Magnetic resonance in medicine · 2026
Non-Rigid Motion-Compensated MR Multitasking for Free-Breathing Low-Dose Dynamic Contrast-Enhanced MRI in the Abdomen.
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Ma Lingceng, Wu Chaowei, Wang Lixia, Lee Hsu-Lei, Chen Junzhou, Hu Zheyuan, Xie Yibin, Pandol Stephen J, Gaddam Srinivas, Li Debiao, Christodoulou Anthony G
Аннотация
PURPOSE: To improve free-breathing low-dose quantitative dynamic contrast-enhanced (DCE) MRI for imaging pancreatic ductal adenocarcinoma.
METHODS: We introduced non-rigid (NR) motion compensation (MoCo) into MR Multitasking using a novel "in-subspace" formulation that directly applies motion fields to spatial feature maps (eigenimages), reducing computational cost relative to warping in the spatiotemporal domain. We evaluated NR-MoCo DCE Multitasking in n = 11 healthy volunteers scanned using 20% (0.02 mmol/kg) of the standard Gd dose; 10 of these volunteers underwent a repeat 20%-dose scan after exiting and re-entering the scanner. Data were reconstructed without MoCo (No-MoCo), translation MoCo (Tr-MoCo), and NR-MoCo Multitasking. We assessed motion by measuring respiratory motion energy ratio and liver dome position across time within the end-expiration respiratory bin. We estimated pharmacokinetic parameters from all reconstruction frameworks, evaluating the test-retest repeatability of parameters in the head, body, and tail of the pancreas.
RESULTS: Non-rigid MoCo of eigenimages was compatible with MR Multitasking, using > 3000× fewer Fourier transforms and motion deformations. Compared with Tr-MoCo and No-MoCo, NR-MoCo showed the best performance in reducing artifactual intra-bin motion along DCE dimension, indicated by the smallest liver-dome position variation (p = 0.026). NR-MoCo lowered the effective tensor rank and improved repeatability of quantitative kinetic vascular properties across healthy volunteers as compared to No-MoCo. The Bland-Altman analysis indicated that NR-MoCo narrowed Ktrans limits of agreement by 2.1× relative to No-MoCo and Tr-MoCo.
CONCLUSION: Non-rigid motion compensation reduces respiratory motion and improves Ktrans repeatability in low-dose free-breathing, whole-abdomen quantitative dynamic contrast enhanced (DCE) MR Multitasking.
METHODS: We introduced non-rigid (NR) motion compensation (MoCo) into MR Multitasking using a novel "in-subspace" formulation that directly applies motion fields to spatial feature maps (eigenimages), reducing computational cost relative to warping in the spatiotemporal domain. We evaluated NR-MoCo DCE Multitasking in n = 11 healthy volunteers scanned using 20% (0.02 mmol/kg) of the standard Gd dose; 10 of these volunteers underwent a repeat 20%-dose scan after exiting and re-entering the scanner. Data were reconstructed without MoCo (No-MoCo), translation MoCo (Tr-MoCo), and NR-MoCo Multitasking. We assessed motion by measuring respiratory motion energy ratio and liver dome position across time within the end-expiration respiratory bin. We estimated pharmacokinetic parameters from all reconstruction frameworks, evaluating the test-retest repeatability of parameters in the head, body, and tail of the pancreas.
RESULTS: Non-rigid MoCo of eigenimages was compatible with MR Multitasking, using > 3000× fewer Fourier transforms and motion deformations. Compared with Tr-MoCo and No-MoCo, NR-MoCo showed the best performance in reducing artifactual intra-bin motion along DCE dimension, indicated by the smallest liver-dome position variation (p = 0.026). NR-MoCo lowered the effective tensor rank and improved repeatability of quantitative kinetic vascular properties across healthy volunteers as compared to No-MoCo. The Bland-Altman analysis indicated that NR-MoCo narrowed Ktrans limits of agreement by 2.1× relative to No-MoCo and Tr-MoCo.
CONCLUSION: Non-rigid motion compensation reduces respiratory motion and improves Ktrans repeatability in low-dose free-breathing, whole-abdomen quantitative dynamic contrast enhanced (DCE) MR Multitasking.