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ANKYRAS enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery.

ANKYRAS also allows for the ability to computationally model the placement of neurointerventional braided endovascular devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures*
• Semi-automatic centerline generation from segmented blood vessels*
• Visualization of X-ray based images*
• Placing and sizing tools for braided endovascular devices
• Save user data
• Download** and share simulation***

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider´s judgment and analysis of the patient´s condition.

ANKYRAS is available in different platforms: Standalone, WebGL and Mobile App.

*Available for Standalone and WebGL platforms
**Available for WebGL platform
***Available for WebGL and Mobile App platforms

ANKYRAS is a medical device software application that allows the simulation of neurointerventional endovascular braided devices, such as flow diverters (FDs), and is intended to be used by physicians trained in medical procedures involving percutaneous and intravascular interventions for preoperational planning and sizing for neurovascular interventions and surgery. The software includes a database with braided endovascular FD devices: P100018/S015 - Pipeline Flex Embolization Device and P100018/S026 - Pipeline Flex Embolization Device with Shield Technology, Medtronic, Inc.; P170024/S003 - Surpass Evolve Flow Diverter System, Stryker Neurovascular; P180027 - Flow Re-Direction Endoluminal Device (FRED®) System and P180027/S002 - Flow Re-Direction Endoluminal Device (FRED®) X System, MicroVention, Inc. This database can be customized (among FDA cleared braided endovascular devices previously mentioned) according to the user's institution or needs.

ANKYRAS is intended to be used with 3D Rotational Angiography (3DRA) images or with VTK surface models from the target artery. From the 3DRA images, the user can extract the target artery vessel model using ANKYRAS segmentation functionality for further anatomical analysis and computational modeling (simulation) of the listed above FDs:

• First, using the vessel model and proximal and distal points selected by the user, ANKYRAS calculates the vessel centerline and displays cross-sectional dimensional information in an interactive chart.
• Second, using the vessel model, centerline, and morphology measurements, ANKYRAS simulates the FD devices selected by the user. The user can compare the results between different simulated FD devices and/or different FD positions including simulated device length, expansion along the centerline, and local porosity.

The information provided by the software is not intended in any way to eliminate, replace, or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

ANKYRAS software is intended to be user with a user license and can be installed on a computer with Windows operating systems or installed on an iOS/Android mobile device.

The FDA 510(k) clearance letter for ANKYRAS (K250160) states that the device was deemed substantially equivalent to the predicate device (K230006) based on verification, validation, and performance testing. While the document outlines the types of tests conducted, it does not provide specific quantitative acceptance criteria or detailed results of those tests. It states that "All tests have passed and demonstrate that the software is designed to meet the software requirements" and that "The computational modeling and prediction accuracy/error deployed length, expansion, and porosity of the selected flow diverters was evaluated through the following two tests." However, it lacks the numerical data to populate a table of reported device performance against specific criteria.

Therefore, many of the requested details about the study that proves the device meets the acceptance criteria are not explicitly present in the provided FDA 510(k) clearance letter. I will extract and infer what information is available and highlight what is missing.

Acceptance Criteria and Device Performance

The document describes the criteria used in software validation testing conceptually, but not with specific numerical thresholds for acceptance. It states what the accuracy of ANKYRAS's estimations "has to be equal or better than" certain references, but it doesn't quantify "equal or better than" in terms of a percentage or specific numerical tolerance.

Table 1: Acceptance Criteria (Conceptual) and Reported Device Performance (Not Quantified)

• The accuracy of the nominal porosity obtained from the nominal FD diameter and the FD manufacturer specifications, AND
• The accuracy of the reference porosity obtained from the patient's mean vessel diameter and the FD manufacturer specifications. | "All tests have passed and demonstrate that the software is designed to meet the software requirements." (No specific numerical accuracy reported) |

Study Details:

1. Sample Size and Data Provenance:

   • Test Set Sample Size: The document mentions "physical phantoms representative of anatomy of patients presenting with intracranial aneurysms" and "retrospective clinical images." However, it does not specify the number of phantoms or retrospective clinical images used in the test set.
   • Data Provenance:
     • Physical Phantoms: Implied to be generated for the study, often representing generic or synthesized anatomies. No specific country of origin mentioned.
     • Retrospective Clinical Images: Data provenance is "retrospective clinical images." No country of origin is specified.

2. Number of Experts and Qualifications for Ground Truth:

   • The document states: "Segmentation by user with clinician review and comment." This implies human input for ground truth, particularly for the anatomical models used.
   • However, the number of experts used to establish the ground truth for the test set and their specific qualifications (e.g., "radiologist with 10 years of experience") are not provided.

3. Adjudication Method for the Test Set:

   • The document implies a "clinician review and comment" for segmentation.
   • The specific adjudication method (e.g., 2+1, 3+1, none) for resolving discrepancies in ground truth establishment for the test set is not detailed.

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

   • No, an MRMC comparative effectiveness study was not explicitly mentioned or described. The validation tests focused on the accuracy of the computational model's predictions (length, expansion, porosity) against a ground truth, rather than measuring how human readers improve with AI assistance compared to without.

5. Standalone Performance:

   • Yes, a standalone (algorithm only) performance evaluation was done for the computational modeling functionality. The validation tests evaluated "the performance (error) of the ANKYRAS in calculating the deployed length, expansion, and porosity of the selected flow diverters." This refers to the accuracy of the algorithm's output itself, not its use by a human.

6. Type of Ground Truth Used:

   • Combined approach:
     • Physical Phantoms: Likely based on precisely measured physical properties or known configurations of flow diverters within phantoms.
     • Clinical Images: The "true length of FD after intervention," "true expansion of FD after intervention," and "true porosity of FD after intervention" were used as reference for the retrospective clinical images. This implies that actual post-intervention measurements, potentially from follow-up imaging, surgical reports, or device specifications applied to the observed post-implant state, served as ground truth. The segmentation itself from 3DRA images involved "clinician review and comment," suggesting expert consensus for the anatomical model from which measurements were derived.

7. Training Set Sample Size:

   • The document does not provide any information on the sample size used for the training set.

8. How Ground Truth for Training Set was Established:

   • The document does not provide any information on how the ground truth for the training set was established. This information is typically proprietary to the manufacturer and not usually detailed in a 510(k) summary.

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Sim&Size enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery. Sim&Size also allows for the ability to computationally model the placement of neurointerventional devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures
• Automatic centerline detection
• Visualization of X-ray based images for 2D review and 3D reconstruction
• Placing and sizing tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

Sim&Size is a Software as a Medical Device (SaMD) for simulating neurovascular implantable medical devices. The product enables visualization of cerebral blood vessels for preoperational planning for neurovascular interventions and surgery. It uses an image of the patient produced by 3D rotational angiography. It offers clinicians the possibility of simulating neurovascular implantable medical devices in the artery or in the aneurysm to be treated through endovascular surgery and provides support in the treatment for the sizing and positioning of implantable medical devices.

Each type of implant device is simulated in a simulation module of Sim&Size:

• FDsize, a module that allows pre-operationally planning Flow-Diverter (FD) devices.
• IDsize, a module that allows pre-operationally planning Intrasaccular (ID) devices.
• STsize, a module that allows pre-operationally planning Stent (ST) devices.
• FCsize, a module that allows pre-operationally planning First and filling coils (FC) devices.

Associated with these four modules, a common module is intended to import DICOM and to provide a 3D reconstruction of the vascular tree in the surgical area.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for Sim&Size:

Acceptance Criteria and Device Performance

The provided document highlights performance testing without explicitly stating quantitative acceptance criteria. However, the nature of the tests implies the device must accurately "predictive behavior of the implantable medical device with its theoretical behavior," accurately "compare the device placement in a silicone phantom model with the device simulation," and accurately "compare the in vitro retrospective cases with the device simulation."

Given the context of a 510(k) submission, the implicit acceptance criterion is that the device's performance is substantially equivalent to the predicate device and that the new features do not raise new questions of safety and effectiveness.

Here's a table based on the types of performance tests conducted:

Study Details:

Based on the provided document, here's what can be inferred about the studies conducted:

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

   • Test Set Sample Size: Not explicitly stated in the document.
   • Data Provenance:
     • "Retrospective in vivo testing" suggests real-world patient data, but the phrase "in vitro retrospective cases" implies these were lab-based re-creations or analyses of that data. The specific country of origin is not mentioned, but given the company's address (Montpellier, France), it's plausible the data could originate from Europe, although this is not confirmed.
     • "Bench testing" uses a "silicone phantom model," which is an experimental setup, not clinical data provenance.
     • "Verification testing" involves comparing theoretical behavior, which doesn't involve a dataset in the same way clinical or phantom models do.

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

   • This information is not provided in the document. The document refers to "theoretical behavior," "silicone phantom model," and "in vitro retrospective cases" as benchmarks, but it doesn't detail how the ground truth for "in vitro retrospective cases" was established or if experts were involved in defining the "theoretical behavior" or validating the phantom results.

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

   • This information is not provided in the document.

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:

   • No MRMC study is explicitly mentioned. The device "enables visualization of cerebral blood vessels" and "allows for the ability to computationally model the placement of neurointerventional devices," but it's stated that "Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition." This indicates it's a tool for assistance, but the document does not detail studies on human reader performance improvement with this AI.

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

   • The "Verification testing," "Bench testing," and "Retrospective in vivo testing" (comparing simulations to "in vitro retrospective cases") all describe methods that would assess the algorithm's standalone performance without a human in the loop for the actual comparison/measurement, although human input (e.g., in segmentation, placing/sizing tools) is part of the device's intended use. The wording "compares the predictive behavior... with its theoretical behavior" and "compares the device placement... with the device simulation" explicitly refers to the device's performance, implying a standalone assessment of the algorithmic component.

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

   • Theoretical Behavior: Used for "Verification testing" (e.g., physical laws, engineering models of device deployment).
   • Physical Phantom Model: Used for "Bench testing" (measurements from a physical silicone model).
   • "In vitro retrospective cases": Used for "Retrospective in vivo testing." This implies a ground truth derived from actual patient data, analyzed or re-created in a laboratory (in vitro). It's not explicitly stated if this ground truth was pathology or outcomes data, but rather a representation of the in vivo reality.

7. The sample size for the training set:

   • This information is not provided in the document. This section focuses on validation testing, not the training of any underlying models.

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

   • This information is not provided as the document does not detail the training process.

Ask a specific question about this device

ANKYRAS enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery.

ANKYRAS also allows for the ability to computationally model the placement of neurointerventional braided endovascular devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures
• Semi-automatic centerline generation from segmented blood vessels
• Visualization of X-ray based images
• Placing and sizing tools for braided endovascular devices
• Save user data

Information provided by the software is not intended in any way to eliminate, replace or substitute for in part, the healthcare provider's judgment and analysis of the patient's condition.

ANKYRAS is a software as a medical device that allows the simulation of neurointerventional braided endovascular devices, such as flow diverters (FDs), and is intended to be used by physicians trained in medical procedures involving percutaneous and intravascular interventions for preoperational planning and sizing for neurovascular interventions and surgery. The software includes a database with FDA-approved FDs: P100018/S015 - Pipeline Flex Embolization Device, Medtronic, Inc.; P170024/S003 - Surpass Evolve Flow Diverter System, Stryker Neurovascular; P180027 - Flow Re-Direction Endoluminal Device (FRED®) System, MicroVention, Inc.

ANKYRAS is intended to be used with 3D Rotational Angiography (3DRA) images. From the 3DRA images the user can extract the target artery vessel model using ANKYRAS segmentation functionality for further analysis and computational modeling (simulation) of the listed above FDs:

• . First, using the vessel model and proximal and distal points selected by the user, ANKYRAS calculates the vessel centerline and displays cross-sectional dimensional information in an interactive chart.
• . Second, using the vessel model, centerline, and dimensions, ANKYRAS simulates the FD devices selected by the user can compare the results between different simulated FD devices and/or different positions including simulated device length, expansion along the centerline, and local porosity.

The information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

ANKYRAS software is intended to be installed on a computer with Windows operating systems.

The provided document describes the ANKYRAS device, its intended use, and its comparison to a predicate device (Sim&Size). It also briefly mentions performance testing. However, it does not provide specific acceptance criteria or detailed results of a study proving the device meets those criteria, especially in the format requested (e.g., a table of performance metrics with thresholds).

The document states:

• "The computational modeling and prediction accuracy/error of deployed length, expansion, and porosity of the selected flow diverters by ANKYRAS was evaluated through the following two tests:"
  • "Using physical phantoms representative of anatomy of patients presenting with intracranial aneurysms to compare the in vitro placement and measurement of flow diverters to virtual flow diverter placement and outputs by ANKYRAS."
  • "Using retrospective clinical images to compare the placement and measurements of actual flow diverters to virtual flow diverter placement and outputs by ANKYRAS."
• "All tests have passed and demonstrate that the software is designed to meet the software requirements."

This indicates that performance testing was conducted, but the specific acceptance criteria (e.g., "accuracy of deployed length must be within X mm") and the quantitative results (e.g., "achieved accuracy of Y mm") are not included in this FDA K-Number summary.

Therefore, I cannot populate all the requested information. I can, however, extract what is available and note what is missing.

Based on the provided document, here's what can be extracted and what is missing regarding acceptance criteria and performance studies:

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

   • ACCEPTANCE CRITERIA: Not explicitly stated as quantitative thresholds in this document. The document vaguely states "All tests have passed and demonstrate that the software is designed to meet the software requirements," implying functional requirements were met, but specific accuracy, precision, sensitivity, or specificity thresholds for computational modeling of length, expansion, or porosity are not provided.
   • REPORTED DEVICE PERFORMANCE: No quantitative performance metrics (e.g., specific accuracy values for length, expansion, porosity) are reported in this document. It only states that tests "passed."

   Table (Incomplete due to lack of data in source document):

2. Sample size used for the test set and the data provenance

   • Test Set Sample Size: Not specified.
   • Data Provenance:
     • "Using physical phantoms representative of anatomy..."
     • "Using retrospective clinical images..." (Country of origin not specified, but the applicant is from Spain, and the context often implies data from similar Western healthcare systems when not explicitly stated).
     • The document implies the use of DICOM images from 3D Rotational Angiography (3DRA).

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

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified. The document mentions "physicians trained in medical procedures involving percutaneous and intravascular interventions" in the context of the device's intended users, but not specifically for ground truth establishment.

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

   • Not specified. The document mentions "in vitro placement and measurement" and "placement and measurements of actual flow diverters," but does not detail how potential discrepancies in measurement or ground truth definition were adjudicated.

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

   • MRMC Study: Not reported or implied. The studies described are focused on the accuracy of the computational modeling of the device itself (standalone performance against ground truth from phantoms or retrospective images), not on human reader performance with or without the device. The device is for "preoperational planning and sizing," and is stated to "not intended in any way to eliminate, replace or substitute for... the healthcare provider's judgment."
   • Effect Size: Not applicable, as no MRMC study is detailed.

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

   • Yes, implicitly. The performance testing described, particularly "computational modeling and prediction accuracy/error of deployed length, expansion, and porosity," appears to be a standalone evaluation of the algorithm's output against ground truth from phantoms or real cases. The device performs a "simulation" of FD devices which implies an algorithmic output.

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

   • Physical Phantoms: In vitro measurements obtained from physical phantoms. This would typically involve highly accurate, direct measurements.
   • Retrospective Clinical Images: "Placement and measurements of actual flow diverters." This implies ground truth was established from clinical assessment or imaging analysis to determine the "actual" deployed characteristics of the flow diverters. The method of establishing this ground truth (e.g., expert reader, consensus, another gold-standard measurement) is not specified.

8. The sample size for the training set

   • Not specified. This document is a 510(k) summary focused on the submission for market clearance, not a detailed technical report on model development. It details performance testing but not training data specifics.

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

   • Not specified. (See point 8).

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Sim&Size enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery.

Sim&Size also allows for the ability to computationally model the placement of neurointerventional devices. General functionalities are provided such as:

• Segmentation of neurovascular structures
• Automatic centerline detection
• Visualization of X-Ray based images for 2D review and 3D reconstruction
• Placing and sizing tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

Sim&Size is a Software as a Medical Device (SaMD) for the simulation of neurovascular implantable medical devices (IMD). The product enables visualization of cerebral blood vessels for preoperational planning for neurovascular interventions and surgery. It uses an image of the patient produced by 3D rotational angiography. It offers clinicians the possibility of computationally modeling the placement of neurovascular IMD in the artery or in the aneurysm to be treated through endovascular surgery and allows to preoperationally plan the sizing and the positioning of IMD.

Sim&Size includes four modules:

• FDsize module allows to pre-operationally plan the choice of size of flow-diverter devices;
• IDsize module allows to pre-operationally plan the choice of size of intrasaccular devices;
• STsize module allows to pre-operationally plan the choice of stents;
• FCsize module allows to pre-operationally plan the choice of first and filling embolization coils.

Associated to these four modules, a common module is intended to import DICOM images and to provide a 3D reconstruction of the vascular tree in the surgical area.

The provided documentation describes the Sim&Size device and its performance testing in support of its 510(k) submission. Here's a breakdown of the requested information:

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

The document provides general statements about meeting predefined acceptance criteria but does not list specific numerical acceptance criteria or detailed reported device performance in a table format. It states:

• "The tests met the pre-defined acceptance criteria."
• "Performance testing and verification and validation activities performed have demonstrated that the device performs as intended."
• "The results of the verification and validation tests demonstrate that the device performs as intended."

Without specific criteria from the document, a detailed table cannot be created.

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

• Sample Size: The document mentions that the studies used "retrospective clinical images" and "silicone phantom based on anatomy of patients presenting with intracranial aneurysms." However, specific numbers for the patient cases or phantom models in the test set are not provided.
• Data Provenance: The data used for the "predictability of the Sim&Size simulations for the Axium (Medtronic) and Hydrogel (MicroVention) embolization coils" and "predictability of the Sim&Size simulations for the overlapping flow diverters feature" were from retrospective clinical images of previously treated patients. The country of origin is not specified but since Sim&Cure is a French company, it is plausible the data originated from Europe.

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 provided in the document.

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

This information is not provided in the document.

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

An MRMC comparative effectiveness study involving human readers' improvement with AI assistance was not explicitly mentioned or described. The studies focused on the predictability of the simulation model (software output vs. measurements from retrospective images or in-vitro tests).

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

Yes, the studies described appear to be standalone (algorithm only) performance evaluations. The document mentions "comparing the software output (volume embolization ratio) with the measurements taken from retrospective images" and "comparing the software output with the measurements taken from retrospective images." The "in-vitro and virtual coil devices implanted in silicone phantom" also suggest an algorithm-only evaluation. There is no mention of human-in-the-loop performance evaluation in these studies.

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

The ground truth used for the studies appears to be:

• In-vitro measurements: For the "in-vitro and virtual coil devices implanted in silicone phantom" study, the ground truth would likely be physical measurements from the in-vitro setup.
• Measurements from retrospective clinical images: For the studies assessing the predictability of coil embolization (volume embolization ratio) and overlapping flow diverters, the ground truth was derived from "measurements taken from retrospective images of previously treated patients." This suggests expert measurements from real-world imaging.

8. The sample size for the training set

The document does not provide any details regarding the sample size or composition of the training set used for the Sim&Size software.

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

The document does not provide any details on how the ground truth for the training set was established. It focuses solely on the performance testing of the device.

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AneuGuide enables visualization of intracranial vessels for preoperational planning and sizing for neurovascular interventions. AneuGuide also allows for the ability to computationally model the placement of neurointerventional devices. General functionalities are provided such as:

• Segmentation of neurovascular structures .
• Automatic centerline detection
• . Visualization of X-ray based images for 2D review and 3D reconstruction
• . Placing and sizing tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

The AneuGuide software is a medical device intended to provide a 3D view of the final placement of implants. It uses an image of the patient produced by 3D rotational angiography. It offers clinicians the possibility of computationally modeling the flow diverters (FD) in the artery to be treated through endovascular surgery.

AneuGuide is intended to import DICOM images and to provide a 3D reconstruction of the vascular tree in the surgical area. Also, it allows to pre-operationally estimate the size of flow diverter devices.

AneuGuide is composed of the following analysis workflows: image loading, selection of the volume of interest (VOI), segmentation threshold adjustment, reconstruction, selection of the region of interest (ROI), selection of the vessel inlet, generation of centerline, initializing the flow diverter, and sizing the flow diverter.

The flow diverter supported by the software is the Pipeline Flex Embolization Device (Micro Therapeutics, Inc. d/b/a ev3 Neurovascular, PMA: P100018/S015), which is an FDA-approved neurointerventional device. AneuGuide software has a "moderate" level of concern. It is intended only for preoperational planning. It is not intended for diagnosis.

The ArteryFlow Technology AneuGuide software is a medical device intended for preoperational planning of neurovascular interventions, specifically for visualizing intracranial vessels and computationally modeling the placement of neurointerventional devices like flow diverters.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them:

1. Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" with specific quantitative thresholds. Instead, it describes general performance tests and a validation study for a key functionality: calculating the deployed length of a flow diverter. The overall acceptance criterion is implied to be that the software functions as intended, and for the flow diverter deployment, that its simulated length is sufficiently accurate compared to real-world implantation.

2. Sample Size and Data Provenance

• Test Set Sample Size: The document mentions two performance tests for computational modeling:
  • Silicone Phantoms: "Using silicone phantoms representative of patients presenting with intracranial aneurysms." The exact number of phantoms is not specified.
  • Patient Implantation Data: "Validation study of the AneuGuide performance comparing the simulated deployed length of the Pipeline Flex Embolization Device with its implanted length in patients with intracranial aneurysms." The exact number of patients or cases is not specified.
• Data Provenance: The document does not specify the country of origin for the patient data used in the validation study. It also does not explicitly state whether the patient data was collected retrospectively or prospectively. Given the context of comparing simulated vs. implanted lengths, it strongly implies retrospective analysis of existing patient implant data.

3. Number of Experts and Qualifications for Ground Truth

The document does not specify the number of experts used to establish the ground truth for the test set, nor does it detail their specific qualifications (e.g., radiologist with X years of experience). The general description implies that the "implanted length" from patients would serve as a real-world ground truth, presumably measured by clinical professionals.

4. Adjudication Method for the Test Set

The document does not mention any formal adjudication method (e.g., 2+1, 3+1) for establishing ground truth for the test set.

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

An MRMC study was not explicitly done or reported. The performance tests described focus on the software's capability to accurately model physical parameters (flow diverter length) rather than evaluating human reader performance with or without AI assistance. The device is for "preoperational planning" and "not intended in any way to eliminate, replace or substitute for...the healthcare provider's judgment." This suggests it's a tool for the human, not an AI to be compared against human readers for diagnostic accuracy.

6. Standalone (Algorithm Only) Performance

Yes, the described "Performance Testing - Bench" section primarily focuses on the standalone (algorithm only) performance of AneuGuide in calculating the deployed length of the Pipeline Flex Embolization Device. The tests involved comparing the software's simulated output against physical measurements (from silicone phantoms and implanted patient data).

7. Type of Ground Truth Used

The type of ground truth used for the computational modeling performance evaluation appears to be:

• Physical Measurements/Knowns: For the silicone phantom study, the "in vitro" placement is likely based on precise physical measurements of the actual flow diverter deployment in the phantoms.
• Outcomes Data/Clinical Measurement: For the patient study, the "implanted length" of the flow diverter is derived from real-world patient data, presumably measured from post-implantation imaging or surgical records. This leans towards clinical outcomes/measurements as ground truth.

8. Sample Size for the Training Set

The document does not provide any information regarding the sample size used for the training set of the AneuGuide software.

9. How Ground Truth for Training Set was Established

The document does not provide any information on how ground truth was established for the training set. Given that the software is for "computational modeling" of device placement and not explicit diagnostic AI, it's possible that the "training" (if it involved machine learning) might have used simulated data, or that "training" in this context refers more to the development and calibration of the underlying physical models rather than a typical supervised learning approach with human-labeled ground truth images.

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Sim&Size enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery. Sim&Size also allows for the ability to computationally model the placement of neurointerventional devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures
• Automatic centerline detection
• Visualization of X-Ray based images for 2D review and 3D reconstruction
• Placing and sizing tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

The Sim&Size software is a medical device intended to provide a 3D view of the final placement of implants. It uses an image of the patient produced by 3D rotational angiography. It offers clinicians the possibility of computationally model neurovascular implantable medical devices (IMD) in the artery or in the aneurysm to be treated through endovascular surgery. IMD such as the flow-diverters (FD) and the intrasaccular devices (ISD).

Sim&Size is a software designed with three modules. FDsize is the module that allows to pre-operationally plan the choice of size of flow-diverter devices. IDsize is the module that allows to pre-operationally plan the choice of size of intrasaccular devices. STsize is the module that allows to pre-operationally plan the choice of stent devices.

Associated to these three module is intended to import DICOM and to provide a 3D reconstruction of the vascular tree in the surgical area.

Here's a breakdown of the acceptance criteria and study information for the Sim&Size device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA submission details a type of "performance testing - bench" for the computational modeling of neurovascular devices. This includes verification tests (checking mathematical definitions) and validation tests (experimental bench tests, in vitro datasets). The document states that "All performance testing has been performed and passed. The Sim&Size software version 1.1.2 has met the required specifications for the completed tests."

While specific numerical acceptance criteria (e.g., tolerance ranges for length or apposition) are not explicitly stated in the provided text, the successful completion of these tests serves as the reported performance, meeting the implicit acceptance criteria of conforming to mathematical definitions, validity for new IMD devices, proper calibration, and predictability.

2. Sample Size for Test Set and Data Provenance

• Sample Size for Test Set:
  • For the FDsize and STsize modules' validation tests, the text mentions:
    • "Experimental bench tests using optical imaging of new IMD devices samples in both unconstrained and constrained configurations." (The exact number of samples is not specified.)
    • "In vitro (silicon model) datasets in which the predictability of the simulation model is assessed comparing in-vitro and virtual Flow Diverter devices implanted in silicone phantom based on anatomy of patients presenting with intracranial aneurysms." (The exact number of datasets/phantoms/patients is not specified.)
• Data Provenance: The phrasing implies the use of in-vitro (silicon model) datasets and experimental bench tests rather than patient data directly for the validation of the modeling. The silicon models are "based on anatomy of patients presenting with intracranial aneurysms," suggesting a derivation from real patient data but not direct use of patient images for this specific performance validation. There is no explicit mention of country of origin for the underlying anatomical data. The study is retrospective in the sense that existing anatomical data or models derived from them are used.

3. Number of Experts and their Qualifications for Ground Truth (Test Set)

The provided text does not specify the number of experts used to establish ground truth for the test set, nor their specific qualifications. The validation tests rely on physical measurements from "optical imaging of new IMD devices samples" and "in vitro (silicon model) datasets" comparing "in-vitro and virtual" results. This suggests the ground truth for these performance tests is derived from direct physical and mathematical conformity, rather than expert consensus on imaging interpretation for the test set performance.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method (like 2+1 or 3+1) for the test set. The performance validation seems to rely on the comparison of the software's computational model outputs with physical measurements from bench tests and in-vitro models, rather than human interpretation.

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

• No, an MRMC comparative effectiveness study was not explicitly mentioned or described. The focus of the performance data is on the standalone accuracy and predictability of the computational modeling, not on how the software improves human reader performance compared to a baseline without AI assistance.
• The device explicitly states in its Indications for Use: "Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition." This reinforces that it's an assistive tool, but the study described does not quantify its impact on human readers.

6. Standalone (Algorithm Only) Performance Study

• Yes, standalone performance (algorithm only) was done and is the primary focus of the performance testing. The "Performance Testing - Bench" section describes verification and validation tests for the "computational modeling of neurovascular devices" in both the FDsize and STsize modules. These tests assess the software's ability to accurately predict IMD length, apposition, conform to mathematical definitions, and be predictive in in-vitro models. This is an assessment of the algorithm's performance in isolation from clinical human-in-the-loop use.

7. Type of Ground Truth Used

The ground truth used for the performance testing (FDsize and STsize modules) includes:

• Mathematical definitions: For verifying that computed lengths and appositions conform.
• Experimental bench tests: Using "optical imaging of new IMD devices samples" providing physical measurements.
• In-vitro (silicon model) datasets: Where the software's predictions are compared against physical implantations in phantoms.

Essentially, the ground truth is a combination of physical measurements, mathematical conformity, and in-vitro experimental results.

8. Sample Size for the Training Set

The document does not provide any information regarding a specific training set size. The description of performance testing focuses on verification and validation of the algorithms without detailing a machine learning training phase or associated dataset. Given the context, it's possible the computational models are based on established biomechanical principles and manufacturer device specifications, rather than being "trained" on a large image dataset in the context of deep learning.

9. How Ground Truth for the Training Set Was Established

As no explicit training set is mentioned in the context of typical machine learning, the question of how its ground truth was established is not addressed. The "simulation model" for the IMD devices is established via "device geometrical parameters that were provided by each of the IMD device manufacturers," and the "in-house numerical solver" for the STsize module, suggesting a rules-based or physics-based modeling approach rather than a data-driven machine learning approach requiring a separate training ground truth.

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Sim&Size enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery. Sim&Size also allows for the ability to computationally model the placement of neurointerventional devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures
• Automatic centerline detection
• Visualization of X-Ray based images for 2D review and 3D reconstruction
• Placing and sizing tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

The Sim&Size software is a medical device intended to provide a 3D view of the final placement of implants. It uses an image of the patient produced by 3D rotational angiography. It offers clinicians the possibility of computationally model neurovascular implantable medical devices (IMD) in the artery or in the aneurysm to be treated through endovascular surgery, IMD such as the flow-diverters (FD) and the intrasaccular devices (ISD).

Sim&Size is a software designed with two modules. FDsize is the module that allows to preoperationally plan the choice of size of flow-diverter devices. IDsize is the module that allows to preoperationally plan the choice of size of intrasaccular devices.

Associated to these two modules, a common module is intended to import DICOM and to provide a 3D reconstruction of the vascular tree in the surgical area.

Sim&Size has been simplified as much as possible to guide the user in an intuitive way in order to reduce the total number of actions required and thus to optimize the time taken to obtain the desired results. There are currently seven steps required to choose the optimal size of an IMD to be placed:

• 1- Importing the images: the 3D rotational angiography DICOM files are imported.
• 2- Selecting of the region of interest (ROI): the user positions and focuses a sphere in the placement zone.
• 3- Threshold validation: the user checks the accuracy of the automatically extracted arterial wall. The threshold can be adjusted if needed.
• 4- Choosing the entry point: the user clicks on the entry point to the arterial network in order to retrieve the vessel centerlines.
• 5- Correct automatically or manually the centerline if needed: the user corrects the centerline going through a vessel fusion with the automatic tool or manually.
• 6- Initializing the implant: the user selects an IMD reference and the ideal placement zone.
• 7- Sizing the implant: IMD apposition is shown by a color chart in the 3D view. The user can change the IMD reference and placement zone to complete the planning for the intervention.

Patient images can be imported into Sim&Size in two ways: the user has the ability to transfer images using an external storage device (e.g. USB stick) or to retrieve images directly from Scanners Workstation if the option is enabled (only the retrieve function is possible).

The Sim&Size software is compatible with the operating systems MS Windows and Mac OS, when it is first installed a check is done to verify if the user's computer meets the minimum requirements for the use of the software. When a new version of the software is available, the update can be done by the user through a link send by Sim&Cure, the user then follow the instructions indicated in the user manual or by the use of the updater tool SacUpdates that notifies the user, then assists the download and the installation of the last version.

The computational modeling of three devices are supported by the software: Medtronic Pipeline Flex Embolization Device (PED - P100018/S015) flow diverter: Stryker Surpass Evolve Flow Diverter System (Evolve - P170024 S003); and Microvention Woven EndoBridge Aneurysm Embolism System (WEB - P170032) intrasaccular devices. The Medtronic Pipeline Flex Embolization Device, Stryker Surpass Evolve Flow Diverter and Microvention Woven EndoBridge Aneurysm Embolism System devices referenced here are FDA-approved neurointerventional devices.

The device is Sim&Size.

1. Table of Acceptance Criteria & Reported Device Performance
The document does not explicitly provide a table of acceptance criteria with numerical thresholds. Instead, it describes various performance tests and states that they were "passed." The general acceptance criterion implied is that the software performs its intended functions accurately and safely, and that the new features or changes do not negatively impact the device's performance or safety compared to the predicate device.

2. Sample Size for the Test Set and Data Provenance
The document does not explicitly state a numerical sample size for the test set. However, it mentions:

• FDsize module validation:
  • "Experimental benchtests to perform optical acquisitions of new IMD devices samples in both unconstrained and constrained configurations." (Likely in-vitro)
  • "Realistic in vitro (silicone model) datasets in which the predictability of the simulation model is assessed comparing in-vitro and virtual Flow Diverters devices implanted in silicone phantom of patients presenting with intracranial aneurysms." (In-vitro)
  • "In vivo studies for which the results are based on comparisons between FD implanted in patients presenting with intracranial aneurysms and virtual FD deployment." (Clinical, retrospective/prospective not specified, but likely retrospective based on existing patient data.)
• IDsize module validation:
  • "Experimental benchtests which assess the accuracy of the IDsize computational model in a well-controlled experimental configuration." (Likely in-vitro)
  • "Realistic in vitro (silicone model) datasets in which a comparison is done between implanted in silicon phantoms of idealized aneurysms anatomies and virtual WEB computationally modeling with Sim&Size." (In-vitro)
  • "In vivo studies for which the results are based on comparisons between WEB implanted in patients presenting with intracranial aneurysms and virtual WEB deployment." (Clinical, retrospective/prospective not specified, but likely retrospective.)

The country of origin for the data is not specified.

3. Number of Experts and Qualifications for Ground Truth
The document does not specify the number or qualifications of experts used to establish ground truth for the test set. For "in vivo studies," it implies comparison with actual patient outcomes, which would inherently involve clinical assessment by qualified medical professionals, but this is not detailed for the ground truth establishment process itself.

4. Adjudication Method
The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for establishing ground truth within the context of the performance testing.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not mention an MRMC comparative effectiveness study that assesses the effect size of AI assistance on human reader improvement. The device description explicitly states: "Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition." This indicates it's a planning tool, not a diagnostic AI intended to assist interpretation, so an MRMC study in that sense might not be applicable or expected.

6. Standalone Performance
Yes, a standalone performance assessment was done. The "Performance Testing - Bench" section describes verification and validation tests for the FDsize and IDsize modules, which evaluate the computational modeling capabilities of the software itself against mathematical definitions, experimental setups (in-vitro), and in-vivo comparisons. This indicates the algorithm's performance without direct human-in-the-loop diagnostic interpretation. The software is a planning tool, meant to be used by a human, but the validity of its computations were tested independently.

7. Type of Ground Truth Used
The ground truth types used appear to be:

• Mathematical definitions: For verification of computed flow diverter length and apposition.
• Experimental measurements: Obtained from "experimental benchtests" and "realistic in vitro (silicone model) datasets." This involves physical measurements from devices implanted in phantoms.
• In-vivo patient outcomes/observations: For "in vivo studies," where virtual deployments are compared to actual deployments in patients. This implies clinical observations or post-procedural imaging.

8. Sample Size for the Training Set
The document does not specify a sample size for the training set. It primarily describes verification and validation of the computational model and the solver, rather than a machine learning model that would require a distinct training set. The changes in this submission relate to adding new IMD databases and a new mechanical solver, which typically involve calibrating parameters for these specific devices or equations, rather than training a deep learning model from scratch on a large image dataset.

9. How Ground Truth for the Training Set Was Established
As a specific "training set" for a machine learning model is not explicitly mentioned and the focus is on computational modeling and solver verification/validation, the concept of ground truth establishment for a training set in the typical AI sense is not detailed. The "ground truth" referenced for validation is against mathematical definitions, experimental data (in-vitro), and in-vivo comparisons, as described in point 7.

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Sim&Size enables visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery. Sim&Size also allows for the ability to computationally model the placement and deployment of neurointerventional devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures
• Automatic centerline detection
• Visualization of X-ray based images for 2D review and 3D reconstruction
• Placing and sizing tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or in part, the healthcare provider's judgment and analysis of the patient's condition.

Sim&Size is software that allows for the preoperational planning of medical device sizes for the treatment of intracranial aneurysms. The computational modeling of neurointerventional devices, such as flow diverters and intrasaccular devices, are supported by the software to provide a patient-specific visualization of the deployment of the device from angiographic DICOM data, Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

The Sim&Size software is intended to be loaded on any Windows- or Mac-OS personal computer. A user license(s) must be purchased from the company in order to use the software after installation. The software also has a training module that offers learning assessments that are relevant to the software.

The software interacts with a patient's DICOM images, the user, and the device. To do so, the graphical interface is organized into three graphical pages (or screens):

• a. Patient selection page
• b. Module selection page
• Simulation page C.

Sim&Size was designed to enable the visualization of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery. Sim&Size also allows for the ability to computationally model the placement, deployment and apposition of neurointerventional devices.

The provided document is a 510(k) summary for the Sim&Size device. It states that "All bench testing has been performed and the software has met the required specifications for the completed tests." However, it does not provide detailed acceptance criteria or the specific results of the device performance against those criteria. It also lacks information on the sample size used for the test set, data provenance, number of experts for ground truth, adjudication methods, details of comparative effectiveness studies (MRMC), standalone performance, type of ground truth used, or details regarding the training set.

Therefore, based solely on the provided text, I cannot complete the requested tables and information.

If I were to make an educated guess about the content of such a study based on the general FDA 510(k) format and the device's function (pre-operational planning and sizing in neurovascular interventions), the study would likely focus on the accuracy of measurements, segmentation, and the computational modeling of device placement against a gold standard. However, this is speculative and not found in the provided document.

Here's what can be extracted from the document regarding the performance testing, acknowledging the significant missing information:

1. Table of Acceptance Criteria and Reported Device Performance:

Note: The document only states that the device "met the required specifications" for all performed tests without detailing what those specifications were (e.g., specific accuracy thresholds, error rates, etc.).

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

• Sample Size: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document only mentions "angiographic DICOM data" but doesn't detail its origin or nature for the test set.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication method for the test set:

• Adjudication Method: Not specified.

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:

• MRMC Study: Not mentioned as being performed or presented. The comparison table focuses on technological characteristics between the subject device and its predicate.

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

• Standalone Study: The performance tests conducted ("bench tests") are implied to be standalone evaluations of the software's functionality and computational modeling. However, no specific "standalone performance" metrics (e.g., recall, precision for segmentation, or specific measurement accuracy) are provided in isolation from human input or a clinical context. The "Human Intervention for Interpretation of Images" characteristic is listed as "Yes" for both subject and predicate devices, suggesting that the device is intended for human-in-the-loop use.

7. The type of ground truth used:

• Type of Ground Truth: Implied to be against "required specifications" and potentially physical device deployment for verification of the computational model. For segmentation and measurements, it would typically be expert annotations or known physical measurements, but this is not explicitly stated.

8. The sample size for the training set:

• Sample Size: Not specified.

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

• Ground Truth Establishment: Not specified.

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SurgicalPreview enables visualization and measurement of cerebral blood vessels for preoperational planning and sizing for neurovascular interventions and surgery. SurgicalPreview also allows for the ability to computationally model the placement and deployment of neurointerventional devices.

General functionalities are provided such as:

• Segmentation of neurovascular structures
• Automatic centerline detection
• Visualization of CT scan images for 2D review and 3D reconstruction
• Measurement and annotation tools
• Reporting tools

Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition.

SurgicalPreview" is a stand-alone software application that runs on any standard Windows or Mac OSX based computer. It enables physicians to upload patient CT scan studies from various data sources, view them, and process the images. SurgicalPreview™ provides a clinical decision support system during the preoperative planning of endovascular surgery.

SurgicalPreview™ enables visualization and measurement of different vascular structures such as vessels, aneurysms, and other anomalies. SurgicalPreview™ also allows for the ability to computationally model the placement and deployment of neurointerventional devices. SurgicalPreview™ can reconstruct 2D scan slices into 3D models of the patient, and can display supporting DICOM CT scan data. It works with DICOM CT scan images and can access multiple DICOM data files.

The device does not contact the patient, nor does it control any life sustaining devices. Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgement and analysis of the patient's condition.

The provided document, a 510(k) summary for the EndoVantage SurgicalPreview device, does not contain explicit acceptance criteria or a detailed study proving the device meets specific performance criteria. Instead, it relies on a comparison to a predicate device and bench testing for validation of its functionalities.

Here's a breakdown of the information available and what is not available based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state acceptance criteria or a table of performance metrics. It lists functionalities and describes bench tests, implying that successful completion of these tests (without specific thresholds) is considered acceptable performance.

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

The document states that "SurgicalPreview™ underwent bench testing to simulate clinical use." However, it does not specify:

• The sample size of cases or images used for these bench tests.
• The data provenance (e.g., country of origin, retrospective or prospective nature of the data).

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

The document does not provide information on:

• The number of experts used to establish ground truth for the bench tests.
• The qualifications of any such experts.

4. Adjudication Method for the Test Set:

The document does not describe any adjudication method used for the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

The document does not mention an MRMC comparative effectiveness study or any effect size for human readers improving with AI assistance. The device is described as "clinical decision support system" and explicitly states that "Information provided by the software is not intended in any way to eliminate, replace or substitute for, in whole or in part, the healthcare provider's judgment and analysis of the patient's condition," which suggests it's an aid rather than a replacement for human interpretation.

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

The document describes "bench testing" of the software's functionalities. This implies standalone performance testing of the algorithms for tasks like segmentation, centerline detection, visualization, and measurement. However, there's no explicit statement about a "standalone performance study" in the context of clinical accuracy metrics (sensitivity, specificity, etc.) against a clinical ground truth. The device is a "clinical decision support system" with "human intervention for interpretation of images."

7. The Type of Ground Truth Used:

The document mentions "bench testing" for various functionalities. The nature of the ground truth for these tests is not explicitly stated. For example, for measurement tests, it's not clear if the measurements were compared against manually acquired measurements by experts, a physical phantom, or another reference standard.

8. The Sample Size for the Training Set:

The document does not provide any information about a training set or its sample size. The device description suggests algorithmic processes (segmentation, centerline detection, computational modeling) that might involve machine learning, but no details on training data are given.

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

Since no information on a training set is provided, there is no information on how its ground truth was established.

Summary of what is present:

• Device Functionalities: Segmentation, automatic centerline detection, 2D/3D visualization, measurement, annotation, reporting, computational modeling of device placement.
• Validation Method: Bench testing to validate specifications, including importation, patient manager, image display/processing, anatomic reconstruction visualization, computational modeling, measurement, and report creation.
• Regulatory Conformance: ACR/NEMA DICOM 3.1, ISO 14971:2007, IEC 62304:2006.
• Predicate Device: EndoSize (K160376), with similar intended use for preoperational planning and image data processing.
• Role of Human Intervention: Explicitly states "Human Intervention for Interpretation of Images: Yes" and that the software does not replace healthcare provider judgment.

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