The structural-functional-connectivity coupling of the aging brain

Aging primarily affects memory and executive functions, a relationship that may be underpinned by the fact that almost all adults over 60 years old develop small vessel disease (SVD). The fact that a wide range of neuropathologies could only explain up to 43% of the variation in age-related cognitive impairment suggests that other factors, such as cognitive reserve, may play a role in the brain's resilience against aging-related cognitive decline. This study aims to examine the relationship between structural-functional-connectivity coupling (SFC), and aging, cognitive abilities and reserve, and SVD-related neuropathologies using a cohort of n = 176 healthy elders from the Harvard Aging Brain Study. The SFC is a recently proposed biomarker that reflects the extent to which anatomical brain connections can predict coordinated neural activity. After controlling for the effect of age, sex, and years of education, global SFC, as well as the intra-network SFC of the dorsolateral somatomotor and dorsal attention networks, and the inter-network SFC between dorsolateral somatomotor and frontoparietal networks decreased with age. The global SFC decreased with total cognitive score. There were significant interaction effects between years of education versus white matter hyperintensities and between years of education versus cerebral microbleeds on inter-network SFC. Enlarged perivascular space in basal ganglia was associated with higher inter-network SFC. Our results suggest that cognitive ability is associated with brain coupling at the global level and cognitive reserve with brain coupling at the inter-functional-brain-cluster level with interaction effect from white matter hyperintensities and cerebral microbleed in a cohort of healthy elderlies.

Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping

BACKGROUND

Cerebral microbleeds (CMB) are indicators of severe cerebral small vessel disease (CSVD) that can be identified through hemosiderin-sensitive sequences in MRI. Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI.

PURPOSE

To automatically detect CMB on QSM, we proposed a two-stage deep learning pipeline.

STUDY TYPE

Retrospective.

SUBJECTS

A total number of 1843 CMBs from 393 patients (69 ± 12) with cerebral small vessel disease were included in this study. Seventy-eight subjects (70 ± 13) were used as external testing.

FIELD STRENGTH/SEQUENCE

3 T/QSM.

ASSESSMENT

The proposed pipeline consisted of two stages. In stage I, 2.5D fast radial symmetry transform (FRST) algorithm along with a one-layer convolutional network was used to identify CMB candidate regions in QSM images. In stage II, the V-Net was utilized to reduce false positives. The V-Net was trained using CMB and non CMB labels, which allowed for high-level feature extraction and differentiation between CMBs and CMB mimics like vessels. The location of CMB was assessed according to the microbleeds anatomical rating scale (MARS) system.

STATISTICAL TESTS

The sensitivity and positive predicative value (PPV) were reported to evaluate the performance of the model. The number of false positive per subject was presented.

RESULTS

Our pipeline demonstrated high sensitivities of up to 94.9% at stage I and 93.5% at stage II. The overall sensitivity was 88.9%, and the false positive rate per subject was 2.87. With respect to MARS, sensitivities of above 85% were observed for nine different brain regions.

DATA CONCLUSION

We have presented a deep learning pipeline for detecting CMB in the CSVD cohort, along with a semi-automated MARS scoring system using the proposed method. Our results demonstrated the successful application of deep learning for CMB detection on QSM and outperformed previous handcrafted methods.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Respiratory-Correlated 4-Dimensional Magnetic Resonance Fingerprinting for Liver Cancer Radiation Therapy Motion Management

PURPOSE

The objective of this study was to develop a respiratory-correlated (RC) 4-dimensional (4D) imaging technique based on magnetic resonance fingerprinting (MRF) (RC-4DMRF) for liver tumor motion management in radiation therapy.

METHODS AND MATERIALS

Thirteen patients with liver cancer were prospectively enrolled in this study. k-space MRF signals of the liver were acquired during free-breathing using the fast acquisition with steady-state precession sequence on a 3T scanner. The signals were binned into 8 respiratory phases based on respiratory surrogates, and interphase displacement vector fields were estimated using a phase-specific low-rank optimization method. Hereafter, the tissue property maps, including T1 and T2 relaxation times, and proton density, were reconstructed using a pyramid motion-compensated method that alternatively optimized interphase displacement vector fields and subspace images. To evaluate the efficacy of RC-4DMRF, amplitude motion differences and Pearson correlation coefficients were determined to assess measurement agreement in tumor motion between RC-4DMRF and cine magnetic resonance imaging (MRI); mean absolute percentage errors of the RC-4DMRF-derived tissue maps were calculated to reveal tissue quantification accuracy using digital human phantom; and tumor-to-liver contrast-to-noise ratio of RC-4DMRF images was compared with that of planning CT and contrast-enhanced MRI (CE-MRI) images. A paired Student t test was used for statistical significance analysis with a P value threshold of .05.

RESULTS

RC-4DMRF achieved excellent agreement in motion measurement with cine MRI, yielding the mean (± standard deviation) Pearson correlation coefficients of 0.95 ± 0.05 and 0.93 ± 0.09 and amplitude motion differences of 1.48 ± 1.06 mm and 0.81 ± 0.64 mm in the superior-inferior and anterior-posterior directions, respectively. Moreover, RC-4DMRF achieved high accuracy in tissue property quantification, with mean absolute percentage errors of 8.8%, 9.6%, and 5.0% for T1, T2, and proton density, respectively. Notably, the tumor contrast-to-noise ratio in RC-4DMRI-derived T1 maps (6.41 ± 3.37) was found to be the highest among all tissue property maps, approximately equal to that of CE-MRI (6.96 ± 1.01, P = .862), and substantially higher than that of planning CT (2.91 ± 1.97, P = .048).

CONCLUSIONS

RC-4DMRF demonstrated high accuracy in respiratory motion measurement and tissue properties quantification, potentially facilitating tumor motion management in liver radiation therapy.

Potential mechanisms underlying the accelerated cognitive decline in people with chronic low back pain: A scoping review

A growing body of evidence has shown that people with chronic low back pain (CLBP) demonstrate significantly greater declines in multiple cognitive domains than people who do not have CLBP. Given the high prevalence of CLBP in the ever-growing aging population that may be more vulnerable to cognitive decline, it is important to understand the mechanisms underlying the accelerated cognitive decline observed in this population, so that proper preventive or treatment approaches can be developed and implemented. The current scoping review summarizes what is known regarding the potential mechanisms underlying suboptimal cognitive performance and cognitive decline in people with CLBP and discusses future research directions. Five potential mechanisms were identified based on the findings from 34 included studies: (1) altered activity in the cortex and neural networks; (2) grey matter atrophy; (3) microglial activation and neuroinflammation; (4) comorbidities associated with CLBP; and (5) gut microbiota dysbiosis. Future studies should deepen the understanding of mechanisms underlying this association so that proper prevention and treatment strategies can be developed.

Advanced Diffusion MRI of Stroke Recovery

There is an urgent need for ways to improve our understanding of poststroke recovery to inform the development of novel rehabilitative interventions, and improve the clinical management of stroke patients. Supported by the notion that predictive information on poststroke recovery is embedded not only in the individual brain regions, but also the connections throughout the brain, majority of previous investigations have focused on the relationship between brain functional connections and post-stroke deficit and recovery. However, considering the fact that it is the static anatomical brain connections that constrain and facilitate the dynamic functional brain connections, the microstructures and structural connections of the brain may potentially be better alternatives to the functional MRI-based biomarkers of stroke recovery. This review, therefore, seeks to provide an overview of the basic concept and applications of two recently proposed advanced diffusion MRI techniques, namely lesion network mapping and fixel-based morphometry, that may be useful for the investigation of stroke recovery at the local and global levels of the brain. This review will also highlight the application of some of other emerging advanced diffusion MRI techniques that warrant further investigation in the context of stroke recovery research.

Early stage NSCLS patients' prognostic prediction with multi-information using transformer and graph neural network model

Background:

We proposed a population graph with Transformer-generated and clinical features for the purpose of predicting overall survival (OS) and recurrence-free survival (RFS) for patients with early stage non-small cell lung carcinomas and to compare this model with traditional models.

Methods:

The study included 1705 patients with lung cancer (stages I and II), and a public data set for external validation (n=127). We proposed a graph with edges representing non-imaging patient characteristics and nodes representing imaging tumour region characteristics generated by a pretrained Vision Transformer. The model was compared with a TNM model and a ResNet-Graph model. To evaluate the models' performance, the area under the receiver operator characteristic curve (ROC-AUC) was calculated for both OS and RFS prediction. The Kaplan–Meier method was used to generate prognostic and survival estimates for low- and high-risk groups, along with net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis. An additional subanalysis was conducted to examine the relationship between clinical data and imaging features associated with risk prediction.

Results:

Our model achieved AUC values of 0.785 (95% confidence interval [CI]: 0.716–0.855) and 0.695 (95% CI: 0.603–0.787) on the testing and external data sets for OS prediction, and 0.726 (95% CI: 0.653–0.800) and 0.700 (95% CI: 0.615–0.785) for RFS prediction. Additional survival analyses indicated that our model outperformed the present TNM and ResNet-Graph models in terms of net benefit for survival prediction.

Conclusions:

Our Transformer-Graph model was effective at predicting survival in patients with early stage lung cancer, which was constructed using both imaging and non-imaging clinical features. Some high-risk patients were distinguishable by using a similarity score function defined by non-imaging characteristics such as age, gender, histology type, and tumour location, while Transformer-generated features demonstrated additional benefits for patients whose non-imaging characteristics were non-discriminatory for survival outcomes.

Funding:

The study was supported by the National Natural Science Foundation of China (91959126, 8210071009), and Science and Technology Commission of Shanghai Municipality (20XD1403000, 21YF1438200).

Association between High Diffusion-Weighted Imaging-Derived Functional Tumor Burden of Peritoneal Carcinomatosis and Overall Survival in Patients with Advanced Ovarian Carcinoma

Objective

To investigate the association between functional tumor burden of peritoneal carcinomatosis (PC) derived from diffusion-weighted imaging (DWI) and overall survival in patients with advanced ovarian carcinoma (OC).

Materials and Methods

This prospective study was approved by the local research ethics committee, and informed consent was obtained. Fifty patients (mean age ± standard deviation, 57 ± 12 years) with stage III–IV OC scheduled for primary or interval debulking surgery (IDS) were recruited between June 2016 and December 2021. DWI (b values: 0, 400, and 800 s/mm²) was acquired with a 16-channel phased-array torso coil. The functional PC burden on DWI was derived based on K-means clustering to discard fat, air, and normal tissue. A score similar to the surgical peritoneal cancer index was assigned to each abdominopelvic region, with additional scores assigned to the involvement of critical sites, denoted as the functional peritoneal cancer index (fPCI). The apparent diffusion coefficient (ADC) of the largest lesion was calculated. Patients were dichotomized by immediate surgical outcome into high- and low-risk groups (with and without residual disease, respectively) with subsequent survival analysis using the Kaplan-Meier curve and log-rank test. Multivariable Cox proportional hazards regression was used to evaluate the association between DWI-derived results and overall survival.

Results

Fifteen (30.0%) patients underwent primary debulking surgery, and 35 (70.0%) patients received neoadjuvant chemotherapy followed by IDS. Complete tumor debulking was achieved in 32 patients. Patients with residual disease after debulking surgery had reduced overall survival (p = 0.043). The fPCI/ADC was negatively associated with overall survival when accounted for clinicopathological information with a hazard ratio of 1.254 for high fPCI/ADC (95% confidence interval, 1.007–1.560; p = 0.043).

Conclusion

A high DWI-derived functional tumor burden was associated with decreased overall survival in patients with advanced OC.

Repeatability of MR fingerprinting in normal cervix and utility in cervical carcinoma

Background

Magnetic resonance fingerprinting (MRF) is a fast-imaging acquisition technique that generates quantitative and co-registered parametric maps. The aim of this feasibility study was to evaluate the agreement between MRF and phantom reference values, scan-rescan repeatability of MRF in normal cervix, and its ability to distinguish cervical carcinoma (CC) from normal cervical tissues.

Methods

An International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) phantom was scanned using MRF 15 times over 65 days. Agreement between MRF and phantom reference T1 and T2 values was assessed by linear regression. Healthy volunteers and patients with suspected CC were prospectively recruited. MRF was repeated twice for healthy volunteers (MRF1 and MRF2). Volumes of interest of normal cervical tissues and CC were delineated on T1 and T2 maps. MRF scan-rescan repeatability was evaluated by Bland-Altman plots, within-subject coefficients of variation (wCV), and intraclass correlation coefficients (ICC). T1 and T2 values were compared between CC and normal cervical tissues using Mann-Whitney U test. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic efficiency.

Results

Strong correlations were observed between MRF and phantom (R²=0.999 for T1, 0.981 for T2). Twelve healthy volunteers (28.7±5.1 years) and 28 patients with CC (54.6±15.2 years) were recruited for the in-vivo experiments. Repeatability of MRF parameters were wCV <3% for T1, <5% for T2 and ICC ≥0.92 for T1, ≥0.94 for T2. T1 value of CC (1,529±112 ms) was higher than normal mucosa [MRF1: 1,430±129 ms, MRF2: 1,440±130 ms; P=0.031, area under the curve (AUC) ≥0.717] and normal stroma (MRF1: 1,258±101 ms, MRF2: 1,276±105 ms; P<0.001, AUC ≥0.946). T2 value of CC (69±9 ms) was lower than normal mucosa (MRF1: 88±16 ms, MRF2: 87±13 ms; P<0.001, AUC ≥0.854), but was not different from normal stroma (P=0.919).

Conclusions

Excellent agreement was observed between MRF and phantom reference values. MRF exhibited excellent scan-rescan repeatability in normal cervix with potential value in differentiating CC from normal cervical tissues.

A multi-inversion-recovery magnetic resonance fingerprinting for multi-compartment water mapping

PURPOSE

This study aimed at introducing short-T1/T2 compartment to MR fingerprinting (MRF) at 3 T. Water that is bound to myelin macromolecules have significantly shorter T1 and T2 than free water and can be distinguished from free water by multi-compartment analysis.

METHODS

We developed a new multi-inversion-recovery (mIR) water mapping-MRF based on an unbalanced steady-state coherent sequence (FISP). mIR pulses with an interval of 400 or 500 repetition times (TRs) were inserted into the conventional FISP MRF sequence. Data from our proposed mIR MRF was used to quantify different compartments, including myelin water, gray matter free water, and white matter free water, of brain water by virtue of the iterative non-negative least square (NNLS) with reweighting. Three healthy volunteers were scanned with mIR MRF on a clinical 3 T MRI.

RESULTS

Using an extended phase graph simulation, we found that our proposed mIR scheme with four IR pulses allowed differentiation between short and long T1/T2 components. For in vivo experiments, we achieved the quantification of myelin water, gray matter water, and white matter water at an image resolution of 1.17 × 1.17 × 5 mm³/pixel. As compared to the conventional MRF technique with single IR, our proposed mIR improved the detection of myelin water content. In addition, mIR MRF using spiral-in/out trajectory provided a higher signal level compared with that with spiral-out trajectory. Myelin water quantification using mIR MRF with 4 IR and 5 IR pulses were qualitatively similar. Meanwhile, 5 IR MRF showed fewer artifacts in myelin water detection.

CONCLUSION

We developed a new mIR MRF sequence for the rapid quantification of brain water compartments.

Investigation of the effect of acquisition schemes on time-resolved magnetic resonance fingerprinting

Purpose.This study aims to investigate the feasibility of different acquisition methods for time-resolved magnetic resonance fingerprinting (TR-MRF) in computer simulation.Methods.An extended cardiac-torso (XCAT) phantom is used to generate abdominal T1, T2, and proton density maps for MRF simulation. The simulated MRF technique consists of an IR-FISP MRF sequence with spiral trajectory acquisition. MRF maps were simulated with different numbers of repetitions from 1 to 15. Three different methods were used to generate TR-MRF maps: (1) continuous acquisition without delay between MRF repetitions; (2) continuous acquisition with 5 s delay between MRF repetitions; (3) triggered acquisition with variable delay between MRF repetitions to allow the next acquisition to start at different respiration phase. After the generation of TR-MRF maps, the image quality indexes including the absolute T1 and T2 values, signal-to-noise-ratio (SNR), tumor-to-liver contrast-to-noise ratio, error in the amplitude of diaphragm motion and tumor volume error were used to evaluate the reconstructed parameter maps. Three volunteers were recruited to test the feasibility of the selected acquisition method.Results.Dynamic MR parametric maps using three different acquisition methods were estimated. The overall and liver T1 value error, liver SNR in T1 and T2 maps, and tumor SNR from T1 maps from triggered method is statistically significantly better than the other two methods (p-value < 0.05). The other image quality indexes have no significant difference between the triggered method and the other two continuous acquisition methods. All image quality indexes exhibit no significant difference between the acquisition methods with 0 s and 5 s delay. The triggered method was successfully performed in three healthy volunteers.Conclusion.TR-MRF technique was investigated using three different acquisition methods in computer simulation where the triggered method showed better performance than the other two methods. The triggered method has been tested successfully in healthy volunteers.

Relation between rich-club organization versus brain functions and functional recovery after acute ischemic stroke

Studies have shown the brain's rich-club organization may underpin brain function and be associated with various brain disorders. In this study, we aimed to investigate the relation between poststroke brain functions and functional recovery versus the rich-club organization of the structural brain network of patients after first-time acute ischemic stroke. A cohort of 16 acute ischemic stroke patients (11 males) was recruited. Structural brain networks were measured using diffusion tensor imaging within 1 week and at 1, 3 and 6 months after stroke. Motor impairment was assessed using the Upper-Extremity Fugl-Meyer motor scale and activities of daily living using the Barthel Index at the same time points as MRI. The rich-club regions that were stable over the course of stroke recovery included the bilateral dorsolateral superior frontal gyri, right supplementary motor area, and left median cingulate and paracingulate gyri. The network properties that correlated with poststroke brain functions were mainly the ratio between communication cost ratio and density ratio of rich-club, feeder and local connections. The recovery of both motor functions and activities of daily living were correlated with higher normalized rich club coefficients and a shorter length of local connections within a week after stroke. The communication cost ratio of feeder connections, the length of rich-club and local connections, and normalized rich club coefficients were found to be potential prognostic indicators of stroke recovery. Our results provide additional support to the notion that different types of network connections play different roles in brain functions as well as functional recovery.

Functional tumour burden of peritoneal carcinomatosis derived from DWI could predict incomplete tumour debulking in advanced ovarian carcinoma

OBJECTIVES

To investigate the predictive value of peritoneal carcinomatosis (PC) quantification by DWI in determining incomplete tumour debulking in ovarian carcinoma (OC).

METHODS

Prospective patients with suspected stage III-IV or recurrent OC were recruited for DWI before surgery. PC on DWI was segmented semi-automatically by k-means clustering, retaining voxels with intermediate apparent diffusion coefficient (ADC) to quantify PC burden. A scoring system, functional peritoneal cancer index (fPCI), was proposed based on the segmentation of tumour volume in 13 abdominopelvic regions with additional point given to involvement of critical sites. ADC of the largest PC was recorded. The surgical complexity and outcomes (complete vs. incomplete tumour debulking) were documented. fPCI was correlated with surgical PCI (sPCI), surgical complexity, and its ability to predict incomplete tumour debulking.

RESULTS

Fifty-three patients with stage III-IV or recurrent OC were included with a mean age of 56.1 ± 11.8 years old. Complete tumour debulking was achieved in 38/53 patients (71.7%). Significant correlation was found between fPCI and sPCI (r > 0.757, p < 0.001). Patients with high-fPCI (fPCI ≥ 6) had a high surgical complexity score (p = 0.043) with 84.2% received radical or supra-radical surgery. The mean fPCI was significantly higher in patients with incomplete tumour debulking than in those with complete debulking (10.27 vs. 4.71, p < 0.001). fPCI/ADC combined with The International Federation of Gynecology and Obstetrics stage achieved 92.5% accuracy in predicting incomplete tumour debulking (AUC 0.947).

CONCLUSIONS

DWI-derived fPCI offered a semi-automated estimation of PC burden. fPCI/ADC could predict the likelihood of incomplete tumour debulking with high accuracy.

KEY POINTS

• Functional peritoneal cancer index (fPCI) derived from DWI offered a semi-automated estimation of tumour burden in ovarian carcinoma. • fPCI was highly correlated with surgical PCI (sPCI). • fPCI/ADC could predict the likelihood of incomplete tumour debulking with high accuracy.

MRI reconstruction using deep Bayesian estimation

PURPOSE

To develop a deep learning-based Bayesian estimation for MRI reconstruction.

METHODS

We modeled the MRI reconstruction problem with Bayes's theorem, following the recently proposed PixelCNN++ method. The image reconstruction from incomplete k-space measurement was obtained by maximizing the posterior possibility. A generative network was utilized as the image prior, which was computationally tractable, and the k-space data fidelity was enforced by using an equality constraint. The stochastic backpropagation was utilized to calculate the descent gradient in the process of maximum a posterior, and a projected subgradient method was used to impose the equality constraint. In contrast to the other deep learning reconstruction methods, the proposed one used the likelihood of prior as the training loss and the objective function in reconstruction to improve the image quality.

RESULTS

The proposed method showed an improved performance in preserving image details and reducing aliasing artifacts, compared with GRAPPA, ℓ 1 -ESPRiT, model-based deep learning architecture for inverse problems (MODL), and variational network (VN), last two were state-of-the-art deep learning reconstruction methods. The proposed method generally achieved more than 3 dB peak signal-to-noise ratio improvement for compressed sensing and parallel imaging reconstructions compared with the other methods.

CONCLUSIONS

The Bayesian estimation significantly improved the reconstruction performance, compared with the conventional ℓ 1 -sparsity prior in compressed sensing reconstruction tasks. More importantly, the proposed reconstruction framework can be generalized for most MRI reconstruction scenarios.

MRF-ZOOM for the unbalanced steady-state free precession (ubSSFP) magnetic resonance fingerprinting

In magnetic resonance fingerprinting (MRF), tissue parameters are determined by finding the best-match to the acquired MR signal from a predefined signal dictionary. This dictionary searching (DS) process is generally performed in an exhaustive manner, which requires a large predefined dictionary and long searching time. A fast MRF DS algorithm, MRF-ZOOM, was recently proposed based on DS objective function optimization. As a proof-of-concept study, MRF-ZOOM was only tested with one of the earliest MRF sequences but not with the recently more popular unbalanced steady state free precession MRF sequence (MRF-ubSSFP, or MRF-FISP). Meanwhile noise effects on MRF and MRF-ZOOM have not been examined. The purpose of this study was to address these open questions and to verify whether MRF-ZOOM can be combined with a dictionary-compression based method to gain further speed. Numerical simulations were performed to evaluate the DS objective function properties, noise effects on MRF, and to compare MRF-ZOOM with other methods in terms of speed and accuracy. In-vivo experiments were performed as well. Evaluation results showed that premises of MRF-ZOOM held for MRF-FISP; noise did not affect MRF-ZOOM more than the conventional MRF method; when SNR ≥ 1, MRF quantification yielded accurate results. Dictionary compression introduced quantification errors more to T2 quantification. MRF-ZOOM was thousands of times faster than the conventional MRF method. Combining MRF-ZOOM with dictionary compression showed no benefit in terms of fitting speed. In conclusion, MRF-ZOOM is valid for MRF- FISP, and can remarkably save MRF dictionary generation and searching time without sacrificing matching accuracy.

Elimination of residual aliasing artifact that resembles brain lesion on multi-oblique diffusion-weighted echo-planar imaging with parallel imaging using virtual coil acquisition

BACKGROUND

Single-shot diffusion-weighted echo-planar imaging (ssDW-EPI) acquired with parallel imaging and a multi-oblique scan plane may suffer from residual aliasing artifacts, resembling lesions on the calculated apparent diffusion coefficient (ADC) map.

PURPOSE

To combine ssDW-EPI and virtual coil acquisition and develop a self-reference reconstruction method to eliminate the residual aliasing artifact on multi-oblique ssDW-EPI sequence with parallel imaging and multiple signal averaging.

STUDY TYPE

Prospective.

SUBJECTS

Three healthy subjects and 50 stroke patients.

FIELD STRENGTH/SEQUENCE

Conventional ssDW-EPI with parallel imaging, and proposed ssDW-EPI with virtual coil acquisition at 1.5T.

ASSESSMENT

The efficacy of the proposed method was evaluated in 50 stroke patients by comparing the ssDW-EPI with conventional parallel imaging reconstructions. The extent of residual aliasing artifacts were rated on a 5-point Likert scale by three independent raters. Only the data without residual aliasing artifacts on conventional ssDW-EPI were included for the assessment of signal-to-noise ratio (SNR), ghost-to-signal ratio (GSR), and ADC.

STATISTICAL TESTS

The interobserver agreements for examining residual aliasing artifacts were measured by the intraclass correlation coefficient (ICC). A two-sample t-test was performed for comparing SNR, GSR, and ADC.

RESULTS

There was a perfect agreement (ICC = 1.00) in the examination of residual aliasing artifacts on images obtained using the proposed method. The incidence rates of the residual aliasing artifact on the ADC maps obtained from the scanner console and proposed method were 60% (ie, 30 out of 50) and 0%, respectively. The proposed method offers significantly lower GSR than conventional parallel imaging reconstruction (P < 0.001). There was no significant difference in SNR (P = 0.20-0.51) and ADC values (P = 0.20-0.94) between conventional parallel imaging reconstructions and the proposed method.

DATA CONCLUSION

It appears that our method could effectively eliminate artifacts and significantly improve the GSR of b = 0 T₂ WI and b > 0 DWI, as well as permit ADC measurement consistent with conventional techniques. Our method may be beneficial to clinical assessment of the brain that utilizes multi-oblique ssDW-EPI.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1442-1453.

Negative Affect Shared with Siblings is Associated with Structural Brain Network Efficiency and Loneliness in Adolescents

Loneliness has a strong neurobiological basis reflected by its specific relationships with structural brain connectivity. Critically, affect traits are highly related to loneliness, which shows close association with the onset and severity of major depressive disorder. This diffusion imaging study was conducted on a sample of adolescent siblings to examine whether positive and negative affect traits were related to loneliness, with brain network efficiency playing a mediating role. The findings of this study confirmed that both global and average local efficiency negatively mediated the association between low positive affect and high negative affect and loneliness, and the mediation was more sensitive to sibling-shared affect traits. The findings have important implications for interventions targeted at reducing the detrimental impact of familiar negative emotional experiences and loneliness.

Brain connectomic associations with traditional Chinese medicine diagnostic classification of major depressive disorder: a diffusion tensor imaging study

Background

Major depressive disorder (MDD) is highly heterogeneous in pathogenesis and manifestations. Further classification may help characterize its heterogeneity. We previously have shown differential metabolomic profiles of traditional Chinese medicine (TCM) diagnostic subtypes of MDD. We further determined brain connectomic associations with TCM subtypes of MDD.

Methods

In this naturalistic study, 44 medication-free patients with a recurrent depressive episode were classified into liver qi stagnation (LQS, n = 26) and Heart and Spleen Deficiency (HSD, n = 18) subtypes according to TCM diagnosis. Healthy subjects (n = 28) were included as controls. Whole-brain white matter connectivity was analyzed on diffusion tensor imaging.

Results

The LQS subtype showed significant differences in multiple network metrics of the angular gyrus, middle occipital gyrus, calcarine sulcus, and Heschl's gyrus compared to the other two groups. The HSD subtype had markedly greater regional connectivity of the insula, parahippocampal gyrus, and posterior cingulate gyrus than the other two groups, and microstructural abnormalities of the frontal medial orbital gyrus and middle temporal pole. The insular betweenness centrality was strongly inversely correlated with the severity of depression and dichotomized the two subtypes at the optimal cutoff value with acceptable sensitivity and specificity.

Conclusions

The LQS subtype is mainly characterized by aberrant connectivity of the audiovisual perception-related temporal-occipital network, whereas the HSD subtype is more closely associated with hyperconnectivity and microstructural abnormalities of the limbic-paralimbic network. Insular connectivity may serve a biomarker for TCM-based classification of depression.Trial registration Registered at http://www.clinicaltrials.gov (NCT02346682) on January 27, 2015.

Age-Specific Associations of Renal Impairment and Cerebral Small Vessel Disease Burden in Chinese with Ischaemic Stroke

BACKGROUND

Recent studies in Caucasians with transient ischaemic attack or ischaemic stroke have demonstrated significant age-specific associations between cerebral small vessel disease (SVD) burden on magnetic resonance imaging and renal impairment. We aimed to validate these findings in a large cohort of Chinese with ischaemic stroke.

METHODS

In 959 Chinese with ischaemic stroke who received a brain magnetic resonance imaging at the University of Hong Kong, we determined the age-specific associations of renal impairment (glomerular filtration rate < 60 mL/min/1.73 m²) with neuroimaging markers of SVD as well as with the SVD score.

RESULTS

Although renal impairment was associated with the SVD score in univariate analysis in all patients (odds ratio 1.61, 95% confidence interval 1.24-2.09, P < .0001), these associations were attenuated after adjusting for age and sex (P = .38). Similar findings were noted in patients with ischaemic stroke due to SVD and non-SVD subtypes. However, in 222 of 959 patients aged <60, renal impairment was independently associated with an increasing microbleed (adjusted odds ratio 6.82, 2.26-20.59), subcortical (4.97, 1.62-15.24) periventricular white matter hyperintensity (3.96, 1.08-14.51) and global SVD burden (3.41, 1.16-10.04; all P < .05) even after adjusting for age, sex, and vascular risk factors. Nevertheless, there were no associations between renal impairment and individual neuroimaging markers of SVD nor with the SVD score in patients aged ≥60 after adjusting for age and sex (all P > .05).

CONCLUSIONS

In Chinese with ischaemic stroke, renal impairment was independently associated with microbleed, white matter hyperintensity and global SVD burden in individuals aged <60, but not in those aged ≥60, suggesting that there may be shared susceptibilities to premature systemic disease.

Fast dictionary generation and searching for magnetic resonance fingerprinting

A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed. MRF ZOOM is quasi-parameter-separable so the multiplicative computation complexity is broken into additive one. Evaluations showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in. Using real data, it yielded nearly the same results as produced by the original method. MRF ZOOM provides a super-fast solution for MR parameter quantification.

Quantitative susceptibility mapping as an indicator of subcortical and limbic iron abnormality in Parkinson's disease with dementia

Late stage Parkinson's disease (PD) patients were commonly observed with other non-motor comorbidities such as dementia and psychosis. While abnormal iron level in the substantia nigra was clinically accepted as a biomarker of PD, it was also suggested that the increased iron deposition could impair other brain regions and induce non-motor symptoms. A new Magnetic Resonance Imaging (MRI) called Quantitative Susceptibility Mapping (QSM) has been found to measure iron concentration in the grey matter reliably. In this study, we investigated iron level of different subcortical and limbic structures of Parkinson's disease (PD) patients with and without dementia by QSM. QSM and volumetric analysis by MRI were performed in 10 PD dementia (PDD) patients (73 ± 6 years), 31 PD patients (63 ± 8 years) and 27 healthy controls (62 ± 7 years). No significant differences were observed in the L-Dopa equivalent dosage for the two PD groups (p = 0.125). Putative iron content was evaluated in different subcortical and limbic structures of the three groups, as well as its relationship with cognitive performance. One-way ANCOVA with FDR adjustment at level of 0.05, adjusted for age and gender, showed significant group differences for left and right hippocampus (p = 0.015 & 0.032, respectively, BH-corrected for multiple ROIs) and right thalamus (p = 0.032, BH-corrected). Post-hoc test with Bonferroni's correction suggested higher magnetic susceptibility in PDD patients than healthy controls in the left and right hippocampus (p = 0.001 & 0.047, respectively, Bonferroni's corrected), while PD patients had higher magnetic susceptibility than the healthy controls in right hippocampus and right thalamus (p = 0.006 & 0.005, respectively, Bonferroni's corrected). PDD patients also had higher susceptibility than the non-demented PD patients in left hippocampus (p = 0.046, Bonferroni's corrected). The magnetic susceptibilities of the left and right hippocampus were negatively correlated with the Mini-Mental State Examination score (r = -0.329 & -0.386, respectively; p < 0.05). This study provides support for iron accumulation in limbic structures of PDD and PD patients and its correlation with cognitive performance, however, its putative involvement in development of non-motor cognitive dysfunction in PD pathogenesis remains to be elucidated.

Long-Term Prognostic Implications of Cerebral Microbleeds in Chinese Patients With Ischemic Stroke

Background

This study was performed to determine the clinical correlates and long‐term prognostic implications of microbleed burden and location in Chinese patients with ischemic stroke.

Methods and Results

We recruited 1003 predominantly Chinese patients with ischemic stroke who received magnetic resonance imaging at the University of Hong Kong. We determined the clinical correlates of microbleeds and the long‐term risks (3126 patient‐years of follow‐up) of recurrent ischemic stroke and intracerebral hemorrhage (ICH) by microbleed burden (0 versus 1, 2–4, and ≥5) and location, adjusting for age, sex, and vascular risk factors and stratified by antithrombotic use. Microbleeds were present in 450 of 1003 of the study population (119/450 had ≥5, 187/450 had mixed location). Having ≥5 microbleeds was independently associated with prior antiplatelet and anticoagulant use, whereas microbleeds of mixed location were independently associated with hypertension and prior anticoagulant use (all P<0.05). Microbleed burden was associated with an increased risk of ICH (microbleed burden versus no microbleeds: 1 microbleed: multivariate hazard ratio: 0.59 [95% confidence interval, 0.07–5.05]; 2–4 microbleeds: multivariate hazard ratio: 2.14 [95% confidence interval, 0.50–9.12]; ≥5 microbleeds: multivariate hazard ratio: 9.51 [95% confidence interval, 3.25–27.81]; P_trend<0.0001), but the relationship of microbleed burden and risk of recurrent ischemic stroke was not significant (P_trend=0.054). Similar findings were noted in the 862 of 1003 patients treated with antiplatelet agents only (ICH: P_trend<0.0001; ischemic stroke P_trend=0.096). Multivariate analysis revealed that, independent of vascular risk factors, antithrombotic use, and other neuroimaging markers of small vessel disease, having ≥5 microbleeds (multivariate hazard ratio: 6.08 [95% confidence interval, 1.11–33.21]; P=0.037) was identified as an independent predictor of subsequent ICH, but neither microbleed burden nor location was predictive of recurrent ischemic stroke risk.

Conclusions

In Chinese patients with ischemic stroke, a high burden of cerebral microbleeds was significantly associated with an increased risk of ICH; however, neither microbleed location nor burden was associated with recurrent ischemic stroke risk.

Concordance of FDG PET/CT metabolic tumour volume versus DW-MRI functional tumour volume with T2-weighted anatomical tumour volume in cervical cancer

Background

¹⁸F–fluoro-deoxyglucose positron emission tomography with computed tomography (FDG PET/CT) has been employed to define radiotherapy targets using a threshold based on the standardised uptake value (SUV), and has been described for use in cervical cancer. The aim of this study was to evaluate the concordance between the metabolic tumour volume (MTV) measured on FDG PET/CT and the anatomical tumour volume (ATV) measured on T2-weighted magnetic resonance imaging (T2W-MRI); and compared with the functional tumour volume (FTV) measured on diffusion-weighted MRI (DW-MRI) in cervical cancer, taking the T2W-ATV as gold standard.

Methods

Consecutive newly diagnosed cervical cancer patients who underwent FDG PET/CT and DW-MRI were retrospectively reviewed from June 2013 to July 2017.

Volumes of interest was inserted to the focal hypermetabolic activity corresponding to the cervical tumour on FDG PET/CT with automated tumour contouring and manual adjustment, based on SUV 20%–80% thresholds of the maximum SUV (SUVmax) to define the MTV_20–80, with intervals of 5%.

Tumour areas were manually delineated on T2W-MRI and multiplied by slice thickness to calculate the ATV.

FTV were derived by manually delineating tumour area on ADC map, multiplied by the slice thickness to determine the FTV_(manual). Diffusion restricted areas was extracted from b0 and ADC map using K-means clustering to determine the FTV_{(semi-automated)}.

The ATVs, FTVs and the MTVs at different thresholds were compared using the mean and correlated using Pearson’s product-moment correlation.

Results

Twenty-nine patients were evaluated (median age 52 years). Paired difference of mean between ATV and MTV was the closest and not statistically significant at MTV₃₀ (−2.9cm³, −5.2%, p = 0.301). This was less than the differences between ATV and FTV_{(semi-automated)} (25.0cm³, 45.1%, p < 0.001) and FTV_(manual) (11.2cm³, 20.1%, p = 0.001). The correlation of MTV₃₀ with ATV was excellent (r = 0.968, p < 0.001) and better than that of the FTVs.

Conclusions

Our study demonstrated that MTV₃₀ was the only parameter investigated with no statistically significant difference with ATV, had the least absolute difference from ATV, and showed excellent positive correlation with ATV, suggesting its superiority as a functional imaging modality when compared with DW-MRI and supporting its use as a surrogate for ATV for radiotherapy tumour contouring.

Functional deficits induced by cortical microinfarcts

Clinical studies have revealed a strong link between increased burden of cerebral microinfarcts and risk for cognitive impairment. Since the sum of tissue damage incurred by microinfarcts is a miniscule percentage of total brain volume, we hypothesized that microinfarcts disrupt brain function beyond the injury site visible to histological or radiological examination. We tested this idea using a mouse model of microinfarcts, where single penetrating vessels that supply mouse cortex were occluded by targeted photothrombosis. We found that in vivo structural and diffusion MRI reliably reported the acute microinfarct core, based on spatial co-registrations with post-mortem stains of neuronal viability. Consistent with our hypothesis, c-Fos assays for neuronal activity and in vivo imaging of single vessel hemodynamics both reported functional deficits in viable peri-lesional tissues beyond the microinfarct core. We estimated that the volume of tissue with functional deficit in cortex was at least 12-fold greater than the volume of the microinfarct core. Impaired hemodynamic responses in peri-lesional tissues persisted at least 14 days, and were attributed to lasting deficits in neuronal circuitry or neurovascular coupling. These data show how individually miniscule microinfarcts could contribute to broader brain dysfunction during vascular cognitive impairment and dementia.

Sensitivity of diffusion MRI to perilesional reactive astrogliosis in focal ischemia

Reactive astrogliosis is a response to injury in the central nervous system that plays an essential role in inflammation and tissue repair. It is characterized by hypertrophy of astrocytes, alterations in astrocyte gene expression and astrocyte proliferation. Reactive astrogliosis occurs in multiple neuropathologies, including stroke, traumatic brain injury and Alzheimer's disease, and it has been proposed as a possible source of the changes in diffusion magnetic resonance imaging (dMRI) metrics observed with these diseases. In this study, the sensitivity of dMRI to reactive astrogliosis was tested in an animal model of focal acute and subacute ischemia induced by the vasoconstricting peptide, endothelin-1. Reactive astrogliosis in perilesional cortex was quantified by calculating the astrocyte surface density as determined with a glial fibrillary acidic protein (GFAP) antibody, whereas perilesional diffusion changes were measured in vivo with diffusional kurtosis imaging. We found substantial changes in the surface density of GFAP-positive astrocyte processes and modest changes in dMRI metrics in the perilesional motor cortex following stroke. Although there are time point-specific correlations between dMRI and histological measures, there is no definitive evidence for a causal relationship.

Tensor estimation for double-pulsed diffusional kurtosis imaging

Double-pulsed diffusional kurtosis imaging (DP-DKI) represents the double diffusion encoding (DDE) MRI signal in terms of six-dimensional (6D) diffusion and kurtosis tensors. Here a method for estimating these tensors from experimental data is described. A standard numerical algorithm for tensor estimation from conventional (i.e. single diffusion encoding) diffusional kurtosis imaging (DKI) data is generalized to DP-DKI. This algorithm is based on a weighted least squares (WLS) fit of the signal model to the data combined with constraints designed to minimize unphysical parameter estimates. The numerical algorithm then takes the form of a quadratic programming problem. The principal change required to adapt the conventional DKI fitting algorithm to DP-DKI is replacing the three-dimensional diffusion and kurtosis tensors with the 6D tensors needed for DP-DKI. In this way, the 6D diffusion and kurtosis tensors for DP-DKI can be conveniently estimated from DDE data by using constrained WLS, providing a practical means for condensing DDE measurements into well-defined mathematical constructs that may be useful for interpreting and applying DDE MRI. Data from healthy volunteers for brain are used to demonstrate the DP-DKI tensor estimation algorithm. In particular, representative parametric maps of selected tensor-derived rotational invariants are presented.

Characterization of Extensive Microstructural Variations Associated with Punctate White Matter Lesions in Preterm Neonates

BACKGROUND AND PURPOSE

Punctate white matter lesions are common in preterm neonates. Neurodevelopmental outcomes of the neonates are related to the degree of extension. This study aimed to characterize the extent of microstructural variations for different punctate white matter lesion grades.

MATERIALS AND METHODS

Preterm neonates with punctate white matter lesions were divided into 3 grades (from mild to severe: grades I-III). DTI-derived fractional anisotropy, axial diffusivity, and radial diffusivity between patients with punctate white matter lesions and controls were compared with Tract-Based Spatial Statistics and tract-quantification methods.

RESULTS

Thirty-three preterm neonates with punctate white matter lesions and 33 matched controls were enrolled. There were 15, 9, and 9 patients, respectively, in grades I, II, and III. Punctate white matter lesions were mainly located in white matter adjacent to the lateral ventricles, especially regions lateral to the trigone, posterior horns, and centrum semiovale and/or corona radiata. Extensive microstructural changes were observed in neonates with grade III punctate white matter lesions, while no significant changes in DTI metrics were found for grades I and II. A pattern of increased axial diffusivity, increased radial diffusivity, and reduced/unchanged fractional anisotropy was found in regions adjacent to punctate white matter lesion sites seen on T1WI and T2WI. Unchanged axial diffusivity, increased radial diffusivity, and reduced/unchanged fractional anisotropy were observed in regions distant from punctate white matter lesion sites.

CONCLUSIONS

White matter microstructural variations were different across punctate white matter lesion grades. Extensive change patterns varied according to the distance to the lesion sites in neonates with severe punctate white matter lesions. These findings may help in determining the outcomes of punctate white matter lesions and selecting treatment strategies.

Structural Brain Network Reorganization in Patients with Neuropsychiatric Systemic Lupus Erythematosus

BACKGROUND AND PURPOSE

Patients with neuropsychiatric systemic lupus erythematosus have worse outcomes compared with those with systemic lupus erythematosus. A better understanding of the mechanisms of neuropsychiatric systemic lupus erythematosus could potentially improve diagnosis and management. The goal of this study was to investigate the differences in the structural brain network of patients with neuropsychiatric systemic lupus erythematosus compared with patients with systemic lupus erythematosus by using brain connectivity analysis.

MATERIALS AND METHODS

We recruited 20 subjects for each patient cohort and age-matched healthy controls. The topology and efficiency of the network and the characteristics of various brain hubs were investigated by using brain connectivity analysis of diffusion MR imaging data.

RESULTS

There were more extensive reorganizations in the structural brain network of patients with neuropsychiatric systemic lupus erythematosus than in patients with systemic lupus erythematosus. For example, the network of the former had significantly decreased clustering coefficient and local efficiency. They also had significantly lower nodal efficiency in the superior temporal gyrus (P = .046) and middle temporal gyrus (P = .041).

CONCLUSIONS

Our results hint at a plausible relationship between the neuropsychiatric symptoms and reorganization of the structural brain network of patients with systemic lupus erythematosus. Brain connectivity analysis may be a potential tool to subtype these patients.

Application of diffusional kurtosis imaging to detect occult brain damage in multiple sclerosis and neuromyelitis optica

Multiple sclerosis (MS) and neuromyelitis optica (NMO) are two common types of inflammatory demyelinating disease of the central nervous system. Early distinction of NMO from MS is crucial but quite challenging. In this study, 13 NMO spectrum disorder patients (Expanded Disability Status Scale (EDSS) of 3.0 ± 1.7, ranging from 2 to 6.5; disease duration of 5.3 ± 4.7 years), 17 relapsing-remitting MS patients (EDSS of 2.6 ± 1.4, ranging from 1 to 5.5; disease duration of 7.9 ± 7.8 years) and 18 healthy volunteers were recruited. Diffusional kurtosis imaging was employed to discriminate NMO and MS patients at the early or stable stage from each other, and from healthy volunteers. The presence of alterations in diffusion and diffusional kurtosis metrics in normal-appearing white matter (NAWM) and diffusely increased mean diffusivity (MD) in the cortical normal-appearing gray matter (NAGM) favors the diagnosis of MS rather than NMO. Meanwhile, normal diffusivities and kurtosis metrics in all NAWM as well as increases in MD in the frontal and temporal NAGM suggest NMO. Our results suggest that diffusion and diffusional kurtosis metrics may well aid in discriminating the two diseases.

Microvascular basis for growth of small infarcts following occlusion of single penetrating arterioles in mouse cortex

Small cerebral infarcts, i.e. microinfarcts, are common in the aging brain and linked to vascular cognitive impairment. However, little is known about the acute growth of these minute lesions and their effect on blood flow in surrounding tissues. We modeled microinfarcts in the mouse cortex by inducing photothrombotic clots in single penetrating arterioles. The resultant hemodynamic changes in tissues surrounding the occluded vessel were then studied using in vivo two-photon microscopy. We were able to generate a spectrum of infarct volumes by occluding arterioles that carried a range of blood fluxes. Those resulting from occlusion of high-flux penetrating arterioles (flux of 2 nL/s or higher) exhibited a radial outgrowth that encompassed unusually large tissue volumes. The gradual expansion of these infarcts was propagated by an evolving insufficiency in capillary flow that encroached on territories of neighboring penetrating arterioles, leading to the stagnation and recruitment of their perfusion domains into the final infarct volume. Our results suggest that local collapse of microvascular function contributes to tissue damage incurred by single penetrating arteriole occlusions in mice, and that a similar mechanism may add to pathophysiology induced by microinfarcts of the human brain.

Hemisphere, gender and age-related effects on iron deposition in deep gray matter revealed by quantitative susceptibility mapping

The purpose of this work was to investigate the effects of hemispheric location, gender and age on susceptibility value, as well as the association between susceptibility value and diffusional metrics, in deep gray matter. Iron content was estimated in vivo using quantitative susceptibility mapping. Microstructure was probed using diffusional kurtosis imaging. Regional susceptibility and diffusional metrics were measured for the putamen, caudate nucleus, globus pallidus, thalamus, substantia nigra and red nucleus in 42 healthy adults (age range 25-78 years). Susceptibility value was significantly higher in the left than the right side of the caudate nucleus (P = 0.043) and substantia nigra (P < 0.001). Women exhibited lower susceptibility values than men in the thalamus (P < 0.001) and red nucleus (P = 0.032). Significant age-related increases of susceptibility were observed in the putamen (P < 0.001), red nucleus (P < 0.001), substantia nigra (P = 0.004), caudate nucleus (P < 0.001) and globus pallidus (P = 0.017). The putamen exhibited the highest rate of iron accumulation with aging (slope of linear regression = 0.73 × 10(-3) ppm/year), which was nearly twice those in substantia nigra (slope = 0.40 × 10(-3) ppm/year) and caudate nucleus (slope = 0.39 × 10(-3) ppm/year). Significant positive correlations between the susceptibility value and diffusion measurements were observed for fractional anisotropy (P = 0.045) and mean kurtosis (P = 0.048) in the putamen without controlling for age. Neither correlation was significant after controlling for age. Hemisphere, gender and age-related differences in iron measurements were observed in deep gray matter. Notably, the putamen exhibited the highest rate of increase in susceptibility with aging. Correlations between susceptibility value and microstructural measurements were inconclusive. These findings could provide new clues for unveiling mechanisms underlying iron-related neurodegenerative diseases.

Abstract T P91: Changes in Diffusion Measures Following Experimental Stroke and Rehabilitative Training

Diffusional kurtosis imaging (DKI) is an advanced diffusion MRI (dMRI) technique that can quantify several diffusion measures that are highly sensitive to microstructural changes in brain. Previously, we found enhanced sensitivity of DKI-derived diffusion metrics following acute stroke in the lesion core and peri-lesional area that correlated with infiltration of activated glia. Studies have demonstrated that skilled motor training after ischemic damage affecting the sensorimotor cortex (SMC) induces functional motor recovery and neural plasticity in the remaining motor cortex. In the current study, we investigated the relationship between dMRI measures and rehabilitation-induced forelimb functional recovery. Adult male rats (3-4 months old) were trained on a skilled reaching task and given an endothelin-1 (ET-1) induced unilateral ischemic stroke over the SMC. Animals then received 21 days of impaired forelimb rehabilitative training (RT) on a reaching task or no rehabilitative training (No-RT). All animals underwent MRI scans prior to injury, 5 days post-injury, and after 21 days of RT or No-RT procedures, using a 7T Bruker Biospec MRI scanner to acquire dMRI images. Diffusivity and diffusional kurtosis metrics were calculated with in-house software. Multi-slice regions-of-interest were drawn in the lesion core, peri-lesional remaining motor cortex and in the forelimb region of the SMC in the non-infarcted hemisphere. All animals had lesion-induced motor deficits following ET-1 strokes and RT improved reaching forelimb function compared to No-RT. Peri-lesional diffusional kurtosis measures remained significantly different between the lesion and non-lesion SMC at four weeks post-injury, at which time diffusivity differences were no longer detected. Fractional anisotropy of the corpus callosum, inclusive of areas with SMC interhemispheric connections was higher following RT versus No-RT. These data indicate that the kurtosis of peri-lesional motor cortex remains sensitive to chronic ischemic effects, unlike diffusivity measures, and that skilled motor RT likely alters white matter connectivity between the two hemispheres.

Diffusional kurtosis and diffusion tensor imaging reveal different time-sensitive stroke-induced microstructural changes

BACKGROUND AND PURPOSE

Diffusion MRI is a promising, clinically feasible imaging technique commonly used to describe white matter changes after stroke. We investigated the sensitivity of diffusion MRI to detect microstructural alterations in gray matter after sensorimotor cortex stroke in adult male rats.

METHODS

The mean diffusivity (MD) and mean kurtosis of perilesional motor cortex were compared with measures in the contralesional forelimb area of sensorimotor cortex at 2 hours, 24 hours, 72 hours, or 25 days after surgery. MD and mean kurtosis were correlated to the surface densities of glia, dendrites, and axons.

RESULTS

Perilesional mean kurtosis was increased at 72 hours and 25 days after stroke, whereas MD was no longer different from contralesional sensorimotor cortex at 24 hours after stroke. There was a significant increase in the density of glial processes at 72 hours after stroke in perilesional motor cortex, which correlated with perilesional MD.

CONCLUSIONS

These data support that mean kurtosis and MD provide different but complimentary information on acute and chronic changes in perilesional cortex. Glia infiltration is associated with pseudonormalization of MD in the perilesional motor cortex at 72 hours after lesion; however, this association is absent 25 days after lesion. These data suggest that there are likely several different, time-specific microstructural changes underlying these 2 complimentary diffusion measures.

Kurtosis analysis of neural diffusion organization

A computational framework is presented for relating the kurtosis tensor for water diffusion in brain to tissue models of brain microstructure. The tissue models are assumed to be comprised of non-exchanging compartments that may be associated with various microstructural spaces separated by cell membranes. Within each compartment the water diffusion is regarded as Gaussian, although the diffusion for the full system would typically be non-Gaussian. The model parameters are determined so as to minimize the Frobenius norm of the difference between the measured kurtosis tensor and the model kurtosis tensor. This framework, referred to as kurtosis analysis of neural diffusion organization (KANDO), may be used to help provide a biophysical interpretation to the information provided by the kurtosis tensor. In addition, KANDO combined with diffusional kurtosis imaging can furnish a practical approach for developing candidate biomarkers for neuropathologies that involve alterations in tissue microstructure. KANDO is illustrated for simple tissue models of white and gray matter using data obtained from healthy human subjects.

Histological correlation of diffusional kurtosis and white matter modeling metrics in cuprizone-induced corpus callosum demyelination

The cuprizone mouse model is well established for studying the processes of both demyelination and remyelination in the corpus callosum, and it has been utilized together with diffusion tensor imaging (DTI) to investigate myelin and axonal pathology. Although some underlying morphological mechanisms contributing to the changes in diffusion tensor (DT) metrics have been identified, the understanding of specific associations between histology and diffusion measures remains limited. Diffusional kurtosis imaging (DKI) is an extension of DTI that provides metrics of diffusional non-Gaussianity, for which an associated white matter modeling (WMM) method has been developed. The main goal of the present study was to quantitatively assess the relationships between diffusion measures and histological measures in the mouse model of cuprizone-induced corpus callosum demyelination. The diffusional kurtosis (DK) and WMM metrics were found to provide additional information that enhances the sensitivity to detect the morphological heterogeneity in the chronic phase of the disease process in the rostral segment of the corpus callosum. Specifically, in the rostral segment, axonal water fraction (d = 2.6; p < 0.0001), radial kurtosis (d = 2.0; p = 0.001) and mean kurtosis (d = 1.5; p = 0.005) showed the most sensitivity between groups with respect to yielding statistically significant p values and high Cohen's d values. These results demonstrate the ability of DK and WMM metrics to detect white mater changes and inflammatory processes associated with cuprizone-induced demyelination. They also validate, in part, the application of these new WMM metrics for studying neurological diseases, as well as helping to elucidate their biophysical meaning.

Double-pulsed diffusional kurtosis imaging

Diffusional kurtosis imaging (DKI) is extended to double-pulsed-field-gradient (d-PFG) diffusion MRI sequences. This gives a practical approach for acquiring and analyzing d-PFG data. In particular, the leading d-PFG effects, beyond what conventional single-pulsed field gradient (s-PFG) provides, are interpreted in terms of the kurtosis for a diffusion displacement probability density function (dPDF) in a six-dimensional (6D) space. The 6D diffusional kurtosis encodes the unique information provided by d-PFG sequences up to second order in the b-value. This observation leads to a compact expression for the signalmagnitude, and it suggests novel data acquisition and analysis methods. Double-pulsed DKI (DP-DKI) is demonstrated for in vivo mouse brain with d-PFG data obtained at 7 T.

Double-pulsed diffusional kurtosis imaging

Diffusional kurtosis imaging (DKI) is extended to double-pulsed-field-gradient (d-PFG) diffusion MRI sequences. This gives a practical approach for acquiring and analyzing d-PFG data. In particular, the leading d-PFG effects, beyond what conventional single-pulsed field gradient (s-PFG) provides, are interpreted in terms of the kurtosis for a diffusion displacement probability density function (dPDF) in a six-dimensional (6D) space. The 6D diffusional kurtosis encodes the unique information provided by d-PFG sequences up to second order in the b-value. This observation leads to a compact expression for the signal magnitude, and it suggests novel data acquisition and analysis methods. Double-pulsed DKI (DP-DKI) is demonstrated for in vivo mouse brain with d-PFG data obtained at 7 T. Copyright © 2014 John Wiley & Sons, Ltd.

Abstract WP44: Acute Damage to Corticospinal Tract Detected by Diffusional Kurtosis Correlates with Motor Outcome at 3 Months After Stroke - A Preliminary Report

Background: Diffusional kurtosis imaging (DKI) is a recently developed diffusion MRI method that yields, in addition to conventional diffusion information, the diffusional kurtosis (K) and white-matter-specific metrics (WMM) that may better characterize tissue microstructure after stroke. This study aims to quantitatively test the hypothesis that motor impairment 3 months post- stroke is correlated with the acute damage to the corticospinal tract (CST) measured by kurtosis metrics.

Methods: DKI was acquired from 15 first-time acute ischemic stroke patients in the acute phase (within 48 hours) with various degrees of motor deficit. Patients were assessed at baseline (between 2 to 5 days from onset of symptom) and at 90 days (+/- 14 days) after stroke using the Fugl-Meyer Motor Scale (FMMS). Kurtosis metrics, including WMM (intra-axonal diffusivity (D a ), extra-axonal axial (D e,// ) and radial (D e,// ) diffusivity ) as well as fractional anisotropy (FA), mean diffusivity (MD), mean Kurtosis (MK) were measured in the lesional CST. Correlation analyses were applied among these metrics and FMMS at 90 days.

Results: Corticospinal tract intra-axonal environment was altered by acute ischemia. D a ( r = 0.75, p = 0.001) and D e,// ( r = 0.52, p=0.048) measured in the acute phase correlated with motor outcome at 3 months. FA, MD, MK and D e,// showed no significant correlations.

Conclusions: The preliminary data supports acute damage to CST detected by WMM with DKI correlated with motor outcome at 3 months. The WMM has potential to be an early imaging biomarker for motor outcome prediction.

Stroke assessment with diffusional kurtosis imaging

BACKGROUND AND PURPOSE

Despite being the gold standard technique for stroke assessment, conventional diffusion MRI provides only partial information about tissue microstructure. Diffusional kurtosis imaging is an advanced diffusion MRI method that yields, in addition to conventional diffusion information, the diffusional kurtosis, which may help improve characterization of tissue microstructure. In particular, this additional information permits the description of white matter (WM) in terms of WM-specific diffusion metrics. The goal of this study is to elucidate possible biophysical mechanisms underlying ischemia using these new WM metrics.

METHODS

We performed a retrospective review of clinical and diffusional kurtosis imaging data of 44 patients with acute/subacute ischemic stroke. Patients with a history of brain neoplasm or intracranial hemorrhages were excluded from this study. Region of interest analysis was performed to measure percent change of diffusion metrics in ischemic WM lesions compared with the contralateral hemisphere.

RESULTS

Kurtosis maps exhibit distinct ischemic lesion heterogeneity that is not apparent on apparent diffusion coefficient maps. Kurtosis metrics also have significantly higher absolute percent change than complementary conventional diffusion metrics. Our WM metrics reveal an increase in axonal density and a larger decrease in the intra-axonal (Da) compared with extra-axonal diffusion microenvironment of the ischemic WM lesion.

CONCLUSIONS

The well-known decrease in the apparent diffusion coefficient of WM after ischemia is found to be mainly driven by a significant drop in the intra-axonal diffusion microenvironment. Our results suggest that ischemia preferentially alters intra-axonal environment, consistent with a proposed mechanism of focal enlargement of axons known as axonal swelling or beading.

Spatiotemporal dynamics of diffusional kurtosis, mean diffusivity and perfusion changes in experimental stroke

Diffusional kurtosis imaging (DKI), which measures the non-Gaussianity of water diffusion, has been demonstrated to be a sensitive biomarker in many neuropathologies. The goal of this study was to longitudinally examine the spatiotemporal dynamics of DKI in cerebral ischemia in an animal model of permanent and transient (45 min) middle cerebral artery occlusion (MCAO) during the hyperacute, acute and chronic phases. Diffusional kurtosis showed different spatiotemporal dynamics. In particular, mean kurtosis (MK) was sensitive to hyperacute and acute stroke changes, and exhibited different contrast than mean diffusivity (MD) and higher contrast than fractional anisotropy (FA) and T2. MK contrast persisted 1 to 7 days post-occlusion, whereas MD showed renormalization at day 1-2 and reversed contrast at day 7. The current study showed that DKI has the potential to complement existing stroke imaging techniques, particularly in the assessment of subacute to early chronic stroke evolution.

Voxel-based analysis of postnatal white matter microstructure in mice exposed to immune challenge in early or late pregnancy

Maternal infection during prenatal life is a risk factor for neurodevelopmental disorders, including schizophrenia and autism, in the offspring. We and others have reported white mater microstructure abnormalities in prefrontal-striato-temporal networks in these disorders. In addition we have shown that early rather than late maternal immune challenge in the mouse model precipitates ventricular volume change and impairs sensorimotor gating similar to that found in schizophrenia. However, it is not known whether the timing of maternal infection has a differential impact upon white matter microstructural indices. Therefore this study directly tested the effect of early or late gestation maternal immune activation on post-natal white matter microstructure in the mouse. The viral mimic PolyI:C was administered on day 9 or day 17 of gestation. In-vivo diffusion tensor imaging (DTI) was carried out when the offspring reached adulthood. We describe a novel application of voxel-based analysis to evaluate fractional anisotrophy (FA). In addition we conducted a preliminary immunohistochemical exploration of the oligodendrocyte marker, 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase), to determine whether differences in myelination might contribute to any changes in FA observed. Our results provide experimental evidence that prenatal exposure to inflammation elicits widespread differences in FA throughout fronto-striatal-limbic circuits compared to control saline exposure. Moreover, FA changes were more extensive in the group exposed earliest in gestation.

In vivo diffusion tensor imaging of chronic spinal cord compression in rat model

Chronic spinal cord compression induced cervical myelopathy is a comon cause of spinal cord dysfunction. The exact mechanisms of underlying progressive cell death remain to be elucidated. In this study, in vivo diffusion tensor imaging (DTI) has been applied to investigate the microstructural changes of white matter (WM) in this neurodegenerative disease. Compared with conventional MRI techniques, DTI is believed to be more specific to pathological changes. Radial diffusivity (lambda upper left and right quadrants) is higher in the ipilesional region, suggesting demyelination or axonal degradation may occur after prolonged compression. Near the epicenter of lesion, axial diffusivity (lambda(//)) is lower. Also, caudal-rostral asymmetry has been observed in lambda(//). Feasibility of using DTI to detect microstructural changes in chronic disease has been demonstrated.

In vivo DTI assessment of hepatic ischemia reperfusion injury in an experimental rat model

PURPOSE

To investigate hepatic ischemia reperfusion injury (IRI) using diffusion tensor imaging (DTI).

MATERIALS AND METHODS

Ten Sprague-Dawley rats were scanned at 7 Tesla (T) with DTI using b-value of 1000 s/mm(2) and 6 gradient directions before, 2 h, and 1 day after 30-min total hepatic IRI. Apparent diffusion coefficient or mean diffusivity (MD), directional diffusivities and fractional anisotropy (FA) were measured. Seven of the animals were also examined with spin-echo echo-planar diffusion-weighted imaging (DWI) with seven b-values up to 2000 s/mm(2) to estimate the true diffusion coefficient (D), blood pseudodiffusion coefficient (D), and perfusion fraction (f) using a bi-compartmental model.

RESULTS

MD 2 h after IRI (0.77 +/- 0.07 x 10(-3) mm(2)/s) was significantly lower (P < 0.01) than that before (1.03 +/- 0.07 x 10(-3) mm(2)/s) and 1 day after IRI (1.01 +/- 0.05 x 10(-3) mm(2)/s). Meanwhile, FA 2 h after IRI (0.33 +/- 0.03) was significantly higher (P < 0.01) than that before (0.21 +/- 0.02) and 1 day after IRI (0.20 +/- 0.02). The bi-compartmental model analysis revealed the transient decrease in D, D and f 2 h after IRI. Liver histology showed the multifocal cell swelling 3 h after IRI and widespread cell necrosis/apoptosis 1 day after IRI. Sinusoidal narrowing and congestion of erythrocytes were also observed 3 h and 1 day after IRI.

CONCLUSION

DTI can characterize hepatic IRI by detecting the transient change in both MD and FA.

The effects of hypercapnia on DTI quantification in anesthetized rat brain

Diffusion Tensor Imaging (DTI) offers a valuable in vivo tool to characterize water diffusion behavior in biological tissues, particularly brain tissues. The accuracy of DTI derived parameters can directly affect the interpretation of underlying microstructures, physiology or pathologies. It is anticipated that measurement of apparent diffusion coefficient (ADC) using DTI could be influenced and complicated by the presence of water molecules in brain vasculature. However, little is known about to what degree does blood signal from vasculature affect the diffusion quantitation. In this study, we examined the effects of hypercapnia on DTI quantification in rat brains using inhalation of 5% carbon dioxide (CO2). It was found that statistically significant changes occurred in parametric DTI maps in response to cerebrovascular challenges, indicating that vascular factors could interfere with in vivo DTI characterization of neural tissues. Consequently, hemodynamic alterations can potentially affect the DTI quantitation and detection of tissue microstructures and pathological alterations. Therefore, cautions must be taken when interpreting DTI parameters in vivo.

Prenatal immune challenge is an environmental risk factor for brain and behavior change relevant to schizophrenia: evidence from MRI in a mouse model

Objectives

Maternal infection during pregnancy increases risk of severe neuropsychiatric disorders, including schizophrenia and autism, in the offspring. The most consistent brain structural abnormality in patients with schizophrenia is enlarged lateral ventricles. However, it is unknown whether the aetiology of ventriculomegaly in schizophrenia involves prenatal infectious processes. The present experiments tested the hypothesis that there is a causal relationship between prenatal immune challenge and emergence of ventricular abnormalities relevant to schizophrenia in adulthood.

Method

We used an established mouse model of maternal immune activation (MIA) by the viral mimic PolyI:C administered in early (day 9) or late (day 17) gestation. Automated voxel-based morphometry mapped cerebrospinal fluid across the whole brain of adult offspring and the results were validated by manual region-of-interest tracing of the lateral ventricles. Parallel behavioral testing determined the existence of schizophrenia-related sensorimotor gating abnormalities.

Results

PolyI:C-induced immune activation, in early but not late gestation, caused marked enlargement of lateral ventricles in adulthood, without affecting total white and grey matter volumes. This early exposure disrupted sensorimotor gating, in the form of prepulse inhibition. Identical immune challenge in late gestation resulted in significant expansion of 4^th ventricle volume but did not disrupt sensorimotor gating.

Conclusions

Our results provide the first experimental evidence that prenatal immune activation is an environmental risk factor for adult ventricular enlargement relevant to schizophrenia. The data indicate immune-associated environmental insults targeting early foetal development may have more extensive neurodevelopmental impact than identical insults in late prenatal life.

Advanced MR diffusion characterization of neural tissue using directional diffusion kurtosis analysis

MR Diffusion kurtosis imaging (DKI) was proposed recently to study the deviation of water diffusion from Gaussian distribution. Mean kurtosis (MK), directionally averaged kurtosis, has been shown to be useful in assessing pathophysilogical changes. However, MK is not sensitive to kurtosis change occurring along a specific direction. Therefore, orthogonal transformation of the 4th order kurtosis tensor was introduced in the current study to compute kurtoses along the 3 eigenvector directions of the 2nd order diffusion tensor. Such axial (K( parallel)) and radial (K perpendicular) kurtoses measured the kurtoses along the directions parallel and perpendicular, respectively, to the principal diffusion direction. DKI experiments were performed in normal adult and formalin-fixed rat brain, and developmental brains. The results showed that directional kurtosis analysis revealed different information for tissue characterization.

Measurement of common carotid artery lumen dynamics during the cardiac cycle using magnetic resonance TrueFISP cine imaging

PURPOSE

To demonstrate magnetic resonance (MR) measurements of vascular lumen dynamics in common carotid arteries by using true fast imaging with steady-state precession (TrueFISP) cine imaging with an aim to provide additional physiologic information on the vessels.

MATERIALS AND METHODS

The left and right common carotid arteries were studied in normal young men (N = 6; age = 21-24 years; body weight = 130-175 lbs) using electrocardiogram (ECG)-triggered TrueFISP cine imaging at 20 frames per cardiac cycle. Lumen area waveforms were characterized with specific time and amplitude ratios. Distension values were quantified.

RESULTS

Distension values were measured at 25.92 +/- 2.58% and 27.58 +/- 4.44% for the left and right common carotid arteries, respectively. These findings are consistent with those previously documented using ultrasound imaging in a similar age group. Consistent lumen area waveform characteristics were found among the subjects studied.

CONCLUSION

These findings demonstrate for the first time that the use of TrueFISP cine imaging is a robust, rapid technique for quantifying carotid lumen area dynamics and distension, which may be valuable in characterizing and diagnosing cardiovascular diseases.

Identifying rodent olfactory bulb structures with micro-DTI

Olfactory bulb (OB) is one of the most developed systems in rodent models with complex neuronal organization and anatomical structures. MR diffusion tensor imaging (DTI) is a non-invasive technique to probe tissue microstructures by examining the diffusion characteristics of water molecules. This paper presents how different OB layers can be identified and quantitatively characterized by micro-DTI using a specially constructed micro-imaging radio frequency (RF) coil. High spatial resolution and high signal to noise ratio (SNR) DTI images of ex vivo rat OBs were obtained. Distinct contrasts were observed between various olfactory bulb layers in trace map, fractional anisotropy (FA) map and FA color map, all in consistency with the known OB neuroanatomy. These experimental results demonstrate the utility of micro-DTI in investigation of complex OB organization.