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Shifting Paradigm from Conventional 2D to 3D-Delayed Gadolinium Enhancement Whole Heart MRI: Implications, Technical Aspects, Applications & Planning
Bourne S., Rivard A., Schieman K., Sherif A.
American Journal of Cardiovascular Disease Research
.
2022
, 8(1), 1-28
Figure
1.
Extracellular Gadolinium Tissue Differentiation. Gadolinium enhancement patterns between normal, acutely and chronically infarcted or fibrous myocardium [2]
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Figure
2
.
Delayed Gadolinium Enhancement Scheme: (a) A 180° pulse inverts the magnetization which then recovers. If the correct TI is chosen (b) while the segmented GRE sequence is played out, the signal from normal myocardium should be zero (dark) while signal within the infarcted tissue is hyperintense, as shown by the arrows in (b) [3]
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Figure
3
.
Selection of optimal TI. One short-axis slice at mid-ventricle level is repeatedly obtained using different inversion times varying from 100-310msec., at short TI times (100-160msec.) non-viable infarcted myocardium (arrows) is mostly dark. Optimal nulling is visually selected at 250 msec. [4]
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Figure
4.
Factors Influencing Optimal TI [4]
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Figure
5.
Effects of Arrythmias on Image Quality: (a) Arrythmias cause poor image quality: As the IR pulse is on, inconsistencies between the time of excitation and relaxation of the magnetization causes contrast variabilities, slice misregistration, blurring and or ghosting. For patients with extremely high heartbeats, triggering on alternating RR cycle (b) will help improve image quality) as compared to every RR cycle (a) [7]
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Figure
6.
CMR of Right Ventricular Dilatation and Wall Motion Abnormality in RVOT (3A, yellow arrow). Focal fibrosis (3B, orange arrow) on 3D DGE turned out to be key in retaining diagnosis of ARVC [1]
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Figure
7
.
Detection of Arrhythmogenic Sites within Post-Infarction Scar. Guided ablation therapy using 3D-DGE Color-coded 3D model: purple: remote myocardium, green to yellow: grey zone, red: dense scar [1]
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Figure
8.
EGE of Structures with Poor or no Uptake of Gadolinium in the Absence of Vascularity at TI>400 msec [11]
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Figure
9
.
Early Stages Post Contrast (1-5minutes). Gadolinium presides mainly in blood-pool and normal tissue, areas with MVO experiences very slow wash-in (a) and are better detected with EGE (b) [12]
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Figure
10
.
Motions and Deformations of Myocardium Consisting of Longitudinal, Circumferential and Radial Components [14]
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Figure
11
.
ECG-R Wave Synchronizing Methods [15]
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Figure
12
.
ECG Wave Components [16]
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Figure
13.
Inter-Relationship between RR-interval and Heart Rate [9,18]
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Figure
14
.
RR-Interval Segmentation.
(
Each RR-interval in this example is divided into 24 separate frames/segments corresponding to different time points (phases) within the cardiac cycle. The location and thickness of the myocardium show that frame 1= early systolic phase, frame 12= end systolic phase and frame 24= end diastolic phase. Each image represented by a fully completed K space, is filled 1 phase encoding line per heartbeat. It takes in total 3 heartbeats to form image 24 with lines “24-1” (from 1
st
HB) “24-2” (from 2
nd
HB) and “24-3” (from 3
rd
HB) [9])
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Figure
15
.
Prospective Triggered (Single Phase) Acquisition. Reduction of acquisition time is obtained by dividing each interval into smaller segments of 3 K-space lines every heartbeat [15]
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Figure
16
.
Key parameters in Prospective Image Acquisition
[18]
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Figure
17.
Spoiled Gradient Inversion Recovery T1-Weighted Sequence. Correct TI time corresponding with acquisition at mid-diastolic phase [21]
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Figure
18
.
Coronary MRA Single-Phase Data Acquisition Windows. Single-phase imaging positioned at specific cardiac phase ideally in the rest periods (diastasis) with least amount of motion (frames yellow or red). Frames green and blue placed at systole shows severe image degradation due to motion of right coronary artery [22]
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Figure
19
.
Segmented (A) vs Single-Shot (B) Acquisition. Acquisition with 3 lines of K-space per heartbeat compared to an entire data set of images within 1 heartbeat ideal in cases of difficult breath holds and arrhythmias [23]
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Figure
20
.
Repetition Time [24]
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Figure
21
.
Temporal Resolution (ability to evaluate dynamic processes) [24]
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Figure
22
.
Frames/Segments/Cardiac Phases [25]
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Figure
23
.
Views per Segments; VPS (K-Space Lines/Lines per Segments/ETL: Echo Train Length [26]
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Figure
24
.
SA Views in Systole with 2 Different Temporal Windows (Left short window (20-45msec) showing images free of motion artefact and right: window larger than 50msec. with motions affecting the image quality [22])
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Figure
25
.
Optimizing Cardiac Motion Artefact with Alternative Synchronization Technique (Retrospective imaging (left) showing cardiac motion artefact caused by poor synchronization. Prospectively triggered cine acquisition (right) with shortest RR-interval [9])
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Figure
26
.
Diaphragm Motion During Respiration. Breathing causes the heart to translate at a significant distance in H-F while imaging plane remains fixed [27]
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Figure
27
.
End-Expiration Respiratory Gated Threshold Scheme. The scan is set in a way that data is accepted if acquisition occurs when respiration falls below a threshold line [29]
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Figure
28
.
Conventional Diaphragm 1D Navigation [30]
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Figure
29
.
Navigator Acquisition at Specific Time Interval (Respiratory motion limited by detection of data only when diaphragm (lung-liver border) falls within narrow acceptance window [29])
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Figure
30
.
Effects of Different Breathing Patterns on Navigator Efficiency (Consistent regular and shallow breathing result in higher navigator efficiency (a) compared to inconsistent and/or deep breathing corresponding to lower efficiency and prolonged scan times (b) [27])
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Figure
31
.
3D Imaging Steps (Red stars indicating manual interactions (*below) at different times during the process of 3D imaging acquisition [31])
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Figure
32.
User Friendly Self-Navigation without Navigator (Self-navigation without navigator, results in higher efficiency & predictable scan times [33])
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Figure
33
.
Narrowing the Image Quality Gap between MRI (upper row) and the Gold Standard CTA (lower row) using Self-Navigated Free Breathing 3D Cardiac Imaging [30]
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Figure
34
.
DGE Image Quality Comparison between 2D (upper rows) and I-NAV 3D (lower rows) (Considerably shorter scan time with novel INAV-3D, red arrows indicating enhancements [35])
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Figure
35
.
3D-DGE with Poor Nulling of Myocardium (At default TI-150 msec and scantime reaching +/- 8minutes, image quality results in underestimation of TI and myocardium showing a negative increased signal intensity (red circle) [37])
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Figure
36
.
Magnitude and Phase-Corrected Signal Intensity. Grey scale depicting contrast difference between viable myocardium and infarct: X-axis: duration in Time Y-axis: Signal intensity from -Mo to +Mo. [24]
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Figure
37
.
Signal Intensity difference between TI scout and PSIR over long range of TI times [38]
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Figure
38
.
Subendocardial Enhancement between Standard IR and Dark blood PSIR [9]
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Figure
39
.
BSSFP Imaging at 3T (Despite overall good image quality albeit with banding artefacts, pacemaker leads showing severe artefacts (top left image) which is avoided with Spoiled GRE technique (bottom right) [9])
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Figure
40
.
Volume and Cross Pair Navigator Positioning on Free-Breathing Localizers [1,10]
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Figure
41
.
Siemens Specific Navigator settings in Physio/Pace [1,10]
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Figure
42
.
Optimal TI is a Moving Target [11]
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Figure
43
.
Delayed Gadolinium Enhancement Characteristics between 2D and 3D. Standard 2D DGE acquisition comprised of multiple BH in SAX, 2-3-4 chamber views with limited spatial resolution compared to high resolution 3D with free breathing. Either with diaphragm or I-NAV to track respiratory motion and restricted to end expiration with multiplanes reconstruction [1]
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Figure
44
.
Shifting Paradigms acquisition [31]
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