1. Diagnostic performance of calcification-suppressed coronary CT angiography using rapid kilovolt-switching dual-energy CT
- Author
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Yasutoshi Ohta, Kazuhiro Yamamoto, Toshihide Ogawa, Shinichiro Kitao, Hiroto Yunaga, Yoshiyuki Furuse, Tomomi Watanabe, and Yasuhiro Kaetsu
- Subjects
Male ,medicine.medical_specialty ,Computed Tomography Angiography ,030204 cardiovascular system & hematology ,Coronary Angiography ,030218 nuclear medicine & medical imaging ,Coronary artery disease ,Radiography, Dual-Energy Scanned Projection ,03 medical and health sciences ,0302 clinical medicine ,Multidetector Computed Tomography ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Vascular Calcification ,Neuroradiology ,Computed tomography angiography ,Aged ,medicine.diagnostic_test ,business.industry ,Ultrasound ,Coronary Stenosis ,Reproducibility of Results ,Interventional radiology ,General Medicine ,Middle Aged ,Reference Standards ,medicine.disease ,Coronary Vessels ,Stenosis ,medicine.anatomical_structure ,Female ,Radiology ,business ,Calcification ,Artery - Abstract
Multi-detector-row computed tomography angiography (MDCTA) plays an important role in the assessment of patients with suspected coronary artery disease. However, MDCTA tends to overestimate stenosis in calcified coronary artery lesions. The aim of our study was to evaluate the diagnostic performance of calcification-suppressed material density (MD) images produced by using a single-detector single-source dual-energy computed tomography (ssDECT). We enrolled 67 patients with suspected or known coronary artery disease who underwent ssDECT with rapid kilovolt-switching (80 and 140 kVp). Coronary artery stenosis was evaluated on the basis of MD images and virtual monochromatic (VM) images. The diagnostic performance of the two methods for detecting coronary artery disease was compared with that of invasive coronary angiography as a reference standard. We evaluated 239 calcified segments. In all the segments, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy for detecting significant stenosis were respectively 88%, 88%, 75%, 95% and 88% for the MD images, 91%, 71%, 56%, 95% and 77% for the VM images. PPV was significantly higher on the MD images than on the VM images (P
- Published
- 2016