Search Results

This device indicated for use in dermatologic and general surgical procedures for electrocoagulation and hemostasis.

The DENSITY, DENZA, DENSITY Noir generates radiofrequency (RF) energy by means of high RF at 6.78MHz. The RF energy is delivered through the skin into the target tissue via a handpiece equipped with an electrode tip. As the RF energy passes through the tissue, it generates an electrothermal reaction which is capable of coagulating the tissue. In detail, the main body uses the "reverse thermal gradient" principle to deliver RF energy, and thus, heat is generated and selective coagulation occurs while cooling the epidermis, resulting in denaturation and contraction of collagen fibers.

The devices are an RF (radiofrequency), software-controlled electrosurgical device used for electrocoagulation of soft tissue and hemostasis.

It consists of the following components:

• Electrosurgical Unit - Main body
• Handpiece
• electrode tips
• Neutral electrode pad and neutral electrode pad cable, cleared under K201685
• Foot switch
• Power cord

This document is a 510(k) clearance letter for an electrosurgical device, not a study report for an AI device. As such, most of the requested information regarding AI device acceptance criteria, study details, and performance metrics (like effect sizes for AI assistance, standalone performance, training sets, etc.) is not present in the provided text.

The device described, "DENSITY; DENZA; DENSITY Noir," is an electrosurgical cutting and coagulation device. The clearance is based on substantial equivalence to a predicate device (K230663), implying that its performance is expected to be similar to legally marketed devices based on established standards and non-clinical testing.

Here's a breakdown of the information that can be extracted from the provided text, along with an explanation of why other requested information is not available:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state "acceptance criteria" for performance that would be found in a typical AI device study (e.g., sensitivity, specificity, AUC thresholds). Instead, the acceptance is based on demonstrating substantial equivalence to a predicate device through adherence to recognized standards and non-clinical performance testing.

Acceptance Criteria (Implied by Substantial Equivalence and Standards Adherence):

• IEC 60601-1:2005, IEC 60601-1:2005/AMD1:2012, IEC 60601-1:2005/AMD2:2020 (Basic safety and essential performance)
• IEC 60601-1-2:2014 (Electromagnetic disturbances)
• IEC 60601-2-2 (HF surgical equipment particular requirements)
• IEC 60601-1-6:2013 (Usability) |
  | Software | Software verified and validated to a moderate level of concern, adhering to software lifecycle processes. | Evaluated according to IEC 62304:2006. |
  | Usability/Human Factors | Application of usability engineering to medical devices. | Evaluated in accordance with IEC 62366:2008 based on Human Factor Engineering. |
  | Biocompatibility | Materials in contact with patients are biocompatible. | Documented in reference to ISO 10993-1:2009, ISO 10993-5:2009, and 10993-10:2010. |
  | Bench Testing Performance | Device operates safely and within predefined design specifications, demonstrating intended function for electrocoagulation and hemostasis. | Bench testing conducted to assure safe operation and adherence to design specifications. |
  | Ex Vivo Thermal Testing | Performance in tissue coagulation and hemostasis, particularly regarding thermal effects. | Ex Vivo testing conducted on three types of tissue under GLP Thermal testing in accordance with FDA guidance "Premarket Notification (510(k)) Submissions for Electrosurgical Devices for General Surgery". |
  | Risk Management | Risks identified, analyzed, and controlled. | Risk analysis conducted based on ISO 14971:2019. |
  | Substantial Equivalence | Device is as safe and effective as a legally marketed predicate device, with no new questions of safety or effectiveness raised by differences. | Compared to predicate device K230663. All key parameters (output energy type, user interface, operating frequency, max power, electrode tip types, temperature range, impedance, coolant solution, communication) were found to be substantially equivalent. Minor differences in electrode tip styles and number of tips were deemed not to affect performance or safety. |

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided as this letter describes non-clinical testing for an electrosurgical device, not a clinical study or AI performance evaluation. The "test set" here refers to the materials and conditions used for bench and ex-vivo testing. The document states:

• "Ex Vivo testing conducted on three types of tissue". No specific sample size (e.g., number of tissue samples) or provenance is mentioned beyond "under GLP Thermal testing."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable/not provided. Ground truth for an AI device is typically established by expert interpretation of medical images or data. For an electrosurgical device, performance is evaluated against engineering specifications, recognized safety standards, and physiological responses during ex-vivo testing, not by expert interpretation generating a "ground truth" in the same sense as an AI diagnostic.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not applicable/not provided. Adjudication methods are used in studies involving human interpretation or labeling, especially for AI algorithm ground truth establishment. This is not relevant for the type of non-clinical testing described.

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

This information is not applicable/not provided. An MRMC study is relevant for evaluating the impact of AI assistance on human performance, typically in diagnostic imaging. The device in question is a standalone electrosurgical instrument and does not involve AI assistance for human readers.

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

This information is not applicable/not provided. This device is a manual electrosurgical instrument, not an AI algorithm. Therefore, "standalone algorithm performance" is not relevant.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

For the non-clinical testing:

• Bench testing: Ground truth is defined by the device's technical specifications and engineering design (e.g., power output within tolerance, correct operating frequency).
• Ex Vivo testing: Ground truth would be the expected physiological effect (e.g., desired thermal coagulation) confirmed through histological examination or other scientific methods in the tissue samples. This is implied by "Ex Vivo testing conducted... under GLP Thermal testing."

8. The sample size for the training set

This information is not applicable/not provided. This device is an electrosurgical instrument, not an AI system that requires a "training set."

9. How the ground truth for the training set was established

This information is not applicable/not provided for the same reason as point 8.

Ask a specific question about this device

Saige-Density is a software application intended for use with compatible full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) systems. Saige-Density provides an ACR BI-RADS Atlas 5th Edition breast density category to aid interpreting physicians in the assessment of breast tissue composition. Saige-Density produces adjunctive information. It is not a diagnostic aid.

Saige-Density is Software as a Medical Device that processes screening and diagnostic digital mammograms using deep learning techniques and generates outputs that serve as an aid for interpreting radiologists in assessing breast density. The software takes as input a single x-ray mammogram study and processes all acceptable 2D image DICOM files (FFDM and/or 2D synthetics) and generates a single study-level breast density category. Two DICOM files are outputted as a result: 1) a structured report (SR) DICOM object containing the case-level breast density category and 2) a secondary capture (SC) DICOM object containing a summary report with the study-level density category. Both output files contain the same breast density category ranging from "A" through "D" following Breast Imaging Reporting and System (BI-RADS) 5th Edition reporting guidelines. The SC report and/or the SR file may be viewed on a mammography viewing workstation.

Here's a breakdown of the acceptance criteria and the study proving the device meets those criteria, based on the provided text:

Acceptance Criteria and Reported Device Performance

The provided text doesn't explicitly list a table of acceptance criteria with specific numerical targets. Instead, it states that the device was validated through a retrospective study (as described in a prior submission, K222275) and that "Verification and Validation testing conducted to support this submission confirm that Saige-Density is safe and effective for its intended use."

The key performance described is the ability to produce an ACR BI-RADS Atlas 5th Edition breast density category to aid interpreting physicians. The device outputs a study-level breast density category ranging from "A" through "D."

To infer the de facto acceptance criterion for performance, we must assume it aligns with demonstrating substantial equivalence to the predicate device (Saige-Density v2.0.0, K222275). This implies that the current version (v2.5.0) performs at least as well as, or equivalently to, the predicate in its ability to classify breast density according to the BI-RADS standard. While no specific performance metrics (like accuracy, sensitivity, specificity, or agreement rates) are stated in this document for this specific submission's validation, the statement of substantial equivalence implies that these metrics were deemed acceptable in the original K222275 submission.

Study Details:

The provided text primarily refers back to the validation performed for the predicate device (K222275) for its clinical performance data. The current submission focuses on verifying that minor technological changes in v2.5.0 do not impact safety or effectiveness.

1. A table of acceptance criteria and the reported device performance:
   As noted above, no explicit table of numerical acceptance criteria or performance metrics for this specific submission is provided. The acceptance hinges on demonstrating "safety and effectiveness for its intended use" and "substantial equivalence" to the predicate, which implies the previous validation (K222275) satisfied performance requirements.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):

   • Sample Size (Test Set): Not explicitly stated in this document. It refers to the validation study described in K222275.
   • Data Provenance: Retrospective study. Data was obtained from "different clinical sites than those used to develop the Saige-Density algorithm." Geographic locations for the training data included "various geographic locations within the US, including racially diverse regions such as New York City and Los Angeles." It's reasonable to infer the test set likely drew from similar diverse US populations to ensure generalizability.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):
   Not explicitly stated in this document. This information would typically be found in the K222275 submission details.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
   Not explicitly stated in this document. This information would typically be found in the K222275 submission details.

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:
   Not explicitly stated in this document. The device "provides an ACR BI-RADS Atlas 5th Edition breast density category to aid interpreting physicians," suggesting it's an adjunctive tool, but this document does not describe an MRMC study comparing human performance with and without the AI.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Yes, the device outputs "a single study-level breast density category" and DICOM files containing this category. The validation study references in K222275 would have assessed the algorithm's performance in categorizing density. The use of "retrospective study" suggests an assessment of the algorithm's output against a ground truth.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
   Not explicitly stated in this document. Given that the output is an "ACR BI-RADS Atlas 5th Edition breast density category," the ground truth was most likely established by expert radiologists (likely through consensus or a similar process using their interpretation of the mammograms). Pathology or outcomes data are less likely to directly establish BI-RADS density categories.

8. The sample size for the training set:
   Not explicitly stated in this document. It mentions the training data consisted of "four datasets across various geographic locations within the US."

9. How the ground truth for the training set was established:
   Not explicitly stated in this document. It is implied that the ground truth for training would also be established by similar expert interpretation of BI-RADS density categories. The text notes "DeepHealth ensured that there was no overlap between the data used to train and test the Saige-Density algorithm," indicating good practice in study design.

Ask a specific question about this device

Transpara Density is a software application intended for use with data from compatible digital breast tomosynthesis systems. Transpara Density utilises deep learning artificial intelligence algorithms to automatically determine volumetric breast density (VBD), breast volume, and an ACR BI-RADS 5th Edition breast density category to aid health care professionals in the assessment of breast tissue composition. It is not a diagnostic aid.

Transpara Density is a software module that uses artificial intelligence techniques to assess breast density in mammography (DM) and breast tomosynthesis (DBT) images and provide support to radiologists in this task. The novel methods of Transpara Density, extend the capabilities of computer aided detection systems for mammography by providing radiologists with decision support via the output of density assessment.

The Transpara Density outputs are:

• Density Grade, in accordance with categories defined in the ACR BI-RADS Atlas 5th Edition (A = almost entirely fat; B = scattered fibroglandular densities; C = heterogeneously dense; and D = extremely dense)
• Volumetric Breast Density in % .
• . Breast volume in cm3

Transpara Density is designed as an optional feature of Transpara. To operate in a clinical environment the software must be embedded in a software application that generates output in standardized formats (e.g. DICOM) and handles communication with external devices (such as PACS systems).

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly derived from the performance goals demonstrated in the clinical studies.

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

• Accuracy (Physics Model & MRI):
  • Physics Model Comparison: 5,468 exams.
  • MRI Comparison: 190 exams.
• Reproducibility (CC vs. MLO, Left vs. Right Breast, FFDM vs. DBT):
  • CC vs. MLO and Left vs. Right Breast: 10,804 exams.
  • FFDM vs. DBT: 433 exams (where images of both modalities were available).
• Agreement with Human Readers (Main Study): 800 women (400 DM and 400 DBT examinations).
• Data Provenance:
  • The test data originated from multiple clinical centers in the US, UK, Turkey, and five EU countries (Netherlands, Sweden, Germany, Spain, Belgium, Italy).
  • The data collection sites are described as "representative for regular breast cancer screening and diagnostic assessment in hospitals."
  • The studies were retrospective, using existing data. The human reader study implies a retrospective collection of images to be reviewed.

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

• Number of Experts: Eight (8) MQSA-qualified radiologists.
• Qualifications of Experts: "MQSA-qualified radiologists according to the ACR BI-RADS Atlas 5th Edition." (MQSA stands for Mammography Quality Standards Act, indicating they are qualified to interpret mammograms clinically in the US).

4. Adjudication Method for the Test Set

• Panel Majority Vote: For each exam, a panel majority vote of the eight radiologists was computed to serve as the reference standard.
• Tie Resolution: Ties in the panel majority vote were resolved by taking the majority vote of the three most experienced radiologists in the panel.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described as being done to assess human reader improvement with AI assistance. The study focused on the standalone performance of the Transpara Density device against human reader consensus, not how the AI assists human readers.

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

• Yes, extensive standalone performance testing was done. The entire "Summary of non-clinical performance data" section describes the device's performance in terms of accuracy, reproducibility, and agreement with human readers, all reflecting the algorithm's direct output. The conclusion explicitly states: "Standalone performance tests demonstrated that requirements were met."

7. The Type of Ground Truth Used

• Expert Consensus (Proxy for Ground Truth): For the agreement with human readers, the ground truth for the ACR BI-RADS 5th Edition breast density category was established by a panel majority vote of eight MQSA-qualified radiologists, with tie-breaking by the three most experienced.
• Physics-Based Model / MRI Measurements (Reference for Accuracy): For the volumetric breast density (VBD) and breast volume (BV) accuracy assessments, the ground truth was based on:
  • A validated physics-based model described in literature (van Engeland 2006).
  • Volumetric measurements from breast MRI studies in the same patients.

8. The Sample Size for the Training Set

• The document does not explicitly state the sample size for the training set. It only mentions that the "test data was not used for algorithm training and was not accessible to members of the research and development team."

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

• The document does not provide details on how the ground truth for the training set was established. It only indicates that the test data was separate from the training data.

Ask a specific question about this device

DENSITY indicated for use in dermatologic and general surgical procedures for electrocoagulation and hemostasis.

The DENSITY generates radiofrequency (RF) energy by means of high RF at 6.78MHz. The RF energy is delivered through the skin into the target tissue via a handpiece equipped with an electrode tip. As the RF energy passes through the tissue, it generates an electrothermal reaction which is capable of coagulating the tissue. In detail, the main body uses the "reverse thermal gradient" principle to deliver RF energy, and thus, heat is generated and selective coaqulation occurs while cooling the epidermis, resulting in denaturation and contraction of collagen fibers.

The DENSITY is an RF (radiofrequency), software-controlled electrosurgical device used for electrocoagulation of soft tissue and hemostasis.

The DENSITY consists of the following components:
•Electrosurgical Unit - Main body
•Handpiece
•6 different electrode tips
•Neutral electrode pad and neutral electrode pad cable, cleared under K201685
•Foot switch
•Power cord

This document is a 510(k) Premarket Notification for the medical device "DENSITY", an electrosurgical unit for dermatologic and general surgical procedures. It seeks substantial equivalence to a predicate device, the Thermage FLX System.

Based on the provided text, the device DENSITY is an electrosurgical cutting and coagulation device. The document does not describe an AI/ML medical device or provide information on acceptance criteria and studies related to AI/ML performance metrics such as accuracy, precision, recall, or human reader improvement with AI assistance. Instead, it focuses on demonstrating substantial equivalence based on technical characteristics and safety standards for an electrosurgical device.

Therefore, many of the requested items related to AI/ML device performance and testing (e.g., acceptance criteria for AI, sample sizes for AI test sets, expert ground truth, MRMC studies, standalone AI performance) are not applicable or cannot be extracted from this document.

However, I can extract the information pertinent to the device's substantial equivalence and non-clinical performance data.

Here's a breakdown of the available information:

1. A table of acceptance criteria and the reported device performance:

The document does not specify "acceptance criteria" in terms of performance metrics like sensitivity or specificity for a diagnostic/AI device. Instead, "acceptance" appears to be based on demonstrating substantial equivalence to a predicate device through conformity to recognized standards and comparable technical specifications.

Here's a table summarizing the comparison with the predicate device (Thermage FLX System K170758), which serves as the basis for demonstrating equivalence in performance and safety for this type of device:

• I-Tip II(Around eye), F-Tip II(Face): 2ea
• B-Tip(Body), B-Tip(Body)II: 4ea | - EYE Tip 0.25: 1ea
• TOTAL Tip 3.0: 1ea
• NEW TOTAL TIP 4.0: 1ea
• BODY TIP 16.0: 4ea |
  | Coolant Control Parameters | Type of gas: 1234ze; Method of gas control: Handpiece solenoid control operation; Mouth valve specifications: 12V; Solenoid valve specifications: 1.8V 24.8 BAR | Type of gas: 1234ze; Method of gas control: Handpiece solenoid control operation; Mouth valve specifications: 12V; Solenoid valve specifications: 1.8V 24.8 BAR |

Key takeaway on performance: The document states: "There are no significant differences between DENSITY and the predicate devices (K170758) that would adversely affect the use of the product. It is substantially equivalent to this device in design, function, and technical characteristics." "Any minor differences in the human interface and accessories design do not raise any new types of safety and effectiveness issues, as verified by performance testing."

2. Sample sizes used for the test set and the data provenance:

• Test Set Sample Size: "No clinical performance testing was performed." The evaluation relies on non-clinical performance data and comparison to the predicate device's established safety and effectiveness.
• Data Provenance: Not applicable as no clinical test set data was used.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable as no clinical test set requiring expert ground truth was performed for this 510(k) submission.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not applicable as no clinical test set requiring adjudication was performed.

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:

• Not applicable. This is not an AI/ML device, and no MRMC study was conducted.

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

• Not applicable. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Not applicable as no clinical ground truth was established for this submission. The "ground truth" for demonstrating substantial equivalence is based on established technical standards and the performance of the predicate device.

8. The sample size for the training set:

• Not applicable as this is not an AI/ML device.

9. How the ground truth for the training set was established:

• Not applicable as this is not an AI/ML device.

Summary of Device Acceptance (for this traditional medical device):

The acceptance of the DENSITY device for marketing is based on demonstrating substantial equivalence to an already legally marketed predicate device (Thermage FLX System K170758). This is achieved through:

• Non-clinical performance data:
  • Evaluation against recognized consensus standards for electrical medical equipment such as IEC 60601-1 (basic safety and essential performance), IEC 60601-1-2 (electromagnetic disturbances), IEC 60601-2-2 (high frequency surgical equipment), IEC 60601-1-6 (usability).
  • Software verification and validation in accordance withIEC 62304 (moderate level of concern) and IEC 62366 (usability engineering/Human Factor Engineering).
  • Biocompatibility testing documented according to ISO 10993 standards.
  • Risk analysis conducted based on ISO 14971.
• Comparison of technical characteristics: As detailed in the table above, demonstrating analogous specifications (e.g., operating frequency, max power, temperature range, impedance, coolant type) to the predicate device.

The document explicitly states: "No clinical performance testing was performed." This means the device's safety and effectiveness for its intended use were demonstrated through the non-clinical testing and the comparison to a legally marketed predicate, rather than through clinical trials with human subjects.

Ask a specific question about this device

PENTARAY® NAV ECO High Density Mapping Catheter:
The PENTARAY® NAV ECO High Density Mapping Catheter is indicated for multiple electrophysiological mapping of cardiac structures in the heart, i.e., recording or stimulation only. This catheter is intended to obtain electrograms in the atrial and ventricular regions of the heart. The PENTARAY® NAV ECO High Density Mapping Catheter provides location information when used with compatible CARTO®3 EP Navigation Systems. (This catheter is not compatible with CARTO® 3 EP Navigation Systems prior to version 3.x).

DECANAV® Mapping Catheter:
The DECANAV® Catheter is indicated for electrophysiological mapping of cardiac structures i.e., recording and stimulation, including in the coronary sinus. In addition, the catheter is used with compatible CARTO® 3 System to provide catheter tip location information.

Webster® CS Catheter with Auto ID, Webster® CS Catheter with EZ Steer Technology, Webster® CS Catheter with EZ Steer Technology and Auto ID:
The Webster® CS Catheter is indicated for electrophysiological mapping of cardiac structures i.e., stimulation and recording only. The catheter is designed for use in the coronary sinus.

PENTARAY® NAV eco High Density Mapping Catheter:
The PENTARAY® NAV eco High Density Mapping Catheter is a multi-electrode diagnostic catheter designed to facilitate electrophysiological mapping of all structures in the heart (recording and stimulation). The catheter's distal end is a flower-shaped probe with 5 spines that radiate from the center. Each spine has 4 ring electrodes that are used for stimulation and recording within the heart. The flower is available in a 30mm diameter and several ring spacing configurations to achieve optimal mapping and contact with various cardiac structures.

DECANAV® Mapping Catheter:
The DECANAV® Catheter has been designed to be used with the CARTO® 3 Navigation System (a magnetic field location technology) to facilitate electrophysiological mapping of the heart. The catheter has a high-torque shaft with a deflectable tip section containing an array of platinum/iridium electrodes that can be used for stimulation and recording of cardiac electrical signals.

The DECANAV® Catheter has a single proximal electrode that can be used for unipolar recording signals. The DECANAV® Catheter tip deflection is controlled by a proximal hand piece that features a thumb operated sliding piston and is offered in various curve types. The plane of the curved tip can be rotated during use.

The DECANAV® Catheter interfaces with standard recording equipment and CARTO® 3 EP Navigation System equipment via interface cables with the appropriate connectors.

Webster® CS Catheter with Auto ID:
The Webster® Coronary Sinus Catheter is a steerable, multi-electrode catheter with a deflectable tip designed to facilitate electrophysiological mapping of the heart. The device is a 6 FR catheter with a usable length of 115 cm. The catheter has a high-torque shaft with a deflectable tip selection containing an array of platinum electrodes that can be used for stimulation and recording.

Standard features of this catheter include a braided 6 FR deflectable tip section with an array of platinum electrodes that includes a 2 mm tip dome. The braided tip is controlled by a proximal hand piece that features a thumb operated sliding piston, and is offered in a various curve types. The high-torque shaft allows the plane of the curved tip to be rotated to facilitate accurate position of the catheter tip at the desired site.

The catheter is equipped with Electronically Erasable Programmable Read Only Memory (EEPROM) which is used to store unique catheter identification information. CARTO® EP Navigation Systems equipped with Auto ID Technology can access the stored information and automatically recognize the catheter information.

The catheter interfaces with CARTO® EP Navigation Systems equipped with Auto ID Technology via interface cables with the appropriate connectors.

Webster® CS Catheter with EZ Steer Technology:
The Webster® CS Catheters with EZ Steer Bi-directional Technology (D-1263-04-S and D-1263-05-S) are diagnostic. 7F, deflectable, mapping electrophysiology (EP) catheters with the ability to map electrical activity within the Coronary Sinus through distal Platinum/Iridium electrodes located along the catheter's pre-shaped tip. The catheters incorporate a 2 mm tip electrode, 10 total electrodes, 2-8-2 mm electrode spacing, have bi-directional deflection and are 115 cm long. These catheters include a braided bi-directional deflectable tip section. The braided bi-directional tip provides the user with two 180° opposed single plane curves. Currently, the available curves include FJ (D-1263-04-S) and DF (D-1263-05-S). These catheters include a handle with a Rocker Lever, which is used to deflect the tip. The high-torque shaft allows the plane of the curved tip to be rotated to facilitate accurate positioning of the catheter tip at the desired site. The following cables are used to provide a means for interface of the catheters with the appropriate equipment:

• D-1221-21
• D-1221-26
• D-1221-25

Webster® CS Catheter with EZ Steer Technology and Auto ID:
The Webster CS Catheters with EZ Steer Bi-directional Technology (D-1263-06-S and D-1263-07-S) are diagnostic, 7Fr, deflectable, mapping electrophysiology (EP) catheters with the ability to map electrical activity within the Coronary Sinus through distal Platinum/Iridium electrodes located along the catheter's pre-shaped tip. The catheters incorporate a 2 mm tip electrode, 10 total electrodes, 2-8-2 mm electrode spacing, have bidirectional deflection and are 115 cm long. These catheters include a braided bi-directional deflectable tip section. The braided bi-directional tip provides the user with two 180° opposed single plane curves. Currently, the available curves include FJ (D-1263-06-S) and DF (D-1263-07-S). These catheters include a handle with a Rocker Lever which is used to deflect the tip. The high-torque shaft allows the plane of the curved tip to be rotated to facilitate accurate positioning of the catheter tip at the desired site. The Webster CS Catheters with EZ Steer Bi-directional Technology and Auto ID (D-1263-06-S & D-1263-07-S) are equipped with Electronically Erasable Programable Read Only Memory (EEPROM) which is used to store unique catheter identification information. CARTO 3 EP Navigation Systems equipped with Auto ID Technology can access the stored information and automatically recognize the catheter information. The catheters interface with CARTO 3 EP Navigation Systems via an interface cable (D-1286-16) with the appropriate connectors.

Here's a breakdown of the acceptance criteria and study findings based on the provided text.

The provided text describes modifications to existing electrophysiology mapping catheters, primarily concerning a change to the instructions for use to allow direct imaging guidance (fluoroscopy or ultrasound) during catheter manipulation.

The submission does not describe an AI/ML-driven device or study. Instead, it focuses on demonstrating the substantial equivalence of modified catheters to their predicate devices, with the main change being the allowed use of direct imaging guidance. Therefore, many of the requested categories related to AI/ML performance, such as test set size, expert ground truth, adjudication methods, MRMC studies, standalone performance, and training set details, are not applicable to this submission.

Acceptance Criteria and Reported Device Performance

Given the nature of the submission (modifications to existing medical devices to allow for direct imaging guidance during use), the "acceptance criteria" are based on demonstrating that these modifications do not adversely affect the safety and effectiveness of the devices, and that they remain substantially equivalent to their predicates. The primary evidence presented is a clinical study focused on the safety and effectiveness of the updated workflow (zero/low fluoroscopy) rather than the inherent performance of an AI component.

As this submission is for modifications to existing non-AI/ML devices, the following inquiries are largely not applicable:

2. Sample size used for the test set and the data provenance: The document mentions a "Real-World Evidence study (REAL AF Registry Sub-Study)" but does not specify a distinct "test set" in the context of algorithm evaluation. It describes a clinical study population.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The clinical study evaluated procedural outcomes and safety, not an algorithm's performance against expert ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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: Not applicable, as this is not an AI-assisted device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is not an AI/ML algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" equivalent would be the clinical outcomes and safety endpoints observed in the "Real-World Evidence study (REAL AF Registry Sub-Study)."
8. The sample size for the training set: Not applicable, as this is not an AI/ML algorithm.
9. How the ground truth for the training set was established: Not applicable, as this is not an AI/ML algorithm.

Ask a specific question about this device

Saige-Density is a software application intended for use with compatible full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) systems. Saige-Density provides an ACR BI-RADS Atlas 5th Edition breast density category to aid interpreting physicians in the assessment of breast tissue composition. Saige-Density produces adjunctive information. It is not a diagnostic aid.

Saige-Density is Software as a Medical Device that processes screening and diagnostic digital mammograms using deep learning techniques and generates outputs that serve as an aid for interpreting radiologists in assessing breast density. The software takes as input a single x-ray mammogram study and processes all acceptable 2D image DICOM files (FFDM and/or 2D synthetics) and generates a single study-level breast density category. Two DICOM files are outputted as a result: 1) a structured report (SR) DICOM object containing the case-level breast density category and 2) a secondary capture (SC) DICOM object containing a summary report with the study-level density category. Both output files contain the same breast density category ranging from "A" through "D" following Breast Imaging Reporting and Data System (BI-RADS) 5th Edition reporting guidelines. The SC report and/or the SR file may be viewed on a mammography viewing workstation.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the reported performance metrics of the Saige-Density device. The primary objective of the standalone performance testing was to quantify the accuracy of Saige-Density's density category outputs. The reported performance is the accuracy of the device in classifying breast density into four categories (A, B, C, or D) and two categories (nondense: A, B; dense: C, D) compared to a consensus ground truth.

• Nondense correctly classified: 87.8%
• Dense correctly classified: 95.2% |

Study Details

1. Sample size used for the test set and the data provenance:

   • Sample Size: A total of 796 mammogram cases (representing 6,170 images) were retrospectively collected for the standalone performance testing.
   • Data Provenance: The data was collected from five breast imaging centers in the United States. The collection sites selected for the pivotal study did not overlap with those used previously to collect data for training or testing the Saige-Density AI algorithm.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: Five expert radiologists were used to establish the ground truth.
   • Qualifications of Experts: The text refers to them as "expert radiologists," implying they are qualified to interpret mammograms, but specific details about their experience (e.g., years of experience) are not provided.

3. Adjudication method for the test set:

   • Adjudication Method: Ground truth for each case was established as the consensus of the five expert radiologists' breast density categories on the same set of cases, and calculated as the median of the reported categories for each case. This suggests a form of consensus-based adjudication, specifically using the median.

4. 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:

   • The provided text does not indicate that an MRMC comparative effectiveness study was conducted to evaluate human readers' improvement with AI assistance. The performance testing described is "Standalone Performance Testing," focusing on the algorithm's performance only.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Yes, a standalone performance study was explicitly conducted and detailed: "Standalone Performance Testing: A multi-site retrospective study was conducted to evaluate the standalone performance of Saige-Density on DBT and FFDM mammograms."

6. The type of ground truth used:

   • The type of ground truth used was expert consensus of five expert radiologists, based on ACR BI-RADS 5th Edition guidelines.

7. The sample size for the training set:

   • The exact sample size for the training set is not explicitly stated. However, the text mentions that the training data consisted of "four datasets across various geographic locations within the US."

8. How the ground truth for the training set was established:

   • The text does not explicitly describe how the ground truth for the training set was established. It only states that the data used for training the algorithm was distinct from the test set and came from "four datasets across various geographic locations within the US, including racially diverse regions such as New York City and Los Angeles."

Ask a specific question about this device

PowerLook Density Assessment is a software application intended for use with digital breast tomosynthesized 2D images from tomosynthesis exams. PowerLook Density Assessment provides an ACR BI-RADS Atlas 5th Edition breast density category to aid health care professionals in the assessment of breast tissue composition. PowerLook Density Assessment produces adjunctive information. It is not a diagnostic aid.

PowerLook Density Assessment 4.0 is a software application intended for use with mammography exams containing synthetic 2D images generated from Digital Breast Tomosynthesis (DBT) data. The PowerLook Density Assessment software assesses breast tissue composition and provides a breast density category aligned with BI-RADS® 5th Edition density lexicon. The PowerLook Density Assessment 4.0 algorithm is designed to be used with cases containing up to four synthetic 2D views. When exams contain only DBT and synthetic 2D images generated from DBT, the 4.0 algorithm is used. The PowerLook Density Assessment software is designed to work in conjunction with iCAD's PowerLook DICOM server platform, which is a Class I exempt medical device. The PowerLook Density Assessment 4.0 utilizes data management capabilities of PowerLook for controlling input to and output from the PowerLook Density Assessment algorithm. Results of the PowerLook Density Assessment software application can be displayed on a mammography review workstation, mammography reporting application or radiology information system (RIS), or printed case report.

Here's an analysis of the provided text to extract the acceptance criteria and study details for the PowerLook Density Assessment V4.0.

1. Table of Acceptance Criteria and Reported Device Performance

The FDA submission for PowerLook Density Assessment V4.0 (K211506) does not explicitly state numerical acceptance criteria in terms of metrics like accuracy, sensitivity, or specificity. Instead, it refers to a qualitative acceptance criteria: "The performance of the system on all three datasets were above the desired performance, demonstrating that PowerLook Density Assessment 4.0 accurately calculates the BI-RADS breast density category for Hologic C-View and GE V-Preview data."

However, based on the nature of breast density assessment devices, the implicit acceptance criteria would typically involve a high level of agreement between the device's output and expert-determined ground truth, particularly concerning the assignment of ACR BI-RADS breast density categories. While specific percentages are not provided, the claim of "accurately calculates" suggests that substantial agreement was achieved.

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

• Sample Size for Test Set: The document does not specify the exact number of cases (images/patients) used in the test set. It mentions "Hologic C-View, GE V-Preview V3 and GE V-Preview V4.1 cases were run through Density Assessment 4.0."
• Data Provenance: The document does not explicitly state the country of origin of the data or whether it was retrospective or prospective.

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

The document does not specify the number of experts used or their qualifications (e.g., years of experience as a radiologist) for establishing the ground truth for the test set. It implicitly refers to "BI-RADS® 5th Edition density lexicon," suggesting that expert radiologists were involved in the ground truth labeling process, as this lexicon is used by radiologists.

4. Adjudication Method for the Test Set

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

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

No multi-reader multi-case (MRMC) comparative effectiveness study is mentioned in the provided text, nor is an effect size for human readers improving with AI assistance. The device is intended to provide "adjunctive information" to aid healthcare professionals, rather than directly assisting in a diagnostic reading task where reader performance would be measured.

6. Standalone Performance

Yes, a standalone performance study was done. The document states: "The performance of the system on all three datasets were above the desired performance, demonstrating that PowerLook Density Assessment 4.0 accurately calculates the BI-RADS breast density category for Hologic C-View and GE V-Preview data." This indicates that the algorithm's performance was evaluated independently in calculating the breast density categories.

7. Type of Ground Truth Used

The ground truth used is based on the ACR BI-RADS Atlas 5th Edition breast density category. This strongly implies expert consensus or expert-assigned categories, as radiologists are trained to use this lexicon.

8. Sample Size for the Training Set

The document does not provide information on the sample size used for the training set. It primarily focuses on the validation of the device.

9. How Ground Truth for the Training Set Was Established

The document does not explicitly state how the ground truth for the training set was established. However, given the device's function and the ground truth used for validation (BI-RADS 5th Edition), it is highly probable that the training data's ground truth was also established by expert radiologists adhering to the same BI-RADS lexicon.

Ask a specific question about this device

The Reprocessed PENTARAY® NAV eco High-Density Mapping Catheter is indicated for multiple electrode electrophysiological mapping of cardiac structures in the heart, i.e., recording or stimulation only. This catheter is intended to obtain electrograms in the atrial and ventricular regions of the heart. The Reprocessed PENTARAY® NAV eco High-Density Mapping Catheter provides location information when used with compatible CARTO™ 3 EP Navigation Systems. This catheter is not compatible with CARTO™ 3 EP Navigation Systems prior to Version 3.x.

The Reprocessed PENTARAY® NAV eco High-Density Mapping Catheter is designed to facilitate electrophysiological mapping of the heart with the CARTO® 3 EP Navigation System. It is designed for deployment in a heart chamber through an 8 Fr guiding sheath. This deflectable catheter consists of multiple 3 Fr spines on the distal tip, each spine having multiple platinum electrodes that are used for stimulation and recording. A magnetic location sensor embedded in the deflectable tip transmits location information to the CARTO® 3 EP Navigation System. The catheter has two electrodes on the deflectable tip to provide for visualization of the tip when used with the CARTO® 3 EP Navigation System. Pushing forward on the catheter thumb knob deflects the tip; pulling back on the thumb knob straightens the tip. This catheter includes an irrigation lumen for connection to a source of continuous drip anticoagulant fluid.

The provided text describes the 510(k) summary for the Reprocessed PENTARAY® NAV eco High-Density Mapping Catheter. This document outlines the device's characteristics and the non-clinical tests performed to demonstrate its substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for this medical device are implicitly derived from demonstrating substantial equivalence to the predicate device, the original PENTARAY® NAV eco High-Density Mapping Catheter (Biosense Webster K123837). The tests performed cover various functional, safety, and manufacturing aspects to ensure the reprocessed device performs as intended and is safe for use.

Ask a specific question about this device

Visage Breast Density is a software application intended for use with compatible full field digital mammography and digital breast tomosynthesis systems. Visage Breast Density assesses breast density from a mammography study and provides an ACR BI-RADS Atlas 5th Edition breast density category to aid radiologists in the assessment of breast tissue composition. Visage Breast Density produces adjunctive information. It is not a diagnostic aid.

Visage Breast Density is a software application that assesses breast density from a mammography study and provides a density category A, B, C, or D according to the ACR BI-RADS Atlas 5th Edition to aid radiologists in the assessment of breast tissue composition.

Visage Breast Density employs a convolutional network (CNN) for the automatic classification of breast density. The CNN has been trained on a large database of mammography exams. When applied to a mammography image, the CNN computes four likelihoods corresponding to the four breast density categories. The classifications of the individual images are merged into a general classification of the mammography study.

Visage Breast Density is designed as an add-on module to the Visage 7 product for distributing, viewing, processing, and archiving medical images. The assessment of breast density is performed from mammography studies stored on the Visage 7 server. The resulting breast density classification is displayed by the Visage 7 client on a computer monitor and stored in the database on the Visage 7 server.

Here's a breakdown of the acceptance criteria and study proving device efficacy for Visage Breast Density, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that the acceptance criteria were defined by comparing the performance of Visage Breast Density to that of the predicate device, PowerLook Density Assessment. Specifically, the acceptance criteria are implicit in the statement: "Visage Breast Density achieved similar accuracies per category and similar total accuracies compared to the predicate device."

While explicit numerical acceptance criteria (e.g., "accuracy must be >= X%") are not provided, the "reported device performance" is the claim of "similar accuracies per category and similar total accuracies compared to the predicate device."

Therefore, the table would look like this:

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

• Sample Size:
  • Test Set 1: 500 studies
  • Test Set 2: 700 studies
  • Total Test Set Size: 1200 studies
• Data Provenance: "two different sites." The country of origin is not explicitly stated, but given the company's German location (Visage Imaging GmbH, Berlin, Germany), it's plausible the data is from Europe, potentially Germany. The document does not specify if the data was retrospective or prospective, but it's common for such studies to use retrospective data.

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

• Number of Experts: Three board-certified radiologists per site were used to establish the consensus ground truth. Since there were two sites, it implies a total of 6 unique radiologists (3 per site).
• Qualifications: "Three board certified radiologists with MQSA qualification per site." MQSA (Mammography Quality Standards Act) qualification is a US standard, which might suggest US sites or radiologists with equivalent qualifications.

4. Adjudication Method for the Test Set

The adjudication method was consensus. "the consensus of the three reviewers was determined for each study." This implies that the three radiologists reviewed each case, and their agreement (or a process to resolve disagreement) led to the final ground truth label. A common consensus method is a majority vote (e.g., 2 out of 3 agree).

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, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted to assess how human readers improve with AI assistance. The study focuses on the standalone performance of the AI by comparing its output to a human-established ground truth. The device is described as providing "adjunctive information," not as a diagnostic aid that would directly assist human reader performance.

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

Yes, a standalone performance evaluation of the algorithm was done. The study assessed "The predicted breast density category of Visage Breast Density... related to the ground truth from the clinical reports and the consensus of the three reviewers." This directly measures the algorithm's performance independent of human input during the assessment process itself.

7. The Type of Ground Truth Used

The ground truth used was a combination of:

• Expert Consensus: "consensus of the three reviewers" (radiologists).
• Clinical Reports: "ground truth from the clinical reports."

This suggests the radiologists reviewed the clinical reports and then formed a consensus, or perhaps the clinical reports served as an initial "gold standard" which was then validated/adjudicated by the expert radiologists.

8. The Sample Size for the Training Set

The sample size for the training set is not explicitly stated. The document only mentions: "The CNN has been trained on a large database of mammography exams."

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

The document does not explicitly describe how the ground truth for the training set was established. It only states that the CNN was "trained on a large database of mammography exams." Typically, for such training, the ground truth would also be established by expert radiologists, likely with similar methods as the test set (consensus or single expert review).

Ask a specific question about this device

EnSite™ X EP System: The EnSite™ X EP System is a suggested diagnostic tool in patients for whom electrophysiology studies have been indicated. The EnSite™ X EP System provides information about the electrical activity of the heart and displays catheter location during conventional electrophysiological (EP) procedures.

EnSite™ X EP System Contact Force Software License: When used with the TactiSys™ Quartz Equipment, the EnSite™ X EP System Contact Force Module is intended to provide visualization of force information from compatible catheters.

EnSite™ X EP System Surface Electrode Kit: The EnSite™ X EP Surface Electrode Kit is indicated for use with the EnSite™ in accordance with the EnSite™ X EP System indications for use.

Advisor™ VL Circular Mapping Catheter, Sensor Enabled™: Advisor™ VL Circular Mapping Catheter, Sensor Enabled™ is a steerable electrophysiology catheter with integrated sensors. The catheter is used for recording intracardiac stimulation during diagnostic electrophysiology studies. The cather can be used to map the atrial regions of the heart.

Advisor™ FL Circular Mapping Catheter, Sensor Enabled™: The Advisor™ FL Circular Mapping Catheter, Sensor Enabled™ is steerable electrophysiology catheter with integrated sensors. The catheter is used for recording intracardiac stimulation during diagnostic electrophysiology studies. The catheter can be used to map the atrial regions of the heart.

Advisor™ HD High Density Mapping Catheter, Sensor Enabled™: The Advisor™ HD Grid Mapping Catheter, Sensor Enabled™, is indicated for multiple electrophysiological mapping of cardiac structures in the heart, i.e., recording or stimulation only. This catheter is intended to obtain electricular regions of the heart.

The EnSite™ X EP System is a catheter navigation and mapping system. A catheter navigation and mapping system is capable of displaying the 3-dimensional (3-D) position of conventional and Sensor Enabled™ (SE) electrophysiology catheters, as well as displaying cardiac electrical activity as waveform traces and as three-dimensional (3D) isopotential and isochronal maps of the cardiac chamber.

The contoured surfaces of the 3D maps are based on the anatomy of the patient's own cardiac chamber. The system creates a model by collecting and labeling the anatomic locations within the chamber. A surface is created by moving a selected catheter to locations within a cardiac structure. As the catheter moves, points are collected at and between all electrodes on the catheter. A surface is wrapped around the outermost points.

Advisor™ VL Circular Mapping Catheter, Sensor Enabled™ (Advisor VL) is a variable radius, circular mapping catheter. It has an adjustable 4 French (F) distal loop size with a diameter ranging from 15mm - 25mm with models containing both ten (10) equidistant or twenty (20) paired platinum-iridium electrodes. The catheter has integrated sensors with two impedance-based navigational electrodes and two magnetic sensors located at the distal end of the shaft. The catheter is intended to be used with the EnSite Precision™ Cardiac Mapping System, or the EnSite™ X EP System.

Advisor™ FL Circular Mapping Catheter, Sensor Enabled™ (Advisor FL, SE) is a circular mapping catheter for performing electrophysiology mapping procedures and providing pacing signals to the heart during electrophysiology procedures. The catheter handle and shaft design allows for improved maneuverability. A magnetic sensor in the distal shaft pocket provides compatibility with visualization and navigation systems. The catheter is compatible with Abbott's EnSite Precision™ Cardiac Mapping System, MediGuide™ System, or EnSite™ X EP System.

The Advisor™ HD Grid Mapping Catheter, Sensor Enabled™, is a sterile, single use, irrigated, high-density mapping catheter with a 7.5F shaft and an 8F distal shaft deflectable section. It is available in a D-F bi-directional curve model that is deflected using the actuator located on the catheter handle. The catheter working length is 110 cm. The device consists of a paddle-shaped distal tip with 16 electrodes, two distal shaft ring electrodes, two magnetic sensors, polymer braided shaft, handle, fluid lumen extension with a luer, and an electrical connector. The catheter also has an introducer tool intended to compress and guide the distal paddle into, and withdraw from, the hemostasis valve of an introducer sheath. The catheter is compatible with the EnSite™ Velocity, EnSite Precision™, and EnSite™ X EP Cardiac Mapping Systems and other accessories, including the connecting cable and commercially available irrigation pumps.

The provided FDA 510(k) summary (K202066) focuses on the substantial equivalence of the EnSite X EP System and associated catheters to previously cleared predicate devices. It largely relies on the similar intended use, indications for use, fundamental scientific technology, and performance of the subject devices compared to the predicate devices. The primary change described is compatibility with the EnSite™ X EP System and updated labeling.

However, the document does not contain specific acceptance criteria, reported device performance metrics, or details of a study structured to prove the device meets pre-defined acceptance criteria in the manner that would be expected for a novel AI/ML diagnostic device with a specific performance claim (e.g., sensitivity, specificity for a disease).

Instead, the non-clinical testing summary focuses on design verification activities, compliance with industry standards, and in vivo preclinical studies to evaluate substantial equivalence, and human factors evaluations. This suggests that the "acceptance criteria" here are more about demonstrating that the new system and its components function as intended and do not raise new questions of safety or effectiveness compared to the predicate(s).

Given this context, I will extract the information available and note where specific details regarding AI/ML performance studies or traditional clinical performance metrics are not present, as they do not appear to be the primary focus of this 510(k).

Acceptance Criteria and Study for K202066

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, this 510(k) does not present performance in terms of specific diagnostic metrics (e.g., sensitivity, specificity, accuracy) with numerical acceptance criteria. Instead, the "acceptance criteria" are implied by successful completion of design verification activities, adherence to standards, and performance in preclinical studies demonstrating substantial equivalence to predicate devices. The reported device performance generally refers to its ability to function as intended and similar to predicate devices.

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

The document mentions "In vivo Preclinical Studies" for the EnSite™ X EP System and Sensor Enabled™ Catheters. However, it does not specify the sample size (e.g., number of patients, cases, or animal subjects) used for these studies, nor does it explicitly state the country of origin or whether the data was retrospective or prospective. The term "preclinical" typically refers to animal studies rather than human clinical data.

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

The document does not specify the use of experts to establish ground truth for a test set in the context of diagnostic interpretation. The studies described are more focused on the functional performance and substantial equivalence of the hardware and software components rather than a diagnostic accuracy study requiring expert human interpretation as ground truth.

4. Adjudication Method for the Test Set

Since the document does not describe a diagnostic study requiring expert interpretation or ground truth establishment in a clinical sense, there is no mention of an adjudication method (e.g., 2+1, 3+1).

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

The document does not indicate that an MRMC comparative effectiveness study was done. The focus is on demonstrating that the device itself performs comparably to predicate devices, which may include functional performance in in-vivo settings, but not a study of human readers' performance with and without AI assistance for improving diagnostic outcomes.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

While the EnSite™ X EP System performs functions involving data processing ("programmable diagnostic computer"), the K202066 submission does not present it as a standalone AI/ML diagnostic algorithm with specific performance metrics (e.g., sensitivity, specificity) proven in a standalone study. The system provides "information about the electrical activity of the heart and displays catheter location" and "visualization of force information." The testing described confirms the system's functional integrity and similarity to predicate devices, rather than a standalone diagnostic performance claim often associated with AI/ML algorithms.

7. Type of Ground Truth Used

For the "in vivo Preclinical Studies" and bench testing, the ground truth would likely be based on:

• Physical measurements and established physiological parameters: For evaluating catheter position, orientation, and electrical activity recording accuracy.
• Comparison to predicate device performance: Demonstrating similar outputs and behavior.
• Engineering specifications and design requirements: For functional tests of hardware and software components.

There is no mention of "pathology" or "outcomes data" being used as ground truth for the evaluations described.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set size. This indicates that the regulatory submission is likely not for a device that relies on continuously learning or adaptive AI/ML algorithms that require specific training data sets in the typical sense. The "software verification" and "system level" testing suggest traditional software development and testing, rather than a machine learning model's training and validation.

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

Since there is no mention of a training set or a machine learning component requiring one, there is no information provided on how ground truth for a training set was established.

Ask a specific question about this device