Synthetic MRI of Preterm Infants at Term-Equivalent Age: Evaluation of Diagnostic Image Quality and Automated Brain Volume Segmentation

Synthetic magnetic resonance-based relaxometry and brain volume: cutoff values for predicting neurocognitive outcomes in very preterm infants

BACKGROUND

Early neurorehabilitation can enhance neurocognitive outcomes in very preterm infants (<32 weeks), and conventional magnetic resonance imaging (MRI) is commonly used to assess neonatal brain injury; however, the predictive value for neurodevelopmental delay is limited. Timely predictive quantitative biomarkers are needed to improve early identification and management of infants at risk of neurodevelopmental delay.

OBJECTIVE

To evaluate the potential of quantitative synthetic MRI measurements at term-equivalent age as predictive biomarkers of neurodevelopmental impairment and establish practical cutoff values to guide clinical decision-making.

MATERIALS AND METHODS

This retrospective study included 93 very preterm infants who underwent synthetic MRI at term-equivalent age between January 2017 and September 2020. Clinical outcomes were assessed using the Bayley-III scale of infant development (mean age 2.1 years). The predictive value for impaired development was analyzed using receiver operating characteristic curves for synthetic MRI-based volumetry and T1 and T2 relaxation measurements.

RESULTS

The T1 relaxation time in the posterior limb of the internal capsule was a potent predictor of severe (sensitivity, 92%; specificity, 80%; area under the curve (AUC), 0.91) and mild or severe (AUC, 0.75) developmental impairment. T2 relaxation time in the posterior limb of the internal capsule was a significant predictor of severe impairment (AUC, 0.76), whereas the brain parenchymal volume was a significant predictor of severe (AUC, 0.72) and mild or severe impairment (AUC, 0.71) outperforming the reported qualitative MRI scores (AUC, 0.66).

CONCLUSION

The proposed cutoff values for T1 relaxation time in the posterior limb of the internal capsule and for total brain volume measurements, derived from synthetic MRI, show promise as predictors of both mild and severe neurodevelopmental impairment in very preterm infants.

Synthetic MRI and MR Fingerprinting-Derived Relaxometry of Antenatal Human Brainstem Myelination: A Postmortem-Based Quantitative Imaging Study

BACKGROUND AND PURPOSE

The radiologic evaluation of ongoing myelination is currently limited prenatally. Novel quantitative MR imaging modalities provide relaxometric properties that are linked to myelinogenesis. In this retrospective postmortem imaging study, the capability of Synthetic MR imaging and MR fingerprinting-derived relaxometry for tracking fetal myelin development was investigated. Moreover, the consistency of results for both MR approaches was analyzed.

MATERIALS AND METHODS

In 26 cases, quantitative postmortem fetal brain MR data were available (gestational age range, 15 + 1 to 32 + 1; female/male ratio, 14/12). Relaxometric measurements (T1-/T2-relexation times) were determined in the medulla oblongata and the midbrain using Synthetic MR imaging/MR fingerprinting-specific postprocessing procedures (Synthetic MR imaging and MR Robust Quantitative Tool for MR fingerprinting). The Pearson correlations were applied to detect relationships between T1-relaxation times/T2-relaxation times metrics and gestational age at MR imaging. Intraclass correlation coefficients were calculated to assess the consistency of the results provided by both modalities.

RESULTS

Both modalities provided quantitative data that revealed negative correlations with gestational age at MR imaging: Synthetic MR imaging-derived relaxation times (medulla oblongata [r = -0.459; P = .021]; midbrain [r = -0.413; P = .040]), T2-relaxation times (medulla oblongata [r = -0.625; P < .001]; midbrain [r = -0.571; P = .003]), and MR fingerprinting-derived T1-relaxation times (medulla oblongata [r = -0.433; P = .035]; midbrain [r = -0.386; P = .062]), and T2-relaxation times (medulla oblongata [r =-0.883; P < .001]; midbrain [r = -0.890; P < .001]).The intraclass correlation coefficient analysis for result consistency between both MR approaches ranged between 0.661 (95% CI, 0.351-0.841) (T2-relaxation times: medulla oblongata) and 0.920 (95% CI, 0.82-0.965) (T1-relaxation times: midbrain).

CONCLUSIONS

There is a good-to-excellent consistency between postmortem Synthetic MR imaging and MR fingerprinting myelin quantifications in fetal brains older than 15 + 1 gestational age. The strong correlations between quantitative myelin metrics and gestational age indicate the potential of quantitative MR imaging to identify delayed or abnormal states of myelination at prenatal stages of cerebral development.

The value of synthetic MRI in detecting the brain changes and hearing impairment of children with sensorineural hearing loss

Introduction

Sensorineural hearing loss (SNHL) can arise from a diverse range of congenital and acquired factors. Detecting it early is pivotal for nurturing speech, language, and cognitive development in children with SNHL. In our study, we utilized synthetic magnetic resonance imaging (SyMRI) to assess alterations in both gray and white matter within the brains of children affected by SNHL.

Methods

The study encompassed both children diagnosed with SNHL and a control group of children with normal hearing {1.5-month-olds (n = 52) and 3-month-olds (n = 78)}. Participants were categorized based on their auditory brainstem response (ABR) threshold, delineated into normal, mild, moderate, and severe subgroups.Clinical parameters were included and assessed the correlation with SNHL. Quantitative analysis of brain morphology was conducted using SyMRI scans, yielding data on brain segmentation and relaxation time.Through both univariate and multivariate analyses, independent factors predictive of SNHL were identified. The efficacy of the prediction model was evaluated using receiver operating characteristic (ROC) curves, with visualization facilitated through the utilization of a nomogram. It's important to note that due to the constraints of our research, we worked with a relatively small sample size.

Results

Neonatal hyperbilirubinemia (NH) and children with inner ear malformation (IEM) were associated with the onset of SNHL both at 1.5 and 3-month groups. At 3-month group, the moderate and severe subgroups exhibited elevated quantitative T1 values in the inferior colliculus (IC), lateral lemniscus (LL), and middle cerebellar peduncle (MCP) compared to the normal group. Additionally, WMV, WMF, MYF, and MYV were significantly reduced relative to the normal group. Additionally, SNHL-children with IEM had high T1 values in IC, and LL and reduced WMV, WMF, MYV and MYF values as compared with SNHL-children without IEM at 3-month group. LL-T1 and WMF were independent risk factors associated with SNHL. Consequently, a prediction model was devised based on LL-T1 and WMF. ROC for training set, validation set and external set were 0.865, 0.806, and 0.736, respectively.

Conclusion

The integration of T1 quantitative values and brain volume segmentation offers a valuable tool for tracking brain development in children affected by SNHL and assessing the progression of the condition's severity.

Assessment of brain structure and volume reveals neurodevelopmental abnormalities in preterm infants with low-grade intraventricular hemorrhage

There is increasing evidence of abnormal neurodevelopmental outcomes in preterm infants with low-grade intraventricular hemorrhage (IVH). The purpose of the study was to explore whether brain microstructure and volume are associated with neuro-behavioral outcomes at 40 weeks corrected gestational age in preterm infants with low-grade IVH. MR imaging at term-equivalent age (TEA) was performed in 25 preterm infants with mild IVH (Papile grading I/II) and 40 control subjects without IVH. These subjects all had neonatal behavioral neurological assessment (NBNA) at 40 weeks' corrected age. Microstructure and volume evaluation of the brain were performed by using diffusion kurtosis imaging (DKI) and Synthetic MRI. Correlations among microstructure parameters, volume, and developmental outcomes were explored by using Spearman's correlation. In preterm infants with low-grade IVH, the volume of brain parenchymal fraction (BPF) was reduced. In addition, mean kurtosis (MK), fractional anisotropy (FA), radial kurtosis (RK), axial kurtosis (AK) in several major brain regions were reduced, while mean diffusivity (MD) was increased (P < 0.05). BPF, RK in the cerebellum, MK in the genu of the corpus callosum, and MK in the thalamus of preterm infants with low-grade IVH were associated with lower NBNA scores (r = 0.831, 0.836, 0.728, 0.772, P < 0.05). DKI and Synthetic MRI can quantitatively evaluate the microstructure alterations and brain volumes in preterm infants with low-grade IVH, which provides clinicians with a more comprehensive and accurate neurobehavioral assessment of preterm infants with low-grade IVH.

Gestational age-related changes in relaxation times of neonatal brain by quantitative synthetic magnetic resonance imaging

OBJECTIVE

This study aimed to explore the correlation between T1 and T2 relaxation times of synthetic MRI (SyMRI) and gestational age (GA) in each hemisphere of preterm and term newborns at the initial 28 days of birth.

METHODS

Seventy preterm and full-term infants were prospectively included in this study. All subjects completed 3.0 T routine MRI and SyMRI (MAGiC) one-stop scanning within 28 days of birth (aged 34-42 W at examination). The SyMRI postprocessing software (v8.0.4) was used to measure the T1 and T2 relaxation values of each brain region. The linear regression equations of quantitative relaxation values with GA were established to compare the variation speed in each brain region.

RESULTS

A significant linear and negative correlation was found between relaxation times and GA in the neonate cerebral cortex and subcortical gray and white matter regions (All p<.05). The relaxation time of the left centrum semiovale decreased with maximum variance with increasing GA among all white matter regions (T1: b = -51.45, β = -0.65, p < .0001; T2: b = -8.77, β = -0.71, p < .0001), whereas the right posterior limb of internal capsule showed minimal variance (T1: b = -27.94, β = -0.60, p < .0001; T2: b = -3.25, β = -0.68, p < .0001). Among all gray matter regions, the right globus pallidus and thalamus indicated the most significant decreasing degree of T1 and T2 relaxation values with GA (right globus pallidus T1: b = -33.14, β = -0.64, p < .0001; right thalamus T2: b = -3.94, β = -0.81, p < .0001), and the right and left occipital lobes indicated the least significant decreasing degree of T1 and T2 relaxation values with GA, respectively (right occipital lobes T1: b = -11.18, β = -0.26, p = .028; left occipital lobes T2: b = -1.22, β = -0.27, p = .024).

CONCLUSIONS

SyMRI could quantitatively evaluate the linear changes of T1 and T2 relaxation values with GA in brain gray and white matter of preterm and term neonates.

Pre-contrast MAGiC in treated gliomas: a pilot study of quantitative MRI

Quantitative MR imaging is becoming more feasible to be used in clinical work since new approaches have been proposed in order to substantially accelerate the acquisition and due to the possibility of synthetically deriving weighted images from the parametric maps. However, their applicability has to be thoroughly validated in order to be included in clinical practice. In this pilot study, we acquired Magnetic Resonance Image Compilation scans to obtain T1, T2 and PD maps in 14 glioma patients. Abnormal tissue was segmented based on conventional images and using a deep learning segmentation technique to define regions of interest (ROIs). The quantitative T1, T2 and PD values inside ROIs were analyzed using the mean, the standard deviation, the skewness and the kurtosis and compared to the quantitative T1, T2 and PD values found in normal white matter. We found significant differences in pre-contrast T1 and T2 values between abnormal tissue and healthy tissue, as well as between T1w-enhancing and non-enhancing regions. ROC analysis was used to evaluate the potential of quantitative T1 and T2 values for voxel-wise classification of abnormal/normal tissue (AUC = 0.95) and of T1w enhancement/non-enhancement (AUC = 0.85). A cross-validated ROC analysis found high sensitivity (73%) and specificity (73%) with AUCs up to 0.68 on the a priori distinction between abnormal tissue with and without T1w-enhancement. These results suggest that normal tissue, abnormal tissue, and tissue with T1w-enhancement are distinguishable by their pre-contrast quantitative values but further investigation is needed.

Accelerated Nonenhanced 3D T1-MPRAGE Using Wave-Controlled Aliasing in Parallel Imaging for Infant Brain Imaging

BACKGROUND AND PURPOSE

MPRAGE is the most commonly used sequence for high-resolution 3D T1-weighted imaging in pediatric patients. However, its longer scan time is a major drawback because pediatric patients are prone to motion and frequently require sedation. This study compared nonenhanced accelerated MPRAGE using wave-controlled aliasing in parallel imaging (wave-T1-MPRAGE) with standard MPRAGE in infants.

MATERIALS AND METHODS

We retrospectively evaluated 68 infants (mean age, 1.78 [SD. 1.70] months) who underwent nonenhanced standard and wave-T1-MPRAGE. Two neuroradiologists independently assessed each image for image quality, artifacts, myelination degree, and anatomic delineation using the 4-point Likert scale. For diagnostic performance, both observers determined whether nonenhancing lesions were present in the brain parenchyma in 2 types of nonenhanced MPRAGE sequences.

RESULTS

Wave-T1-MPRAGE showed a significantly lower mean score and lower interobserver agreement for overall image quality and anatomic delineation than standard MPRAGE (P< .001 for each). However, there were no significant differences between the 2 types of MPRAGE sequences for motion artifacts (P = .90 for observer 1, P = .14 for observer 2) and degree of myelination (P = .16 for observer 1, P = .32 for observer 2). Among the nonenhancing pathologic lesions observed on standard MPRAGE by both observers, only 2 were missed on wave-T1-MPRAGE, and they were very tiny, faint, nonhemorrhagic WM injuries.

CONCLUSIONS

Although wave-T1-MPRAGE showed lower overall image quality than standard MPRAGE, the diagnostic performance for nonenhancing parenchymal lesions was comparable. Wave-T1-MPRAGE could be an alternative for diagnosing intracranial lesions in infants, with marked scan time reduction.

Accelerated Synthetic MRI with Deep Learning-Based Reconstruction for Pediatric Neuroimaging

BACKGROUND AND PURPOSE

Synthetic MR imaging is a time-efficient technique. However, its rather long scan time can be challenging for children. This study aimed to evaluate the clinical feasibility of accelerated synthetic MR imaging with deep learning-based reconstruction in pediatric neuroimaging and to investigate the impact of deep learning-based reconstruction on image quality and quantitative values in synthetic MR imaging.

MATERIALS AND METHODS

This study included 47 children 2.3-14.7 years of age who underwent both standard and accelerated synthetic MR imaging at 3T. The accelerated synthetic MR imaging was reconstructed using a deep learning pipeline. The image quality, lesion detectability, tissue values, and brain volumetry were compared among accelerated deep learning and accelerated and standard synthetic data sets.

RESULTS

The use of deep learning-based reconstruction in the accelerated synthetic scans significantly improved image quality for all contrast weightings (P < .001), resulting in image quality comparable with or superior to that of standard scans. There was no significant difference in lesion detectability between the accelerated deep learning and standard scans (P > .05). The tissue values and brain tissue volumes obtained with accelerated deep learning and the other 2 scans showed excellent agreement and a strong linear relationship (all, R 2 > 0.9). The difference in quantitative values of accelerated scans versus accelerated deep learning scans was very small (tissue values, <0.5%; volumetry, -1.46%-0.83%).

CONCLUSIONS

The use of deep learning-based reconstruction in synthetic MR imaging can reduce scan time by 42% while maintaining image quality and lesion detectability and providing consistent quantitative values. The accelerated deep learning synthetic MR imaging can replace standard synthetic MR imaging in both contrast-weighted and quantitative imaging.

Time-saving synthetic magnetic resonance imaging protocols for pediatric neuroimaging: impact of echo train length and bandwidth on image quality

BACKGROUND

Synthetic MRI is a time-efficient imaging technique that provides both quantitative MRI and contrast-weighted images simultaneously. However, a rather long single scan time can be challenging for children.

OBJECTIVE

To evaluate the clinical feasibility of time-saving synthetic MRI protocols adjusted for echo train length and receiver bandwidth in pediatric neuroimaging based on image quality assessment and quantitative data analysis.

MATERIALS AND METHODS

In total, we included 33 children ages 1.6-17.4 years who underwent synthetic MRI using three sets of echo train length and receiver bandwidth combinations (echo train length [E]12-bandwidth [B in KHz]22, E16-B22 and E16-B83) at 3 T. The image quality and lesion conspicuity of synthetic contrast-weighted images were compared between the suggested protocol (E12-B22) and adjusted protocols (E16-B22 and E16-B83). We also compared tissue values (T1, T2, proton-density values) and brain volumetry.

RESULTS

For the E16-B83 combination, image quality was sufficient except for 15.2% of T1-W and 3% of T2-W fluid-attenuated inversion recovery (FLAIR) images, with remarkable scan time reduction (up to 35%). The E16-B22 combination demonstrated a comparable image quality to E12-B22 (P&gt;0.05) with a scan time reduction of up to 8%. There were no significant differences in lesion conspicuity among the three protocols (P&gt;0.05). Tissue value measurements and brain tissue volumes obtained with the E12-B22 protocol and adjusted protocols showed excellent agreement and strong correlations except for gray matter volume and non-white matter/gray matter/cerebrospinal fluid volume in E12-B22 vs. E16-B83.

CONCLUSION

The adjusted synthetic protocols produced image quality sufficient or comparable to that of the suggested protocol while maintaining lesion conspicuity with reduced scan time. The quantitative values were generally consistent with the suggested MRI-protocol-derived values, which supports the clinical application of adjusted protocols in pediatric neuroimaging.

Impact of Prematurity on the Tissue Properties of the Neonatal Brain Stem: A Quantitative MR Approach

BACKGROUND AND PURPOSE

Preterm birth interferes with regular brain development. The aim of this study was to investigate the impact of prematurity on the physical tissue properties of the neonatal brain stem using a quantitative MR imaging approach.

MATERIALS AND METHODS

A total of 55 neonates (extremely preterm [n = 30]: <28 + 0 weeks gestational age; preterm [n = 10]: 28 + 0-36 + 6 weeks gestational age; term [n = 15]: ≥37 + 0 weeks gestational age) were included in this retrospective study. In most cases, imaging was performed at approximately term-equivalent age using a standard MR protocol. MR data postprocessing software SyMRI was used to perform multidynamic multiecho sequence (acquisition time: 5 minutes, 24 seconds)-based MR postprocessing to determine T1 relaxation time, T2 relaxation time, and proton density. Mixed-model ANCOVA (covariate: gestational age at MR imaging) and the post hoc Bonferroni test were used to compare the groups.

RESULTS

There were significant differences between premature and term infants for T1 relaxation time (midbrain: P < .001; pons: P < .001; basis pontis: P = .005; tegmentum pontis: P < .001; medulla oblongata: P < .001), T2 relaxation time (midbrain: P < .001; tegmentum pontis: P < .001), and proton density (tegmentum pontis: P = .004). The post hoc Bonferroni test revealed that T1 relaxation time/T2 relaxation time in the midbrain differed significantly between extremely preterm and preterm (T1 relaxation time: P < .001/T2 relaxation time: P = .02), extremely preterm and term (T1 relaxation time/T2 relaxation time: P < .001), and preterm and term infants (T1 relaxation time: P < .001/T2 relaxation time: P = .006).

CONCLUSIONS

Quantitative MR parameters allow preterm and term neonates to be differentiated. T1 and T2 relaxation time metrics of the midbrain allow differentiation between the different stages of prematurity. SyMRI allows for a quantitative assessment of incomplete brain maturation by providing tissue-specific properties while not exceeding a clinically acceptable imaging time.

Pediatric Head CT: Automated Quantitative Analysis with Quantile Regression

BACKGROUND AND PURPOSE

Together with quantile regression methods, such a model would have the potential for clinical utility through automated quantitative comparison of individual cases relative to their age and gender-matched peer group. Our aim was to demonstrate the automated processing of digital clinical head CT data in the development of a clinically useful model of age-related changes of the brain in the first 2 decades of life.

MATERIALS AND METHODS

A total of 415 (209 female) consecutive, clinical head CTs with radiographically normal findings from patients from birth through 20 years of age were retrospectively selected and subjected to automated segmentation. Brain volume, brain parenchymal fraction, brain radiodensity, and brain radiomass were assessed as a function of patient age. Statistical modeling and quantile regression were performed.

RESULTS

Brain volume increased from 400 cm3 at birth to 1350 cm3 at 20 years of age (>3-fold). Males had a slightly steeper growth trajectory than females, with approximately 8% difference in volume between the sexes established in the first few years of life. Brain parenchymal fraction was variable at younger than 2 years of age, stabilizing between 0.85 and 0.92 at 2-3 years of age. Brain mean radiodensity was lower at birth (24 HU) and increased through 3 years of age, after which it stabilized near 30 HU, an approximately 25% increase. The product of brain volume and mean brain radiodensity (radiomass), increased from 700 HU × mL at birth to 3900 HU × mL, a 5.6-fold increase, with approximately 5% difference between males and females at 20 years. Quantile regression enables a given metric to be interpreted relative to an age- and sex-matched peer group.

CONCLUSIONS

Automated segmentation of clinical head CT images permitted the generation of a reference database for quantitative analysis of pediatric and adolescent brains. Quantile regression facilitates clinical application.

Synthetic MRI demonstrates prolonged regional relaxation times in the brain of preterm born neonates with severe postnatal morbidity

BACKGROUND

To identify preterm infants at risk for neurodevelopment impairment that might benefit from early neurorehabilitation, early prognostic biomarkers of future outcomes are needed.

OBJECTIVE

To determine whether synthetic MRI is sensitive to age-related changes in regional tissue relaxation times in the brain of preterm born neonates when scanned at term equivalent age (TEA, 37-42 weeks), and to investigate whether severe postnatal morbidity results in prolonged regional tissue relaxation times.

MATERIALS AND METHODS

This retrospective study included 70 very preterm born infants scanned with conventional and synthetic MRI between January 2017 and June 2019 at TEA. Infants with severe postnatal morbidity were allocated to a high-risk group (n = 22). All other neonates were allocated to a low-risk group (n = 48). Linear regression analysis was performed to determine the relationship between relaxation times and postmenstrual age (PMA) at scan. Analysis of covariance was used to evaluate the impact of severe postnatal morbidity in the high-risk group on T1 and T2 relaxation times. Receiver operating characteristic (ROC) curves were plotted and analysed with area under the ROC curve (AUC) to evaluate the accuracy of classifying high-risk patients based on regional relaxation times.

RESULTS

A linear age-related decrease of T1 and T2 relaxation times correlating with PMA at scan (between 37 and 42 weeks) was found in the deep gray matter, the cerebellum, the cortex, and the posterior limb of the internal capsule (PLIC) (p < .005 each), but not in the global, frontal, parietal, or central white matter. Analysis of covariance for both risk groups, adjusted for PMA, revealed significantly prolonged regional tissue relaxation times in neonates with severe postnatal morbidity, which was best illustrated in the central white matter of the centrum semiovale (T1 Δ = 11.5%, T2 Δ = 13.4%, p < .001) and in the PLIC (T1 Δ = 9.2%, T2 Δ = 6.9%, p < .001). The relaxation times in the PLIC and the central white matter predicted high-risk status with excellent accuracy (AUC range 0.82-0.86).

CONCLUSION

Synthetic MRI-based relaxometry in the brain of preterm born neonates is sensitive to age-related maturational changes close to TEA. Severe postnatal morbidity correlated with a significant delay in tissue relaxation. Synthetic MRI may provide early prognostic biomarkers for neurodevelopment impairment.