Development and evaluation of a high resolution 0.5mm isotropic T1-weighted template of the older adult brain

Niaz, Mohammad Rakeen; Ridwan, Abdur Raquib; Wu, Yingjuan; Initiative, Alzheimer’s Disease Neuroimaging; Bennett, David A.; Arfanakis, Konstantinos

doi:10.1016/j.neuroimage.2021.118869

Cited by 8 publications

(3 citation statements)

References 78 publications

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“…A simplified approximation to SR can be achieved through repeated multi‐resolution registration as implemented in the Advanced Normalization Tools (ANTS) multivariate template construction tool 29 as described in Ref. [30]. Here, the low‐resolution images are aligned using linear and diffeomorphic registration with symmetric normalization.…”

Section: Methodsmentioning

confidence: 99%

Simultaneous high‐resolution T₂‐weighted imaging and quantitative T₂ mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Deoni

O’Muircheartaigh

Ljungberg

et al. 2022

Magnetic Resonance in Med

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Purpose: Low magnetic field systems provide an important opportunity to expand MRI to new and diverse clinical and research study populations. However, a fundamental limitation of low field strength systems is the reduced SNR compared to 1.5 or 3T, necessitating compromises in spatial resolution and imaging time. Most often, images are acquired with anisotropic voxels with low through-plane resolution, which provide acceptable image quality with reasonable scan times, but can impair visualization of subtle pathology. Methods: Here, we describe a super-resolution approach to reconstruct high-resolution isotropic T 2 -weighted images from a series of low-resolution anisotropic images acquired in orthogonal orientations. Furthermore, acquiring each image with an incremented TE allows calculations of quantitative T 2 images without time penalty. Results: Our approach is demonstrated via phantom and in vivo human brain imaging, with simultaneous 1.5 × 1.5 × 1.5 mm 3 T 2 -weighted and quantitative T 2 maps acquired using a clinically feasible approach that combines three acquisition that require approximately 4-min each to collect. Calculated T 2 values agree with reference multiple TE measures with intraclass correlation values of 0.96 and 0.85 in phantom and in vivo measures, respectively, in line with previously reported brain T 2 values at 150 mT, 1.5T, and 3T. Conclusion: Our multi-orientation and multi-TE approach is a time-efficient method for high-resolution T 2 -weighted images for anatomical visualization with simultaneous quantitative T 2 imaging for increased sensitivity to tissue microstructure and chemical composition.

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Section: Methodsmentioning

confidence: 99%

Simultaneous high‐resolution T₂‐weighted imaging and quantitative T₂ mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Deoni

O’Muircheartaigh

Ljungberg

et al. 2022

Magnetic Resonance in Med

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show abstract

“…For all the analyses, we added age, sex, education, handedness, and mean FD as covariates. Finally, the Z-threshold maps were further resampled to a 0.5 mm resolution version of the MIITRA template ( Niaz et al, 2022 ).…”

Section: Methodsmentioning

confidence: 99%

Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults

Iandolo,

Avci,

Bommarito

et al. 2024

NeuroImage: Clinical

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“…In recent years, with the development of deep learning (DL), SR has achieved superior performance in medical imaging [26]. As for its application in MRI examinations, Masutani et al [27] proposed a novel convolutional neural network (CNN) model which optimized high-frequency spatial detail in short-axis cardiac MRI imaging; in the work named SCSRN, Niaz et al [28] reported that DL-SR algorithms improved the image quality for brain morphology diagnosis. Apart from the good stability and reliability the recovered SR images showed in the multi-spaceladder, DL-SR has attracted attention in medical imaging because the radiomics features extracted from SR images were quantitatively proven to be remarkably reproducible and robust [24].…”

Section: Introductionmentioning

confidence: 99%

Deep-learning-based 3D super-resolution MRI radiomics model: superior predictive performance in preoperative T-staging of rectal cancer

2022

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Objectives To investigate the feasibility and efficacy of a deep-learning (DL)-based three-dimensional (3D) super-resolution (SR) MRI radiomics model for preoperative T-staging prediction in rectal cancer (RC). Methods Seven hundred six eligible RC patients (T1/2 = 287, T3/4 = 419) were retrospectively enrolled in this study and chronologically allocated into a training cohort (n = 565) and a validation cohort (n = 141). We conducted a deep-transfer-learning network on high-resolution (HR) T2-weighted imaging (T2WI) to enhance the z-resolution of the images and acquired the preoperative SRT2WI. The radiomics models named modelHRT2 and modelSRT2 were respectively constructed with high-dimensional quantitative features extracted from manually segmented volume of interests of HRT2WI and SRT2WI through the Least Absolute Shrinkage and Selection Operator method. The performances of the models were evaluated by ROC, calibration, and decision curves. Results ModelSRT2 outperformed modelHRT2 (AUC 0.869, sensitivity 71.1%, specificity 93.1%, and accuracy 83.3% vs. AUC 0.810, sensitivity 89.5%, specificity 70.1%, and accuracy 77.3%) in distinguishing T1/2 and T3/4 RC with significant difference (p < 0.05). Both radiomics models achieved higher AUCs than the expert radiologists (0.685, 95% confidence interval 0.595–0.775, p < 0.05). The calibration curves confirmed high goodness of fit, and the decision curve analysis revealed the clinical value. Conclusions ModelSRT2 yielded superior predictive performance in preoperative RC T-staging by comparison with modelHRT2 and expert radiologists’ visual assessments. Key Points • For the first time, DL-based 3D SR images were applied in radiomics analysis for clinical utility. • Compared with the visual assessment of expert radiologists and the conventional radiomics model based on HRT2WI, the SR radiomics model showed a more favorable capability in helping clinicians assess the invasion depth of RC preoperatively. • This is the largest radiomics study for T-staging prediction in RC.

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Development and evaluation of a high resolution 0.5mm isotropic T1-weighted template of the older adult brain

Cited by 8 publications

References 78 publications

Simultaneous high‐resolution T₂‐weighted imaging and quantitative T₂ mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Simultaneous high‐resolution T₂‐weighted imaging and quantitative T₂ mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults

Deep-learning-based 3D super-resolution MRI radiomics model: superior predictive performance in preoperative T-staging of rectal cancer

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Development and evaluation of a high resolution 0.5mm isotropic T1-weighted template of the older adult brain

Cited by 8 publications

References 78 publications

Simultaneous high‐resolution T2‐weighted imaging and quantitative T2 mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Simultaneous high‐resolution T2‐weighted imaging and quantitative T2 mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults

Deep-learning-based 3D super-resolution MRI radiomics model: superior predictive performance in preoperative T-staging of rectal cancer

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Simultaneous high‐resolution T₂‐weighted imaging and quantitative T₂ mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach

Simultaneous high‐resolution T₂‐weighted imaging and quantitative T₂ mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach