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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 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.

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

There are not any functional, performance, feature, or design changes required for the CT systems which the option is applied:

• SCENARIA Phase 3 Whole-Body X-ray CT System K150595
• SUPRIA Whole-body X-ray CT System Phase 3 K163528
  Because neither of the CTs will require hardware or software modifications the subject device will include:
• Three reference LCS protocols (small, average, large patient) for each CT System
• Protocols will be loaded onto the system, there will be no need for installation instructions
• Low Dose CT Lung Cancer Screening Option instruction manual
  The reconstruction method for the LCS protocols is Filtered Back Projection with no iterative reconstruction method. The reconstruction algorithm used was a 21 Lung which is common to demonstrate lung tissues nodules and other lung pathology.
  In addition, Beam Hardening Correction is utilized in the reconstruction process. The beam hardening correction applied to the lung reconstruction algorithm corrects image quality degradation due to radiation hardening caused by metals and other dense subject matter such as shoulders, etc. Hitachi does not apply any other tools or software in the reconstruction process.

The provided text describes the substantial equivalence determination for the "Low Dose CT Lung Cancer Screening Option" from Hitachi Healthcare Americas. The submission focuses on demonstrating that the new option, which consists of reference LCS protocols for existing SCENARIA and SUPRIA CT systems, performs equivalently to a legally marketed predicate device (Philips Multislice CT System with Low Dose CT Lung Cancer Screening - K153444).

Here's an analysis based on the provided information:

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

The document does not explicitly state "acceptance criteria" with numerical thresholds set for a new device. Instead, it defines "Image Quality Metric CTQs" (Critical to Quality) as important parameters for lung cancer screening and subsequently compares the subject devices (Hitachi SCENARIA and SUPRIA CT systems with the LCS option) to the predicate device (Philips Brilliance CT 64-channel) based on these metrics. The goal was to prove "substantial equivalence," meaning the new device performs similarly to the predicate.

Here's a table summarizing the image quality metrics and the reported comparative performance:

Conclusion on Acceptance: Hitachi concluded that the comparison demonstrated "substantial equivalence" based on these metrics, meaning the subject device performs as effectively and safely as the predicate.

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: The non-clinical testing was performed using phantom studies. The document specifies repetition and slice counts for the phantom measurements:
  • SUPRIA and SCENARIA scanners: 15 repetitions one slice, 15 slices one study.
  • Philips scanner: 17 repetitions one slice, 25 slices one study.
• Data provenance: This was a non-clinical bench study comparing CT scanners in a lab setting, not human data. Therefore, country of origin or retrospective/prospective classification (as typically applied to clinical trials) is not applicable. The study was conducted by Hitachi Healthcare Americas.

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)

• For the non-clinical phantom study, there were no human experts establishing ground truth in the traditional sense of clinical interpretation. The "ground truth" was the physical properties of the phantom and the objective numerical measurements derived from the CT images of the phantom.
• The analysis was done using MATLAB, implying objective quantitative assessment.

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

• Since the test set involved objective phantom measurements and not human interpretation of clinical images, an adjudication method for expert consensus is not applicable. The measurements were quantitative and compared directly.

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 MRMC study was done. The submission states: "Hitachi has determined that additional clinical data for our LCS feature is not needed and that comparative phantom analysis is sufficient to demonstrate substantial equivalence."
• This device is not an AI algorithm adding assistance to human readers. It's a set of low-dose protocols for CT systems that are already cleared. The comparison is between the performance of the CT system with these protocols to a predicate CT system with similar protocols, using phantom measurements. Therefore, the question about AI assistance and reader improvement is not relevant to this submission.

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

• This device is not an algorithm in the sense of a standalone AI diagnostic tool. It is a set of acquisition protocols for a CT scanner. The "standalone" performance in this context would refer to the image quality produced by the CT system using these protocols without human intervention in the acquisition process, which was assessed via the phantom study.

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

• The ground truth for the non-clinical testing was the physical properties of the phantom itself. The phantom contains materials of known density and structures of known size. The measurements (e.g., CT numbers, contrast, small object visibility) derived from the CT images are compared against these known physical properties and also against the performance of the predicate device.

8. The sample size for the training set

• This submission focuses on protocols for existing CT systems, not a new algorithm that requires a "training set" in the context of machine learning or AI. The protocols were developed to take advantage of existing CT system capabilities, and their effectiveness was demonstrated by comparing their image quality metrics to a predicate device. Therefore, a "training set" as commonly understood in AI/ML is not applicable.

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

• As a training set is not applicable, establishing corresponding ground truth is also not applicable. The protocols themselves were designed based on engineering principles and NEMA XR25 guidelines to optimize dose reduction while maintaining image quality. Their performance was then validated through the comparative phantom study.

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