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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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The Low Dose CT (LDCT) Lung Cancer Screening Option (LCS) for Qualified GE Systems is indicated for using low dose CT for lung cancer screening must be performed within the established inclusion criteria of programs/ protocols that have been approved and published by either a governmental body or professional medical society.

*Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

There are not any functional, performance, feature, or design changes required for the Qualified CT system onto which the Option is applied.

Because none of the CTs will require hardware or software modifications the subject device for qualified systems in the installed base consists of:

1. a set of three reference LDCT LCS protocols (small, average, large patient) for each qualified CT System on a per CT platform basis;

2. detailed instructions on how to transfer the protocols onto the corresponding CT System: and

3. a dedicated for user's manual for LDCT LCS that covers all qualified systems.

For qualified forward production systems, the three above elements that constitute the subject device for the qualified systems in the installed will be deployed in a modified manner:

1. the 3 LDCT LCS reference protocols for the Qualified system will be loaded onto the system at the factory:

2. because the reference LDCT LCS protocols will already be on the system, there will be no need for detailed instructions on how to manually enter the protocols; and

3. the dedicated user manual for LDCT LCS may be folded in as a new separate chapter of the system's user manual.

For qualified forward production systems, the LDCT LCS "device" will be structured into the qualified systems. This will result in all qualified forward production systems always incorporating this LDCT LCS Option.

The provided document is a 510(k) Premarket Notification Submission for a "Low Dose CT Lung Cancer Screening Option for Qualified GE CT Systems". It describes the device's indications for use, technological characteristics, and arguments for substantial equivalence to predicate devices, rather than presenting a study specifically designed to establish acceptance criteria and prove the device meets those criteria with detailed performance metrics.

However, from the document, we can infer some "acceptance criteria" through the image quality metrics used for evaluating substantial equivalence and the general claim that the device is "safe and effective". The study conducted to support this is a bench test using phantoms, rather than a clinical trial with human subjects.

Here's an attempt to structure the information based on your request, with the understanding that not all specific details you asked for are explicitly provided in this type of regulatory document.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly derived from the ability of the qualified GE CT systems, using the new LDCT LCS protocols, to maintain image quality comparable to or better than predicate devices used in past clinical trials (like NLST) and to allow for the detection and sizing of lung nodules. The performance is assessed via phantom studies.

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

• Test Set (Phantom Study): The test set primarily consisted of:
  • Standard IQ phantoms (e.g., Catphan for NPS).
  • An anthropomorphic clinical simulation lung phantom with 5mm solid and nonsolid nodules.
• Sample Size:
  • For the IQ phantoms, it's not specified how many scans or instances were used, but rather the type of phantoms.
  • For the anthropomorphic lung phantom, specific nodules (5mm solid and nonsolid) were evaluated.
  • The "test set" also implicitly refers to the representative CT systems chosen: LightSpeed 16, Discovery CT590 RT, LightSpeed VCT and Optima CT 660, Discovery CT750 HD, and Revolution CT.
• Data Provenance: The data was generated through bench testing (phantom studies) conducted by GE Medical Systems, LLC (GE Healthcare). The location of the testing is not explicitly stated but presumed to be internal GE facilities. This is a prospective generation of data for the 510(k) submission.

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

• Number of Experts: "Experienced imaging physicists and applications specialists" were used. The exact number is not specified, but the plural "specialists" suggests more than one.
• Qualifications: "Experienced imaging physicists and applications specialists." No specific number of years of experience or board certifications (like radiologist) are mentioned, as the evaluation was of phantom images, not clinical images.

4. Adjudication Method for the Test Set

• The document states, "In all cases, the small, lowest contrast nodule was easily seen" by the experienced imaging physicists and applications specialists. This suggests a consensus or affirmation rather than a formal adjudication method (like 2+1 or 3+1). Since it was a detectability assessment on phantom images rather than a diagnostic decision, a formal adjudication protocol appears to have been deemed unnecessary.

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

• No, an MRMC comparative effectiveness study was not done for this specific 510(k) submission to demonstrate the effectiveness of the device itself.
• The submission references large clinical trials like the National Lung Screening Trial (NLST) and I-ELCAP to establish the safety and effectiveness of LDCT Lung Cancer Screening in general, performed within established protocols, for which GE CT systems were previously used. However, these trials were not conducted to compare human readers with and without the specific GE device option at hand.
• Effect size of human reader improvement: Not applicable, as no such study was performed.

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

• Not applicable. The "Low Dose CT Lung Cancer Screening Option" is not an AI algorithm for nodule detection or diagnosis; rather, it is a set of optimized acquisition protocols and a user manual for existing GE CT systems to be used for LDCT lung cancer screening. Its performance is assessed by the physical image quality metrics it produces, which then aids human readers.

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

• For the phantom study, the "ground truth" for the nodules (size, type, location) was inherent in the design of the anthropomorphic lung phantom. The detectability was then visually confirmed by experienced imaging physicists and applications specialists.
• For the broader claim of the safety and effectiveness of LDCT LCS, the submission relies on the ground truth established by large-scale clinical trials (e.g., NLST) and medical professional society guidelines, which are based on clinical outcomes and expert consensus.

8. The Sample Size for the Training Set

• This device is not an AI/ML algorithm that requires a "training set" in the conventional sense. The "training" for developing the new LDCT LCS protocols involved:
  • Reviewing existing reference protocols for Chest CT on GE CT systems.
  • A literature review of current guidance on appropriate CT acquisition parameters, reconstructions, and system functional performance capabilities for LDCT LCS.
  • Synthesizing this information and guidance recommendations to determine acquisition and reconstruction attributes.
  • Using these attributes and GE CT system knowledge to develop the specific LDCT LCS Scan Parameters for each qualified CT system.
• Therefore, there isn't a quantifiable "sample size" for a training set as would be found in an AI/ML device submission.

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

• As noted above, there isn't a traditional "training set" with ground truth in the context of an algorithm. Instead, the protocol development was based on:
  • Existing product specifications and performance data: From GE CT systems.
  • Published clinical literature and guidelines: Reference publications, clinical trials (like NLST, I-ELCAP), medical professional society guides and recommendations (e.g., USPSTF, CMS decisions). These sources provided the "ground truth" (or accepted best practices) for what constitutes effective and safe LDCT LCS.
  • Expert knowledge: Internal GE CT system knowledge and the expertise of their engineers and applications specialists.

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