Magnetic resonance imaging · 2024
Quiescent frame, contrast-enhanced coronary magnetic resonance angiography reconstructed using limited number of physiologic frames from 5D free-running acquisitions.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод в очереди
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Yang Yitong, Hair Jackson, Yerly Jérôme, Piccini Davide, Di Sopra Lorenzo, Bustin Aurelien, Prsa Milan, Si-Mohamed Salim, Stuber Matthias, Oshinski John N
Аннотация
BACKGROUND: 5D, free-running imaging resolves sets of 3D whole-heart images in both cardiac and respiratory dimensions. In an application such as coronary imaging when a single, static image is of interest, computationally expensive offline iterative reconstruction is still needed to compute the multiple 3D datasets.
PURPOSE: Evaluate how the number of physiologic bins included in the reconstruction affects the computational cost and resulting image quality of a single, static volume reconstruction.
STUDY TYPE: Retrospective.
SUBJECTS: 15 pediatric patients following Ferumoxytol infusion (4 mg/kg).
FIELD STRENGTH/SEQUENCE: 1.5 T/Ungated 5D free-running GRE sequence.
ASSESSMENT: The raw data of each subject were binned and reconstructed into a 5D (x-y-z-cardiac-respiratory) images. 1, 3, 5, 7, and 9 bins adjacent to both sides of the retrospectively determined cardiac resting phase and 1, 3 bins adjacent to the end-expiration phase are used for limited frame reconstructions. The static volume within each limited reconstruction was compared with the corresponding full 5D reconstruction using the structural similarity index measure (SSIM). A non-linear regression model was used to fit SSIM with the percentage of data used compared to full reconstruction (% data). A linear regression model was used to fit computation time with % raw data used. Coronary artery sharpness is measured on each limited reconstructed images to determine the minimal number of cardiac and respiratory bins needed to preserve image quality.
STATISTICAL TESTS: The coefficient of determination (R2) is computed for each regression model.
RESULTS: The % of data used in the reconstruction was linearly related to the computational time (R2 = 0.99). The SSIM of the static image from the limited reconstructions is non-linearly related with the % of data used (R2 = 0.80). Over the 15 patients, the model showed SSIM of 0.9 with 18% of data, and SSIM of 0.96 with 30% of data. The coronary artery sharpness of images reconstructed using no less than 5 cardiac and all respiratory phases is not significantly different from the full reconstructed images using all cardiac and respiratory bins.
DATA CONCLUSION: Reconstruction using only a limited number of acquired physiological states can linearly reduce the computational cost while preserving similarity to the full reconstruction image. It is suggested to use no less than 5 cardiac and all respiratory phases in the limited reconstruction to best preserve the original quality seen on the full reconstructed images.
PURPOSE: Evaluate how the number of physiologic bins included in the reconstruction affects the computational cost and resulting image quality of a single, static volume reconstruction.
STUDY TYPE: Retrospective.
SUBJECTS: 15 pediatric patients following Ferumoxytol infusion (4 mg/kg).
FIELD STRENGTH/SEQUENCE: 1.5 T/Ungated 5D free-running GRE sequence.
ASSESSMENT: The raw data of each subject were binned and reconstructed into a 5D (x-y-z-cardiac-respiratory) images. 1, 3, 5, 7, and 9 bins adjacent to both sides of the retrospectively determined cardiac resting phase and 1, 3 bins adjacent to the end-expiration phase are used for limited frame reconstructions. The static volume within each limited reconstruction was compared with the corresponding full 5D reconstruction using the structural similarity index measure (SSIM). A non-linear regression model was used to fit SSIM with the percentage of data used compared to full reconstruction (% data). A linear regression model was used to fit computation time with % raw data used. Coronary artery sharpness is measured on each limited reconstructed images to determine the minimal number of cardiac and respiratory bins needed to preserve image quality.
STATISTICAL TESTS: The coefficient of determination (R2) is computed for each regression model.
RESULTS: The % of data used in the reconstruction was linearly related to the computational time (R2 = 0.99). The SSIM of the static image from the limited reconstructions is non-linearly related with the % of data used (R2 = 0.80). Over the 15 patients, the model showed SSIM of 0.9 with 18% of data, and SSIM of 0.96 with 30% of data. The coronary artery sharpness of images reconstructed using no less than 5 cardiac and all respiratory phases is not significantly different from the full reconstructed images using all cardiac and respiratory bins.
DATA CONCLUSION: Reconstruction using only a limited number of acquired physiological states can linearly reduce the computational cost while preserving similarity to the full reconstruction image. It is suggested to use no less than 5 cardiac and all respiratory phases in the limited reconstruction to best preserve the original quality seen on the full reconstructed images.