Role of T1 mapping to evaluate brain aging in a healthy population

Küpeli, Ali; Koçak, Mehmet; Göktepeli, Mehmet; Karavaş, Erdal; Danışan, Gürkan

doi:10.1016/j.clinimag.2019.09.005

Cited by 15 publications

(13 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is a gain compared to conventional methods such as FLAIR or

T_{2}

‐weighted images. We found no significant increase in

T_{1}

and

T_{2}^{*}

with either age or gender, although a number of studies demonstrated that

T_{1}

does change with age 57,58 . This might be due to the smaller number of subjects since we split between the healthy and diseased subjects and the narrow age range, especially for the healthy subjects.…”

Section: Discussioncontrasting

confidence: 69%

“…We found no significant increase in T 1 and T * 2 with either age or gender, although a number of studies demonstrated that T 1 does change with age. 57,58 This might be due to the smaller number of subjects since we split between the healthy and diseased subjects and the narrow age range, especially for the healthy subjects. Further analysis of this might be performed when more subjects are measured.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Accelerated white matter lesion analysis based on simultaneous T₁ and T₂^∗ quantification using magnetic resonance fingerprinting and deep learning

Hermann

Martínez‐Heras

Rieger

et al. 2021

Magnetic Resonance in Med

View full text Add to dashboard Cite

show abstract

“…This is a gain compared to conventional methods such as FLAIR or

T_{2}

‐weighted images. We found no significant increase in

T_{1}

and

T_{2}^{*}

with either age or gender, although a number of studies demonstrated that

T_{1}

Section: Discussioncontrasting

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Accelerated white matter lesion analysis based on simultaneous T₁ and T₂^∗ quantification using magnetic resonance fingerprinting and deep learning

Hermann

Martínez‐Heras

Rieger

et al. 2021

Magnetic Resonance in Med

View full text Add to dashboard Cite

show abstract

“…overlap with pathologies such as inflammation and edema [5]. On the other hand, and despite these limitations, a diagnostic benefit of quantitative T1 mapping of the brain has been convincingly demonstrated for a number of conditions, including hepatic encephalopathy [6], multiple sclerosis [7][8][9], sickle cell anemia [10], epilepsy [11], heavy metal deposition [12], neurofibromatosis [13], brain tumor follow-up [14,15], infantile brain development [16][17][18] and aging [19]. The continuing desire for a viable quantitative MR sequence is also reflected in the multitude of recent faster mapping approaches, such as the MP2RAGE sequence [20], synthetic MRI [21] and MR fingerprinting [22].…”

Section: Introductionmentioning

confidence: 99%

Quantitative T1 mapping of the normal brain from early infancy to adulthood

Gräfe¹,

Frahm

Merkenschlager

et al. 2020

Pediatr Radiol

View full text Add to dashboard Cite

Background Quantitative mapping of MRI relaxation times is expected to uncover pathological processes in the brain more subtly than standard MRI techniques with weighted contrasts. So far, however, most mapping techniques suffer from a long measuring time, low spatial resolution or even sensitivity to magnetic field inhomogeneity. Objective To obtain T1 relaxation times of the normal brain from early infancy to adulthood using a novel technique for fast and accurate T1 mapping at high spatial resolution. Materials and methods We performed whole-brain T1 mapping within less than 3 min in 100 patients between 2 months and 18 years of age with normal brain at a field strength of 3 T. We analyzed T1 relaxation times in several gray-matter nuclei and white matter. Subsequently, we derived regression equations for mean value and confidence interval. Results T1 relaxation times of the pediatric brain rapidly decrease in all regions within the first 3 years of age, followed by a significantly weaker decrease until adulthood. These characteristics are more pronounced in white matter than in deep gray matter. Conclusion Regardless of age, quantitative T1 mapping of the pediatric brain is feasible in clinical practice. Normal age-dependent values should contribute to improved discrimination of subtle intracerebral alterations.

show abstract

“…Recent studies indicated that the characterization of these processes could be realized using quantitative MRI biomarkers of brain tissue microstructure [9,10]. Quantitative MR techniques have been used to study multiple central nervous system conditions by providing useful information for assessing diseases' microscopic biophysical processes [11][12][13]. However, so far, no studies have explored T1, T2 relaxation times of the brain pathophysiology in ADHD, where brain microstructure abnormalities could potentially be uncovered.…”

Section: Introductionmentioning

confidence: 99%

“…Myelin has a key role in brain microarchitectural changes. Quantitative MRI parameters provide well-de ned physical parameters and can be applied to estimate the human brain's development [13,14]. Speci cally, the T1 relaxation time is affected by myelin, water, and iron concentrations in brain tissue; myelin content affects the T1 value, and iron de ciency prolongs the T1 value [14].…”

Section: Introductionmentioning

confidence: 99%

Quantitative MRI Reveals Grey Matter Abnormalities in Children With Drug-Naïve Attention-Deficit/Hyperactivity Disorder

Chen

Dai

et al. 2021

Preprint

View full text Add to dashboard Cite

Purpose To investigate the quantitative profiles of brain GM in pediatric drug-naïve ADHD patients using Synthetic magnetic resonance imaging (SyMRI). Method and Materials: A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Results Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.1401, P = 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.2509, P = 0.0016), and right cerebellum crus2 (R = 0.1422, P = 0.0214). Conclusion Altered T1, T2 values found in specific regions of GM may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies.

show abstract

Role of T1 mapping to evaluate brain aging in a healthy population

Cited by 15 publications

References 27 publications

Accelerated white matter lesion analysis based on simultaneous T₁ and T₂^∗ quantification using magnetic resonance fingerprinting and deep learning

Accelerated white matter lesion analysis based on simultaneous T₁ and T₂^∗ quantification using magnetic resonance fingerprinting and deep learning

Quantitative T1 mapping of the normal brain from early infancy to adulthood

Quantitative MRI Reveals Grey Matter Abnormalities in Children With Drug-Naïve Attention-Deficit/Hyperactivity Disorder

Contact Info

Product

Resources

About

Role of T1 mapping to evaluate brain aging in a healthy population

Cited by 15 publications

References 27 publications

Accelerated white matter lesion analysis based on simultaneous T1 and T2∗ quantification using magnetic resonance fingerprinting and deep learning

Accelerated white matter lesion analysis based on simultaneous T1 and T2∗ quantification using magnetic resonance fingerprinting and deep learning

Quantitative T1 mapping of the normal brain from early infancy to adulthood

Quantitative MRI Reveals Grey Matter Abnormalities in Children With Drug-Naïve Attention-Deficit/Hyperactivity Disorder

Contact Info

Product

Resources

About

Accelerated white matter lesion analysis based on simultaneous T₁ and T₂^∗ quantification using magnetic resonance fingerprinting and deep learning

Accelerated white matter lesion analysis based on simultaneous T₁ and T₂^∗ quantification using magnetic resonance fingerprinting and deep learning