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Status unknownNCT05643664Updated Dec 15, 2022

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

An interventional study of prosthetics of the abdominal aorta and prosthetics of the abdominal aorta after determining the safe zones of clamping in Frequency of Embolic Complications and Frequency of Ischemic Complications, sponsored by Meshalkin Research Institute of Pathology of Circulation. Status unknown at 4 sites in Russia. Open to participants aged 45 Years to 75 Years. Per ClinicalTrials.gov, last updated 2022-12-15.

Sponsored by Meshalkin Research Institute of Pathology of Circulation · Not applicable, Interventional, and Prevention

The sponsor has not verified this record recently (last verified Nov 2022), so the status shown — last known as Not yet recruiting — may be out of date.
Phase
Not applicable
Study type
Interventional
Enrollment
100
Allocation
Randomized
Ages
45 Years to 75 Years
Sex
All
01

Study summary

"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."

Read the 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.

02

Conditions studied

  • Frequency of Embolic Complications
  • Frequency of Ischemic Complications

Keywords

  • Aortic aneyrism
  • Artificial intelligence
  • "safe" zone of clamping
  • embolic complications
03

In context

Lead sponsor

Meshalkin Research Institute of Pathology of Circulation is the lead sponsor of 118 studies on the registry; 8 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
45 Years to 75 Years
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

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

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;
05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
100 participants (estimated)

Study arms

  • Active comparator
    Standart technology

    the zone of aortic and main artery clamping is determined by the surgeon intraoperatively.

    Procedure: prosthetics of the abdominal aorta

  • 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.

    Procedure: prosthetics of the abdominal aorta after determining the safe zones of clamping

Interventions

  • Procedureprosthetics of the abdominal aorta

    aneurysmectomy is performed with prosthetics of the abdominal aorta using the standard technology.

  • Procedureprosthetics of the abdominal aorta after determining the safe zones of clamping

    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.

06

What researchers measure

Primary outcomes

  1. frequency of intraoperative and early postoperative embolism

    Number of intraoperative embolism according to intraoperative ultrasound monitoring. The number of developed occlusions of peripheral arteries according to ultrasound scanning

    Time frame: 12 months

Secondary outcomes

  1. Primary patency of the operated segment.

    The number of restenosis (50% or more) or reocclusion according to ultrasound duplex scanning of the operated segment at control points

    Time frame: 12 months

  2. secondary patency of the operated segment

    The number of restenosis (50% or more) or reocclusion according to ultrasound duplex scanning of the operated segment after repeated intervention at control points

    Time frame: 12 months

  3. MALE

    The number of major adverse events that occurred in the extremities the observation period

    Time frame: 12 months

07

Study locations

4 sites
  • Alexander A Gostev
    Novosibirsk, Novosibirskaya Obl 630005, Russia
  • Federal State Institution Academician E.N.Meshalkin Novosibirsk State Research Institute Of Circulation Pathology Rusmedtechnology
    Novosibirsk, 630055, Russia
  • Novosibirsk Research Institute of Circulation Pathology
    Novosibirsk, 630055, Russia
  • E. Meshalkin National Medical Research Center
    Novosibirsk, Russia
08

References and documents

Individual participant data

Plan to share: Yes — 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.

Supporting information: Study protocol, Informed consent form, Clinical study report

Time frame: 1 year after the first publication

Access criteria: access to data on a personal request

Data sharing details ↗ · meshalkin.ru

No publications or documents are linked to this record.

09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reached

Start is estimated for Jan 2023; primary completion for Dec 2023, 11 months later.

How these figures are worked out, and which studies are left out of them.

Registered
Nov 15, 2022
First posted
Dec 9, 2022
StartEst.
Jan 1, 2023
Primary completionEst.
Dec 31, 2023
CompletionEst.
Dec 31, 2024
Last update
Dec 15, 2022
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Dec 15, 2022, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT05643664
Responsible party
Sponsor
First posted
Dec 9, 2022
Start date
Jan 1, 2023 (estimated)
Primary completion
Dec 31, 2023 (estimated)
Completion
Dec 31, 2024 (estimated)
Last update
Dec 15, 2022

Study contacts

Andrey A Karpenko, PhD
Contact
andreikarpenko@rambler.ru
+79139504100
Alexandr A Gostev, PhD
Contact
a_gostev@meshalkin.ru
+79139555074

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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