Diffusion Tensor Imaging Parameters Research Articles

Developing Topics.

The novel diffusion-based Neurite Orientation and Dispersion Imaging (NODDI) model may provide complementary information to Diffusion Tensor Imaging (DTI) to increase sensitivity in characterizing tissue microarchitecture. We examined if one or a combination of both approaches can improve our understanding of at-risk tissue in and around white matter hyperintensities (WMH). From ADNI3, we identified individuals [n = 54, age = 78 ± 7, 46% F) with concurrent measures of multi-shell DTI, 3D FLAIR, and 3D MPRAGE. We segmented WMH from structural data using Lesion Segmentation Toolbox. We derived DTI (FA, MD) and NODDI parameters (NDI, ODI, Fiso) using QSIprep. We dilated up to 5 mm outside the WMH, applied an FA threshold of ≥ 0.2 to exclude gray matter, calculated DTI and NODDI parameters at 1 mm intervals within this region. We performed Pearson correlations between all parameters. Assuming normal white matter at 5 mm, we normalized these parameters with their respective values at 5 mm and plotted the spatial variation of each parameter in and outside the WMH. Normalized DTI and NODDI parameters representing spatial variations within the 5 mm region are shown in Fig 1A. Table 1 shows p-values comparing DTI and NODDI parameters between WMH the subsequent regions outside it. Compared to WMH, Fiso was significantly different at all distances. FA showed similar spatial characteristics with NDI and was negatively correlated with ODI. Fiso correlated very strongly with MD. In the WMHs and its immediate vicinity, low FA, NDI, ODI suggest lower cell density, while low Fiso and MD suggest low extracellular fluid volume. Together these observations may reflect cytotoxic edema, cell loss, and injury. Normal appearing white matter (3-5 mm) showed high FA, NDI, ODI, and low MD consistent with high cell density and normal extracellular water. In the transition between WMH vicinity and normal white matter, low FA, NDI, ODI, high MD and Fiso suggest cell loss only. This transition region could be at risk of converting to WMH. Future work will include longitudinal evaluation of WMH growth in the at-risk tissue. However, final validation of WMH pathology will need histological confirmation.

Advanced muscle imaging in adolescent elite rowers utilizing diffusion tensor imaging: Association of imaging findings with stroke typology.

Muscular overuse injuries are a common health issue in elite athletes. Changes in the muscular microenvironment can be depicted by Diffusion Tensor Imaging (DTI). We hypothesize that the biomechanics of different stroke typologies plays a role in muscle injury and tested our hypothesis by magnetic resonance imaging (MRI) examination of the lumbar spine muscles of adolescent rowers utilizing DTI. Twenty-two male elite rowers (12 sweep, 10 scull rowers) with a mean age of 15.8 ± 1.2 years underwent 3-Tesla MRI of the lumbar spine 6 hours after cessation of training. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were calculated for the erector spinae and multifidus muscle. Student's t-test was used to test differences of DTI parameters between sweep and scull rowers and a Pearson correlation was utilized to correlate the parameters to training volume. ADC values in the erector spinae and multifidus muscle were significantly higher (p = 0.039) and FA values significantly lower (p < 0.001) in sweep rowers compared to scull rowers. There was no significant association between DTI parameters and training volume (r ≤ -0.459, p ≥ 0.074). Our DTI results show that lumbar spine muscle diffusivity is higher in sweep rowers than in scull rowers. Altered muscle diffusivity is suggestive of microscopic tissue disruption and might be attributable to biomechanical differences between stroke typologies.

Cerebellar peduncle damage in Langerhans cell histiocytosis-associated neurodegenerative disease revealed by diffusion tensor imaging.

To confirm the hypothesis that brain white matter damage is involved in the pathogenesis and disease progression of Langerhans cell histiocytosis (LCH)-associated neurodegenerative disease (ND), we aimed to analyze pediatric patients with LCH using diffusion tensor imaging (DTI). We enrolled 33 patients with LCH and obtained 33 DTI datasets. Using DTI-based tractography, fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD) were measured in the cerebral and cerebellar white matter tracts. The participants were divided into three groups-non-ND, ND without clinical symptoms (r-ND), and ND with clinical symptoms (c-ND)-according to their clinical status during the examination with DTI. We compared the DTI parameters in white matter tracts were compared among the three groups. In the order of non-ND, r-ND, and c-ND groups, the FA in superior cerebellar peduncle (SCP) and middle cerebellar peduncle (MCP) significantly decreased, the ADC, AD, and RD of MCP, and the RD of SCP were significantly elevated (FA-SCP; p < 0.001, FA-MCP; p = 0.026, ADC-MCP; p < 0.001, AD-MCP; p = 0.002, RD-MCP; p = 0.003, and RD-SCP; p = 0.018). Furthermore, in the simple linear regression analysis, the FA, ADC, AD, and RD values in the MCP and the FA value in the SCP were significantly influenced by the presence of neurological symptoms and ND findings on MRI (all p < 0.001). In LCH-ND, we identified microstructural damage in the SCP and MCP. DTI parameters in these tracts may help monitor LCH-ND; therefore, future studies are required to validate these results in a large cohort.

Diffusion tensor imaging changes of the cortico-thalamic-striatal tracts correlate with fatigue and disability in people with relapsing-remitting MS

PurposeTo investigate how the microstructural neural integrity of cortico-thalamic-striatal (CTS) tracts correlate with fatigue and disability over time. The primary outcome was diffusion tensor imaging (DTI) metrics change over time, and the secondary outcome was correlations with fatigue and disability in people with RRMS (pw-RRMS). Methods76 clinically stable pw-RRMS and 43 matched healthy controls (HCs). The pw-RRMS cohort consisted of three different treatment subgroups. All participants underwent disability, cognitive, fatigue and mental health assessments. Structural and diffusion scans were performed at baseline (BL) and 2-year follow-up (2-YFU) for all participants. Fractional anisotropy (FA), mean, radial and axial diffusivities (MD, RD, AD) of normal-appearing white matter (NAWM) and white matter lesion (WML) in nine tracts-of-interests (TOIs) were estimated using our MRtrix3 in-house pipeline. ResultsWe found significant BL and 2-YFU differences in most diffusion metrics in TOIs in pw-RRMS compared to HCs (pFDR ≤ 0.001; false-detection-rate (FDR)-corrected). There was a significant decrease in WML diffusivities and an increase in FA over the follow-up period in most TOIs (pFDR ≤ 0.001). Additionally, there were no differences in DTI parameters across treatment groups. AD and MD were positively correlated with fatigue scores (r ≤ 0.33, p ≤ 0.01) in NAWM-TOIs, while disability (EDSS) was negatively correlated with FA in most NAWM-TOIs (|r|≤0.31, p ≤ 0.01) at both time points. Disability scores correlated with all diffusivity parameters (r ≤ 0.29, p ≤ 0.01) in most WML-TOIs at both time points. ConclusionStatistically significant changes in diffusion metrics in WML might be indicative of integrity improvement over two years in CTS tracts in clinically stable pw-RRMS. This finding represents structural changes within lesioned tracts. Measuring diffusivity in pw-RRMS affected tracts might be a relevant measure for future remyelination clinical trials.

Maternal pre-pregnancy obesity affects the uncinate fasciculus white matter tract in preterm infants.

A growing body of evidence suggests an association between a higher maternal pre-pregnancy body mass index (BMI) and adverse long-term neurodevelopmental outcomes for their offspring. Despite recent attention to the effects of maternal obesity on fetal and neonatal brain development, changes in the brain microstructure of preterm infants born to mothers with pre-pregnancy obesity are still not well understood. This study aimed to detect the changes in the brain microstructure of obese mothers in pre-pregnancy and their offspring born as preterm infants using diffusion tensor imaging (DTI). A total of 32 preterm infants (born to 16 mothers with normal BMI and 16 mothers with a high BMI) at <32 weeks of gestation without brain injury underwent brain magnetic resonance imaging at term-equivalent age (TEA). The BMI of all pregnant women was measured within approximately 12 weeks before pregnancy or the first 2 weeks of gestation. We analyzed the brain volume using a morphologically adaptive neonatal tissue segmentation toolbox and calculated the major white matter (WM) tracts using probabilistic maps of the Johns Hopkins University neonatal atlas. We investigated the differences in brain volume and WM microstructure between preterm infants of mothers with normal and high BMI. The DTI parameters were compared among groups using analysis of covariance adjusted for postmenstrual age at scan and multiple comparisons. Preterm infants born to mothers with a high BMI showed significantly increased cortical gray matter volume (p = 0.001) and decreased WM volume (p = 0.003) after controlling for postmenstrual age and multiple comparisons. We found a significantly lower axial diffusivity in the uncinate fasciculus (UNC) in mothers with high BMI than that in mothers with normal BMI (1.690 ± 0.066 vs. 1.762 ± 0.101, respectively; p = 0.005). Our study is the first to demonstrate that maternal obesity impacts perinatal brain development patterns in preterm infants at TEA, even in the absence of apparent brain injury. These findings provide evidence for the detrimental effects of maternal obesity on brain developmental trajectories in offspring and suggest potential neurodevelopmental outcomes based on an altered UNC WM microstructure, which is known to be critical for language and social-emotional functions.

Abstract 13302: Associations of Allostatic Load With Brain Macro-Morphology, Subclinical Cerebrovascular Disease, and Microstructural Integrity of White Matter Pathways: The Boston Puerto Rican Health Study

Introduction: Allostatic load (AL), a measure of overall body wear and tear, has been associated with structural and functional alterations of the brain, but the evidence remains scarce. We aimed to evaluate the prospective associations of AL with brain MRI measures in the Boston Puerto Rican Health Study (BPRHS). Research Questions: Whether AL is associated with 1) brain macro-morphology: brain age and volumes, 2) subclinical cerebrovascular disease: white matter hyperintensity (WMH) and brain infarcts, and 3) microstructural integrity of white matter (WM) pathways in Puerto Rican adults. Methods: Adults from the BPRHS cohort who provided blood and urine samples at baseline, 2-y, and 6-y visits and underwent MRI scans at 13-y visit were included in analyses (n=226). AL was evaluated as a composite score (0-11) of 11 physiological parameters in five body systems. An overall AL score was calculated by averaging the scores of the baseline, 2-y, and 6-y visits, with higher scores indicating greater dysregulation. We evaluated brain age and volumes using T1-weighted MRI, WMH and brain infarcts using T2-weighted MRI, and microstructural integrity of WM pathways using diffusion tensor imaging. Multivariable logistic regression models were used to examine the associations between AL and brain infarcts, and linear regression models were used for other MRI outcomes. Results: Mean age at baseline was 54.6 ± 6.6 y, with 79.2% female. Higher AL was associated with higher brain age z scores (β = 0.129, P = 0.031) and lower volumes of total WM, cerebral WM (especially parietal and temporal lobes), cerebellum, and brain stem. Higher AL was also associated with higher grades of WMH (β = 0.207, P = 0.024) and higher odds of small vessel infarcts [OR (95% CI) = 3.50 (1.56-7.87), P = 0.002], but not large vessel infarcts [OR (95% CI) = 1.33 (0.73-2.40), P = 0.348]. Diffusion tensor imaging parameters showed that participants with higher AL had more microstructural deterioration patterns in major WM pathways. Conclusions: Higher AL score was associated with brain macro- and microstructural disruptions and a higher risk of subclinical cerebrovascular disease, suggesting that AL may be a potential indicator of the need for early intervention in preventing neuronal damage in older adults.

Prediction of Mild Cognitive Impairment Progression to Alzheimer’s Disease Based on Diffusion Tensor Imaging-Derived Diffusion Parameters: Construction and Validation of a Nomogram

Introduction: The aim of the study was to construct and validate a nomogram that combines diffusion tensor imaging (DTI) parameters and clinically relevant features for predicting the progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD). Method: A retrospective analysis was conducted on the MRI and clinical data of 121 MCI patients, of whom 32 progressed to AD during a 4-year follow-up period. The MCI patients were divided into training and validation sets at a ratio of 7:3. DTI features were extracted from MCI patient data in the training set, and their dimensionality was reduced to construct a radiomics signature (RS). Then, combining the RS with independent predictors of MCI disease progression, a joint model was constructed, and a nomogram was generated. Finally, the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the diagnostic and clinical efficacy of the nomogram based on the data from the validation set. Result: The AUCs of the RS in the training and validation sets were 0.81 and 0.84, with sensitivities of 0.87 and 0.78 and specificities of 0.71 and 0.81, respectively. Multiple logistic regression analysis showed that the RS, clinical dementia rating scale score, and Alzheimer's disease assessment scale score were the independent predictors of progression and were thus used to construct the nomogram. The AUCs of the nomogram in the training and validation sets were 0.89 and 0.91, respectively, with sensitivities of 0.78 and 0.89 and specificities of 0.90 and 0.88, respectively. DCA showed that the nomogram was the most valuable model for predicting the progression of MCI to AD and that it provided greater net benefits than other analysed models. Conclusion: Changes in white matter fibre bundles can serve as predictive imaging markers for MCI disease progression, and the combination of white matter DTI features and relevant clinical features can be used to construct a nomogram with important predictive value for MCI disease progression.

Machine learning classificatory as a tool in the diagnosis of amyotrophic lateral sclerosis using diffusion tensor imaging parameters collected with 1.5T MRI scanner: A case study

The relevance of the study lies in the need to improve the diagnosis of amyotrophic lateral sclerosis (ALS) by utilizing diffusion tensor imaging (DTI) obtained from conventional 1.5 Tesla MRI scanners. The study aimed to investigate the potential of using different machine learning (ML) classifiers to distinguish between individuals with ALS. In this study, five ML classifiers (“support vector machine (SVM)”, “k-nearest neighbors (K-NN)”, naïve Bayesian classifier, “decision tree”, and “decision forest”) were used, based on two DTI parameters: fractional anisotropy and apparent diffusion coefficient, obtained from two manually selected ROIs at the level of the brain pyramids in 47 ALS patients and 55 healthy subjects. The quality of each classifier was evaluated using the confusion matrix and ROC curves. The highest accuracy in differentiating ALS patients from healthy individuals based on DTI data was demonstrated by the radial kernel support vector method (77% accuracy [p=0.01]), while K-NN and “decision tree” classifiers had slightly lower performance, and “decision forest” classifier was overtrained to the training set (AUC=1). The authors have shown a sufficiently accuracy of ML classifier “SVM” in detecting radiological characteristics of ALS in pyramidal tracts.

Disturbed white matter integrity on diffusion tensor imaging in young children with epilepsy

To evaluate whether abnormalities in white matter (WM) integrity are present in young children with epilepsy. Twelve children (3-6 years old) with epilepsy and six matched healthy controls were recruited for brain diffusion tensor imaging (DTI). Track-based spatial statistics (TBSS) was used to analyse and compare DTI indices of mean diffusivity (MD), fractional anisotropy (FA), axial and radial diffusivity (AD/RD) between patients and controls, and correlations between clinical variables and DTI parameters were analysed. Compared with controls, patients showed increased FA in the left superior corona radiata and increased AD in the bilateral superior corona radiata. In children with generalised epilepsy, FA was increased in the left external capsule, while AD was decreased in the body of the corpus callosum, the left external capsule and the left superior longitudinal fasciculus. In those with focal epilepsy, FA was increased in the genu and body of the corpus callosum, and RD was decreased in the genu of the corpus callosum and left external capsule. Compared with partial epilepsy, generalised epilepsy was associated with increased FA in the right anterior corona radiata and decreased RD in the right anterior corona radiata and the genu and body of the corpus callosum. No significant correlations were observed between clinical variables and DTI parameters. The results of this study indicate that the microstructure of the white matter is disturbed by epileptic discharges and a compensatory response occurs during early brain development.

THU347 Diffusion Tensor Imaging Of The Tibial Nerve Can Detect Peripheral Neuropathy In Type 2 Diabetes

Abstract Disclosure: H. Park: None. E. Oh: None. S. Park: None. H. Kim: None. D. Byun: None. Magnetic resonance imaging (MRI) has played little role for the study of peripheral nerve disease. However, recent technological advances in MRI have provided us more information about neural microstructure and higher resolution in peripheral nerves. The aim of this study is to evaluate whether diffusion tensor imaging (DTI) parameters in MRI can detect peripheral neuropathy in type 2 diabetes (T2D). In this prospective, single-center study, eight T2D patients (mean age, 62.1 ± 10.8 yr; 5 M/ 3F) with peripheral neuropathy and seven healthy controls (65.0 ± 3.3 yr, 7 F) were included. All T2D patients underwent Michigan Neuropathy Screening Instrument questionnaire and quantitative sensory testing. MRI including DTI and axial T2-weight Dixon sequence was performed for each participant. Region of interest analysis was independently performed by one radiologist on each side of tibial nerve at two levels: lower margin of adductor magnus muscle insertion (level 1), and quadriceps femoris tendon at patellar attachment (level 2). DTI parameters including cross-sectional areas (CSA), fractional anisotropy (FA), as well as diffusivity (mean (MD), axial (AD), and radial (RD)) were calculated. FA was significantly lower in T2D patients with peripheral neuropathy than healthy controls at both level 1 (396 ± 74 vs. 541 ± 141, P&amp;lt;0.05) and level 2 (422 ± 65 vs. 565 ± 108, P&amp;lt;0.05). AD was significantly lower in T2D patients with peripheral neuropathy than controls at level 2 (2,207 ± 492 vs. 2,884 ± 497, P&amp;lt;0.05). RD was significantly higher in T2D patients with peripheral neuropathy than controls at level 1 (1,156 ± 313 vs. 867 ± 147, P&amp;lt;0.05). No difference in the CSA of the tibial nerve was seen in both levels between two groups. Our results have shown that DTI parameters can detect nerve abnormalities of the tibial nerve in T2D patients, suggesting DTI may be useful as a biomarker in diabetic peripheral neuropathy. Presentation: Thursday, June 15, 2023

Role of white matter in cognitive impairment among relapsing remitting multiple sclerosis patients

BackgroundMultiple Sclerosis (MS) associated cognitive impairment is believed to be mostly connected with damage to gray matter. The contribution of white matter is still poorly understood. We aim to examine the relationship between cognition and white matter tracts among relapsing remitting MS (RRMS) patients. MethodsThirty RRMS patients were selected undergo the (3-seconds-interstimulus-interval paced auditory serial addition test) PASAT-3, the (symbol digit modalities test (SDMT) and full-brain MRI scans on a SIEMENS 3 Tesla Verio scanner. Diffusion Tensor Imaging (DTI) parameters, such as fractional anisotropy (FA) and mean diffusivity (MD) were examined in 37 white matter (WM) tracts. WM tracts were selected from the association pathways, projection pathways, commissural pathways by applying Human Connectome project (HCP)842 tractography atlas after DTI data reconstruction and registration to HCP1065 diffusion template in DSI Studio (version March 2021) In SPSS v26, Spearman's rank correlation analysis was used to examine the connection between DTI WM tracts and cognitive scores. The power of the study was increased by using false discovery rate (FDR) software. ResultsThe mean scores on the PASAT-3 and SDMT were 31.5 ± 12.8 and 46.9 ± 16.7 respectively. Better cognitive performance was correlated to higher FA values, while lower cognitive function was correlated to higher MD values. There was a positive correlation between FA values in the right medial lemniscus and superior cerebellar peduncle and SDMT scores (p 0.05). Additionally, there was a trend for significance between the FA values in the left corticothalamic tract and SDMT scores. MD values in the superior cerebellar peduncle, left arcuate Fasciculus and left extreme capsule were negatively correlated with SDMT scores (p<0.05). PASAT-3 scores were negatively correlated with MD values in the right cerebellum, however, there was no significant correlation between PASAT-3 and FA values. ConclusionsWhite matter tracts, particularly the superior cerebellar peduncle, contribute to the cognitive impairment in RRMS. Larger sample sizes for longitudinal research are necessary.

White matter microstructure and connectivity changes after surgery in male adults with obstructive sleep apnea: recovery or reorganization?

Obstructive sleep apnea (OSA) is a prevalent clinical problem significantly affecting cognitive functions. Surgical treatment is recommended for those unable to use continuous positive airway pressure. We aimed to investigate the therapeutic effect of upper airway surgery on the white matter (WM) microstructure and brain connectivity in patients with OSA. Twenty-one male patients with moderate-to-severe OSA were recruited for multi-level upper airway surgery. Overnight polysomnography (PSG), neuropsychiatric tests, and brain MRI scans were acquired before and 6.1 ± 0.8 months after surgery. Nineteen male patients with untreated OSA were also included as a reference group. We calculated the longitudinal changes of diffusion tensor imaging (DTI) parameters, including fractional anisotropy (ΔFA) and mean/axial/radial diffusivity (ΔMD/AD/RD). We also assessed changes in network properties based on graph theory. Surgically treated patients showed improvement in PSG parameters and verbal memory after surgery. Globally, ΔFA was significantly higher and ΔRD was lower in the surgery group than in the untreated group. Especially ΔFA of the tracts involved in the limbic system was higher after surgery. In network analysis, higher Δbetweenness and lower Δclustering coefficients were observed in the surgical group than in the untreated group. Finally, the improvement of verbal memory after surgery positively correlated with ΔFA in superior thalamic radiation (p = 0.021), fronto aslant tracts (p = 0.027), and forceps minor tracts (p = 0.032). Surgical treatment of OSA can alleviate alterations in WM integrity and disruptions in local networks, particularly for the tracts involved in the limbic system. These findings may further explain the cognitive improvement observed after the treatment of OSA.

Differences in diffusion tensor imaging parameters of brain white matter tracts between patients with myotonic dystrophy type 1 and type 2 - a retrospective single-centre study.

The main aim of our study was to compare diffusion tensor imaging (DTI) parameters in patients with myotonic dystrophy types 1 and 2 (DM1 and DM2). To ascertain whether DTI could be used to assess the integrity of white matter tracts in the brain and identify any abnormalities or disruptions in connectivity between different brain regions in patients with DM. By providing a more detailed understanding of the structural changes in the brain associated with DM, could DTI potentially be used to develop more effective treatments for the cognitive and neurological symptoms of the disorder? We retrospectively compared MRI scans of 19 patients with DM1 to those of 23 healthy, matched controls, and of 16 patients with DM2 to those of 20 healthy, matched controls, and finally compared the DM1 and DM2 samples. Fraction anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) values were assessed using Tract Based Spatial Statistics (TBSS). In patients with DM1, a statistically significant decrease in the values of the FA parameter was revealed in 45/48 white matter tracts compared to patients with DM2. There was no statistically significant decrease in the values of the FA parameter in patients with DM2 compared to DM1. The values of MD and RD were significantly higher in 47 tracts in DM1 patients compared to DM2 patients. AD values were significantly higher in all 48 tracts in DM1 patients compared to DM2 patients. There were no tracts with increased MD, AD, or RD values in DM2 patients compared to DM1. Our results indicate diffuse disintegration of white matter pathways in DM patients, especially in the DM1 group. The damage to all types of fibres (association, commissural, and projection) may explain the diversity of clinical symptoms, which were more severe in the DM1 group of patients than in the DM2 group. DTI in patients with DM may help us to understand the neural mechanisms underlying brain involvement during the disease. In future, it may help to identify biomarkers for disease progression and treatment response.

Diffusion tensor imaging in trigeminal neuralgia: beyond the normal morphology

BackgroundTrigeminal neuralgia (TN) is an electric-like recurrent pain of a sudden onset and is localized to the area supplied by the trigeminal nerve, and the patients are usually free in between the attacks. It’s one of the most common causes of facial pain and is commonly induced by mechanical irritation, and there’s strong evidence suggesting an insult at the trigeminal nerve root which is usually caused by a neurovascular compression. The aim of the study was to evaluate the role of diffusion tensor imaging (DTI) in the detection of microstructural changes of normal appearing trigeminal nerve in patients with trigeminal neuralgia and the correlation between DTI parameters and pain severity.ResultsThirty one cases were included in the study (16 patients with TN and 15 healthy controls) underwent MRI with diffusion tensor imaging. The fractional anisotropy (FA) values of the trigeminal nerves were recorded and then comparison between the affected and unaffected sides in TN patients and healthy controls was done, also the degree of FA reduction was correlated with the pain severity in TN groups. The mean FA value of the affected trigeminal nerves was 0.43 ± 0.083, while that of the unaffected sides was 0.56 ± 0.058. The mean FA value of the trigeminal nerves in the healthy controls was 0.54 ± 0.057. A significant statistical differences was found between affected and unaffected sides (P < 0.00001) and between the affected sides and healthy controls (P < 0.0003), while no statistically significant difference was detected between the unaffected side and the healthy controls. A strong negative correlation was found between the pain score and the degree of FA reduction (P < 0.001).ConclusionsDiffusion tensor imaging is a functional MRI technique which can detect the microstructural changes in the normal appearing trigeminal nerves in patients with trigeminal neuralgia with a strong negative correlation between the severity of pain and the degree of FA reduction of the affected trigeminal nerve.

Noninvasive Prediction of Sperm Retrieval Using Diffusion Tensor Imaging in Patients with Nonobstructive Azoospermia.

Microdissection testicular sperm extraction (mTESE) is the first-line treatment plan for nonobstructive azoospermia (NOA). However, studies reported that the overall sperm retrieval rate (SRR) was 43% to 63% among men with NOA, implying that nearly half of the patients fail sperm retrieval. This study aimed to evaluate the diagnostic performance of parameters derived from diffusion tensor imaging (DTI) in predicting SRR in patients with NOA. Seventy patients diagnosed with NOA were enrolled and classified into two groups based on the outcome of sperm retrieval during mTESE: success (29 patients) and failure (41 patients). Scrotal magnetic resonance imaging was performed, and the DTI parameters, including mean diffusivity and fractional anisotropy, were analyzed between groups. The results showed that there was a significant difference in mean diffusivity values between the two groups, and the area under the curve for mean diffusivity was calculated as 0.865, with a sensitivity of 72.2% and a specificity of 97.5%. No statistically significant difference was observed in fractional anisotropy values and sex hormone levels between the two groups. This study demonstrated that the mean diffusivity value might serve as a useful noninvasive imaging marker for predicting the SRR of NOA patients undergoing mTESE.

Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study.

To explore the specific alterations of white matter microstructure in children with attention-deficit/hyperactivity disorder (ADHD) by automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), and to analyze the correlation between white matter abnormality and impairment of executive function. In this prospective study, a total of twenty-seven patients diagnosed with ADHD (20 males, 7 females; mean age of 8.89 ± 1.67 years) and twenty-two healthy control (HC) individuals (11 males, 11 females, mean age of 9.82 ± 2.13 years) were included. All participants were scanned with diffusion kurtosis imaging (DKI) and assessed for executive functions. AFQ and TBSS analysis methods were used to investigate the white matter fiber impairment of ADHD patients, respectively. Axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA) of 17 fiber properties were calculated using the AFQ. The mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MDDKI), axial diffusivity (ADDKI), radial diffusivity (RDDKI) and fractional anisotropy (FADKI) of DKI and AD, RD, MD, and FA of diffusion tensor imaging (DTI) assessed the integrity of the white matter based on TBSS. Partial correlation analyses were conducted to evaluate the correlation between white matter abnormalities and clinical test scores in ADHD while taking age, gender, and education years into account. The analyses were all family-wise error rate (FWE) corrected. ADHD patients performed worse on the Behavior Rating Inventory of Executive Function (BRIEF) test (p < 0.05). Minor variances existed in gender and age between ADHD and HC, but these variances did not yield statistically significant distinctions. There were no significant differences in TBSS for DKI and DTI parameters (p > 0.05, TFCE-corrected). Compared to HC volunteers, the mean AD value of right cingulum bundle (CB_R) fiber tract showed a significantly higher level in ADHD patients following the correction of FWE. As a result of the point-wise comparison between groups, significant alterations (FWE correction, p < 0.05) were mainly located in AD (nodes 36-38, nodes 83-97) and MD (nodes 92-95) of CB_R. There was no significant correlation between white matter diffusion parameters and clinical test scores in ADHD while taking age, gender, and education years into account. The AFQ method can detect ADHD white matter abnormalities in a specific location with greater sensitivity, and the CB_R played a critical role. Our findings may be helpful in further studying the relationship between focal white matter abnormalities and ADHD.

Age-related changes in the healthy adult visual pathway: evidence from diffusion tensor imaging with fixel-based analysis.

Fixel-based analysis (FBA) is anew method that overcomes the technical limitations of diffusion tensor imaging (DTI) by enabling the characterization of multiple fiber populations within avoxel, and provides biologically meaningful indicators. This study aimed to explore age-related changes in the visual pathway in healthy adults and to observe differences in imaging quality between data collected using different b‑values. In this prospective cross-sectional study, brain DTI scans which were collected with more than six uniformly distributed gradient directions and higher b‑values (up to 2000 s/mm2) than traditional DTI were performed in 72healthy adults across the adult lifespan (20-79years). After image preprocessing, FBA was used to process the dataset. At the same time, conventional DTI metrics were also calculated. Pearson's correlation analysis showed that DTI parameters of white matter (optic nerve, optic chiasma, optic tract, and optic radiation) in the optic pathway were correlated with age. FA values were negatively correlated with age, while MD/AD/RD showed apositive correlation (P < 0.05). FBA showed that the index including FD/FC/FDC tended to decline with age (P < 0.05). Linear regression analysis showed alinear relationship between DTI metrics of the dataset collected by b‑values of 1000 and 2000 s/mm2 (P < 0.05). FBA provides auseful method to assess age-related changes in the visual pathway, which is sensitive to diffusion. In addition, the b‑value influences DTI parameters and signal-to-noise ratio of the image.

Magnetic resonance imaging parameters on lacrimal gland in thyroid eye disease: a systematic review and meta-analysis

BackgroundThyroid eye disease is an extrathyroidal manifestation of Graves’ disease and is associated with dry eye disease. This is the first systematic review and meta-analysis to evaluate the role of magnetic resonance imaging lacrimal gland parameters in thyroid eye disease diagnosis, activity grading, and therapeutic responses prediction.MethodsUp to 23 August, 2022, 504 studies from PubMed and Cochrane Library were analyzed. After removing duplicates and imposing selection criteria, nine eligible studies were included. Risk of bias assessment was done. Meta-analyses were performed using random-effect model if heterogeneity was significant. Otherwise, fixed-effect model was used. Main outcome measures include seven structural magnetic resonance imaging parameters (lacrimal gland herniation, maximum axial area, maximum coronal area, maximum axial length, maximum coronal length, maximum axial width, maximum coronal width), and three functional magnetic resonance imaging parameters (diffusion tensor imaging-fractional anisotropy, diffusion tensor imaging-apparent diffusion coefficient or mean diffusivity, diffusion-weighted imaging-apparent diffusion coefficient).ResultsThyroid eye disease showed larger maximum axial area, maximum coronal area, maximum axial length, maximum axial width, maximum coronal width, diffusion tensor imaging-apparent diffusion coefficient/ mean diffusivity, and lower diffusion tensor imaging-fractional anisotropy than controls. Active thyroid eye disease showed larger lacrimal gland herniation, maximum coronal area, diffusion-weighted imaging-apparent diffusion coefficient than inactive. Lacrimal gland dimensional (maximum axial area, maximum coronal area, maximum axial length, maximum axial width, maximum coronal width) and functional parameters (diffusion tensor imaging-apparent diffusion coefficient, diffusion tensor imaging-apparent diffusion coefficient) could be used for diagnosing thyroid eye disease; lacrimal gland herniation, maximum coronal area, and diffusion-weighted imaging-apparent diffusion coefficient for differentiating active from inactive thyroid eye disease; diffusion tensor imaging parameters (diffusion tensor imaging-fractional anisotropy, diffusion tensor imaging-mean diffusivity) and lacrimal gland herniation for helping grading and therapeutic responses prediction respectively.ConclusionsMagnetic resonance imaging lacrimal gland parameters can detect active thyroid eye disease and differentiate thyroid eye disease from controls. Maximum coronal area is the most effective indicator for thyroid eye disease diagnosis and activity grading. There are inconclusive results showing whether structural or functional lacrimal gland parameters have diagnostic superiority. Future studies are warranted to determine the use of magnetic resonance imaging lacrimal gland parameters in thyroid eye disease.

Diffusion tensor imaging of fetal spinal cord: feasibility and gestational-age-related changes.

Diffusion tensor imaging (DTI) of the fetal brain is a relatively new technique that allows evaluation of white matter tracts of the central nervous system throughout pregnancy, as well as in certain pathological conditions. The objectives of this study were to evaluate the feasibility of DTI of the spinal cord in utero and to examine gestational-age (GA)-related changes in DTI parameters during pregnancy. This was a prospective study conducted between December 2021 and June 2022 in the LUMIERE Platform, Necker-Enfants Malades Hospital, Paris, France, as part of the LUMIERE SUR LE FETUS trial. Women with a pregnancy between 18 and 36 weeks of gestation without fetal or maternal abnormality were eligible for inclusion. Sagittal diffusion-weighted scans of the fetal spine were acquired, without sedation, using a 1.5-Tesla magnetic resonance imaging scanner. Theimaging parameters were as follows: 15 non-collinear direction diffusion-weighted magnetic-pulsed gradients with a b-value 700 s/mm2 and one B0 image without diffusion-weighting; slice thickness, 3 mm; field of view (FOV), 36 mm; phase FOV, 1.00; voxel size, 4.5 × 2.8 × 3 mm3 ; number of slices, 7-10; repetition time, 2800 ms; echo time, minimum; and total acquisition time, 2.3 min. DTI parameters, including fractional anisotropy (FA) and apparent diffusion coefficient (ADC), were extracted at the cervical, upper thoracic, lower thoracic and lumbar levels of the spinal cord. Cases with motion degradation and those with aberrant reconstruction of the spinal cord on tractography were excluded. Pearson's correlation analysis was performed to evaluate GA-related changes of DTI parameters during pregnancy. During the study period, 42 pregnant women were included at a median GA of 29.3 (range, 22.0-35.7) weeks. Five (11.9%) patients were not included in the analysis because of fetal movement. Two (4.8%) patients with aberrant tractography reconstruction were also excluded from analysis. Acquisition of DTI parameters was feasible in all remaining cases (35/35). Increasing GA correlated with increasing FA averaged over the entire fetal spinal cord (r, 0.37; P < 0.01), as well as at the individual cervical (r, 0.519; P < 0.01), upper thoracic (r, 0.468; P < 0.01), lower thoracic (r, 0.425; P = 0.02) and lumbar (r, 0.427; P = 0.02) levels. There was no correlation between GA and ADC averaged over the entire spinal cord (r, 0.01; P = 0.99) or at the individual cervical (r, -0.109; P = 0.56), upper thoracic (r, -0.226; P = 0.22), lower thoracic (r, -0.052; P = 0.78) or lumbar (r, -0.11; P = 0.95) levels. This study shows that DTI of the spinal cord is feasible in normal fetuses in typical clinical practice and allows extraction of DTI parameters of the spinal cord. There is a significant GA-related change in FA in the fetal spinal cord during pregnancy, which may result from decreasing water content as observed during myelination of fiber tracts occurring in utero. This study may serve as a basis for further investigation of DTI in the fetus, including research into its potential in pathological conditions that impact spinal cord development. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

White matter microstructural disruption in minimal hepatic encephalopathy: a neurite orientation dispersion and density imaging (NODDI) study.

To evaluate the ability of neurite orientation dispersion and density imaging (NODDI) for detecting white matter (WM) microstructural abnormalities in minimal hepatic encephalopathy (MHE). Diffusion-weighted images, enabling the estimation of NODDI and diffusion tensor imaging (DTI) parameters, were acquired from 20 healthy controls (HC), 22 cirrhotic patients without MHE (NHE), and 15 cirrhotic patients with MHE. Tract-based spatial statistics were used to determine differences in DTI (including fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) and NODDI parameters (including neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISO]). Voxel-wise analyses of correlations between diffusion parameters and neurocognitive performance determined by Psychometric Hepatic Encephalopathy Score (PHES) were completed. MHE patients had extensive NDI reduction and rare ODI reduction, primarily involving the genu and body of corpus callosum and the bilateral frontal lobe, corona radiata, external capsule, anterior limb of internal capsule, temporal lobe, posterior thalamic radiation, and brainstem. The extent of NDI and ODI reduction expanded from NHE to MHE. In both MHE and NHE groups, the extent of NDI change was quite larger than that of FA change. No significant intergroup difference in ISO/MD/AD/RD was observed. Tissue specificity afforded by NODDI revealed the underpinning of FA reduction in MHE. The NDI in left frontal lobe was significantly correlated with PHES. MHE is characterized by diffuse WM microstructural impairment (especially neurite density reduction). NODDI can improve the detection of WM microstructural impairments in MHE and provides more precise information about MHE-related pathology than DTI.