Efficient correction of inhomogeneous static magnetic field-induced distortion in Echo Planar Imaging

Quantitative MRI biomarker for classification of clinically significant prostate cancer: Calibration for reproducibility across echo times

PURPOSE

The purpose of the present study is to develop a calibration method to account for differences in echo times (TE) and facilitate the use of restriction spectrum imaging restriction score (RSIrs) as a quantitative biomarker for the detection of clinically significant prostate cancer (csPCa).

METHODS

This study included 197 consecutive patients who underwent MRI and biopsy examination; 97 were diagnosed with csPCa (grade group ≥ 2). RSI data were acquired three times during the same session: twice at minimum TE ~75 ms and once at TE = 90 ms (TEmin1, TEmin2, and TE90, respectively). A linear regression model was determined to match the C-maps of TE90 to the reference C-maps of TEmin1 within the interval ranging from 95th to 99th percentile of signal intensity within the prostate. RSIrs comparisons were made at the 98th percentile within each patient's prostate. We compared RSIrs from calibrated TE90 (RSIrsTE90corr) and uncorrected TE90 (RSIrsTE90) to RSIrs from reference TEmin1 (RSIrsTEmin1) and repeated TEmin2 (RSIrsTEmin2). Calibration performance was evaluated with sensitivity, specificity and area under the ROC curve (AUC).

RESULTS

Scaling factors for C1, C2, C3, and C4 were estimated as 1.68, 1.33, 1.02, and 1.13, respectively. In non-csPCa cases, the 98th percentile of RSIrsTEmin2 and RSIrsTEmin1 differed by 0.27 ± 0.86SI (mean ± standard deviation), whereas RSIrsTE90 differed from RSIrsTEmin1 by 1.82 ± 1.20SI. After calibration, this bias was reduced to -0.51 ± 1.21SI, representing a 72% reduction in absolute error. For patients with csPCa, the difference was 0.54 ± 1.98SI between RSIrsTEmin2 and RSIrsTEmin1 and 2.28 ± 2.06SI between RSIrsTE90 and RSIrsTEmin1. After calibration, the mean difference decreased to -1.03SI, a 55% reduction in absolute error. At the Youden index for patient-level classification of csPCa (8.94SI), RSIrsTEmin1 has a sensitivity of 66% and a specificity of 72%.

CONCLUSIONS

The proposed linear calibration method produces similar quantitative biomarker values for acquisitions with different TE, reducing TE-induced error by 72% and 55% for non-csPCa and csPCa, respectively.

Decreased inter-hemispheric connectivity predicts a coherent retrieval of auditory symbolic material

Investigating the transmission of information between individuals is essential to better understand how humans communicate. Coherent information transmission (i.e., transmission without significant modifications or loss of fidelity) helps preserving cultural traits and traditions over time, while innovation may lead to new cultural variants. Although much research has focused on the cognitive mechanisms underlying cultural transmission, little is known on the brain features which correlates with coherent transmission of information. To address this gap, we combined structural (from high-resolution diffusion imaging) and functional connectivity (from resting-state functional magnetic resonance imaging [fMRI]) with a laboratory model of cultural transmission, the signalling games, implemented outside the MRI scanner. We found that individuals who exhibited more coherence in the transmission of auditory symbolic information were characterized by lower levels of both structural and functional inter-hemispheric connectivity. Specifically, higher coherence negatively correlated with the strength of bilateral structural connections between frontal and subcortical, insular and temporal brain regions. Similarly, we observed increased inter-hemispheric functional connectivity between inferior frontal brain regions derived from structural connectivity analysis in individuals who exhibited lower transmission coherence. Our results suggest that lateralization of cognitive processes involved in semantic mappings in the brain may be related to the stability over time of auditory symbolic systems.

Discrimination Between Benign and Malignant Lesions With Restriction Spectrum Imaging MRI in an Enriched Breast Cancer Screening Cohort

BACKGROUND

Breast cancer screening with dynamic contrast-enhanced MRI (DCE-MRI) is recommended for high-risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high-risk benign lesions (HRBL) from average-risk benign lesions (ARBL). Complementary non-invasive imaging techniques would be useful to improve specificity.

PURPOSE

To evaluate the performance of a previously-developed breast-specific diffusion-weighted MRI (DW-MRI) model (BS-RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population.

STUDY TYPE

Prospective.

SUBJECTS

Exactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high-risk individuals undergoing routine breast MRI (N = 138), before the biopsy.

FIELD STRENGTH/SEQUENCE

Multishell DW-MRI echo planar imaging sequence with a reduced field of view at 3.0 T.

ASSESSMENT

A total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW-MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C1, C2, and C3-restricted, hindered, and free diffusion, respectively) from the BS-RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE-MRI findings by two radiologists; control ROIs were drawn in the contralateral breast.

STATISTICAL TESTS

One-way ANOVA and two-sided t-tests were used to assess differences in signal contributions and ADC values among groups. P-values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra-class correlations (ICC) were also evaluated.

RESULTS

C1, √C1C2, andlog C 1 C 2 C 3 $$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ were significantly different in HRBLs compared with ARBLs (P-values < 0.05). Thelog C 1 C 2 C 3 $$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ had the highest AUC (0.821) in differentiating CHRLs from ARBLs, performing better than ADC (0.696), especially in non-mass enhancement (0.776 vs. 0.517).

DATA CONCLUSION

This study demonstrated the BS-RSI3C could differentiate HRBLs from ARBLs in a screening population, and separate CHRLs from ARBLs better than ADC.

LEVEL OF EVIDENCE: 1

TECHNICAL EFFICACY STAGE

2.

Structural Development of Speech Networks in Young Children at Risk for Speech Disorder

Characterizing the structural development of the neural speech network in early childhood is important for understanding speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old at risk for early speech disorder were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using multi-compartment restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus ( pars opercularis ), right pre-supplementary/ supplementary motor area (pre-SMA/SMA), and bilateral cerebellar grey matter ( p < .005). Age moderated these associations in left pars opercularis and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automatic fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT. These findings suggest that individual differences in speech performance are reflected in structural gray and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.

Reverse Encoding Distortion Correction for Clinical Head Echo-Planar Diffusion-Weighted MRI: Initial Experience

OBJECTIVE

This study aimed to evaluate the feasibility of the recently commercialized reverse encoding distortion correction (RDC) method for echo-planar imaging (EPI) diffusion-weighted imaging (DWI) by applying clinical head MRI.

METHODS

This study included 50 consecutive patients who underwent head MRI, including single-shot (SS) EPI DWI and RDC-EPI DWI. For evaluation of normal structures, qualitative scores for image distortion, Dice similarity coefficient (DSC) values, distortion ratios, and mean apparent diffusion coefficient (ADC) values were assessed in the pons, temporal lobe at the skull base, and frontal lobe at the level of the lateral ventricles in 30 patients. To evaluate pathologies, qualitative scores for image distortion were assessed for 25 intracranial and 21 extracranial pathologies identified in 32 patients.

RESULTS

Qualitative scores for image distortion, DSC values, distortion ratios, and mean ADC values of the pons and temporal lobe were significantly different between SS-EPI DWI and RDC-EPI DWI, whereas those of the frontal lobe at the level of the lateral ventricles were not significantly different between the 2 DWIs. The qualitative scores for image distortion and mean ADC values of extracranial pathologies were significantly different between the DWIs, whereas those of intracranial pathologies were not significantly different.

CONCLUSIONS

RDC-EPI DWI significantly reduced image distortion and showed higher mean ADC values of the brain parenchyma in the skull base and extracranial pathologies.

Music reward sensitivity is associated with greater information transfer capacity within dorsal and motor white matter networks in musicians

There are pronounced differences in the degree to which individuals experience music-induced pleasure which are linked to variations in structural connectivity between auditory and reward areas. However, previous studies exploring the link between white matter structure and music reward sensitivity (MRS) have relied on standard diffusion tensor imaging methods, which present challenges in terms of anatomical accuracy and interpretability. Further, the link between MRS and connectivity in regions outside of auditory-reward networks, as well as the role of musical training, have yet to be investigated. Therefore, we investigated the relation between MRS and structural connectivity in a large number of directly segmented and anatomically verified white matter tracts in musicians (n = 24) and non-musicians (n = 23) using state-of-the-art tract reconstruction and fixel-based analysis. Using a manual tract-of-interest approach, we additionally tested MRS-white matter associations in auditory-reward networks seen in previous studies. Within the musician group, there was a significant positive relation between MRS and fiber density and cross section in the right middle longitudinal fascicle connecting auditory and inferior parietal cortices. There were also positive relations between MRS and fiber-bundle cross-section in tracts connecting the left thalamus to the ventral precentral gyrus and connecting the right thalamus to the right supplementary motor area, however, these did not survive FDR correction. These results suggest that, within musicians, dorsal auditory and motor networks are crucial to MRS, possibly via their roles in top-down predictive processing and auditory-motor transformations.

Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study

Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.

Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer

BACKGROUND

High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.

METHODS

One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).

RESULTS

Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.

CONCLUSION

sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

HAITCH: A Framework for Distortion and Motion Correction in Fetal Multi-Shell Diffusion-Weighted MRI

Diffusion magnetic resonance imaging (dMRI) is pivotal for probing the microstructure of the rapidly-developing fetal brain. However, fetal motion during scans and its interaction with magnetic field inhomogeneities result in artifacts and data scattering across spatial and angular domains. The effects of those artifacts are more pronounced in high-angular resolution fetal dMRI, where signal-to-noise ratio is very low. Those effects lead to biased estimates and compromise the consistency and reliability of dMRI analysis. This work presents HAITCH, the first and the only publicly available tool to correct and reconstruct multi-shell high-angular resolution fetal dMRI data. HAITCH offers several technical advances that include a blip-reversed dual-echo acquisition for dynamic distortion correction, advanced motion correction for model-free and robust reconstruction, optimized multi-shell design for enhanced information capture and increased tolerance to motion, and outlier detection for improved reconstruction fidelity. The framework is open-source, flexible, and can be used to process any type of fetal dMRI data including single-echo or single-shell acquisitions, but is most effective when used with multi-shell multi-echo fetal dMRI data that cannot be processed with any of the existing tools. Validation experiments on real fetal dMRI scans demonstrate significant improvements and accurate correction across diverse fetal ages and motion levels. HAITCH successfully removes artifacts and reconstructs high-fidelity fetal dMRI data suitable for advanced diffusion modeling, including fiber orientation distribution function estimation. These advancements pave the way for more reliable analysis of the fetal brain microstructure and tractography under challenging imaging conditions.

Childhood adversity is associated with reduced BOLD response in inhibitory control regions amongst preadolescents from the ABCD study

Adolescence is characterized by dynamic neurodevelopment, which poses opportunities for risk and resilience. Adverse childhood experiences (ACEs) confer additional risk to the developing brain, where ACEs have been associated with alterations in functional magnetic resonance imaging (fMRI) BOLD signaling in brain regions underlying inhibitory control. Socioenvironmental factors like the family environment may amplify or buffer against the neurodevelopmental risks associated with ACEs. Using baseline to Year 2 follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study, the current study examined how ACEs relate to fMRI BOLD signaling during successful inhibition on the Stop Signal Task in regions associated with inhibitory control and examined whether family conflict levels moderated that relationship. Results showed that greater ACEs were associated with reduced BOLD response in the right opercular region of the inferior frontal gyrus and bilaterally in the pre-supplementary motor area, which are key regions underlying inhibitory control. Further, greater BOLD response was correlated with less impulsivity behaviorally, suggesting reduced activation may not be behaviorally adaptive at this age. No significant two or three-way interactions with family conflict levels or time were found. Findings highlight the continued utility of examining the relationship between ACEs and neurodevelopmental outcomes and the importance of intervention/prevention of ACES.

PyHySCO: GPU-enabled susceptibility artifact distortion correction in seconds

Over the past decade, reversed gradient polarity (RGP) methods have become a popular approach for correcting susceptibility artifacts in echo-planar imaging (EPI). Although several post-processing tools for RGP are available, their implementations do not fully leverage recent hardware, algorithmic, and computational advances, leading to correction times of several minutes per image volume. To enable 3D RGP correction in seconds, we introduce PyTorch Hyperelastic Susceptibility Correction (PyHySCO), a user-friendly EPI distortion correction tool implemented in PyTorch that enables multi-threading and efficient use of graphics processing units (GPUs). PyHySCO uses a time-tested physical distortion model and mathematical formulation and is, therefore, reliable without training. An algorithmic improvement in PyHySCO is its use of the one-dimensional distortion correction method by Chang and Fitzpatrick to initialize the non-linear optimization. PyHySCO is published under the GNU public license and can be used from the command line or its Python interface. Our extensive numerical validation using 3T and 7T data from the Human Connectome Project suggests that PyHySCO can achieve accuracy comparable to that of leading RGP tools at a fraction of the cost. We also validate the new initialization scheme, compare different optimization algorithms, and test the algorithm on different hardware and arithmetic precisions.

PyDesigner v1.0: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Magnetic Resonance Imaging

PyDesigner is a Python-based software package based on the original Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline (Dv1) for dMRI preprocessing and tensor estimation. This software is openly provided for non-commercial research and may not be used for clinical care. PyDesigner combines tools from FSL and MRtrix3 to perform denoising, Gibbs ringing correction, eddy current motion correction, brain masking, image smoothing, and Rician bias correction to optimize the estimation of multiple diffusion measures. It can be used across platforms on Windows, Mac, and Linux to accurately derive commonly used metrics from DKI, DTI, WMTI, FBI, and FBWM datasets as well as tractography ODFs and .fib files. It is also file-format agnostic, accepting inputs in the form of .nii, .nii.gz, .mif, and dicom format. User-friendly and easy to install, this software also outputs quality control metrics illustrating signal-to-noise ratio graphs, outlier voxels, and head motion to evaluate data integrity. Additionally, this dMRI processing pipeline supports multiple echo-time dataset processing and features pipeline customization, allowing the user to specify which processes are employed and which outputs are produced to meet a variety of user needs.

Neural Reward Anticipation Moderates Longitudinal Relation between Parents' Familism Values and Latinx American Youth's School Disengagement

Parents' familism values predict a variety of Latinx American youth's academic adjustment. However, it is unclear how cultural values such as familism interact with youth's brain development, which is sensitive to sociocultural input, to shape their academic adjustment. Using a sample of 1916 Latinx American youth (mean age = 9.90 years, SD = .63 years; 50% girls) and their primary caregivers (mean age = 38.43 years, SD = 6.81 years; 90% mothers) from the Adolescent Brain Cognitive Development Study, this study examined the longitudinal relation between parents' familism values and youth's school disengagement, as well as the moderating role of youth's neural sensitivity to personal reward. Parents' familism values predicted youth's decreased school disengagement 1 year later, adjusting for their baseline school disengagement and demographic covariates. Notably, this association was more salient among youth who showed lower (vs. higher) neural activation in the ventral striatum and the lateral OFC during the anticipation of a personal reward. These findings underscore the protective role of familism for Latinx American youth, highlighting the necessity of developing culturally informed interventions that take into consideration a youth's brain development.

LATENT SUBGROUP IDENTIFICATION IN IMAGE-ON-SCALAR REGRESSION

Image-on-scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interventions to increase the number of youths who benefit. It is of great interest to identify subgroups of individuals from the population such that: (1) within each subgroup the brain activities have homogeneous associations with the clinical measures; (2) across subgroups the associations are heterogeneous, and (3) the group allocation depends on individual characteristics. Existing image-on-scalar regression methods and clustering methods cannot directly achieve this goal. We propose a latent subgroup image-on-scalar regression model (LASIR) to analyze large-scale, multisite neuroimaging data with diverse sociode-mographics. LASIR introduces the latent subgroup for each individual and group-specific, spatially varying effects, with an efficient stochastic expectation maximization algorithm for inferences. We demonstrate that LASIR outperforms existing alternatives for subgroup identification of brain activation patterns with functional magnetic resonance imaging data via comprehensive simulations and applications to the ABCD study. We have released our reproducible codes for public use with the software package available on Github.

Effect of Phase Encoding Direction on Image Quality in Single-Shot EPI Diffusion-Weighted Imaging of the Breast

BACKGROUND

In breast diffusion-weighted imaging (DWI), distortion and physiologic artifacts affect clinical interpretation. Image quality can be optimized by addressing the effect of phase encoding (PE) direction on these artifacts.

PURPOSE

To compare distortion artifacts in breast DWI acquired with different PE directions and polarities, and to discuss their clinical implications.

STUDY TYPE

Prospective.

POPULATION

Eleven healthy volunteers (median age: 47 years old; range: 22-74 years old) and a breast phantom.

FIELD STRENGTH/SEQUENCE

Single-shot echo planar DWI and three-dimensional fast gradient echo sequences at 3 T.

ASSESSMENT

All DWI data were acquired with left-right, right-left, posterior-anterior, and anterior-posterior PE directions. In phantom data, displacement magnitude was evaluated by comparing the location of landmarks in anatomical and DWI images. Three breast radiologists (5, 17, and 23 years of experience) assessed the presence or absence of physiologic artifacts in volunteers' DWI datasets and indicated their PE-direction preference.

STATISTICAL TESTS

Analysis of variance with post-hoc tests were used to assess differences in displacement magnitude across DWI datasets and observers. A binomial test and a chi-squared test were used to evaluate if each in vivo DWI dataset had an equal probability (25%) of being preferred by radiologists. Inter-reader agreement was evaluated using Gwet's AC1 agreement coefficient. A P-value <0.05 was considered statistically significant.

RESULTS

In the phantom study, median displacement was the significantly largest in posterior-anterior data. While the displacement in the anterior-posterior and left-right data were equivalent (P = 0.545). In the in vivo data, there were no physiological artifacts observed in any dataset, regardless of PE direction. In the reader study, there was a significant preference for the posterior-anterior datasets which were selected 94% of the time. There was good agreement between readers (0.936).

DATA CONCLUSION

This study showed the impact of PE direction on distortion artifacts in breast DWI. In healthy volunteers, the posterior-to-anterior PE direction was preferred by readers.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Comparison of distortion correction preprocessing pipelines for DTI in the upper limb

PURPOSE

DTI characterizes tissue microstructure and provides proxy measures of nerve health. Echo-planar imaging is a popular method of acquiring DTI but is susceptible to various artifacts (e.g., susceptibility, motion, and eddy currents), which may be ameliorated via preprocessing. There are many pipelines available but limited data comparing their performance, which provides the rationale for this study.

METHODS

DTI was acquired from the upper limb of heathy volunteers at 3T in blip-up and blip-down directions. Data were independently corrected using (i) FSL's TOPUP & eddy, (ii) FSL's TOPUP, (iii) DSI Studio, and (iv) TORTOISE. DTI metrics were extracted from the median, radial, and ulnar nerves and compared (between pipelines) using mixed-effects linear regression. The geometric similarity of corrected b = 0 images and the slice matched T1-weighted (T1w) images were computed using the Sörenson-Dice coefficient.

RESULTS

Without preprocessing, the similarity coefficient of the blip-up and blip-down datasets to the T1w was 0·80 and 0·79, respectively. Preprocessing improved the geometric similarity by 1% with no difference between pipelines. Compared to TOPUP & eddy, DSI Studio and TORTOISE generated 2% and 6% lower estimates of fractional anisotropy, and 6% and 13% higher estimates of radial diffusivity, respectively. Estimates of anisotropy from TOPUP & eddy versus TOPUP were not different but TOPUP reduced radial diffusivity by 3%. The agreement of DTI metrics between pipelines was poor.

CONCLUSIONS

Preprocessing DTI from the upper limb improves geometric similarity but the choice of the pipeline introduces clinically important variability in diffusion parameter estimates from peripheral nerves.

Brain connectivity patterns associated with individual differences in the access to experience-near personal semantics: a resting-state fMRI study

It has been proposed that a continuum of specificity exists between episodic and semantic autobiographical memory. Personal semantics have been theorized to situate intermediately on this continuum, with more "experience-near" personal semantics (enPS) closer to the episodic end. We used individual differences in behavior as a model to investigate brain networks associated with the access to episodic autobiographical (EAM) and enPS information, assessing the relation between performance in the EAM and enPS conditions of the Autobiographical Fluency Task (AFT) and intrinsic brain connectivity. Results of an intrinsic connectivity contrast analysis showed that the global connectivity of two clusters in the left and right posterior cingulate cortex (PCC) was predicted by performance in the enPS conditions. Moreover, enPS scores predicted the connectivity strength of the right PCC with the bilateral anterior hippocampus (aHC), anterior middle temporal gyrus (aMTG) and medial orbitofrontal cortex, and the left aMTG and PCC. enPS scores also predicted the connectivity strength of the left PCC with the bilateral HC and MTG. The network highlighted involves parts of the core and of the dorsal medial subsystems of the Default Mode Network, in line with the proposal that enPS represents an intermediate entity between episodic and semantic memory.

Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies

PURPOSE

The purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI).

METHODS

Forty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student's t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student's t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar's test.

RESULTS

DR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05).

CONCLUSION

RDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.

Early life stress modulates the genetic influence on brain structure and cognitive function in children

The enduring influence of early life stress (ELS) on brain and cognitive development has been widely acknowledged, yet the precise mechanisms underlying this association remain elusive. We hypothesize that ELS might disrupt the genome-wide influence on brain morphology and connectivity development, consequently exerting a detrimental impact on children's cognitive ability. We analyzed the multimodal data of DNA genotypes, brain imaging (structural and diffusion MRI), and neurocognitive battery (NIH Toolbox) of 4276 children (ages 9-10 years, European ancestry) from the Adolescent Brain Cognitive Development (ABCD) study. The genome-wide influence on cognitive function was estimated using the polygenic score (GPS). By using brain morphometry and tractography, we identified the brain correlates of the cognition GPSs. Statistical analyses revealed relationships for the gene-brain-cognition pathway. The brain structural variance significantly mediated the genetic influence on cognition (indirect effect = 0.016, PFDR < 0.001). Of note, this gene-brain relationship was significantly modulated by abuse, resulting in diminished cognitive capacity (Index of Moderated Mediation = -0.007; 95 % CI = -0.012 ∼ -0.002). Our results support a novel gene-brain-cognition model likely elucidating the long-lasting negative impact of ELS on children's cognitive development.

FD-Net: An unsupervised deep forward-distortion model for susceptibility artifact correction in EPI

PURPOSE

To introduce an unsupervised deep-learning method for fast and effective correction of susceptibility artifacts in reversed phase-encode (PE) image pairs acquired with echo planar imaging (EPI).

METHODS

Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield a corrected image. Unsupervised learning in these unwarping-based methods is commonly attained via a similarity constraint between the unwarped images in reversed-PE directions, neglecting consistency to the acquired EPI images. This work introduces a novel unsupervised deep Forward-Distortion Network (FD-Net) that predicts both the susceptibility-induced displacement field and the underlying anatomically correct image. Unlike previous methods, FD-Net enforces the forward-distortions of the correct image in both PE directions to be consistent with the acquired reversed-PE image pair. FD-Net further leverages a multiresolution architecture to maintain high local and global performance.

RESULTS

FD-Net performs competitively with a gold-standard reference method (TOPUP) in image quality, while enabling a leap in computational efficiency. Furthermore, FD-Net outperforms recent unwarping-based methods for unsupervised correction in terms of both image and field quality.

CONCLUSION

The unsupervised FD-Net method introduces a deep forward-distortion approach to enable fast, high-fidelity correction of susceptibility artifacts in EPI by maintaining consistency to measured data. Therefore, it holds great promise for improving the anatomical accuracy of EPI imaging.

Update on Optimization of Prostate MR Imaging Technique and Image Quality

Prostate MR imaging quality has improved dramatically over recent times, driven by advances in hardware, software, and improved functional imaging techniques. MRI now plays a key role in prostate cancer diagnostic work-up, but outcomes of the MRI-directed pathway are heavily dependent on image quality and optimization. MR sequences can be affected by patient-related degradations relating to motion and susceptibility artifacts which may enable only partial mitigation. In this Review, we explore issues relating to prostate MRI acquisition and interpretation, mitigation strategies at a patient and scanner level, PI-QUAL reporting, and future directions in image quality, including artificial intelligence solutions.

Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion

PURPOSE

EPI with blip-up/down acquisition (BUDA) can provide high-quality images with minimal distortions by using two readout trains with opposing phase-encoding gradients. Because of the need for two separate acquisitions, BUDA doubles the scan time and degrades the temporal resolution when compared to single-shot EPI, presenting a major challenge for many applications, particularly fMRI. This study aims at overcoming this challenge by developing an echo-shifted EPI BUDA (esEPI-BUDA) technique to acquire both blip-up and blip-down datasets in a single shot.

METHODS

A 3D esEPI-BUDA pulse sequence was designed by using an echo-shifting strategy to produce two EPI readout trains. These readout trains produced a pair of k-space datasets whose k-space trajectories were interleaved with opposite phase-encoding gradient directions. The two k-space datasets were separately reconstructed using a 3D SENSE algorithm, from which time-resolved B0 -field maps were derived using TOPUP in FSL and then input into a forward model of joint parallel imaging reconstruction to correct for geometric distortion. In addition, Hankel structured low-rank constraint was incorporated into the reconstruction framework to improve image quality by mitigating the phase errors between the two interleaved k-space datasets.

RESULTS

The 3D esEPI-BUDA technique was demonstrated in a phantom and an fMRI study on healthy human subjects. Geometric distortions were effectively corrected in both phantom and human brain images. In the fMRI study, the visual activation volumes and their BOLD responses were comparable to those from conventional 3D echo-planar images.

CONCLUSION

The improved imaging efficiency and dynamic distortion correction capability afforded by 3D esEPI-BUDA are expected to benefit many EPI applications.

Study of structural network connectivity using DTI tractography in insomnia disorder

Most of tractography studies on insomnia disorder (ID) have reported decreased structural connectivity between cortical and subcortical structures. Tractography based on standard diffusion tensor imaging (DTI) can generate high number of false-positive streamlines connections between gray matter regions. In the present study, we employed the convex optimization modeling for microstructure informed tractography-2 (COMMIT2) to improve the accuracy of the reconstructed whole-brain connectome and filter implausible brain connections in 28 patients with ID and compared with 27 healthy controls. Then, we used NBS-predict (a prediction-based extension to the network-based statistic method) in the COMMIT2-weighted connectome. Our results revealed decreased structural connectivity between subregions of the left somatomotor, ventral attention, frontoparietal, dorsal attention and default mode networks in the insomnia group. Moreover, there is a negative correlation between sleep efficiency and structural connectivity within the left frontoparietal, visual, default mode network, limbic, dorsal attention, right dorsal attention as well as right default mode networks. By comparing with standard connectivity analysis, we showed that by removing of false-positive streamlines connections after COMMIT2 filtering, abnormal structural connectivity was reduced in patients with ID compared to controls. Our results demonstrate the importance of improving the accuracy of tractography for understanding structural connectivity networks in ID.

Diffusion Tensor Imaging of Peripheral Nerves: Current Status and New Developments

Diffusion tensor imaging (DTI) is an emerging technique for peripheral nerve imaging that can provide information about the microstructural organization and connectivity of these nerves and complement the information gained from anatomical magnetic resonance imaging (MRI) sequences. With DTI it is possible to reconstruct nerve pathways and visualize the three-dimensional trajectory of nerve fibers, as in nerve tractography. More importantly, DTI allows for quantitative evaluation of peripheral nerves by the calculation of several important parameters that offer insight into the functional status of a nerve. Thus DTI has a high potential to add value to the work-up of peripheral nerve pathologies, although it is more technically demanding. Peripheral nerves pose specific challenges to DTI due to their small diameter and DTI's spatial resolution, contrast, location, and inherent field inhomogeneities when imaging certain anatomical locations. Numerous efforts are underway to resolve these technical challenges and thus enable wider acceptance of DTI in peripheral nerve MRI.

Microstructural Cerebellar Injury Independently Associated With Processing Speed in Adult Patients With Primary Brain Tumors: Implications for Cognitive Preservation

PURPOSE

The cerebellum's role in posttreatment neurocognitive decline is unexplored. This study investigated associations between cerebellar microstructural integrity using quantitative neuroimaging biomarkers and neurocognition among patients with primary brain tumors receiving partial-brain radiation therapy (RT).

METHODS AND MATERIALS

In a prospective trial, 65 patients underwent volumetric brain magnetic resonance imaging, diffusion tensor imaging, and memory, executive function, language, attention, and processing speed (PS) assessment before RT and at 3, 6, and 12 months after RT. Delis-Kaplan Executive Function System-Trail Making (D-KEFS-TM) visual scanning and number and letter sequencing and Wechsler Adult Intelligence Scale, Fourth Edition, coding were used to evaluate PS. The cerebellar cortex and white matter (WM) and supratentorial structures subserving the previously mentioned cognitive domains were autosegmented. Volume was measured within each structure at each time point along with diffusion biomarkers (fractional anisotropy and mean diffusivity) in WM structures. Linear mixed-effects models assessed cerebellar biomarkers as predictors of neurocognitive scores. If associated, cerebellar biomarkers were evaluated as independent predictors of cognitive scores controlling for domain-specific supratentorial biomarkers.

RESULTS

Left (P = .04) and right (P < .001) cerebellar WM volume declined significantly over time. Cerebellar biomarkers were not associated with memory, executive function, or language. Smaller left cerebellar cortex volume was associated with worse D-KEFS-TM number (P = .01) and letter (P = .01) sequencing scores. A smaller right cerebellar cortex volume correlated with worse D-KEFS-TM visual scanning (P = .02) and number (P = .03) and letter (P = .02) sequencing scores. Greater right cerebellar WM mean diffusivity, indicating WM injury, was associated with worse D-KEFS-TM visual scanning performance (P = .03). Associations remained significant after controlling for corpus callosum and intrahemispheric WM injury biomarkers.

CONCLUSIONS

Injury to the cerebellum as measured with quantitative biomarkers correlates with worse post-RT PS, independent of corpus callosum and intrahemispheric WM damage. Efforts to preserve cerebellar integrity may preserve PS.

Longitudinal Associations Between White Matter Microstructure and Psychiatric Symptoms in Youth

OBJECTIVE

Associations between psychiatric problems and white matter (WM) microstructure have been reported in youth. Yet, a deeper understanding of this relation has been hampered by a dearth of well-powered longitudinal studies and a lack of explicit examination of the bidirectional associations between brain and behavior. We investigated the temporal directionality of WM microstructure and psychiatric symptom associations in youth.

METHOD

In this observational study, we leveraged the world's largest single- and multi-site cohorts of neurodevelopment: the Generation R (GenR) and Adolescent Brain Cognitive Development Studies (ABCD) (total n scans = 11,400; total N = 5,700). We assessed psychiatric symptoms with the Child Behavioral Checklist as broad-band internalizing and externalizing scales, and as syndrome scales (eg, Anxious/Depressed). We quantified WM with diffusion tensor imaging (DTI), globally and at a tract level. We used cross-lagged panel models to test bidirectional associations of global and specific measures of psychopathology and WM microstructure, meta-analyzed results across cohorts, and used linear mixed-effects models for validation.

RESULTS

We did not identify any longitudinal associations of global WM microstructure with internalizing or externalizing problems across cohorts (confirmatory analyses) before, and after multiple testing corrections. We observed similar findings for longitudinal associations between tract-based microstructure with internalizing and externalizing symptoms, and for global WM microstructure with specific syndromes (exploratory analyses). Some cross-sectional associations surpassed multiple testing corrections in ABCD, but not in GenR.

CONCLUSION

Uni- or bi-directionality of longitudinal associations between WM and psychiatric symptoms were not robustly identified. We have proposed several explanations for these findings, including interindividual differences, the use of longitudinal approaches, and smaller effects than expected.

STUDY REGISTRATION INFORMATION

Bidirectionality Brain Function and Psychiatric Symptoms; https://doi.org/10.17605/OSF.IO/PNY92.

Probing Renal Microstructure and Function with Advanced Diffusion MRI: Concepts, Applications, Challenges, and Future Directions

Diffusion measurements in the kidney are affected not only by renal microstructure but also by physiological processes (i.e., glomerular filtration, water reabsorption, and urine formation). Because of the superposition of passive tissue diffusion, blood perfusion, and tubular pre-urine flow, the limitations of the monoexponential apparent diffusion coefficient (ADC) model in assessing pathophysiological changes in renal tissue are becoming apparent and motivate the development of more advanced diffusion-weighted imaging (DWI) variants. These approaches take advantage of the fact that the length scale probed in DWI measurements can be adjusted by experimental parameters, including diffusion-weighting, diffusion gradient directions and diffusion time. This forms the basis by which advanced DWI models can be used to capture not only passive diffusion effects, but also microcirculation, compartmentalization, tissue anisotropy. In this review, we provide a comprehensive overview of the recent advancements in the field of renal DWI. Following a short introduction on renal structure and physiology, we present the key methodological approaches for the acquisition and analysis of renal DWI data, including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), non-Gaussian diffusion, and hybrid IVIM-DTI. We then briefly summarize the applications of these methods in chronic kidney disease and renal allograft dysfunction. Finally, we discuss the challenges and potential avenues for further development of renal DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Multiparametric MRI in Era of Artificial Intelligence for Bladder Cancer Therapies

This review focuses on the principles, applications, and performance of mpMRI for bladder imaging. Quantitative imaging biomarkers (QIBs) derived from mpMRI are increasingly used in oncological applications, including tumor staging, prognosis, and assessment of treatment response. To standardize mpMRI acquisition and interpretation, an expert panel developed the Vesical Imaging-Reporting and Data System (VI-RADS). Many studies confirm the standardization and high degree of inter-reader agreement to discriminate muscle invasiveness in bladder cancer, supporting VI-RADS implementation in routine clinical practice. The standard MRI sequences for VI-RADS scoring are anatomical imaging, including T2w images, and physiological imaging with diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI). Physiological QIBs derived from analysis of DW- and DCE-MRI data and radiomic image features extracted from mpMRI images play an important role in bladder cancer. The current development of AI tools for analyzing mpMRI data and their potential impact on bladder imaging are surveyed. AI architectures are often implemented based on convolutional neural networks (CNNs), focusing on narrow/specific tasks. The application of AI can substantially impact bladder imaging clinical workflows; for example, manual tumor segmentation, which demands high time commitment and has inter-reader variability, can be replaced by an autosegmentation tool. The use of mpMRI and AI is projected to drive the field toward the personalized management of bladder cancer patients.

Dose-Dependent Atrophy in Bilateral Amygdalae and Nuclei After Brain Radiation Therapy and Its Association With Mood and Memory Outcomes on a Longitudinal Clinical Trial

PURPOSE

Amygdalae are bilateral, almond-shaped structures located anterior to the hippocampi, critical to limbic system functions of emotional processing and memory consolidation. The amygdalae are heterogeneous, composed of multiple nuclei with distinct structural and functional properties. We prospectively assessed associations between longitudinal changes in amygdala morphometry, including component nuclei, and functional outcomes in patients with primary brain tumors receiving radiation therapy (RT).

METHODS AND MATERIALS

On a prospective longitudinal trial, 63 patients underwent high-resolution volumetric brain magnetic resonance imaging and testing for mood (Beck Depression Inventory and Beck Anxiety Inventory), memory (Brief Visuospatial Memory Test-Revised [BVMT] Total Recall and Delayed Recall; Hopkins Verbal Learning Test-Revised [HVLT] Total Recall and Delayed Recall), and health-related quality-of-life outcomes (Functional Assessment of Cancer Therapy-Brain Social/Family Well-Being and Emotional Well-Being) at baseline and 3, 6, and 12 months after RT. Amygdalae, including 8 nuclei, were autosegmented bilaterally using validated techniques. Linear mixed-effects models assessed longitudinal change in amygdalae and nuclei volumes and associations with dose and outcomes. Wilcoxon rank sum tests compared amygdala volume change between patient groups with worse and more stable outcomes at each time point.

RESULTS

Atrophy was found in the right amygdala at 6 months (P = .001) and the left amygdala at 12 months (P = .046). A higher dose was associated with atrophy of the left amygdala (P = .013) at 12 months. The right amygdala showed dose-dependent atrophy at 6 months (P = .016) and 12 months (P = .001). Worse BVMT-Total, HVLT-Total, and HVLT-Delayed performance was associated with smaller left lateral (P = .014, P = .004, and P = .007, respectively) and left basal (P = .034, P = .016, and P = .026, respectively) nuclei volumes. Increased anxiety at 6 months was associated with greater combined (P = .031) and right (P = .007) amygdala atrophy. Greater left amygdala atrophy (P = .038) was noted in patients with decreased emotional well-being at 12 months.

CONCLUSIONS

Bilateral amygdalae and nuclei undergo time- and dose-dependent atrophy after brain RT. Atrophy in amygdalae and specific nuclei was associated with poorer memory, mood, and emotional well-being. Amygdalae-sparing treatment planning may preserve neurocognitive and neuropsychiatric outcomes in this population.

Evaluating Reproducibility of the ADC and Distortion in Diffusion-weighted Imaging (DWI) with Reverse Encoding Distortion Correction (RDC)

PURPOSE

To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers.

METHODS

This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant. RDC-DWIs were created from images obtained at 3T in three orthogonal directions in a phantom and in 10 participants (mean age, 70.9 years; age range, 63-83 years). Images without distortion correction (noDC-DWI) and those corrected with B0 (B0c-DWI) were also created. To evaluate distortion, coefficients of variation were calculated for each voxel and ROIs were placed at four levels of the brain. To evaluate the reproducibility of apparent diffusion coefficient (ADC) measurements, intra- and inter-scan variability (%CVADC) were calculated from repeated scans of the phantom. Analysis was performed using Wilcoxon signed-rank test with Bonferroni correction, and P < 0.05 was considered statistically significant.

RESULTS

In the phantom, distortion was less in RDC-DWI than in B0c-DWI (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). Intra-scan %CVADC was within 1.30%, and inter-scan %CVADC was within 2.99%. In the volunteers, distortion was less in RDC-DWI than in B0c-DWI in three of four locations (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). At the middle cerebellar peduncle, distortion was less in RDC-DWI than in noDC-DWI (P < 0.006), and was less in noDC-DWI than in B0c-DWI (P < 0.0177).

CONCLUSION

In both the phantom and in volunteers, distortion was the least in RDC-DWI than in B0c-DWI and noDC-DWI.

Fine Motor Skill Decline After Brain Radiation Therapy-A Multivariate Normal Tissue Complication Probability Study of a Prospective Trial

PURPOSE

Brain radiation therapy can impair fine motor skills (FMS). Fine motor skills are essential for activities of daily living, enabling hand-eye coordination for manipulative movements. We developed normal tissue complication probability (NTCP) models for the decline in FMS after fractionated brain radiation therapy (RT).

METHODS AND MATERIALS

On a prospective trial, 44 patients with primary brain tumors received fractioned RT; underwent high-resolution volumetric magnetic resonance imaging, diffusion tensor imaging, and comprehensive FMS assessments (Delis-Kaplan Executive Function System Trail Making Test Motor Speed [DKEFS-MS]; and Grooved Pegboard dominant/nondominant hands) at baseline and 6 months postRT. Regions of interest subserving motor function (including cortex, superficial white matter, thalamus, basal ganglia, cerebellum, and white matter tracts) were autosegmented using validated methods and manually verified. Dosimetric and clinical variables were included in multivariate NTCP models using automated bootstrapped logistic regression, least absolute shrinkage and selection operator logistic regression, and random forests with nested cross-validation.

RESULTS

Half of the patients showed a decline on grooved pegboard test of nondominant hands, 17 of 42 (40.4%) on grooved pegboard test of -dominant hands, and 11 of 44 (25%) on DKEFS-MS. Automated bootstrapped logistic regression selected a 1-term model including maximum dose to dominant postcentral white matter. The least absolute shrinkage and selection operator logistic regression selected this term and steroid use. The top 5 variables in the random forest were all dosimetric: maximum dose to dominant thalamus, mean dose to dominant caudate, mean and maximum dose to the dominant corticospinal tract, and maximum dose to dominant postcentral white matter. This technique performed best with an area under the curve of 0.69 (95% CI, 0.68-0.70) on nested cross-validation.

CONCLUSIONS

We present the first NTCP models for FMS impairment after brain RT. Dose to several supratentorial motor-associated regions of interest correlated with a decline in dominant-hand fine motor dexterity in patients with primary brain tumors in multivariate models, outperforming clinical variables. These data can guide prospective fine motor-sparing strategies for brain RT.

The prefrontal cortex of the bottlenose dolphin (Tursiops truncatus Montagu, 1821): a tractography study and comparison with the human

Cetaceans are well known for their remarkable cognitive abilities including self-recognition, sound imitation and decision making. In other mammals, the prefrontal cortex (PFC) takes a key role in such cognitive feats. In cetaceans, however, a PFC could up to now not be discerned based on its usual topography. Classical in vivo methods like tract tracing are legally not possible to perform in Cetacea, leaving diffusion-weighted imaging (DWI) as the most viable alternative. This is the first investigation focussed on the identification of the cetacean PFC homologue. In our study, we applied the constrained spherical deconvolution (CSD) algorithm on 3 T DWI scans of three formalin-fixed brains of bottlenose dolphins (Tursiops truncatus) and compared the obtained results to human brains, using the same methodology. We first identified fibres related to the medio-dorsal thalamic nuclei (MD) and then seeded the obtained putative PFC in the dolphin as well as the known PFC in humans. Our results outlined the dolphin PFC in areas not previously studied, in the cranio-lateral, ectolateral and opercular gyri, and furthermore demonstrated a similar connectivity pattern between the human and dolphin PFC. The antero-lateral rotation of the PFC, like in other areas, might be the result of the telescoping process which occurred in these animals during evolution.

Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL)

The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.

Improving tractography in brainstem cavernoma patients by distortion correction

Introduction

The resection of brainstem cerebral cavernous malformations (CCM) harbors the risk of damaging the corticospinal tract (CST) and other major tracts. Hence, visualization of eloquent fiber tracts supports pre- and intraoperative planning. However, diffusion tensor imaging fiber tracking at brainstem level suffers from distortion due to field inhomogeneities and eddy currents by steep diffusion gradients.

Research question

This study aims to analyze the effect of distortion correction for CST tractography in brainstem CCM patients.

Material and methods

25 patients who underwent resection of brainstem CCM were enrolled, 24 suffered from hemorrhage. We performed an anatomically based tractography of the CST with a mean minimal fractional anisotropy of 0.22 ± 0.04 before and after cranial distortion correction (CDC). Accuracy was measured by anatomical plausibility and aberrant fibers.

Results

CDC led to a more precise CST tractography, further approximating its assumed anatomical localization in all cases. CDC resulted in a significantly more ventral location of the CST of 1.5 ± 0.6 mm (6.1 ± 2.7 mm before CDC vs. 4.6 ± 2.1 mm after CDC; p < .0001) as measured by the distance to the basilar artery and of 1.7 ± 0.6 mm (8.9 ± 2.7 mm vs. 7.2 ± 2.1 mm; p < .0001) in relation to the clivus. Aberrant fibers were reduced by CDC in 44% of cases. We found a mean difference in CST volume of 0.6 ± 0.8 ccm. We could not detect motor deficits after resection of irregular fibers.

Discussion and conclusion

CDC effectively corrects tractography for distortion at brainstem level, especially in patients suffering from brainstem CCM, further approximating its actual anatomical localization.

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.

Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high-resolution 3D diffusion MRI

PURPOSE

To develop a new method for high-fidelity, high-resolution 3D multi-slab diffusion MRI with minimal distortion and boundary slice aliasing.

METHODS

Our method modifies 3D multi-slab imaging to integrate blip-reversed acquisitions for distortion correction and oversampling in the slice direction (kz ) for reducing boundary slice aliasing. Our aim is to achieve robust acceleration to keep the scan time the same as conventional 3D multi-slab acquisitions, in which data are acquired with a single direction of blip traversal and without kz -oversampling. We employ a two-stage reconstruction. In the first stage, the blip-up/down images are respectively reconstructed and analyzed to produce a field map for each diffusion direction. In the second stage, the blip-reversed data and the field map are incorporated into a joint reconstruction to produce images that are corrected for distortion and boundary slice aliasing.

RESULTS

We conducted experiments at 7T in six healthy subjects. Stage 1 reconstruction produces images from highly under-sampled data (R = 7.2) with sufficient quality to provide accurate field map estimation. Stage 2 joint reconstruction substantially reduces distortion artifacts with comparable quality to fully-sampled blip-reversed results (2.4× scan time). Whole-brain in-vivo results acquired at 1.22 mm and 1.05 mm isotropic resolutions demonstrate improved anatomical fidelity compared to conventional 3D multi-slab imaging. Data demonstrate good reliability and reproducibility of the proposed method over multiple subjects.

CONCLUSION

The proposed acquisition and reconstruction framework provide major reductions in distortion and boundary slice aliasing for 3D multi-slab diffusion MRI without increasing the scan time, which can potentially produce high-quality, high-resolution diffusion MRI.

Restriction spectrum imaging with elastic image registration for automated evaluation of response to neoadjuvant therapy in breast cancer

Purpose

Dynamic contrast-enhanced MRI (DCE) and apparent diffusion coefficient (ADC) are currently used to evaluate treatment response of breast cancer. The purpose of the current study was to evaluate the three-component Restriction Spectrum Imaging model (RSI3C), a recent diffusion-weighted MRI (DWI)-based tumor classification method, combined with elastic image registration, to automatically monitor breast tumor size throughout neoadjuvant therapy.

Experimental design

Breast cancer patients (n=27) underwent multi-parametric 3T MRI at four time points during treatment. Elastically-registered DWI images were used to generate an automatic RSI3C response classifier, assessed against manual DCE tumor size measurements and mean ADC values. Predictions of therapy response during treatment and residual tumor post-treatment were assessed using non-pathological complete response (non-pCR) as an endpoint.

Results

Ten patients experienced pCR. Prediction of non-pCR using ROC AUC (95% CI) for change in measured tumor size from pre-treatment time point to early-treatment time point was 0.65 (0.38-0.92) for the RSI3C classifier, 0.64 (0.36-0.91) for DCE, and 0.45 (0.16-0.75) for change in mean ADC. Sensitivity for detection of residual disease post-treatment was 0.71 (0.44-0.90) for the RSI3C classifier, compared to 0.88 (0.64-0.99) for DCE and 0.76 (0.50-0.93) for ADC. Specificity was 0.90 (0.56-1.00) for the RSI3C classifier, 0.70 (0.35-0.93) for DCE, and 0.50 (0.19-0.81) for ADC.

Conclusion

The automatic RSI3C classifier with elastic image registration suggested prediction of response to treatment after only three weeks, and showed performance comparable to DCE for assessment of residual tumor post-therapy. RSI3C may guide clinical decision-making and enable tailored treatment regimens and cost-efficient evaluation of neoadjuvant therapy of breast cancer.

A whole-body diffusion MRI normal atlas: development, evaluation and initial use

BACKGROUND

Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task.

METHODS

Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture.

RESULTS

Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision.

CONCLUSIONS

Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.

Suicidal thoughts and behaviours among military veterans: protocol for a prospective, observational, neuroimaging study

INTRODUCTION

This study's overarching goal is to examine the relationship between brain circuits and suicidal thoughts and behaviours (STBs) in a transdiagnostic sample of US military veterans. Because STBs have been linked with maladaptive decision-making and disorders linked to impulsivity, this investigation focuses on valence and inhibitory control circuits.

METHODS AND ANALYSIS

In this prospective, observational study, we will collect functional MRI (fMRI), cognitive and clinical data from 136 veterans (target sample size) recruited from the Providence VA Health System (PVAHS): 68 with STBs and 68 matched controls. Behavioural data will be collected using standardised measures of STBs, psychiatric symptoms, cognition, functioning and medical history. Neuroimaging data will include structural, task and resting fMRI. We will conduct follow-up interviews and assessments at 6, 12 and 24 months post-enrolment. Primary analyses will compare data from veterans with and without STBs and will also evaluate whether activation and connectivity within circuits of valence and inhibition covary with historical and prospective patterns of suicidal ideation and behaviour.

ETHICS AND DISSEMINATION

The PVAHS Institutional Review Board approved this study (2018-051). Written informed consent will be obtained from all participants. Findings from this study will be published in peer-reviewed journals and presented at local, regional, national and international conferences.Nauder Namaky, Ph.D.* nauder_namaky@brown.edu.

Spatial patterns of gray and white matter compromise relate to age of seizure onset in temporal lobe epilepsy

OBJECTIVE

Temporal Lobe Epilepsy (TLE) is frequently a neurodevelopmental disorder, involving subcortical volume loss, cortical atrophy, and white matter (WM) disruption. However, few studies have addressed how these pathological changes in TLE relate to one another. In this study, we investigate spatial patterns of gray and white matter degeneration in TLE and evaluate the hypothesis that the relationship among these patterns varies as a function of the age at which seizures begin.

METHODS

Eighty-two patients with TLE and 59 healthy controls were enrolled. T1-weighted images were used to obtain hippocampal volumes and cortical thickness estimates. Diffusion-weighted imaging was used to obtain fractional anisotropy (FA) and mean diffusivity (MD) of the superficial WM (SWM) and deep WM tracts. Analysis of covariance was used to examine patterns of WM and gray matter alterations in TLE relative to controls, controlling for age and sex. Sliding window correlations were then performed to examine the relationships between SWM degeneration, cortical thinning, and hippocampal atrophy across ages of seizure onset.

RESULTS

Cortical thinning in TLE followed a widespread, bilateral pattern that was pronounced in posterior centroparietal regions, whereas SWM and deep WM loss occurred mostly in ipsilateral, temporolimbic regions compared to controls. Window correlations revealed a relationship between hippocampal volume loss and whole brain SWM disruption in patients who developed epilepsy during childhood. On the other hand, in patients with adult-onset TLE, co-occurring cortical and SWM alterations were observed in the medial temporal lobe ipsilateral to the seizure focus.

SIGNIFICANCE

Our results suggest that although cortical, hippocampal and WM alterations appear spatially discordant at the group level, the relationship among these features depends on the age at which seizures begin. Whereas neurodevelopmental aspects of TLE may result in co-occurring WM and hippocampal degeneration near the epileptogenic zone, the onset of seizures in adulthood may set off a cascade of SWM microstructural loss and cortical atrophy of a neurodegenerative nature.

Sleep quality and sleep duration predict brain microstructure among community-dwelling older adults

Although poor sleep quality and extreme sleep durations have been associated with brain atrophy and dementia, it is unclear whether sleep disturbances contribute to neural injury in the absence of neurodegeneration and cognitive impairment. In 146 dementia-free older adults of the Rancho Bernardo Study of Healthy Aging (76.7 ± 7.8 years at MRI), we examined associations of restriction spectrum imaging metrics of brain microstructure with self-reported sleep quality 6.3 ± 0.7 years prior, and with sleep duration reported 25, 15 and 9 years prior. Worse sleep quality predicted lower white matter restricted isotropic diffusion and neurite density and higher amygdala free water, with stronger associations between poor sleep quality and abnormal microstructure for men. Among women only, short or long sleep duration 25 and 15 years before MRI predicted lower white matter restricted isotropic diffusion and increased free water. Associations persisted after accounting for associated health and lifestyle factors. Sleep patterns were not related to brain volume or cortical thickness. Optimizing sleep behaviors throughout the life-course may help to preserve healthy brain aging.

Unsupervised cycle-consistent network using restricted subspace field map for removing susceptibility artifacts in EPI

PURPOSE

To design an unsupervised deep neural model for correcting susceptibility artifacts in single-shot Echo Planar Imaging (EPI) and evaluate the model for preclinical and clinical applications.

METHODS

This work proposes an unsupervised cycle-consistent model based on the restricted subspace field map to take advantage of both the deep learning (DL) and the reverse polarity-gradient (RPG) method for single-shot EPI. The proposed model consists of three main components: (1) DLRPG neural network (DLRPG-net) to obtain field maps based on a pair of images acquired with reversed phase encoding; (2) spin physical model-based modules to obtain the corrected undistorted images based on the learned field map; and (3) cycle-consistency loss between the input images and back-calculated images from each cycle is explored for network training. In addition, the field maps generated by DLRPG-net belong to a restricted subspace, which is a span of predefined cubic splines to ensure the smoothness of the field maps and avoid blurring in the corrected images. This new method is trained and validated on both preclinical and clinical datasets for diffusion MRI.

RESULTS

The proposed network could effectively generate smooth field maps and correct susceptibility artifacts in single-shot EPI. Simulated and in vivo preclinical/clinical experiments demonstrated that our method outperforms the state-of-the-art susceptibility artifact correction methods. Furthermore, the ablation experiments of the cycle-consistent network and the restricted subspace in generating field maps did show the advantages of DLRPG-net.

CONCLUSION

The proposed method (DLRPG-net) can effectively correct susceptibility artifacts for preclinical and clinical single-shot EPI sequences.

Apparent Diffusion Coefficient Reproducibility Across 3 T Scanners in a Breast Diffusion Phantom

BACKGROUND

To date, the accuracy and variability of diffusion-weighted MRI (DW-MRI) metrics have been reported in a limited number of scanner/protocol/coil combinations.

PURPOSE

To evaluate the reproducibility of DW-MRI estimates across multiple scanners and DW-MRI protocols and to assess the effects of using an 8-channel vs. 16-channel breast coil in a breast phantom.

STUDY TYPE

Prospective.

PHANTOM

Breast phantom containing tubes of water and differing polyvinylpyrrolidone (PVP) concentrations with apparent diffusion coefficients (ADCs) matching breast tissue.

FIELD STRENGTH/SEQUENCE

3 T (three standard and one wide bore), three DW-MRI single-shot echo planar imaging protocols of varying acquired spatial resolution.

ASSESSMENT

Accuracy of estimated ADCs was assessed using percent differences (PD) relative to nuclear magnetic resonance spectroscopy-derived reference values. Coefficients of variation (CV) were calculated to determine variation across scanners. CVs based on the median standard deviation (CV_M ) were used to evaluate tube-specific dispersion using 8- or 16-channel coils at a single scanner. ADCs of PVP-containing tubes were additionally normalized by the median water tube ADC to account for temperature effects.

STATISTICAL TESTS

Two-way repeated measures analysis of variance and post hoc tests were used to evaluate differences in ADC, CV, and CV_M across scanners and protocols (α = 0.05).

RESULTS

ADCs were within 11% (interquartile range [IQR] 7%) of reference values and significantly improved to 2% (IQR 7%) after normalization to an internal water reference. Normalization significantly reduced interscanner variability of ADC estimates from 7% to 4%. DW-MRI protocol did not affect ADC accuracy; however, the clinical and higher-resolution clinical protocols resulted in the greatest (9%) and least (6%) interscanner variability, respectively. The 8- and 16-channel receive coils yielded similar accuracy (PD: 12% vs. 16%) and precision (CV_M : 2.7% vs. 2.9%).

DATA CONCLUSION

Normalization by an internal reference improved interscanner ADC reproducibility. High-resolution protocols yielded comparably accurate and significantly less variable ADCs compared to a clinical standard protocol.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Diffusion Tensor and Kurtosis Imaging Findings the First Year following Mild Traumatic Brain Injury

Despite enormous research interest in diffusion tensor imaging and diffusion kurtosis imaging (DTI; DKI) following mild traumatic brain injury (MTBI), it remains unknown how diffusion in white matter evolves post-injury and relates to acute MTBI characteristics. This prospective cohort study aimed to characterize diffusion changes in white matter the first year after MTBI. Patients with MTBI (n = 193) and matched controls (n = 83) underwent 3T magnetic resonance imaging (MRI) within 72 h and 3- and 12-months post-injury. Diffusion data were analyzed in three steps: 1) voxel-wise comparisons between the MTBI and control group were performed with tract-based spatial statistics at each time-point; 2) clusters of significant voxels identified in step 1 above were evaluated longitudinally with mixed-effect models; 3) the MTBI group was divided into: (A) complicated (with macrostructural findings on MRI) and uncomplicated MTBI; (B) long (1-24 h) and short (< 1 h) post-traumatic amnesia (PTA); and (C) other and no other concurrent injuries to investigate if findings in step 1 were driven mainly by aberrant diffusion in patients with a more severe injury. At 72 h, voxel-wise comparisons revealed significantly lower fractional anisotropy (FA) in one tract and significantly lower mean kurtosis (Kmean) in 11 tracts in the MTBI compared with control group. At 3 months, the MTBI group had significantly higher mean diffusivity in eight tracts compared with controls. At 12 months, FA was significantly lower in four tracts and Kmean in 10 tracts in patients with MTBI compared with controls. There was considerable overlap in affected tracts across time, including the corpus callosum, corona radiata, internal and external capsule, and cerebellar peduncles. Longitudinal analyses revealed that the diffusion metrics remained relatively stable throughout the first year after MTBI. The significant group*time interactions identified were driven by changes in the control rather than the MTBI group. Further, differences identified in step 1 did not result from greater diffusion abnormalities in patients with complicated MTBI, long PTA, or other concurrent injuries, as standardized mean differences in diffusion metrics between the groups were small (0.07 ± 0.11) and non-significant. However, follow-up voxel-wise analyses revealed that other concurrent injuries had effects on diffusion metrics, but predominantly in other metrics and at other time-points than the effects observed in the MTBI versus control group analysis. In conclusion, patients with MTBI differed from controls in white matter integrity already 72 h after injury. Diffusion metrics remained relatively stable throughout the first year after MTBI and were not driven by deviating diffusion in patients with a more severe MTBI.

Midlife omega-3 fatty acid intake predicts later life white matter microstructure in an age- and APOE-dependent manner

Omega-3 intake has been positively associated with healthy brain aging, yet it remains unclear whether high omega-3 intake beginning early in life may optimize its protective effects against brain aging. We examined whether omega-3 intake is associated with brain microstructure over 2 decades later among dementia-free older adults. The 128 participants (62% women; age at magnetic resonance imaging: 76.6 ± 7.9) from the Rancho Bernardo Study of Healthy Aging completed at least 1 dietary assessment between 1984 and 1996 and underwent restriction spectrum imaging (RSI) 22.8 ± 3.1 years later. We evaluated associations between prior omega-3 intake and RSI metrics of gray and white matter (WM) microstructure. Higher prior omega-3 intake was associated with greater restricted diffusion in the superior cortico-striatal fasciculus. A correlation between higher prior omega-3 intake and greater cingulum restricted diffusion was stronger among participants >80 years old. Higher omega-3 intake correlated with greater restricted diffusion in the inferior longitudinal and inferior fronto-occipital fasciculus more strongly for apolipoprotein E (APOE) ε4 carriers than noncarriers. Associations were not modified by adjustment for dietary pattern, health, or lifestyle. High omega-3 intake in midlife may help to maintain WM integrity into older age, particularly in the latest decades of life and among APOE ε4 carriers.

Comparison of synthesized and acquired high b -value diffusion-weighted MRI for detection of prostate cancer

Background

High b -value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). To decrease scan time and improve signal-to-noise ratio, high b -value (>1000 s/mm 2 ) images are often synthesized instead of acquired.

Purpose

Qualitatively and quantitatively compare synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.

Study Type

Retrospective.

Subjects

151 consecutive patients who underwent prostate MRI and biopsy.

Sequence

Axial DWI with b =0, 500, 1000, and 2000 s/mm 2 using a 3T clinical scanner using a 32-channel phased-array body coil.

Assessment

We synthesized DWI for b =2000 s/mm 2 via extrapolation based on monoexponential decay, using b =0 and b =500 s/mm 2 (sDWI 500 ) and b =0, b =500, and b =1000 s/mm 2 (sDWI 1000 ). Differences between sDWI and aDWI were evaluated within regions of interest (ROIs). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was also compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI.

Statistical Tests

Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). Statistical significance was assessed using bootstrap difference (two-sided α=0.05).

Results

Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46±35% for sDWI 1000 and -67±24% for sDWI 500 . AUC for aDWI, sDWI 500, sDWI 1000 , and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. When considering the whole field of view, classification accuracy and qualitative image quality decreased notably for sDWI compared to aDWI and RSIrs.

Data Conclusion

sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

A Multicompartmental Diffusion Model for Improved Assessment of Whole-Body Diffusion-weighted Imaging Data and Evaluation of Prostate Cancer Bone Metastases

Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10^-3, 2.8 × 10^-3, and >3.0 ×10^-2 mm²/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

Fixel-based analysis of the diffusion properties of the patients with brain injury and chronic health symptoms

The diffusion properties from diffusion tensor imaging (DTI) are sensitive to white matter (WM) abnormalities and could serve as indicators of diffuse axonal damages incurred during a traumatic brain injury (TBI). Analyses of diffusion metrics in the regions of interest (ROIs) were used to compare the differences in the 18 major fiber tracts in 46 participants, between TBI participants with (n = 17) or without (n = 16) chronic symptoms (CS) and a control group (CG, n = 13). In addition to the widely used diffusion metrics, such as fractional anisotropy (FA), mean (MD), axial (AD) and radial (RD) diffusivities, apparent fiber density (AFD), complexity (CX) and fixel number (FN) derived from Mrtrix3 software package were used to characterize WM tracts and compare between participant groups in the ROIs defined by the fixel numbers. Significant differences were found in FA, AFD, MD, RD and CX in ROIs with different FNs in the corpus callosum forceps minor, left and right inferior longitudinal fasciculus, and left and right uncinate fasciculus for both TBI groups compared to controls. Diffusion properties in ROIs with different FNs can serve as detailed biomarkers of WM abnormalities, especially for individuals with chronic TBI related symptoms.

Intrinsic hippocampal connectivity is associated with individual differences in retrospective duration processing

The estimation of incidentally encoded durations of time intervals (retrospective duration processing) is thought to rely on the retrieval of contextual information associated with a sequence of events, automatically encoded in medial temporal lobe regions. "Time cells" have been described in the hippocampus (HC), encoding the temporal progression of events and their duration. However, whether the HC supports explicit retrospective duration judgments in humans, and which neural dynamics are involved, is still poorly understood. Here we used resting-state fMRI to test the relation between variations in intrinsic connectivity patterns of the HC, and individual differences in retrospective duration processing, assessed using a novel task involving the presentation of ecological stimuli. Results showed that retrospective duration discrimination performance predicted variations in the intrinsic connectivity of the bilateral HC with the right precentral gyrus; follow-up exploratory analyses suggested a role of the CA1 and CA4/DG subfields in driving the observed pattern. Findings provide insights on neural networks associated with implicit processing of durations in the second range.

Anxiety in Parkinson's Disease Is Associated with Changes in Brain Structural Connectivity

BACKGROUND

Anxiety in Parkinson's disease (PD) has been associated with grey matter changes and functional changes in anxiety-related neuronal circuits. So far, no study has analyzed white matter (WM) changes in patients with PD and anxiety.

OBJECTIVE

The aim of this study was to identify WM changes by comparing PD patients with and without anxiety, using diffusion-tensor imaging (DTI).

METHODS

108 non-demented PD patients with (n = 31) and without (n = 77) anxiety as defined by their score on the Parkinson Anxiety Scale participated. DTI was used to determine the fractional anisotropy (FA) and mean diffusivity (MD) in specific tracts within anxiety-related neuronal circuits. Mean FA and MD were compared between groups and correlated with the severity of anxiety adjusted by sex, center, Hoehn & Yahr stage, levodopa equivalent daily dosage, and Hamilton depression rating scale.

RESULTS

Compared to patients without anxiety, PD patients with anxiety showed lower FA within the striato-orbitofrontal, striato-cingulate, cingulate-limbic, and caudate-thalamic tracts; higher FA within the striato-limbic and accumbens-thalamic tracts; higher MD within the striato-thalamic tract and lower MD within the striato-limbic tract.

CONCLUSIONS

Anxiety in PD is associated with microstructural alterations in anxiety-related neuronal circuits within the WM. This result reinforces the view that PD-related anxiety is linked to structural alteration within the anxiety-related brain circuits.