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The Auto Positioning feature provides an alternate, streamlined and efficient workflow and safety checks for the CT technologist in setting up CT examinations of the initiation of the first scout scan.

Auto Positioning acquires 3D spatial information of the individual patient on the table and combines it with information from the selected protocol to automatically calculate and visually display the scout's start and end locations. Concurrently it checks for proper patient orientation, determines the table height for optimum patient centering, and checks for potential contact between the patient and the gantry. Upon acceptance by the technologist the patient is automatically moved to the correct scout start location.

Use of Auto Positioning is intended to provide consistent patient positioning for optimal image quality and automatic exposure control.

Auto Positioning is an optional feature developed for use with GE CT systems. The purpose of this feature is to provide both a streamlined workflow and enhanced quality and safety checks during the exam setup process up to the initiation of the first scout scan. Incorporation of this optional feature does not preclude the technologist from preforming the existing manual workflow on the CT system, if desired.

Auto Positioning uses a fixed, ceiling mounted, off the shelf, 2D/3D video camera that is capable of determining distances to points in its field of view. It displays standard RGB video images on the CT system's existing gantry-mounted touchscreens. Information from the standard output of the camera, precise spatial information of the individual CT system's gantry and table installation geometry, and information contained in the user-selected protocol is used to determine the anatomical landmark location and the start and end locations for the scout scan(s).

Information from the standard output of the camera, precise spatial information of the individual CT system's gantry and table installation geometry, and information contained in the userselected protocol is used to determine the anatomical landmark location and the start and end locations for the scout scan(s).

Addition functionality of Auto Positioning includes performing safety checks for patient orientation and the potential for the patient to come into contact with the gantry while the patient is placed into the gantry and during scanning.

The GE Auto Positioning device is a patient positioning workflow enhancement tool for CT systems. It uses a 2D/3D video camera and deep learning to automate the process of setting the landmark, patient centering, scout's start and end locations, and the scout's start table position. It also performs safety checks for patient orientation and potential patient-gantry collision.

Here's an analysis of its acceptance criteria and the study that proves its effectiveness:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list a table of acceptance criteria with corresponding performance metrics for the Auto Positioning device. However, it indicates that "All testing met its predefined acceptance criteria." The narrative suggests the criteria would relate to the accuracy of landmark location, scout scan start and end locations, proper patient centering, correct patient orientation detection, and gantry collision prevention.

Based on the information, the reported device performance is that all non-clinical bench testing, which included the evaluation of landmark location and scout scan's start and end location, successfully met its predefined acceptance criteria. The document also states that the device was developed under GE Healthcare's quality system, and all subsystem and system verification testing, including hazard mitigation, demonstrated that the Auto Positioning feature meets its design inputs and user needs.

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

The document explicitly states: "Because Auto Postioning is for the exam setup process up to the initiation of the first scout scan, and does not involve diagnostic imaging or diagnostic evaluation, non-clinical bench testing is appropriate."

And further: "The Auto Positioning can be fully tested on the engineering bench thus no additional clinical testing was required."

Therefore, no clinical test set with patient data (and thus no associated sample size or data provenance) was used for direct performance evaluation for this 510(k) submission. The testing was conducted on an "engineering bench."

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

Since the testing was non-clinical bench testing and no clinical test set was used, there is no mention of experts or their qualifications for establishing ground truth from patient data. The "ground truth" for the non-clinical testing would have been established by engineering specifications and measurements. Engineers or technical experts involved in the design and verification would have assumed this role.

4. Adjudication Method for the Test Set

As there was no clinical test set using human readers, there was no adjudication method employed.

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

No, an MRMC comparative effectiveness study was not done. The document states that no clinical testing was required or performed. The device is focused on workflow enhancement and safety checks, not diagnostic image interpretation.

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

Yes, the primary evaluation was a standalone "algorithm only" performance, given the context of "non-clinical bench testing" and the statement that the device "can be fully tested on the engineering bench." The system's ability to accurately determine landmark locations, scout start/end points, patient orientation, and gantry collision potential was evaluated without human intervention in the positioning process itself. The technologist's role is to accept the automatically calculated positions.

7. The Type of Ground Truth Used

For the non-clinical bench testing described, the ground truth would have been based on:

• Engineering Specifications: Precisely defined parameters and measurements for expected landmark locations, optimal patient centering, and safe gantry clearance.
• Physical Measurements: Direct measurements of dummy patients, phantoms, or test setups on the engineering bench to represent ideal or boundary conditions. These measurements would then be compared against the device's output.

8. The Sample Size for the Training Set

The document mentions that "Auto Positioning uses Deep Learning CNNs to determine the scout's landmark location and the patient orientation." However, it does not provide any information regarding the sample size of the training set used for these Deep Learning Convolutional Neural Networks (CNNs).

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

The document does not describe how the ground truth for the training set was established for the Deep Learning CNNs. Typically, for such applications, ground truth for training data would involve:

• Manual Annotation by Experts: CT technologists or other medical imaging professionals manually identifying landmarks and patient orientations in a large dataset of patient images or 3D scans.
• Synthetic Data Generation: Creating artificial data with known ground truth based on anatomical models.
• Measurement from Phantoms/Physical Setups: Using a controlled environment with phantoms where the exact positions and orientations are known.

Without further information, the specific method used for the Auto Positioning device's deep learning training ground truth remains unknown from the provided text.

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