(Withdrawal) AI-Based Low-Dose 3D-DSA Reconstruction

(Withdrawal) Validation of a Patient-Specific Generative AI-Based Low-Dose Cerebrovascular 3D-DSA Image Reconstruction Method: A Stepwise, Multicenter, Randomized Crossover Trial

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.

Inclusion Criteria:

1. Age ≥18 years.
2. Requires 3D-DSA-guided interventional diagnosis or treatment (e.g., cerebral angiography, cerebral artery chemoembolization) and meets operational indications.
3. Can understand the study's purpose, procedures, potential risks, and benefits, and voluntarily signs a written informed consent form.

Exclusion Criteria:

1. Severe heart or lung disease, such as heart failure or chronic obstructive pulmonary disease (COPD).
2. History of high-dose radiation exams or treatments.
3. Known allergies or severe adverse reactions to iodine contrast agents or other relevant medications.
4. Pregnant or breastfeeding women.
5. Severe comorbidities or chronic diseases (e.g., severe diabetes, renal insufficiency).
6. Severe mental illness or cognitive impairment preventing understanding of the study procedures or providing informed consent.