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Contrast-Sparing Imaging Utilizing Spectral Detector CT for Transcatheter Aortic Valve Replacement Procedure Planning

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Taylor & Francis Group2021-05-27 更新2026-04-16 收录
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https://tandf.figshare.com/articles/dataset/Contrast-Sparing_Imaging_Utilizing_Spectral_Detector_CT_for_Transcatheter_Aortic_Valve_Replacement_Procedure_Planning/12091554/1
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<b>:</b> Cardiac CTA is an indispensable imaging tool for TAVR procedure planning. Post-processing of the dual-energy CT utilizing dual-source and kV-switching approach enables an increase in the density of iodine and allows the reduction of iodine dose. We hypothesized that the use of a dual-layer Spectral Detector CT (SDCT) can enhance the signal of intravascular iodine contrast material, reduce iodine contrast material volume, and facilitate pre-TAVR planning. <b>:</b> We tested this in a preclinical porcine animal model, with results suggesting that spectral imaging may be superior to conventional imaging even at 21-35% of the full contrast medium dose with regard to reader confidence, higher SNR and CNR at the level of the aortic annulus and root. We subsequently followed this up by a prospective human validation study of 24 patients undergoing TAVR. <b>:</b> We demonstrate that SNR and CNR with SDCT were significantly higher (highest in lower energy virtual mono-energetic images (VMI) (monoE 40 keV) compared to conventional images, with the spectral images preferred for procedure planning by an experienced TAVR operator and imaging specialist. This was associated with a reduction in inter-observer variability in TAVR sizing measurements in low dose contrast studies (33% of the full contrast dose) resulting in a higher rate of agreement on the choice of valve prosthesis size. <b>:</b> Low contrast dose spectral images achieved similar SNR and CNR compared to full contrast dose conventional images. Taken together, our results suggest that the use of SDCT imaging may facilitate the routine use of low contrast dose as part of pre-TAVR imaging.
提供机构:
Chung-Lieh Hung; Hiram G. Bezerra; Chun-Ho Yun
创建时间:
2020-04-07
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