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The AcQMap System is intended for use in patients for whom electrophysiology procedures have been prescribed.

When used with the AcQMap Catheters, the AcQMap System is intended to be used to reconstruct the selected chamber from ultrasound data for purposes of visualizing the chamber anatomy and displaying electrical impulses as either charge density-based or voltage-based maps of complex arrhythmias that may be difficult to identify using conventional mapping systems alone.

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When used with the specified Patient Electrodes, the AcQMap System is intended to display the position of AcQMap Catheters and conventional electrophysiology (EP) catheters in the heart.

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When used with conventional electrophysiology catheters, the AcQMap System provides information about the electrical activity of the heart and about catheter location during the procedure.

The AcQMap High Resolution Imaging and Mapping System, Model 900100 operates outside of the sterile field and consists of the AcQMap Console, the AcQMap Workstation and the AcQMap Auxiliary Interface Box.

The AcQMap High Resolution Imaging and Mapping System, Model 900100 ("AcQMap System Model, 900100") is a diagnostic recording system. This computer-based system is intended for use in the Electrophysiology (EP) Lab, and it is capable of imaging, navigation and mapping of the atrial chambers of the heart.

The AcQMap System hardware consists of three functional subsystems:

• . Ultrasound imaging,
• . ECG and EGM recording; and
• o Impedance based electrode Localization.

The AcQMap System, Model 900100 is used in conjunction with the associated AcQMap 3D Imaging and Mapping Catheter (cleared under K170819). The AcQMap System provides:

• . 3-D cardiac chamber reconstruction - Contact and non-contact (ultrasound),
• . Three-dimensional position of the AcQMap Catheter and conventional electrophysiology catheters,
• o Cardiac electrical activity as waveform traces,
• . Contact LAT and voltage amplitude maps
• . Remapping of the chamber at any time during the procedure; and
• Dynamic, three-dimensional, charge density maps overlaid on the cardiac chamber reconstruction . to show chamber-wide electrical activation.

The AcQMap System, Model 900100 is intended to create a surface reconstruction of the cardiac chamber as well as an electrical map of the substrate. The surface reconstruction and electrical map are then used by physicians to identify the source(s) of the arrhythmia.

Additionally, the modified AcQMap System allows physicians to perform traditional contact mapping activities, including establishing a coordinate system, localizing conventional electrophysiology catheters relative to one another within the coording contact electrograms, and initiating a procedure without the AcQMap Catheter present. Based on the information captured in the contact electrograms, the physician may decide to treat an arrythmia without deploying the AcQMap Catheter.

The provided text is a 510(k) premarket notification for the AcQMap® High Resolution Imaging and Mapping System, Model 900100. It focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than presenting a detailed de novo clinical study with specific acceptance criteria and performance data for a new AI/ML algorithm.

Therefore, much of the requested information regarding acceptance criteria, multi-reader multi-case studies, and specific performance metrics of an AI model cannot be extracted directly from this document. This document primarily discusses the safety and effectiveness of a medical device (hardware/software system) for cardiac imaging and mapping, not an AI/ML algorithm requiring rigorous clinical validation for its own performance.

However, I can extract information related to the device's validation and the high-level assessment of its performance.

Here's what can be gathered, with limitations noted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not present specific quantitative acceptance criteria or performance metrics in a tabular format as would be expected for an AI/ML algorithm's clinical validation study (e.g., sensitivity, specificity, AUC). Instead, it states that "the collective results of the nonclinical testing... demonstrate that the proposed device does not raise different questions of safety or effectiveness when compared to the predicate device" and that the clinical study "demonstrated that the AcQMap System is safe and effective for its intended use."

The document focuses on "functional and performance characteristics" of the system as compared to its predicate, rather than an AI's accuracy against a ground truth.

2. Sample Size and Data Provenance for Test Set:

• Test Set Description: The document refers to the "necessary clinical testing" being completed for the original AcQMap System (K170948) and incorporated by reference. This implies that the current submission (K191392) did not involve a new, dedicated clinical "test set" for performance evaluation of a new algorithm, but rather relies on the prior clinical data for the predicate device.
• Sample Size: "The results for 84 patients demonstrated that the AcQMap System is safe and effective for its intended use."
• Data Provenance: The study was "a prospective, non-randomized, open-label study conducted at eight clinical sites outside the U.S." (indicating international, prospective data).

3. Number of Experts and Qualifications:

• The document does not specify the number or qualifications of experts used to establish ground truth. As this is a medical device for imaging and mapping, the "ground truth" would likely be derived from its direct measurements and comparisons against established methods, rather than expert consensus on image interpretation.

4. Adjudication Method for Test Set:

• Not specified. The document does not describe an adjudication method, which is typically relevant for studies involving human readers or subjective interpretations.

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

• Not explicitly mentioned or described. The document focuses on the device's inherent performance and its equivalence to a predicate, not on how human readers' performance might improve with or without AI assistance. This is consistent with a medical device submission focused on basic safety and effectiveness rather than a specific AI diagnostic algorithm.

6. Standalone (Algorithm Only) Performance:

• The AcQMap System is a hardware-software integrated device. The "performance data" describes the system's ability to perform its core functions (imaging, mapping, catheter localization). It is not a standalone AI algorithm that provides a diagnosis or measurement without human interaction with the device. Therefore, a "standalone algorithm only" performance study in the typical AI sense is not applicable or described. The performance tested refers to the entire system.

7. Type of Ground Truth Used:

• The nature of the "ground truth" is implied by the device's function: it's intended to reconstruct chamber anatomy and display electrical impulses. The "truth" would be the physiological parameters or anatomical structures it measures. The document states "Accuracy Testing" and "Accuracy Validation Testing Animal Study" were performed, suggesting comparison against known or benchmarked physical/physiological parameters.
• The clinical study was described as "Dipole Density Right (and left) Atrial Mapping and Assessment of Therapy In Complex Supraventricular Tachycardia, (DDRAMATIC-SVT)". This suggests the ground truth was related to the physiological electrical activity and anatomical representation of the heart, likely validated against established clinical methods or direct measurements during procedures. It is not stated to be expert consensus (e.g., on images), pathology results, or outcomes data directly, though outcomes (therapy assessment) would have been part of the clinical study.

8. Sample Size for Training Set:

• This is a 510(k) submission for a medical device (hardware/software system), not a de novo submission for a new AI/ML algorithm. Therefore, the concept of a "training set" for an AI model (as understood in machine learning) is not applicable in this document's context and is not described. The system itself has software, but the document refers to "Software Verification and Validation" (V&V), which is a standard engineering process for ensuring software meets specifications, not AI model training.

9. How Ground Truth for Training Set was Established:

• As the concept of an AI "training set" is not applicable, this information is not provided.

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