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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 FUJIFILM Corporation.

The SCENARIA View system is intended for general populations.

The subject device SCENARIA View is a multi-slice CT system consists of a gantry, operator's workstation, patient table, high-frequency X-ray generator, and accessories. The system performance is similar to the predicate device.

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.

Compared to the predicate device referenced within this submission, the subject devices support the following modifications:

1. New features

• AutoPose is an AI-based function that recognizes a specific body part in an image of localization scan and then automatically sets the scan range and the image reconstruction range.
• RemoteRecon is a function of setting image reconstruction parameters that runs on the external personal computer (hereinafter referred to as "PC") connected to the CT system.

2. Modified features

• The maximum load capacity of patient table type has been increased from 250kg to 300 kg.
• Motion corrected reconstruction is an image reconstruction feature that reduces motion artifacts. The feature has been modified to include applicability for chest examinations, which is a non-gated scan.
• AutoPositioning is a feature that assist in positioning the patient by camera images. The feature has been modified to include additional 12 body parts (Head and Neck, Neck, C-spine, Heart, Chest-Abdomen, Chest-Upper Abdomen, Abdomen-Pelvis, Abdomen, Pelvis, T-spine, L-spine, T-L-spine), in addition to the 2 body parts (Head, Chest) of the predicate device, with scanogram ranges displayed according to the selected protocol.

The provided FDA 510(k) Clearance Letter for SCENARIA View Phase 5.0 primarily focuses on demonstrating substantial equivalence to a predicate device (SCENARIA View 4.2). The document outlines non-clinical and some clinical tests, but it does not present a formal "acceptance criteria" table with specific quantitative metrics for the device performance of the new AI features (AutoPose, Body Still Shot) in the same way one might find for a novel AI/CADe device.

The "acceptance criteria" for this submission appear to be centered around workflow improvement and sufficient image quality when compared to manual or predicate methods, rather than hard quantitative performance targets. The study designs are more akin to usability studies and qualitative image reviews.

Here's an attempt to extract and interpret the information based on your requested structure, acknowledging the limitations of the provided text in terms of explicit acceptance criteria and standalone performance metrics for the AI components.

Acceptance Criteria and Device Performance for SCENARIA View Phase 5.0 (AI Components)

The provided document describes the acceptance criteria and study results for the new features AutoPose and Body Still Shot introduced in the SCENARIA View Phase 5.0 system. The acceptance criteria are largely qualitative, focusing on workflow improvement and sufficient image quality.

1. Table of Acceptance Criteria and Reported Device Performance

Note on "Acceptance Criteria": The document does not explicitly list quantitative acceptance criteria in a table format for the AI features. The criteria listed above are inferred from the Methods and Results sections of the non-clinical and clinical tests described. The primary goal was to demonstrate workflow efficiency (AutoPose) and qualitative image improvement (Body Still Shot).

2. Sample Sizes and Data Provenance

• AutoPose (Clinical Test):

  • Total Cases: 50 (Head), 50 (Neck), 52 (Chest), 54 (Heart), 52 (Abdomen), 52 (Abdomen-Pelvis), 50 (Chest-Abdomen), 24 (T-L-Spine), 50 (C-Spine), 50 (T-Spine), 50 (L-Spine).
    • Note: The table layout in the original document makes it unclear if Chest-Upper Abdomen had cases listed, but it's empty. Assuming 50 for Chest-Abdomen and 0 for Chest-Upper Abdomen as it's not specified.
  • Total Sum (if all distinct): 50 + 50 + 52 + 54 + 52 + 52 + 50 + 50 + 50 + 50 + 24 = 504 cases.
  • Data Provenance: Clinical sites in the USA.
  • Retrospective/Prospective: Not explicitly stated, but the nature of evaluating steps in a procedure suggests it was likely a prospective workflow evaluation with certified technologists.

• Body Still Shot (Clinical Test):

  • Total Cases: Not specified.
  • Data Provenance: Not specified (only mentions "Japanese M.D." reviewers).
  • Retrospective/Prospective: Not specified.

• Training Set Sample Size:

  • Not disclosed in the provided document. The document primarily details the validation/test set.

3. Number of Experts and Qualifications for Ground Truth

• AutoPose (Clinical Test):

  • Number of Experts: Not explicitly stated how many "certified radiological technologists" performed the evaluations, only that they were certified.
  • Qualifications: "certified radiological technologists." No specific years of experience or other details are provided.
  • Role in Ground Truth: Their assessment of the number of steps and the "expected position" for manual adjustment served as the comparison for AutoPose's performance.

• Body Still Shot (Clinical Test):

  • Number of Experts: Not explicitly stated how many "Japanese M.D." (Medical Doctors) reviewed the images, only that they were "Japanese M.D."
  • Qualifications: "Japanese M.D." No specific specialty (e.g., radiologist), years of experience, or other details are provided.
  • Role in Ground Truth: Their qualitative review ("evaluated to be able to obtain images of sufficient quality") served as the ground truth for image quality.

4. Adjudication Method for the Test Set

• AutoPose: Not explicitly stated. The results imply a direct comparison of workflow steps, but it's not mentioned if multiple technologists evaluated the same cases or how discrepancies were handled.
• Body Still Shot: Not explicitly stated how reviews were conducted if multiple M.D.s were involved (e.g., consensus, majority vote).

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

• Was it done?: No, a formal MRMC comparative effectiveness study demonstrating how human readers improve with AI vs. without AI assistance was not performed or reported for either AutoPose or Body Still Shot.
• Effect Size: Not applicable, as no such study was presented. The studies were focused on workflow efficiency (AutoPose) and qualitative image quality (Body Still Shot).

6. Standalone (Algorithm Only) Performance

• Was it done?: The document does not describe a standalone AI performance study (e.g., precision, recall, F1-score for AutoPose's pose recognition; or a quantitative image quality metric for Body Still Shot). The evaluation of AutoPose was focused on the workflow impact, and Body Still Shot on perceived image quality by human reviewers.

7. Type of Ground Truth Used

• AutoPose:
  • For Scan Range Setting: The "ground truth" or reference for the AutoPose evaluation was the manual scan range setting process and the expected optimal scan position as determined by certified radiological technologists. The metric was a reduction in the number of workflow steps.
• Body Still Shot:
  • For Image Quality: The ground truth for image quality was based on the qualitative assessment and review by "Japanese M.D." to determine "sufficient quality." This is essentially expert consensus on image usability.

8. Sample Size for the Training Set

• The document does not provide information on the sample size used for training the AI models (AutoPose and Body Still Shot).

9. How Ground Truth for the Training Set was Established

• The document does not provide information on how the ground truth for the training set was established for the AI models.

Ask a specific question about this device

The SCENARIA View 4.2 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 quidance. 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 FUJIFILM Healthcare Corporation.

The SCENARIA View 4.2 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 4.20system 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 4.2 system consists of a Gantry, Operator's Workstation, Patient Table, High- Frequency X-ray Generator, and accessories.

Here's a breakdown of the acceptance criteria and study information for the Scenaria View 4.2 CT system, based on the provided text:

Important Note: The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. This type of document often relies on comparative analysis and verification that new features do not negatively impact existing performance, rather than extensive clinical efficacy studies for the entire device. For a CT Scanner, the primary acceptance criteria revolve around image quality, dose, and safety, often demonstrated through bench testing and compliance with recognized standards.

Acceptance Criteria and Reported Device Performance

• Automatic analysis queue for main recon of original inspection registered and executed.
• Automatic analysis queue for original inspection multi-recon registered and executed after multi-recon.
• Automatic analysis queue for PES registered and executed after Exam Split.
• Exam Split starts after scan, Multi Recon starts after recon completion. All testing passed. |
  | Safety & Standards | Compliance with:
• AAMI ANSI ES60601-1:2005/(R) 2012 and A1:2012. C1:2009/(R)2012 and . A2:2010/(R)2012 (Medical electrical equipment - General requirements for basic safety and essential performance) | Conformance demonstrated. |
  | | - IEC 60601-1-2 Edition 4.0 (Electromagnetic compatibility) | Conformance demonstrated. |
  | | - IEC 60601-1-3 Edition 2.1 (Radiation protection in diagnostic X-ray equipment) | Conformance demonstrated. |
  | | - IEC 60601-2-44 Edition 3.2 (Particular requirements for the basic safety and essential performance of x-ray equipment for computed tomography) | Conformance demonstrated. |
  | | - IEC 62304 Edition 1.1 (Medical device software - Software life cycle processes) | Conformance demonstrated. |
  | | - NEMA XR 25 (Computed Tomography Dose Check) | Conformance demonstrated. |
  | Technological Equivalence| Features (Tilt for helical scan, improved Exam Split, AutoPositioning) do not impact safety and effectiveness compared to the predicate device, and the subject device is substantially equivalent to the predicate device (K213829). | Thorough analysis and comparison conducted. Technological characteristics (e.g., SSD for image storage, new features) do not impact safety and effectiveness. |

Study Details

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

   • The document does not specify a numerical "sample size" in terms of patient cases for testing.
   • The performance evaluations for image quality and dose (Dose Profile, Noise, MTF, Slice Thickness, CT dose index, etc.) are described as "Performance Testing - Bench." This typically involves phantom studies or specified calibration procedures rather than patient data.
   • For the new software features (AutoPositioning, ExamSplit), testing involved "various cases" and "mock procedure," which are likely internal verification and validation tests rather than tests on a diverse patient dataset.
   • Data Provenance: Not explicitly stated as retrospective or prospective patient data, but the descriptions strongly suggest bench testing with phantoms/test objects or internal system validation using mock scenarios/simulated data. No country of origin for patient data is mentioned as no clinical studies with patient data were detailed for the new features.

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

   • This information is not provided in the summary. For performance testing on a CT scanner, ground truth is usually established through physical measurements, calibration standards, and technical specifications, rather than expert interpretation of images for diagnosis. For the software features, the "ground truth" was whether the feature performed as designed based on the functional requirements.

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

   • None is explicitly mentioned. The testing described (bench tests, functional verification) does not typically involve human adjudication in the way clinical studies for diagnostic accuracy would.

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 was done or described. The device is a CT imaging system, and while it has a "Low Dose CT Lung Cancer Screening Option," the submission discusses the system's performance and new software features like AutoPositioning and ExamSplit, not a specific AI-assisted diagnostic tool. There is no mention of AI assistance for human readers or any effect size related to reader improvement.

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

   • The document describes the performance of the CT system and its software features. The "Low Dose CT Lung Cancer Screening Option" is an indication of use for the system, not a separate standalone algorithm whose performance is being evaluated independently. The new features (AutoPositioning, ExamSplit) are functionalities of the CT system itself, not standalone algorithms for diagnosis. The performance testing is focused on the system's technical specifications and the correct functioning of these features. Therefore, this question is not directly applicable in the context of the information provided for this CT device's 510(k).

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

   • For image quality and dose metrics (Dose Profile, Noise, MTF, etc.), the ground truth is established by physical measurements, standardized phantoms, and adherence to technical specifications and industry standards.
   • For the new software features (AutoPositioning, ExamSplit), the ground truth was the pre-defined functional requirements and expected system behavior.

7. The sample size for the training set:

   • This information is not provided as the document describes a CT imaging system and its software features, not a machine learning or AI model that requires a dedicated training set for diagnostic purposes described in the output. The software features mentioned (AutoPositioning, ExamSplit) are likely rule-based or algorithmic improvements, not deep learning models.

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

   • This information is not provided and is not applicable given the absence of a stated training set for a machine learning or AI algorithm.

Ask a specific question about this device

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.

Ask a specific question about this device

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 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 text describes a 510(k) premarket notification for the Hitachi SCENARIA View computed tomography x-ray system (K200498). However, it focuses heavily on demonstrating substantial equivalence to a predicate device (SCENARIA View K190841) rather than detailing specific acceptance criteria and a study proving those criteria are met for this new iteration of the device, especially concerning any new AI features.

The document does mention two new features: "Volume Shuttle Scan" and "HiMAR Plus," and a "clinical image study to assess the image quality of the images reconstructed by using FBP and the two new features (HiMAR Plus, Intelli IPV)." It's unclear if "Intelli IPV" is a typo for "Volume Shuttle Scan" or another unmentioned feature.

Given the information provided, I cannot fully answer all aspects of your request as the document does not contain explicit acceptance criteria and detailed study results in the format you've requested for the new features. It primarily states that the overall device performance is "similar to the predicate device" and that "evaluation results confirm the performance characteristics of the SCENARIA View are comparable to the predicate device."

Here's an attempt to organize the available information based on your request, with significant gaps noted:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in a quantitative manner for new features or a direct comparison to specific performance metrics for the subject device (K200498) against pre-defined thresholds. Instead, it relies on demonstrating comparability to a predicate device (K190841) and general compliance with standards.

For the overall system, the document states:

• "This device complies with all applicable requirements for Dose Profile, Noise, Mean CT number and Uniformity, Spatial Resolution, Tomographic Section Thickness and Sensitivity Profile, Tomographic Plane Location, and CT dose index."
• "The evaluation results confirm the performance characteristics of the SCENARIA View are comparable to the predicate device."

For the new features (HiMAR Plus, Volume Shuttle Scan, and potentially Intelli IPV), specific acceptance criteria and their met performance are not detailed. The phrase "clinical image study to assess the image quality of the images reconstructed by using FBP and the two new features" implies an evaluation, but the results or acceptance criteria for this evaluation are not provided.

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

The document mentions a "clinical image study" for the new features. However, it does not provide any specific information on:

• Sample size (number of images or patients) used for this test set.
• Data provenance (e.g., country of origin, retrospective or prospective nature).

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

This information is not provided in the document.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. It briefly notes a "clinical evaluation comparison was conducted with the SCENARIA View system and the SCENARIA Phase 3 System (K150595) and found to be substantially equivalent," but this appears to be a general comparison of overall system performance rather than a specific MRMC study involving human readers with/without AI assistance.

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

The document does not specify if a standalone performance study was conducted. The mentioned "clinical image study" likely involves subjective evaluation of reconstructed images, which could imply a standalone assessment of image quality, but details are lacking.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for the "clinical image study." Given the context of image quality assessment for new CT reconstruction features, the ground truth would likely be based on:

• Expert Consensus: Radiologist interpretation of image quality parameters.
• Physical Phantoms: Quantitative measurements using known phantom properties (though this tends to be more for technical performance aspects like noise and spatial resolution rather than a "clinical image study").

The document mentions evaluations for "dose profile, image noise, Modulation Transfer Function (MTF), slice thickness and sensitivity profile, slice plane location, and CT dose index," which would typically use physical phantoms. However, the "clinical image study" for "image quality of the images reconstructed by using FBP and the two new features" suggests a different type of assessment.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This is expected as the document describes a CT system (hardware and associated software features) rather than a deep learning AI model that typically requires extensive training data. The "new features" like HiMAR Plus (HItachi's Metal Artifact Reduction) are often based on algorithmic improvements rather than learned models from large datasets.

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

As no training set is mentioned in the context of typical AI/ML development, this information is not applicable/provided.

Summary of Gaps:

The FDA 510(k) summary provided is primarily focused on demonstrating substantial equivalence to a predicate device rather than detailing specific, quantitative acceptance criteria and the rigorous testing (especially for any AI components) that would fully answer your questions. While it mentions new features and a clinical image study, critical details such as sample sizes, expert qualifications, and specific results are absent in this public summary. These details would typically be found in the full submission to the FDA.

Ask a specific question about this device

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 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 text details the 510(k) premarket notification for the Hitachi SCENARIA View computed tomography x-ray system (K190841). The core of the submission focuses on demonstrating substantial equivalence to a predicate device, the SCENARIA Phase 3 (K150595).

Based on the provided document, here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

The document does not explicitly present a table of quantitative acceptance criteria for the overall device performance in the sense of a new AI/software component with specific clinical performance metrics (e.g., sensitivity, specificity for a diagnostic task). Instead, the acceptance criteria are implicitly tied to demonstrating that the SCENARIA View system performs comparably to its predicate device (SCENARIA Phase 3) and meets established industry standards for CT systems.

The performance characteristics evaluated and reported are typically those for CT imaging systems, rather than AI-specific metrics. The document states:

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

The document mentions "a clinical image study of the head, chest, abdomen, and shoulder" and "a clinical study was conducted with the Intelli IPV, FBP, and HiMAR features". However, it does not specify the sample size (number of patients or images) used in these clinical studies or bench tests for the test set.

The data provenance (e.g., country of origin, retrospective or prospective) is also not specified in the provided text.

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

The document states, "Therefore, based on a thorough analysis and of the clinical images Hitachi believes the SCENARIA View is diagnostic and meet the user needs." This implies an expert review, but it does not specify the number of experts, their qualifications, or the methodology they used to establish ground truth or evaluate the "diagnosticity" or "user needs."

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

The document does not specify any adjudication method used for reviewing the clinical images or test sets.

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

The document does not indicate that an MRMC study was performed. The evaluation focuses on the system's inherent performance and its substantial equivalence to a predicate, not on human reader performance with or without AI assistance. The "Intelli IPV" and "HiMAR" features are described as new iterative reconstruction and metal artifact reduction techniques, respectively, which are intrinsic image processing methods of the CT system rather than assistive AI tools for human interpretation in the common sense of an AI CAD (Computer-Aided Detection) or CADx (Computer-Aided Diagnosis) system.

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

The entire submission focuses on the performance of the integrated CT system (SCENARIA View) which includes its image acquisition and reconstruction algorithms. Therefore, the "evaluations were conducted for dose profile, image noise, Modulation Transfer Function (MTF), slice thickness and sensitivity profile, slice plane location, and CT dose index" and "bench testing...in terms of image quality metrics such as CT number accuracy, uniformity, noise" can be considered forms of standalone algorithmic performance assessment based on objective phantom and image quality metrics. The "clinical image study" also evaluates the system's output directly.

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

For the technical performance evaluations (dose profile, noise, MTF, etc.), the ground truth relies on physical phantom measurements and engineering specifications/standards.

For the "clinical image study," the ground truth implicitly relies on expert subjective assessment of image diagnosticity and ability to meet user needs, "based on a thorough analysis and of the clinical images Hitachi believes the SCENARIA View is diagnostic and meet the user needs." There is no mention of pathology or outcomes data as ground truth.

8. The sample size for the training set

The document does not describe a "training set" in the context of an AI model being developed from scratch. The "Intelli IPV" and "HiMAR" are advanced image reconstruction techniques, which are typically developed using a combination of physics models, empirical data, and potentially machine learning techniques, but the document does not disclose details about any training data or its sample size for these specific features. The device's substantial equivalence is demonstrated against an existing predicate CT system, which implies that its fundamental design and performance are already established, rather than being a de novo AI system requiring a separate training and validation set disclosure in this context.

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

As no specific training set for a new AI model is described, there's no information on how its ground truth was established. The performance of the image reconstruction algorithms (Intelli IPV, HiMAR) would have been validated against various phantom and clinical datasets to ensure they produce images of acceptable diagnostic quality, likely benchmarked against existing reconstruction methods and assessed by image quality experts. However, the specifics of this process are not detailed in the provided K190841 summary.

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