Bi-phase age-related brain gray matter magnetic resonance T1ρ relaxation time change in adults

Lǐ, Yáo T.; Huang, Hua; Zhuo, Zhizheng; Lu, Pu-Xuan; Chen, Weitian; Wáng, Yì Xiáng J.

doi:10.1016/j.mri.2017.03.005

Cited by 13 publications

(14 citation statements)

References 48 publications

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“…Moreover, the IVIM parameters were calculated based on the mean signal intensity of the whole ROI, which can offer better estimation than pixel-wise fitting in cases when the SNR is low. 10,11 With the full fitting method, all the parameters (D slow , D fast , PF and D' slow , D' fast , D' Vfast , F ' slow , F ' fast ) were estimated by a single least-squares nonlinear regression. For bi-exponential model segmented fitting, the threshold b-value was chosen to be b = 200 s/mm 2 .…”

Section: Methodsmentioning

confidence: 99%

“…Using ROI analysis, an R 2 value higher than 0.95 generally indicates good fit. 11,16,17 In addition to the IVIM parameter estimation based on individual scans, the measured signals at each b-value from the 50 scans were additionally averaged together; the averaged signals (total-averaged) were then fitted with the four approaches as they were from a single scan. 6,18 To…”

Section: Methodsmentioning

confidence: 99%

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Comparison of tri‐exponential decay versus bi‐exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

et al. 2019

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Objectives To determine whether bi‐ or tri‐exponential models, and full or segmented fittings, better fit the intravoxel incoherent motion (IVIM) imaging signal of healthy livers. Methods Diffusion‐weighted images were acquired with a 3 T scanner using a respiratory‐triggered echo‐planar sequence and 16 b‐values (0–800 s/mm2). Eighteen healthy volunteers had their livers scanned twice in the same session, and then once in another session. Liver parenchyma region‐of‐interest‐based measurements were processed with bi‐exponential and tri‐exponential models, with both full fitting and segmented fitting (threshold b‐value = 200 s/mm2). Results With the signal of all scans averaged, bi‐exponential model full fitting showed Dslow = 1.14 × 10−3 mm2/s, Dfast = 193.6 × 10−3 mm2/s, and perfusion fraction (PF) = 16.9%, and segmented fitting showed Dslow = 0.98 × 10−3 mm2/s, Dfast = 42.2 × 10−3 mm2/s, and PF = 23.3%. IVIM parameters derived from the tri‐exponential model were similar for full fitting and segmented fitting, with slow (D'slow = 0.98 × 10−3 mm2/s; F'slow = 76.4 or 76.6%), fast (D'fast = 15.1 or 15.4 × 10−3 mm2/s; F'fast = 11.8 or 11.7%) and very fast (D'Vfast = 445.0 or 448.8 × 10−3 mm2/s; F'Vfast = 11.8 or 11.7%) diffusion compartments. The tri‐exponential model provided an overall better fit than the bi‐exponential model. For the bi‐exponential model, full fitting provided a better fit at very low and low b‐values compared with segmented fitting, with the latter tending to underestimate Dfast; however, the segmented method demonstrated lower error in signal prediction for high b‐values. Compared with full fitting, tri‐exponential segmented fitting offered better scan‐rescan reproducibility. Conclusion For healthy liver, tri‐exponential modeling is preferred to bi‐exponential modeling. For the bi‐exponential model, segmented fitting underestimates Dfast, but offers a more accurate estimation of Dslow.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Comparison of tri‐exponential decay versus bi‐exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

et al. 2019

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“…For ROI analysis, the IVIM parameters were calculated based on the mean signal intensity of the whole ROI, which has been shown to offer better estimation than pixel-wise fitting when the signal-to-noise of the DW images is low. 30, 31…”

Section: Methodsmentioning

confidence: 99%

“…Regions-of-interest (ROIs) were positioned to cover a large portion of liver parenchyma while avoiding large vessels (Fig 1). For ROI analysis, the IVIM parameters were calculated based on the mean signal intensity of the whole ROI, which give better estimation than pixel-wise fitting when the signal-to-noise of the DW images is low [30, 31].…”

Section: Methodsmentioning

confidence: 99%

A combined use of intravoxel incoherent motion MRI parameters can differentiate early stage hepatitis-b fibrotic livers from healthy livers

Wáng

Deng

Lǐ

et al. 2017

Preprint

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This study investigated a combined use of IVIM parameters Dslow (D), PF (f) and Dfast (D*) for liver fibrosis evaluation. 16 healthy volunteers (F0) and 33 hepatitis-b patients (stage F1= 15, stage F2-4 = 18) were included. With a 1.5-T MR scanner and respiration-gating, IVIM diffusion weighted imaging was acquired using a single-shot echo-planar imaging sequence with ten b-values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm2. Signal measurement was performed on right liver parenchyma. With a 3-dimensional tool, Dslow, PF, and Dfast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate healthy volunteers from patients. 3-dimensional tool demonstrated healthy volunteers and all patients with liver fibrosis could be separated. Classification and Regression Tree showed a combination of PF (PF < 12.55%), Dslow (Dslow < 1.152 ×10−3 mm2/s) and Dfast (Dfast <13.36 ×10−3 mm2/s) could differentiate healthy subjects and all fibrotic livers (F1-F4) with an area under the curve of logistic regression (AUC) of 0.986. The AUC for differentiation of healthy livers vs. F2-4 livers was 1. PF offered the best diagnostic value, followed by Dslow; however, all three parameters of PF, Dslow, and Dfast contributed to liver fibrosis detection.

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“…All curve-fitting algorithms were implemented in a custom program developed on MatLab (Mathworks, Natick, MA, USA). For ROI analysis, the IVIM parameters were calculated based on the mean signal intensity of the whole ROI, which has been shown to offer better estimation than pixel-wise fitting when the signal-to-noise ratio (SNR) of the diffusion weighted images is low (8,9). The same as some other reports (10)(11)(12)(13)(14)(15)(16)(17)(18), only the right lobe of the liver was measured in the current study ( Fig.…”

Section: Methodsmentioning

confidence: 83%

IVIM parameters have good scan-rescan reproducibility when evidential motion contaminated and poorly fitted image data are removed

Chevallier¹,

Zhou²,

He³

et al. 2017

Preprint

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Bi-phase age-related brain gray matter magnetic resonance T1ρ relaxation time change in adults

Cited by 13 publications

References 48 publications

Comparison of tri‐exponential decay versus bi‐exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

Comparison of tri‐exponential decay versus bi‐exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

A combined use of intravoxel incoherent motion MRI parameters can differentiate early stage hepatitis-b fibrotic livers from healthy livers

IVIM parameters have good scan-rescan reproducibility when evidential motion contaminated and poorly fitted image data are removed

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