Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients

Igata, Natsuki; Kakeda, Shingo; Watanabe, Keita; Nozaki, Atsushi; Rettmann, Dan; Narimatsu, Hidekuni; Ide, Satoru; Abe, Osamu; Korogi, Yukunori

doi:10.1007/s00330-016-4730-7

Cited by 6 publications

(3 citation statements)

References 21 publications

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“…These patients usually find it difficult to tolerate the long scanning time, and their involuntary head movement often leads to obvious motion artifacts, which seriously affect the diagnosis (24). Thus, during the MRI examination, reducing motion artifact without increasing the acquisition time is extremely vital for those patients with involuntary head motion (25). The total acquisition time of the ACS-SS-FLAIR used in the present study was 34 s in all patients, which was significantly shorter than that of conventional PI-FLAIR (1 min 59 s in all patients).…”

Section: Discussionmentioning

confidence: 99%

The clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) for evaluation of uncooperative patients with brain diseases: comparison with the conventional T2-FLAIR with parallel imaging

Sun

et al. 2022

Acta Radiol

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Background Satisfactory magnetic resonance imaging (MRI) of those patients with involuntary head motion due to brain diseases is essential in avoiding missed diagnosis and guiding treatment. Purpose To investigate the clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) in evaluating patients with involuntary head motion due to brain diseases, compared with the conventional T2-FLAIR with parallel imaging (PI-FLAIR). Material and Methods A total of 33 uncooperative patients with brain disease were prospectively enrolled. Two readers independently reviewed images acquired with ACS-SS-FLAIR and PI-FLAIR at a 3.0-T MR scanner. In the aspects of qualitative evaluation of image quality, overall image quality and lesion conspicuity of ACS-SS-FLAIR and PI-FLAIR were assessed and then statistically compared by paired Wilcoxon rank-sum test. For quantitative evaluation, the relative contrast of lesion-to-cerebral parenchyma were calculated and compared. Results Overall image quality scores of ACS-SS-FLAIR evaluated by two readers were 2.94 ± 0.24 and 2.91 ± 0.29, respectively, both of which were significantly higher than that of PI-FLAIR, respectively ( P < 0.001 and <0.001). Lesion conspicuity scores of were 2.74 ± 0.47 and 2.79 ± 0.44, both of which were significantly higher than that of PI-FLAIR, respectively ( P < 0.001 and <0.001). In the quantitative evaluation for image quality, the relative contrast of lesion-to-cerebral parenchyma was 0.34 ± 0.09 in the ACS-SS-FLAIR sequence, significantly larger than that in the PI-FLAIR sequence ( P = 0.001). Conclusion The ACS-SS-FLAIR sequence is clinically feasible in the MRI workup of those patients with involuntary head motion due to brain diseases, showing shorter image acquisition time and better image quality compared with conventional PI-FLAIR.

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Section: Discussionmentioning

confidence: 99%

The clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) for evaluation of uncooperative patients with brain diseases: comparison with the conventional T2-FLAIR with parallel imaging

Sun

et al. 2022

Acta Radiol

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“…Head motion always exists during magnetic resonance imaging (MRI) acquisitions, particularly when children, elderly, and patients (e.g., with chronic pain or Parkinson's disease) are scanned (Alfaro‐Almagro et al, 2018; Igata et al, 2017; Malfliet et al, 2017; Satterthwaite et al, 2012; Yuan et al, 2009). Moreover, head motion is considered one of the major confounding factors impairing the quality of functional MRI (fMRI) data and consequently reducing analytical efficiency (Ciric et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Dissimilarity of functional connectivity uncovers the influence of participant's motion in functional magnetic resonance imaging studies

Yang

Fan

et al. 2020

Human Brain Mapping

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Head motion is a major confounding factor impairing the quality of functional magnetic resonance imaging (fMRI) data. In particular, head motion can reduce analytical efficiency, and its effects are still present even after preprocessing. To examine the validity of motion removal and to evaluate the remaining effects of motion on the quality of the preprocessed fMRI data, a new metric of group quality control (QC), dissimilarity of functional connectivity, is introduced. Here, we investigate the association between head motion, represented by mean framewise displacement, and dissimilarity of functional connectivity by applying four preprocessing methods in two independent resting‐state fMRI datasets: one consisting of healthy participants (N = 167) scanned in a 3T GE‐Discovery 750 with longer TR (2.5 s), and the other of chronic back pain patients (N = 143) in a 3T Siemens Magnetom Prisma scanner with shorter TR (0.555 s). We found that dissimilarity of functional connectivity uncovers the influence of participant's motion, and this relationship is independent of population, scanner, and preprocessing method. The association between motion and dissimilarity of functional connectivity, and how the removal of high‐motion participants affects this association, is a new strategy for group‐level QC following preprocessing.

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“…PROMO is ideal for studies of pediatric or adult patient populations as no additional hardware needs to be placed on the subject [ 13 ]. When utilized within an MPRAGE sequence, PROMO has been previously shown to reduce errors in cortical surface reconstructions [ 12 , 14 ], as well as remove bias in total gray matter volume and cortical thickness estimates for moving subjects [ 15 , 16 ]. Navigator-based PMC techniques can employ two strategies to improve image quality: 1) updating the gradients and RF pulses to ensure excitation and acquisition of the same brain slice/slab and imaging field-of-view (FOV) in every TR (hereafter referred to as ‘FOV-update’), and 2) reacquisition of k-space data in which excessive motion has occurred between navigators acquired immediately before and after a particular k-space segment (hereafter referred to as ‘Reacquisition’).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T

Sarlls

Lalonde

Rettmann³

et al. 2018

PLoS ONE

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In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images. Prospective motion correction (PMC) techniques have been developed to help mitigate artifacts due to subject motion. In this work, high-resolution MPRAGE images are acquired during intentional head motion to evaluate the effectiveness of navigator-based PMC techniques to improve both the accuracy and reproducibility of cortical morphometry measures obtained from image segmentation. The contribution of reacquiring segments of k-space affected by motion to the overall performance of PMC is assessed. Additionally, the effect of subject motion on subcortical structure volumes is investigated. In the presence of head motion, navigator-based PMC is shown to improve both the accuracy and reproducibility of cortical and subcortical measures. It is shown that reacquiring segments of k-space data that are corrupted by motion is an essential part of navigator-based PMC performance. Subcortical structure volumes are not affected by motion in the same way as cortical measures; there is not a consistent underestimation.

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Utility of real-time prospective motion correction (PROMO) for segmentation of cerebral cortex on 3D T1-weighted imaging: Voxel-based morphometry analysis for uncooperative patients

Abstract: • Motion artifacts pose significant problems for VBM analyses. • PROMO correction can reduce the motion artifacts in high-resolution 3D T1WI. • The use of PROMO may improve the precision of VBM analyses.

Cited by 6 publications

References 21 publications

The clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) for evaluation of uncooperative patients with brain diseases: comparison with the conventional T2-FLAIR with parallel imaging

The clinical feasibility of artificial intelligence-assisted compressed sensing single-shot fluid-attenuated inversion recovery (ACS-SS-FLAIR) for evaluation of uncooperative patients with brain diseases: comparison with the conventional T2-FLAIR with parallel imaging

Dissimilarity of functional connectivity uncovers the influence of participant's motion in functional magnetic resonance imaging studies

Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T

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