IGUANe: A 3D generalizable CycleGAN for multicenter harmonization of brain MR images

In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances sample size but may introduce site-related variabilities that hinder consistency in subsequent analyses. Deep learning methods for image translation have emerged as a solution for harmonizing MR images across sites. In this study, we introduce IGUANe (Image Generation with Unified Adversarial Networks), an original 3D model that leverages the strengths of domain translation and straightforward application of style transfer methods for multicenter brain MR image harmonization. IGUANe extends CycleGAN by integrating an arbitrary number of domains for training through a many-to-one architecture. The framework based on domain pairs enables the implementation of sampling strategies that prevent confusion between site-related and biological variabilities. During inference, the model can be applied to any image, even from an unknown acquisition site, making it a universal generator for harmonization. Trained on a dataset comprising T1-weighted images from 11 different scanners, IGUANe was evaluated on data from unseen sites. The assessments included the transformation of MR images with traveling subjects, the preservation of pairwise distances between MR images within domains, the evolution of volumetric patterns related to age and Alzheimer's disease (AD), and the performance in age regression and patient classification tasks. Comparisons with other harmonization and normalization methods suggest that IGUANe better preserves individual information in MR images and is more suitable for maintaining and reinforcing variabilities related to age and AD. Future studies may further assess IGUANe in other multicenter contexts, either using the same model or retraining it for applications to different image modalities. Codes and the trained IGUANe model are available at https://github.com/RocaVincent/iguane_harmonization.git.

Sex differences in normal fetal regional brain apparent diffusion coefficient changes assessed by in utero DWI

Objective

There are differences in the vulnerability of male and female fetal brains to adverse intrauterine exposure, preterm birth, and associated perinatal brain injury. The main objective of this study was to identify any statistically significant difference in the change of apparent diffusion coefficient (ADC) in the intracranial regions of male and female fetuses in the second and third trimesters.

Methods

Diffusion-weighted imaging (DWI) was performed in 200 fetuses between 20 and 37 gestational ages (GA) with normal results or suspicious results on sonography followed by structural MRI. Pairwise ADC values of the regions of interest (ROIs) were manually delineated on either side of the cerebral white matter: frontal white matter (FWM), parietal white matter (PWM), occipital white matter (OWM), temporal white matter (TWM), basal ganglia (BG), thalamus (THA), cerebellar hemisphere (CBM), and a single measurement in the pons. The changes in these values were studied over the gestational range, along with potential sex differences and asymmetries of the cerebral hemispheres.

Results

During the third trimester, ADC values in OWM, TWM, and CBM were significantly higher in male fetuses than those in female fetuses (p < 0.05). After the correction of false-discovery rates (FDR), the difference in CBM was the only statistically significant (p = 0.0032). However, the decreased rate of ADC values in male fetuses in CWM (except for FWM), BG, THA, CBM, and pons was higher than that in female fetuses during the second and third trimesters.

Conclusions

We have shown some differences in the intracranial regional ADC changes between male and female fetuses using in utero DWI during the second and third trimesters.

A three-dimensional deep learning model for inter-site harmonization of structural MR images of the brain: Extensive validation with a multicenter dataset

In multicenter MRI studies, pooling the imaging data can introduce site-related variabilities and can therefore bias the subsequent analyses. To harmonize the intensity distributions of brain MR images in a multicenter dataset, unsupervised deep learning methods can be employed. Here, we developed a model based on cycle-consistent adversarial networks for the harmonization of T1-weighted brain MR images. In contrast to previous works, it was designed to process three-dimensional whole-brain images in a stable manner while optimizing computation resources. Using six different MRI datasets for healthy adults (n=1525 in total) with different acquisition parameters, we tested the model in (i) three pairwise harmonizations with site effects of various sizes, (ii) an overall harmonization of the six datasets with different age distributions, and (iii) a traveling-subject dataset. Our results for intensity distributions, brain volumes, image quality metrics and radiomic features indicated that the MRI characteristics at the various sites had been effectively homogenized. Next, brain age prediction experiments and the observed correlation between the gray-matter volume and age showed that thanks to an appropriate training strategy and despite biological differences between the dataset populations, the model reinforced biological patterns. Furthermore, radiologic analyses of the harmonized images attested to the conservation of the radiologic information in the original images. The robustness of the harmonization model (as judged with various datasets and metrics) demonstrates its potential for application in retrospective multicenter studies.

FreeSurfer based cortical mapping and T1-relaxometry with MPnRAGE: Test-retest reliability with and without retrospective motion correction

A test-retest study of FreeSurfer derived cortical thickness, cortical surface area, and cortical volume, as well as quantitative R1 relaxometry assessed on the midpoint of the cortex, was performed on a cohort of pediatric subjects (6-12 years old) scanned without sedation using SNARE-MPnRAGE (self navigated retrospective motion corrected magnetization prepared with n rapid gradient echoes) imaging. Reliability was assessed with coefficients of variation (CoVs) and intraclass correlation coefficients (ICCs) and statistical tests were used to determine differences with and without SNARE motion correction. Comparison of the test-retest measures of SNARE-MPnRAGE with prospectively motion corrected PROMO MPRAGE were also performed. When SNARE motion correction was used all parameters had statistically significant improvements and demonstrated high reliability. Reliability varied depending on parameter, region, and measurement type (vertex or region of interest). For mean thickness/surface area/volume/mean R1 across the regions of FreeSurfer's DK Atlas, the mean CoVs (% x100) were (1.2/1.6/1.9/0.9) and the mean ICCs were (0.88/0.96/0.94/0.83). When assessed on a per-vertex basis, the CoVs and ICCs for thickness/R1 had mean values of (2.9/1.9) and (0.82/0.68) across the regions of the DK Atlas. Retrospectively motion corrected MPnRAGE had significantly lower CoVs and higher ICCs for the morphological measures than PROMO MPRAGE. Motion correction effectively removed motion related biases in nearly all regions for R1 and morphometric measures.

Brain Magnetic Resonance Imaging Reveals Different Courses of Disease in Pediatric and Adult Cerebral Malaria

BACKGROUND

Cerebral malaria is a common presentation of severe Plasmodium falciparum infection and remains an important cause of death in the tropics. Key aspects of its pathogenesis are still incompletely understood, but severe brain swelling identified by magnetic resonance imaging (MRI) was associated with a fatal outcome in African children. In contrast, neuroimaging investigations failed to identify cerebral features associated with fatality in Asian adults.

METHODS

Quantitative MRI with brain volume assessment and apparent diffusion coefficient (ADC) histogram analyses were performed for the first time in 65 patients with cerebral malaria to compare disease signatures between children and adults from the same cohort, as well as between fatal and nonfatal cases.

RESULTS

We found an age-dependent decrease in brain swelling during acute cerebral malaria, and brain volumes did not differ between fatal and nonfatal cases across both age groups. In nonfatal disease, reversible, hypoxia-induced cytotoxic edema occurred predominantly in the white matter in children, and in the basal ganglia in adults. In fatal cases, quantitative ADC histogram analyses also demonstrated different end-stage patterns between adults and children: Severe hypoxia, evidenced by global ADC decrease and elevated plasma levels of lipocalin-2 and microRNA-150, was associated with a fatal outcome in adults. In fatal pediatric disease, our results corroborate an increase in brain volume, leading to augmented cerebral pressure, brainstem herniation, and death.

CONCLUSIONS

Our findings suggest distinct pathogenic patterns in pediatric and adult cerebral malaria with a stronger cytotoxic component in adults, supporting the development of age-specific adjunct therapies.

A Cross-Sectional Study on the Impact of Arterial Stiffness on the Corpus Callosum, a Key White Matter Tract Implicated in Alzheimer's Disease

BACKGROUND

Vascular risk factors such as arterial stiffness play an important role in the etiology of Alzheimer's disease (AD), presumably due to the emergence of white matter lesions. However, the impact of arterial stiffness to white matter structure involved in the etiology of AD, including the corpus callosum remains poorly understood.

OBJECTIVE

The aims of the study are to better understand the relationship between arterial stiffness, white matter microstructure, and perfusion of the corpus callosum in older adults.

METHODS

Arterial stiffness was estimated using the gold standard measure of carotid-femoral pulse wave velocity (cfPWV). Cognitive performance was evaluated with the Trail Making Test part B-A. Neurite orientation dispersion and density imaging was used to obtain microstructural information such as neurite density and extracellular water diffusion. The cerebral blood flow was estimated using arterial spin labelling.

RESULTS

cfPWV better predicts the microstructural integrity of the corpus callosum when compared with other index of vascular aging (the augmentation index, the systolic blood pressure, and the pulse pressure). In particular, significant associations were found between the cfPWV, an alteration of the extracellular water diffusion, and a neuronal density increase in the body of the corpus callosum which was also correlated with the performance in cognitive flexibility.

CONCLUSION

Our results suggest that arterial stiffness is associated with an alteration of brain integrity which impacts cognitive function in older adults.

Longitudinal quantification of metabolites and macromolecules reveals age- and sex-related changes in the healthy Fischer 344 rat brain

Normal aging is associated with numerous biological changes, including altered brain metabolism and tissue chemistry. In vivo characterization of the neurochemical profile during aging is possible using magnetic resonance spectroscopy, a powerful noninvasive technique capable of quantifying brain metabolites involved in physiological processes that become impaired with age. A prominent macromolecular signal underlies those of brain metabolites and is particularly visible at high fields; parameterization of this signal into components improves quantification and expands the number of biomarkers comprising the neurochemical profile. The present study reports, for the first time, the simultaneous absolute quantification of brain metabolites and individual macromolecules in aging male and female Fischer 344 rats, measured longitudinally using proton magnetic resonance spectroscopy at 7 T. We identified age- and sex-related changes in neurochemistry, with prominent differences in metabolites implicated in anaerobic energy metabolism, antioxidant defenses, and neuroprotection, as well as numerous macromolecule changes. These findings contribute to our understanding of the neurobiological processes associated with healthy aging, critical for the proper identification and management of pathologic aging trajectories. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Three-dimensional motion-corrected T1 relaxometry with MPnRAGE

PURPOSE

To test the performance of the MPnRAGE motion-correction algorithm on quantitative relaxometry estimates.

METHODS

Twelve children (9.4 ± 2.6 years, min = 6.5 years, max = 13.8 years) were imaged 3 times in a session without sedation. Stabilization padding was not used for the second and third scans. Quantitative T1 values were estimated in each voxel on images reconstructed with and without motion correction. Mean T1 values were assessed in various regions determined from automated segmentation algorithms. Statistical tests were performed on mean values and the coefficient of variation across the measurements. Accuracy of T1 estimates were determined by scanning the High Precision Devices (Boulder, CO) MRI system phantom with the same protocol.

RESULTS

The T1 values obtained with MPnRAGE agreed within 4% of the reference values of the High Precision Devices phantom. The best fit line was T1 (MPnRAGE) = 1.02 T1 (reference)-0.9 ms, R2  = 0.9999. For in vivo studies, motion correction reduced the coefficients of variation of mean T1 values in whole-brain tissue regions determined by FSL FAST by 74% ± 7%, and subcortical regions determined by FIRST and FreeSurfer by 32% ± 21% and 33% ± 26%, respectively. Across all participants, the mean coefficients of variation ranged from 0.8% to 2.0% for subcortical regions and 0.6% ± 0.5% for cortical regions when motion correction was applied.

CONCLUSION

The MPnRAGE technique demonstrated highly accurate values in phantom measurements. When combined with retrospective motion correction, MPnRAGE demonstrated highly reproducible T1 values, even in participants who moved during the acquisition.

Test-retest of automated segmentation with different motion correction strategies: A comparison of prospective versus retrospective methods

Test-retest of automated image segmentation algorithms (FSL FAST, FSL FIRST, and FREESURFER) are computed on magnetic resonance images from 12 unsedated children aged 9.4±2.6 years ([min,max] ​= ​[6.5 years, 13.8 years]) using different approaches to motion correction (prospective versus retrospective). The prospective technique, PROMO MPRAGE, dynamically estimates motion using specially acquired navigator images and adjusts the remaining acquisition accordingly, whereas the retrospective technique, MPnRAGE, uses a self-navigation property to retrospectively estimate and account for motion during image reconstruction. To increase the likelihood and range of motions, participants heads were not stabilized with padding during repeated scans. When motion was negligible both techniques had similar performance. When motion was not negligible, the automated image segmentation and anatomical labeling software tools showed the most consistent performance with the retrospectively corrected MPnRAGE technique (≥80% volume overlaps for 15 of 16 regions for FIRST and FREESURFER, with greater than 90% volume overlaps for 12 regions with FIRST and 11 regions with FREESURFER). Prospectively corrected MPRAGE with linear view-ordering also demonstrated lower performance than MPnRAGE without retrospective motion correction.

MR-based age-related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan

While numerous studies have used magnetic resonance imaging (MRI) to elucidate normative age-related trajectories in subcortical structures across the human lifespan, there exists substantial heterogeneity among different studies. Here, we investigated the normative relationships between age and morphology (i.e., volume and shape), and microstructure (using the T1-weighted/T2-weighted [T1w/T2w] signal ratio as a putative index of myelin and microstructure) of the striatum, globus pallidus, and thalamus across the adult lifespan using a dataset carefully quality controlled, yielding a final sample of 178 for the morphological analyses, and 162 for the T1w/T2w analyses from an initial dataset of 253 healthy subjects, aged 18-83. In accordance with previous cross-sectional studies of adults, we observed age-related volume decrease that followed a quadratic relationship between age and bilateral striatal and thalamic volumes, and a linear relationship in the globus pallidus. Our shape indices consistently demonstrated age-related posterior and medial areal contraction bilaterally across all three structures. Beyond morphology, we observed a quadratic inverted U-shaped relationship between T1w/T2w signal ratio and age, with a peak value occurring in middle age (at around 50 years old). After permutation testing, the Akaike information criterion determined age relationships remained significant for the bilateral globus pallidus and thalamus, for both the volumetric and T1w/T2w analyses. Our findings serve to strengthen and expand upon previous volumetric analyses by providing a normative baseline of morphology and microstructure of these structures to which future studies investigating patients with various disorders can be compared.

Rapid high resolution T1 mapping as a marker of brain development: Normative ranges in key regions of interest

Objectives

We studied in a clinical setting the age dependent T1 relaxation time as a marker of normal late brain maturation and compared it to conventional techniques, namely the apparent diffusion coefficient (ADC).

Materials and methods

Forty-two healthy subjects ranging from ages 1 year to 20 years were included in our study. T1 brain maps in which the intensity of each pixel corresponded to T1 relaxation times were generated based on MR imaging data acquired using a MP2RAGE sequence. During the same session, diffusion tensor imaging data was collected. T1 relaxation times and ADC in white matter and grey matter were measured in seven clinically relevant regions of interest and were correlated to subjects’ age.

Results

In the basal ganglia, there was a small, yet significant, decrease in T1 relaxation time (-0.45 ≤R≤-0.59, p<10⁻²) and ADC (-0.60≤R≤-0.65, p<10⁻⁴) as a function of age. In the frontal and parietal white matter, there was a significant decrease in T1 relaxation time (-0.62≤R≤-0.68, p<10⁻⁴) and ADC (-0.81≤R≤-0.85, p<10⁻⁴) as a function of age. T1 relaxation time changes in the corpus callosum and internal capsule were less relevant for this age range. There was no significant difference between the correlation of T1 relaxation time and ADC with respect to age (p-value = 0.39). The correlation between T1 relaxation and ADC is strong in the white matter but only moderate in basal ganglia over this age period.

Conclusions

T1 relaxation time is a marker of brain maturation or myelination during late brain development. Between the age of 1 and 20 years, T1 relaxation time decreases as a function of age in the white matter and basal ganglia. The greatest changes occur in frontal and parietal white matter. These regions are known to mature in the final stage of development and are mainly composed of association circuits. Age-correlation is not significantly different between T1 relaxation time and ADC. Therefore, T1 relaxation time does not appear to be a superior marker of brain maturation than ADC but may be considered as complementary owing the intrinsic differences in bio-physical sensitivity. This work may serve as normative ranges in clinical imaging routines.

Magnetic resonance imaging and brain injury in the chronic phase after aneurysmal subarachnoid hemorrhage: A systematic review

Background Case-fatality rates after aneurysmal subarachnoid hemorrhage have decreased over the past decades. However, many patients who survive an aneurysmal subarachnoid hemorrhage have long-term functional and cognitive impairments. Aims We sought to review all data on conventional brain MRI obtained in the chronic phase after aneurysmal subarachnoid hemorrhage to (1) analyze the proportion of patients with cerebral infarction or brain volume changes; (2) investigate baseline determinants predictive of MRI-detected damage; and (3) assess if brain damage is predictive of patient outcome. Summary of review All original data published between 1 January 2000 and 4 October 2017 was searched using the PUBMED, EMBASE, and Web of Science databases. Based on preset inclusion criteria, 15 from 5200 articles were included with a total of 996 aneurysmal subarachnoid hemorrhage patients. Quality assessment, risk of bias assessment, and level of evidence assessment were performed. The results according to aim, with levels of evidence, were: (1) 25 to 81% of aneurysmal subarachnoid hemorrhage patients show infarcts (strong); there is a higher ratio of cerebrospinal fluid-to-intracranial volume in patients compared to controls (strong); (2) there is a negative relation between age (moderate), DCI (low) and brain volume measurement outcomes; (3) lower brain parenchymal volume (strong) and the presence of infarcts or infarct volumes (moderate) are associated with a worse outcome. Conclusion Patients after aneurysmal subarachnoid hemorrhage may demonstrate brain infarcts and decreased brain parenchyma, which is related to worse outcome. Thereby, both brain infarcts and brain volume measurements could be used as outcome markers in pharmaceutical trials. Systematic Review Registration PROSPERO CRD42016040095.

Sex disparities in substance abuse research: Evaluating 23 years of structural neuroimaging studies

BACKGROUND

Sex differences in brain structure and clinical course of substance use disorders underscores the need to include women in structural brain imaging studies. The NIH has supported the need for research to address sex differences. We evaluated female enrollment in substance abuse structural brain imaging research and the methods used to study sex differences in substance effects.

METHODS

Structural brain imaging studies published through 2016 (n=230) were evaluated for number of participants by sex and substance use status and methods used to evaluate sex differences. Temporal trends in the numbers of participants by sex and substance use status were analyzed. We evaluated how often sex effects were appropriately analyzed and the proportion of studies that found sex by substance interactions on volumetric measures.

RESULTS

Female enrollment increased over time, but remained significantly lower than male enrollment (p=0.01), with the greatest bias for alcohol and opiate studies. 79% of studies included both sexes; however, 74% did not evaluate sex effects or used an analytic approach that precluded detection of sex by substance use interactions. 85% of studies that stratified by sex reported different substance effects on brain volumes. Only 33% of studies examining two-way interactions found significant interactions, highlighting that many studies were underpowered to detect interactions.

CONCLUSIONS

Although female participation in substance use studies of brain morphometry has increased, sex disparity persists. Studying adequate numbers of both sexes and employing correct analytic approaches is critical for understanding sex differences in brain morphometric changes in substance abuse.

Comparison of automated brain segmentation using a brain phantom and patients with early Alzheimer's dementia or mild cognitive impairment

Magnetic resonance imaging (MRI) and brain volumetry allow for the quantification of changes in brain volume using automatic algorithms which are widely used in both, clinical and scientific studies. However, studies comparing the reliability of these programmes are scarce and mainly involved MRI derived from younger healthy controls. This study evaluates the reliability of frequently used segmentation programmes (SPM, FreeSurfer, FSL) using a realistic digital brain phantom and MRI brain acquisitions from patients with manifest Alzheimer's disease (AD, n=34), mild cognitive impairment (MCI, n=60), and healthy subjects (n=32) matched for age and sex. Analysis of the brain phantom dataset demonstrated that SPM, FSL and FreeSurfer underestimate grey matter and overestimate white matter volumes with increasing noise. FreeSurfer calculated overall smaller brain volumes with increasing noise. Image inhomogeneity had only minor, non- significant effects on the results obtained with SPM and FreeSurfer 5.1, but had effects on the FSL results (increased white matter volumes with decreased grey matter volumes). The analysis of the patient data yielded decreasing volumes of grey and white matter with progression of brain atrophy independent of the method used. FreeSurfer calculated the largest grey matter and the smallest white matter volumes. FSL calculated the smallest grey matter volumes; SPM the largest white matter volumes. Best results are obtained with good image quality. With poor image quality, especially noise, SPM provides the best segmentation results. An optimised template for segmentation had no significant effect on segmentation results. While our findings underline the applicability of the programmes investigated, SPM may be the programme of choice when MRIs with limited image quality or brain images of elderly should be analysed.

Reproducibility of brain metabolite concentration measurements in lesion free white matter at 1.5 T

Background

Post processing for brain spectra has a great influence on the fit quality of individual spectra, as well as on the reproducibility of results from comparable spectra. This investigation used pairs of spectra, identical in system parameters, position and time assumed to differ only in noise. The metabolite amplitudes of fitted time domain spectroscopic data were tested on reproducibility for the main brain metabolites.

Methods

Proton spectra of white matter brain tissue were acquired with a short spin echo time of 30 ms and a moderate repetition time of 1500 ms at 1.5 T. The pairs were investigated with one time domain post-processing algorithm using different parameters. The number of metabolites, the use of prior knowledge, base line parameters and common or individual damping were varied to evaluate the best reproducibility.

Results

The protocols with most reproducible amplitudes for N-acetylaspartate, creatine, choline, myo-inositol and the combined Glx line of glutamate and glutamine in lesion free white matter have the following common features: common damping of the main metabolites, a baseline using only the points of the first 10 ms, no additional lipid/macromolecule lines and Glx is taken as the sum of separately fitted glutamate and glutamine. This parameter set is different to the one delivering the best individual fit results.

Discussion

All spectra were acquired in “lesion free” (no lesion signs found in MR imaging) white matter. Spectra of brain lesions, for example tumors, can be drastically different. Thus the results are limited to lesion free brain tissue. Nevertheless the application to studies is broad, because small alterations in brain biochemistry of lesion free areas had been detected nearby tumors, in patients with multiple sclerosis, drug abuse or psychiatric disorders.

Conclusion

Main metabolite amplitudes inside healthy brain can be quantified with a normalized root mean square deviation around 5 % using CH₃ of creatine as reference. Only the reproducibility of myo-inositol is roughly twice as bad. The reproducibility should be similar using other references like internal or external water for an absolute concentration evaluation and are not influenced by relaxation corrections with literature values.

Multi-parametric evaluation of the white matter maturation

In vivo evaluation of the brain white matter maturation is still a challenging task with no existing gold standards. In this article we propose an original approach to evaluate the early maturation of the white matter bundles, which is based on comparison of infant and adult groups using the Mahalanobis distance computed from four complementary MRI parameters: quantitative qT1 and qT2 relaxation times, longitudinal λ_║ and transverse λ_⊥ diffusivities from diffusion tensor imaging. Such multi-parametric approach is expected to better describe maturational asynchrony than conventional univariate approaches because it takes into account complementary dependencies of the parameters on different maturational processes, notably the decrease in water content and the myelination. Our approach was tested on 17 healthy infants (aged 3- to 21-week old) for 18 different bundles. It finely confirmed maturational asynchrony across the bundles: the spino-thalamic tract, the optic radiations, the cortico-spinal tract and the fornix have the most advanced maturation, while the superior longitudinal and arcuate fasciculi, the anterior limb of the internal capsule and the external capsule have the most delayed maturation. Furthermore, this approach was more reliable than univariate approaches as it revealed more maturational relationships between the bundles and did not violate a priori assumptions on the temporal order of the bundle maturation. Mahalanobis distances decreased exponentially with age in all bundles, with the only difference between them explained by different onsets of maturation. Estimation of these relative delays confirmed that the most dramatic changes occur during the first post-natal year.

Assessment of apparent diffusion coefficient of normal fetal brain development from gestational age week 24 up to term age: a preliminary study

OBJECTIVES

This study was designed to investigate the feasibility of apparent diffusion coefficient (ADC) values in evaluating normal fetal brain development from gestational week 24 up to term age.

METHODS

Diffusion-weighted imaging (DWI) was performed on 40 normal fetuses (with normal results on sonography and normal fetal MRI results), with two b-values of 0 and 600 s/mm² in the three (x, y, z) orthogonal axes. Ten regions of interest (ROIs) were manually placed symmetrically in the bilateral frontal white matter (FWM), occipital white matter (OWM), thalamus (THAL), basal ganglia (BG), and cerebellar hemispheres (CH). ADC values of the ten ROIs in all subjects were measured by two radiologists independently. One-way ANOVA was used to calculate the differences among the five regions in the fetal brain and linear regression analysis was used to evaluate the correlation between ADC values and gestational age (GA). p < 0.05 was considered significantly different.

RESULTS

Mean GA was 31.3 ± 3.9 (range 24-41) weeks. The overall mean ADC values (× 10⁻⁶ mm²/s) of the fetuses were 1,800 ± 214 (FWM), 1,400 ± 100 (BG), 1,300 ± 126 (THAL), 1,700 ± 133 (OWM) and 1,400 ± 155 (CH), respectively. The ADC value of BG was not significantly different from those of THAL and CH, while the other four ROIs had significant differences with each other. The ADC values of BG, THAL, OWM and CH had strong negative correlations with increasing GA (R were -0.568, -0.716, -0.830 and -0.700, respectively, all p < 0.01), OWM declined fastest with GA, followed by CH and THAL, the slowest being BG. The ADC value of FWM had no significant change with GA (p = 0.366).

CONCLUSIONS

The measurement of ADC values is feasible to evaluate fetal brain development with high reliability and reproducibility.