Search Results

The NL3000 [CereTom Elite] CT system is intended to be used for x-ray computed tomography applications for anatomy that can be imaged in the 25cm field of view, primarily head and neck.

The CT system is intended to be used for both pediatric and adult imaging and as such has preset dose settings based upon weight and age. The CT images can be obtained either with or without contrast.

The CereTom Elite is an improved version of CereTom computed tomography system providing enhanced functionality. It still has the same high resolution, 8 row, 32 cm bore and 25cm field of view. The lightweight translating gantry consists of a rotating disk with a solid state x-ray generator, Gd2O2S detector array, collimator, control computer, communications link, power slip-ring, data acquisition system, reconstruction computer, power system and brushless DC servo drive system (disk rotation). The power system consists of batteries which provide system power while unplugged from the charging outlet. The system has the necessary safety features such as the emergency stop switch, xray indicators, interlocks, patient alignment laser and 110% x-ray timer. CereTom Elite also has a scanner drive system (SDS), so that the system can be moved easily to different locations.

The provided text describes the CereTom Elite Computed Tomography system and compares it to a predicate device (CereTom K051765) and a reference device (Philips Brilliance CT 16-slice Configuration K012009). The document focuses on demonstrating substantial equivalence rather than presenting a standalone study with specific acceptance criteria and performance metrics for a novel AI/algorithm.

Based on the information provided, here's an analysis of the requested points, with the understanding that this is a CT system, not an AI algorithm in the typical sense for which these questions are usually posed:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with reported numerical performance values in the context of an AI-driven diagnostic accuracy study. Instead, it discusses the device's conformance to safety, performance, and image quality standards, and its equivalence to a predicate device.

The "acceptance criteria" here are implied by the compliance with recognized consensus standards and the demonstration of comparable image quality to the predicate device.

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

The document describes phantom image quality tests for the CereTom Elite system. It does not mention a test set based on patient data, nor does it specify a sample size for these phantom tests (e.g., how many phantom scans were performed).

• Sample Size: Not specified for image quality tests, but they were conducted using an "anatomical phantom."
• Data Provenance: The tests are internal verification and validation activities, and external testing, implying controlled laboratory or manufacturing settings using phantoms. No patient data provenance (country, retrospective/prospective) is provided as it's not a clinical study on patient data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not applicable in the context of the provided document. The CereTom Elite is a CT imaging device, and its performance evaluation primarily involves physical measurements using phantoms and comparing those measurements to established engineering and medical device standards. There is no mention of human experts establishing "ground truth" for diagnostic accuracy in a clinical dataset.

4. Adjudication Method for the Test Set

This information is not applicable as there is no mention of a human expert diagnostic reading study or any adjudication process for a test set of clinical images. The evaluation is based on technical performance metrics from phantom scans.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted or reported in this document. This typically involves human readers interpreting cases with and without an AI's assistance to measure the AI's impact on diagnostic performance. The document describes the technical performance and equivalence of a CT scanner.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study in the context of an "algorithm only without human-in-the-loop performance" is not explicitly performed or detailed in the way typically expected for an AI algorithm. The document assesses the standalone technical performance of the CT scanner hardware and its integrated software features (like AEC, MAR, reconstruction algorithms) through phantom testing. The performance metrics cited (spatial resolution, noise, etc.) are inherent to the device's image generation capabilities.

7. Type of Ground Truth Used

The "ground truth" for the technical and image quality tests primarily relies on:

• Phantom measurements: Physical properties and known configurations of the phantoms.
• Engineering specifications and regulatory standards: Conformance to established benchmarks for CT system performance (e.g., spatial resolution targets, dose limits, safety standards).
• Comparison to predicate device: The performance of the predicate device (CereTom K051765) serves as a benchmark for equivalence.

8. Sample Size for the Training Set

This information is not applicable. The CereTom Elite is a CT imaging system. While it has embedded software with algorithms for image reconstruction, artifact reduction, and dose control, it is not described as a deep learning or machine learning system that requires a distinct "training set" of patient data in the typical AI sense. The algorithms are likely based on traditional signal processing and image reconstruction techniques, which are validated against known inputs and expected outputs, not "trained" on large datasets.

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

This information is not applicable for the same reasons as point 8. No explicit training set or ground truth establishment method for it is mentioned. Development and validation would involve engineering principles and testing against known physical properties and simulated scenarios.

Ask a specific question about this device