(208 days)
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).
| Acceptance Criteria Category | Reported Device Performance (Supria Whole-body X-ray CT System) |
|---|---|
| Clinical Usability / Image Quality (Implicit) | Clinical Performance Testing: |
- 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.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.