| Abstract |
Chronic Total Occlusions (CTOs) of peripheral arteries are defined as complete blockages of blood flow that have been present for at least three months. These occlusions are characterized by heavy plaque buildup that hardens and calcifies over time. CTOs commonly occur in coronary and peripheral arteries, leading to severe clinical manifestations such as chest pain or claudication, limb ischemia and even amputation, respectively. These lesions are complex forms of Peripheral Artery Disease (PAD) that are particularly difficult to manage due to their dense and calcified nature which may often complicate or prevent successful revascularization using standard endovascular procedures. The inability to effectively visualize and characterize the occlusion usually leads to endovascular treatment complications or failure.
Imaging techniques are crucial for managing CTOs, with Computed Tomography Angiography (CTA) and Magnetic Resonance Angiography (MRA) playing key roles in treatment planning. These modalities, however, have limitations in providing detailed insights into lesion characteristics, particularly in differentiating between various plaque components essential for selecting optimal therapeutic strategies. Moreover, anatomical classification systems like Trans-Atlantic Inter-Society Consensus Document (TASC), Global Limb Anatomic Staging System (GLASS), and CTO plaque cap morphology (CTOP), while useful, do not consistently offer precise information on lesion characteristics or reliably predict treatment outcomes. There is a significant gap in both current imaging capabilities and classification systems, underscoring the urgent need for advanced imaging solutions. These solutions must provide more accurate and comprehensive assessments of CTO composition to enhance treatment planning and clinical results.
The aim of this PhD was to evaluate the efficacy of novel imaging techniques such as Dual-Energy Computed Tomography (DECT) in accurately characterizing the composition of CTOs, while simultaneously developing a predictive model based on lesion morphological characteristics and demographic characteristics. This approach could potentially enhance treatment planning by providing a more precise and personalized assessment, improving clinical outcomes for patients with PAD. DECT has proven to be a valuable tool in the study conducted for this PhD, demonstrating its ability to differentiate between calcified and non-calcified plaque components through its quantitative analysis capabilities. The research utilized specific DECT metrics such as the Effective Atomic Number (Zeff) and the Dual-Energy Index (DEI), derived from pre-procedural DECT-CTO examinations. The findings indicated that higher values of Zeff and DEI, which signify denser and harder plaques, are associated with increased procedural complexity and duration. This hypothesis was thoroughly investigated and confirmed by strong correlations between DECT values and various procedural characteristics, including the difficulty of crossing the lesion, the procedural time required, and the use of specialized materials for CTOs. These insights highlight DECT's potential to significantly enhance the planning and execution of endovascular interventions for Chronic Total Occlusions.
Furthermore, in the context of this study a novel predictive model (EVACROSS-CTO) specifically developed to enhance the planning of endovascular treatments for CTOs. This scoring system was crafted by analyzing pre-procedural CTA data alongside demographic and clinical characteristics. The development process involved a comprehensive examination of CTA images to extract detailed morphological features of the CTOs, such as length, calcification extent, and location. These features, combined with patient-specific data such as age, history of diabetes, and endovascular treatment outcome, were used to create a multivariable logistic regression model. The resulting score from this model provided a numerical value that predicts the procedural difficulty and potential success of endovascular treatments. The score's effectiveness was validated through a series of retrospective studies, comparing its predictive accuracy against actual procedural outcomes. This validation confirmed that higher EVACROSS-CTO scores correlate with increased procedural challenges and complexity, aiding clinicians in better preparing for and potentially modifying their intervention strategies based on the predicted difficulty level.
This study contributes to the field of vascular medicine by enhancing the understanding and management of CTOs in peripheral arteries. By integrating advanced imaging techniques like DECT and developing the predictive EVACROSS-CTO score, the research offers valuable tools for clinicians to more accurately assess and plan endovascular treatments. These advancements could potentially reduce procedural complications, tailor interventions to individual patient profiles, and ultimately improve outcomes for patients suffering from this severe form of PAD. Looking forward, the methodologies developed in this study set a foundation for future research to further refine imaging and predictive capabilities, potentially incorporating artificial intelligence to analyze imaging data and predict treatment outcomes with even greater accuracy. This progressive approach to diagnosing and treating CTOs could pave the way for more personalized, effective, and minimally invasive therapies, transforming patient care.
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