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Coronary computed tomography angiography (CCTA) has emerged as a pivotal non-invasive imaging modality for detailed assessment of coronary anatomy and plaque characteristics, playing a significant role in diagnosing and managing ischemic heart disease (IHD). Traditional approaches, such as the Segment Stenosis Score, Segment Involvement Score, and Leaman score, offer semi-quantitative evaluations of plaque burden. However, they are limited by their inability to quantify plaque volume precisely. Recent advancements in CCTA software have enabled more accurate, quantitative assessments that strongly correlate with invasive methods like intravascular ultrasonography and optical coherence tomography. These software tools also allow for detailed plaque characterization, categorizing plaques by composition and identifying high-risk features that may predict future cardiovascular events. The emerging photon-counting CT technique further enhances plaque analysis by individually measuring photons to assess plaque structure. Additionally, perfusion CT offers a functional imaging approach to evaluate myocardial blood flow, complementing CCTA by detecting microcirculatory dysfunction and providing insights into myocardial tissue, especially in fibrosis cases. The peri-coronary Fat Attenuation Index (pFAI), a 3D tool analyzing peri-coronary fat, has emerged as a significant prognostic marker, improving risk stratification in IHD. The evaluation of pFAI, particularly in patients with non-obstructive coronary disease, provides valuable information on inflammation and cardiovascular risk, making it a critical component of comprehensive IHD assessment. The advancement of CCTA-derived plaque analysis represents a significant change in cardiovascular imaging, enhancing diagnostic precision and risk assessment. As precision medicine advances, the integration of CCTA plaque analysis is set to transform the treatment of complex cardiovascular diseases.
Coronary computed tomography angiography (CCTA) has emerged as a pivotal non-invasive imaging modality for detailed assessment of coronary anatomy and plaque characteristics, playing a significant role in diagnosing and managing ischemic heart disease (IHD). Traditional approaches, such as the Segment Stenosis Score, Segment Involvement Score, and Leaman score, offer semi-quantitative evaluations of plaque burden. However, they are limited by their inability to quantify plaque volume precisely. Recent advancements in CCTA software have enabled more accurate, quantitative assessments that strongly correlate with invasive methods like intravascular ultrasonography and optical coherence tomography. These software tools also allow for detailed plaque characterization, categorizing plaques by composition and identifying high-risk features that may predict future cardiovascular events. The emerging photon-counting CT technique further enhances plaque analysis by individually measuring photons to assess plaque structure. Additionally, perfusion CT offers a functional imaging approach to evaluate myocardial blood flow, complementing CCTA by detecting microcirculatory dysfunction and providing insights into myocardial tissue, especially in fibrosis cases. The peri-coronary Fat Attenuation Index (pFAI), a 3D tool analyzing peri-coronary fat, has emerged as a significant prognostic marker, improving risk stratification in IHD. The evaluation of pFAI, particularly in patients with non-obstructive coronary disease, provides valuable information on inflammation and cardiovascular risk, making it a critical component of comprehensive IHD assessment. The advancement of CCTA-derived plaque analysis represents a significant change in cardiovascular imaging, enhancing diagnostic precision and risk assessment. As precision medicine advances, the integration of CCTA plaque analysis is set to transform the treatment of complex cardiovascular diseases.
Background: Arrhythmogenic cardiomyopathy (ACM) is a genetic disorder characterized by fibrofatty replacement of myocardial tissue, predominantly affecting the right ventricle (RV), but often involving the left ventricle (LV) as well. The early detection of fibrosis, crucial for risk stratification, has been enhanced by advanced imaging techniques. Global longitudinal strain (GLS) has shown promise as a surrogate marker for late enhancement (LE) in identifying myocardial fibrosis, yet precise cut-off values for strain are lacking. The aim of the study is to evaluate LV strain as a predictor of LE in ACM and to define strain cut-offs for early fibrosis detection, enhancing non-invasive diagnostic accuracy. Methods: This retrospective single-center study included 64 patients diagnosed with ACM. Echocardiographic analysis using speckle-tracking echocardiography was performed to assess LV strain. LE was evaluated through cardiac magnetic resonance (CMR) or via cardiac computed tomography (CCT) in cases with CMR contraindications. The study aimed to correlate regional LV strain values with the presence of LE, identifying cut-off values predictive of fibrosis. Results: The study found significant correlations between reduced LV strain values and the presence of LE, particularly in the anterolateral and inferolateral segments (p < 0.05). Specific strain thresholds, such as those for segment 12 (p = 0.02) and segment 17 (p = 0.03), were identified as predictive markers for LE. These findings suggest that strain imaging could serve as a non-invasive tool for the early detection of myocardial fibrosis in ACM patients. Conclusions: LV strain analysis offers potential as a non-invasive surrogate marker for myocardial fibrosis in ACM. Incorporating strain imaging into routine echocardiographic evaluations could improve early diagnosis and risk stratification, guiding patient management.
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