Search Results

Multi-Modality Image Fusion is a software application to be used by physicians in the clinic or hospital for 2-D and 3-D visualization, image registration, and fusion of MRI, CT and Ultrasound imaging modalities for mapping planning information across modalities. Additional software features include database management, data communication, surface rendering, segmentation, regions of interest (ROI) delineation, volumetric measurements, and data reporting.

Multi-Modality Image Fusion (MMIF) is software, which comprises of two software components, which is referred to as offline and online. The offline component perfains to the preparation of gland and suspected lesion boundaries on a DICOM image file days or hours prior to the biopsy procedure. The online component fuses the DICOM image files, which were, prepared on the offline component, with a snap shot incoming TRUS image. Each of the two software components can work together or independently.

The provided 510(k) summary for the Multi-Modality Image Fusion device does not contain a specific table of acceptance criteria or detailed results of a study proving the device meets those criteria. However, it does outline the types of tests performed and provides a general statement of success.

Based on the available information, here is a description of the acceptance criteria (inferred from the testing) and the study conducted:

1. Acceptance Criteria and Reported Device Performance

Since explicit acceptance criteria are not provided, they are inferred from the types of tests performed. The document states that "All product and engineering specifications were verified and validated" and that "All the above mentioned tests passed." This implies that the device successfully met the intended performance parameters for each test.

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

The document mentions "clinical data collected from the hospital setting" for the "Registration Accuracy for Clinical Data (bench test)." However, the sample size for this test set (number of cases/patients) is not specified. The data provenance is generally stated as "clinical data collected from the hospital setting," indicating it is likely retrospective clinical data used for a bench test.

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

The document does not specify the number of experts used or their qualifications for establishing the ground truth of the "clinical data" used in testing. It only mentions that the "offline software would be typically executed by Radiologists."

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for establishing ground truth on the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with AI assistance versus without AI assistance was not mentioned or described in the provided summary. The focus of the performance testing appears to be on the device's standalone accuracy and functionality.

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

Yes, a standalone performance evaluation of the algorithm (referred to as "the new MMIF software") was performed. The "Testing and Performance Data" section describes "bench testing" activities conducted "to ensure the performance of the new MMIF software by verifying the accuracy of the specifications and simulating real customer data collected from the hospital setting." The registration accuracy and volume measurements were assessed for the software itself.

7. The Type of Ground Truth Used

The ground truth for the bench tests involved:

• Simulated prostates in test phantoms: Used for "Phantom Volume Measurements" and "Phantom Registration Accuracy." This represents a controlled and precisely known ground truth.
• "Clinical data collected from the hospital setting": Used for "Registration Accuracy for Clinical Data." The method for establishing ground truth for this clinical data (e.g., expert consensus, pathology, surgical outcomes) is not explicitly stated.

8. The Sample Size for the Training Set

The document does not specify a training set size. The summary focuses on device verification and validation, implying that the device was perhaps developed or configured based on various data, but the specific characteristics of a "training set" (in the machine learning sense) are not outlined.

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

Since a training set is not explicitly mentioned, the method for establishing its ground truth is not provided. The device seems to be a software application for image processing and fusion, rather than a machine learning model that requires explicit training data in the context of this 510(k) summary. For software applications of this nature, ground truth is often implicitly established by the underlying physical principles of image registration algorithms and validated against physical models or existing clinical standards.

Ask a specific question about this device

The device is intended to provide physicians with tools for electromagnetic tracking of instruments with respect to image data.

Electromagnetic tracking tool kit works in conjunction with images gathered by OEM imaging devices to provide physicians with a tool for image registration and/or tracking of instruments. This is accomplished by utilizing attachment brackets, needle guides, adhesive skin markers or fiducial markers, needles and other housings that are specially configured to contain an electromagnetic sensor. The electromagnetic sensor in the tracked instrument is used within an EM field introduced by OEM equipment. The position and orientation can be thus detected and combined with the acquired imaging to assist with navigating a tracked instrument. The system also utilizes accessories in conjunction with the system to allow the users additional options for protecting the equipment from contamination, needle guidance, and image registration.

The provided text describes a 510(k) summary for an Electromagnetic Tracking System. However, it does not contain any information regarding specific acceptance criteria, a study that proves the device meets those criteria, or performance data.

The document primarily focuses on:

• Intended Use: Electromagnetic tracking of instruments with respect to image data.
• Device Description: EM sensor within tracked instruments, used with OEM imaging devices, and various accessories (EMT sensor covers, EMT slot guide, skin markers).
• Predicate Devices: A list of previously cleared devices to which the current device claims substantial equivalence.
• Substantial Equivalence Claim: Based on equivalent intended uses, manufacturing materials, operating principles, and physical/operational specifications compared to predicate devices, with the only noted difference being qualification with the GE Logiq E9 system.
• FDA Clearance Letter: Confirming the 510(k) clearance and regulatory details.
• Indications for Use: Reiterating the intended use.

Therefore, I cannot provide the requested table and study details as they are not present in the input text. The document states that "There are no significant differences between the proposed and predicate devices except that they have now been qualified with the GE Logiq E9 system," which implies that the substantial equivalence argument, rather than a new performance study against specific acceptance criteria, was the primary basis for clearance.

Ask a specific question about this device