The Role of Artificial Intelligence in the Treatment of Abdominal Aortic Aneurysms

"Pilot Randomized Prospective Clinical Study of the Effectiveness of the Use of Artificial Intelligence in Determining the "Safe" Clamping Zones in the Surgical Treatment of Abdominal Aortic Aneurysms

"Pilot randomized prospective clinical study of the effectiveness of the use of artificial intelligence in determining "safe" clamping zones in the surgical treatment of abdominal aortic aneurysms."

Study Overview

Detailed Description

Abdominal aortic aneurysm is a life-threatening disease, a formidable complication of which is an aneurysm rupture (Editor's Choice - European Society for Vascular Surgery). The main method of treating aneurysms is surgical reconstruction, including open or endovascular intervention ((ESVS) 2019 Clinical Practice Guidelines on the Management of Abdominal Aorto-iliac Artery Aneurysms). Anatomical features of aneurysms and the presence of intraluminal thrombomass are among the criteria in deciding on the tactics of surgical treatment. These factors carry additional technical difficulties and lead to the development of intraoperative complications, including ischemic ones. Ischemia of the lower extremities is the most common complication and can be caused by thrombosis, embolism or dissection of the aortic wall (occurs in 7% of patients) (Complications Associated with Aortic Aneurysm Repair).

Thus, in order to reduce the frequency of embolic complications, it is important for the surgeon to determine a "safe" zone for applying a clamp to the aorta and main vessels. Thus, artificial intelligence (AI) can be used to interpret and analyze images of aneurysms that allow automatic quantitative measurements and determination of the exact characteristics of morphology and hydrodynamics, as well as the presence of intraluminal blood clots and calcifications. Analysis based on artificial intelligence can lead to the development of computational programs for predicting the development of aneurysms and the risk of their rupture, as well as postoperative outcomes. Artificial intelligence can also be used to determine the "safe" areas of aortic clamping. (Artificial intelligence in abdominal aortic aneurysm).

Adam and co-authors trained a neural network to detect and estimate the maximum outer diameter of aneurysms using a database of 489 CT angiographs of abdominal aortic aneurysms. AI has achieved a level of performance and accuracy suitable for clinical practice, and with the use of more CT images, further improvement in accuracy is expected (Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence). In a study by Fujiwara et al. 145 non-contrast CT scans with suspected aneurysm were retrospectively collected. Initially, AI was trained by manually segmenting CT images. Image processing was used to determine the abdominal aortic aneurysm area and to automatically measure the size. This method has shown that AI is a useful tool for fully automatic detection and measurement of aneurysm diameter. (Fully automatic detection and measurement of abdominal aortic aneurysm using artificial intelligence). Florent Lalys and his coauthor. an automatic fast and universal algorithm for determining an intraluminal thrombus was developed. The method was tested on pre- and postoperative CT scans of the abdominal aorta and iliac artery of 145 patients and consists in determining the central line and segmentation of the aortic lumen, an optimized stage of pretreatment and the use of a 3D model (Generic thrombus segmentation from pre- and post-operative CTA).

Taking into account the references already available in some studies of the use of artificial intelligence for the treatment of cardiovascular diseases, its use is seen as a promising method for making decisions in determining "safe" clamping zones in the surgical treatment of abdominal aortic aneurysms, which will reduce the frequency of postoperative complications.

Study Type

Interventional

Enrollment (Anticipated)

100

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

      • Novosibirsk, Russian Federation, 630055
        • Federal State Institution Academician E.N.Meshalkin Novosibirsk State Research Institute Of Circulation Pathology Rusmedtechnology
      • Novosibirsk, Russian Federation
        • E. Meshalkin National Medical Research Center
      • Novosibirsk, Russian Federation, 630055
        • Novosibirsk Research Institute of Circulation Pathology
    • Novosibirskaya Obl
      • Novosibirsk, Novosibirskaya Obl, Russian Federation, 630005
        • Alexander A Gostev

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

45 years to 75 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • Patients with aneurysmal dilation of the abdominal aorta, who are shown surgery.
  • Patients who have agreed to participate in this study

Exclusion Criteria:

  • Chronic heart failure of functional class III -IV according to NYHA classification;
  • Chronic decompensated "pulmonary" heart;
  • Severe hepatic or renal insufficiency (bilirubin >35 mmol/l, glomerular filtration rate <60 ml/min);
  • Polyvalent drug allergy;
  • Malignant oncological diseases in the terminal stage with a predicted life span of up to 6 months;
  • Acute cerebrovascular accident;

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Standart technology
the zone of aortic and main artery clamping is determined by the surgeon intraoperatively.
aneurysmectomy is performed with prosthetics of the abdominal aorta using the standard technology.
Experimental: Artificial intellect
The multispiral computed tomography data is evaluated using artificial intelligence and the definition of "safe" zones of aortic and main artery clamping is performed. Intraoperatively, clamping is performed in the settlement zones.
aneurysmectomy is performed with prosthetics of the abdominal aorta using the standard technology. Before surgery, multispiral computed tomography data is evaluated using artificial intelligence and safe zones of aortic and arterial clampings are determined. Intraoperatively, clamping is performed in the settlement zones.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
frequency of intraoperative and early postoperative embolism
Time Frame: 12 months
Number of intraoperative embolism according to intraoperative ultrasound monitoring. The number of developed occlusions of peripheral arteries according to ultrasound scanning
12 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Primary patency of the operated segment.
Time Frame: 12 months
The number of restenosis (50% or more) or reocclusion according to ultrasound duplex scanning of the operated segment at control points
12 months
secondary patency of the operated segment
Time Frame: 12 months
The number of restenosis (50% or more) or reocclusion according to ultrasound duplex scanning of the operated segment after repeated intervention at control points
12 months
MALE
Time Frame: 12 months
The number of major adverse events that occurred in the extremities the observation period
12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

January 1, 2023

Primary Completion (Anticipated)

December 31, 2023

Study Completion (Anticipated)

December 31, 2024

Study Registration Dates

First Submitted

November 15, 2022

First Submitted That Met QC Criteria

December 6, 2022

First Posted (Actual)

December 9, 2022

Study Record Updates

Last Update Posted (Estimate)

December 15, 2022

Last Update Submitted That Met QC Criteria

December 13, 2022

Last Verified

November 1, 2022

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

Yes

IPD Plan Description

after the end of the study, receipt of the results and publication of the first data, these sections will be available to other researchers upon personal request.

IPD Sharing Time Frame

1 year after the first publication

IPD Sharing Access Criteria

access to data on a personal request

IPD Sharing Supporting Information Type

  • Study Protocol
  • Informed Consent Form (ICF)
  • Clinical Study Report (CSR)

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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