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RTHawk is an accessory to 1.5T and 3.0T whole-body magnetic devices (MRDD or MR). It is intended to operate alongside, and in parallel with, the existing MR console to acquire traditional, real-time and accelerated images. The Heart Vista Cardiac Package is a collection of RTHawk Apps designed to acquire, reconstruct and display cardiovascular MR (CMR) images.

RTHawk produces static and dynamic transverse, coronal, sagittal, and oblique cross-sectional images that display the internal structures and/or functions of the entire body. The images produced reflect the spatial distribution of nuclei exhibiting magnetic resonance. The magnetic resonance properties that determine image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that may assist in the determination of a diagnosis.

RTHawk is intended for use as an accessory to the following MRI systems:

Manufacturer: GE Healthcare (GEHC) Field Strength: 1.5T and 3.0T Scanner Software Versions: 15, 16, 23, 24, 25

RTHawk is a software platform intended for the efficient real-time MRI data acquisition, data transfer, image reconstruction, and interactive scan control and display of static and dynamic MR imaging data.

As an accessory to clinical 1.5T and 3.0T MR systems, RTHawk operates alongside, and in parallel with, the MR scanner console with no permanent physical modifications to the MRI system required. RTHawk is designed to run on a stand-alone linux-based computer workstation, with color monitor, keyboard and mouse. A private ethernet network connects the workstation to the MR scanner computer. When not in use, the workstation may be disconnected from the MR scanner with no detrimental, residual impact upon MR scanner function, operation, or throughput.

RTHawk is a linux operating system-level software application that is intended to control the MR scanner, acquiring high quality, real-time MRI image data and performing post-processing. The RTHawk software includes optimized image acquisition applications, a pipelined raw data image reconstruction engine, a rich graphical user interface for interactive scan control, real-time adjustment of pulse sequence parameters, and display of reconstructed images, and drivers and protocols for communications with, and control of, the OEM MR scanner console.

RTHawk Apps (Applications) are comprised of a pulse sequence, predefined fixed and adjustable parameters, reconstruction pipeline(s), and a tailored graphical user interface containing image visualization and scan control tools. RTHawk Apps may provide real-time interactive scanning, conventional (fraditional) batch-mode scanning, accelerated scanning, or calibration functions, in which data acquired may be used to tune or optimize other Apps.

The HeartVista Cardiac Package is a collection of RTHawk APPs that enables the performance of a comprehensive cardiovascular MR (CMR) study in a clinically feasible amount of time. These APPs are designed and optimized to acquire, reconstruct, and display CMR images, with features including:

• On-the-fly, sub-second latency adjustment of image acquisition parameters (e.g., scan plane, flip angle, field-of-view, etc.)
• Real-time imaging, enabling less reliance on ECG gating and artifact suppression techniques. Real-time imaging may be used for scan plane localization, instantaneous tracking of patient motion, and clinical user observation of transient events
• High spatial resolution imaging, including single breath-hold, multi-slice high-resolution GRE app offering near total heart coverage
• Free-breathing, multi-slice SSFP and GRE apps that rapidly acquire high-quality images potentially useful for patients who suffer from arrhythmia or who cannot hold their breath
• Multi-slice dynamic SR GRE app with one heartbeat temporal resolution for time-course imaging.
• Continuous flow quantification

The conventional MRI concept of anatomy- and indication-specific Protocols is implemented within the HeartVista Cardiac Package. APPs within the HeartVista Cardiac Package are organized into basic Protocols pre-set by HeartVista. The clinical user may modify APP parameters from default values within their ranges. These modified APPs may be saved into new or existing user-created Protocols to create unique CMR-indicated protocols tailored to the user's clinical interests.

This document is a 510(k) summary for the HeartVista Cardiac Package (K153740), a software accessory for MRI systems. It primarily focuses on demonstrating substantial equivalence to a predicate device (RTHawk 1.0.1, K142997). The information provided is about the device's technical specifications and the testing performed to ensure its safety and effectiveness.

Here’s an attempt to extract and present the requested information, understanding that a 510(k) summary often does not contain detailed clinical study reports for acceptance criteria, but rather focuses on technical performance and equivalence.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative clinical acceptance criteria for diagnostic performance (e.g., sensitivity, specificity for a particular pathology). Instead, the performance evaluations are focused on technical aspects and subjective diagnostic utility by experts.

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

• Sample Size for Test Set: The document does not specify a numerical sample size for patients or cases used in the performance evaluation (e.g., for "clinical images were acquired using RTHawk").
• Data Provenance: Not explicitly stated regarding country of origin. The study appears to be retrospective in the sense that images were acquired and then evaluated, but it is not detailed if these were pre-existing patient scans or prospectively acquired for the purpose of the study. The phrasing "clinical images were acquired using RTHawk" might suggest prospective acquisition for evaluation, but further specifics are not available.

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

• Number of Experts: Not specified. The document states "radiologist expertise" (plural), indicating more than one.
• Qualifications of Experts: "Trained physician" and "radiologist expertise" are mentioned. No years of experience or specific subspecialty certifications are provided in this summary.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified. It only mentions evaluation by "radiologist expertise."

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

• No MRMC comparative effectiveness study is mentioned for evaluating human reader improvement with or without AI assistance. The device is a software platform intended to acquire, reconstruct, and display images, not explicitly an AI-driven diagnostic aid to human readers in the sense of often-seen AI studies comparing aided vs. unaided performance. The focus is on the diagnostic usefulness of the images produced by the device, not on AI-assisted interpretation.

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

• Yes, a standalone performance was done in the sense that the device itself (RTHawk producing images) was evaluated for its technical performance (SNR, uniformity) and for the diagnostic usefulness of the images it produced, before human interpretation for a diagnosis. The evaluation of image quality by radiologists ("diagnostically useful") represents a form of standalone assessment of the device's output.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• For the "clinical images were acquired using RTHawk, and were evaluated directly based upon radiologist expertise and found to be diagnostically useful," the ground truth can be inferred as expert opinion/consensus on image quality and diagnostic utility. There is no mention of pathology, long-term outcomes, or detailed clinical diagnostic ground truth used for comparison.

8. The Sample Size for the Training Set

• The document does not provide information about a "training set" sample size. Given this is a 510(k) summary for an MRI software platform primarily focused on image acquisition, reconstruction, and display, it's unlikely to feature a machine learning model with a distinct training set in the way a modern AI diagnostic device would. Its "training" would be more akin to software development and validation.

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

• As no specific training set for a machine learning model is mentioned, there is no information on how its ground truth would have been established. The development of the pulse sequences and reconstruction pipelines would rely on established MRI physics principles and engineering validation, rather than annotated training data in the context of typical AI/ML.

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