(12 days)
Quantitative Blood Pool SPECT (QBS) is a standalone software application for the display and analysis of gated short axis blood pool (red blood cells, RBC) SPECT datasets. The results provided by QBS should be reviewed by qualified healthcare professionals (e.g., radiologists, cardiologists, or general nuclear medicine physicians) trained in the use of medical imaging devices.
Ouantitative Blood Pool SPECT (OBS) is a standalone software application for the display and analysis of gated short axis blood pool (red blood cells, RBC) SPECT datasets. The results provided by QBS should be reviewed by qualified healthcare professionals (e.g., radiologists, cardiologists, or general nuclear medicine physicians) trained in the use of medical imaging devices. QBS provides the following functionality:
. Automatic generation of left and right ventricular endocardial surfaces and valve planes from three-dimensional (3D) gated short axis blood pool images.
. Automatic calculation of left and right ventricular volumes and ejection fractions.
Two-dimensional (2D) image display using standard American . College of Cardiology (ACC) cardiac SPECT conventions.
3D image display. Ability to combine isosurfaces extracted from the . data with the calculated endocardial surfaces in various ways (endocardial borders displayed as wireframes, shaded surfaces or both).
Ability to support manual identification of the left-ventricular (LV) . region, to separate it from the right ventricle (RV) in cases where the automatic algorithm fails or returns unsatisfactory results.
Ability to rotate, zoom and cine surfaces. ●
Calculation and display of polar maps representing wall motion. .
The provided text describes a 510(k) summary for the Quantitative Blood Pool SPECT (QBS) device. It asserts substantial equivalence to a predicate device but does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets them. The document focuses on regulatory compliance based on similarity to a previously cleared device rather than detailed performance reporting against pre-defined metrics.
Therefore, much of the requested information regarding acceptance criteria and performance data is not explicitly available in the provided text. Based on the document:
1. Table of Acceptance Criteria and Reported Device Performance:
The document does not explicitly list acceptance criteria or provide specific quantitative performance metrics for the QBS device. It primarily states that the QBS performs "in a similar manner" to the predicate device.
2. Sample Size Used for the Test Set and Data Provenance:
Not specified in the provided text. The document refers to "data display and analysis" but does not detail a test set or its characteristics.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:
Not specified in the provided text.
4. Adjudication Method:
Not specified in the provided text.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
Not mentioned in the provided text.
6. Standalone Performance Study:
A standalone study in the sense of demonstrating algorithm performance via concrete metrics is not explicitly reported. The device itself is described as a "standalone software application," but this refers to its operational independence, not a performance study methodology. The document establishes substantial equivalence by comparing the QBS device's functionality to the predicate device, stating they "have similar indications for use and overall function and perform in a similar manner with respect to data display and analysis."
7. Type of Ground Truth Used:
Not specified in the provided text for any performance evaluation. The document mentions that "The results provided by QBS should be reviewed by qualified healthcare professionals (e.g., radiologists, cardiologists, or general nuclear medicine physicians)," implying human review as the ultimate arbiter, but it doesn't detail how ground truth was established for testing the QBS software itself.
8. Sample Size for the Training Set:
Not specified in the provided text. This document focuses on a 510(k) submission, which often relies on demonstrating equivalence rather than providing detailed algorithm training and testing data.
9. How the Ground Truth for the Training Set Was Established:
Not specified in the provided text.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).