The thesis investigates Digital Variance Angiography (DVA) and its color-coded variant (ccDVA) as novel imaging techniques aimed at overcoming the qualitative and diagnostic limitations of traditional Digital Subtraction Angiography (DSA), while also potentially reducing radiation exposure and contrast agent volume. The author focused on three primary research objectives:
1. To assess the applicability of DVA in new therapeutic indications, specifically Transarterial Chemoembolization (TACE) for liver tumors and Prostatic Artery Embolization (PAE).
2. To evaluate the qualitative advantages of ccDVA in other therapeutic interventions, particularly PAE.
3. To determine the reliability of the time-related parameters of ccDVA, especially in comparison to the commercially available Syngo iFlow software.
Three retrospective, proof-of-concept studies were conducted:
1. TACE study: Pre-embolization angiographic images from 25 liver cancer patients were analyzed. DSA and DVA image pairs were compared based on Contrast-to-Noise Ratio (CNR) and visual assessment by experts.
2. PAE study: Angiographic images from 30 male patients treated for benign prostatic hyperplasia were examined. DSA, DVA, and ccDVA images were assessed for CNR, visual quality, and diagnostic value.
3. ccDVA study: Color-coded DVA and Syngo iFlow images from 19 patients with peripheral artery disease were compared based on their temporal parameters, primarily Time-to-Peak (TTP).
Objective (CNR) and subjective (expert visual evaluation) methods were employed, supported by statistical analyses (e.g., Wilcoxon signed-rank test, Kendall's W, Pearson correlation).
Results for each study:
1. TACE study: DVA images exhibited a median 24% higher CNR compared to DSA and were rated significantly better in visual evaluations. Lesion and feeding artery detection were clearer with DVA (32% and 26% clear identification for DVA, versus 22% and 16% for DSA, respectively).
2. PAE study: DVA's CNR was four times higher than DSA's, and visual scores were significantly better (DVA median score: 4.5 vs. DSA: 3.39). ccDVA demonstrated significant advantages over DSA in visualizing large vessels, small vessels, tissue blush, and feeding arteries.
3. ccDVA study: The temporal parameters (specifically TTP) of ccDVA showed a very high correlation with those of Syngo iFlow (Pearson r=0.99), irrespective of image acquisition settings, validating ccDVA's reliability for hemodynamic analysis.
Conclusions:
1. DVA and ccDVA offer significant improvements in image quality and diagnostic value over DSA in liver TACE and PAE procedures, extending their known benefits beyond lower limb interventions.
2. ccDVA can enhance the visualization of small arteries, feeding vessels, and tissue perfusion, potentially improving the safety and efficacy of embolization procedures.
3. The time-related parameters of ccDVA are reliable and equivalent to those of established systems like Syngo iFlow, positioning ccDVA as a viable alternative decision-support tool in endovascular interventions.
4. The inherent quality reserve of DVA technology suggests a potential for reducing radiation dose and contrast agent volume, which warrants further investigation in larger, prospective studies.
The findings suggest that the broader clinical adoption of DVA and ccDVA could contribute to safer, more effective, and patient-friendly minimally invasive vascular procedures, while potentially reducing procedural risks and costs.
