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The Supria system is indicated for head, whole body, and vascular X-ray Computed Tomography applications in patients of all ages. The images can be acquired in either axial, helical, or dynamic modes.

The volume datasets acquired by the Supria can be post processed by the system to provide additional information. Post processing capabilities included in the Supria software include CT angiography (CTA), Multi-planar reconstruction (MPR) and volume rendering.

Volume datasets acquired by the Supria can be transferred to external devices via a DICOM standard interface.

The guideShot Option adds a remote in-room display and controls to support interventional imaging. The device output can provide an aid to diagnosis when used by a qualified physician.

The Supria is a multi-slice computed tomography system designed to perform multi-slice CT scanning supported by 16-detector technology. The system allows optimum clinical applications ranging from routine exams in response to the diversified circumstances in imaging whole body regions.

The Supria system uses 16-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 16 slices of data simultaneously. The Xray 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 Supria system consists of a Gantry, Operator's Workstation, Patient Table, High-Frequency X-ray Generator, and accessories.

The provided text is a 510(k) Pre-market Notification for a medical device, specifically the HITACHI Supria Whole-body X-ray CT System Phase 3. It compares the new device to a predicate device (HITACHI SUPRIA w/guideShot Option K161748) to demonstrate substantial equivalence, rather than providing a detailed study proving the device meets acceptance criteria in the sense of a performance study with specific metrics and statistical analysis.

The document states that the new device has two new features: "Intelli IP Quick" (a faster noise reduction technique) and "HiMAR" (reduces artifacts caused by metal). The "Performance Testing - Clinical" section briefly mentions that "clinical images were collected and analyzed" for these new features to "ensure that images constructed by the Supria Whole-body X-ray CT System meet user needs." It also notes that "Hitachi has provided clinical images demonstrating the image quality of Intelli IP Quick and HiMAR features and validated by a physician."

Therefore, it is important to note that the provided text does NOT contain the detailed information typically found in a clinical study report that defines and proves specific acceptance criteria for performance metrics (like sensitivity, specificity, accuracy) using a rigorous methodology. Instead, it relies on demonstrating comparable performance to a predicate device and physician validation of image quality for new features.

Based on the provided text, here's what can be extracted and what remains unknown:

Acceptance Criteria and Device Performance (Based on provided text)

Since direct quantitative acceptance criteria and performance metrics are not explicitly stated in a table format for the new features or overall device, we can infer the "acceptance" is primarily based on substantial equivalence to the predicate device and subjective physician validation of image quality for the new features.

"Hitachi believes that, based on the information included in the submission, Supria Whole-body X-ray CT System Phase 3 is substantially equivalent with respect to hardware, base elements of the software, safety, effectiveness, and functionality to the SUPRIA w/guideShot Option (K161748)." |
| - Hardware | No differences identified (e.g., Gantry, Detector, X-ray Tube, X-ray Generator, Patient Table, Display, Image Storage parameters are identical to predicate). |
| - Base elements of software | Most software features are identical to the predicate. Key differences (Intelli IP Quick, HiMAR, Orbit synchronization scan, Off-time mode, On-time standby, Shutter Scan Reduction) are described as improvements or additional functionalities. |
| - Safety | "The technological characteristics do not impact safety and effectiveness." (Stated for the differences in Table 3). Compliance with applicable safety standards (e.g., IEC 60601 series, NEMA XR 25, NEMA XR26) is declared. |
| - Effectiveness | "The technological characteristics do not impact safety and effectiveness." (Stated for the differences in Table 3). Clinical images demonstrating the image quality of Intelli IP Quick and HiMAR features were "collected and analyzed" and "validated by a physician" to "ensure that images constructed by the Supria Whole-body X-ray CT System meet user needs." The overall "Performance Comparison" section also states "A clinical evaluation comparison was conducted with the Supria Phase 3 system and the SUPRIA w/guideShot Option (K161748) and found to be substantially equivalent." |
| - Functionality | Detailed comparison in Table 2 shows identical functionality for many parameters, with new features (Intelli IP Quick, HiMAR etc.) presented as enhancements that do not negatively impact core functionality. |
| Image Quality with new features (Intelli IP Quick, HiMAR) | "clinical images demonstrating the image quality of Intelli IP Quick and HiMAR features and validated by a physician." The images were collected and analyzed "to ensure that images constructed by the Supria Whole-body X-ray CT System meet user needs." |

Study Details:

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

   • Test Set Sample Size: Not specified. The document only mentions that "clinical images were collected and analyzed" for the new features. No specific number of images or patients is provided.
   • Data Provenance: Not specified regarding country of origin. The study is described as "clinical images were collected," implying real patient data. It is a retrospective or prospective study is not specified, but the phrasing "were collected" could suggest a collection from existing or newly acquired cases.

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

   • Number of Experts: Not specified. The document states the image quality was "validated by a physician." It does not specify if this was one physician or a panel.
   • Qualifications of Experts: The qualification is generally stated as "a physician." Specific specialties (e.g., Radiologist) or years of experience are not mentioned.

3. Adjudication method for the test set:

   • Not specified. Given the limited detail ("validated by a physician"), it's unlikely a formal adjudication method (like 2+1 or 3+1) was employed and documented in this 510(k) submission.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

   • Not explicitly stated or described. The document refers to a "clinical evaluation comparison" but does not detail it as a formal MRMC study. It states the comparison "found to be substantially equivalent" and that clinical images were "validated by a physician." There is no mention of multiple human readers, a comparative effectiveness study design, or an effect size for human readers' improvement with AI assistance. The new features (Intelli IP Quick, HiMAR) are signal processing techniques within the CT system, not an AI assistance tool for human interpretation in the sense of a CAD system.

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

   • The "performance comparison" section mentions "Performance Testing - Bench" with a rationale analysis indicating "Hitachi judged that Supria Whole-body X-ray CT System Phase 3 is substantially equivalent to the predicate." It also notes that the 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." This sounds like standalone technical performance testing, but not necessarily a clinical "algorithm only" performance evaluation akin to an AI diagnostic tool. The device itself is a CT scanner, not an AI algorithm intended for standalone diagnosis.

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

   • For the clinical evaluation of the new features (Intelli IP Quick, HiMAR), the ground truth appears to be based on "physician validation" of "image quality" and ensuring that the images "meet user needs." This is a subjective assessment, not pathology or outcomes data. For the comparison to the predicate, it's about comparable physical and performance characteristics.

7. The sample size for the training set:

   • Not applicable / Not specified. The document describes a CT system and its new image processing features. It does not mention a "training set" in the context of machine learning. The "Intelli IP Quick" and "HiMAR" are described as "processing techniques" that reduce noise or reduce metal artifacts, implying algorithms that might have been developed and tuned, but the text does not detail any "training data" or "training set" as would be seen for a deep learning model.

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

   • Not applicable / Not specified. As no training set or machine learning model is explicitly described, there is no information on how a ground truth for such a set would have been established.

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The Supria system is indicated for head, whole body, cardiac and vascular X-ray Computed Tomography applications in patients of all ages. The images can be acquired in either axial, helical, gated or dynamic modes.

The volume datasets acquired by the Supria can be post processed by the system to provide additional information and can be transferred to external devices via a DICOM standard interface.

Post processing capabilities included in the Supria software include CT angiography (CTA), Multi-planar reconstruction (MPR) and volume rendering.

The device output can provide an aid to diagnosis when used by a qualified physician.

The Supria is a multi-slice computed tomography system designed to perform multi-slice CT scanning supported by 16-detector technology. The system allows optimum clinical applications ranging from routine exams in response to the diversified circumstances in imaging whole body regions.

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

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria for clinical performance in a structured table. Instead, it relies on a qualitative assessment against a predicate device. The performance comparisons for the Supria CT system are primarily against the SCENARIA Phase 2 Whole-body X-ray CT System (K123509).

• Six clinical image examples were provided and judged sufficient to demonstrate clinical usability across general anatomy outlined in indications for use. These were deemed comparable to the predicate's examples, with the exception of cardiac images due to lack of ECG support in Supria.
• A radiologist validated that clinical images using image quality optimization technology (Intelli IP Advanced and IntelliEC) exhibited "acceptable image quality for clinical use." |
  | Physical and Performance Characteristics (General equivalence to predicate and regulatory compliance) | Bench Performance Testing:
• Evaluation for dose profile, image noise, Modulation Transfer Function (MTF), slice thickness and sensitivity profile, slice plane location, and CT dose index were conducted.
• Found to be "substantially equivalent" to the predicate device for these parameters.
• Confirmed that these items met the conditions of 21 CFR 1020.33(c) or (g).
• Performance characteristics are comparable to the predicate device. |
  | Technological Characteristics (No significant impact on safety and effectiveness despite differences from predicate) | Demonstrated through a detailed comparison (Table 2 & 3) that differences in Gantry, Detector, X-ray Tube, X-ray Generator, Patient Table, Image Storage, Scanning/Reconstruction, Dose Controls, and Features do not "substantially affect the intended use of the device and does not impact the effectivity and safety of this device". For example, the lack of ECG function is acknowledged but deemed not to impact safety/effectiveness for the device's general-purpose use. |
  | Compliance with Standards | Conformance with a list of applicable standards, including AAMI ANSI ES60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-44, NEMA XR 25, NEMA XR26, and IEC 62304. |

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

• Sample Size for Clinical Test Set: "Six clinical image examples" were used. This is a very small sample size for a clinical evaluation.
• Data Provenance: Not explicitly stated, but it's implied that these images were generated by the Supria system itself during its development or testing. No information on country of origin or whether it was retrospective/prospective is provided.

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

• Number of Experts: "A radiologist" (singular) was used to validate the clinical images.
• Qualifications of Experts: The document explicitly states "a radiologist." No further details on experience level (e.g., "10 years of experience") are provided.

4. Adjudication Method for the Test Set

• Adjudication Method: "A radiologist validated" the images. This implies a single-reader assessment rather than a multi-reader adjudication process. No mention of 2+1, 3+1, or any other consensus method.

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, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or performed. This device is an X-ray CT system, not an AI-powered diagnostic tool, and the evaluation focuses on the inherent performance and image quality of the hardware and software without specific "AI assistance" for human readers in a comparative effectiveness study.

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

• This device is an X-ray CT system. Its primary output is images, which are then interpreted by human physicians. Therefore, the concept of "standalone (algorithm only) performance" as it might apply to an AI diagnostic algorithm is not directly applicable here. The performance tests (dose profile, noise, MTF, etc.) are inherent to the machine's operation, and the clinical image assessment validates the output of the machine for human interpretation.

7. The Type of Ground Truth Used

• Ground Truth Type:
  • For bench performance testing, the ground truth was regulatory standards (21 CFR 1020.33(c) or (g)) and physical measurements against known values (e.g., for spatial resolution, MTF).
  • For clinical image examples, the "ground truth" was a qualitative assessment by "a radiologist" that the images had "acceptable image quality for clinical use" and were "sufficient to judge a clinical usability." This is effectively expert consensus (from a single expert) on image quality suitable for diagnosis, rather than pathology, or outcomes data resolving the presence/absence of a specific condition.

8. The Sample Size for the Training Set

• The document does not explicitly mention a "training set" in the context of an AI/machine learning model. The Supria is a CT imaging system. While it has "image quality optimization technology (Intelli IP Advanced and IntelliEC)" and "Iterative Reconstruction," these are typically engineered features based on physics and signal processing principles, not necessarily machine learning models that require a distinct "training set" in the way a diagnostic AI algorithm would. If these features involved machine learning, the training data used is not disclosed.

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

• As a "training set" is not explicitly mentioned or implied for a machine learning context, the method for establishing its ground truth is not provided.

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