High b-value diffusion-weighted MRI of normal brain

Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas

OBJECTIVES

To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADCb500/b1000, ADCb500/b2000, ADCb500/b3000, ADCb500/b4000, ADCb500/b6000, ADCb500/b8000, and ADCb500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared.

RESULTS

All ADCs were significantly higher in IDH mutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADCb500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADCb500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADCb500/b8000 and ADCb500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADCb500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADCb500/b8000 and ADCb500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADCb500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all).

CONCLUSION

Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria.

CLINICAL RELEVANCE STATEMENT

Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma.

KEY POINTS

• Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review

ABSTRACT

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.

Neural network algorithms predict new diffusion MRI data for multi-compartmental analysis of brain microstructure in a clinical setting

High angular resolution diffusion imaging (HARDI) is a promising method for advanced analysis of brain microstructure. However, comprehensive HARDI analysis requires multiple acquisitions of diffusion images (multi-shell HARDI), which is time consuming and often impractical in clinical settings. This study aimed to establish neural network models that can predict new diffusion datasets from clinically feasible brain diffusion MRI for multi-shell HARDI. The development included 2 algorithms: multi-layer perceptron (MLP) and convolutional neural network (CNN). Both followed a voxel-based approach for model training (70%), validation (15%), and testing (15%). The investigations involved 2 multi-shell HARDI datasets: 1) 11 healthy subjects from the Human Connectome Project (HCP); and 2) 10 local subjects with multiple sclerosis (MS). To assess outcomes, we conducted neurite orientation dispersion and density imaging using both predicted and original data and compared their orientation dispersion index (ODI) and neurite density index (NDI) in different brain tissues with 2 measures: peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Results showed that both models achieved robust predictions, which provided competitive ODI and NDI, especially in brain white matter. The CNN outperformed MLP with the HCP data on both PSNR (p < 0.001) and SSIM (p < 0.01). With the MS data, the models performed similarly. Overall, the optimized neural networks can help generate non-acquired brain diffusion MRI, which will make advanced HARDI analysis possible in clinical practice following further validation. Enabling detailed characterization of brain microstructure will allow enhanced understanding of brain function in both health and disease.

Glioma segmentation with DWI weighted images, conventional anatomical images, and post-contrast enhancement magnetic resonance imaging images by U-Net

Glioma segmentation is believed to be one of the most important stages of treatment management. Recent developments in magnetic resonance imaging (MRI) protocols have led to a renewed interest in using automatic glioma segmentation with different MRI image weights. U-Net is a major area of interest within the field of automatic glioma segmentation. This paper examines the impact of different input MRI image-weight on the U-Net output performance for glioma segmentation. One hundred forty-nine glioma patients were scanned with a 1.5T MRI scanner. The main MRI image-weights acquired are diffusion-weighted imaging (DWI) weighted images (b50, b500, b1000, Apparent diffusion coefficient (ADC) map, Exponential apparent diffusion coefficient (eADC) map), anatomical image-weights (T₂, T₁, T₂-FLAIR), and post enhancement image-weights (T₁Gd). The U-Net and data augmentation are used to segment the glioma tumors. Having the Dice coefficient and accuracy enabled us to compare our results with the previous study. The first set of analyses examined the impact of epoch number on the accuracy of U-Net, and n_epoch = 20 was selected for U-Net training. The mean Dice coefficient for b50, b500, b1000, ADC map, eADC map, T₂, T₁, T₂-FLAIR, and T₁Gd image weights for glioma segmentation with U-Net were calculated 0.892, 0.872, 0.752, 0.931, 0.944, 0.762, 0.721, 0.896, 0.694 respectively. This study has found that, DWI image-weights have a higher diagnostic value for glioma segmentation with U-Net in comparison with anatomical image-weights and post enhancement image-weights. The results of this investigation show that ADC and eADC maps have higher performance for glioma segmentation with U-Net.

Single-shell to multi-shell dMRI transformation using spatial and volumetric multilevel hierarchical reconstruction framework

Single or Multi-shell high angular resolution diffusion imaging (HARDI) has become an important dMRI acquisition technique for studying brain white matter fibers. Existing single-shell HARDI makes it challenging to estimate the intravoxel structure up to the desired resolution. However, multi-shell acquisition (with multiple b-values) can provide higher resolution for the intravoxel structure, which further helps in getting accurate fiber tracts; But, this comes at the cost of larger acquisition time and larger setup. Hence, we propose a novel deep learning architecture for the reconstruction of diffusion MRI volumes for different b-values (degree of diffusion weighting) using acquisitions at a fixed b-value (termed as single-shell) acquisition. This reconstruction has been performed in the spherical harmonics space to better manage varying gradient directions. In this work, we have demonstrated such a reconstruction for b = 3000 s/mm² and b = 2000 s/mm² from b = 1000 s/mm². The proposed Multilevel Hierarchical Spherical Harmonics Coefficients Reconstruction (MHSH) framework takes advantage of contextual information within each slice as well as across the slices by involving Slice Level ReconNet (SLRNet) network and a Volumetric ROI Level ReconNet (VPLRNet) network, respectively. Three-loss functions have been used to optimize network learning, i.e., L₁, Adversarial, and Total Variation Loss. Finally, the network is trained and validated on the publicly available HCP data-set with standard qualitative and quantitative performance measures and achieves promising results.

Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting

BACKGROUND

The purpose of this study was to determine whether advanced quantitative magnetic resonance imaging (MRI) can be deployed outside of large, research-oriented academic hospitals and into community care settings to predict eventual pathological complete response (pCR) to neoadjuvant therapy (NAT) in patients with locally advanced breast cancer.

METHODS

Patients with stage II/III breast cancer (N = 28) were enrolled in a multicenter study performed in community radiology settings. Dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI data were acquired at four time points during the course of NAT. Estimates of the vascular perfusion and permeability, as assessed by the volume transfer rate (K^trans) using the Patlak model, were generated from the DCE-MRI data while estimates of cell density, as assessed by the apparent diffusion coefficient (ADC), were calculated from DW-MRI data. Tumor volume was calculated using semi-automatic segmentation and combined with K^trans and ADC to yield bulk tumor blood flow and cellularity, respectively. The percent change in quantitative parameters at each MRI scan was calculated and compared to pathological response at the time of surgery. The predictive accuracy of each MRI parameter at different time points was quantified using receiver operating characteristic curves.

RESULTS

Tumor size and quantitative MRI parameters were similar at baseline between groups that achieved pCR (n = 8) and those that did not (n = 20). Patients achieving a pCR had a larger decline in volume and cellularity than those who did not achieve pCR after one cycle of NAT (p < 0.05). At the third and fourth MRI, changes in tumor volume, K^trans, ADC, cellularity, and bulk tumor flow from baseline (pre-treatment) were all significantly greater (p < 0.05) in the cohort who achieved pCR compared to those patients with non-pCR.

CONCLUSIONS

Quantitative analysis of DCE-MRI and DW-MRI can be implemented in the community care setting to accurately predict the response of breast cancer to NAT. Dissemination of quantitative MRI into the community setting allows for the incorporation of these parameters into the standard of care and increases the number of clinical community sites able to participate in novel drug trials that require quantitative MRI.

Preliminary study of multiple b-value diffusion-weighted images and T1 post enhancement magnetic resonance imaging images fusion with Laplacian Re-decomposition (LRD) medical fusion algorithm for glioma grading

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LRD medical image fusion algorithm can be used for glioma grading.

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We can use the LRD fusion algorithm with MRI image for glioma grading.

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Fusing of DWI (b50) and T₁ enhancement (T₁Gd) by LRD, have highest diagnostic value for glioma grading.

Background

Grade of brain tumor is thought to be the most significant and crucial component in treatment management. Recent development in medical imaging techniques have led to the introduce non-invasive methods for brain tumor grading such as different magnetic resonance imaging (MRI) protocols. Combination of different MRI protocols with fusion algorithms for tumor grading is used to increase diagnostic improvement. This paper investigated the efficiency of the Laplacian Re-decomposition (LRD) fusion algorithms for glioma grading.

Procedures

In this study, 69 patients were examined with MRI. The T1 post enhancement (T1Gd) and diffusion-weighted images (DWI) were obtained. To evaluated LRD performance for glioma grading, we compared the parameters of the receiver operating characteristic (ROC) curves.

Findings

We found that the average Relative Signal Contrast (RSC) for high-grade gliomas is greater than RSCs for low-grade gliomas in T1Gd images and all fused images. No significant difference in RSCs of DWI images was observed between low-grade and high-grade gliomas. However, a significant RSCs difference was detected between grade III and IV in the T1Gd, b50, and all fussed images.

Conclusions

This research suggests that T1Gd images are an appropriate imaging protocol for separating low-grade and high-grade gliomas. According to the findings of this study, we may use the LRD fusion algorithm to increase the diagnostic value of T1Gd and DWI picture for grades III and IV glioma distinction. In conclusion, this article has emphasized the significance of the LRD fusion algorithm as a tool for differentiating grade III and IV gliomas.

Alterations in Diffusion Measures of White Matter Integrity Associated with Healthy Aging

This study aimed to characterize age-related white matter changes by evaluating patterns of overlap between the linear association of age with fractional anisotropy (FA) with mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Specifically, we assessed patterns of overlap between diffusion measures of normal appearing white matter by covarying for white matter hyperintensity (WMH) load, as WMHs are thought to increase with age and impact diffusion measures. Seventy-nine healthy adults aged between 18 and 75 years took part in the study. Diffusion tensor imaging (DTI) data were based on 61 directions acquired with a b-value of 2,000. We found five main patterns of overlap: FA alone (15.95%); FA and RD (31.90%); FA and AD (12.99%); FA, RD, and AD (27.93%); and FA, RD, and MD (8.79%). We showed that cognitively healthy aging adults had low WMH load, which subsequently had minimal effect on diffusion measures. We discuss how patterns of overlap may reflect underlying biological changes observed with aging such as loss of myelination, axonal damage, as well as mild microstructural and chronic white matter impairments. This study contributes to understanding the underlying causes of degeneration in specific regions of the brain and highlights the importance of considering the impact of WMHs in aging studies of white matter.

Diffusion tensor imaging reveals neuronal microstructural changes in myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients suffer from a variety of physical and neurological complaints indicating the central nervous system plays a role in ME/CFS pathophysiology. Diffusion tensor imaging (DTI) has been used to study microstructural changes in neurodegenerative diseases. In this study, we evaluated DTI parameters to investigate microstructural abnormalities in ME/CFS patients. We estimated DTI parameters in 25 ME/CFS patients who met Fukuda criteria (ME/CFS_Fukuda ), 18 ME/CFS patients who met International Consensus Criteria (ICC) (ME/CFS_ICC ) only and 26 healthy control (HC) subjects. In addition to voxel-based DTI-parameter group comparisons, we performed voxel-based DTI-parameter interaction-with-group regressions with clinical and autonomic measures to test for abnormal regressions. Group comparisons between ME/CFS_ICC and HC detected significant clusters (a) with decreased axial diffusivity (p = .001) and mean diffusivity (p = .01) in the descending cortico-cerebellar tract in the midbrain and pons and (b) with increased transverse diffusivity in the medulla. The mode of anisotropy was significantly decreased (p = .001) in a cluster in the superior longitudinal fasciculus region. Voxel-based group comparisons between ME/CFS_Fukuda and HC did not detect significant clusters. For ME/CFS_ICC and HC, DTI parameter interaction-with-group regressions were abnormal for the clinical measures of information processing score, SF36 physical, sleep disturbance score and respiration rate in both grey and white matter regions. Our study demonstrated that DTI parameters are sensitive to microstructural changes in ME/CFS_ICC and could potentially act as an imaging biomarker of abnormal pathophysiology in ME/CFS. The study also shows that strict case definitions are essential in investigation of the pathophysiology of ME/CFS.

Diffusion-weighted MRI of ischemic stroke at 3T: Value of synthetic b-values

OBJECTIVES

Diffusion-weighted imaging (DWI) plays a crucial role in the diagnosis of ischemic stroke. We assessed the value of computed and acquired high b-value DWI in comparison with conventional b = 1000 s mm^-2 DWI for ischemic stroke at 3T.

METHODS

We included 36 patients with acute ischemic stroke who presented with diffusion abnormalities on DWI performed within 24 h of symptom onset. B-values of 0, 500, 1000 and 2000 s mm^-2 were acquired. Synthetic images with b-values of 1000, 1500, 2000 and 2500 s mm^-2 were computed. Two readers compared synthetic (syn) and acquired (acq) b = 2000 s mm^-2 images with acquired b = 1000 s mm^-2 images in terms of lesion detection rate, image quality, presence of uncertain hyperintensities and lesion conspicuity. Readers also selected their preferred b-value. Contrast ratio (CR) measurements were performed. Non-parametrical statistical tests and weighted Cohens' κ tests were computed.

RESULTS

Syn1000 and syn1500 matched acq1000 images in terms of lesion detection rate, image quality and presence of uncertain hyperintensities but presented with significantly improved lesion conspicuity (p < 0.01) and were frequently selected as preferred b-values. Acq2000 images exhibited a similar lesion detection rate and improved lesion conspicuity (p < 0.01) but worse image quality (p < 0.01) than acq1000 images. Syn2000 and syn2500 images performed significantly worse (p < 0.01) than acq1000 images in most or all categories. CR significantly increased with increasing b-values.

CONCLUSION

Synthetic images at b = 1000 and 1500 s mm^-2 and acquired DWI images at b = 2000 s mm^-2 may be of clinical value due to improved lesion conspicuity.

ADVANCES IN KNOWLEDGE

Synthetic b-values enable improved lesion conspicuity for DWI of ischemic stroke.

Deep Learning-Based Denoising for High b-Value at 2000 s/mm2 Diffusion-Weighted Imaging

Diffusion-weighted imaging (DWI) allows white matter quantification of the white matter tracts of the brain. However, at a high b-value (≥ 2000 s/mm2), DWI acquisition suffers from noise due to longer acquisition times obscuring white matter interpretation. DWI denoising techniques can be used to acquire high b-value DWI without increasing the number of signal averages. We used a residual learning-based convolutional neural network (DnCNN) to reduce noise in high b-value DWI based on the literature review. We applied the proposed denoising method on high b-value, retrospectively collected DWI data with multiple noise levels. Experimental results show an improved image quality after denoising in retrospective DWI (average PSNR before and after denoising: 27.63 ± 1.06 dB and 51.76 ± 1.95 dB, respectively). The prospective DWI included one and two signal averages for denoising. DWI with four signal averages was used as the reference. Representative images show high b-value prospective DW images denoised using the DnCNN. We demonstrated DnCNN for cases of multiple noise levels and signal averages. For the prospective study, the PSNR values for 1-NEX before and after denoising were 27.39 ± 3.75 dB and 27.68 ± 3.75 dB. For 2-NEX, the PSNR values before and after denoising were 27.51 ± 4.18 dB and 27.75 ± 4.05 dB.

Preclinical Molecular Imaging for Precision Medicine in Breast Cancer Mouse Models

Precision and personalized medicine is gaining importance in modern clinical medicine, as it aims to improve diagnostic precision and to reduce consequent therapeutic failures. In this regard, prior to use in human trials, animal models can help evaluate novel imaging approaches and therapeutic strategies and can help discover new biomarkers. Breast cancer is the most common malignancy in women worldwide, accounting for 25% of cases of all cancers and is responsible for approximately 500,000 deaths per year. Thus, it is important to identify accurate biomarkers for precise stratification of affected patients and for early detection of responsiveness to the selected therapeutic protocol. This review aims to summarize the latest advancements in preclinical molecular imaging in breast cancer mouse models. Positron emission tomography (PET) imaging remains one of the most common preclinical techniques used to evaluate biomarker expression in vivo, whereas magnetic resonance imaging (MRI), particularly diffusion-weighted (DW) sequences, has been demonstrated as capable of distinguishing responders from nonresponders for both conventional and innovative chemo- and immune-therapies with high sensitivity and in a noninvasive manner. The ability to customize therapies is desirable, as this will enable early detection of diseases and tailoring of treatments to individual patient profiles. Animal models remain irreplaceable in the effort to understand the molecular mechanisms and patterns of oncologic diseases.

Diffusion Tensor Model links to Neurite Orientation Dispersion and Density Imaging at high b-value in Cerebral Cortical Gray Matter

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm²). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture.

Bright Edge Sign on High b-Value Diffusion-Weighted Imaging as a New Imaging Biomarker to Predict Poor Prognosis in Glioma Patients: A Retrospective Pilot Study

Purpose: To investigate the prognostic value of bright edge sign observed on high b-value diffusion-weighted imaging (DWI) map in glioma patients. Methods: We retrospectively reviewed our prospectively collected database for gliomas. Bright edge sign was defined as the presence of extremely high signal in tumor margin on high b-value DWI map (b = 3,000 s/mm²) with the signal intensity higher than those in contralateral normal white matter and tumor central region. Extremely poor prognosis was defined as overall survival time < 9 months. Survival analyses were conducted by using the Cox regression for both the univariable and multivariable analyses. Results: A total of 52 patients were enrolled (WHO IV, 25; WHO III, 13; WHO II, 14). Bright edge sign presented in 10 (19.2%) patients (WHO IV, 5; WHO III, 3; WHO II, 2). Nine (90.0%) patients with bright edge sign had extremely poor prognosis, while only 1 (2.4 %) patient without bright edge sign had extremely poor prognosis. The sensitivity and specificity of bright edge sign in determining extremely poor prognosis were 90 and 97.7%, respectively. Bright edge sign (HR [95% CI] = 25.11 [7.26-86.81], p < 0.001) was an independent predictor of poor prognosis after adjustment. Conclusion: Bright edge sign on high b-value DWI may be an accurate predictor of extremely poor prognosis in glioma patients, regardless of pathologic grades.

Aging-Related Microstructural Alterations Along the Length of the Cingulum Bundle

The aim of this study was to investigate the aging-related structural changes of the cingulum, one of the major components of the limbic network, which has a critical role in emotion, attention, and memory. Thirty-five healthy young adults (22.3 ± 2.7 years) and 33 healthy older adults (69.5 ± 3.5 years) were recruited. Diffusion weighted imaging data were acquired with a b-value = 2000 sec/mm² and 61 diffusion directions and 4 non-weighted images. The fiber directions in each voxel were based on the constrained spherical deconvolution model. The cingulum was segmented into three branches using deterministic tractography (subgenual, retrosplenial, and parahippocampal), using a region-of-interest-based approach. Atlas-based tractography was the method used to obtain the output tracts of each branch of the cingulum. Along-tract analysis was performed on each branch. We found a statistically significant change with aging in the left subgenual branch of the cingulum with a decrease in fractional anisotropy and axial diffusivity, as well as an increase in radial diffusivity. No statistically significant differences were found between young and older groups in the other two branches. This study adds to knowledge about how the cingulum changes structurally along its entire length during aging in a more detailed way, thanks to an advanced methodological approach.

Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting

BACKGROUND

Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer.

PURPOSE/HYPOTHESIS

To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1 -mapping of the breast in community radiology practices.

STUDY TYPE

Prospective.

SUBJECTS/PHANTOM

Ice-water DW-MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test-retest analysis at one site in normal subjects (n = 12) was used to assess repeatability.

FIELD STRENGTH/SEQUENCE

3T Siemens Skyra MRI quantitative DW-MRI and T1 -mapping.

ASSESSMENT

Quantitative DW-MRI and T1 -mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast.

STATISTICAL TESTS

Average values of breast tissue were quantified and Bland-Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility.

RESULTS

ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice-water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively).

DATA CONCLUSION

Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1 -mapping and DW-MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment.

LEVEL OF EVIDENCE

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

The value of multi ultra high-b-value DWI in grading cerebral astrocytomas and its association with aquaporin-4

OBJECTIVE

To investigate the value of multi-ultrahigh-b-value diffusion-weighted imaging (UHBV-DWI) in differentiating high-grade astrocytomas (HGAs) from low-grade astrocytomas (LGAs), analyze its association with aquaporin (AQP) expression.

METHODS

40 astrocytomas divided into LGAs (N = 15) and HGAs (N = 25) were studied. Apparent diffusion coefficient (ADC) and UHBV-ADC values in solid parts and peritumoral edema were compared between LGAs and HGAs groups by the t-test. Using receiver operating characteristic curves to identify the better parameter. Using real time polymerase chain reaction to assess AQP messenger ribonucleic acid (mRNA). Using spearman correlation analysis to assess the correlation of AQP mRNA with each parameter.

RESULTS

ADC values in solid parts of HGAs were significantly lower than LGAs (p = 0.02), while UHBV-ADC values of HGAs were significantly higher than LGAs (p < 0.01). Area under the curve (AUC) of UHBV-ADC (0.810) was larger than ADC (0.713), and the area under the curve of UHBV-ADC was significantly higher than that of ADC (p = 0.041). AQP4 mRNA was significantly higher in HGAs than that in LGAs (p < 0.01); there was less AQP9 mRNA and no AQP1 mRNA in LGAs and HGAs groups (p > 0.05); ADC value showed a negative correlation with AQP4 mRNA (r = -0.357; p = 0.024). UHBV-ADC value positively correlated with the AQP4 mRNA (r = 0.646; p < 0.01).

CONCLUSION

UHBV-DWI allowed for a more accurate grading of cerebral astrocytoma than DWI, and UHBV-ADC value may be related with the AQP4 mRNA levels. UHBV-DWI could be of value in the assessment of astrocytoma. Advances in knowledge: UHBV-DWI generated by multi UHBV could have particular value for astrocytoma grading, and the level of AQP4 mRNA might be potentially linked to the change of UHBV-DWI parameter, and we might find the exact reason for the difference of UHBV-ADC between the LGAs and HGAs.

Glioma infiltration sign on high b-value diffusion-weighted imaging in gliomas and its prognostic value

BACKGROUND

Glioma cells may infiltrate beyond the tumor margins revealed on conventional structural images.

PURPOSE

To investigate whether the presence of a glioma infiltration sign on high b-value diffusion-weighted imaging (DWI) can predict the prognosis of gliomas.

STUDY TYPE

Retrospective cohort.

SUBJECTS

Fifty-two patients with gliomas (14 WHO grade II; 13 WHO grade III; 25 WHO grade IV).

FIELD STRENGTH/SEQUENCE

3.0T, including a T1 -weighted contrast-enhanced (T1 w-CE) sequence, contrast-enhanced T2 -flair sequence, and a DWI sequence.

ASSESSMENT

T1 w-CE images and contrast-enhanced T2 -flair images were used for identifying the tumor region for enhancing and nonenhancing gliomas, respectively. The glioma infiltration sign was defined as the presence of a peritumoral abnormal high signal region on DWI map, which was adjacent to the tumor region and had higher signal than surrounding areas. This sign was assessed on a high b-value DWI map with b = 3000 s/mm2 . For patients with glioma infiltration sign, DWI3000max , DWI1000max , ADC3000min , and ADC1000min were measured by drawing a region of interest over the peritumoral abnormal high signal region.

STATISTICAL TESTS

Survival analysis was conducted by using Cox regression.

RESULTS

Glioma infiltration sign was observed in 28 (53.8%) patients. The occurrence rate of this sign was 92.0% in grade IV gliomas, 30.8% in grade III gliomas, and 7.1% in grade II gliomas. The glioma infiltration sign could independently predict both the progression-free survival (hazard ratio [HR], 95% confidence interval [CI] = 8.58 [3.19-23.03], P < 0.001) and overall survival (HR, 95% CI = 11.90 [3.41-41.55], P < 0.001) after adjustment. For patients with glioma infiltration sign, DWI3000max (P = 0.005) and ADC3000min (P = 0.008) were both independent predictors of overall survival after adjustment, while DWI1000max and ADC1000min were not.

DATA CONCLUSION

The glioma infiltration sign on high b-value DWI is an independent predictor of poor prognosis in glioma patients. High b-value DWI might be a convenient method to detect glioma infiltration.

LEVEL OF EVIDENCE

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

Use of high b value diffusion-weighted magnetic resonance imaging in acute encephalopathy/encephalitis during childhood

AIM

To determine the use of high b value diffusion-weighted imaging (DWI) in the diagnosis and assessment of acute febrile encephalopathy/encephalitis in childhood.

SUBJECTS AND METHODS

We enrolled 22 children, for whom we examined DWI with b=1000s/mm², DWI with b=3000s/mm², and apparent diffusion coefficient (ADC) map with b=1000 during the acute phase of febrile encephalopathy/encephalitis. Clinical diagnoses included acute encephalopathy with biphasic seizures and late reduced diffusion (AESD; n=6), clinically mild encephalopathy/encephalitis with a reversible splenial lesion (MERS; n=6), and herpes simplex virus encephalitis (HSE; n=3), unclassified acute encephalopathy/acute encephalitis (n=2); acute encephalitis with refractory, repetitive partial seizures (AERRPS; n=1); other encephalopathy (n=1); infarction (n=1); head injury (n=1); or mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (n=1). The diagnostic quality of brain lesions was compared between b=1000 and b=3000 DWI images by visual inspection. In addition, we attempted a quantitative assessment using apparent diffusion coefficient (ADC) value and an index of signal intensity (SI) ratio, defined as the mean SI at the affected lesion divided by the mean SI at the pons.

RESULTS

High intensity lesions were either visible only on b=3000 DWI (n=5; 2 AESD, 1 MERS, 1 HSE, and 1 unclassifiable encephalopathy) or more effectively identified on b=3000 DWI than on b=1000 DWI (n=17). The outcome of the former five subjects was favorable, without motor or intellectual sequelae. The mean SI ratio of b=3000 was significantly greater than that of b=1000 in AESD and MERS subgroups as well as in all 22 subjects. Mean ADC values were lower in the AESD and MERS than that in the HSE subgroups.

CONCLUSION

We concluded that b=3000 DWI was superior to b=1000 DWI in detecting abnormal lesions in acute encephalopathy/encephalitis during childhood.

Brain structural connectivity during adrenarche: Associations between hormone levels and white matter microstructure

Levels of the adrenal hormones dehydroepiandrosterone (DHEA), its sulfate (DHEAS), and testosterone, have all been linked to behavior and mental health during adrenarche, and preclinical studies suggest that these hormones influence brain development. However, little is known about how variation in these hormones is associated with white matter structure during this period of life. The current study aimed to examine associations between DHEA, DHEAS, and testosterone, and white matter microstructure during adrenarche. To avoid the confounding effect of age on hormone levels, we tested these associations in 87 children within a narrow age range (mean age 9.56 years, SD=0.34) but varying in hormone levels. All children provided saliva samples directly after waking and completed a diffusion-weighted MRI scan. Higher levels of DHEA were associated with higher mean diffusivity (MD) in a widespread cluster of white matter tracts, which was partially explained by higher radial diffusivity (RD) and partially by higher axial diffusivity (AD). In addition, there was an interaction between DHEA and testosterone, with higher levels of testosterone being associated with higher fractional anisotropy (FA) and lower MD and RD when DHEA levels were relatively high, but with lower FA and higher MD and RD when DHEA levels were low. These findings suggest that relatively early exposure to DHEA, as well as an imbalance between the adrenal hormones, may be associated with alterations in white matter microstructure. These findings highlight the potential relevance of adrenarcheal hormones for structural brain development.

Benefit of 3T Diffusion-weighted Imaging in Comparison to Contrast-enhanced MR Imaging for the Evaluation of Disseminated Lesions in Primary Malignant Brain Tumors

PURPOSE

We aimed to determine whether 3T diffusion-weighted imaging (DWI) has an additive value relative to contrast-enhanced MR imaging for the detection of disseminated lesions in patients with primary malignant brain tumors.

METHODS

We included consecutive 12 patients with nodular disseminated lesions of primary malignant brain tumors that were confirmed by surgery or follow-up MR imaging. All underwent conventional MR imaging, DWI at b = 1000 and 3000 s/mm², post-contrast T₁-weighted and 3D gradient-echo imaging at 3T. For the largest lesion per person, two radiologists independently evaluated the presence of additional information on DWI compared with postcontrast MR images using a 4-point scoring system. On DW images, one radiologist measured the lesion-to-brain contrast ratio (LBCR).

RESULTS

Compared with postcontrast studies, radiologists 1 and 2, respectively, assigned more apparent lesion conspicuity in 2 (17%) and 1 (8%) DWI at b = 1000 s/mm² and 4 (33%) and 5 (42%) DWI at b = 3000 s/mm² studies. For one of them, the mean score was significantly higher for b = 3000 s/mm² than b = 1000 s/mm² (P < 0.05). Interobserver agreement for DWI at b = 1000 s/mm² and b = 3000 s/mm² was very good (κ = 0.85; 95% CI, 0.63-1.00) and excellent (κ = 0.93; 95% CI, 0.78-1.00), respectively. The mean LBCR was significantly higher for DWI at b = 3000 s/mm² than DWI at b = 1000 s/mm² (P < 0.01).

CONCLUSION

In the detection of disseminated lesions in patients with primary malignant brain tumors, 3T DWI has an additive value relative to contrast-enhanced MR imaging. DWI at b = 3000 s/mm² may be more useful than DWI at b = 1000 s/mm².

High b-value diffusion-weighted imaging in progressive multifocal leukoencephalopathy in HIV patients

Objectives

An ill-defined hyperintense edge and hypointense core on diffusion-weighted imaging (DWI) is typical of progressive multifocal leukoencephalopathy (PML). We aimed to investigate whether a b-value of 3,000 s/mm² (b3000) can improve visualisation of PML, or provide different structural information compared to 1,000 s/mm² (b1000).

Methods

We retrospectively identified HIV-positive patients with confirmed PML studied under a clinical protocol including both b1000 and b3000 DWI. The rim and core of each PML lesion and normal-appearing white matter (NAWM) were outlined on trace-weighted DWI. Signal intensities, apparent diffusion coefficient (ADC) values and volumes were measured and compared between b1000 and b3000.

Results

Nine lesions from seven patients were analysed. The rim and core were better visualised on b3000, with higher signal of the rim and lower signal of the core compared to NAWM. The hyperintense rim had non-restricted average ADCs, but included foci of low ADC on both b3000 and b1000. Despite similar total lesion volumes, b3000 displayed significantly larger core and smaller rim volumes than b1000.

Conclusion

b3000 improves visualisation of this important PML hallmark. Moreover, b3000 partly reclassifies tissue from rim into core, and might provide potentially more accurate biomarkers of PML activity and prognosis.

Key Points

• B3000 improves contrast resolution between lesion rim, core and normal-appearing white matter.

• B3000 improves identification of the typical rim-and-core pattern of PML lesions.

• B3000 and b1000 similarly identify lesions, but b3000 results in smaller rims and larger cores.

• B3000 excludes some high diffusion components from rim, reclassifying them into core.

• B3000 DWI may provide more precise PML biomarkers of disease activity and tissue damage.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4761-8) contains supplementary material, which is available to authorized users.

Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences

Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.

Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging

PURPOSE

To explore the role of histogram analysis of apparent diffusion coefficient (ADC) maps obtained at standard- and high-b-value (1000 and 3000 sec/mm(2), respectively) diffusion-weighted (DW) imaging in the differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board of Seoul National University Hospital, and informed consent requirement was waived. Thirty patients with histopathologically proved glioblastoma who had undergone concurrent chemotherapy and radiation therapy (CCRT) with temozolomide underwent diffusion-weighted MR imaging with b values of 1000 and 3000 sec/mm(2), and corresponding ADC maps were calculated from entire newly developed or enlarged enhancing lesions after completion of CCRT. Histogram parameters of each ADC map between true progression (n = 15) and pseudoprogression (n = 15) groups were compared by using the unpaired Student t test. Receiver operating characteristic analysis was used to determine the best cutoff values for predictors in the differentiation of true progression from pseudoprogression. Results were validated in an independent test set of nine patients by using the best cutoff value to predict differentiation of true progression from pseudoprogression. The accuracy of the selected best cutoff value in the independent test set was then calculated.

RESULTS

In terms of cumulative histograms, the fifth percentile of both ADC at b value of 1000 sec/mm(2) (ADC1000) and the ADC at b value of 3000 sec/mm(2) (ADC3000) were significantly lower in the true progression group than in the pseudoprogression group (P = .049 and P < .001, respectively). In contrast, neither the mean ADC1000 nor the mean ADC3000 was significantly different between the two groups. The diagnostic values of the parameters derived from ADC1000 and ADC3000 were compared, and a significant difference (0.224, P = .016) was found between the area under the receiver operating characteristic curve of the fifth percentile for ADC1000 and that for ADC3000. The accuracies were 66.7% (six of nine patients) and 88.9% (eight of nine patients) based on the fifth percentile of both ADC1000 and ADC3000 in the independent test set, respectively.

CONCLUSION

The fifth percentile of the cumulative ADC histogram obtained at a high b value was the most promising parameter in the differentiation of true progression from pseudoprogression of the newly developed or enlarged enhancing lesions after CCRT with temozolomide for glioblastoma treatment. Online supplemental material is available for this article.

Added value of high-b-value (b = 3000 s/mm2) diffusion-weighted imaging at 3 T in relation to fluid-attenuated inversion recovery images for the evaluation of cortical lesions in inflammatory brain diseases

OBJECTIVE

The purpose of this study was to determine how the gray-to-white matter contrast in healthy subjects changes on high-b-value diffusion-weighted imaging (DWI) acquired at 3 T and evaluate whether high-b-value DWI at 3 T is useful for the detection of cortical lesions in inflammatory brain diseases.

METHODS

Ten healthy volunteers underwent DWI at b = 1000, 2000, 3000, 4000, and 5000 s/mm(2) on a 3-T MRI unit. On DW images, 1 radiologist performed region-of-interest measurements of the signal intensity of 8 gray matter structures. The gray-to-white matter contrast ratio (GWCR) was calculated. Ten patients with inflammatory cortical lesions were also included. All patients underwent conventional MRI and DWI at b = 1000 and 3000 s/mm(2). Using a 4-point grading system, 2 radiologists independently assessed the presence of additional information on DW images compared with fluid-attenuated inversion recovery images. Interobserver agreement was assessed by κ statistics.

RESULTS

In the healthy subjects, the b value increased as the GWCR decreased in all evaluated gray matter structures. On DW images acquired at b = 3000 s/mm(2), mean GWCR was less than 1.0 in 7 of 8 structures. For both reviewers, DWI at b = 3000 s/mm(2) yielded significantly more additional information than did DWI at b = 1000 s/mm(2) (P < 0.05). Interobserver agreement for DWI at b = 1000 s/mm(2) and b = 3000 s/mm(2) was fair (κ = 0.35) and excellent (κ = 1.0), respectively.

CONCLUSIONS

At 3-T DWI, the gray-to-white matter contrast in most gray matter structures reverses at b = 3000 s/mm. In the evaluation of cortical lesions in patients with inflammatory brain diseases, 3-T DWI at b = 3000 s/mm was more useful than b = 1000 s/mm(2).

A decade of DTI in traumatic brain injury: 10 years and 100 articles later

SUMMARY

The past decade has seen an increase in the number of articles reporting the use of DTI to detect brain abnormalities in patients with traumatic brain injury. DTI is well-suited to the interrogation of white matter microstructure, the most important location of pathology in TBI. Additionally, studies in animal models have demonstrated the correlation of DTI findings and TBI pathology. One hundred articles met the inclusion criteria for this quantitative literature review. Despite significant variability in sample characteristics, technical aspects of imaging, and analysis approaches, the consensus is that DTI effectively differentiates patients with TBI and controls, regardless of the severity and timeframe following injury. Furthermore, many have established a relationship between DTI measures and TBI outcomes. However, the heterogeneity of specific outcome measures used limits interpretation of the literature. Similarly, few longitudinal studies have been performed, limiting inferences regarding the long-term predictive utility of DTI. Larger longitudinal studies, using standardized imaging, analysis approaches, and outcome measures will help realize the promise of DTI as a prognostic tool in the care of patients with TBI.

Methodology of diffusion-weighted, diffusion tensor and magnetisation transfer imaging

MRI offers a number of opportunities to examine characteristics of tissue well below the spatial resolution of the imaging technique. The best known of these is diffusion imaging, which allows the production of images whose contrast reflects the ability of water molecules to move through the extravascular extracellular space. Less well-known, but increasingly important, is magnetisation transfer imaging, which produces contrast based on the ability of protons to move between the free water pool and local macromolecules. Both of these techniques offer unique information about the microscopic and molecular structure of tumour tissue. This article will briefly review the underlying theory and technical aspects associated with these imaging techniques.

Conspicuity of breast lesions at different b values on diffusion-weighted imaging

Background

Diffusion-weighted (DW) imaging has shown potential to differentiate between malignant and benign breast lesions. However, different b values have been used with varied sensitivity and specificity. This study aims to prospectively evaluate the influence of b value on the detection and assessment of breast lesions.

Methods

Institutional review board approval and informed patient consent were obtained. Between February 2010 and September 2010, sixty women suspected of having breast cancer by clinical examination and mammography underwent bilateral breast MRI and DW imaging (with maximum b values of 600, 800, and 1000 s/mm²). Conspicuity grades of lesions at different b values on DW images were performed. Signal intensity and apparent diffusion coefficient (ADC) values were recorded and compared among different b values by the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and receiver operating characteristic (ROC) curve.

Results

Fifty-seven lesions from 52 recruited patients including 39/57 (68%) malignant and 18/57 (32%) benign were confirmed with pathology. DCE MRI accurately detected 53 lesions with the sensitivity of 93.0% and specificity of 66.7%, and DW imaging accurately detected 51 lesions with the sensitivity of 89.5% and specificity of 100%. There were no significant differences in conspicuity grades compared among the three b values (P = 0.072), although the SNR and CNR of breast lesions decreased significantly with higher b values. Mean ADCs of malignant lesions (b = 600 s/mm², 1.07 ± 0.26 × 10^-3 mm²/s; b = 800 s/mm², 0.96 ± 0.22 × 10^-3 mm²/s; b = 1000 s/mm², 0.92 ± 0.26 × 10^-3 mm²/s) were significantly lower than those of benign lesions (b = 600 s/mm², 1.55 ± 0.40 × 10^-3 mm²/s; b = 800 s/mm², 1.43 ± 0.38 × 10^-3 mm²/s; b = 1000 s/mm², 1.49 ± 0.38 × 10^-3 mm²/s) with all P values <0.001, but there were no significant differences among the three b values (P = 0.303 and 0.840 for malignant and benign lesions, respectively). According to the area under the ROC curves, which were derived from ADC and differentiate malignant from benign lesions, no significant differences were found among the three b values (P = 0.743).

Conclusions

DW imaging is a potential adjunct to conventional MRI in the differentiation between malignant and benign breast lesions. Varying the maximum b value from 600 to 1000 s/mm² does not influence the conspicuity of breast lesions on DW imaging at 1.5 T.

A multi-center study: intra-scan and inter-scan variability of diffusion spectrum imaging

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

High b-value diffusion-weighted imaging: a sensitive method to reveal white matter differences in schizophrenia

Over the last 10 years, diffusion-weighted imaging (DWI) has become an important tool to investigate white matter (WM) anomalies in schizophrenia. Despite technological improvement and the exponential use of this technique, discrepancies remain and little is known about optimal parameters to apply for diffusion weighting during image acquisition. Specifically, high b-value diffusion-weighted imaging known to be more sensitive to slow diffusion is not widely used, even though subtle myelin alterations as thought to happen in schizophrenia are likely to affect slow-diffusing protons. Schizophrenia patients and healthy controls were scanned with a high b-value (4000 s/mm(2)) protocol. Apparent diffusion coefficient (ADC) measures turned out to be very sensitive in detecting differences between schizophrenia patients and healthy volunteers even in a relatively small sample. We speculate that this is related to the sensitivity of high b-value imaging to the slow-diffusing compartment believed to reflect mainly the intra-axonal and myelin bound water pool. We also compared these results to a low b-value imaging experiment performed on the same population in the same scanning session. Even though the acquisition protocols are not strictly comparable, we noticed important differences in sensitivities in the favor of high b-value imaging, warranting further exploration.

3-T high-b-value diffusion-weighted MR imaging of hyperacute ischemic stroke in the vertebrobasilar territory

BACKGROUND AND PURPOSE

Diffusion-weighted imaging (DWI) is the key method for diagnosing acute ischemic stroke. Applied b values in stroke diffusion studies are usually in the range of 800-1500 s/mm², but progress in magnetic resonance (MR) technology now permits higher b values. However, it is uncertain whether high-b-value DW sequences improve the detection of acute and hyperacute ischemic lesions. The aim of this study is to explore the sensitivity of high b values vs standard b values at 3T in hyperacute stroke in the vertebrobasilar territory.

MATERIAL AND METHODS

3-T DWI was performed in referred patients with a clinical diagnosis of hyperacute (<6h from onset) cerebral infarction using conventional MR sequences as well as DW sequences. Examinations included the usual DW sequence (b=1000 s/mm²) and two high-b-value DW sequences (b=3000 s/mm² and b=5000 s/mm²). Patients with hyperacute stroke in the posterior circulation were included if MR imaging, including the usual DW sequence, was normal or if the diagnosis was uncertain.

RESULTS

In all six studied patients, ischemic lesions were better visualized with high-b-value DWI compared with the usual DWI. On increasing the b value, DW images appeared to be noisier while white-matter tracts became progressively hyperintense.

CONCLUSION

At 3T, high-b-value DW sequences may be helpful for diagnosing hyperacute infarctions in the vertebrobasilar territory, but further studies are needed to confirm this hypothesis.

Apparent diffusion coefficient with higher b-value correlates better with viable cell count quantified from the cavity of brain abscess

BACKGROUND AND PURPOSE

DWI by using higher b-values provides tissue diffusivity with less T2 shinethrough effect. VCD in the abscess cavity correlates with ADC values. The purpose of this study was to investigate which b-value-derived ADC correlates better with VCD.

MATERIALS AND METHODS

Thirty patients with brain abscess underwent conventional MR imaging and DWI with b = 1000, 2000, and 3000 s/mm(2) on a 3T MR imaging scanner. ADC values were quantified by placing regions of interest inside the abscess cavity in all sections where the lesion was apparent on coregistered ADC maps derived from different b-values. VCD was measured on pus aspirated.

RESULTS

An increase in b-value was associated with a decrease in ADC values in normal parenchyma as well as in the abscess cavity. The most significant negative correlation of VCD was observed with b = 3000 s/mm(2) (r = -0.98, P = .01).

CONCLUSIONS

VCD in the abscess cavity can be best assessed at b = 3000 s/mm(2) secondary to the reduction in the T2 shinethrough effect. DWI with b = 3000 s/mm(2) is of promising value in the assessment of the therapeutic response of brain abscess.

Meta-analysis of apparent diffusion coefficients in the newborn brain

Diffusion-weighted imaging and its quantitative apparent diffusion coefficient can assess severity in newborn hypoxic-ischemic injuries. A meta-analysis established normative values in term newborns, in comparison to those values in hypoxic-ischemic newborns with good versus poor outcomes. Measurements from 14 reports were stratified into three levels of increasing specificity: tissue type (gray matter, white matter, or cerebellum), tissue distribution (e.g., cortex or white-matter tracts), and anatomic structures (e.g., frontal white matter or posterior limb of the internal capsule). Normative apparent diffusion coefficients constituted white matter > gray matter = cerebellum, with lowest values in the posterior limb of the internal capsule and thalamus, and the highest in frontal and occipital white matter. Differences between normative and hypoxic-ischemic injury good-outcome groups were not evident. Values in the poor outcome group were significantly lower than normative data in white matter, gray matter, cortical gray matter, white matter tracts, posterior limb of the internal capsule, and cortical, frontal, and occipital white matter. Comparisons between injury groups found that coefficients were only significantly lower in the occipital cortex among poor outcomes. Coefficient values were lower in deep brain compared with cortical structures, reflecting tissue maturation and myelination. Differences between normative and hypoxic-ischemic injury poor-outcome groups suggest pathologies associated with neurologic sequelae. This meta-analysis provides the basis for normative apparent diffusion coefficient values in the newborn brain.

Enhanced detection of diffusion reductions in Creutzfeldt-Jakob disease at a higher B factor

BACKGROUND AND PURPOSE

Diffusion-weighted imaging (DWI) is sensitive to the cerebral manifestations of human prion diseases. The magnitude of diffusion weighting, termed "b factor," has only been evaluated at the standard b = 1000 s/mm(2). This is the first rigorous evaluation of b = 2000 s/mm(2) in Creutzfeldt-Jakob Disease (CJD).

MATERIALS AND METHODS

We compared DWI characteristics of 13 patients with CJD and 15 healthy controls at b = 1000 s/mm(2) and b = 2000 s/mm(2). Apparent diffusion coefficients (ADC) were computed and analyzed for the whole brain by voxel-wise analysis (by SPM5) as well as in anatomically defined volumes of interest (by FSL FIRST).

RESULTS

Measured ADC was significantly lower (by approximately 5%-15%) at b = 2000 s/mm(2) than at b = 1000 s/mm(2) and significantly lower in patients than in controls. The differences between patients and controls were greater and more extensive at b = 2000 s/mm(2) than at b = 1000 s/mm(2) in the expected regions (thalamus, putamen, and caudate nucleus).

CONCLUSIONS

Because higher b factors change the absolute value of observed ADC, as well as lesion detection, care should be taken when combining studies using different b factors. While the clinical application of high b factors is currently limited by a low signal intensity-to-noise ratio, it may offer more information in questionable cases, and our results confirm and extend the central role of diffusion imaging in human prion diseases.

[Brain apparent diffusion coefficient: differences caused by age, sex, laterality, and distinct b value]

OBJECTIVE

To analyze the effects of age, sex, and b value on the apparent diffusion coefficient (ADC) in brain areas affected by neurodegenerative diseases.

MATERIAL AND METHODS

We studied the ADC of the genu and splenium of the corpus callosum and of the hippocampus in normal patients using diffusion magnetic resonance imaging (dMRI) with b1,000 s/mm2 and b3,000 s/mm2. We calculated the differences between the ADC (diffusion differential [DD]) with b1,000 and with b3,000 for each region. Patients were classified into the following age groups (<or=30 years old, 31-60 years old, >60 years old). We used a Kruskal-Wallis one-way ANOVA and the Bonferroni correction to analyze the differences in ADC and DD between age groups and between sexes. Pearson's chi-square test was used to correlate the ADC and DD with age.

RESULTS

In the right hippocampus, we observed differences in ADC (b1,000, p=0.011; b3,000, p=0.024) and DD (p=0.006) with age. Differences in ADC were observed between the 31-60 year-old age group and the >60 year-old age group (p=0.009) for b1,000, and between the<30 year-old age group and the 31-60 year-old age group (p=0.036) for b3,000. The DD in the >60 year-old age group was different from the rest. In the corpus callosum, there were significant differences between sexes in the DD of the genu (p=0.016). The DD was correlated with age in the right hippocampus (r=0.321, p=0.023).

CONCLUSIONS

Our data indicate greater stability in mean ADC values with b3000 during aging. It might be useful to analyze the ADC with a higher b in patients with neurodegenerative diseases.

High b-value diffusion (b = 3000 s/mm2) MR imaging in cerebral gliomas at 3T: visual and quantitative comparisons with b = 1000 s/mm2

BACKGROUND AND PURPOSE

High b-value diffusion-weighted imaging (DWI) provides different features not appreciated at lower b-value and have been recently studied in several clinical issues. The purpose of this study was to assess whether DWI at b = 3000 s/mm(2) is more useful in discriminating high-grade and low-grade gliomas than DWI at b = 1000 s/mm(2) at 3T.

MATERIALS AND METHODS

DWIs at both b = 1000 and 3000 s/mm(2) were performed at 3T in 62 patients, 49 high-grade gliomas (20 World Health Organization [WHO] grade III and 29 grade IV) and 13 low-grade gliomas (13 grade II). Visual assessments based on 5-point scaled evaluations, receiver operating characteristic (ROC) curve analysis, and quantitative assessment based on DWI signal intensity (SI) ratio (tumor SI/normal SI) and apparent diffusion coefficient (ADC) values were compared between DWIs at b = 1000 and 3000 s/mm(2).

RESULTS

By visual assessment, DWI at b = 3000 s/mm(2) showed more conspicuous hyperintensity in high-grade gliomas and hypointensity in low-grade gliomas than DWI at b = 1000 s/mm(2). Sensitivity and specificity at b = 3000 s/mm(2) were higher than at b = 1000 s/mm(2) (83.7%, 84.6% vs 69.4%, 76.9%, respectively). Quantitative assessments showed that mean SI ratio of high-grade gliomas was significantly higher than that of low-grade gliomas at both b-values. The mean ADC value of high-grade gliomas was significantly lower than that of low-grade gliomas at both b-values. The difference between the SI ratios of high-grade and low-grade gliomas was significantly larger at b = 3000 s/mm(2) than at b = 1000 s/mm(2).

CONCLUSION

DWI at b = 3000 s/mm(2) is more useful than DWI at b = 1000 s/mm(2) in terms of discriminating high-grade and low-grade gliomas at 3T.

ADC measurements at low and high b values: insight into normal brain structure with clinical DWI

PURPOSE

To demonstrate drop in brain ADC measurements from low to high b values; to evaluate the structural information provided based on those changes; and to discuss the anatomical reasons for ADC differences.

METHODS

Four cerebral ROI (precuneus-PRC, hippocampus-HIP, and the genu-GCC and splenium-SCC of the corpus callosum-CC) were drawn for ADC measurements with low (1000) and high (3000) b-value DWI in 50 normal subjects. ANOVA and Bonferroni correction tested ADC differences between areas, between both hemispheres, between GCC and SCC, and between b-value related ADC drop within areas. Pearson test evaluated dependence of interhemispheric and intercallosum ADC measurements obtained with the same b-value, dependence between areas of intrazonal drop, and the interhemispheric and intercallosum dependence of intrazonal drop.

RESULTS

ADCs differed between areas (P<.0001). Interhemispheric ADC only differed in PRC with low b-value (P<.027). No HIP asymmetries occurred regardless the b-value. ADC drop within PRC and HIP was similar but differed (P<.0001) from ADC drop within both CC ROI. ADC drop was also different between GCC and SCC (P<.0001). In PRC and HIP, ADC showed a significant interhemispheric and intrazonal dependence (P<.0001). There was no GCC to SCC ADC dependence. Intrazonal dependence in the CC was only significant in the SCC (P<.001). Interhemispheric dependence of intrazonal drop was significant (PRC P=.007; HIP P<.0001) but failed to reach significance in the CC.

CONCLUSION

Low and high b-value measurements show different diffusion behaviours within different tissues, especially in a highly anisotropic structure as the corpus callosum. This fact can provide valuable information about brain structure and different diffusion compartments in clinical DWI.

Radiological assessment of Creutzfeldt-Jakob disease

Creutzfeldt-Jakob disease is a rare fatal neurodegenerative disorder, characterized by rapidly progressive dementia and neurological signs. There is a need for early and accurate clinical diagnosis in order to exclude any treatable disorder. Additionally, it is of public interest to differentiate the sporadic form of the disease from the variant CJD type (vCJD), which is probably transmitted from cattle infected with bovine spongiform encephalopathy (BSE). High signal in the striatum on T2-weighted, FLAIR and diffusion weighted (DW) MRI as well as cortical high signal in FLAIR and DW MRI are the classical findings in sCJD. The "pulvinar sign", defined as high signal in the pulvinar thalami that is brighter than potential additional high signal in the basal ganglia, is considered pathognomonic for vCJD.

Diffusion-weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response

Diffusion-weighted magnetic resonance (MR) imaging and perfusion MR imaging are advanced techniques that provide information not available from conventional MR imaging. In particular, these techniques have a number of applications with regard to characterization of tumors and assessment of tumor response to therapy. In this review, the authors describe the fundamental principles of diffusion-weighted and perfusion MR imaging and provide an overview of the ways in which these techniques are being used to characterize tumors by helping distinguish tumor types, assess tumor grade, and attempt to determine tumor margins. In addition, the role of these techniques for evaluating response to tumor therapy is outlined.

Quantitative diffusion tensor MR imaging of the brain: field strength related variance of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) scalars

The objectives were to study the "impact" of the magnetic field strength on diffusion tensor imaging (DTI) metrics and also to determine whether magnetic-field-related differences in T2-relaxation times of brain tissue influence DTI measurements. DTI was performed on 12 healthy volunteers at 1.5 and 3.0 Tesla (within 2 h) using identical DTI scan parameters. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured at multiple gray and white matter locations. ADC and FA values were compared and analyzed for statistically significant differences. In addition, DTI measurements were performed at different echo times (TE) for both field strengths. ADC values for gray and white matter were statistically significantly lower at 3.0 Tesla compared with 1.5 Tesla (% change between -1.94% and -9.79%). FA values were statistically significantly higher at 3.0 Tesla compared with 1.5 Tesla (% change between +4.04 and 11.15%). ADC and FA values are not significantly different for TE=91 ms and TE=125 ms. Thus, ADC and FA values vary with the used field strength. Comparative clinical studies using ADC or FA values should consequently compare ADC or FA results with normative ADC or FA values that have been determined for the field strength used.

Early Detection of Subacute Sclerosing Panencephalitis by High b-Value Diffusion-Weighted Imaging

The authors report a case of subacute sclerosing panencephalitis in which the diagnosis was suggested by high b-value diffusion-weighted imaging (DWI) findings. The signal abnormalities were located asymmetrically at bilateral cerebral corticosubcortical regions. High b-value DWI showed these signal abnormalities as marked hyperintensity with decreased apparent diffusion coefficient values. The signal abnormalities were difficult to identify on other magnetic resonance imaging sequences, including routine DWI. High b-value DWI could be valuable for earlier detection of subacute sclerosing panencephalitis.

Normal white matter development from infancy to adulthood: comparing diffusion tensor and high b value diffusion weighted MR images

PURPOSE

To evaluate the sensitivity of high b value diffusion weight magnetic resonance imaging (DWI) in detecting normal white matter maturation, compare it to conventional diffusion tensor imaging (DTI), and to obtain normative quantitative data using this method.

MATERIALS AND METHODS

High b value DWI (b(max) = 6000 sec/mm(2)) using q-space analysis and conventional DTI (b = 1000 sec/mm(2)) were performed on 36 healthy subjects aged 4 months to 23 years. Fractional-anisotropy (FA), apparent-displacement, and apparent-probability values were measured in all slices and in six regions of interest (ROIs) of large fiber tracks. Values were correlated with each other and with age using regression analysis.

RESULTS

FA, displacement, and probability indices from all slices were highly correlated with each other (r > 0.87, P < 0.0001) and with age (r > 0.82, P < 0.0001). All age-related changes in the six pre-determined ROIs were best fitted by mono-exponential functions. Changes in the splenium extended to a later age when compared with the genu of the corpus-callosum, while the centrum semi-ovale demonstrated the latest changes with age.

CONCLUSIONS

High b-value DWI and DTI showed changes in white matter from infancy through adulthood. However, high b-value detects a signal that is likely to originate mainly from the intra-axonal water population, and thus may represent different aspects of development and different sensitivity to pathology.

How does DWI correlate with white matter structures?

Diffusion-weighted MRI (DWI) is widely used to characterize brain white matter (WM), particularly through the use of diffusion tensor imaging (DTI). In this study the spatial characteristics of DWI in WM of cat visual cortex were investigated at 9.4T at very high resolution. It is shown that the spatial extent of the WM tract as measured from the DWI images depends highly on the b-value. In particular, when the diffusion gradient is applied perpendicular to the main direction of the fiber tract, the estimated thickness of the tract at the commonly used b-value of 1000 s/mm2 exceeds by 50% the thickness as it appears on a T2-weighted image. Only at b-values greater than 6000 s/mm2 does the thickness of the tract approach the thickness characterized by the T2-weighted image and that observed on histological slices of the same area. Further analysis of these results indicates that the choice of b-value of 1000 s/mm2 may not be optimal for the demarcation of anisotropic WM structures. DWI at high b-value may contain spatial information that is more specific to WM tracts.