Fast magnetic resonance diffusion-weighted imaging of acute human stroke

From Brownian motion to virtual biopsy: a historical perspective from 40 years of diffusion MRI

Diffusion MRI was introduced in 1985, showing how the diffusive motion of molecules, especially water, could be spatially encoded with MRI to produce images revealing the underlying structure of biologic tissues at a microscopic scale. Diffusion is one of several Intravoxel Incoherent Motions (IVIM) accessible to MRI together with blood microcirculation. Diffusion imaging first revolutionized the management of acute cerebral ischemia by allowing diagnosis at an acute stage when therapies can still work, saving the outcomes of many patients. Since then, the field of diffusion imaging has expanded to the whole body, with broad applications in both clinical and research settings, providing insights into tissue integrity, structural and functional abnormalities from the hindered diffusive movement of water molecules in tissues. Diffusion imaging is particularly used to manage many neurologic disorders and in oncology for detecting and classifying cancer lesions, as well as monitoring treatment response at an early stage. The second major impact of diffusion imaging concerns the wiring of the brain (Diffusion Tensor Imaging, DTI), allowing to obtain from the anisotropic movement of water molecules in the brain white-matter images in 3 dimensions of the brain connections making up the Connectome. DTI has opened up new avenues of clinical diagnosis and research to investigate brain diseases, neurogenesis and aging, with a rapidly extending field of application in psychiatry, revealing how mental illnesses could be seen as Connectome spacetime disorders. Adding that water diffusion is closely associated to neuronal activity, as shown from diffusion fMRI, one may consider that diffusion MRI is ideally suited to investigate both brain structure and function. This article retraces the early days and milestones of diffusion MRI which spawned over 40 years, showing how diffusion MRI emerged and expanded in the research and clinical fields, up to become a pillar of modern clinical imaging.

David G. Sherman Lecture: Improving Stroke Diagnosis and Treatment-A Journey Toward the End of Time

In the 2024 David G. Sherman Lecture, Steven J. Warach, illustrating with examples from his research, walks through the history of magnetic resonance imaging in acute stroke from the 1990s and early 2000s with the introduction, validation, and application of diffusion-weighted imaging, penumbral imaging (the diffusion-perfusion mismatch), and other imaging markers of the acute stroke pathology into routine clinical practice and stroke trials. The adaptation of diffusion-weighted imaging for clinical scanners in the acute hospital setting began a revolution in ischemic stroke diagnosis as the presence, location, and size of ischemic lesions could now be visualized at the earliest times after stroke onset when computed tomography and conventional magnetic resonance imaging still appeared normal. In combination with perfusion magnetic resonance imaging, diffusion-weighted imaging made imaging of the ischemic penumbra a practical reality for routine clinical use and feasible for integration as a selection tool into clinical trials. It was apparent from the initial use of diffusion-perfusion imaging in acute stroke that many patients had persistence of penumbra as late as 24 hours after stroke onset although the probability of penumbra decreased over time. The therapeutic time window for ischemic stroke selected by clinical and temporal criteria reflected the decreased proportion of patients with the therapeutic target over time rather than the absence of the penumbral target in all patients at later times. This work provided the empirical and conceptual framework for the shift toward selection and evaluation of patients for acute stroke therapies based on direct observation of the target pathology and away from the exclusive dependence on clinical and temporal surrogates to infer the presence of stroke therapeutic targets, a shift that has expanded the indications for acute reperfusion therapies over the last 10 years.

Motion-induced phase-corrected homodyne reconstruction for partial Fourier single-shot diffusion-weighted echo planar imaging of the liver

Partial Fourier encoding is popular in single-shot (ss) diffusion-weighted (DW) echo planar imaging (EPI) because it enables a shorter echo time (TE) and, hence, improves the signal-to-noise-ratio. Motion during diffusion encoding causes k-space shifting and dispersion, which compromises the quality of the homodyne reconstruction. This work provides a comprehensive understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data in the presence of motion-induced phase and proposes the motion-induced phase-corrected homodyne (mpc-hdyne) reconstruction method to ameliorate these artifacts. Simulations with different types of motion-induced phase were performed to provide an understanding of the potential artifacts that occur in the homodyne reconstruction of partial Fourier ss-DW-EPI data. To correct for the artifacts, the mpc-hdyne reconstruction is proposed. The algorithm recenters k-space, updates the partial Fourier factor according to detected global k-space shifts, and removes low-resolution nonlinear phase before the conventional homodyne reconstruction. The mpc-hdyne reconstruction is tested on both simulation and in vivo data. Motion-induced phase can cause signal overestimation, worm artifacts, and signal loss in partial Fourier ss-DW-EPI data with the conventional homodyne reconstruction. Simulation and in vivo data showed that the proposed mpc-hdyne reconstruction ameliorated artifacts, yielding higher quality DW images compared with conventional homodyne reconstruction. Based on the understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data, the mpc-hdyne reconstruction was proposed and showed superior performance compared with the conventional homodyne reconstruction on both simulation and in vivo data.

Artery of Percheron Infarction: Clinical Presentation and Outcomes

Background and Objectives

Occlusion of the artery of Percheron (AOP) produces bilateral thalamic infarction classically leading to deficits of arousal. This nonspecific presentation complicates the diagnosis of acute ischemic stroke. We sought to describe the spectrum of clinical presentation, diagnostic neuroimaging findings, and outcomes in AOP infarction (AOPi).

Methods

We conducted a keyword search of our health system's neuroimaging database from 2014 to 2022 to identify patients with AOPi. We abstracted patient demographics, clinical presentation, neuroimaging findings, acute treatment, and modified Rankin Scale (mRS) scores (at baseline, 3 months, and 12 months). We used descriptive statistics to report our findings.

Results

Our initial keyword search identified 192 potential AOPi cases. Fifteen cases of AOPi were confirmed and included in our study (8 female [53%], median age 65 years [interquartile range (IQR): 59.5-79.5], median presenting NIHSS 6 [IQR: 2-22]). Common clinical findings on presentation were systolic blood pressure (SBP) > 140: 12 patients (80%); decreased level of consciousness (LOC): 11 patients (73%); diplopia: 8 patients (57%); disorientation: 6 patients (42%); dysarthria: 4 patients (28%); and acute memory/cognitive disturbance: 3 patients (21%). Twelve cases (80%) presented to the emergency department (ED). Median time from symptom onset to ED arrival was 774.5 minutes (IQR: 202.25-3789.0), 4 cases (27%) arrived within 4.5 hours, and one patient (7%) received intravenous thrombolysis. The median time from ED arrival to stroke diagnosis was 519.0 minutes (IQR: 227.5-1307). Head CT was only diagnostic when obtained >570 minutes from time last known well; MRI was diagnostic at all time points. Rates of functional independence (mRS ≤2) at baseline, 3 months, and 12 months were 64%, 21%, and 18%, respectively.

Discussion

The diagnosis of stroke was considerably delayed in patients with AOPi, and only one patient received IV thrombolysis. SBP >140, impaired consciousness, and diplopia were the most common findings at presentation. CT was often nondiagnostic, but MRI demonstrated bilateral thalamic infarct in all cases. AOPi caused considerable long-term morbidity. Clinicians should maintain a high degree of suspicion for AOP stroke and consider thrombolysis in appropriately selected patients.

Breaking with a dogma: persisting diffusion restrictions (pDWI) in follow-up after endovascular treatment for stroke

BACKGROUND

Post-stroke diffusion weighted imaging (DWI) signal transformation of the infarct core, which results in high apparent diffusion coefficient (ADC) values and variable DWI signal intensity, is completed no later than 1 month after onset of ischemia. We observed frequent exceptions to this timeline of change in DWI signal, which led to uncertainties in further clinical patient management.

METHODS

A prospective single-center study of patients treated with mechanical thrombectomy of a large vessel occlusion in the anterior circulation was conducted. Patients received high-resolution MRI at 3T, including DWI, in the acute post-stroke phase and in the follow-up after 3-12 months.

RESULTS

Overall, 78 patients (45 men) of mean age 63.6 years were evaluated. We identified persisting or new diffusion restriction in 29 of the 78 patients (37.2%) on follow-up imaging. Diffusion restrictions in a different location from the infarct core, representing new (sub-)acute ischemia, were observed in four patients (5.1%). Smaller areas of persisting diffusion restriction (pDWI lesions with high DWI signal and reduced ADC values) within the former infarct core were observed in 25 patients (32.1%) without clinical evidence of recurrent stroke, but with worse outcome scores at follow-up compared with patients without pDWI lesions. The presence of pDWI lesions is associated with a large primary infarct core (multivariate regression OR 1.03 (95% CI 1.01 to 1.05); p<0.01), mediating the relationship between pDWI lesions and clinical outcome.

CONCLUSION

Smaller foci of persisting diffusion restriction (pDWI lesions) in the follow-up after endovascular treatment for stroke are frequent and likely represent a slowed ADC signal progression within a formerly large infarct core.

Dependence of apparent diffusion coefficient on slice position in magnetic resonance diffusion imaging

PURPOSE

The position dependence of the apparent diffusion coefficient (ADC) in magnetic resonance imaging (MRI) by echo-planar imaging (EPI)- and turbo spin echo (TSE)-diffusion-weighted imaging (DWI) was assessed using phantoms.

METHODS

Six pure water-filled containers were placed parallel to the direction of the static magnetic field from the center of the magnetic field to the foot direction (five containers) and the head direction (one container). Six slice positions were set, and a cross-section image was scanned at the center of each container using a 1.5-T MRI scanner. Diffusion times for both EPI- and TSE-DWI were matched as much as possible. The slice thickness was adjusted to match the signal-to-noise ratio (SNR) at the center of the magnetic field for both sequences. A B₁ map was analyzed. The ADC and SNR at each position of both sequences were tested using the Wilcoxon signed-rank test (P = 0.05) and compared using Friedman and Steel-Dwass multiple comparison tests (P = 0.05). Pearson correlation coefficients between ADC and SNR and between ADC and flip angle (FA) were calculated.

RESULTS

ADC decreased significantly with distance from the center of the magnetic field for both EPI-DWI and TSE-DWI (P < 0.05). TSE-ADC was significantly higher than EPI-ADC for all combinations (P < 0.01). Based on the Friedman test, the SNR of EPI- and TSE-DWI was significantly different and depended on the slice position (P < 0.01). The Pearson correlation coefficient between ADC and SNR was 0.78 in EPI-DWI and 0.60 in TSE-DWI, whereas that between ADC and FA was 0.97 in EPI-DWI and 0.94 in TSE-DWI. The FA decreased by 0.048 and 0.047° per mm from the center of the magnetic field to head and foot directions, respectively.

CONCLUSION

ADC depends on the slice position and decreases with an increase in distance from the magnetic field center. Caution should be taken when comparing and quantitatively evaluating the ADC at sites shifted in the long-axis direction.

Neuroimaging in Patient Selection for Thrombectomy, From the AJR Special Series on Emergency Radiology

Endovascular thrombectomy has become the standard-of-care treatment for carefully selected patients with acute ischemic stroke due to a large-vessel occlusion of the anterior circulation. Neuroimaging plays a vital role in determining patient eligibility for thrombectomy, both in the early (0-6 hours from symptom onset) and late (> 6 to 24 hours from symptom onset) time windows. Various neuroimaging algorithms are used to determine thrombectomy eligibility, and each algorithm must be optimized for institutional workflow. In this review, we describe common imaging modalities and recommended algorithms for the evaluation of patients for endovascular thrombectomy. We also discuss emerging patient populations who might qualify for thrombectomy in the coming years.

DWI-Based Radiomics Predicts the Functional Outcome of Endovascular Treatment in Acute Basilar Artery Occlusion

BACKGROUND AND PURPOSE

Endovascular treatment is a reference treatment for acute basilar artery occlusion (ABAO). However, no established and specific methods are available for the preoperative screening of patients with ABAO suitable for endovascular treatment. This study explores the potential value of DWI-based radiomics in predicting the functional outcomes of endovascular treatment in ABAO.

MATERIALS AND METHODS

Patients with ABAO treated with endovascular treatment from the BASILAR registry (91 patients in the training cohort) and the hospitals in the Northwest of China (31 patients for the external testing cohort) were included in this study. The Mann-Whitney U test, random forests algorithm, and least absolute shrinkage and selection operator were used to reduce the feature dimension. A machine learning model was developed on the basis of the training cohort to predict the prognosis of endovascular treatment. The performance of the model was evaluated on the independent external testing cohort.

RESULTS

A subset of radiomics features (n = 6) was used to predict the functional outcomes in patients with ABAO. The areas under the receiver operating characteristic curve of the radiomics model were 0.870 and 0.781 in the training cohort and testing cohort, respectively. The accuracy of the radiomics model was 77.4%, with a sensitivity of 78.9%, specificity of 75%, positive predictive value of 83.3%, and negative predictive value of 69.2% in the testing cohort.

CONCLUSIONS

DWI-based radiomics can predict the prognosis of endovascular treatment in patients with ABAO, hence allowing a potentially better selection of patients who are most likely to benefit from this treatment.

Comparison of uniform-density, variable-density, and dual-density spiral samplings for multi-shot DWI

PURPOSE

To compare the performances of uniform-density spiral (UDS), variable-density spiral (VDS), and dual-density spiral (DDS) samplings in multi-shot diffusion imaging, and determine a sampling strategy that balances reliability of shot navigator and overall DWI image quality.

THEORY AND METHODS

UDS, VDS, and DDS trajectories were implemented to achieve four-shot diffusion-weighted spiral imaging. First, the static B0 off-resonance effects in UDS, VDS, and DDS acquisitions were analyzed based on a signal model. Then, in vivo experiments were performed to verify the theoretical analyses, and fractional anisotropy (FA) fitting residuals were used to quantitatively assess the quality of spiral diffusion data for tensor estimation. Finally, the SNR performances and g-factor behavior of the three spiral samplings were evaluated using a Monte Carlo-based pseudo multiple replica method.

RESULTS

Among the three spiral trajectories with the same readout duration, UDS sampling exhibited the least off-resonance artifacts. This was most evident when the static B0 off-resonance effect was severe. The UDS diffusion images had higher anatomical fidelity and lower FA fitting residuals than the other two counterparts. Furthermore, the four-shot UDS acquisition achieved the best SNR performance in diffusion imaging with 12.11% and 40.85% improvements over the VDS and DDS acquisitions with the same readout duration, respectively.

CONCLUSION

UDS sampling is an efficient spiral acquisition scheme for high-resolution diffusion imaging with reliable navigator information. It provides superior off-resonance performance and SNR efficiency over the VDS and DDS samplings for the tested scenarios.

PET/MR imaging of inflammation in atherosclerosis

Myocardial infarction, stroke, mental disorders, neurodegenerative processes, autoimmune diseases, cancer and the human immunodeficiency virus impact the haematopoietic system, which through immunity and inflammation may aggravate pre-existing atherosclerosis. The interplay between the haematopoietic system and its modulation of atherosclerosis has been studied by imaging the cardiovascular system and the activation of haematopoietic organs via scanners integrating positron emission tomography and resonance imaging (PET/MRI). In this Perspective, we review the applicability of integrated whole-body PET/MRI for the study of immune-mediated phenomena associated with haematopoietic activity and cardiovascular disease, and discuss the translational opportunities and challenges of the technology.

Reperfusion Injury Is Associated With Poor Outcome in Patients With Recanalization After Thrombectomy

BACKGROUND

The existence of cerebral reperfusion injury in human beings remains controversial. Thus, we aimed to explore the presence of reperfusion injury in acute ischemic stroke patients with recanalization after mechanical thrombectomy and analyzed its impact on neurological outcome.

METHODS

We reviewed our prospectively collected database CIPPIS (Comparison Influence to Prognosis of CTP and MRP in AIS Patients, NCT03367286), and enrolled anterior circulation large artery occlusion patients with recanalization after mechanical thrombectomy who underwent (1) computed tomography (CT) perfusion on admission and immediately after recanalization to determine reperfusion region, and (2) CT and/or magnetic resonance imaging (MRI) immediately and 24 hours after recanalization to determine lesion areas. The expansion of lesion between recanalization and 24 hours within reperfusion region was potentially caused by reperfusion, thus termed as radiological observed reperfusion injury (RORI). Based on the imaging modality immediately after recanalization, RORI was further divided into RORI_CT and RORI_MRI. We first included a small cohort who had performed both CT and MRI immediately after recanalization to validate the consistency between RORI_CT and RORI_MRI (Study 1). Then the association with RORI_CT and poor outcome, defined as 3-month modified Rankin Scale score of 3 to 6, was explored in a larger cohort (Study 2).

RESULTS

Study 1 included 23 patients and good consistency was found between RORI_CT and RORI_MRI (intraclass correlation=0.97, P<0.001). Among 226 patients included in Study 2, a total of 106 (46.9%) were identified with RORI. The ratio of RORI to reperfusion region was 30.1 (16.2, 51.0)% and was independently associated with poor outcome (odds ratio=1.55 per 10% [95% CI' 1.30-1.84]; P<0.001).

CONCLUSIONS

Our findings suggested that RORI was relatively frequent in stroke patients with recanalization after mechanical thrombectomy and associated with poor outcome despite successful recanalization.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT03367286.

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset

Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions ( https://doi.org/10.5281/zenodo.7153326 ). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge ( https://www.isles-challenge.org/ ) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke.

In vivo fluorescence imaging: success in preclinical imaging paves the way for clinical applications

Advances in diagnostic imaging have provided unprecedented opportunities to detect diseases at early stages and with high reliability. Diagnostic imaging is also crucial to monitoring the progress or remission of disease and thus is often the central basis of therapeutic decision-making. Currently, several diagnostic imaging modalities (computed tomography, magnetic resonance imaging, and positron emission tomography, among others) are routinely used in clinics and present their own advantages and limitations. In vivo near-infrared (NIR) fluorescence imaging has recently emerged as an attractive imaging modality combining low cost, high sensitivity, and relative safety. As a preclinical tool, it can be used to investigate disease mechanisms and for testing novel diagnostics and therapeutics prior to their clinical use. However, the limited depth of tissue penetration is a major challenge to efficient clinical use. Therefore, the current clinical use of fluorescence imaging is limited to a few applications such as image-guided surgery on tumors and retinal angiography, using FDA-approved dyes. Progress in fluorophore development and NIR imaging technologies holds promise to extend their clinical application to oncology, cardiovascular diseases, plastic surgery, and brain imaging, among others. Nanotechnology is expected to revolutionize diagnostic in vivo fluorescence imaging through targeted delivery of NIR fluorescent probes using antibody conjugation. In this review, we discuss the latest advances in in vivo fluorescence imaging technologies, NIR fluorescent probes, and current and future clinical applications.

Investigated regional apparent diffusion coefficient values of the morphologically normal feline brain

OBJECTIVES

Diffusion-weighted imaging (DWI) MRI is increasingly available in veterinary medicine for investigation of the brain. However, apparent diffusion coefficient (ADC) values have only been reported in a small number of cats or in research settings. The aim of this study was to investigate the ADC values of different anatomical regions of the morphologically normal brain in a feline patient population. Additionally, we aimed to assess the possible influence on the ADC values of different patient-related factors, such as sex, body weight, age, imaging of the left and right side of the cerebral hemispheres and white vs grey matter regions.

METHODS

This retrospective study included cats undergoing an MRI (3T) examination with DWI sequences of the head at the Vetsuisse Faculty of the University Zurich between 2015 and 2021. Only cats with morphologically normal brains were included. On the ADC maps, 10 regions of interest (ROIs) were manually drawn on the following anatomical regions: caudate nucleus; internal capsule (two locations); piriform lobe; thalamus; hippocampus; cortex cerebri (two locations); cerebellar hemisphere; and one ROI in the centre of the cerebellar vermis. Except for the ROI at the cerebellar vermis, each ROI was drawn in the left and right hemisphere. The ADC values were calculated by the software and recorded.

RESULTS

A total of 129 cats were included in this study. The ADC varied in the different ROIs, with the highest mean ADC value in the hippocampus and the lowest in the cerebellar hemisphere. ADC was significantly lower in the white cerebral matter compared with the grey matter. ADC values were not influenced by age, with the exception of the hippocampus and the cingulate gyrus.

CONCLUSION AND RELEVANCE

ADC values of different anatomical regions of the morphologically normal feline brain in a patient population of 129 cats in a clinical setting are reported for the first time.

Multiple B-Value Model-Based Residual Network (MORN) for Accelerated High-Resolution Diffusion-Weighted Imaging

Single-Shot Echo Planar Imaging (SSEPI) based Diffusion Weighted Imaging (DWI) has shortcomings such as low resolution and severe distortions. In contrast, Multi-Shot EPI (MSEPI) provides optimal spatial resolution but increases scan time. This study proposed a Multiple b-value mOdel-based Residual Network (MORN) model to reconstruct multiple b-value high-resolution DWI from undersampled k-space data simultaneously. We incorporated Parallel Imaging (PI) into a residual U-net to reconstruct multiple b-value multi-coil data with the supervision of MUltiplexed Sensitivity-Encoding (MUSE) reconstructed Multi-Shot DWI (MSDWI). Moreover, asymmetric concatenations among different b-values and the combined loss to back propagate helped the feature transfer. After training and validation of the MORN in a dataset of 32 healthy cases, additional assessments were performed on 6 patients with different tumor types. The experimental results demonstrated that the MORN model outperformed conventional PI reconstruction (i.e. SENSE) and two state-of-the-art deep learning methods (SENSE-GAN and VSNet) in terms of PSNR (Peak Signal-to-Noise Ratio), SSIM (Structual SIMilarity) and apparent diffusion coefficient maps. In addition, using the pre-trained model under DWI, the MORN achieved consistent fractional anisotrophy and mean diffusivity reconstructed from multiple diffusion directions. Hence, the proposed method shows potential in clinical application according to the observations on tumor patients as well as images of multiple diffusion directions.

Diffusion-Weighted MRI in the Genitourinary System

Diffusion weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence's usage in female pelvis, prostate, bladder, penis, testis and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging-Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors has significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or in the bladder and testicular mpMRI.

Correlation Tensor MRI deciphers underlying kurtosis sources in stroke

Noninvasively detecting and characterizing modulations in cellular scale micro-architecture remains a desideratum for contemporary neuroimaging. Diffusion MRI (dMRI) has become the mainstay methodology for probing microstructure, and, in ischemia, its contrasts have revolutionized stroke management. Diffusion kurtosis imaging (DKI) has been shown to significantly enhance the sensitivity of stroke detection compared to its diffusion tensor imaging (DTI) counterparts. However, the interpretation of DKI remains ambiguous as its contrast may arise from competing kurtosis sources related to the anisotropy of tissue components, diffusivity variance across components, and microscopic kurtosis (e.g., arising from cross-sectional variance, structural disorder, and restriction). Resolving these sources may be fundamental for developing more specific imaging techniques for stroke management, prognosis, and understanding its pathophysiology. In this study, we apply Correlation Tensor MRI (CTI) - a double diffusion encoding (DDE) methodology recently introduced for deciphering kurtosis sources based on the unique information captured in DDE's diffusion correlation tensors - to investigate the underpinnings of kurtosis measurements in acute ischemic lesions. Simulations for the different kurtosis sources revealed specific signatures for cross-sectional variance (representing neurite beading), edema, and cell swelling. Ex vivo CTI experiments at 16.4 T were then performed in an experimental photothrombotic stroke model 3 h post-stroke (N = 10), and successfully separated anisotropic, isotropic, and microscopic non-Gaussian diffusion sources in the ischemic lesions. Each of these kurtosis sources provided unique contrasts in the stroked area. Particularly, microscopic kurtosis was shown to be a primary "driver" of total kurtosis upon ischemia; its large increases, coupled with decreases in anisotropic kurtosis, are consistent with the expected elevation in cross-sectional variance, likely linked to beading effects in small objects such as neurites. In vivo experiments at 9.4 T at the same time point (3 h post ischemia, N = 5) demonstrated the stability and relevance of the findings and showed that fixation is not a dominant confounder in our findings. In future studies, the different CTI contrasts may be useful to address current limitations of stroke imaging, e.g., penumbra characterization, distinguishing lesion progression form tissue recovery, and elucidating pathophysiological correlates.

MR Perfusion in the Evaluation of Mechanical Thrombectomy Candidacy

ABSTRACT

Stroke is a leading cause of disability and mortality, and the incidence of ischemic stroke is projected to continue to rise in coming decades. These projections emphasize the need for improved imaging techniques for accurate diagnosis allowing effective treatments for ischemic stroke. Ischemic stroke is commonly evaluated with computed tomography (CT) or magnetic resonance imaging (MRI). Noncontrast CT is typically used within 4.5 hours of symptom onset to identify candidates for thrombolysis. Beyond this time window, thrombolytic therapy may lead to poor outcomes if patients are not optimally selected using appropriate imaging. MRI provides an accurate method for the earliest identification of core infarct, and MR perfusion can identify salvageable hypoperfused penumbra. The prognostic value for a better outcome in these patients lies in the ability to distinguish between core infarct and salvageable brain at risk-the ischemic penumbra-which is a function of the degree of ischemia and time. Many centers underutilize MRI for acute evaluation of ischemic stroke. This review will illustrate how perfusion-diffusion mismatch calculated from diffusion-weighted MRI and MR perfusion is a reliable approach for patient selection for stroke therapy and can be performed in timeframes that are comparable to CT-based algorithms while providing potentially superior diagnostic information.

On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol

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B-tensor encoding enables estimation of spherical cellular structures in the brain.

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Spherical compartments may provide markers for apparent neural soma density.

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Model parameters can be estimated in a fast and robust way using deep learning.

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Practical acquisition times are achievable on widely available clinical scanners.

Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.

In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution

We present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy participant. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

Diffusion weighted imaging in acute ischemic stroke: A review of its interpretation pitfalls and advanced diffusion imaging application

Diffusion weighted imaging (DWI) is a widely used imaging technique to evaluate patients with stroke. It can detect brain ischemia within minutes of stroke onset. However, DWI has few potential pitfalls that should be recognized during interpretation. DWI lesion could be reversible in the early hours of stroke and the entire lesion may not represent ischemic core. False negative DWI could lead to diagnosis of DWI negative stroke or to a missed stroke diagnosis. Ischemic stroke mimics can occur on DWI with non-cerebrovascular neurological conditions. In this article, the history of DWI, its clinical applications, and potential pitfalls for use in acute ischemic stroke are reviewed. Advanced diffusion imaging techniques with reference to Diffusion Kurtosis Imaging and Diffusion Tensor Imaging that has been studied to evaluate ischemic core are discussed.

Apparent diffusion coefficient measured by diffusion MRI of moving and deforming domains

The modeling of the diffusion MRI signal from moving and deforming organs such as the heart is challenging due to significant motion and deformation of the imaged medium during the signal acquisition. Recently, a mathematical formulation of the Bloch-Torrey equation, describing the complex transverse magnetization due to diffusion-encoding magnetic field gradients, was developed to account for the motion and deformation. In that work, the motivation was to cancel the effect of the motion and deformation in the MRI image and the space scale of interest spans multiple voxels. In the present work, we adapt the mathematical equation to study the diffusion MRI signal at the much smaller scale of biological cells. We start with the Bloch-Torrey equation defined on a cell that is moving and deforming and linearize the equation around the magnitude of the diffusion-encoding gradient. The result is a second order signal model in which the linear term gives the imaginary part of the diffusion MRI signal and the quadratic term gives the apparent diffusion coefficient (ADC) attributable to the biological cell. We numerically validate this model for a variety of motions and deformations.

Fully Automatic Segmentation of Acute Ischemic Lesions on Diffusion-Weighted Imaging Using Convolutional Neural Networks: Comparison with Conventional Algorithms

Objective

To develop algorithms using convolutional neural networks (CNNs) for automatic segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) and compare them with conventional algorithms, including a thresholding-based segmentation.

Materials and Methods

Between September 2005 and August 2015, 429 patients presenting with acute cerebral ischemia (training:validation:test set = 246:89:94) were retrospectively enrolled in this study, which was performed under Institutional Review Board approval. Ground truth segmentations for acute ischemic lesions on DWI were manually drawn under the consensus of two expert radiologists. CNN algorithms were developed using two-dimensional U-Net with squeeze-and-excitation blocks (U-Net) and a DenseNet with squeeze-and-excitation blocks (DenseNet) with squeeze-and-excitation operations for automatic segmentation of acute ischemic lesions on DWI. The CNN algorithms were compared with conventional algorithms based on DWI and the apparent diffusion coefficient (ADC) signal intensity. The performances of the algorithms were assessed using the Dice index with 5-fold cross-validation. The Dice indices were analyzed according to infarct volumes (< 10 mL, ≥ 10 mL), number of infarcts (≤ 5, 6–10, ≥ 11), and b-value of 1000 (b1000) signal intensities (< 50, 50–100, > 100), time intervals to DWI, and DWI protocols.

Results

The CNN algorithms were significantly superior to conventional algorithms (p < 0.001). Dice indices for the CNN algorithms were 0.85 for U-Net and DenseNet and 0.86 for an ensemble of U-Net and DenseNet, while the indices were 0.58 for ADC-b1000 and b1000-ADC and 0.52 for the commercial ADC algorithm. The Dice indices for small and large lesions, respectively, were 0.81 and 0.88 with U-Net, 0.80 and 0.88 with DenseNet, and 0.82 and 0.89 with the ensemble of U-Net and DenseNet. The CNN algorithms showed significant differences in Dice indices according to infarct volumes (p < 0.001).

Conclusion

The CNN algorithm for automatic segmentation of acute ischemic lesions on DWI achieved Dice indices greater than or equal to 0.85 and showed superior performance to conventional algorithms.

Ventricular apparent diffusion coefficient measurements in patients with neoplastic leptomeningeal disease

Background

To test the hypothesis that intraventricular ADC values can be used to determine the presence of neoplastic leptomeningeal disease (LMD).

Materials and methods

ADC values were measured at multiple sites in the ventricular system in 32 patients with cytologically-proven LMD and 40 control subjects. Multiple linear regression analysis was used to determine the mean difference of ADCs between the LMD and control groups after adjusting for ventricle size and tumor type. Receiver operating characteristics (ROC) analysis was performed and optimal ADC value cut-off point for predicting the presence of LMD. ADC was compared to T1 enhancement and FLAIR signal hyperintensity for determining the presence of LMD.

Results

After adjusting for ventricular volume and tumor type, the mid body of lateral ventricles showed no significant difference in ventricular volume and a significant difference in ADC values between the control and LMD groups (p > 0.05). In the mid-body of the right lateral ventricle the AUC was 0.69 (95% CI 0.57–0.81) with an optimal ADC cut off point of 3.22 × 10^− 9 m²/s (sensitivity, specificity; 0.72, 0.68). In the mid-body of left lateral ventricle the AUC was 0.7 (95% CI 0.58–0.82) with an optimal cut-off point of 3.23 × 10^− 9 m²/s (0.81, 0.62). Using an average value of HU measurements in the lateral ventricles the AUC was 0.73 (95% CI 0.61–0.84) with an optimal cut off point was 3.11 × 10^− 9 m²/s (0.78, 0.65). Compared to the T1 post-contrast series, ADC was predictive of the presence of LMD in the mid-body of the left lateral ventricle (p = 0.036).

Conclusion

Complex interactions affect ADC measurements in patients with LMD. ADC values in the lateral ventricles may provide non-invasive clues to the presence of LMD.

Non-invasive treatment with near-infrared light: A novel mechanisms-based strategy that evokes sustained reduction in brain injury after stroke

Ischemic stroke is a debilitating disease that causes significant brain injury. While restoration of blood flow is critical to salvage the ischemic brain, reperfusion can exacerbate damage by inducing generation of reactive oxygen species (ROS). Recent studies by our group found that non-invasive mitochondrial modulation with near-infrared (NIR) light limits ROS generation following global brain ischemia. NIR interacts with cytochrome c oxidase (COX) to transiently reduce COX activity, attenuate mitochondrial membrane potential hyperpolarization, and thus reduce ROS production. We evaluated a specific combination of COX-inhibitory NIR (750 nm and 950 nm) in a rat stroke model with longitudinal analysis of brain injury using magnetic resonance imaging. Treatment with NIR for 2 h resulted in a 21% reduction in brain injury at 24 h of reperfusion measured by diffusion-weighted imaging (DWI) and a 25% reduction in infarct volume measured by T2-weighted imaging (T2WI) at 7 and 14 days of reperfusion, respectively. Additionally, extended treatment reduced brain injury in the acute phase of brain injury, and 7 and 14 days of reperfusion, demonstrating a >50% reduction in infarction. Our data suggest that mitochondrial modulation with NIR attenuates ischemia-reperfusion injury and evokes a sustained reduction in infarct volume following ischemic stroke.

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.

Oscillating-gradient diffusion magnetic resonance imaging detects acute subcellular structural changes in the mouse forebrain after neonatal hypoxia-ischemia

The recently developed oscillating-gradient diffusion MRI (OG-dMRI) technique extends our ability to examine brain structures at different spatial scales. In this study, we investigated the sensitivity of OG-dMRI in detecting cellular and subcellular structural changes in a mouse model of neonatal hypoxia ischemia (HI). Neonatal mice received unilateral HI injury or sham injury at postnatal day 10, followed by in vivo T₂-weighted and diffusion MRI of the brains at 3-6 h and 24 h after HI. Apparent diffusion coefficient (ADC) maps were acquired using conventional pulsed-gradient dMRI (PG-dMRI) and OG-dMRI with oscillating frequencies from 50 to 200 Hz. Pathology at cellular and subcellular levels was evaluated using neuronal, glial, and mitochondrial markers. We found significantly higher rates of ADC increase with oscillating frequencies (Δ_fADC) in the ipsilateral edema region, compared to the contralateral side, starting as early as 3 h after HI. Even in injured regions that showed no apparent change in PG-ADC or pseudo-normalized PG-ADC measurements, Δ_fADC remained significantly elevated. Histopathology showed swelling of sub-cellular structures in these regions with no apparent whole-cell level change. These results suggest that OG-dMRI is sensitive to subcellular structural changes in the brain after HI and is less susceptible to pseudo-normalization than PG-dMRI.

The heme and radical scavenger α1-microglobulin (A1M) confers early protection of the immature brain following preterm intraventricular hemorrhage

Background

Germinal matrix intraventricular hemorrhage (GM-IVH) is associated with cerebro-cerebellar damage in very preterm infants, leading to neurodevelopmental impairment. Penetration, from the intraventricular space, of extravasated red blood cells and extracellular hemoglobin (Hb), to the periventricular parenchyma and the cerebellum has been shown to be causal in the development of brain injury following GM-IVH. Furthermore, the damage has been described to be associated with the cytotoxic nature of extracellular Hb-metabolites. To date, there is no therapy available to prevent infants from developing either hydrocephalus or serious neurological disability. Mechanisms previously described to cause brain damage following GM-IVH, i.e., oxidative stress and Hb-metabolite toxicity, suggest that the free radical and heme scavenger α₁-microglobulin (A1M) may constitute a potential neuroprotective intervention.

Methods

Using a preterm rabbit pup model of IVH, where IVH was induced shortly after birth in pups delivered by cesarean section at E29 (3 days prior to term), we investigated the brain distribution of recombinant A1M (rA1M) following intracerebroventricular (i.c.v.) administration at 24 h post-IVH induction. Further, short-term functional protection of i.c.v.-administered human A1M (hA1M) following IVH in the preterm rabbit pup model was evaluated.

Results

Following i.c.v. administration, rA1M was distributed in periventricular white matter regions, throughout the fore- and midbrain and extending to the cerebellum. The regional distribution of rA1M was accompanied by a high co-existence of positive staining for extracellular Hb.

Administration of i.c.v.-injected hA1M was associated with decreased structural tissue and mitochondrial damage and with reduced mRNA expression for proinflammatory and inflammatory signaling-related genes induced by IVH in periventricular brain tissue.

Conclusions

The results of this study indicate that rA1M/hA1M is a potential candidate for neuroprotective treatment following preterm IVH.

Electronic supplementary material

The online version of this article (10.1186/s12974-019-1486-4) contains supplementary material, which is available to authorized users.

Development of anisotropic phantoms using wood and fiber materials for diffusion tensor imaging and diffusion kurtosis imaging

Objective

Several studies have demonstrated that anisotropic phantoms can be utilized for diffusion magnetic resonance imaging. The purpose of our study was to examine whether wood is suitable as an anisotropic phantom material from the viewpoints of affordability and availability. In the current study, wood was used for restricted diffusion, and fibers were used for hindered diffusion.

Materials and methods

Wood and fiber phantoms were made. Diffusion kurtosis images were acquired with three magnetic resonance scanners. Fractional anisotropy, radial diffusivity, axial diffusivity, radial kurtosis and axial kurtosis values were measured. The wood phantom was imaged, and its durability was confirmed. The phantoms were imaged in varying orientations within the magnetic field. The wood was observed using an optical microscope.

Results

Ten kinds of wood and the fiber had a diffusion metrics. The wood diffusion metrics suggested low variation over a period of 9 months. Changing the orientation of the phantoms within the magnetic field resulted in changes in diffusion metrics. Observation of wood vessels and fibers was conducted.

Discussion

Wood and fibers have anisotropy and are promising as phantom materials. The development of anisotropic phantoms that anyone can use is useful for diffusion magnetic resonance imaging research and clinical applications.

The quest for high spatial resolution diffusion-weighted imaging of the human brain in vivo

Diffusion-weighted imaging, a contrast unique to MRI, is used for assessment of tissue microstructure in vivo. However, this exquisite sensitivity to finer scales far above imaging resolution comes at the cost of vulnerability to errors caused by sources of motion other than diffusion motion. Addressing the issue of motion has traditionally limited diffusion-weighted imaging to a few acquisition techniques and, as a consequence, to poorer spatial resolution than other MRI applications. Advances in MRI imaging methodology have allowed diffusion-weighted MRI to push to ever higher spatial resolution. In this review we focus on the pulse sequences and associated techniques under development that have pushed the limits of image quality and spatial resolution in diffusion-weighted MRI.

Diffusion MRI simulation in thin-layer and thin-tube media using a discretization on manifolds

The Bloch-Torrey partial differential equation can be used to describe the evolution of the transverse magnetization of the imaged sample under the influence of diffusion-encoding magnetic field gradients inside the MRI scanner. The integral of the magnetization inside a voxel gives the simulated diffusion MRI signal. This paper proposes a finite element discretization on manifolds in order to efficiently simulate the diffusion MRI signal in domains that have a thin layer or a thin tube geometrical structure. The variable thickness of the three-dimensional domains is included in the weak formulation established on the manifolds. We conducted a numerical study of the proposed approach by simulating the diffusion MRI signals from the extracellular space (a thin layer medium) and from neurons (a thin tube medium), comparing the results with the reference signals obtained using a standard three-dimensional finite element discretization. We show good agreements between the simulated signals using our proposed method and the reference signals for a wide range of diffusion MRI parameters. The approximation becomes better as the diffusion time increases. The method helps to significantly reduce the required simulation time, computational memory, and difficulties associated with mesh generation, thus opening the possibilities to simulating complicated structures at low cost for a better understanding of diffusion MRI in the brain.

Silent brain infarcts on diffusion-weighted imaging after carotid revascularisation: A surrogate outcome measure for procedural stroke? A systematic review and meta-analysis

Aim

To investigate whether lesions on diffusion-weighted imaging (DWI+) after carotid artery stenting (CAS) or endarterectomy (CEA) might provide a surrogate outcome measure for procedural stroke.

Materials and Methods

Systematic MedLine® database search with selection of all studies published up to the end of 2016 in which DWI scans were obtained before and within seven days after CAS or CEA. The correlation between the underlying log odds of stroke and of DWI+ across all treatment groups (i.e. CAS or CEA groups) from included studies was estimated using a bivariate random effects logistic regression model. Relative risks of DWI+ and stroke in studies comparing CAS vs. CEA were estimated using fixed-effect Mantel-Haenszel models.

Results

We included data of 4871 CAS and 2099 CEA procedures (85 studies). Across all treatment groups (CAS and CEA), the log odds for DWI+ was significantly associated with the log odds for clinically manifest stroke (correlation coefficient 0.61 (95% CI 0.27 to 0.87), p = 0.0012). Across all carotid artery stenting groups, the correlation coefficient was 0.19 (p = 0.074). There were too few CEA groups to reliably estimate a correlation coefficient in this subset alone. In 19 studies comparing CAS vs. CEA, the relative risks (95% confidence intervals) of DWI+ and stroke were 3.83 (3.17-4.63, p < 0.00001) and 2.38 (1.44-3.94, p = 0.0007), respectively.

Discussion

This systematic meta-analysis demonstrates a correlation between the occurrence of silent brain infarcts on diffusion-weighted imaging and the risk of clinically manifest stroke in carotid revascularisation procedures.

Conclusion

Our findings strengthen the evidence base for the use of DWI as a surrogate outcome measure for procedural stroke in carotid revascularisation procedures. Further randomised studies comparing treatment effects on DWI lesions and clinical stroke are needed to fully establish surrogacy.

Longitudinal investigation of ischemic stroke using magnetic resonance imaging: Animal model

BACKGROUND

Arterial embolism is a major cause of ischemic stroke. Currently, digital subtraction angiography (DSA) is the gold standard in clinical arterial embolization examinations. However, it is invasive and risky.

OBJECTIVE

This study aims to longitudinally assess the progression of carotid artery embolism in middle cerebral artery occlusion animal model (MCAO) using magnetic resonance imaging (MRI) techniques.

METHODS

Turbo spin echo (TSE), time of flight magnetic resonance angiography (TOF-MRA) and diffusion weighted magnetic resonance imaging (DWI) were used to evaluate the image characteristics of cerebral tissues at 1, 2, 3, 7, 14, 21 and 28 days after MCAO microsurgery on Sprague-Dawley (SD) rats. Quantitative analysis was performed and compared in MCAO hemisphere and contralateral normal hemisphere. Furthermore, pathologic section using triphenyl tetrazolium chloride (TTC) stain was performed as well.

RESULTS

TOF-MRA showed carotid signal void in the embolism side, which is evidence of artery occlusion. The used MRI techniques showed that edema gradually dissipated within one week, but there was no significant change afterwards. The time-varying signal intensity of MRI techniques in MCAO hemisphere changed significantly, but there were no significant changes in contralateral normal hemisphere. Cerebral injury was also confirmed by analysis of pathology images.

CONCLUSIONS

The MCAO animal model was successfully established on SD rats using the microsurgery to assess arterial embolization of intracranial tissue injury.

In vivo microscopic diffusional kurtosis imaging with symmetrized double diffusion encoding EPI

PURPOSE

Diffusional kurtosis imaging (DKI) measures the deviation of the displacement probability from a normal distribution, complementing the data commonly acquired by diffusion MRI. It is important to elucidate the sources of kurtosis contrast, particularly in biological tissues where microscopic kurtosis (intrinsic kurtosis) and diffusional heterogeneity may co-exist.

METHODS

We have developed a technique for microscopic kurtosis MRI, dubbed microscopic diffusional kurtosis imaging (µDKI), using a symmetrized double diffusion encoding (s-DDE) EPI sequence. We compared this newly developed µDKI to conventional DKI methods in both a triple compartment phantom and in vivo.

RESULTS

Our results showed that whereas conventional DKI and µDKI provided similar measurements in a compartment of monosphere beads, kurtosis measured by µDKI was significantly less than that measured by conventional DKI in a compartment of mixed Gaussian pools. For in vivo brain imaging, µDKI showed small yet significantly lower kurtosis measurement in regions of the cortex, CSF, and internal capsule compared to the conventional DKI approach.

CONCLUSIONS

Our study showed that µDKI is less susceptible than conventional DKI to sub-voxel diffusional heterogeneity. Our study also provided important preliminary demonstration of our technique in vivo, warranting future studies to investigate its diagnostic use in examining neurological disorders.

Diffusion weighted magnetic resonance imaging for temperature measurements in catalyst supports with an axial gas flow

In situ thermometry of catalytic gas phase reactions allows to determine temperature profiles in catalyst beds. Diffusion weighted MRI is proposed as an alternative method for temperature measurements using capillaries filled with different liquids.

Diffusion kurtosis imaging of microstructural changes in brain tissue affected by acute ischemic stroke in different locations

The location of an acute ischemic stroke is associated with its prognosis. The widely used Gaussian model-based parameter, apparent diffusion coefficient (ADC), cannot reveal microstructural changes in different locations or the degree of infarction. This prospective observational study was reviewed and approved by the Institutional Review Board of Xiamen Second Hospital, China (approval No. 2014002). Diffusion kurtosis imaging (DKI) was used to detect 199 lesions in 156 patients with acute ischemic stroke (61 males and 95 females), mean age 63.15 ± 12.34 years. A total of 199 lesions were located in the periventricular white matter (n = 52), corpus callosum (n = 14), cerebellum (n = 29), basal ganglia and thalamus (n = 21), brainstem (n = 21) and gray-white matter junctions (n = 62). Percentage changes of apparent diffusion coefficient (ΔADC) and DKI-derived indices (fractional anisotropy [ΔFA], mean diffusivity [ΔMD], axial diffusivity [ΔD_a], radial diffusivity ΔD_r, mean kurtosis [ΔMK], axial kurtosis [ΔK_a], and radial kurtosis [ΔK_r]) of each lesion were computed relative to the normal contralateral region. The results showed that (1) there was no significant difference in ΔADC, ΔMD, ΔD_a or ΔD_r among almost all locations. (2) There was significant difference in ΔMK among almost all locations (except basal ganglia and thalamus vs. brain stem; basal ganglia and thalamus vs. gray-white matter junctions; and brainstem vs. gray-white matter junctions. (3) The degree of change in diffusional kurtosis in descending order was as follows: corpus callosum > periventricular white matter > brainstem > gray-white matter junctions > basal ganglia and thalamus > cerebellum. In conclusion, DKI could reveal the differences in microstructure changes among various locations affected by acute ischemic stroke, and performed better than diffusivity among all groups.

The derivation of homogenized diffusion kurtosis models for diffusion MRI

We use homogenization theory to establish a new macroscopic model for the complex transverse water proton magnetization in a voxel due to diffusion-encoding magnetic field gradient pulses in the case of biological tissue with impermeable membranes. In this model, new higher-order diffusion tensors emerge and offer more information about the structure of the biological tissues. We explicitly solve the macroscopic model to obtain an ordinary differential equation for the diffusion MRI signal that has similar structure as diffusional kurtosis imaging models. We finally present some validating numerical results on synthetic examples showing the accuracy of the model with respect to signals obtained by solving the Bloch-Torrey equation.

Reliability of fast magnetic resonance imaging for acute ischemic stroke patients using a 1.5-T scanner

OBJECTIVES

To determine whether fast scanned MRI using a 1.5-T scanner is a reliable method for the detection and characterization of acute ischemic stroke in comparison with conventional MRI.

METHODS

From May 2015 to June 2016, 862 patients (FLAIR, n = 482; GRE, n = 380; MRA, n = 190) were prospectively enrolled in the study, with informed consent and under institutional review board approval. The patients underwent both fast (EPI-FLAIR, ETL-FLAIR, TR-FLAIR, EPI-GRE, parallel-GRE, fast CE-MRA) and conventional MRI (FLAIR, GRE, time-of-flight MRA, fast CE-MRA). Two neuroradiologists independently assessed agreements in acute and chronic ischemic hyperintensity, hyperintense vessels (FLAIR), microbleeds, susceptibility vessel signs, hemorrhagic transformation (GRE), stenosis (MRA), and image quality (all MRI), between fast and conventional MRI. Agreements between fast and conventional MRI were evaluated by generalized estimating equations. Z-scores were used for comparisons of the percentage agreement among fast FLAIR sequences and fast GRE sequences and between conventional and fast MRA.

RESULTS

Agreements of more than 80% were achieved between fast and conventional MRI (ETL-FLAIR, 96%; TR-FLAIR, 97%; EPI-GRE, 96%; parallel-GRE, 98%; fast CE-MRA, 86%). ETL- and TR-FLAIR were significantly superior to EPI-FLAIR in the detection of acute ischemic hyperintensity and hyperintense vessels, while parallel-GRE was significantly superior to EPI-GRE in the detection of susceptibility vessel sign (p value < 0.05 for all). There were no significant differences in the other scores and image qualities (p value > 0.05).

CONCLUSIONS

Fast MRI at 1.5 T is a reliable method for the detection and characterization of acute ischemic stroke in comparison with conventional MRI.

KEY POINTS

• Fast MRI at 1.5 T may achieve a high intermethod reliability in the detection and characterization of acute ischemic stroke with a reduction in scan time in comparison with conventional MRI.

Experimental determination of pore shapes using phase retrieval from q-space NMR diffraction

This paper presents an approach to solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method that allows imaging the shape of arbitrary closed pores filled with an NMR-detectable medium for investigation of the microstructure of biological tissue and porous materials. Classical q-space imaging composed of two short diffusion-encoding gradient pulses yields, analogously to diffraction experiments, the modulus squared of the Fourier transform of the pore image which entails an inversion problem: An unambiguous reconstruction of the pore image requires both magnitude and phase. Here the phase information is recovered from the Fourier modulus by applying a phase retrieval algorithm. This allows omitting experimentally challenging phase measurements using specialized temporal gradient profiles. A combination of the hybrid input-output algorithm and the error reduction algorithm was used with dynamically adapting support (shrinkwrap extension). No a priori knowledge on the pore shape was fed to the algorithm except for a finite pore extent. The phase retrieval approach proved successful for simulated data with and without noise and was validated in phantom experiments with well-defined pores using hyperpolarized xenon gas.

Imaging the physiological evolution of the ischemic penumbra in acute ischemic stroke

We review the hemodynamic, metabolic and cellular parameters affected during early ischemia and their changes as a function of approximate cerebral blood flow ( CBF) thresholds. These parameters underlie the current practical definition of an ischemic penumbra, namely metabolically affected but still viable brain tissue. Such tissue is at risk of infarction under continuing conditions of reduced CBF, but can be rescued through timely intervention. This definition will be useful in clinical diagnosis only if imaging techniques exist that can rapidly, and with sufficient accuracy, visualize the existence of a mismatch between such a metabolically affected area and regions that have suffered cell depolarization. Unfortunately, clinical data show that defining the outer boundary of the penumbra based solely on perfusion-related thresholds may not be sufficiently accurate. Also, thresholds for CBF and cerebral blood volume ( CBV) differ for white and gray matter and evolve with time for both inner and outer penumbral boundaries. As such, practical penumbral imaging would involve parameters in which the physiology is immediately displayed in a manner independent of baseline CBF or CBF threshold, namely pH, oxygen extraction fraction ( OEF), diffusion constant and mean transit time ( MTT). Suitable imaging technologies will need to meet this requirement in a 10-20 min exam.

Impaired white matter connectivity between regions containing mirror neurons, and relationship to negative symptoms and social cognition, in patients with first-episode schizophrenia

In schizophrenia, abnormalities in structural connectivity between brain regions known to contain mirror neurons and their relationship to negative symptoms related to a domain of social cognition are not well understood. Diffusion tensor imaging (DTI) scans were acquired in 16 patients with first episode schizophrenia and 16 matched healthy controls. FA and Trace of the tracts interconnecting regions known to be rich in mirror neurons, i.e., anterior cingulate cortex (ACC), inferior parietal lobe (IPL) and premotor cortex (PMC) were evaluated. A significant group effect for Trace was observed in IPL-PMC white matter fiber tract (F (1, 28) = 7.13, p = .012), as well as in the PMC-ACC white matter fiber tract (F (1, 28) = 4.64, p = .040). There were no group differences in FA. In addition, patients with schizophrenia showed a significant positive correlation between the Trace of the left IPL-PMC white matter fiber tract, and the Ability to Feel Intimacy and Closeness score (rho = .57, p = 0.034), and a negative correlation between the Trace of the left PMC-ACC and the Relationships with Friends and Peers score (rho = remove -.54, p = 0.049). We have demonstrated disrupted white mater microstructure within the white matter tracts subserving brain regions containing mirror neurons. We further showed that such structural disruptions might impact negative symptoms and, more specifically, contribute to the inability to feel intimacy (a measure conceptually related to theory of mind) in first episode schizophrenia. Further studies are needed to understand the potential of our results for diagnosis, prognosis and therapeutic interventions.