Coronary artery calcium measurement on attenuation correction computed tomography using artificial intelligence: correlation with coronary flow capacity and prognosis.

• Tác giả: Kyung Hoon Cho, Sang-Geon Cho, Jahae Kim, Ju Han Kim, Kang Bin Kim, Jong Eun Lee, Jang Bae Moon, Ki-Seong Park, Ho-Chun Song
• Ngôn ngữ: eng
• Ký hiệu phân loại: 952.03 1868-1945
• Thông tin xuất bản: Germany : European journal of nuclear medicine and molecular imaging , 2025
• Bộ sưu tập: NCBI
• ID: 188058

Tóm tắt

 PURPOSE: This study aimed to test whether the coronary artery calcium (CAC) burden on attenuation correction computed tomography (CTac), measured using artificial intelligence (AI-CACac), correlates with coronary flow capacity (CFC) and prognosis. MATERIALS AND METHODS: We retrospectively enrolled patients who underwent [ RESULTS: In total, 289 patients were included in this study. Significant negative correlations were found between AI-CACac and stress MBF (ρ = -0.363, p <
  0.001) and MFR (ρ = -0.305, p <
  0.001). AI-CACac >
  10 was associated with a significantly higher prevalence of impaired CFC (31% vs. 7%, p <
  0.001) and significant ischaemia (20% vs. 7%), which remained significant after adjusting for other risk factors. MACE occurred in 49 (17%) patients (median follow-up, 284 days), and those who experienced MACE had significantly higher AI-CACac (median, 166 vs. 56
  p = 0.039). However, multivariable analysis revealed an independent prognostic association among impaired CFC, diabetes, smoking, but not for AI-CACac. CONCLUSION: AI-measured CACac correlates well with PET-measured MBF and CFC, but its prognostic significance requires further validation.