Repeatability and variation of region-of-interest methods using quantitative diffusion tensor MR imaging of the brain

Comparison of T1-weighted landmark placement and ROI transfer onto diffusion-weighted EPI sequences for targeted tractography tasks in the optic nerve

Diffusion-based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert-placed, high-resolution T1-weighted ROI-data transfer onto lower spatial resolution diffusion-weighted images. Slab volumes from 20 volunteers were acquired and preprocessed including distortion bias correction and artifact reduction. Constrained spherical deconvolution was used to generate a directional diffusion information grid (fibre orientation distribution-model [FOD]). Three neuroradiologists marked landmarks on both diffusion imaging variants and structural datasets. Structural ROI information (volumetric interpolated breath-hold sequence [VIBE]) was respectively registered (linear with 6/12 degrees of freedom [DOF]) onto single-shot EPI (ss-EPI) and readout-segmented EPI (rs-EPI) volumes, respectively. All eight ROI/FOD-combinations were compared in a targeted tractography task of the optic nerve pathway. Inter-rater reliability for placed ROIs among experts was highest in VIBE images (lower confidence interval 0.84 to 0.97, mean 0.91) and lower in both ss-EPI (0.61 to 0.95, mean 0.79) and rs-EPI (0.59 to 0.86, mean 0.70). Tractography success rate based on streamline selection performance was highest in VIBE-drawn ROIs registered (6-DOF) onto rs-EPI FOD (70.0% over 5%-threshold, capped to failed ratio 39/16) followed by both 12-DOF-registered (67.5%; 41/16) and nonregistered VIBE (67.5%; 40/23). On ss-EPI FOD, VIBE-ROI-datasets obtained fewer streamlines overall with each at 55.0% above 5%-threshold and with lower capped to failed ratio (6-DOF: 35/36; 12-DOF: 34/34, nonregistered 33/36). The combination of VIBE-placed ROIs (highest inter-rater reliability) with 6-DOF registration onto rs-EPI targets (best streamline selection performance) is most suitable for white matter template generation required in group studies.

A diffusion tensor imaging white matter atlas of the domestic canine brain

There is increasing reliance on magnetic resonance imaging (MRI) techniques in both research and clinical settings. However, few standardized methods exist to permit comparative studies of brain pathology and function. To help facilitate these studies, we have created a detailed, MRI-based white matter atlas of the canine brain using diffusion tensor imaging. This technique, which relies on the movement properties of water, permits the creation of a three-dimensional diffusivity map of white matter brain regions that can be used to predict major axonal tracts. To generate an atlas of white matter tracts, thirty neurologically and clinically normal dogs underwent MRI imaging under anesthesia. High-resolution, three-dimensional T1-weighted sequences were collected and averaged to create a population average template. Diffusion-weighted imaging sequences were collected and used to generate diffusivity maps, which were then registered to the T1-weighted template. Using these diffusivity maps, individual white matter tracts-including association, projection, commissural, brainstem, olfactory, and cerebellar tracts-were identified with reference to previous canine brain atlas sources. To enable the use of this atlas, we created downloadable overlay files for each white matter tract identified using manual segmentation software. In addition, using diffusion tensor imaging tractography, we created tract files to delineate major projection pathways. This comprehensive white matter atlas serves as a standard reference to aid in the interpretation of quantitative changes in brain structure and function in clinical and research settings.

Inter-software reliability and agreement for follicular and luteal morphometric and echotextural ultrasonographic parameters in beef cattle

This study aimed to compare the inter-software and inter-observer reliability and agreement for the assessment of follicular and luteal morphometry and echotexture parameters in beef crossbreed females (3/8 Bos taurus indicus and 5/8 Bos taurus taurus). B-mode and color Doppler ultrasonographic ovarian images were obtained at specific time points of estradiol-progesterone-based protocols for timed artificial insemination (TAI). Sonograms were analyzed by two observers using a licensed (IASP1) and an open access (IASP2) software package. A total of 292 snap-shot sonograms were analyzed for morphometric parameters and 504 for echotexture parameters. inter-software reliability was judged moderate to excellent (ICC or CCC=0.73-0.98), whereas inter-observer reliability for morphometric parameters was deemed good to excellent (ICC or CCC=0.82-0.98). A small percentage (up to 10.95 %) of measured parameters fell outside the limits of inter-software and inter-observer agreement. For echotexture parameters, inter-software reliability varied widely (ICC or CCC=0.16-0.95) based on the size of regions of interest (ROI), while inter-observer reliability ranged from moderate to excellent (ICC or CCC= 0.71-0.97). The highest inter-software reliability for pixel value and heterogeneity value was observed for the corpus luteum (ICCs=0.81-0.95; P>0.05), followed by the peripheral follicular antrum (ICCs=0.75-0.78; P<0.05). However, lower reliability was determined for the follicular wall (ICCs=0.08-0.33; P<0.0001) and perifollicular stroma (ICCs=0.16-0.46; P<0.05). In conclusion, both software packages showed high reproducibility for morphometric measurements, while echotexture measurements were more challenging to replicate based on ROI sizes. Caution is advised when selecting ROI sizes for echotexture measurements in bovine ovaries.

Assessing the variability and correlation between SUV and ADC parameters of head and neck cancers derived from simultaneous PET/MRI: A single-center study

OBJECTIVE

Intratumoral heterogeneity is associated with poor outcomes in head and neck cancer (HNC) patients owing to chemoradiotherapy resistance. [¹⁸ F]-FDG positron emission tomography (PET) / Magnetic Resonance Imaging (MRI) provides spatial information about tumor mass, allowing intratumor heterogeneity assessment through histogram analysis. However, variability in quantitative PET/MRI parameter measurements could influence their reliability in assessing patient prognosis. Therefore, to use standardized uptake value (SUV) and apparent diffusion coefficient (ADC) parameters for assessing tumor response, this study aimed to measure SUV and ADC's variability and assess their relationship in HNC.

METHODS

First, ADC variability was measured in an in-house diffusion phantom and in five healthy volunteers. The SUV variability was only measured with the NEMA phantom using a clinical imaging protocol. Furthermore, simultaneous PET/MRI data of 11 HNC patients were retrospectively collected from the National Cyclotron and PET center in Chulabhorn Hospital. Tumor contours were manually drawn from PET images by an experienced nuclear medicine radiologist before tumor volume segmentation. Next, SUV and ADC's histogram were used to extract statistic variables of ADC and SUV: mean, median, min, max, skewness, kurtosis, and 5^th , 10^th , 25^th , 50^th , 75^th , 90^th , and 95^th percentiles. Finally, the correlation between the statistic variables of ADC and SUV, as well as Metabolic Tumor volume and Total Lesion Glycolysis parameters was assessed using Pearson's correlation.

RESULTS

This pilot study showed that both parameters' maximum coefficient of variation was 13.9% and 9.8% in the phantom and in vivo, respectively. Furthermore, we found a strong and negative correlation between SUV_max and ADV_med (r = -0.75, P = 0.01).

CONCLUSION

The SUV and ADC obtained by simultaneous PET/MRI can be potentially used as an imaging biomarker for assessing intratumoral heterogeneity in patients with HNC. The low variability and relationship between SUV and ADC could allow multimodal prediction of tumor response in future studies.

Current and Future Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a debilitating autoimmune disorder. Currently, there is a lack of effective treatment for the progressive form of MS, partly due to insensitive readout for neurodegeneration. The recent development of sensitive assays for neurofilament light chain (NfL) has made it a potential new biomarker in predicting MS disease activity and progression, providing an additional readout in clinical trials. However, NfL is elevated in other neurodegenerative disorders besides MS, and, furthermore, it is also confounded by age, body mass index (BMI), and blood volume. Additionally, there is considerable overlap in the range of serum NfL (sNfL) levels compared to healthy controls. These confounders demonstrate the limitations of using solely NfL as a marker to monitor disease activity in MS patients. Other blood and cerebrospinal fluid (CSF) biomarkers of axonal damage, neuronal damage, glial dysfunction, demyelination, and inflammation have been studied as actionable biomarkers for MS and have provided insight into the pathology underlying the disease process of MS. However, these other biomarkers may be plagued with similar issues as NfL. Using biomarkers of a bioinformatic approach that includes cellular studies, micro-RNAs (miRNAs), extracellular vesicles (EVs), metabolomics, metabolites and the microbiome may prove to be useful in developing a more comprehensive panel that addresses the limitations of using a single biomarker. Therefore, more research with recent technological and statistical approaches is needed to identify novel and useful diagnostic and prognostic biomarker tools in MS.

Unveiling the phantom: What neuroimaging has taught us about phantom limb pain

Phantom limb pain (PLP) is a complicated condition with diverse clinical challenges. It consists of pain perception of a previously amputated limb. The exact pain mechanism is disputed and includes mechanisms involving cerebral, peripheral, and spinal origins. Such controversy limits researchers' and clinicians' ability to develop consistent therapeutics or management. Neuroimaging is an essential tool that can address this problem. This review explores diffusion tensor imaging, functional magnetic resonance imaging, electroencephalography, and magnetoencephalography in the context of PLP. These imaging modalities have distinct mechanisms, implications, applications, and limitations. Diffusion tensor imaging can outline structural changes and has surgical applications. Functional magnetic resonance imaging captures functional changes with spatial resolution and has therapeutic applications. Electroencephalography and magnetoencephalography can identify functional changes with a strong temporal resolution. Each imaging technique provides a unique perspective and they can be used in concert to reveal the true nature of PLP. Furthermore, researchers can utilize the respective strengths of each neuroimaging technique to support the development of innovative therapies. PLP exemplifies how neuroimaging and clinical management are intricately connected. This review can assist clinicians and researchers seeking a foundation for applications and understanding the limitations of neuroimaging techniques in the context of PLP.

Reproducibility of diffusion tensor image analysis along the perivascular space (DTI-ALPS) for evaluating interstitial fluid diffusivity and glymphatic function: CHanges in Alps index on Multiple conditiON acquIsition eXperiment (CHAMONIX) study

PURPOSE

The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method was developed to evaluate the brain's glymphatic function or interstitial fluid dynamics. This study aimed to evaluate the reproducibility of the DTI-ALPS method and the effect of modifications in the imaging method and data evaluation.

MATERIALS AND METHODS

Seven healthy volunteers were enrolled in this study. Image acquisition was performed for this test-retest study using a fixed imaging sequence and modified imaging methods which included the placement of region of interest (ROI), imaging plane, head position, averaging, number of motion-proving gradients, echo time (TE), and a different scanner. The ALPS-index values were evaluated for the change of conditions listed above.

RESULTS

This test-retest study by a fixed imaging sequence showed very high reproducibility (intraclass coefficient = 0.828) for the ALPS-index value. The bilateral ROI placement showed higher reproducibility. The number of averaging and the difference of the scanner did not influence the ALPS-index values. However, modification of the imaging plane and head position impaired reproducibility, and the number of motion-proving gradients affected the ALPS-index value. The ALPS-index values from 12-axis DTI and 3-axis diffusion-weighted image (DWI) showed good correlation (r = 0.86). Also, a shorter TE resulted in a larger value of the ALPS-index.

CONCLUSION

ALPS index was robust under the fixed imaging method even when different scanners were used. ALPS index was influenced by the imaging plane, the number of motion-proving gradient axes, and TE in the imaging sequence. These factors should be uniformed in the planning ALPS method studies. The possibility to develop a 3-axis DWI-ALPS method using three axes of the motion-proving gradient was also suggested.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at b values ranging from 1000 sec/mm² to 5000 sec/mm² in patients with prostate cancer. Materials and Methods In this retrospective study, images of the prostate obtained at DWI with a b value of 0 sec/mm², DWI with a b value of 1000 sec/mm² (DWI₁₀₀₀), DWI with a b value of 3000 sec/mm² (DWI₃₀₀₀), and DWI with a b value of 5000 sec/mm² (DWI₅₀₀₀) from consecutive patients with biopsy-proven cancer from January to June 2020 were reconstructed with and without DLR. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) from region-of-interest analysis and qualitatively assessed using a five-point visual scoring system (1 [very poor] to 5 [excellent]) for each high-b-value DWI sequence with and without DLR. The SNR, CNR, and visual score for DWI with and without DLR were compared with the paired t test and the Wilcoxon signed rank test with Bonferroni correction, respectively. Apparent diffusion coefficients (ADCs) from DWI with and without DLR were also compared with the paired t test with Bonferroni correction. Results A total of 60 patients (mean age, 67 years; age range, 49-79 years) were analyzed. DWI with DLR showed significantly higher SNRs and CNRs than DWI without DLR (P < .001); for example, with DWI₁₀₀₀ the mean SNR was 38.7 ± 0.6 versus 17.8 ± 0.6, respectively (P < .001), and the mean CNR was 18.4 ± 5.6 versus 7.4 ± 5.6, respectively (P < .001). DWI with DLR also demonstrated higher qualitative image quality than DWI without DLR (mean score: 4.8 ± 0.4 vs 4.0 ± 0.7, respectively, with DWI₁₀₀₀ [P = .001], 3.8 ± 0.7 vs 3.0 ± 0.8 with DWI₃₀₀₀ [P = .002], and 3.1 ± 0.8 vs 2.0 ± 0.9 with DWI₅₀₀₀ [P < .001]). ADCs derived with and without DLR did not differ substantially (P > .99). Conclusion Deep learning reconstruction improves the image quality of diffusion-weighted MRI scans of prostate cancer with no impact on apparent diffusion coefficient quantitation with a 3.0-T MRI system. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Investigating Optimal Echo Times for Quantitative Susceptibility Mapping of Basal Ganglia Nuclei in the Healthy Brain

BACKGROUND

Quantitative susceptibility mapping (QSM) technique had been used to measure the magnetic susceptibility of brain tissue in clinical practice. However, QSM presented echo-time (TE) dependence, and an appropriate number of echo-times (nTEs) for QSM became more important to obtain the reliable susceptibility value.

OBJECTIVE

The aim of the study was to explore the optimal nTEs for quantitative susceptibility mapping (QSM) measurements of basal ganglia nuclei in the healthy brain.

METHODS

3D multi-echo enhanced gradient recalled echo T2 star weighted angiography (ESWAN) sequence was acquired on a 3.0T MR scanner for QSM analysis. Regions of interests (ROIs) were drawn along the margin of the head of the caudate nucleus (HCN), putamen (Pu) and globus pallidus (GP). The mean susceptibility value and standard deviation of the ROIs were derived from the pixels within each region.

RESULTS

CV analysis demonstrated that TE6, TE8 and TE14 ESWAN sequences presented consistent lower CV value (< 1) for QSM measure of HCN, Pu and GP. ANOVA identified that susceptibility value showed no significant difference between TE6 and TE8 in HCN, Pu and GP (P > 0.05). ICC analysis demonstrated that the susceptibility value of TE6-TE8 had the highest ICC value as compared with TE6-TE14 and TE8-TE14 in HCN, Pu and GP. Combined with the timeefficiency of MRI scanning, TE6 sequence could not only provide the reliable QSM measurement but also short imaging time.

CONCLUSION

The current study identified that the optimal nTEs of ESWAN were 6 TEs (2.9ms ~ 80.9ms) for QSM measurement of basal ganglia nuclei in the healthy brain.

Reliability of the freehand region-of-interest method in quantitative cerebral diffusion tensor imaging

Background

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique used for evaluating changes in the white matter in brain parenchyma. The reliability of quantitative DTI analysis is influenced by several factors, such as the imaging protocol, pre-processing and post-processing methods, and selected diffusion parameters. The region-of-interest (ROI) method is most widely used of the post-processing methods because it is found in commercial software. The focus of our research was to study the reliability of the freehand ROI method using various intra- and inter-observer analyses.

Methods

This study included 40 neurologically healthy participants who underwent diffusion MRI of the brain with a 3 T scanner. The measurements were performed at nine different anatomical locations using a freehand ROI method. The data extracted from the ROIs included the regional mean values, intra- and inter-observer variability and reliability. The used DTI parameters were fractional anisotropy (FA), the apparent diffusion coefficient (ADC), and axial (AD) and radial (RD) diffusivity.

Results

The average intra-class correlation coefficient (ICC) of the intra-observer was found to be 0.9 (excellent). The single ICC results were excellent (> 0.8) or adequate (> 0.69) in eight out of the nine regions in terms of FA and ADC. The most reliable results were found in the frontobasal regions. Significant differences between age groups were also found in the frontobasal regions. Specifically, the FA and AD values were significantly higher and the RD values lower in the youngest age group (18–30 years) compared to the other age groups.

Conclusions

The quantitative freehand ROI method can be considered highly reliable for the average ICC and mostly adequate for the single ICC. The freehand method is suitable for research work with a well-experienced observer. Measurements should be performed at least twice in the same region to ensure that the results are sufficiently reliable. In our study, reliability was slightly undermined by artifacts in some regions such as the cerebral peduncle and centrum semiovale. From a clinical point of view, the results are most reliable in adults under the age of 30, when age-related changes in brain white matter have not yet occurred.

Potential Biomarkers Associated with Multiple Sclerosis Pathology

Multiple sclerosis (MS) is a complex disease of the central nervous system (CNS) that involves an intricate and aberrant interaction of immune cells leading to inflammation, demyelination, and neurodegeneration. Due to the heterogeneity of clinical subtypes, their diagnosis becomes challenging and the best treatment cannot be easily provided to patients. Biomarkers have been used to simplify the diagnosis and prognosis of MS, as well as to evaluate the results of clinical treatments. In recent years, research on biomarkers has advanced rapidly due to their ability to be easily and promptly measured, their specificity, and their reproducibility. Biomarkers are classified into several categories depending on whether they address personal or predictive susceptibility, diagnosis, prognosis, disease activity, or response to treatment in different clinical courses of MS. The identified members indicate a variety of pathological processes of MS, such as neuroaxonal damage, gliosis, demyelination, progression of disability, and remyelination, among others. The present review analyzes biomarkers in cerebrospinal fluid (CSF) and blood serum, the most promising imaging biomarkers used in clinical practice. Furthermore, it aims to shed light on the criteria and challenges that a biomarker must face to be considered as a standard in daily clinical practice.

Clinical application of diffusion tensor tractography to postoperative C5 palsy

STUDY DESIGN

Diagnostic study.

OBJECTIVE

Although C5 palsy is a well-known potential complication after cervical procedure, the exact pathophysiology remains uncertain. Diffusion tensor tractography (DTT) has recently been proposed as a useful tool to examine quantitatively and non-invasively the pathology of spinal cord disorders. The purpose of this study is to determine the clinical interest of DTT in patients with C5 palsy after cervical laminoplasty.

SETTING

Single university hospital.

METHODS

Five patients with C5 palsy out of 108 patients after cervical laminoplasty were subjected to DTT using a 1.5 Tesla magnetic resonance imaging in our hospital between 2010 and 2012. For the tractography, two regions of interest (ROI) were placed at the C5 segmental level and the bilateral C4/5 intervertebral foramen level.

RESULTS

The postoperative number of tract fibers at the C5 segmental spinal cord level was significantly increased compared to the preoperative number, despite the C5 palsy. Analyses of two ROIs (at the C5 segmental level and the C4/5 intervertebral foramen level) showed that the number of tract fibers at the palsy side was significantly decreased compared to the intact side. Furthermore, in the patient who spontaneously recovered from C5 palsy within postoperative 6 months, a gradual augmentation of tract fibers was identified at the palsy side.

CONCLUSIONS

Our findings suggest that DTT can document C5 palsy in detail, as the anatomical region between C5 segmental level and C4/5 intervertebral foramen level was potentially damaged in patients with C5 palsy after laminoplasty.

Imaging characteristics of H3 K27M histone-mutant diffuse midline glioma in teenagers and adults

Background

To assess anatomical and quantitative diffusion-weighted MR imaging features in a recently classified lethal neoplasm, H3 K27M histone-mutant diffuse midline glioma [World Health Organization (WHO) IV].

Methods

Fifteen untreated gliomas in teenagers and adults (median age 19, range, 14-64) with confirmed H3 K27M histone-mutant genotype were analysed at a national referral centre. Morphological characteristics including tumour epicentre(s), T2/FLAIR and Gadolinium enhancement patterns, calcification, haemorrhage and cyst formation were recorded. Multiple apparent diffusion coefficient (ADC_min, ADC_mean) regions of interest were sited in solid tumour and normal appearing white matter (ADC_NAWM) using post-processing software (Olea Sphere v2.3, Olea Medical). ADC histogram data (2^nd, 5^th, 10^th percentile, median, mean, kurtosis, skewness) were calculated from volumetric tumour segmentations and tested against the regions of interest (ROI) data (Wilcoxon signed rank test).

Results

The median interval from imaging to tissue diagnosis was 9 (range, 0-74) days. The structural MR imaging findings varied between individuals and within tumours, often featuring signal heterogeneity on all MR sequences. All gliomas demonstrated contact with the brain midline, and 67% exhibited rim-enhancing necrosis. The mean ROI ADC_min value was 0.84 (±0.15 standard deviation, SD) ×10^-3 mm²/s. In the largest tumour cross-section (excluding necrosis), an average ADC_mean value of 1.12 (±0.25)×10^-3 mm²/s was observed. The mean ADC_min/NAWM ratio was 1.097 (±0.149), and the mean ADC_mean/NAWM ratio measured 1.466 (±0.299). With the exception of the 2^nd centile, no statistical difference was observed between the regional and histogram derived ADC results.

Conclusions

H3 K27M-mutant gliomas demonstrate variable morphology and diffusivity, commonly featuring moderately low ADC values in solid tumour. Regional ADC measurements appeared representative of volumetric histogram data in this study.

Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: Comparison of its utility in routine clinical practice

PURPOSE

To directly compare the capability of compressed sensing (CS) and parallel imaging (PI) accelerated T2 FSE (Fast Spin Echo) sequence with PI for head and neck MR imaging.

METHODS

Thirty consecutive patients with various head and neck diseases (15 men and 15 women, mean age 53 ± 22 years) underwent MR imaging by PI with CS and by PI. Reduction factors were as follows: PI with CS, 3 and PI, 1.5. Examination times for PI with CS and PI were all recorded. For quantitative image quality assessment, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. For qualitative assessment, two investigators assessed overall image quality, artifacts and diagnostic confidence level using a 5-point scoring system, and final scores were determined by consensus of two readers. Mean examination time and all indexes were compared by means of paired t-test and Wilcoxon signed-rank test. Inter-observer agreement for each qualitative index was assessed in terms of kappa statistics.

RESULTS

Mean examination time for PI with CS (83.5 ± 11.0 s) was significantly shorter than that for PI (173.0 ± 54.4 s, p < 0.0001). SNR and CNR of PI with CS were significantly better than those with PI (mean SNR; 11.2 ± 3.6 vs 8.9 ± 2.6, median of CNR; 7.4 vs. 6.1, p < 0.0001). All inter-observer agreements were assessed as significant and substantial (0.62 < κ < 0.81).

CONCLUSION

PI with CS accelerated T2 weighted sequence performs equally well or even slightly better than its PI accelerated, conventional counterpart at reduced scan times in the context of head and neck MR imaging.

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

PURPOSE

To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI.

METHOD

Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test.

RESULTS

Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003).

CONCLUSION

Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.

Strategic white matter injury associated with long-term information processing speed deficits in mild traumatic brain injury

Deficits in information processing speed (IPS) are among the earliest and most prominent cognitive manifestations in mild traumatic brain injury (mTBI). We investigated the impact of white matter fiber location on IPS outcome in an individual basis assessment. A total of 112 acute mild TBI with all CT negative underwent brain DTI and blood sampling for inflammation cytokines within 7 days postinjury and 72 age- and sex matched healthy controls with same assessments were enrolled. IPS outcome was assessed by the trail making test at 6-12 month postinjury in mild TBI. Fractional anisotropy (FA) features were extracted using a novel lesion-load analytical strategy to capture spatially heterogeneous white matter injuries and minimize implicit assumptions of uniform injury across diverse clinical presentations. Acute mild TBI exhibited a general pattern of increased and decreased FA in specific white matter tracts. The power of acute FA measures to identify patients developing IPS deficits with 92% accuracy and further improved to 96% accuracy by adding inflammation cytokines. The classifiers predicted individual's IPS and working memory ratings (r = .74 and .80, respectively, p < .001). The thalamo-cortical circuits and commissural tracts projecting or connecting frontal regions became important predictors. This prognostic model was also verified by an independent replicate sample. Our findings highlighted damage to frontal interhemispheric and thalamic projection fiber tracts harboring frontal-subcortical neuronal circuits as a predictor for processing speed performance in mild TBI.

Creation of a novel trigeminal tractography atlas for automated trigeminal nerve identification

Diffusion MRI (dMRI) tractography has been successfully used to study the trigeminal nerves (TGNs) in many clinical and research applications. Currently, identification of the TGN in tractography data requires expert nerve selection using manually drawn regions of interest (ROIs), which is prone to inter-observer variability, time-consuming and carries high clinical and labor costs. To overcome these issues, we propose to create a novel anatomically curated TGN tractography atlas that enables automated identification of the TGN from dMRI tractography. In this paper, we first illustrate the creation of a trigeminal tractography atlas. Leveraging a well-established computational pipeline and expert neuroanatomical knowledge, we generate a data-driven TGN fiber clustering atlas using tractography data from 50 subjects from the Human Connectome Project. Then, we demonstrate the application of the proposed atlas for automated TGN identification in new subjects, without relying on expert ROI placement. Quantitative and visual experiments are performed with comparison to expert TGN identification using dMRI data from two different acquisition sites. We show highly comparable results between the automatically and manually identified TGNs in terms of spatial overlap and visualization, while our proposed method has several advantages. First, our method performs automated TGN identification, and thus it provides an efficient tool to reduce expert labor costs and inter-operator bias relative to expert manual selection. Second, our method is robust to potential imaging artifacts and/or noise that can prevent successful manual ROI placement for TGN selection and hence yields a higher successful TGN identification rate.

Pre-operative MRI measurements versus anthropometric data: Which is more accurate in predicting 4-stranded hamstring graft size in anterior cruciate ligament reconstruction?

Background/objective

Graft diameter has been shown to play an important role in anterior cruciate ligament (ACL) autograft failure rates. The roles of pre-operative MRI measurement of graft size and anthropometric data have been studied in the prediction of hamstring graft size. Pre-operative knowledge of hamstring graft diameter allows surgeons to perform better surgical planning and provides an opportunity to discuss with patients on alternative graft options such as allografts should the need arises. The purpose of this study was to compare the accuracy of pre-operative anthropometric data and MRI measurements in the prediction of 4-stranded hamstring autograft size in anterior cruciate ligament reconstruction.

Method

This was a cohort study involving 141 subjects (115 males and 26 females) who underwent a single bundle ACL reconstruction utilising a 4-stranded hamstring graft by a single surgeon from 2008 to 2012. Pre-operatively, the height, weight, body mass index (BMI), age, gender and smoking status was recorded. The MRI scans used for diagnosis were utilized to measure the gracilis (GT) and semi-tendinosus (ST) cross sectional area (CSA).

Result

We found the strongest correlation between Combined (ST + GT) CSA and intra-operative graft size (r = 0.596, p < 0.001). This was followed by ST CSA (r = 0.570,p < 0.001), Body surface area (r = 0.507,p < 0.001), and GT CSA (r = 0.460,p < 0.001). No significant correlation was found between 2 anthropometric data (Age and BMI). There was also no significant difference between different strengths of MRIs (1.5T vs 3.0T) in determining the intra-operative graft size (p = 0.438).

Conclusion

We conclude that pre-operative MRI is superior to anthropometric variables in predicting the size of 4-stranded hamstring autografts used in ACL reconstruction.

A Three-Dimensional Statistical Volume Element for Histology Informed Micromechanical Modeling of Brain White Matter

This study presents a novel statistical volume element (SVE) for micromechanical modeling of the white matter structures, with histology-informed randomized distribution of axonal tracts within the extracellular matrix. The model was constructed based on the probability distribution functions obtained from the results of diffusion tensor imaging as well as the histological observations of scanning electron micrograph, at two structures of white matter susceptible to traumatic brain injury, i.e. corpus callosum and corona radiata. A simplistic representative volume element (RVE) with symmetrical arrangement of fully alligned axonal fibers was also created as a reference for comparison. A parametric study was conducted to find the optimum grid and edge size which ensured the periodicity and ergodicity of the SVE and RVE models. A multi-objective evolutionary optimization procedure was used to find the hyperelastic and viscoelastic material constants of the constituents, based on the experimentally reported responses of corpus callosum to axonal and transverse loadings. The optimal material properties were then used to predict the homogenized and localized responses of corpus callosum and corona radiata. The results indicated similar homogenized responses of the SVE and RVE under quasi-static extension, which were in good agreement with the experimental data. Under shear strain, however, the models exhibited different behaviors, with the SVE model showing much closer response to the experimental observations. Moreover, the SVE model displayed a significantly better agreement with the reports of the experiments at high strain rates. The results suggest that the randomized fiber architecture has a great influence on the validity of the micromechanical models of white matter, with a distinguished impact on the model's response to shear deformation and high strain rates. Moreover, it can provide a more detailed presentation of the localized responses of the tissue substructures, including the stress concentrations around the low caliber axonal tracts, which is critical for studying the axonal injury mechanisms.

Diffusion tensor imaging and disability progression in multiple sclerosis: A 4-year follow-up study

OBJECTIVES

Diffusion tensor imaging (DTI) is sensitive technique to detect widespread changes in water diffusivity in the normal-appearing white matter (NAWM) that appears unaffected in conventional magnetic resonance imaging. We aimed to investigate the prognostic value and stability of DTI indices in the NAWM of the brain in an assessment of disability progression in patients with a relapsing-onset multiple sclerosis (MS).

METHODS

Forty-six MS patients were studied for DTI indices (fractional anisotropy (FA), mean diffusivity (MD), radial (RD), and axial (AD) diffusivity) in the NAWM of the corpus callosum (CC) and the internal capsule at baseline and at 1 year after. DTI analysis for 10 healthy controls was also performed at baseline. Simultaneously, focal brain lesion volume and atrophy measurements were done at baseline for MS patients. Associations between DTI indices, volumetric measurements, and disability progression over 4 years were studied by multivariate logistic regression analysis.

RESULTS

At baseline, most DTI metrics differed significantly between MS patients and healthy controls. There was tendency for associations between baseline DTI indices in the CC and disability progression (p < 0.05). Changes in DTI indices over 1 year were observed only in the CC (p < 0.008), and those changes were not found to predict clinical worsening over 4 years. Clear-cut association with disability progression was not detected for baseline volumetric measurements.

CONCLUSION

Aberrant diffusivity measures in the NAWM of the CC may provide additional information for individual disability progression over 4 years in MS with the relapsing-onset disease. CC may be a good target for DTI measurements in monitoring disease activity in MS, and more studies are needed to assess the related prognostic potential.

Microstructural White Matter Abnormalities in the Dorsal Cingulum of Adolescents with IBS

Alterations in fractional anisotropy (FA) have been considered to reflect microstructural white matter (WM) changes in disease conditions; however, no study to date has examined WM changes using diffusion tensor imaging (DTI) in adolescents with irritable bowel syndrome (IBS). The objective of the present study was two-fold: (1) to determine whether differences in FA, and other non-FA metrics, were present in adolescents with IBS compared to healthy controls using whole-brain, region of interest (ROI)-restricted tract-based spatial statistics (TBSS) and canonical ROI DTI analyses for the cingulum bundle, and (2) to determine whether these metrics were related to clinical measures of disease duration and pain intensity in the IBS group. A total of 16 adolescents with a Rome III diagnosis of IBS (females = 12; mean age = 16.29, age range: 11.96-18.5 years) and 16 age- and gender-matched healthy controls (females = 12; mean age = 16.24; age range: 11.71-20.32 years) participated in this study. Diffusion-weighted images were acquired using a Siemens 3-T Trio Tim Syngo MRI scanner with a 32-channel head coil. The ROI-restricted TBSS and canonical ROI-based DTI analyses revealed that adolescents with IBS showed decreased FA in the right dorsal cingulum bundle compared to controls. No relationship between FA and disease severity measures was found. Microstructural WM alterations in the right dorsal cingulum bundle in adolescents with IBS may reflect a premorbid brain state or the emergence of a disease-driven process that results from complex changes in pain- and affect-related processing via spinothalamic and corticolimbic pathways.

Analysis of variability of fractional anisotropy values at 3T using a novel diffusion tensor imaging phantom

We employed a novel diffusion tensor imaging phantom to study intra- and interscanner reproducibility on two 3T magnetic resonance (MR) scanners. Using a phantom containing thousands of hollow micron-size tubes in complex arrays, we performed two experiments using a b value of 1000 s/ms² on two Siemens 3T Trio scanners. First, we performed 12-direction scans. Second, on one scanner, we performed two 64-direction protocols with different repetition times (TRs). We used a one-way analysis of variance to calculate differences between scanners and the Mann-Whitney U test to assess differences between 12-direction and 64-direction data. We calculated the coefficient of variation (CoV) for intrascanner and interscanner data. For 12-direction protocols, mean fractional anisotropy (FA) was 0.3003 for Scanner 1 (four scans) and 0.3094 for Scanner 2 (three scans). Lowest FA value on Scanner 1 was 2.56 standard deviations below the mean of Scanner 2. For 64-direction scans, mean FA was 0.2640 for 4000 ms TR and 0.2582 for 13,200 ms TR scans. For 12-direction scans, within-scanner CoV was 0.0326 for Scanner 1 and 0.0240 for Scanner 2; between-scanner CoV was 0.032. For 64-direction scans, CoV was 0.056 for TR 4000 ms and 0.0533 for TR 13,200 ms. The difference between median FA values of 12-direction and 64-direction scans was statistically significant ( p < 0.001). We found relatively good reproducibility on any single MR scanner. FA values from one scanner were sometimes significantly below the mean FA of another scanner, which has important implications for clinical use of DTI.

Surgery of language-eloquent tumors in patients not eligible for awake surgery: the impact of a protocol based on navigated transcranial magnetic stimulation on presurgical planning and language outcome, with evidence of tumor-induced intra-hemispheric plasticity

OBJECTIVES

Awake surgery and intraoperative monitoring represent the gold standard for surgery of brain tumors located in the perisylvian region of the dominant hemisphere due to their ability to map and preserve the language network during surgery. Nevertheless, in some cases awake surgery is not feasible. This could increase the risk of postoperative language deficit. Navigated transcranial magnetic stimulation (nTMS) and nTMS-based DTI fiber tracking (DTI-FT) provide a preoperative mapping and reconstruction of the cortico-subcortical language network. This can be used to plan and guide the surgical strategy to preserve the language function. The objective if this study is to describe the impact of a non-invasive preoperative protocol for mapping the language network through the nTMS and nTMS-based DTI-FT in patients not eligible for awake surgery and thereby operated under general anesthesia for suspected language-eloquent brain tumors.

PATIENTS AND METHODS

We reviewed clinical data of patients not eligible for awake surgery and operated under general anaesthesia between 2015 and 2016. All patients underwent nTMS language cortical mapping and nTMS-based DTI-FT of subcortical language fascicles. The nTMS findings were used to plan and guide the maximal safe resection of the tumor. The impact on postoperative language outcome and the accuracy of the nTMS-based mapping in predicting language deficits were evaluated.

RESULTS

Twenty patients were enrolled in the study. The nTMS-based reconstruction of the language network was successful in all patients. Interestingly, we observed a significant association between tumor localization and the cortical distribution of the nTMS errors (p = 0.004), thereby suggesting an intra-hemispheric plasticity of language cortical areas, probably induced by the tumor itself. The nTMS mapping disclosed the true-eloquence of lesions in 12 (60%) of all suspected cases. In the remaining 8 cases (40%) the suspected eloquence of the lesion was disproved. The nTMS-based findings guided the planning and surgery through the visual feedback of navigation. This resulted in a slight reduction of the postoperative language performance at discharge that was completely recovered after one month from surgery. The accuracy of the nTMS-based protocol in predicting postoperative permanent deficits was significantly high, especially for false-eloquent lesions (p = 0.04; sensitivity 100%, specificity 57.14%, negative predictive value 100%, positive predicitive value 50%).

CONCLUSIONS

The nTMS-based preoperative mapping allows for a reliable visualization of the language network, being also able to identify an intra-hemispheric tumor-induced cortical plasticity. It allows for a customized surgical strategy that could preserve post-operative language function. This approach should be considered as a support for neurosurgeons whenever approaching patients affected by suspected language-eloquent tumors but not eligible for awake surgery.

Diffusion tensor imaging in multiple sclerosis at different final outcomes

OBJECTIVES

Methods to evaluate the relative contributions of demyelination vs axonal degeneration over the long-term course of MS are urgently needed. We used magnetic resonance diffusion tensor imaging (DTI) to estimate degrees of demyelination and axonal degeneration in the corpus callosum (CC) in cases of MS with different final outcomes.

MATERIALS AND METHODS

We determined DTI measures mean diffusivity (MD), fractional anisotropy (FA), and axial (AD) and radial (RD) diffusivities in the CC of 31 MS patients, of whom 13 presented a secondary progressive course, 11 a non-progressive course, and seven a monophasic course. The study participants were survivors from an incidence cohort of 254 attack-onset MS patients with 50 years of longitudinal follow-up. As reference, we included five healthy individuals without significant morbidity.

RESULTS

In patients with secondary progression, compared to all other groups, the corpus callosum showed increased RD and reduced FA, but no change in AD. None of the parameters exhibited differences among non-progressive and monophasic course groups and controls.

CONCLUSION

Increased RD was observed in secondary progressive MS, indicating significant myelin loss. Normal RD values observed in the clinically isolated syndrome and non-progressive groups confirm their benign nature. AD was not a characterizing parameter for long-term outcome. Demyelination revealed by increased RD is a distinguishing trait for secondary progression.

Temperature and concentration calibration of aqueous polyvinylpyrrolidone (PVP) solutions for isotropic diffusion MRI phantoms

To use the "apparent diffusion coefficient" (Dapp) as a quantitative imaging parameter, well-suited test fluids are essential. In this study, the previously proposed aqueous solutions of polyvinylpyrrolidone (PVP) were examined and temperature calibrations were obtained. For example, at a temperature of 20°C, Dapp ranged from 1.594 (95% CI: 1.593, 1.595) μm2/ms to 0.3326 (95% CI: 0. 3304, 0.3348) μm2/ms for PVP-concentrations ranging from 10% (w/w) to 50% (w/w) using K30 polymer lengths. The temperature dependence of Dapp was found to be so strong that a negligence seems not advisable. The temperature dependence is descriptively modelled by an exponential function exp(c2 (T - 20°C)) and the determined c2 values are reported, which can be used for temperature calibration. For example, we find the value 0.02952 K-1 for 30% (w/w) PVP-concentration and K30 polymer length. In general, aqueous PVP solutions were found to be suitable to produce easily applicable and reliable Dapp-phantoms.

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging

This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25-65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R2 of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R2 in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R2 with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand.

Fractional Anisotropy Correlates with Overall Survival in Glioblastoma

OBJECTIVE

Glioblastoma (GB) is an infiltrative disease that results in microstructural damage on a cellular level. Fractional anisotropy (FA) is an important estimate of diffusion tensor imaging (DTI) that can be used to assess microstructural integrity. The aim of this study was to examine the correlation between FA values and overall survival (OS) in patients with GB.

METHODS

This retrospective single-center study included 122 consecutive patients with GB (50 women; median age, 63 years) with preoperative MRI including fluid attenuated inversion recovery (FLAIR), contrast-enhanced T1-weighted sequences, and DTI. FA and apparent diffusion coefficient (ADC) values in contrast-enhancing lesions (FA-CEL, FA-ADC), nonenhancing lesions, and central tumor regions were correlated to histopathologic and clinical parameters. Univariate and multivariate survival analyses were performed.

RESULTS

Patients with low FA-CEL (median <0.31) showed significantly improved OS in univariate analysis (P = 0.028). FA-CEL also showed a positive correlation with Ki-67 proliferation index (P = 0.003). However, in a multivariate survival model, FA values could not be identified as independent prognostic parameters beside established factors such as age and Karnofsky performance scale score. FA values in nonenhancing lesions and central tumor regions and mean ADC values had no distinct influence on OS.

CONCLUSIONS

FA values can provide prognostic information regarding OS in patients with GB. There is a correlation between FA-CEL values and Ki-67 proliferation index, a marker for malignancy. Noninvasive identification of more aggressive GB growth patterns might be beneficial for preoperative risk evaluation and estimation of prognosis.

Impact of region-of-interest method on quantitative analysis of DTI data in the optic tracts

Background

To extract DTI parameters from a specific structure, a region of interest (ROI) must be defined. ROI selection in small structures is challenging; the final measurement results could be affected due to the significant impact of small geometrical errors. In this study the optic tracts were analyzed with the aim to assess differences in DTI parameters due to ROI method and to identify the most reliable method.

Methods

Images of 20 healthy subjects were acquired. Fractional anisotropy (FA) was extracted from the optic tracts by four different ROI methods. Manual tracing was performed in 1) the b0 image and 2) a T1-weighted image registered to the FA image. Semi-automatic segmentation was performed based on 3) tractography and 4) the FA-skeleton algorithm in the tract-based spatial statistics (TBSS) framework. Results were analyzed with regard to ROI method as well as to inter-scan, intra-rater and inter-rater reliability.

Results

The resulting FA values divided the ROI methods into two groups that differed significantly: 1) the FA-skeleton and the b0 methods showed higher FA values compared to 2) the tractography and the T1-weighted methods. The intra- and inter-rater variabilities were similar for all methods, except for the tractography method where the inter-rater variability was higher. The FA-skeleton method had a better reproducibility than the other methods.

Conclusion

Choice of ROI method was found to be highly influential on FA values when the optic tracts were analyzed. The FA-skeleton method performed the best, yielding low variability and high repeatability.

Diffusion-Weighted Breast Magnetic Resonance Imaging: A Semiautomated Voxel Selection Technique Improves Interreader Reproducibility of Apparent Diffusion Coefficient Measurements

OBJECTIVE

To determine whether a semiautomated voxel selection technique improves interreader reproducibility for breast apparent diffusion coefficient (ADC) measurements.

METHODS

Three readers retrospectively performed ADC measurements of 31 breast lesions (16 malignant, 15 benign) and contralateral normal tissue in 26 women both unassisted (manual method) and assisted by a semiautomated software tool that excludes voxels below a dynamically specified signal intensity threshold. Reproducibility between readers for each technique was assessed by Bland-Altman analysis and concordance correlation coefficients (CCCs).

RESULTS

Differences between readers' measured ADCs of lesions were smaller with the semiautomated tool vs the manual method. Concordance correlation coefficients for each reader pair were greater with the semiautomated tool for lesions (mean CCC difference, 0.11; 95% confidence interval, 0.04-0.26). For normal tissue, reader agreement was lower than for lesions and did not differ based on software tools (mean CCC difference, 0.00; 95% confidence interval, -0.14 to 0.13).

CONCLUSIONS

A semiautomated voxel selection tool can improve interreader reproducibility of breast lesion ADC measures.

Multi-site study of diffusion metric variability: effects of site, vendor, field strength, and echo time on regions-of-interest and histogram-bin analyses

It is now common for magnetic-resonance-imaging (MRI) based multi-site trials to include diffusion-weighted imaging (DWI) as part of the protocol. It is also common for these sites to possess MR scanners of different manufacturers, different software and hardware, and different software licenses. These differences mean that scanners may not be able to acquire data with the same number of gradient amplitude values and number of available gradient directions. Variability can also occur in achievable b-values and minimum echo times. The challenge of a multi-site study then, is to create a common protocol by understanding and then minimizing the effects of scanner variability and identifying reliable and accurate diffusion metrics. This study describes the effect of site, scanner vendor, field strength, and TE on two diffusion metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA) using two common analyses (region-of-interest and mean-bin value of whole brain histograms). The goal of the study was to identify sources of variability in diffusion-sensitized imaging and their influence on commonly reported metrics. The results demonstrate that the site, vendor, field strength, and echo time all contribute to variability in FA and MD, though to different extent. We conclude that characterization of the variability of DTI metrics due to site, vendor, field strength, and echo time is a worthwhile step in the construction of multi-center trials.

Advanced magnetic resonance neuroimaging in bulbar and limb onset early amyotrophic lateral sclerosis

Introduction:

Amyotrophic lateral sclerosis (ALS) is a fatal and most common motor neuron disease, caused by progressive loss of motor neurons. Diffusion tensor imaging (DTI) and magnetic resonance spectroscopic (MRS) studies detect pathological changes in neuronal fibers in vivo. We evaluated the role of DTI and MRS in early course of the disease, which may prove beneficial in the early diagnosis and better management.

Materials and Methods:

Twenty-one patients with ALS and 13 age-matched controls received 1.5T DTI and three-dimensional multi-voxel MRS. Fractional anisotropy (FA), apparent diffusion coefficient, N-acetyl aspartate (NAA)/Creatine (Cr), and NAA/Choline (Ch) ratios were analyzed in various regions of the brain and compared with healthy controls. ALS patients were classified as definite, possible, and probable category, and patients were also studied in limb versus bulbar onset.

Results:

Decreased FA and increase mean diffusivity values in regions of corticospinal tract (CST) and corpus callosum (CC) was consistent finding in definite and probable disease category (P < 0.05). In possible disease, CC involvement was not significant. NAA/Cr and NAA/Ch ratios were lower in CC and regions of CST. However, in possible disease, CC involvement was not significant, while regions of CST were showing significant reduction in NAA/Cr and NAA/Ch ratios (P < 0.05).

Conclusion:

DTI and MRS detect changes associated with ALS even in the early phase of the disease. Bulbar onset and limb onset ALS patients show different pattern of involvement. Extramotor involvement suggested by CC involvement is a feature seen in bulbar onset patient and can suggest poor outcome in such patients. The present findings may be helpful for designing further studies in the direction of more early diagnosis of disease and its management.

Gadolinium-Enhancing Lesions Lead to Decreases in White Matter Tract Fractional Anisotropy in Multiple Sclerosis

PURPOSE

Although MRI identification of new lesions forms the basis for monitoring disease progression in multiple sclerosis patients, how lesion activity relates to longitudinal white matter changes in the brain is unknown. We hypothesized that patients with gadolinium-enhancing lesions would show greater longitudinal decline in fractional anisotropy in major tracts compared to those with stable disease.

METHODS

Thirty patients with relapsing-remitting multiple sclerosis were included in this study-13 had enhancing lesions at baseline and 17 did not. Each patient underwent at least two 3 Tesla contrast-enhanced MRI scans with a DTI sequence with a median interval of 2.1 years between scans. The forceps major and minor of the corpus callosum and the bilateral corticospinal tracts were selected as the major white matter tracts of interest. These tracts were reconstructed using region-of-interest placement on standard anatomical landmarks and a fiber assignment by continuous tracking algorithm using TrackVis (version 0.5.2.2) software. Mixed-effects regression models were used to determine the association between enhancing lesions and subsequent longitudinal change in fractional anisotropy.

RESULTS

In patients with enhancing lesions, there was greater decline in fractional anisotropy compared to those with stable disease in the forceps major (P = .026), right corticospinal tract (P = .032), and marginally in the left corticospinal tract (P = .050), but not the forceps minor (P = .11).

CONCLUSION

Fractional anisotropy of major white matter tracts declined more rapidly in patients with enhancing lesions, suggesting greater diffuse white matter injury with active inflammatory disease. DTI may provide a means of monitoring white matter injury following relapses.

Inter- and intra-rater reliability of diffusion tensor imaging parameters in the normal pediatric spinal cord

AIM

To assess inter- and intra-rater reliability (agreement) between two region of interest (ROI) methods in pediatric spinal cord diffusion tensor imaging (DTI).

METHODS

Inner-Field-of-View DTI data previously acquired from ten pediatric healthy subjects (mean age = 12.10 years) was used to assess for reliability. ROIs were drawn by two neuroradiologists on each subject data twice within a 3-mo interval. ROIs were placed on axial B0 maps along the cervical spine using free-hand and fixed-size ROIs. Agreement analyses for fractional anisotropy (FA), axial diffusivity, radial diffusivity and mean diffusivity were performed using intra-class-correlation (ICC) and Cronbach's alpha statistical methods.

RESULTS

Inter- and intra-rater agreement between the two ROI methods showed moderate (ICC = 0.5) to strong (ICC = 0.84). There were significant differences between raters in the number of pixels selected using free-hand ROIs (P < 0.05). However, no significant differences were observed in DTI parameter values. FA showed highest variability in ICC values (0.10-0.87). Cronbach's alpha showed moderate-high values for raters and ROI methods.

CONCLUSION

The study showed that high reproducibility in spinal cord DTI can be achieved, and demonstrated the importance of setting detailed methodology for post-processing DTI data, specifically the placement of ROIs.

Hemispheric asymmetry measured by texture analysis and diffusion tensor imaging in two multiple sclerosis subtypes

BACKGROUND

This paper addresses two subtypes of multiple sclerosis (MS), primary progressive multiple sclerosis (PPMS) and relapsing-remitting multiple sclerosis (RRMS). The separation of PPMS and RRMS is challenging in certain cases.

PURPOSE

To quantitatively determine MS subtypes using texture analysis (TA) and diffusion tensor imaging (DTI).

MATERIAL AND METHODS

T1-weighted (T1W) magnetic resonance imaging (MRI) and DTI of the left and right brain hemispheres of 17 patients with PPMS and 19 patients with RRMS were studied. Areas of the caudate nucleus and thalamus were investigated as normal appearing gray matter (NAGM), and areas of the cerebral peduncle and centrum semiovale were investigated as normal appearing white matter (NAWM). The described locations were symmetrical and were accurately marked. TA was performed on the T1W images, and the fractional anisotropy and apparent diffusion coefficient were determined from the DTI data.

RESULTS

Hemispherical differences were found with both TA and DTI. Several texture and diffusion tensor parameter values calculated for the left and right hemispheres of the patients showed statistically significant differences. The patients with RRMS had greater significant differences (P < 0.01) in the thalamus between the hemispheres than did the patients with PPMS. The TA classification accuracy of the PPMS and RRMS subtypes was above 80%.

CONCLUSION

TA can be helpful when distinguishing between PPMS and RRMS, while DTI appears to reveal the hemispherical asymmetry of RRMS patients.

Diffusion-weighted MRI findings and clinical correlations in sporadic Creutzfeldt-Jakob disease

The objective of this study is to investigate the hyperintense lesions on diffusion-weighted magnetic resonance imaging (DWI) and its clinical correlation in sporadic Creutzfeldt-Jakob disease (sCJD). Patients who suffered from sCJD and followed up at the Department of Neurology at the General Hospital of the People's Liberation Army during the period of June 1, 2007 to July 1, 2014 were reviewed. The location of the hyperintense lesions on DWI, apparent diffusion coefficient (ADC) values of the hyperintense lesions were correlated with symptoms and clinical course. A total of 58 sCJD patients and ten healthy controls were included. Hyperintense lesions on DWI were observed in all the patients. The patients with basal ganglia (BG) hyperintense lesions on DWI had shorter disease duration and higher incidence of myoclonus (92 versus 44 %) than those without BG hyperintense lesions. The patients with occipital cortex hyperintense lesions on DWI had shorter disease duration between symptom onset and akinetic mutism than those without these lesions. The lower of the BG ADC value the faster presence of akinetic mutism and the shorter disease duration the patients will have. The presence of BG and occipital cortex hyperintense lesions on DWI and BG ADC values is correlated with the clinical course and clinical symptoms.

A prospective biopsychosocial study of the persistent post-concussion symptoms following mild traumatic brain injury

This study examined multiple biopsychosocial factors relating to post-concussion symptom (PCS) reporting in patients with mild traumatic brain injuries (mTBI), including structural (computed tomography and magnetic resonance imaging [MRI]) and microstructural neuroimaging (diffusion tensor imaging [DTI]). Patients with mTBIs completed several questionnaires and cognitive testing at approximately one month (n=126) and one year (n=103) post-injury. At approximately three weeks post-injury, DTI was undertaken using a Siemens 3T scanner in a subgroup (n=71). Measures of fractional anisotropy were calculated for 16 regions of interest (ROIs) and measures of apparent diffusion coefficient were calculated for 10 ROIs. Patients were compared with healthy control subjects. Using International Classification of Diseases, Tenth Revision (ICD-10) PCS criteria and mild or greater symptom reporting, 59% of the mTBI sample met criteria at one month and 38% met criteria at one year. However, 31% of the healthy control sample also met criteria for the syndrome-illustrating a high false-positive rate. Significant predictors of ICD-10 PCS at one month were pre-injury mental health problems and the presence of extra-cranial bodily injuries. Being symptomatic at one month was a significant predictor of being symptomatic at one year, and depression was significantly related to PCS at both one month and one year. Intracranial abnormalities visible on MRI were present in 12.1% of this sample, and multifocal areas of unusual white matter as measured by DTI were present in 50.7% (compared with 12.4% of controls). Structural MRI abnormalities and microstructural white matter findings were not significantly associated with greater post-concussion symptom reporting. The personal experience and reporting of post-concussion symptoms is likely individualized, representing the cumulative effect of multiple variables, such as genetics, mental health history, current life stress, medical problems, chronic pain, depression, personality factors, and other psychosocial and environmental factors. The extent to which damage to the structure of the brain contributes to the persistence of post-concussion symptoms remains unclear.

Statistical Instability of TBSS Analysis Based on DTI Fitting Algorithm

Voxel-based DTI analysis is an important approach in the comparison of subject groups by detecting and localizing gray and white matter changes in the brain. One of the principal problems for intersubject comparison is the absence of a "gold standard" processing pipeline. As a result, contradictory results may be obtained from identical data using different data processing pipelines, for example, in the data normalization or smoothing procedures. Tract-based spatial statistics (TBSS) shows potential to overcome this problem by automatic detection of white matter changes and decreasing variation in the performed analysis. However, skeleton projection approaches, such as TBSS, critically depend on the accuracy of the diffusion scalar metric estimations. In this work, we demonstrate that the agreement and reliability of TBSS results depend on the applied DTI data processing algorithm. Statistical tests have been performed using two in vivo measured datasets and compared with different implementations of the least squares algorithm. As a result, we recommend repeating TBSS analysis using different fitting algorithms, in particular, using on iteratively-assessed robust estimators, as accurate and more reliable approach in voxel-based analysis, particularly, for TBSS. Repeating TBSS analysis allows one to detect and localize suspicious regions in white matter which were estimated as the regions with significant difference. Finally, we did not find a favorite fitting algorithm (or class of them) which can be marked as more reliable for group comparison.

Possible confounding factors on cerebral diffusion tensor imaging measurements

BACKGROUND

Diffusion tensor imaging (DTI) is prone to numerous systemic confounding factors that should be acknowledged to avoid false conclusions.

PURPOSE

To investigate the possible effects of age, gender, smoking, alcohol consumption, and education on cerebral DTI parameters in a generally healthy homogenous sample with no neurological or psychiatric diseases.

MATERIAL AND METHODS

Forty (n = 40) subjects (mean age, 40.3 years; SD, 12.3) underwent brain DTI with 3 T magnetic resonance imaging (MRI). At enrolment, all the subjects were interviewed with respect to general health, education, history of smoking, and alcohol consumption. Studied DTI parameters included: (i) fractional anisotropy (FA); and (ii) apparent diffusion coefficient (ADC). Region-of-interest (ROI)-based measurements were estimated at 13 anatomical locations bilaterally on the axial images, except for the corpus callosum in which the ROIs were placed on the sagittal images. Circular ROI measurements were mainly used. Freehand ROI method was used with the forceps minor, uncinate fasciculus, and thalamus. Intra-observer variability and repeatability were assessed.

RESULTS

The most consistent finding was that aging decreased FA values in the frontal brain regions. Regarding the other confounding factors, the results were discontinuous and no concrete conclusions could be drawn from these findings. In general, intra-observer repeatability of the DTI measurement was considered relatively good.

CONCLUSION

Age should be noted as considerable confounding factors in ROI-based DTI analysis. More research on the effects of gender, smoking, alcohol consumption, and education is needed.

MRI Texture Analysis and Diffusion Tensor Imaging in Chronic Right Hemisphere Ischemic Stroke

BACKGROUND AND PURPOSE

Diffusion tensor imaging (DTI) is shown to reveal changes caused by cerebral infarction. The aim of this study is to reveal those changes also in the conventional magnetic resonance (MR) images using a quantitative image analysis method, texture analysis (TA).

METHODS

Thirty patients who had suffered their first ever infarction located on the right hemisphere underwent DTI and conventional MRI studies in the chronic phase. DTI parameters fractional anisotropy and mean diffusivity, as well as four second-order texture parameters were calculated. Interhemispheric differences and correlations between DTI and TA parameters were evaluated.

RESULTS

Our DTI findings supported earlier studies as fractional anisotropy values were lowered and mean diffusivity values elevated in the lesion site, and ipsilateral cerebral peduncle, thalamus, and centrum semiovale compared to the unaffected side. Textural homogeneity parameters showed lower and complexity parameters higher values in the lesion site and ipsilateral centrum semiovale compared to the contralateral hemisphere. Correlation between the two methods was found in ipsilateral mesencephalon.

CONCLUSIONS

In addition to DTI method, TA could assist in revealing the changes caused by infarction, also outside the lesion site. Damaged areas were found more heterogeneous and random in texture compared to unaffected sites.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

Changes in white matter integrity before conversion from mild cognitive impairment to Alzheimer's disease

BACKGROUND

Mild cognitive impairment (MCI) may represent an early stage of dementia conferring a particularly high annual risk of 15-20% of conversion to Alzheimer's disease (AD). Recent findings suggest that not only gray matter (GM) loss but also a decline in white matter (WM) integrity may be associated with imminent conversion from MCI to AD.

OBJECTIVE

In this study we used Voxel-based morphometry (VBM) to examine if gray matter loss and/or an increase of the apparent diffusion coefficient (ADC) reflecting mean diffusivity (MD) are an early marker of conversion from MCI to AD in a high risk population.

METHOD

Retrospective neuropsychological and clinical data were collected for fifty-five subjects (MCI converters n = 13, MCI non-converters n = 14, healthy controls n = 28) at baseline and one follow-up visit. All participants underwent diffusion weighted imaging (DWI) and T1-weighted structural magnetic resonance imaging scans at baseline to analyse changes in GM density and WM integrity using VBM.

RESULTS

At baseline MCI converters showed impaired performance in verbal memory and naming compared to MCI non-converters. Further, MCI converters showed decreased WM integrity in the frontal, parietal, occipital, as well as the temporal lobe prior to conversion to AD. Multiple regression analysis showed a positive correlation of gray matter atrophy with specific neuropsychological test results.

CONCLUSION

Our results suggest that additionally to morphological changes of GM a reduced integrity of WM indicates an imminent progression from MCI stage to AD. Therefore, we suggest that DWI is useful in the early diagnosis of AD.

Diffusion Tensor Imaging in NAWM and NADGM in MS and CIS: Association with Candidate Biomarkers in Sera

The aim of this study was to evaluate diffusion tensor imaging (DTI) indices in the corpus callosum and pyramidal tract in normal-appearing white matter (NAWM) and the caudate nucleus and thalamus in deep grey matter (NADGM) in all MS subtypes and clinically isolated syndrome (CIS). Furthermore, it was determined whether these metrics are associated with clinical measures and the serum levels of candidate immune biomarkers. Apparent diffusion coefficients (ADC) values were significantly higher than in controls in all six studied NAWM regions in SPMS, 4/6 regions in RRMS and PPMS and 2/6 regions in CIS. In contrast, decreased fractional anisotropy (FA) values in comparison to controls were detected in 2/6 NAWM regions in SPMS and 1/6 in RRMS and PPMS. In RRMS, the level of neurological disability correlated with thalamic FA values (r = 0.479, P = 0.004). In chronic progressive subtypes and CIS, ADC values of NAWM and NADGM were associated with the levels of MIF, sFas, and sTNF-α. Our data indicate that DTI may be useful in detecting pathological changes in NAWM and NADGM in MS patients and that these changes are related to neurological disability.