the effectiveness of a new reconstruction algorithm (MCR) in image quality. It does not describe a study comparing human reader performance with and without AI assistance.

6. Standalone (Algorithm Only) Performance:

• The MCR feature is an "image reconstruction feature that reduces motion artifacts." This inherently implies an algorithm-only function. However, a formal "standalone performance" study with specific metrics (e.g., accuracy, sensitivity, specificity for identifying or correcting motion) is not described. The evaluation mentioned is about assessing the "effectiveness of the images reconstructed by using MCR," which could refer to qualitative or quantitative image quality assessment.

7. Type of Ground Truth Used:

• Not specified. For the MCR evaluation, the ground truth would ideally involve images with known motion artifacts and/or comparison to a higher-fidelity scan if motion was absent. However, this is not detailed in the document. For the overall system, typical CT performance metrics are evaluated against industry standards and physical phantoms.

8. Sample Size for the Training Set:

• Not applicable as this is a CT system with a new reconstruction algorithm (MCR), not a deep learning AI model requiring a distinct "training set" in the common sense for AI diagnostics. MCR is likely based on image processing and reconstruction physics, not machine learning that learns from a vast training dataset in the same way a diagnostic AI would.

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

• Not applicable for the same reasons as #8.

In summary, the provided document is a regulatory submission demonstrating substantial equivalence for a CT scanner. It mentions evaluations for new features (like MCR) and overall system performance compared to a predicate device. However, it does not contain the detailed reports, acceptance criteria, or quantitative results of these studies that would typically be expected for a comprehensive answer regarding acceptance criteria and device performance. The key missing pieces are "Section 10 - Performance" and the "explanatory document in the Specification section" that supposedly contain these details.

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This ARIETTA 50 is intended for use by trained personnel (doctor, sonographer, etc.) while in a healthcare facility for the diagnostic ultrasound evaluation of Fetal, Abdominal, Intra-operative (Spec.), Pediatric, Small Organ (Spec.), A Small Organ (Spec.), Adult Cephalic, Trans-rectal, Trans-vaginal, Trans-esoph. (non-Card.), Musculo-skel. (Convent.), Musculo-skel. (Superfic.), Other (Wound), Cardiac Adult, Cardiac Pediatric, Transesophageal (card.), Peripheral vessel, Other (Gynecological), clinical applications.

The Modes of Operation are B mode, M mode, PW mode (Pulsed Wave Doppler), CW mode (Continuous Wave Doppler), Color Doppler, Power Doppler (Color Flow Angiography), TDI (Tissue Doppler Imaging).

The ARIETTA 50 is a multi-functional ultrasound diagnostic scanner in which Doppler, Color Flow Mapping, etc. are provided and all circuits related to image quality are fully digitalized. This device can be utilized with linear, convex, radial and phased array scan type probes for usage with a variety of clinical applications.

The ARIETTA 50 can be used for individual or combined display in the image display model listed below.

• . B mode is a display mode in which the tomographic image is formed with plural ultrasound beams by the methods mentioned above. During the process of creating the tomographic image, adaptive filters (HI REZ) that modify the characteristics of each echo filter are used to produce a clear image.
• M mode is a display mode of ultrasound beams received sequentially and repeatedly on . the screen from the same direction. It indicates these reflected echoes in one direction from the interior of the patient's body's on time-series scale.
• There are two types of D (Doppler) mode: PW Doppler mode and CW Doppler mode. . PW Doppler mode displays bloodstream information consecutively at a sample point that is detected by pulsed Doppler sonography. CW Doppler mode displays bloodstream information continuously in the single-direction ultrasound beam that is detected by the CW Doppler method.
• Color Doppler mode receives ultrasound from the same direction and detects any . changes that occur over time to identify three types of bloodstream information: its direction, its speed, and its inconsistency. The mode then colors that information and displays it as an overlay on B mode or M mode. Color Flow Mode, Power Doppler Mode, High-Resolution Power Doppler (eFlow) Mode can be used with this instrument according to need.

The 4 methods of electronic scanning are as follows.

• . Linear Scanning Method:
  By this method, the ultrasound beam from the ultrasound probe is emitted in a straight line (linearly) and draws a tomographic image of the test subject.

• Convex Scanning Method:
  By this method, the ultrasound beam from the ultrasound probe is emitted radially and draws a tomographic image of the test subject.

• . Sector Scanning Method:
  By this method, the ultrasound beam from the ultrasound probe is emitted in a fan shape (sector) and draws a tomographic image of the test subject.

• Trapezoidal Scanning Method: ●
  By this method, the ultrasound beam from the ultrasound probe is emitted radially without regard to the form of the probe head and draws a tomographic image of the patient.

This document describes the Fujifilm ARIETTA 50 ultrasound system and its substantial equivalence to a predicate device. Below is a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not contain a table of specific acceptance criteria (e.g., specific quantitative metrics for performance) or a direct comparison of the reported device performance against such criteria. Instead, the document focuses on demonstrating substantial equivalence to a predicate device (ARIETTA 50, K190248) through a comparison of physical, performance, and technological characteristics.

The "Performance Comparison" section states: "No new hazards were identified with the ARIETTA 50. The subject device and its transducers have been evaluated for acoustic output, biocompatibility, cleaning & disinfection effectiveness, electromagnetic compatibility, as well as electrical and mechanical safety, and have been found to conform to applicable medical device safety standards."

The implicit acceptance criteria are the safety and effectiveness standards met by the predicate device and the applicable medical device safety standards mentioned. The reported device performance is that the ARIETTA 50 "conforms to applicable medical device safety standards" and its "performance characteristics... are comparable to the predicate device."

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

The document explicitly states: "Performance Testing - Clinical: None required." This indicates that no clinical test set of patient data (retrospective or prospective) was used for evaluating the device's performance in a clinical setting against specific acceptance criteria for diagnostic accuracy or efficacy. The evaluation appears to be based on an engineering and regulatory comparison to a predicate device.

Therefore, information on sample size for a test set and data provenance (country of origin, retrospective/prospective) is not applicable as no such clinical study was conducted.

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

Since no clinical test set was used for performance testing (as clinical testing was not required), there is no information about experts establishing ground truth for a test set.

4. Adjudication Method for the Test Set

As no clinical test set was used, there is no adjudication method to report.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Reader Improvement with AI vs. Without AI Assistance

No MRMC comparative effectiveness study was mentioned or implied. The device is an ultrasound diagnostic scanner, and the evaluation focused on physical and technical equivalence to a predicate, not on human-in-the-loop performance or AI assistance.

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

The document does not describe any standalone algorithm performance study. The ARIETTA 50 is an ultrasound system with various imaging modes, not an AI-driven algorithm designed to perform diagnostic tasks without human interaction. Its evaluation focuses on the overall system's safety and performance characteristics compared to a predicate ultrasound system.

7. The Type of Ground Truth Used

Given that clinical testing was not required and the submission relies on substantial equivalence to a predicate device, there is no mention of ground truth established through expert consensus, pathology, or outcomes data for the ARIETTA 50 itself. The basis for safety and effectiveness is compliance with standards and comparability to the predicate.

8. The Sample Size for the Training Set

No training set is mentioned as neither an AI/ML component requiring a training set nor a clinical study with a training phase was conducted.

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

Since no training set was used, this information is not applicable.

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