State-of-the-art MRI techniques in neuroradiology: principles, pitfalls, and clinical applications

Evaluation of the contribution of individual arteries to the cerebral blood supply in patients with Moyamoya angiopathy: comparison of vessel-encoded arterial spin labeling and digital subtraction angiography

PURPOSE

Vessel-encoded arterial spin labeling (VE-ASL) is able to provide noninvasive information about the contribution of individual arteries to the cerebral perfusion. The aim of this study was to compare VE-ASL to the diagnostic standard digital subtraction angiography (DSA) with respect to its ability to visualize vascular territories.

METHODS

In total, 20 VE-ASL and DSA data sets of 17 patients with Moyamoya angiopathy with and without revascularization surgery were retrospectively analyzed. Two neuroradiologists independently assessed the agreement between VE-ASL and DSA using a 4-point Likert scale (no- very high agreement). Additionally, grading of the vascular supply of subterritories (A1-A2, M1-M6) on the VE-ASL images and angiograms was performed. The intermodal agreement was calculated for all subterritories in total and for the subdivision into without and after revascularization (direct or indirect bypass).

RESULTS

There was a very high agreement between the VE-ASL and the DSA data sets (median = 1, modus = 1) with a substantial inter-rater agreement (kw = 0.762 (95% CI 0.561-0.963)). The inter-modality agreement between VE-ASL and DSA in vascular subterritories was almost perfect for all subterritories (k = 0.899 (0.865-0.945)), in the subgroup of direct revascularized subterritories (k = 0.827 (0.738-0.915)), in the subgroup of indirect revascularized subterritories (k = 0.843 (0.683-1.003)), and in the subgroup of never revascularized subterritories (k = 0.958 (0.899-1.017)).

CONCLUSION

Vessel-encoded ASL seems to be a promising non-invasive method to depict the contributions of individual arteries to the cerebral perfusion before and after revascularization surgery.

MRI motion artifact reduction using a conditional diffusion probabilistic model (MAR-CDPM)

BACKGROUND

High-resolution magnetic resonance imaging (MRI) with excellent soft-tissue contrast is a valuable tool utilized for diagnosis and prognosis. However, MRI sequences with long acquisition time are susceptible to motion artifacts, which can adversely affect the accuracy of post-processing algorithms.

PURPOSE

This study proposes a novel retrospective motion correction method named "motion artifact reduction using conditional diffusion probabilistic model" (MAR-CDPM). The MAR-CDPM aimed to remove motion artifacts from multicenter three-dimensional contrast-enhanced T1 magnetization-prepared rapid acquisition gradient echo (3D ceT1 MPRAGE) brain dataset with different brain tumor types.

MATERIALS AND METHODS

This study employed two publicly accessible MRI datasets: one containing 3D ceT1 MPRAGE and 2D T2-fluid attenuated inversion recovery (FLAIR) images from 230 patients with diverse brain tumors, and the other comprising 3D T1-weighted (T1W) MRI images of 148 healthy volunteers, which included real motion artifacts. The former was used to train and evaluate the model using the in silico data, and the latter was used to evaluate the model performance to remove real motion artifacts. A motion simulation was performed in k-space domain to generate an in silico dataset with minor, moderate, and heavy distortion levels. The diffusion process of the MAR-CDPM was then implemented in k-space to convert structure data into Gaussian noise by gradually increasing motion artifact levels. A conditional network with a Unet backbone was trained to reverse the diffusion process to convert the distorted images to structured data. The MAR-CDPM was trained in two scenarios: one conditioning on the time step t $t$ of the diffusion process, and the other conditioning on both t $t$ and T2-FLAIR images. The MAR-CDPM was quantitatively and qualitatively compared with supervised Unet, Unet conditioned on T2-FLAIR, CycleGAN, Pix2pix, and Pix2pix conditioned on T2-FLAIR models. To quantify the spatial distortions and the level of remaining motion artifacts after applying the models, quantitative metrics were reported including normalized mean squared error (NMSE), structural similarity index (SSIM), multiscale structural similarity index (MS-SSIM), peak signal-to-noise ratio (PSNR), visual information fidelity (VIF), and multiscale gradient magnitude similarity deviation (MS-GMSD). Tukey's Honestly Significant Difference multiple comparison test was employed to quantify the difference between the models where p-value < 0.05 $ < 0.05$ was considered statistically significant.

RESULTS

Qualitatively, MAR-CDPM outperformed these methods in preserving soft-tissue contrast and different brain regions. It also successfully preserved tumor boundaries for heavy motion artifacts, like the supervised method. Our MAR-CDPM recovered motion-free in silico images with the highest PSNR and VIF for all distortion levels where the differences were statistically significant (p-values< 0.05 $< 0.05$ ). In addition, our method conditioned on t and T2-FLAIR outperformed (p-values< 0.05 $< 0.05$ ) other methods to remove motion artifacts from the in silico dataset in terms of NMSE, MS-SSIM, SSIM, and MS-GMSD. Moreover, our method conditioned on only t outperformed generative models (p-values< 0.05 $< 0.05$ ) and had comparable performances compared with the supervised model (p-values> 0.05 $> 0.05$ ) to remove real motion artifacts.

CONCLUSIONS

The MAR-CDPM could successfully remove motion artifacts from 3D ceT1 MPRAGE. It is particularly beneficial for elderly who may experience involuntary movements during high-resolution MRI imaging with long acquisition times.

Spinal cord perfusion is associated with microstructural damage in cervical spondylotic myelopathy patients who underwent cervical laminoplasty

OBJECTIVES

To investigate the association between spinal cord perfusion and microstructural damage in CSM patients who underwent cervical laminoplasty using MR dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) techniques.

METHODS

A follow-up cohort study was conducted with 53 consecutively recruited CSM patients who had undergone cervical laminoplasty 12-14 months after the surgery from April 2016 to December 2016. Twenty-one aged-matched healthy volunteers were recruited as controls. For each patient, decompressed spinal cord levels were imaged on a 3.0-T MRI scanner by diffusion and DSC sequences to quantify the degrees of microstructural damage and perfusion conditions, respectively. The diffusion data were analyzed by DTI and NODDI models to produce diffusion metrics. Classic indicator dilution model was used to quantify the DSC metrics. Mann-Whitney U test was performed for comparison of diffusion metrics between patients and healthy controls. Pearson correlation was used to explore the associations between the metrics of spinal cord perfusion and microstructural damage.

RESULTS

DTI metrics, neurite density, and isotropic volume fraction had significant differences between postoperative patients and healthy controls. Pearson correlation test showed that SCBV was significantly positively correlated with RD, MD, and ODI, and negatively correlated with FA and NDI. SCBF was found to be significantly positively correlated with RD and MD, and negatively correlated with FA.

CONCLUSIONS

Increased spinal cord perfusion quantified by DSC is associated with microstructural damage assessed by diffusion MRI in CSM patients who underwent cervical laminoplasty.

CLINICAL RELEVANCE STATEMENT

This study found that the spinal cord perfusion is associated with microstructural damage in postoperative cervical spondylotic myelopathy patients, indicating that high perfusion may play a role in the pathophysiological process of cervical spondylotic myelopathy and deserves more attention.

KEY POINTS

• Spinal cord microstructural damage can be persistent despite the compression had been relieved 12-14 months after the cervical laminoplasty in cervical spondylotic myelopathy (CSM) patients. • Spinal cord perfusion is associated with microstructural damage in CSM patients after the cervical laminoplasty. • Inflammation in the decompressed spinal cord may be a cause of increased perfusion and is associated with microstructural damage during the recovery period of CSM.

Unveiling the power of imaging techniques: comparing high-resolution ultrasound and functional MR neurography in peripheral nervous system pathology: a short communication

MRI and ultrasonography are used for diagnosing and helping manage peripheral nervous system pathologies. Multiple studies have compared the diagnostic accuracy of these two modalities, but the results can vary depending on the specific conditions being evaluated. In general, high-resolution ultrasound is considered a reliable and accurate tool for evaluating peripheral nerves, with high sensitivity and specificity. High-resolution ultrasound and functional MR neurography are both noninvasive imaging techniques used to evaluate nerve structures in the body. However, they differ in several technical aspects like imaging modality, spatial resolution, field of view, image quality, and accessibility. Establishing consensus on image acquisition techniques, and reporting formats to facilitate effective communication and comparison of results will further enhance the outcomes. The use of advanced ultrasound techniques, such as contrast-enhanced ultrasound, elastography, and ultrasound biomicroscopy, should be promoted for better visualization and characterization of nervous tissues, like transcranial Doppler for cerebrovascular evaluation.

Quantitative Cerebral Blood Volume Image Synthesis from Standard MRI Using Image-to-Image Translation for Brain Tumors

Background Cerebral blood volume (CBV) maps derived from dynamic susceptibility contrast-enhanced (DSC) MRI are useful but not commonly available in clinical scenarios. Purpose To test image-to-image translation techniques for generating CBV maps from standard MRI sequences of brain tumors using the bookend technique DSC MRI as ground-truth references. Materials and Methods A total of 756 MRI examinations, including quantitative CBV maps produced from bookend DSC MRI, were included in this retrospective study. Two algorithms, the feature-consistency generative adversarial network (GAN) and three-dimensional encoder-decoder network with only mean absolute error loss, were trained to synthesize CBV maps. The performance of the two algorithms was evaluated quantitatively using the structural similarity index (SSIM) and qualitatively by two neuroradiologists using a four-point Likert scale. The clinical value of combining synthetic CBV maps and standard MRI scans of brain tumors was assessed in several clinical scenarios (tumor grading, prognosis prediction, differential diagnosis) using multicenter data sets (four external and one internal). Differences in diagnostic and predictive accuracy were tested using the z test. Results The three-dimensional encoder-decoder network with T1-weighted images, contrast-enhanced T1-weighted images, and apparent diffusion coefficient maps as the input achieved the highest synthetic performance (SSIM, 86.29% ± 4.30). The mean qualitative score of the synthesized CBV maps by neuroradiologists was 2.63. Combining synthetic CBV with standard MRI improved the accuracy of grading gliomas (standard MRI scans area under the receiver operating characteristic curve [AUC], 0.707; standard MRI scans with CBV maps AUC, 0.857; z = 15.17; P < .001), prediction of prognosis in gliomas (standard MRI scans AUC, 0.654; standard MRI scans with CBV maps AUC, 0.793; z = 9.62; P < .001), and differential diagnosis between tumor recurrence and treatment response in gliomas (standard MRI scans AUC, 0.778; standard MRI scans with CBV maps AUC, 0.853; z = 4.86; P < .001) and brain metastases (standard MRI scans AUC, 0.749; standard MRI scans with CBV maps AUC, 0.857; z = 6.13; P < .001). Conclusion GAN image-to-image translation techniques produced accurate synthetic CBV maps from standard MRI scans, which could be used for improving the clinical evaluation of brain tumors. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Branstetter in this issue.

Direct jet coaxial electrospinning of axon-mimicking fibers for diffusion tensor imaging

Hollow polymer microfibers with variable microstructural and hydrophilic properties were proposed as building elements to create axon-mimicking phantoms for validation of diffusion tensor imaging (DTI). The axon-mimicking microfibers were fabricated in a mm-thick 3D anisotropic fiber strip, by direct jet coaxial electrospinning of PCL/polysiloxane-based surfactant (PSi) mixture as shell and polyethylene oxide (PEO) as core. Hydrophilic PCL-PSi fiber strips were first obtained by carefully selecting appropriate solvents for the core and appropriate fiber collector rotating and transverse speeds. The porous cross-section and anisotropic orientation of axon-mimicking fibers were then quantitatively evaluated using two ImageJ plugins-nearest distance (ND) and directionality based on their scanning electron microscopy (SEM) images. Third, axon-mimicking phantom was constructed from PCL-PSi fiber strips with variable porous-section and fiber orientation and tested on a 3T clinical MR scanner. The relationship between DTI measurements (mean diffusivity [MD] and fractional anisotropy [FA]) of phantom samples and their pore size and fiber orientation was investigated. Two key microstructural parameters of axon-mimicking phantoms including normalized pore distance and dispersion of fiber orientation could well interpret the variations in DTI measurements. Two PCL-PSi phantom samples made from different regions of the same fiber strips were found to have similar MD and FA values, indicating that the direct jet coaxial electrospun fiber strips had consistent microstructure. More importantly, the MD and FA values of the developed axon-mimicking phantoms were mostly in the biologically relevant range.

Correlations between DKI and DWI with Ki-67 in gastric adenocarcinoma

BACKGROUND

Diffusion kurtosis imaging (DKI) has been applied for gastric adenocarcinoma. Correlations between its parameters and Ki-67 are unclear.

PURPOSE

To investigate the correlation between DKI and diffusion-weighted imaging (DWI) parameters with the Ki-67 index in gastric adenocarcinoma.

MATERIAL AND METHODS

A total of 54 patients with gastric adenocarcinoma were enrolled in the study and underwent DWI and DKI at 3.0-T MRI before surgery. Based on the settings of the regions of interest, the DWI and DKI parameters (including apparent diffusion coefficient [ADC], diffusion kurtosis [K], and diffusion coefficient [DK]) of each patient's gastric adenocarcinoma were measured and calculated. The participants were divided into two groups (low Ki-67 group and high Ki-67 groups). The intraclass correlation coefficient (ICC) and independent-sample t-test were used to compare differences in each parameter between two groups. Spearman's correlation coefficient was calculated to determine the correlation between Ki-67 and the parameters. Each parameter was compared using the area under the receiver operating characteristic curve. All parameters were included in the multivariate logistic regression analysis to explore the relationship between each parameter and high Ki-67 index.

RESULTS

ADC and DK were negatively relevant with Ki-67 and K was positively relevant with Ki-67 in gastric adenocarcinoma. ADC, DK, and K had diagnostic efficiency in differentiating the low Ki-67 group from the high Ki-67 group. A higher K value independently predicted a high Ki-67 status.

CONCLUSION

DWI and DKI reflected the proliferative characteristics of gastric adenocarcinoma. K was the strongest independent factor for predicting high Ki-67 status.

More Space, Less Noise-New-generation Low-Field Magnetic Resonance Imaging Systems Can Improve Patient Comfort: A Prospective 0.55T-1.5T-Scanner Comparison

OBJECTIVES

The objectives of this study were to assess patient comfort when imaged on a newly introduced 0.55T low-field magnetic resonance (MR) scanner system with a wider bore opening compared to a conventional 1.5T MR scanner system.

MATERIALS AND METHODS

In this prospective study, fifty patients (mean age: 66.2 ± 17.0 years, 22 females, 28 males) underwent subsequent magnetic resonance imaging (MRI) examinations with matched imaging protocols at 0.55T (MAGNETOM FreeMax, Siemens Healthineers; Erlangen, Germany) and 1.5T (MAGNETOM Avanto Fit, Siemens Healthineers; Erlangen, Germany) on the same day. MRI performed between 05/2021 and 07/2021 was included for analysis. The 0.55T MRI system had a bore opening of 80 cm, while the bore diameter of the 1.5T scanner system was 60 cm. Four patient groups were defined by imaged body regions: (1) cranial or cervical spine MRI using a head/neck coil (n = 27), (2) lumbar or thoracic spine MRI using only the in-table spine coils (n = 10), (3) hip MRI using a large flex coil (n = 8) and (4) upper- or lower-extremity MRI using small flex coils (n = 5). Following the MRI examinations, patients evaluated (1) sense of space, (2) noise level, (3) comfort, (4) coil comfort and (5) overall examination impression on a 5-point Likert-scale (range: 1= "much worse" to 5 = "much better") using a questionnaire. Maximum noise levels of all performed imaging studies were measured in decibels (dB) by a sound level meter placed in the bore center.

RESULTS

Sense of space was perceived to be "better" or "much better" by 84% of patients for imaging examinations performed on the 0.55T MRI scanner system (mean score: 4.34 ± 0.75). Additionally, 84% of patients rated noise levels as "better" or "much better" when imaged on the low-field scanner system (mean score: 3.90 ± 0.61). Overall sensation during the imaging examination at 0.55T was rated as "better" or "much better" by 78% of patients (mean score: 3.96 ± 0.70). Quantitative assessment showed significantly reduced maximum noise levels for all 0.55T MRI studies, regardless of body region compared to 1.5T, i.e., brain MRI (83.8 ± 3.6 dB vs. 89.3 ± 5.4 dB; p = 0.04), spine MRI (83.7 ± 3.7 dB vs. 89.4 ± 2.6 dB; p = 0.004) and hip MRI (86.3 ± 5.0 dB vs. 89.1 ± 1.4 dB; p = 0.04).

CONCLUSIONS

Patients perceived 0.55T new-generation low-field MRI to be more comfortable than conventional 1.5T MRI, given its larger bore opening and reduced noise levels during image acquisition. Therefore, new concepts regarding bore design and noise level reduction of MR scanner systems may help to reduce patient anxiety and improve well-being when undergoing MR imaging.

Classification of Brain Tumor from Magnetic Resonance Imaging Using Vision Transformers Ensembling

The automated classification of brain tumors plays an important role in supporting radiologists in decision making. Recently, vision transformer (ViT)-based deep neural network architectures have gained attention in the computer vision research domain owing to the tremendous success of transformer models in natural language processing. Hence, in this study, the ability of an ensemble of standard ViT models for the diagnosis of brain tumors from T1-weighted (T1w) magnetic resonance imaging (MRI) is investigated. Pretrained and finetuned ViT models (B/16, B/32, L/16, and L/32) on ImageNet were adopted for the classification task. A brain tumor dataset from figshare, consisting of 3064 T1w contrast-enhanced (CE) MRI slices with meningiomas, gliomas, and pituitary tumors, was used for the cross-validation and testing of the ensemble ViT model's ability to perform a three-class classification task. The best individual model was L/32, with an overall test accuracy of 98.2% at 384 × 384 resolution. The ensemble of all four ViT models demonstrated an overall testing accuracy of 98.7% at the same resolution, outperforming individual model's ability at both resolutions and their ensembling at 224 × 224 resolution. In conclusion, an ensemble of ViT models could be deployed for the computer-aided diagnosis of brain tumors based on T1w CE MRI, leading to radiologist relief.

Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions

BACKGROUND

 Recently introduced MRI techniques facilitate accelerated examinations or increased resolution with the same duration. Further techniques offer homogeneous image quality in regions with anatomical transitions. The question arises whether and how these techniques can be adopted for routine diagnostic imaging.

METHODS

 Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered.

RESULTS AND CONCLUSIONS

 Compressed sensing and simultaneous multi-slice imaging are novel acceleration techniques with different yet complimentary applications. They do not suffer from classical signal-to-noise-ratio penalties. Combining 3 D and acceleration techniques facilitates new broader examination protocols, particularly for clinical brain imaging. In further regions of the nervous systems mainly specific applications appear to benefit from recent technological improvements.

KEY POINTS

  · New acceleration techniques allow for faster or higher resolution examinations.. · New brain imaging approaches have evolved, including more universal examination protocols.. · Other regions of the nervous system are dominated by targeted applications of recently introduced MRI techniques..

CITATION FORMAT

· Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1800-8789.

Practical Aspects of novel MRI Techniques in Neuroradiology: Part 1-3D Acquisitions, Dixon Techniques and Artefact Reduction

BACKGROUND

 Recently introduced MRI techniques offer improved image quality and facilitate examinations of patients even when artefacts are expected. They pave the way for novel diagnostic imaging strategies in neuroradiology. These methods include improved 3D imaging, movement and metal artefact reduction techniques as well as Dixon techniques.

METHODS

 Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered.

RESULTS AND CONCLUSIONS

 3D FLAIR is an example of a versatile 3D Turbo Spin Echo sequence with broad applicability in routine brain protocols. It facilitates detection of smaller lesions and more precise measurements for follow-up imaging. It also offers high sensitivity for extracerebral lesions. 3D techniques are increasingly adopted for imaging arterial vessel walls, cerebrospinal fluid spaces and peripheral nerves. Improved hybrid-radial acquisitions are available for movement artefact reduction in a broad application spectrum. Novel susceptibility artefact reduction techniques for targeted application supplement previously established metal artefact reduction sequences. Most of these techniques can be further adapted to achieve the desired diagnostic performances. Dixon techniques allow for homogeneous fat suppression in transition areas and calculation of different image contrasts based on a single acquisition.

KEY POINTS

  · 3D FLAIR can replace 2 D FLAIR for most brain imaging applications and can be a cornerstone of more precise and more widely applicable protocols.. · Further 3D TSE sequences are increasingly replacing 2D TSE sequences for specific applications.. · Improvement of artefact reduction techniques increase the potential for effective diagnostic MRI exams despite movement or near metal implants.. · Dixon techniques facilitate homogeneous fat suppression and simultaneous acquisition of multiple contrasts..

CITATION FORMAT

· Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 1-3D Acquisitions, Dixon Techniques and Artefact Reduction. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1800-8692.

[Economic aspects of low-field magnetic resonance imaging : Acquisition, installation, and maintenance costs of 0.55 T systems]

BACKGROUND

Low-field magnetic resonance imaging (MRI) scanners offer an opportunity for cost reduction in the healthcare system. This is due to lower manufacturing costs and reduced construction requirements for installation and operation.

OBJECTIVES

To discuss potential cost reductions in acquisition, installation, and maintenance by using new low-field MRI systems.

METHODS

We provide an overview of key cost drivers and an evaluation of the potential savings of a recent generation 0.55T low-field MRI compared to conventional 1.5T and 3T MRI systems in routine clinical practice.

RESULTS

In terms of purchase price, the savings potential of a 0.55T MRI compared to a 1.5T MRI system is about 40-50%. The 25% lower weight of the system reduces the transportation costs incurred, and the smaller size of the unit allows for installation by a remotely controlled mobile robotic system without opening the exterior façade, if the operating site is at ground level. Together with the lack of need to install a quench pipe, this reduces the total cost of installation by up to 70%. The maintenance cost of a 0.55T MRI is approximately 45% less than that of a 1.5T unit with a comparable service contract. Further cost reductions result from the smaller room size and potentially lower energy consumption for examinations and cooling.

CONCLUSION

The use of lower field strength MRI systems offers enormous economic and environmental potential for both hospitals and practice operators, as well as for the healthcare system as a whole.

Radiomics and radiogenomics in gliomas: a contemporary update

The natural history and treatment landscape of primary brain tumours are complicated by the varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low-grade lesions), as well as the dilemmas with identification of radiation necrosis, tumour progression, and pseudoprogression on MRI. Radiomics and radiogenomics promise to offer precise diagnosis, predict prognosis, and assess tumour response to modern chemotherapy/immunotherapy and radiation therapy. This is achieved by a triumvirate of morphological, textural, and functional signatures, derived from a high-throughput extraction of quantitative voxel-level MR image metrics. However, the lack of standardisation of acquisition parameters and inconsistent methodology between working groups have made validations unreliable, hence multi-centre studies involving heterogenous study populations are warranted. We elucidate novel radiomic and radiogenomic workflow concepts and state-of-the-art descriptors in sub-visual MR image processing, with relevant literature on applications of such machine learning techniques in glioma management.

Research progress on mechanism and imaging of temporal lobe injury induced by radiotherapy for head and neck cancer

Radiotherapy (RT) is an effective treatment for head and neck cancer (HNC). Radiation-induced temporal lobe injury (TLI) is a serious complication of RT. Late symptoms of radiation-induced TLI are irreversible and manifest as memory loss, cognitive impairment, and even temporal lobe necrosis (TLN). It is currently believed that the mechanism of radiation-induced TLI involves microvascular injury, neuron and neural stem cell injury, glial cell damage, inflammation, and the production of free radicals. Significant RT-related structural changes and dose-dependent changes in gray matter (GM) and white matter (WM) volume and morphology were observed through computed tomography (CT) and magnetic resonance imaging (MRI) which were common imaging assessment tools. Diffusion tensor imaging (DTI), dispersion kurtosis imaging (DKI), susceptibility-weighted imaging (SWI), resting-state functional magnetic resonance (rs-fMRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET) can be used for early diagnosis and prognosis evaluation according to functional, molecular, and cellular processes of TLI. Early diagnosis of TLI is helpful to reduce the incidence of TLN and its related complications. This review summarizes the clinical features, mechanisms, and imaging of radiation-induced TLI in HNC patients. KEY POINTS: • Radiation-induced temporal lobe injury (TLI) is a clinical complication and its symptoms mainly include memory impairment, headache, and cognitive impairment. • The mechanisms of TLI include microvascular injury, cell injury, and inflammatory and free radical injury. Significant RT-related structural changes and dose-dependent changes in TL volume and morphology were observed through CT and MRI. • SWI, MRS, DTI, and DKI and other imaging examinations can detect anatomical and functional, molecular, and cellular changes of TLI.

The Effect of Heterogenous Subregions in Glioblastomas on Survival Stratification: A Radiomics Analysis Using the Multimodality MRI

Intratumor heterogeneity is partly responsible for the poor prognosis of glioblastoma (GBM) patients. In this study, we aimed to assess the effect of different heterogeneous subregions of GBM on overall survival (OS) stratification. A total of 105 GBM patients were retrospectively enrolled and divided into long-term and short-term OS groups. Four MRI sequences, including contrast-enhanced T1-weighted imaging (T1C), T1, T2, and FLAIR, were collected for each patient. Then, 4 heterogeneous subregions, i.e. the region of entire abnormality (rEA), the regions of contrast-enhanced tumor (rCET), necrosis (rNec) and edema/non-contrast-enhanced tumor (rE/nCET), were manually drawn from the 4 MRI sequences. For each subregion, 50 radiomics features were extracted. The stratification performance of 4 heterogeneous subregions, as well as the performances of 4 MRI sequences, was evaluated both alone and in combination. Our results showed that rEA was superior in stratifying long-and short-term OS. For the 4 MRI sequences used in this study, the FLAIR sequence demonstrated the best performance of survival stratification based on the manual delineation of heterogeneous subregions. Our results suggest that heterogeneous subregions of GBMs contain different prognostic information, which should be considered when investigating survival stratification in patients with GBM.

Anatomical Variations, Mimics, and Pitfalls in Imaging of Patients with Epilepsy

Epilepsy is among one of the most common neurologic disorders. The role of magnetic resonance imaging (MRI) in the diagnosis and management of patients with epilepsy is well established, and most patients with epilepsy are likely to undergo at least one or more MRI examinations in the course of their disease. Recent advances in high-field MRI have enabled high resolution in vivo visualization of small and intricate anatomic structures that are of great importance in the assessment of seizure disorders. Familiarity with normal anatomic variations is essential in the accurate diagnosis and image interpretation, as these variations may be mistaken for epileptogenic foci, leading to unnecessary follow-up imaging, or worse, unnecessary treatment. After a brief overview of normal imaging anatomy of the mesial temporal lobe, this article will review a few important common and uncommon anatomic variations, mimics, and pitfalls that may be encountered in the imaging evaluation of patients with epilepsy.

Noise dependency in vascular parameters from combined gradient-echo and spin-echo DSC MRI

Dynamic susceptibility contrast (DSC) imaging is a widely used technique for assessment of cerebral blood volume (CBV). With combined gradient-echo and spin-echo DSC techniques, measures of the underlying vessel size and vessel architecture can be obtained from the vessel size index (VSI) and vortex area, respectively. However, how noise, and specifically the contrast-to-noise ratio (CNR), affect the estimations of these parameters has largely been overlooked. In order to address this issue, we have performed simulations to generate DSC signals with varying levels of CNR, defined by the peak of relaxation rate curve divided by the standard deviation of the baseline. Moreover, DSC data from 59 brain cancer patients were acquired at two different 3 T-scanners (N = 29 and N = 30, respectively), where CNR and relative parameter maps were obtained. Our simulations showed that the measured parameters were affected by CNR in different ways, where low CNR led to overestimations of CBV and underestimations of VSI and vortex area. In addition, a higher noise-sensitivity was found in vortex area than in CBV and VSI. Results from clinical data were consistent with simulations, and indicated that CNR < 4 gives highly unreliable measurements. Moreover, we have shown that the distribution of values in the tumour regions could change considerably when voxels with CNR below a given cut off are excluded when generating the relative parameter maps. The widespread use of CBV and attractive potential of VSI and vortex area, makes the noise-sensitivity of these parameters found in our study relevant for further use and development of the DSC imaging technique. Our results suggest that the CNR has considerable impact on the measured parameters, with the potential to affect the clinical interpretation of DSC-MRI, and should therefore be taken into account in the clinical decision-making process.

Double Dissociation of Auditory Attention Span and Visual Attention in Long-Term Survivors of Childhood Cerebellar Tumor: A Deterministic Tractography Study of the Cerebellar-Frontal and the Superior Longitudinal Fasciculus Pathways

OBJECTIVE

Right cerebellar-left frontal (RC-LF) white matter integrity (WMI) has been associated with working memory. However, prior studies have employed measures of working memory that include processing speed and attention. We examined the relationships between the RC-LF WMI and processing speed, attention, and working memory to clarify the relationship of RC-LF WMI with a specific cognitive function. Right superior longitudinal fasciculus II (SLF II) WMI and visual attention were included as a negative control tract and task to demonstrate a double dissociation.

METHODS

Adult survivors of childhood brain tumors [n = 29, age: M = 22 years (SD = 5), 45% female] and demographically matched controls were recruited (n = 29). Tests of auditory attention span, working memory, and visual attention served as cognitive measures. Participants completed a 3-T MRI diffusion-weighted imaging scan. Fractional anisotropy (FA) and radial diffusivity (RD) served as WMI measures. Partial correlations between WMI and cognitive scores included controlling for type of treatment.

RESULTS

A correlational double dissociation was found. RC-LF WMI was associated with auditory attention (FA: r = .42, p = .03; RD: r = -.50, p = .01) and was not associated with visual attention (FA: r = -.11, p = .59; RD: r = -.11, p = .57). SLF II FA WMI was associated with visual attention (FA: r = .44, p = .02; RD: r = -.17, p = .40) and was not associated with auditory attention (FA: r = .24, p = .22; RD: r = -.10, p = .62).

CONCLUSIONS

The results show that RC-LF WMI is associated with auditory attention span rather than working memory per se and provides evidence for a specificity based on the correlational double dissociation.

A preliminary study on the application of DTI in the treatment of brain tumors in motor function areas with gamma knife

OBJECTIVES

The treatment safety and efficiency as well as the life quality of patients are still main concerns in gamma knife radiosurgery. In this study, the feasibility of applying diffusion tensor imaging (DTI) in gamma knife radiosurgery for the treatment of brain tumor in motor function areas was investigated, which aims to provide protection on the pyramidal tract and preserve the motor function in patients.

PATIENTS AND METHODS

Total 74 patients with solid brain tumor were enrolled and divided into DTI group and control group. The tumor control rate was assessed at 3 months after surgery. The muscle strength of affected limb, KPS scores, ZEW scores and complications were evaluated at 3 and 6 months after gamma knife radiosurgery.

RESULTS

Our results indicated that the tumor control rate, complication rate, the muscle strength of affected limb and KPS scores were not significantly different between the two groups at 3 months after surgery. At 6 months after gamma knife radiosurgery, the complication rate (0% vs 50 %, P = 0.044), KPS scores (64.9 % vs 37.8 %, P = 0.036) and ZEW scores (78.4 % vs 54.1 %, P = 0.044) of DTI group were better than the control group. Furthermore, the stability of muscle strength in patients with limb dysfunction was significantly improved in DTI group (86.4 % vs 50 %, P = 0.028).

CONCLUSION

In summary, the application of DTI in gamma knife radiosurgery for the treatment of brain tumors in motor function areas can precisely define the tumor edge from pyramidal tract, which will support on designing individual treatment plan, reducing the incidence of complications, and improving long-term life quality in patients.

Advances in the pathophysiology of adult-onset focal dystonias: recent neurophysiological and neuroimaging evidence

Focal dystonia is a movement disorder characterized by involuntary muscle contractions that determine abnormal postures. The traditional hypothesis that the pathophysiology of focal dystonia entails a single structural dysfunction (i.e. basal ganglia) has recently come under scrutiny. The proposed network disorder model implies that focal dystonias arise from aberrant communication between various brain areas. Based on findings from animal studies, the role of the cerebellum has attracted increased interest in the last few years. Moreover, it has been increasingly reported that focal dystonias also include nonmotor disturbances, including sensory processing abnormalities, which have begun to attract attention. Current evidence from neurophysiological and neuroimaging investigations suggests that cerebellar involvement in the network and mechanisms underlying sensory abnormalities may have a role in determining the clinical heterogeneity of focal dystonias.

High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management

Objective

To investigate the performance of high-order radiomics features and models based on T2-weighted fluid-attenuated inversion recovery (T2 FLAIR) in predicting the immunohistochemical biomarkers of glioma, in order to execute a non-invasive, more precise and personalized glioma disease management.

Methods

51 pathologically confirmed gliomas patients committed in our hospital from March 2015 to June 2018 were retrospective analysis, and Ki-67, vimentin, S-100 and CD34 immunohistochemical data were collected. The volumes of interest (VOIs) were manually sketched and the radiomics features were extracted. Feature reduction was performed by ANOVA+ Mann-Whiney, spearman correlation analysis, least absolute shrinkage and selection operator (LASSO) and Gradient descent algorithm (GBDT). SMOTE technique was used to solve the data bias between two groups. Comprehensive binary logistic regression models were established. Area under the ROC curves (AUC), sensitivity, specificity and accuracy were used to evaluate the predict performance of models. Models reliability were decided according to the standard net benefit of the decision curves.

Results

Four clusters of significant features were screened out and four predicting models were constructed. AUC of Ki-67, S-100, vimentin and CD34 models were 0.713, 0.923, 0.854 and 0.745, respectively. The sensitivities were 0.692, 0.893, 0.875 and 0.556, respectively. The specificities were: 0.667, 0.905, 0.722, and 0.875, with accuracy of 0.660, 0.898, 0.738, and 0.667, respectively. According to the decision curves, the Ki-67, S-100 and vimentin models had reference values.

Conclusion

The radiomics features based on T2 FLAIR can potentially predict the Ki-67, S-100, vimentin and CD34 expression. Radiomics model were expected to be a computer-intelligent, non-invasive, accurate and personalized management method for gliomas.

Temporal lobe microstructural abnormalities in patients with nasopharyngeal carcinoma quantitatively evaluated by high-resolution DWI and DKI after concurrent chemoradiotherapy

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DKI could detect early radiation-induced microstructural abnormalities after CCRT.

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The ADC, Dmean, and FA of temporal lobe showed a unique time-dependent trajectory.

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Kmean might be more sensitive to detection of effects in the late delayed phases.

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White and grey matter all underwent microstructural changes after radiotherapy.

Purpose

To investigate temporal lobe microstructural abnormalities and neurocognitive function impairment after concurrent chemoradiotherapy (CCRT) in patients with nasopharyngeal carcinoma (NPC).

Methods

NPC patients who underwent CCRT were enrolled. High-resolution diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) and diffusion-kurtosis imaging (DKI) MRI, were performed 5 times per patient (once pre-CCRT, 1 week post-CCRT, 3 months post-CCRT, 6 months post-CCRT, and 12 months post-CCRT). Neurocognitive function was evaluated by Montreal Neurocognitive Assessment (MoCA) twice per patient, once pre-CCRT, and once 12-months after CCRT.

Results

Of 111 patients, 56 completed the entire protocol. The MRI derived apparent diffusion coefficient (ADC), mean of diffusion coefficient (Dmean) and fractional anisotropy (FA) values were significantly decreased (p < 0.05) over the 0–3 month period following CCRT and significantly increased (p < 0.05) over the 3–12 month period following CCRT. The mean of kurtosis coefficient (Kmean) continued to decline over a year post-CCRT. All parameters reveal more pronounced changes in white matter (WM) than in grey matter (GM). MoCA also declined after CCRT (p < 0.001). MoCA showed significant positive correlation with Kmean-WM-6 m, Kmean-WM-12 m and ΔKmean-WM.

Conclusions

High-resolution DWI and DKI should be considered as a promising method for the investigation of temporal lobe microstructural change in NPC patients after CCRT.

Neuroimaging for the Neurologist: Clinical MRI and Future Trends

MRI is a commonly used diagnostic tool in neurology, and all neurologists should possess a working knowledge of imaging fundamentals. An overview of current and impending MRI techniques is presented to help the referring clinician communicate better with the imaging department, understand the utility and limitations of current and emerging technology, improve specificity and appropriateness when ordering MRI studies, and recognize key findings.

Combined native magnetic resonance angiography, flow-quantifying, and perfusion-imaging for impending second-stroke assessment

This special report introduces native flow quantitative imaging for evaluating stroke risk. Moreover, the advantage of combining three imaging techniques [magnetic resonance angiography (MRA), phase-contrast (PC) flow imaging, and arterial spin-labeling imaging] is shown to be beneficial for responding to ischemia and preserving viable neurons. These quantitative imaging techniques provide authoritative information for diagnosing impending stroke and selecting appropriate treatment.

Presence of Probst Bundles Indicate White Matter Remodeling in a Dog With Corpus Callosum Hypoplasia and Dysplasia

Corpus callosum abnormalities (CCA) rarely occur in dogs and are related to hypo/adypsic hypernatremia and seizures. Hypoplasia and dysplasia of the corpus callosum (CC) with concomitant lobar holoprosencephaly is the most common variant. It is currently uncertain using conventional MRI if canine CCA reflects the failure of commissural fibers to develop or the failure of the commissural fibers to cross hemispheres. Diffusion tensor imaging was performed in a 4-year-old Staffordshire mix breed dog with CCA and an age-matched healthy Beagle. In comparison to the control dog, CC tractography of the affected dog depicted only axonal tracts corresponding to the temporal CC fibers. The cingulum bundles appeared supernumerary with unorganized architecture, extending into the ipsilateral cerebral cortex, and therefore strongly suggested homology to Probst bundles reported in humans with CCA. The presence of Probst bundles in canine CCA could represent compensatory neuroplasticity-mediated networking and may contribute the fair prognosis reported in affected dogs.

Comparison of Various Parameters of DWI in Distinguishing Solitary Pulmonary Nodules

In order to prospectively assess various parameters of diffusion weighted imaging (DWI) in differential diagnosis of benign and malignant solitary pulmonary nodules (SPNs), 58 patients (40 men and 18 women, and mean age of 48.1±10.4 years old) with SPNs undergoing conventional MR, DWI using b=500 s/mm² on a 1.5T MR scanner, were studied. Various DWI parameters [apparent diffusion coefficient (ADC), lesion-tospinal cord signal intensity ratio (LSR), signal intensity (SI) score] were calculated and compared between malignant and benign SPNs groups. A receiver operating characteristic (ROC) curve analysis was employed to compare the diagnostic capabilities of all the parameters for discrimination between benign and malignant SPNs. The results showed that there were 42 malignant and 16 benign SPNs. The ADC was significantly lower in malignant SPNs (1.40±0.44)×10^-3 mm²/s than in benign SPNs (1.81±0.58)×10^-3 mm²/s. The LSR and SI scores were significantly increased in malignant SPNs (0.90±0.37 and 2.8±1.2) as compared with those in benign SPNs (0.68±0.39 and 2.2±1.2). The area under the ROC curves (AUC) of all parameters was not significantly different between malignant SPNs and benign SPNs. It was suggested that as three reported parameters for DWI, ADC, LSR and SI scores are all feasible for discrimination of malignant and benign SPNs. The three parameters have equal diagnostic performance.

Novel Imaging Biomarkers for Huntington's Disease and Other Hereditary Choreas

PURPOSE OF THE REVIEW

Imaging biomarkers for neurodegenerative disorders are primarily developed with the goal to aid diagnosis, to monitor disease progression, and to assess the efficacy of disease-modifying therapies in support to clinical outcomes that may either show limited sensitivity or need extended time for their evaluation. This article will review the most recent concepts and findings in the field of neuroimaging applied to Huntington's disease and Huntington-like syndromes. Emphasis will be given to the discussion of potential pharmacodynamic biomarkers for clinical trials in Huntington's disease (HD) and of neuroimaging tools that can be used as diagnostic biomarkers in HD-like syndromes.

RECENT FINDINGS

Several magnetic resonance (MR) and positron emission tomography (PET) molecular imaging tools have been identified as potential pharmacodynamic biomarkers and others are in the pipeline after preclinical validation. MRI and 18F-fluorodeoxyglucose PET can be considered useful supportive diagnostic tools for the differentiation of other HD-like syndromes. New trials in HD have the primary goal to lower mutant huntingtin (mHTT) protein levels in the brain in order to reduce or alter the progression of the disease. MR and PET molecular imaging markers have been developed as tools to monitor disease progression and to evaluate treatment outcomes of disease-modifying trials in HD. These markers could be used alone or in combination for detecting structural and pharmacodynamic changes potentially associated with the lowering of mHTT.

Crossed cerebellar diaschisis in post-treatment glioma patients: A comparative study of arterial spin labelling and dynamic susceptibility contrast

OBJECTIVES

To assess crossed cerebellar diaschisis (CCD) in post-treatment glioma patients, and to compare the performance of arterial spin labelling (ASL) and dynamic susceptibility contrast (DSC) in detecting CCD.

METHODS AND MATERIALS

This retrospective study included 130 patients who had both DSC and ASL. Among them, 16 had underwent fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT). We investigated the relationship between CCD and the location and size of supratentorial lesions, and compared PET diagnostic performance with that of ASL and DSC. We assessed the inter-methods agreement for ASL and DSC, and performed quantitative analysis by calculating the asymmetry index (AI) between bilateral cerebellum and exploring how the AI values for ASL-CBF, DSC-rCBF, and DSC-rCBV maps correlated with each other.

RESULT

Supratentorial lesions affecting the corona radiata (P < 0.001), basal ganglia (P < 0.001), and insula (P = 0.046) were significantly associated with the occurrence of CCD. Lesion size was significantly larger (P = 0.005) in the CCD positive group. With PET as a reference, ASL-CBF and DSC-rCBF maps exhibited the best diagnostic performance compared with the other DSC-generated maps (diagnostic accuracy = 83.3% for both, area under curve (AUC) of ASL = 0.967, AUC of rCBF = 0.983), although differences were not statistically significant. The κ value for the inter-methods (ASL and DSC) agreement in detecting CCD was 0.893, while the degree of perfusion asymmetry was more significant in ASL- than DSC-generated maps. Bland-Altman plots showed that the AI for ASL-CBF was moderately correlated with those for DSC-rCBF and DSC-rCBV.

CONCLUSIONS

CCD can present in post-treatment glioma patients and is detectable on MR-perfusion images including ASL-CBF, DSC-rCBF, and DSC-rCBV maps.

Can dynamic contrast-enhanced MRI evaluate VEGF expression in brain glioma? An MRI-guided stereotactic biopsy study

PURPOSE

To investigate whether pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to evaluate vascular endothelial growth factor (VEGF) expression in brain glioma based on a point-to-point basis.

MATERIALS AND METHODS

Forty-seven patients with treatment-naïve glioma received preoperative DCE-MRI before stereotactic biopsy. We histologically quantified VEGF from section of stereotactic biopsies, and co-registered biopsy locations with localized measurements of DCE-MRI parameters including volume transfer coefficient (K^trans), reverse reflux rate constant (Kep), extracellular extravascular volume fraction (Ve) and blood plasma volume (Vp). The correlations between DCE-MRI parameters (K^trans, Kep, Ve and Vp) and VEGF were determined using Spearman correlation coefficient. P≤.05 was considered statistically significant.

RESULTS

Seventy-nine biopsy samples were obtained and graded into 45 high-grade gliomas (HGGs) and 34 low-grade gliomas (LGGs). K^trans showed a significant positive correlation with VEGF expression in HGGs group (ρ=0.505, P<0.001) and in combined group (LGGs+HGGs) (ρ=0.549, P<0.001), but not in LGGs group (P>0.05). Kep, Ve or Vp was not correlated with VEGF even though a positive trend showed (P>0.05).

CONCLUSIONS

DCE-MRI is a useful, non-invasive imaging technique for quantitative evaluation of VEGF, and its parameter K^trans other than Kep, Ve or Vp may be used as a surrogate for VEGF expression in brain gliomas.

Pseudoprogression of brain tumors

This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high-grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day-to-day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9-30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow-up. The combination of MRS and diffusion-weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer-aided diagnostic technology, and meticulous evaluation with clinical and pathological data.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Radiomics strategy for glioma grading using texture features from multiparametric MRI

BACKGROUND

Accurate glioma grading plays an important role in the clinical management of patients and is also the basis of molecular stratification nowadays.

PURPOSE/HYPOTHESIS

To verify the superiority of radiomics features extracted from multiparametric MRI to glioma grading and evaluate the grading potential of different MRI sequences or parametric maps.

STUDY TYPE

Retrospective; radiomics.

POPULATION

A total of 153 patients including 42, 33, and 78 patients with Grades II, III, and IV gliomas, respectively.

FIELD STRENGTH/SEQUENCE

3.0T MRI/T₁ -weighted images before and after contrast-enhanced, T₂ -weighted, multi-b-value diffusion-weighted and 3D arterial spin labeling images.

ASSESSMENT

After multiparametric MRI preprocessing, high-throughput features were derived from patients' volumes of interests (VOIs). The support vector machine-based recursive feature elimination was adopted to find the optimal features for low-grade glioma (LGG) vs. high-grade glioma (HGG), and Grade III vs. IV glioma classification tasks. Then support vector machine (SVM) classifiers were established using the optimal features. The accuracy and area under the curve (AUC) was used to assess the grading efficiency.

STATISTICAL TESTS

Student's t-test or a chi-square test were applied on different clinical characteristics to confirm whether intergroup significant differences exist.

RESULTS

Patients' ages between LGG and HGG groups were significantly different (P < 0.01). For each patient, 420 texture and 90 histogram parameters were derived from 10 VOIs of multiparametric MRI. SVM models were established using 30 and 28 optimal features for classifying LGGs from HGGs and grades III from IV, respectively. The accuracies/AUCs were 96.8%/0.987 for classifying LGGs from HGGs, and 98.1%/0.992 for classifying grades III from IV, which were more promising than using histogram parameters or using the single sequence MRI.

DATA CONCLUSION

Texture features were more effective for noninvasively grading gliomas than histogram parameters. The combined application of multiparametric MRI provided a higher grading efficiency. The proposed radiomic strategy could facilitate clinical decision-making for patients with varied glioma grades.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1518-1528.

Radiographic patterns of recurrence and pathologic correlation in malignant gliomas treated with bevacizumab

Interpretation of MRI abnormalities in patients with malignant gliomas (MG) treated with bevacizumab is challenging. Recent reports describe quantitative analyses of diffusion-weighted imaging abnormalities not available in standard clinical settings, to differentiate tumor recurrence from treatment necrosis. We retrospectively reviewed bevacizumab treated MG patients who underwent surgery or autopsy to correlate radiographic recurrence patterns with pathologic findings. 32 patients with MG (26 glioblastoma, three anaplastic astrocytoma and three anaplastic oligodendroglioma) were identified. Recurrence patterns: local enhancing (n = 23), distant enhancing (n = 1), nonenhancing (n = 7) and leptomeningeal (n = 1). Histology: tumor (n = 25), mixed tumor/necrosis (n = 5) and all necrosis (n = 2). On diffusion-weighted imaging, 5/32 had restricted diffusion (three mixed and two necrosis). Irrespective of radiographic recurrence pattern, tumor was found in 94% of cases. Restricted diffusion correlated with necrosis.

Principles of diffusion kurtosis imaging and its role in early diagnosis of neurodegenerative disorders

Pathology of neurodegenerative diseases can be correlated with intra-neuronal as well as extracellular changes which lead to neuronal degeneration. The central nervous system (CNS) is a complex structure comprising of many biological barriers. These microstructural barriers might be affected by a variety of pathological processes. Specifically, changes in the brain tissue's microstructure affect the diffusion of water which can be assessed non-invasively by diffusion weighted (DW) magnetic resonance imaging (MRI) techniques. Diffusion tensor imaging (DTI) is a diffusion MRI technique that considers diffusivity as a Gaussian process, i.e. does not account for any diffusion hindrance. However, environment of the brain tissues is characterized by a non-Gaussian diffusion. Therefore, diffusion kurtosis imaging (DKI) was developed as an extension of DTI method in order to quantify the non-Gaussian distribution of water diffusion. This technique represents a promising approach for early diagnosis of neurodegenerative diseases when the neurodegenerative process starts. Hence, the purpose of this article is to summarize the ongoing clinical and preclinical research on Parkinson's, Alzheimer's and Huntington diseases, using DKI and to discuss the role of this technique as an early stage biomarker of neurodegenerative conditions.

Advanced MRI Measures of Cerebral Perfusion and Their Clinical Applications

Cerebral blood flow measurement by magnetic resonance imaging perfusion (MRP) techniques is broadly applied to patients with acute ischemic stroke, vasospasm following aneurysmal subarachnoid hemorrhage, chronic arterial steno-occlusive disease, cervical atherosclerotic disease, and primary brain neoplasms. MRP may be performed using an exogenous tracer, most commonly gadolinium-based intravenous contrast, or an endogenous tracer, such as arterial spin labeling (ASL) or intravoxel incoherent motion (IVIM). Here, we review the technical basis of commonly performed MRP techniques, the interpretation of MRP imaging maps, and how MRP provides valuable clinical information in the triage of patients with cerebral disease.

Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis

BACKGROUND

Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing.

METHODS

We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (DES) as the main variable; the heterogeneity index (I2) and Pearson's correlations between the DES and co-variables (demographic, clinical and MRI parameters) were also calculated.

RESULTS

Our results showed that FA-DES and MD-DES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-DES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter.

CONCLUSIONS

Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.

Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity

Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems by treating neural elements (cells, volumes) as nodes in a graph and neural interactions (synapses, white matter tracts) as edges in that graph. Here, we review the emerging discipline of network neuroscience, which uses and develops tools from graph theory to better understand and manipulate neural systems from micro- to macroscales. We present examples of how human brain imaging data are being modeled with network analysis and underscore potential pitfalls. We then highlight current computational and theoretical frontiers and emphasize their utility in informing diagnosis and monitoring, brain-machine interfaces, and brain stimulation. A flexible and rapidly evolving enterprise, network neuroscience provides a set of powerful approaches and fundamental insights that are critical for the neuroengineer's tool kit.

A theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast MRI

Mapping the complex heterogeneity of vascular tissue in the brain is important for understanding cerebrovascular disease. In this translational study, we build on previous work using vessel architectural imaging (VAI) and present a theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast magnetic resonance imaging (MRI). Our tissue model covers realistic structural architectures for vessel branching and orientations, as well as a range of hemodynamic scenarios for blood flow, capillary transit times and oxygenation. In a typical image voxel, our findings show that the apparent MRI relaxation rates are independent of the mean vessel orientation and that the vortex area, a VAI-based parameter, is determined by the relative oxygen saturation level and the vessel branching of the tissue. Finally, in both simulated and patient data, we show that the relative distributions of the vortex area parameter as a function of capillary transit times show unique characteristics in normal-appearing white and gray matter tissue, whereas tumour-voxels in comparison display a heterogeneous distribution. Collectively, our study presents a comprehensive framework that may serve as a roadmap for in vivo and per-voxel determination of vascular status and heterogeneity in cerebral tissue.

Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature

Since Emil Kraepelin's conceptualization of endogenous psychoses as dementia praecox and manic depression, the separation between primary psychotic disorders and primary affective disorders has been much debated. We conducted a systematic review of case-control studies contrasting magnetic resonance imaging studies in schizophrenia and bipolar disorder. A literature search in PubMed of studies published between January 2005 and December 2016 was conducted, and 50 structural, 29 functional, 7 magnetic resonance spectroscopy, and 8 combined imaging and genetic studies were deemed eligible for systematic review. Structural neuroimaging studies suggest white matter integrity deficits that are consistent across the illnesses, while gray matter reductions appear more widespread in schizophrenia compared to bipolar disorder. Spectroscopy studies in cortical gray matter report evidence of decreased neuronal integrity in both disorders. Functional neuroimaging studies typically report similar functional architecture of brain networks in healthy controls and patients across the psychosis spectrum, but find differential extent of alterations in task related activation and resting state connectivity between illnesses. The very limited imaging-genetic literature suggests a relationship between psychosis risk genes and brain structure, and possible gene by diagnosis interaction effects on functional imaging markers. While the existing literature suggests some shared and some distinct neural markers in schizophrenia and bipolar disorder, it will be imperative to conduct large, well designed, multi-modal neuroimaging studies in medication-naïve first episode patients that will be followed longitudinally over the course of their illness in an effort to advance our understanding of disease mechanisms.

Reproducibility of dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI in the study of brain gliomas: a comparison of data obtained using different commercial software

PURPOSE

Dynamic susceptibility contrast MRI (DSC) and dynamic contrast-enhanced MRI (DCE) are useful tools in the diagnosis and follow-up of brain gliomas; nevertheless, both techniques leave the open issue of data reproducibility. We evaluated the reproducibility of data obtained using two different commercial software for perfusion maps calculation and analysis, as one of the potential sources of variability can be the software itself.

METHODS

DSC and DCE analyses from 20 patients with gliomas were tested for both the intrasoftware (as intraobserver and interobserver reproducibility) and the intersoftware reproducibility, as well as the impact of different postprocessing choices [vascular input function (VIF) selection and deconvolution algorithms] on the quantification of perfusion biomarkers plasma volume (Vp), volume transfer constant (K ^trans) and rCBV. Data reproducibility was evaluated with the intraclass correlation coefficient (ICC) and Bland-Altman analysis.

RESULTS

For all the biomarkers, the intra- and interobserver reproducibility resulted in almost perfect agreement in each software, whereas for the intersoftware reproducibility the value ranged from 0.311 to 0.577, suggesting fair to moderate agreement; Bland-Altman analysis showed high dispersion of data, thus confirming these findings. Comparisons of different VIF estimation methods for DCE biomarkers resulted in ICC of 0.636 for K ^trans and 0.662 for Vp; comparison of two deconvolution algorithms in DSC resulted in an ICC of 0.999.

CONCLUSIONS

The use of single software ensures very good intraobserver and interobservers reproducibility. Caution should be taken when comparing data obtained using different software or different postprocessing within the same software, as reproducibility is not guaranteed anymore.

Extreme Mountain Ultra-Marathon Leads to Acute but Transient Increase in Cerebral Water Diffusivity and Plasma Biomarkers Levels Changes

Background: Pioneer studies demonstrate the impact of extreme sport load on the human brain, leading to threatening conditions for athlete's health such as cerebral edema. The investigation of brain water diffusivity, allowing the measurement of the intercellular water and the assessment of cerebral edema, can give a great contribution to the investigation of the effects of extreme sports on the brain. We therefore assessed the effect of supra-physiological effort (extreme distance and elevation changes) in mountain ultra-marathons (MUMs) athletes combining for the first time brain magnetic resonance imaging (MRI) and blood parameters.

Methods:This longitudinal study included 19 volunteers (44.2 ± 9.5 years) finishing a MUM (330 km, elevation + 24000 m). Quantitative measurements of brain diffusion-weighted images (DWI) were performed at 3 time-points: Before the race, upon arrival and after 48 h. Multiple blood biomarkers were simultaneously investigated. Data analyses included brain apparent diffusion coefficient (ADC) and physiological data comparisons between three time-points.

Results:The whole brain ADC significantly increased from baseline to arrival (p = 0.005) and then significantly decreased at recovery (p = 0.005) to lower values than at baseline (p = 0.005). While sodium, potassium, calcium, and chloride as well as hematocrit (HCT) changed over time, the serum osmolality remained constant. Significant correlations were found between whole brain ADC changes and osmolality (p = 0.01), cholesterol (p = 0.009), c-reactive protein (p = 0.04), sodium (p = 0.01), and chloride (p = 0.002) plasma level variations.

Conclusions:These results suggest the relative increase of the inter-cellular volume upon arrival, and subsequently its reduction to lower values than at baseline, indicating that even after 48 h the brain has not fully recovered to its equilibrium state. Even though serum electrolytes may only indirectly indicate modifications at the brain level due to the blood brain barrier, the results concerning osmolality suggest that body water might directly influence the change in cerebral ADC. These findings establish therefore a direct link between general brain inter-cellular water content and physiological biomarkers modifications produced by extreme sport.

Wallerian Degeneration Beyond the Corticospinal Tracts: Conventional and Advanced MRI Findings

Wallerian degeneration (WD) is defined as progressive anterograde disintegration of axons and accompanying demyelination after an injury to the proximal axon or cell body. Since the 1980s and 1990s, conventional magnetic resonance imaging (MRI) sequences have been shown to be sensitive to changes of WD in the subacute to chronic phases. More recently, advanced MRI techniques, such as diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI), have demonstrated some of earliest changes attributed to acute WD, typically on the order of days. In addition, there is increasing evidence on the value of advanced MRI techniques in providing important prognostic information related to WD. This article reviews the utility of conventional and advanced MRI techniques for assessing WD, by focusing not only on the corticospinal tract but also other neural tracts less commonly thought of, including corticopontocerebellar tract, dentate-rubro-olivary pathway, posterior column of the spinal cord, corpus callosum, limbic circuit, and optic pathway. The basic anatomy of these neural pathways will be discussed, followed by a comprehensive review of existing literature supported by instructive clinical examples. The goal of this review is for readers to become more familiar with both conventional and advanced MRI findings of WD involving important neural pathways, as well as to illustrate increasing utility of advanced MRI techniques in providing important prognostic information for various pathologies.

Cervical Spinal Cord DTI Is Improved by Reduced FOV with Specific Balance between the Number of Diffusion Gradient Directions and Averages

BACKGROUND AND PURPOSE

Reduced-FOV DTI is promising for exploring the cervical spinal cord, but the optimal set of parameters needs to be clarified. We hypothesized that the number of excitations should be favored over the number of diffusion gradient directions regarding the strong orientation of the cord in a single rostrocaudal axis.

MATERIALS AND METHODS

Fifteen healthy individuals underwent cervical spinal cord MR imaging at 3T, including an anatomic 3D-Multi-Echo Recombined Gradient Echo, high-resolution full-FOV DTI with a NEX of 3 and 20 diffusion gradient directions and 5 sets of reduced-FOV DTIs differently balanced in terms of NEX/number of diffusion gradient directions: (NEX/number of diffusion gradient directions = 3/20, 5/16, 7/12, 9/9, and 12/6). Each DTI sequence lasted 4 minutes 30 seconds, an acceptable duration, to cover C1-C4 in the axial plane. Fractional anisotropy maps and tractograms were reconstructed. Qualitatively, 2 radiologists rated the DTI sets blinded to the sequence. Quantitatively, we compared distortions, SNR, variance of fractional anisotropy values, and numbers of detected fibers.

RESULTS

Qualitatively, reduced-FOV DTI sequences with a NEX of ≥5 were significantly better rated than the full-FOV DTI and the reduced-FOV DTI with low NEX (N = 3) and a high number of diffusion gradient directions (D = 20). Quantitatively, the best trade-off was reached by the reduced-FOV DTI with a NEX of 9 and 9 diffusion gradient directions, which provided significantly fewer artifacts, higher SNR on trace at b = 750 s/mm² and an increased number of fibers tracked while maintaining similar fractional anisotropy values and dispersion.

CONCLUSIONS

Optimized reduced-FOV DTI improves spinal cord imaging. The best compromise was obtained with a NEX of 9 and 9 diffusion gradient directions, which emphasizes the need for increasing the NEX at the expense of the number of diffusion gradient directions for spinal cord DTI contrary to brain DTI.

Cerebral hemispheric low-grade glial tumors in children: preoperative anatomic assessment with MRI and DTI

PURPOSE

The aims of this study are to analyze how the nature and the behavior of low-grade glial tumors (LGGT) in children may correlate with the anatomy of the cerebral hemispheres and to evaluate the consequent impact of diffusion tensor imaging (DTI) techniques in the presurgical assessment.

METHODS

This is a combined review of a series of 155 cases of LGGT and of the recent literature on the subject.

RESULTS

The cases retrieved from our data bank were divided in central hemispheric tumors (basal ganglia and thalami) (36 cases), glioneuronal cortical-based tumors (49 cases), and glial tumors of the cerebral mantle (70 cases). A close correlation was found in the thalamus between the primary location of the tumor (juxta-ventricular, inferior, lateral, bilateral) and its extension (ventricular lumen, midbrain and mesial temporal, globus pallidus, respectively) which may relate to the connectivity. Among the glioneuronal tumors, most gangliogliomas were located in the temporal lobe and especially in the mesial temporal structures. In addition, the morphologic feature of the ganglioglioma was different there from the neocortical areas. As a complementary approach, DTI data may assist in evaluating the structure and the extension of the LGGT, in addition to planning the surgical strategy.

CONCLUSIONS

In the cerebral hemispheres like in the rest of the central nervous system, there is some degree of correlation between the anatomy and the nature, appearance, and behavior of the LGGT in children.

A chronic encapsulated intracerebral hematoma mimicking a brain tumor: Findings on arterial spin labeling of MRI

BACKGROUND

Intracerebral hematoma usually resolves spontaneously. Chronic encapsulated intracerebral hematoma is rare and mimics a brain tumor.

CASE DESCRIPTION

A 50-year-old man had developed intracerebral hematoma in the right temporal lobe. Computed tomography (CT) showed the gradually decreasing density of the hematoma. However, the hematoma did not decrease in size and it showed ring enhancement on contrast-enhanced CT for more than 1 year. Magnetic resonance imaging (MRI) revealed a lesion content showing a high intensity on both T1- and T2-weighted images with ring enhancement. The lesion was diagnosed as a chronic encapsulated intracerebral hematoma developing from an acute hematoma. Arterial spin labeling of MRI showed decreased blood perfusion even in the enhanced capsule, being different from findings of a cystic brain tumor.

CONCLUSION

Arterial spin labeling might be a useful modality to distinguish a chronic encapsulated intracerebral hematoma from a cystic hypervascular brain tumor.