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If the participants agree to participate in this study, the participants will undergo two scans (classic 3D-DSA and PS-3D-DSA assisted scan) to compare the imaging effects of both. After the procedure, the investigators will record the radiation exposure and collect DSA images.
Although several previous studies have used deep learning methods to reduce 3D-DSA radiation dose, no prospective clinical trial had yet validated the practical application of these models. Herein, the investigators introduce a patient-specific generative AI-based low-dose cerebrovascular 3D-DSA image reconstruction method (PS-3D-DSA) to reconstruct 3D-DSA images from ultra-sparse 2D projection views and a prospective cohort is used to validate its efficacy in clinical practice.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| PS-3D-DSA | Experimental | undergo a PS-3D-DSA scan |
|
| classic 3D-DSA | Sham Comparator | undergo a classic 3D-DSA scan |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| PS-3D-DSA | Radiation | undergo a PS-3D-DSA scan |
| |
| classic 3D-DSA |
| Measure | Description | Time Frame |
|---|---|---|
| The radiation dose received by patients during interventional procedures when using two scanning protocols (classic 3D-DSA and PS-3D-DSA) | Using the built-in radiation monitoring function of interventional surgical equipment (DSA system), the radiation dose (AK，air kerma) received by the patient during the procedure is directly measured and recorded. The collected radiation dose data is documented in the patient's medical records and stored in the research database for subsequent analysis and comparative studies. | No more than 6 hours |
| Measure | Description | Time Frame |
|---|---|---|
| The image diagnostic capabilities using two scanning protocols (classic 3D-DSA and PS-3D-DSA) | The secondary outcomes focus on evaluating the performance of interventional radiologists using either PS-3D-DSA or classic 3D-DSA for diagnostic tasks, with accuracy as the primary measure. Specifically, the diagnostic results from multiple radiologists will be compared against the gold standard to determine the level of agreement and diagnostic accuracy. This comparison will involve calculating sensitivity, specificity, and overall accuracy. Furthermore, receiver operating characteristic (ROC) curves will be plotted to assess the diagnostic performance and to visually represent the trade-off between sensitivity and specificity for each method. |
| Measure | Description | Time Frame |
|---|---|---|
| Comparison of image quality using two scanning protocols (classic 3D-DSA and PS-3D-DSA) | Algorithmic performance for image quality and interventional radiologists' scoring of image. Specifically, multiple radiologists will provide subjective ratings of image quality, with the best quality rated as 5 and the worst as 1. Image Quality (5 points):
|
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Huangxuan Zhao, PhD | Contact | +86 18627162379 | zhao_huangxuan@sina.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Wuhan Union Hospital | Wuhan | Hubei | 430022 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26553142 | Result | van Asch CJ, Velthuis BK, Rinkel GJ, Algra A, de Kort GA, Witkamp TD, de Ridder JC, van Nieuwenhuizen KM, de Leeuw FE, Schonewille WJ, de Kort PL, Dippel DW, Raaymakers TW, Hofmeijer J, Wermer MJ, Kerkhoff H, Jellema K, Bronner IM, Remmers MJ, Bienfait HP, Witjes RJ, Greving JP, Klijn CJ; DIAGRAM Investigators. Diagnostic yield and accuracy of CT angiography, MR angiography, and digital subtraction angiography for detection of macrovascular causes of intracerebral haemorrhage: prospective, multicentre cohort study. BMJ. 2015 Nov 9;351:h5762. doi: 10.1136/bmj.h5762. | |
| 37556901 |
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| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| ID | Term |
|---|---|
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D014652 | Vascular Diseases |
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| Radiation |
undergo a classic 3D-DSA scan |
|
| No more than 1 month |
| No more than 1 month |
| Result |
| Irfan M, Malik KM, Ahmad J, Malik G. StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm. Comput Med Imaging Graph. 2023 Sep;108:102271. doi: 10.1016/j.compmedimag.2023.102271. Epub 2023 Jul 22. |
| D002318 | Cardiovascular Diseases |