Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram

Purpose. The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered.Methods. Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line.Results. A consistent fitting of the histograms of all age groups was possible with the proposed model.Conclusions. This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

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Subarachnoid Hemorrhage in the Subacute Stage: Elevated Apparent Diffusion Coefficient in Normal-appearing Brain Tissue after Treatment

Radiology ◽

10.1148/radiol.2422051698 ◽

2007 ◽

Vol 242 (2) ◽

pp. 518-525 ◽

Cited By ~ 31

Author(s):

Yawu Liu ◽

Ville Soppi ◽

Timo Mustonen ◽

Mervi Könönen ◽

Timo Koivisto ◽

...

Keyword(s):

Diffusion Coefficient ◽

Subarachnoid Hemorrhage ◽

Apparent Diffusion Coefficient ◽

Brain Tissue ◽

Subacute Stage ◽

Apparent Diffusion

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Quantitative brain histogram of canine epilepsy using magnetic resonance imaging

Acta Radiologica ◽

10.1177/0284185120914031 ◽

2020 ◽

pp. 028418512091403

Author(s):

Somkiat Huaijantug ◽

Paranee Yatmark ◽

Phanupong Chinnabrut ◽

Nutruja Rueangsawat ◽

Avirut Wongkumlue ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Diffusion Coefficient ◽

Magnetic Resonance ◽

Apparent Diffusion Coefficient ◽

Diffusion Weighted Imaging ◽

Idiopathic Epilepsy ◽

Resonance Imaging ◽

Mr Images ◽

Apparent Diffusion ◽

The Brain

Background Quantitative magnetic resonance imaging (MRI) is used to study the anatomy of the brain in dogs with idiopathic epilepsy. Purpose To quantitate MRI images in terms of volumetric ratios and histogram analyses of the following regions of interest (ROI) in dogs with idiopathic epilepsy: frontal; parietal; temporal; piriform; thalamic; and hippocampal regions. Material and Methods Nine dogs with epilepsy and four healthy controls were evaluated. We examined the volumetric ratios and histogram analyses of six ROIs in all dogs. Results MR images, in T1-weighted, T2-weighted, FLAIR, diffusion-weighted imaging, and apparent diffusion coefficient sequences detected changes in 4/9 (44%) epileptic dogs found in 5/6 regions: frontal; parietal; temporal; piriform; and hippocampal regions. However, no such changes were observed in the thalamic region. Interestingly, the frontal and piriform volumetric ratios of epileptic dogs were significantly lower than those of control dogs. The histogram analyses in 4/6 regions were significantly increased in epileptic dogs. Conclusion Our results demonstrated MRI finding abnormalities in several regions of the brain in several sequences including T1-weighted, T2-weighted, FLAIR, diffusion-weighted imaging, and apparent diffusion coefficient in epileptic dogs. In several regions of the brain, atrophy may exist, and hyperintensity may be present on MR images in epileptic dogs. These findings suggest that the diagnostic yield of MRI, which is an advanced neuroimaging technique, is high in epileptic dogs and has good reliability and sensitivity in detecting abnormal areas in patients.

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Whole brain apparent diffusion coefficient histogram: A new tool for evaluation of leukoaraiosis

Journal of Magnetic Resonance Imaging ◽

10.1002/jmri.10050 ◽

2002 ◽

Vol 15 (2) ◽

pp. 144-148 ◽

Cited By ~ 24

Author(s):

Mario Mascalchi ◽

Carlo Tessa ◽

Marco Moretti ◽

Riccardo Della Nave ◽

Vieri Boddi ◽

...

Keyword(s):

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Whole Brain ◽

Apparent Diffusion

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Changes in Apparent Diffusion Coefficient ( ADC) during Cardiac Cycle of the Brain in Idiopathic Normal Pressure Hydrocephalus Before and After Cerebrospinal Fluid Drainage

Journal of Magnetic Resonance Imaging ◽

10.1002/jmri.27412 ◽

2020 ◽

Author(s):

Tomoshi Osawa ◽

Naoki Ohno ◽

Mitsuhito Mase ◽

Tosiaki Miyati ◽

Ryoko Omasa ◽

...

Keyword(s):

Cerebrospinal Fluid ◽

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Normal Pressure Hydrocephalus ◽

Cardiac Cycle ◽

Normal Pressure ◽

Cerebrospinal Fluid Drainage ◽

Before And After ◽

Apparent Diffusion ◽

The Brain

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Whole brain apparent diffusion coefficient measurements correlate with survival in glioblastoma patients

Journal of Neuro-Oncology ◽

10.1007/s11060-019-03357-y ◽

2019 ◽

Vol 146 (1) ◽

pp. 157-162 ◽

Cited By ~ 2

Author(s):

Aaron Michael Rulseh ◽

Josef Vymazal

Keyword(s):

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Disease Progression ◽

Cox Regression ◽

Primary Brain Tumor ◽

Whole Brain ◽

Early Detection Of Disease ◽

Regression Slope ◽

Apparent Diffusion ◽

Adc Values

Abstract Introduction Glioblastoma (GBM) is the most common malignant primary brain tumor, and methods to improve the early detection of disease progression and evaluate treatment response are highly desirable. We therefore explored changes in whole-brain apparent diffusion coefficient (ADC) values with respect to survival (progression-free [PFS], overall [OS]) in a cohort of GBM patients followed at regular intervals until disease progression. Methods A total of 43 subjects met inclusion criteria and were analyzed retrospectively. Histogram data were extracted from standardized whole-brain ADC maps including skewness, kurtosis, entropy, median, mode, 15th percentile (p15) and 85th percentile (p85) values, and linear regression slopes (metrics versus time) were fitted. Regression slope directionality (positive/negative) was subjected to univariate Cox regression. The final model was determined by aLASSO on metrics above threshold. Results Skewness, kurtosis, median, p15 and p85 were all below threshold for both PFS and OS and were analyzed further. Median regression slope directionality best modeled PFS (p = 0.001; HR 3.3; 95% CI 1.6–6.7), while p85 was selected for OS (p = 0.002; HR 0.29; 95% CI 0.13–0.64). Conclusions Our data show tantalizing potential in the use of whole-brain ADC measurements in the follow up of GBM patients, specifically serial median ADC values which correlated with PFS, and serial p85 values which correlated with OS. Whole-brain ADC measurements are fast and easy to perform, and free of ROI-placement bias.

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