Application of motion-sensitized driven equilibrium based black blood 3D TSE sequence in the detection of brain metastases

Chen, Jun; Li, Shuhua; Xue, Zheng; Chunqing, Bu; He, Min

doi:10.1016/j.mri.2022.08.010

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…Black-blood (BB) imaging is used to complement the contrast-enhanced 3D gradient-echo (CE 3D GRE) imaging to detect BM, wherein variable refocusing flip angles combined with flow-sensitizing gradients are used, selectively suppressing moving blood while stationary tumor contrast remains visible 13 . These sequences can be useful in acquiring 3D brain data from BM patients and overcoming the disadvantages of the 3D magnetization-prepared rapid gradient echo (MPRAGE), which was originally commonly used for detecting BM 13 , 14 because of its high spatial resolution and low partial volume effects. Single-slab 3D turbo spin echo BB images with slab selective, variable excitation pulses, such as sampling perfection with application-optimized contrasts using different flip-angle evolution (SPACE), enable the acquisition of high-resolution 3D datasets with contrasts similar to those obtained from 2D T2-weighted, T1-weighted, proton density, and dark fluid protocols.…”

Section: Introductionmentioning

confidence: 99%

Deep learning-based detection algorithm for brain metastases on black blood imaging

Lee

Kim

et al. 2022

Sci Rep

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Brain metastases (BM) are the most common intracranial tumors, and their prevalence is increasing. High-resolution black-blood (BB) imaging was used to complement the conventional contrast-enhanced 3D gradient-echo imaging to detect BM. In this study, we propose an efficient deep learning algorithm (DLA) for BM detection in BB imaging with contrast enhancement scans, and assess the efficacy of an automatic detection algorithm for BM. A total of 113 BM participants with 585 metastases were included in the training cohort for five-fold cross-validation. The You Only Look Once (YOLO) V2 network was trained with 3D BB sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) images to investigate the BM detection. For the observer performance, two board-certified radiologists and two second-year radiology residents detected the BM and recorded the reading time. For the training cohort, the overall performance of the five-fold cross-validation was 87.95%, 24.82%, 19.35%, 14.48, and 18.40 for sensitivity, precision, F1-Score, the false positive average for the BM dataset, and the false positive average for the normal individual dataset, respectively. For the comparison of reading time with and without DLA, the average reading time was reduced by 20.86% in the range of 15.22–25.77%. The proposed method has the potential to detect BM with a high sensitivity and has a limited number of false positives using BB imaging.

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Section: Introductionmentioning

confidence: 99%

Deep learning-based detection algorithm for brain metastases on black blood imaging

Lee

Kim

et al. 2022

Sci Rep

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“…Through sensitizing the equilibrium magnetization to motion, iMSDE can effectively suppress the blood signal while also diminish motion artifacts. 22,23 Understanding the advantages and limitations of different DB techniques in T 2 mapping is important for optimizing T 2 mapping protocols and improving diagnostic capabilities. However, comparative studies of iMSDE and DIR are lacking.…”

mentioning

confidence: 99%

“…Unlike DIR, which depends on multiple inversion pulses, iMSDE exploits the intrinsic motion of the myocardium to achieve DB imaging. Through sensitizing the equilibrium magnetization to motion, iMSDE can effectively suppress the blood signal while also diminish motion artifacts 22,23 …”

mentioning

confidence: 99%

The Role of Improved Motion‐Sensitized Driven Equilibrium Blood Suppression and Fat Saturation on T₂ Relaxation Time, Using GraSE Sequence in Cardiac Magnetic Resonance Imaging

Hammood,

Shirani,

Sadri

et al. 2023

Magnetic Resonance Imaging

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BackgroundT2 mapping is a valuable technique in cardiac MR imaging that offers insights into the microstructural characteristics of myocardial tissue. However, it was shown that myocardial T2 relaxation times (T2) measured vary significantly depending on sequence, sequence parameters, and field strength.PurposeTo assess T2 variability and image quality in cardiac T2 maps using four variants of the gradient‐spin echo (GraSE) sequence, having different methods of blood signal suppression (double inversion recovery (DIR) and improved motion‐sensitized driven equilibrium (iMSDE) and with and without the addition of fat saturation (FS).Study TypeProspective.Population48 healthy volunteers (46.7 +/− 21.5 years, 24 male) with no cardiac history.Field Strength/SequenceGraSE sequence with DIR (GraSEDIR), with iMSDE (GraSEiMSDE) and FS (GraSEDIR‐FS) and with both iMSDE and FS (GraSEiMSDE‐FS) at 1.5T.AssessmentGlobal T2 from three short axis myocardial slices. and image quality assessments using a 5‐point Lickert scale (1, (non‐diagnostic) to 5, (excellent)) were conducted to evaluate the impact of DB and FS techniques on myocardial T2 measurements and image quality.Statistical TestsPaired t‐tests or non‐parametric equivalents for comparisons between sequences. The Bland–Altmann plots and Pearson rank correlation analyses, as appropriate. A P value <0.05 was considered statistically significant.ResultsThe mean global T2 values for GraSEDIR, GraSEDIR‐FS, GraSEiMSDE, and GraSEiMSDE‐FS, were 52.84 ± 5.72 msec, 54.98 ± 3.59 msec, 53.9 ± 4.05 msec, and 55.14 ± 4.28 msec, respectively, with no significant differences (P = 0.092). High image quality scores (>4 out of 5) were obtained for all sequence variants with no significant differences between them (P = 0.11).Data ConclusionAll GraSE sequence variants exhibited approximately the same results and variations in the DB technique and addition of FS did not have significant impact on myocardial T2 values.Level of Evidence2Technical EfficacyStage 1

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Feature pyramid network-based computer-aided detection and monitoring treatment response of brain metastases on contrast-enhanced MRI

Chen

Meng

et al. 2023

Clinical Radiology

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Application of motion-sensitized driven equilibrium based black blood 3D TSE sequence in the detection of brain metastases

Cited by 4 publications

References 19 publications

Deep learning-based detection algorithm for brain metastases on black blood imaging

Deep learning-based detection algorithm for brain metastases on black blood imaging

The Role of Improved Motion‐Sensitized Driven Equilibrium Blood Suppression and Fat Saturation on T₂ Relaxation Time, Using GraSE Sequence in Cardiac Magnetic Resonance Imaging

Feature pyramid network-based computer-aided detection and monitoring treatment response of brain metastases on contrast-enhanced MRI

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Application of motion-sensitized driven equilibrium based black blood 3D TSE sequence in the detection of brain metastases

Cited by 4 publications

References 19 publications

Deep learning-based detection algorithm for brain metastases on black blood imaging

Deep learning-based detection algorithm for brain metastases on black blood imaging

The Role of Improved Motion‐Sensitized Driven Equilibrium Blood Suppression and Fat Saturation on T2 Relaxation Time, Using GraSE Sequence in Cardiac Magnetic Resonance Imaging

Feature pyramid network-based computer-aided detection and monitoring treatment response of brain metastases on contrast-enhanced MRI

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The Role of Improved Motion‐Sensitized Driven Equilibrium Blood Suppression and Fat Saturation on T₂ Relaxation Time, Using GraSE Sequence in Cardiac Magnetic Resonance Imaging