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The AiORTA - Plan tool is an image analysis software tool for volumetric assessment, image analysis, geometric analysis, and pre-operative sizing and planning. It provides volumetric visualization and measurements based on 3D reconstruction computed from cardiovascular CTA scans. The software device is intended to provide adjunct information to a licensed healthcare practitioner (HCP) in addition to clinical data and other inputs, as a measurement tool used in assessment of aortic aneurysm, pre-operative evaluation, planning and sizing for cardiovascular intervention and surgery, and for post-operative evaluation in patients 22 years old and older.

The device is not intended to provide stand-alone diagnosis or suggest an immediate course of action in treatment or patient management.

AiORTA - Plan v2.0 is a cloud-based software tool used to make and review geometric measurements of cardiovascular structures, specifically abdominal aortic aneurysms. The software uses CT scan data as input to make measurements from 2D and 3D mesh based images. Software outputs are intended to be used as a measurement tool used in assessment of aortic aneurysm, pre-operative evaluation, planning and sizing for cardiovascular intervention and surgery, and for post-operative evaluation.

The AiORTA - Plan v2.0 software consists of two components, the Analysis Pipeline and Web Application.

The Analysis Pipeline is the data processing engine that produces measurements of the abdominal aorta based on the input DICOM images. It consists of multiple automated modules that are used to preprocess the DICOM images, compute geometric parameters (e.g., centerlines, diameters, lengths, volumes), and upload the results to the Web App for clinician review. The end user (licensed healthcare practitioner) is ultimately responsible for the accuracy of the segmentations, the resulting measurements, and any clinical decisions based on these outputs.

The workflow of the Analysis Pipeline can be described in the following steps:

• Input: the Analysis Pipeline receives a CTA scan as input.
• Segmentation: an AI-powered auto-masking algorithm performs segmentation of the aortic lumen, wall, and key anatomical landmarks, including the superior mesenteric, celiac, and renal arteries, as well as the external iliac arteries and a large portion of the descending aorta.
• 3D conversion: the segmentations are converted into 3D mesh representations.
• Measurement computation: from the 3D representations, the aortic centerline and geometric measurements, such as diameters, lengths, and volumes, are computed.
• Follow-up study analysis: for patients with multiple studies, the system can detect and display changes in aortic geometry between studies.
• Report generation: a report is generated by the user in the web application containing key measurements and a 3D Anatomy Map providing multiple views of the abdominal aorta and its landmarks. A detailed breakdown is presented including targeting landing zones and critical regions of interest and C-ARM calculations for proximal neck and distal left and right common iliac arteries.
• Web application integration: the outputs, including the segmented CT masks, and 3D visualizations, are uploaded to the Web App for interactive review and analysis.

The Web Application (Web App) is the front end and user facing component of the system. It is a cloud-based user interface offered to the qualified clinician to first upload de-identified cardiovascular CTA scans in DICOM format, along with relevant demographic and medical information about the patient and current study. The uploaded data is processed asynchronously by the Analysis Pipeline. Once processing is complete, the Web App then enables clinicians to interactively review and analyze the resulting outputs.

Main features of the Web App include:

• Full suite of image analysis tools: Clinicians can review segmentations and make manual corrections of all measurements generated by the software by viewing the CT slices alongside the segmentation masks. Segmentations can be revised using tools such as a brush or pixel eraser, with adjustable brush size, to select or remove pixels as needed. When clinicians revise segmentations, they can request asynchronous re-analysis by the Analysis Pipeline, which generates updated measurements and a 3D Anatomy Map of the aorta based on the revised segmentations.
• 3D visualization: The aorta and key anatomical landmarks can be examined in full rotational views using the 3D Anatomy Map.
• Measurement tools: Clinicians can perform measurements directly on the 3D Anatomy Map of the abdominal aorta and have access to a variety of measurement tools, including:
  • Centerline distance, which measures the distance (in mm) between two user-selected planes along the aortic centerline.
  • Diameter range, which measures the minimum and maximum diameters (in mm) within the region of interest between two user-selected planes along the aortic centerline.
  • Local diameter, which measures the diameter (in mm) at the user-selected plane along the aortic centerline.
  • Volume, which measures the volume (in mL) between two user-selected planes along the aortic centerline.
  • Calipers, which allow additional linear measurements (in mm) at user-selected points.
• Screenshots: Clinicians can capture images of the 3D visualizations of the aorta or the segmentations displayed on the CT slices.
• Longitudinal analysis: For patients with multiple studies, the Web App allows side-by-side review of studies. Clinicians have access to the same measurement and visualization tools available in single-study review, enabling comparison between studies.
• Reporting: Clinicians can generate and download reports containing all measurements in the application measurements and screenshots captured during review.

I'm sorry, but the provided text does not contain the detailed information necessary to answer all parts of your request regarding the acceptance criteria and the study proving the device meets them. The text primarily focuses on comparing the subject device (AiORTA - Plan v2.0) to its predicate (AiORTA - Plan v1.1) and explaining the differences in features and functionality.

Here's what can be extracted and what is missing:

1. Table of acceptance criteria and the reported device performance:
The document does not explicitly state specific acceptance criteria (e.g., minimum accuracy, sensitivity, specificity thresholds) for the device's performance, nor does it present a table of reported device performance metrics against such criteria. It only mentions that "No additional performance testing was conducted for the AI/ML algorithms, as these are identical to those used by the predicate." This implies that the performance of AiORTA Plan v2.0 is assumed to be equivalent to v1.1 based on the AI/ML algorithms being the same.

2. Sample size used for the test set and the data provenance:
This information is not available in the provided text. The document refers to "Performance Testing" but states that "No additional performance testing was conducted for the AI/ML algorithms." It does not describe any specific test set used for validating the v2.0 or even refer to the details of the predicate's validation study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
This information is not available in the provided text.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
This information is not available in the provided text.

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 available in the provided text.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The document states that "Users in v2.0 have the option of employing an automated algorithm instead of a ViTAA analyst for segmentation. Clinicians retain control over the end result." and "A full suite of image analysis tools for manual correction by a clinician has been added. All corrections and edits are performed by the physician." This suggests that the device is intended for human-in-the-loop use, and it does not explicitly mention if a standalone performance study was conducted. Given the statement "No additional performance testing was conducted for the AI/ML algorithms," it's unlikely such a study focusing on the algorithms alone was performed for v2.0.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
This information is not available in the provided text.

8. The sample size for the training set:
This information is not available in the provided text.

9. How the ground truth for the training set was established:
This information is not available in the provided text.

In summary, the provided FDA 510(k) clearance letter and its summary primarily focus on demonstrating substantial equivalence to a predicate device, highlighting the differences in features and functionality rather than presenting detailed performance data for the subject device. It relies on the assumption that the underlying AI/ML algorithms, which were deemed identical to the predicate, already meet performance standards.

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