2d image navigators (inavs)  (Respiratory Motion)

Journal: Journal of Cardiovascular Magnetic Resonance

Article Title: Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis

doi: 10.1016/j.jocmr.2024.101097

Figure Lengend Snippet: Summary of the iNav-AUTO CMRA study protocol in comparison to the two previous non–contrast-enhanced multi-center studies assessing the diagnostic accuracy of CMRA.

Article Snippet: Respiratory motion correction , Right hemidiaphragmatic navigator gating , Abdominal belt in combination with right hemidiaphragmatic navigator gating , 2D image navigator (iNav).

Techniques: Comparison, Diagnostic Assay, Software

Journal: Journal of Cardiovascular Magnetic Resonance

Article Title: Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis

doi: 10.1016/j.jocmr.2024.101097

Figure Lengend Snippet: Appearance of the iNav-AUTO CMRA acquisition planning. The image slab including oversampling (yellow) and 2D image navigator (iNav) (blue) are automatically determined by a deep-learning–based tool which is part of work-in-progress software (Siemens Healthineers, cardiac dot companion). iNav-AUTO CMRA image navigator–based, automated coronary magnetic resonance angiography, 2D two-dimensional

Article Snippet: Respiratory motion correction , Right hemidiaphragmatic navigator gating , Abdominal belt in combination with right hemidiaphragmatic navigator gating , 2D image navigator (iNav).

Techniques: Software

Journal: Journal of Cardiovascular Magnetic Resonance

Article Title: Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis

doi: 10.1016/j.jocmr.2024.101097

Figure Lengend Snippet: Illustration of the protocol for whole-heart free-breathing sub-millimeter iNav-AUTO CMRA acquisition. (A) Acquisition of undersampled CMRA images. 2D image navigators (iNav) to mitigate respiratory-induced motion and to allow 100% respiratory scan efficiency precedes acquisition with 3D variable density, spiral-like Cartesian trajectory with golden angle between spiral-like interleaves (VD-CASPR). (B) Motion correction. Before reconstruction, the inferior-superior and left-right respiratory motion is estimated from the 2D iNavs. The data are then allocated into respiratory bins. Soft-gated iterative SENSE is used to reconstruct each respiratory bin. Non–rigid 3D motion is then estimated from these respiratory bin datasets via image registration. (C) Image reconstruction. 3D non–rigid motion-corrected iterative SENSE undersampled reconstruction with patch–based low-rank denoising (PROST) is then used to generate the final CMRA image. iNav-AUTO CMRA image navigator–based, automated coronary magnetic resonance angiography, 2D two-dimensional, 3D three-dimensional, SENSE sensitivity encoding, ECG electrocardiogram, FATSAT; fat saturation.

Article Snippet: Respiratory motion correction , Right hemidiaphragmatic navigator gating , Abdominal belt in combination with right hemidiaphragmatic navigator gating , 2D image navigator (iNav).

Techniques:

Journal: Magnetic Resonance in Medicine

Article Title: Non‐contrast enhanced simultaneous 3D whole‐heart bright‐blood pulmonary veins visualization and black‐blood quantification of atrial wall thickness

doi: 10.1002/mrm.27472

Figure Lengend Snippet: Proposed framework for simultaneous 3D whole‐heart bright‐blood depiction of the PVs and heart anatomy and black‐blood visualization of atrial walls. Two magnetization prepared bright‐blood volumes are acquired in odd and even heartbeats. Specifically, magnetization transfer in combination with an inversion pulse is used in odd heartbeats (MTC‐IR BOOST A), whereas magnetization transfer solely is exploited in even heartbeats (MTC BOOST B), The MTC‐IR acquisition is designed for comprehensive visualization of the heart anatomy. Although a short TI is exploited for fat saturation in odd heartbeats, spectral presaturation (Fat Sat) is used in even heartbeats. Data acquisition is performed using a 3D Cartesian trajectory with spiral profile order and segmented over multiple heartbeats (green, red, blue). A low‐resolution 2D iNAV is acquired in each heartbeat by spatially encoding the ramp‐up pulses of the bSSFP sequences. The bright‐blood MTC‐IR BOOST and MTC BOOST volumes are non‐rigidly motion corrected at the end‐expiratory level and, subsequently, combined in a PSIR‐like reconstruction to generate a complementary black‐blood volume for atrial wall visualization (PSIR BOOST, C). PVs, pulmonary veins; MTC, magnetization transfer contrast; IR, inversion recovery pulse; PSIR, phase sensitive inversion recovery

Article Snippet: In each heartbeat, a low resolution 2D image‐based navigator (iNAV) is acquired by spatially encoding the ramp‐up pulses of the bSSFP sequence, therefore allowing for the estimation of respiratory motion along the SI and right‐left (RL) directions.

Techniques:

Journal: Magnetic Resonance in Medicine

Article Title: Non‐contrast enhanced simultaneous 3D whole‐heart bright‐blood pulmonary veins visualization and black‐blood quantification of atrial wall thickness

doi: 10.1002/mrm.27472

Figure Lengend Snippet: Image‐navigated respiratory motion tracking with the proposed MT‐prepared BOOST configuration and with a more conventional approach for black‐blood PSIR. The BOOST framework acquires 2 differently weighted bright‐blood data sets (MTC‐IR BOOST and MTC BOOST), providing iNAVs where the heart is depicted with high signal and contrast (A and B). As such, the respiratory displacement can be extracted using a template positioned at the level of the heart itself (red rectangles). This leads to a sharp depiction of the cardiac anatomy after non‐rigid motion correction. Similarly, this results in good anatomy depiction after PSIR computation (E). In contrast, and with a more conventional black‐blood PSIR sequence, iNAVs exhibit low signal and contrast because of blood signal nulling (C) and to a low flip‐angle acquisition for the reference image (D). Consequently, the respiratory motion appears to be tracked at the level of the high‐contrast interface between the liver and the heart and lungs. Although this leads to a sharp delineation of the liver and abdominal vessels, the low signal in both odd and even heartbeats prevents the estimation of non‐rigid motion fields at the level of the heart; this results in reduced heart sharpness after PSIR computation (F). PSIR, phase sensitive inversion recovery; MTC, magnetization transfer contrast; IR, inversion recovery pulse; iNAV, image‐based navigator; UC, uncorrected

Article Snippet: In each heartbeat, a low resolution 2D image‐based navigator (iNAV) is acquired by spatially encoding the ramp‐up pulses of the bSSFP sequence, therefore allowing for the estimation of respiratory motion along the SI and right‐left (RL) directions.

Techniques: Sequencing

Journal: Magnetic Resonance in Medicine

Article Title: Non‐contrast enhanced simultaneous 3D whole‐heart bright‐blood pulmonary veins visualization and black‐blood quantification of atrial wall thickness

doi: 10.1002/mrm.27472

Figure Lengend Snippet: Motion correction performances using 2D translational and 3D non‐rigid motion correction in 2 representative healthy subjects. Before motion correction (red rectangle, A and D), images are affected by severe motion blurring preventing a sharp visualization of the overall cardiac anatomy. Translational motion correction (blue rectangles, B and E) already improves the depiction of several anatomical details, especially in the area where the iNAV template is typically placed (green arrows). Differently, static structures or structures without the template suffer from introduced blurring (yellow arrows). The use of non‐rigid respiratory motion correction successfully restores overall image sharpness, leading to the visualization of the overall cardiac anatomy with excellent image quality (purple rectangles, C and F)

Article Snippet: In each heartbeat, a low resolution 2D image‐based navigator (iNAV) is acquired by spatially encoding the ramp‐up pulses of the bSSFP sequence, therefore allowing for the estimation of respiratory motion along the SI and right‐left (RL) directions.

Techniques: