Quantitative T1 mapping and absolute water content measurement using MRI

Repository of MRI-derived models of the breast with single and multiple benign and malignant tumors for microwave imaging research

The diagnosis of breast cancer through MicroWave Imaging (MWI) technology has been extensively researched over the past few decades. However, continuous improvements to systems are needed to achieve clinical viability. To this end, the numerical models employed in simulation studies need to be diversified, anatomically accurate, and also representative of the cases in clinical settings. Hence, we have created the first open-access repository of 3D anatomically accurate numerical models of the breast, derived from 3.0T Magnetic Resonance Images (MRI) of benign breast disease and breast cancer patients. The models include normal breast tissues (fat, fibroglandular, skin, and muscle tissues), and benign and cancerous breast tumors. The repository contains easily reconfigurable models which can be tumor-free or contain single or multiple tumors, allowing complex and realistic test scenarios needed for feasibility and performance assessment of MWI devices prior to experimental and clinical testing. It also includes an executable file which enables researchers to generate models incorporating the dielectric properties of breast tissues at a chosen frequency ranging from 3 to 10 GHz, thereby ensuring compatibility with a wide spectrum of research requirements and stages of development for any breast MWI prototype system. Currently, our dataset comprises MRI scans of 55 patients, but new exams will be continuously added.

A Novel MRI-Based Quantitative Water Content Atlas of the Human Brain

The measurement of quantitative, tissue-specific MR properties, e.g., water content, longitudinal relaxation time (T₁) and effective transverse relaxation time (T₂*), using quantitative MRI at a clinical field strength (1.5 T to 3T) is a well-explored topic. However, none of the commonly used standard brain atlases, such as MNI or JHU, provide quantitative information. Within the framework of quantitative MRI of the brain, this work reports on the development of the first quantitative brain atlas for tissue water content at 3T. A methodology to create this quantitative atlas of in vivo brain water content based on healthy volunteers is presented, and preliminary, practical examples of its potential applications are also shown. Established methods for the fast and reliable measurement of the absolute water content were used to achieve high precision and accuracy. Water content and T₂* were mapped based on two different methods: an intermediate-TR, two-point method and a long-TR, single-scan method. Twenty healthy subjects (age 25.3 ± 2.5 years) were examined with these quantitative imaging protocols. The images were normalised to MNI stereotactic coordinates, and water content atlases of healthy volunteers were created for each method and compared. Regions-of-interest were generated with the help of a standard MNI template, and water content values averaged across the ROIs were compared to water content values from the literature. Finally, in order to demonstrate the strength of quantitative MRI, water content maps from patients with pathological changes in the brain due to stroke, tumour (glioblastoma) and multiple sclerosis were voxel-wise compared to the healthy brain. The water content atlases were largely independent of the method used to acquire the individual water maps. Global grey matter and white matter water content values between the methods agreed with each other to within 0.5 %. The feasibility of detecting abnormal water content in the brains of patients based on comparison to a healthy brain water content atlas was demonstrated. In summary, the first quantitative water content brain atlas in vivo has been developed and a voxel-wise assessment of pathology-related changes in the brain water content has been performed. These results suggest that qMRI, in combination with a water content atlas, allows for a quantitative interpretation of changes due to disease and could be used for disease monitoring.

A robust method for the detection of small changes in relaxation parameters and free water content in the vicinity of the substantia nigra in Parkinson's disease patients

Alterations in the substantia nigra are strongly associated with Parkinson's disease. However, due to low contrast and partial volume effects present in typical MRI images, the substantia nigra is not of sufficient size to obtain a reliable segmentation for region-of-interest based analysis. To combat this problem, the approach proposed here offers a method to investigate and reveal changes in quantitative MRI parameters in the vicinity of substantia nigra without any a priori delineation. This approach uses an alternative method of statistical, voxel-based analysis of quantitative maps and was tested on 18 patients and 15 healthy controls using a well-established, quantitative free water mapping protocol. It was possible to reveal the topology and the location of pathological changes in the substantia nigra and its vicinity. Moreover, a decrease in free water content, T1 and T2* in the vicinity of substantia nigra was indicated in the Parkinson's disease patients compared to the healthy controls. These findings reflect a disruption of grey matter and iron accumulation, which is known to lead to neurodegeneration. Consequently, the proposed method demonstrates an increased sensitivity for the detection of pathological changes-even in small regions-and can facilitate disease monitoring via quantitative MR parameters.

Cortical quantitative MRI parameters are related to the cognitive status in patients with relapsing-remitting multiple sclerosis

OBJECTIVES

We aimed to assess cortical damage in patients with relapsing-remitting multiple sclerosis (RRMS)/clinically isolated syndrome (CIS) with a multiparametric, surface-based quantitative MRI (qMRI) approach and to evaluate the correlation of imaging-derived parameters with cognitive scores, hypothesizing that qMRI parameters are correlated with cognitive abilities.

METHODS

Multiparametric qMRI-data (T1, T2 and T2* relaxation times and proton density (PD)) were obtained from 34 patients/24 matched healthy control subjects. Cortical qMRI values were analyzed on the reconstructed cortical surface with Freesurfer. We tested for group differences of cortical microstructural parameters between the healthy and patient collectives and for partial Pearson correlations of qMRI parameters with cognitive scores, correcting for age.

RESULTS

Cortical T2-/T2*-/PD values and four cognitive parameters differed between groups (p ≤ 0.046). These cognitive scores, reflecting information processing speed, verbal memory, visuospatial abilities, and attention, were correlated with cortical T2 (p ≤ 0.02) and T2* (p ≤ 0.03). Cortical changes appeared heterogeneous across the cortex and their distribution differed between the parameters. Vertex-wise correlation of T2 with neuropsychological parameters revealed specific patterns of cortical damage being related to distinct cognitive deficits.

CONCLUSIONS

Microstructural changes are distributed heterogeneously across the cortex in RRMS/CIS. QMRI has the potential to provide surrogate parameters for the assessment of cognitive impairment in these patients for clinical studies. The characteristics of cognitive impairment in RRMS might depend on the distribution of cortical changes.

KEY POINTS

• The goal of the presented study was to investigate cortical changes in RRMS/CIS and their relation to the cognitive status, using multiparametric quantitative MRI. • Cortical T2, T2*, and PD increases observed in patients appeared heterogeneous across the cortex and their distribution differed between the parameters. • Vertex-wise correlation of T2 with neuropsychological scores revealed specific patterns of cortical changes being related to distinct cognitive deficits.

Brain metabolism in patients with hepatic encephalopathy studied by PET and MR

We review PET- and MR studies on hepatic encephalopathy (HE) metabolism in human subjects from the point of views of methods, methodological assumptions and use in studies of cirrhotic patients with clinically overt HE, cirrhotic patients with minimal HE, cirrhotic patients with no history of HE and healthy subjects. Key results are: (1) Cerebral oxygen uptake and blood flow are reduced to 2/3 in cirrhotic patients with clinically overt HE but not in cirrhotic patients with minimal HE or no HE compared to healthy subjects. (2) Cerebral ammonia metabolism is enhanced due to increased blood ammonia in cirrhotic patients but the kinetics of cerebral ammonia uptake and metabolism is not affected by hyperammonemia. (3) Recent advantages in MR demonstrate low-grade cerebral oedema not only in astrocytes but also in the white matter in cirrhotic patients with HE.

Quantitative cerebral water content mapping in hepatic encephalopathy

There is increasing evidence that the pathophysiology of hepatic encephalopathy is tightly associated with low-grade cerebral oedema; however, no method has yet specifically and unambiguously confirmed this hypothesis in vivo. The current study describes the quantitative measurement of localised water content using MRI in a cohort of 38 patients suffering from hepatic encephalopathy. A significant global increase in cerebral water content was observed in white matter whereas water content in grey matter was globally unaffected. However, significant spatial variations in the water content distribution, especially in grey matter, were observed and were correlated with disease grade and critical flicker frequency. In addition, regions-of-interest were defined and a significant change in water content with disease grade was found in the frontal and occipital white matter, the globus pallidus, the anterior limb of the internal capsule and the putamen. No association of water content and HE grade was established for the occipital visual and frontal cortices, the thalamus, the posterior limb of the internal capsule, the caudate nucleus and the coronal white matter. In conclusion, the measurements presented here are the first direct and quantitative demonstration of the presence of low-grade cerebral oedema in patients with hepatic encephalopathy. Further, absolute changes in tissue water content were quantified for various brain regions.

A new method for fast quantitative mapping of absolute water content in vivo

The presence of brain edema, in its various forms, is an accompanying feature of many diseased states. Although the localized occurrence of brain edema may be demonstrated with MRI, the quantitative determination of absolute water content, an aspect that could play an important role in the objective evaluation of the dynamics of brain edema and the monitoring of the efficiency of treatment, is much more demanding. We present a method for the localized and quantitative measurement of absolute water content based on the combination of two fast multi-slice and multi-time point sequences QUTE and TAPIR for mapping the T(2)* and T(1) relaxation times, respectively. Incorporation of corrections for local B(1) field miscalibrations, temperature differences between the subject and a reference probe placed in the FOV, receiver profile inhomogeneities and T(1) saturation effects are included and allow the determination of water content with anatomical resolution and a precision >98%. The method was validated in phantom studies and was applied to the localized in vivo measurement of water content in a group of normal individuals and a patient with brain tumor. The results demonstrate that in vivo measurement of regional absolute water content is possible in clinically relevant measurement times with a statistical and systematic measurement error of <2%.

Fully-automated detection of cerebral water content changes: Study of age- and gender-related H2O patterns with quantitative MRI

We present a simple and robust method for the automated image analysis of quantitative cerebral water content maps acquired with MRI. The method is based on a new approach for the absolute and quantitative mapping of water content in vivo. Water content maps were automatically segmented into grey and white matter by employing the quantitative T1 information acquired as part of the water content mapping procedure. Based on the segmented maps, twenty-two parameters sensitive to both absolute water content and its spatial organisation are automatically extracted without user interaction. The parameters include, amongst others, absolute water content in grey and white matter and spatial asymmetries of the cerebral water content distribution. Significant age- and gender-related changes in the parameters determined were observed in a study of forty-four healthy subjects. Most notably, the grey matter water content decreases at a rate of 0.034%/year for females between the 3rd and 8th decade of life, whilst a much stronger decrease is observed in males which sets in after the 5th decade of life. In addition, female grey matter water content is, on average, 1.2% higher than the respective male grey matter water content. In contrast to the heterogeneity observed in grey matter, no significant physiological variation was observed for white matter water content. In addition to absolute grey matter water content, characteristic age- and gender-specific variations were also observed in most of the other variables. To check the potential loss of information associated with the large reduction of the dimensionality of the dataset to 22 parameters only, the age and gender of each individual subject were predicted by employing robust linear discriminant analysis based on only the determined twenty-two variables. The median deviation between predicted and real age was 6.3 years resulting in a high correlation coefficient between both values (r = 0.69). Gender is correctly predicted in 68.2% of all cases which improves to 87.5% when age-dependent effects are first corrected, demonstrating the high information content present in the variables even though the dimension of the dataset was significantly reduced. These results form the baseline for future studies of cerebral pathology. The method presented is fully automated, robust and flexible, making it an ideal tool for routine application in both neuroscientific studies and clinical diagnosis based on the quantitative measurement of cerebral water content.