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Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time- and frequency-dependent (restricted) and anisotropic self-diffusion of water. While new designs of time-dependent magnetic field gradient waveforms have enabled disambiguation between different aspects of translational motion that are convolved in traditional MRI methods relying on single pairs of field gradient pulses, data analysis for complex heterogeneous materials remains a challenge. Here, we propose and demonstrate nonparametric distributions of tensor-valued Lorentzian diffusion spectra, or "D(ω) distributions," as a general representation with sufficient flexibility to describe the MRI signal response from a wide range of model systems and biological tissues investigated with modulated gradient waveforms separating and correlating the effects of restricted and anisotropic diffusion. [ABSTRACT FROM AUTHOR]

Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment MRI scans in patients with glioblastoma and to predict overall survival (OS) and progression-free survival (PFS). Materials and Methods This retrospective study included 1397 MRI scans in 1297 patients with glioblastoma, including an internal set of 243 MRI scans (January 2010 to June 2022) for model training and cross-validation and four external test cohorts. Cellular tumor maps were segmented by two radiologists on the basis of imaging, clinical history, and pathologic findings. Multimodal MRI data with perfusion and multishell diffusion imaging were inputted into a nnU-Net DL model to segment cellular tumor. Segmentation performance (Dice score) and performance in distinguishing recurrent tumor from posttreatment changes (area under the receiver operating characteristic curve [AUC]) were quantified. Model performance in predicting OS and PFS was assessed using Cox multivariable analysis. Results A cohort of 178 patients (mean age, 56 years ± 13 [SD]; 116 male, 62 female) with 243 MRI timepoints, as well as four external datasets with 55, 70, 610, and 419 MRI timepoints, respectively, were evaluated. The median Dice score was 0.79 (IQR, 0.53-0.89), and the AUC for detecting residual or recurrent tumor was 0.84 (95% CI: 0.79, 0.89). In the internal test set, estimated cellular tumor volume was significantly associated with OS (hazard ratio [HR] = 1.04 per milliliter; P < .001) and PFS (HR = 1.04 per milliliter; P < .001) after adjustment for age, sex, and gross total resection (GTR) status. In the external test sets, estimated cellular tumor volume was significantly associated with OS (HR = 1.01 per milliliter; P < .001) after adjustment for age, sex, and GTR status. Conclusion A DL model incorporating advanced imaging could accurately segment enhancing and nonenhancing cellular tumor, distinguish recurrent or residual tumor from posttreatment changes, and predict OS and PFS in patients with glioblastoma. Keywords: Segmentation, Glioblastoma, Multishell Diffusion MRI Supplemental material is available for this article. © RSNA, 2024.

Cyclic fluctuations in hypothalamic-pituitary-gonadal axis (HPG-axis) hormones exert powerful behavioral, structural, and functional effects through actions on the mammalian central nervous system. Yet, very little is known about how these fluctuations alter the structural nodes and information highways of the human brain. In a study of 30 naturally cycling women, we employed multidimensional diffusion and T1-weighted imaging during three estimated menstrual cycle phases (menses, ovulation, and mid-luteal) to investigate whether HPG-axis hormone concentrations co-fluctuate with alterations in white matter (WM) microstructure, cortical thickness (CT), and brain volume. Across the whole brain, 17β-estradiol and luteinizing hormone (LH) concentrations were directly proportional to diffusion anisotropy (μFA; 17β-estradiol: β1 = 0.145, highest density interval (HDI) = [0.211, 0.4]; LH: β1 = 0.111, HDI = [0.157, 0.364]), while follicle-stimulating hormone (FSH) was directly proportional to CT (β1 = 0 .162, HDI = [0.115, 0.678]). Within several individual regions, FSH and progesterone demonstrated opposing relationships with mean diffusivity (Diso) and CT. These regions mainly reside within the temporal and occipital lobes, with functional implications for the limbic and visual systems. Finally, progesterone was associated with increased tissue (β1 = 0.66, HDI = [0.607, 15.845]) and decreased cerebrospinal fluid (CSF; β1 = -0.749, HDI = [-11.604, -0.903]) volumes, with total brain volume remaining unchanged. These results are the first to report simultaneous brain-wide changes in human WM microstructure and CT coinciding with menstrual cycle-driven hormone rhythms. Effects were observed in both classically known HPG-axis receptor-dense regions (medial temporal lobe, prefrontal cortex) and in other regions located across frontal, occipital, temporal, and parietal lobes. Our results suggest that HPG-axis hormone fluctuations may have significant structural impacts across the entire brain.

Neurocognitive aging researchers are increasingly focused on the locus coeruleus, a neuromodulatory brainstem structure that degrades with age. With this rapid growth, the field will benefit from consensus regarding which magnetic resonance imaging (MRI) metrics of locus coeruleus structure are most sensitive to age and cognition. To address this need, the current study acquired magnetization transfer- and diffusion-weighted MRI images in younger and older adults who also completed a free recall memory task. Results revealed significantly larger differences between younger and older adults for maximum than average magnetization transfer-weighted contrast (MTC), axial than mean or radial single-tensor diffusivity (DTI), and free than restricted multi-compartment diffusion (NODDI) metrics in the locus coeruleus; with maximum MTC being the best predictor of age group. Age effects for all imaging modalities interacted with sex, with larger age group differences in males than females for MTC and NODDI metrics. Age group differences also varied across locus coeruleus subdivision for DTI and NODDI metrics, and across locus coeruleus hemispheres for MTC. Within older adults, however, there were no significant effects of age on MTC or DTI metrics, only an interaction between age and sex for free diffusion. Finally, independent of age and sex, higher restricted diffusion in the locus coeruleus was significantly related to better (lower) recall variability, but not mean recall. Whereas MTC has been widely used in the literature, our comparison between the average and maximum MTC metrics, inclusion of DTI and NODDI metrics, and breakdowns by locus coeruleus subdivision and hemisphere make important and novel contributions to our understanding of the aging of locus coeruleus structure.

The short association fibers or U-fibers travel in the superficial white matter (SWM) beneath the cortical layer. While the U-fibers play a crucial role in various brain disorders, there is a lack of effective tools to reconstruct their highly curved trajectory from diffusion MRI (dMRI). In this work, we propose a novel surface-based framework for the probabilistic tracking of fibers on the triangular mesh representation of the SWM. By deriving a closed-form solution to transform the spherical harmonics (SPHARM) coefficients of 3D fiber orientation distributions (FODs) to local coordinate systems on each triangle, we develop a novel approach to project the FODs onto the tangent space of the SWM. After that, we utilize parallel transport to realize the intrinsic propagation of streamlines on SWM following probabilistically sampled fiber directions. Our intrinsic and surface-based method eliminates the need to perform the necessary but challenging sharp turns in 3D compared with conventional volume-based tractography methods. Using data from the Human Connectome Project (HCP), we performed quantitative comparisons to demonstrate the proposed algorithm can more effectively reconstruct the U-fibers connecting the precentral and postcentral gyrus than previous methods. Quantitative validations were then performed on post-mortem MRIs to show the reconstructed U-fibers from our method more faithfully follow the SWM than volume-based tractography. Finally, we applied our algorithm to study the parietal U-fiber connectivity changes in autosomal dominant Alzheimers disease (ADAD) patients and successfully detected significant associations between U-fiber connectivity and disease severity.

BACKGROUND: Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity. METHODS AND RESULTS: Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (β per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures. CONCLUSIONS: These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.

BACKGROUND: Sensory processing dysfunction (SPD) is linked to altered white matter (WM) microstructure in school-age children. Sensory over-responsivity (SOR), a form of SPD, affects at least 2.5% of all children and has substantial deleterious impact on learning and mental health. However, SOR has not been well studied using microstructural imaging such as diffusion MRI (dMRI). Since SOR involves hypersensitivity to external stimuli, we test the hypothesis that children with SOR require compensatory neuroplasticity in the form of superior WM microstructural integrity to protect against internalizing behavior, leaving those with impaired WM microstructure vulnerable to somatization and depression. METHODS: Children ages 8-12 years old with neurodevelopmental concerns were assessed for SOR using a comprehensive structured clinical evaluation, the Sensory Processing 3 Dimensions Assessment, and underwent 3 Tesla MRI with multishell multiband dMRI. Tract-based spatial statistics was used to measure diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics from global WM and nineteen selected WM tracts. Correlations of DTI and NODDI measures with measures of somatization and emotional disturbance from the Behavioral Assessment System for Children, 3rd edition (BASC-3), were computed in the SOR group and in matched children with neurodevelopmental concerns but not SOR. RESULTS: Global WM fractional anisotropy (FA) is negatively correlated with somatization and with emotional disturbance in the SOR group but not the non-SOR group. Also observed in children with SOR are positive correlations of radial diffusivity (RD) and free water fraction (FISO) with somatization and, in most cases, emotional disturbance. These effects are significant in boys with SOR, whereas the study is underpowered for girls. The most affected white matter are medial lemniscus and internal capsule sensory tracts, although effects of SOR are observed in many cerebral, cerebellar, and brainstem tracts. CONCLUSION: White matter microstructure is related to affective behavior in children with SOR.

BackgroundHigh b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.MethodsOne hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).ResultsWithin the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.ConclusionsDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

The article discusses the imaging findings of intracerebral infection after deep brain stimulation in pediatric cases, highlighting the importance of prompt diagnosis and treatment. The study presents four original pediatric cases and reviews 24 adult cases, emphasizing the need for careful confirmation of infection due to symptom reemergence post-explantation. The article underscores the underreporting of intracerebral DBS infection, particularly in children, and provides insights into clinical and neuroimaging findings to guide future diagnoses and treatments. [Extracted from the article]

Purpose Methods Results Conclusion Apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance imaging (DWI MRI) provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to image artifacts, leading to inaccurate ADC measurements. This study aims to develop a deep learning framework to synthesize ADC maps from multi‐parametric MR images.We proposed the multiparametric residual vision transformer model (MPR‐ViT) that leverages the long‐range context of vision transformer (ViT) layers along with the precision of convolutional operators. Residual blocks throughout the network significantly increasing the representational power of the model. The MPR‐ViT model was applied to T1w and T2‐fluid attenuated inversion recovery images of 501 glioma cases from a publicly available dataset including preprocessed ADC maps. Selected patients were divided into training (N = 400), validation (N = 50), and test (N = 51) sets, respectively. Using the preprocessed ADC maps as ground truth, model performance was evaluated and compared against the Vision Convolutional Transformer (VCT) and residual vision transformer (ResViT) models with the peak signal‐to‐noise ratio (PSNR), structural similarity index measure (SSIM), and mean squared error (MSE).The results are as follows using T1w + T2‐FLAIR MRI as inputs: MPR‐ViT—PSNR: 31.0 ± 2.1, MSE: 0.009 ± 0.0005, SSIM: 0.950 ± 0.015. In addition, ablation studies showed the relative impact on performance of each input sequence. Both qualitative and quantitative results indicate that the proposed MR‐ViT model performs favorably against the ground truth data.We show that high‐quality ADC maps can be synthesized from structural MRI using a MPR‐ViT model. Our predicted images show better conformality to the ground truth volume than ResViT and VCT predictions. These high‐quality synthetic ADC maps would be particularly useful for disease diagnosis and intervention, especially when ADC maps have artifacts or are unavailable. [ABSTRACT FROM AUTHOR]

Ex vivo studies of the brain are often employed as experimental systems in neuroscience. In general, brains for ex vivo MRI studies are usually fixed with paraformaldehyde to preserve molecular structure and prevent tissue destruction during long-term storage. As a result, fixing brain tissue causes microstructural changes and a decrease in brain volume. Therefore, the purpose of this study was to investigate the regional effect of brain volume and microstructural changes on the restricted diffusion of water molecules in the common marmoset brain using in vivo and ex vivo brains from the same individual. We used 9.4T magnetic resonance imaging and also compared the T2-weighted images and diffusion-weighted imaging (DWI) data between in vivo and ex vivo brains to investigate changes in brain volume and diffusion of water molecules in 12 common marmosets. We compared fractional anisotropy, mean diffusivity, AD (axial diffusivity), and radial diffusivity values in white matter and gray matter between in vivo and ex vivo brains. We observed that AD showed the strongest correlation with regional volume changes in gray matter. The results showed a strong correlation between AD and changes in brain volume. By comparing the in vivo and ex vivo brains of the same individual, we identified significant correlations between the local effects of perfusion fixation on microstructural and volumetric changes of the brain and alterations in the restricted diffusion of water molecules within the brain. These findings provide valuable insights into the complex relationships between tissue fixation, brain structure, and water diffusion properties in the marmoset brain. [ABSTRACT FROM AUTHOR]

ObjectiveMethodsResultsConclusionComatose survivors of cardiac arrest (CA) pose a complex challenge for physicians reliant on imperfect studies to determine the extent of neurologic injury. Clinically available imaging is frequently relied upon despite limited sensitivity. We conducted a prospective pilot study comparing diffusion kurtosis imaging (DKI)-MRI and somatosensory evoked potentials (SSEPs) in comatose survivors of CA to investigate the benefit of utilizing higher diffusion b-values to enhance prediction of arousal recovery.Survivors of CA admitted from June 2015 through November 2019 with DKI-MRI and SSEPs were evaluated. Advanced diffusion metrics differentiating present or absent SSEPs were analyzed using whole-brain voxelwise nonparametric permutation inference with threshold-free cluster enhancement.Twenty survivors of CA were included, mean age 52, 45% female and out-of-hospital arrests accounting for 75% of cases. Baseline characteristics and examination findings were not statistically different between groups at admission or 48 h after achieving normothermia. A decrease in mean diffusivity (MD) and increase in mean kurtosis (MK) was demonstrated in subjects without arousal recovery potential, most prominently in the posterior mesial temporal, parietal and occipital lobes.DKI-MRI may improve early arousal recovery prediction during the immediate phase of post-CA care, especially where SSEPs are unavailable or unreliable. [ABSTRACT FROM AUTHOR]

Background: Neuronal Intranuclear Inclusion Disease (NIID) is a neurodegenerative disorder characterized by the formation of eosinophilic inclusions in the neurons, visceral and skin cells. The cause is associated with the GGC nucleotide repeat expansion in the NOTCH2NLC gene. The imaging hallmark of NIID is hyperintensities on diffusion-weighted imaging (DWI) at the corticomedullary junction. Clinical manifestations of NIID are highly heterogeneous. Here, we report a case of NIID presenting with acute-onset dementia and cortical edema. Case presentation: We describe an elderly male patient who presented with sudden dementia within a day. Considering the abrupt onset and the stroke history, we initially diagnosed vascular disease. However, further imaging revealed cortical edema in the temporo-parieto-occipital lobes. Blood and cerebrospinal fluid tests ruled out immunological, metabolic, infectious, or neoplastic etiologies. Genetic testing ultimately confirmed the diagnosis of NIID. Intravenous immunoglobulin (IVIG) therapy did not improve the patient's symptoms; However, about 1 month after treatment, spontaneous improvement was observed. It is noteworthy that 22 months before the onset of cognitive impairment, the patient's MRI for headaches already exhibited the typical imaging lesions of this disease in the cerebellum paravermal region. Conclusion: Patients with encephalopathy syndrome exhibiting imaging features resembling mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome or Creutzfeldt-Jakob disease should consider the NIID as differential diagnosis. Chronic headaches and symmetric lesions in the cerebellar paravermal region on MRI may be noteworthy indicators of NIID during non-episodic phases. [ABSTRACT FROM AUTHOR]

Background: The pancreas plays an important role in the nutrition and metabolism of the whole body. Many disease processes including obesity, diabetes mellitus (DM), acute or chronic pancreatitis, and pancreatic carcinoma result in abnormality of pancreas morphology and function. Magnetic resonance imaging (MRI) provides quantitative parameters including T1, T2, and apparent diffusion coefficient (ADC) values for evaluating normal and abnormal pancreas. Based on the normal range of these quantitative parameters, pancreatic abnormality could be detected early. However, the range and the relationship of T1, T2, and ADC values with gender and age groups using the same dataset have not been explored. Purpose: To establish the ranges of MRI tissue and functional parameters, including T1, T2, and ADC values, in healthy adult pancreas and their correlations with gender, subregion, and age. Materials and methods: The T1, T2, and ADC values of healthy pancreas in 86 adults were measured using a 3.0-T MRI scanner. The average T1, T2, and ADC values were obtained in the whole pancreas and subregions (head, neck, body, and tail). Their correlations with gender and age were investigated. Results: The T1, T2, and ADC values of the whole pancreas from all subjects were 870.07 ± 61.86 ms, 44.07 ± 6.14 ms, and 1.072 ± 0.212 × 10−3 mm2/s, respectively. T2 values were significantly different between genders (P < 0.05). No significant differences were found between subregions. The T1, T2, and ADC values differed significantly among the age groups (P < 0.05). The T1 value revealed a moderately positive correlation, while the T2 and ADC values displayed negative correlations with age (r = 0.31, −0.45, and −0.39, respectively). The combination of T1, T2, and ADC values achieved the highest AUC value and showed a significant difference compared to T1, T2, and ADC values alone in predicting age older than 45 years. Conclusion: This study established the normal ranges of T1, T2, and ADC. We found that T2 is different between men and women, and T1, T2, and ADC are age-dependent. These results could be useful for quantitative MRI of pancreatic disease. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion Infected pancreatic necrosis (IPN) is a major determinant of mortality in acute pancreatitis (AP). Non‐invasive diagnosis of IPN could guide the intervention in AP. We aimed to investigate the role of non‐invasive methods like diffusion weighted magnetic resonance imaging (DW‐MRI) and clinico‐laboratory parameters as predictors of IPN.Prospective evaluation for predictors of IPN by diffusion restriction (DR) on DW‐MRI and clinico‐laboratory parameters was performed.Out of 39 patients included, 31 were analysed after exclusion. Twenty‐six (83.8%) patients had moderately severe AP, and the rest had severe disease. They were categorized into Group A: patients with documented infection after intervention (n = 17) and Group B: successfully managed without intervention or negative culture after intervention (n = 14). On univariate analysis, Group A had significantly more incidence of fever (P = 0.020), persistent unwellness (P = 0.003), elevated neutrophil count (P = 0.007), lymphocyte count (P = 0.007), neutrophil lymphocyte ratio (NLR) (P = 0.028), DR on DW‐MRI (P = 0.001) and low apparent diffusion coefficient (ADC) (P = 0.086). Multivariate analysis revealed DR on DW‐MRI (P = 0.004) and NLR (P = 0.035) as significant predictors of IPN, among other factors. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DW‐MRI were 94.1%, 78.6%, 91.66%, and 84.21%, respectively. The area under curve of NLR on the ROC plot was 0.85 and the best cutoff was >3.5, with sensitivity, specificity, PPV, and NPV of 70.6%, 78.6%, 80%, and 68.7% respectively.DW‐MRI and NLR are promising non‐invasive tools for accurate prediction of IPN and hence can guide the need for intervention in acute pancreatitis. [ABSTRACT FROM AUTHOR]

Objective: Pediatric posterior fossa tumors pose diagnostic challenges due to their diverse histopathological features and variable clinical presentations. Conventional magnetic resonance imaging (MRI) serves as the initial diagnostic tool; however, additional modalities, such as diffusion-weighted imaging (DWI), are essential for refining tumor classification. This retrospective single-center study aimed to evaluate the diagnostic utility of apparent diffusion coefficient (ADC) parameters in distinguishing between the most common pediatric posterior fossa tumors. Materials and Methods: Fifty-nine patients under the age of 18 (27 females and 32 males) with histopathologically diagnosed primary posterior fossa tumors underwent pre-treatment conventional and diffusion MRI. Apparent diffusion coefficient values were measured from solid tumor regions and normal cerebellar parenchyma, with subsequent calculation of tumor/normal cerebellar ADC ratios. Results: The median ADC values for pilocytic astrocytomas (PAs) were 1786.2 ×10−6 mm² /s, ependymomas 1144.9 × 10−6 mm² /s, and for medulloblastomas 666.1 × 10−6 mm2 /s were significantly different (P < .001 for all three). Similarly, the median ADC ratios demonstrated discriminatory potential, with PAs showing the highest ratio (2.46), followed by ependymomas (1.55) and medulloblastomas (0.89) (P < .001 for all three). Receiver operating characteristic analysis revealed distinct ADC cutoffs and ratios for differentiating all tumor types from each other. Conclusion: Despite limitations, such as a small cohort size and different MRI protocols, our results show that ADC metrics are especially useful for distinguishing between the most common pediatric posterior fossa tumors. We recommend that future studies integrate advanced imaging techniques and larger cohorts to improve diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Peak width of skeletonized mean diffusivity (PSMD) is an emerging diffusion-MRI based marker to study subtle early alterations to white matter microstructure. We assessed PSMD over the clinical continuum in Dutch-type hereditary CAA (D-CAA) and its association with other CAA-related MRI-markers and cognitive symptoms. We included (pre)symptomatic D-CAA mutation-carriers and calculated PSMD from diffusion-MRI data. Associations between PSMD-levels, cognitive performance and CAA-related MRI-markers were assessed with linear regression models. We included 59 participants (25/34 presymptomatic/symptomatic; mean age 39/58 y). PSMD-levels increased with disease severity and were higher in symptomatic D-CAA mutation-carriers (median [range] 4.90 [2.77–9.50]mm2/s × 10−4) compared with presymptomatic mutation-carriers (2.62 [1.96–3.43]mm2/s × 10−4) p = <0.001. PSMD was positively correlated with age, CAA-SVD burden on MRI (adj.B [confidence interval] = 0.42 [0.16–0.67], p = 0.002), with number of cerebral microbleeds (adj.B = 0.30 [0.08–0.53], p = 0.009), and with both deep (adj.B = 0.46 [0.22–0.69], p = <0.001) and periventricular (adj.B = 0.38 [0.13–0.62], p = 0.004) white matter hyperintensities. Increasing PSMD was associated with decreasing Trail Making Test (TMT)-A performance (B = −0.42 [−0.69–0.14], p = 0.04. In D-CAA mutation-carriers microstructural white matter damage is associated with disease phase, CAA burden on MRI and cognitive impairment as reflected by a decrease in information processing speed. PSMD, as a global measure of alterations to the white matter microstructure, may be a useful tool to monitor disease progression in CAA. [ABSTRACT FROM AUTHOR]

Background: Epidermoid cysts are benign, slow growing extra-axial lesions most commonly found in the cerebellopontine angle that have a characteristic imaging pattern of restricted diffusion on diffusion-weighted imaging (DWI). Methods: A 10-year-old male with a history of asthma and diabetes was found to have a lesion within the fourth ventricle on a magnetic resonance imaging (MRI) brain study. MRI showed a well-circumscribed vermian lesion without contrast enhancement or restricted diffusion with mild hydrocephalus. He was referred to the neurosurgical service once he acutely developed symptoms of dizziness. He underwent a gross-total resection of the lesion on which histopathology confirmed an epidermoid cyst. Results: Here, we report a case of an atypical epidermoid cysts found in the midline of the fourth ventricle without restricted diffusion on MRI. Conclusion: Avid restricted-diffusion on DWI is usually pathognomonic for an epidermoid cyst when evaluating an extra-axial lesion, yet we report the second case in the literature of an epidermoid cyst without this classical imaging characteristic. [ABSTRACT FROM AUTHOR]

Acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) is the most common encephalopathy syndrome among Japanese children. We report, for the first time, a case of AESD, in which magnetic resonance imaging (MRI) showed no diffusion abnormalities, but hyperperfusion was detected by arterial spin labelling (ASL). A previously healthy Japanese 1-year and 5-month-old boy was transferred to our hospital due to a consciousness disorder after >60 min of status epilepticus on the first day of fever. Brain MRI on the first day revealed no abnormal findings. On the fourth day, focal seizures of the left upper and lower limbs were observed. Thereafter, the patient's condition progressed without seizures. Diffusion-weighted imaging (DWI) on day 6 showed no abnormal findings, including a bright tree appearance. However, ASL showed hyperperfusion in the frontoparietal lobes. MRI scans on days 19 and 39 revealed that the hyperperfusion lesions on day 6 had transitioned to hypoperfusion on ASL and displayed high signal intensity on T2-weighted and fluid-attenuated inversion recovery imaging. Cerebral atrophy was also observed. Based on the clinical course and imaging findings during the chronic phase, a diagnosis of AESD was made. ASL may be more sensitive than DWI for detecting AESD lesions and should be performed in children with suspected AESD. [ABSTRACT FROM AUTHOR]

Objectives: Using magnetic resonance imaging (MRI), we analysed the clinical manifestations of granulomatous lobular mastitis (GLM) before and after treatment with traditional Chinese medicine (TCM). Methods: This was a retrospective study. Clinical manifestations and imaging features of patients with biopsy-proven GLM before and after treatment were retrospectively analysed from April 2021 to April 2023 at Xiyuan Hospital, China Academy of Chinese Medical Sciences. Results: Among 29 women of childbearing age (mean age, 34.3±3.6 years), Compared to pre-therapy, the number of patients with lumps, ruptures, pain, and menstrual irregularities was significantly reduced (P < 0.05). The Chinese medicine staging demonstrated a transition from bulk to ulcerated (P=0.041). Pre- and post-treatment MRI changes included lesion number, distribution, maximal diameter, time-signal intensity curves (TIC), apparent diffusion coefficients (ADC), and BI-RADS categories 3 and 4a (all P<0.05). Furthermore, substantial changes were seen in chest wall invasion, nipple discharge, increased feeding arteries, and skin edema (all P<0.05). Conclusion: Combining internal and external Traditional Chinese Medicine (TCM) therapy proved successful for GLM. A reliable assessment of therapy efficacy is provided by MRI examination of lesion changes before and after treatment. [ABSTRACT FROM AUTHOR]

Objectives: To compare the image quality of 1.5T and 3T prostate MRIs of the same post-hip arthroplasty patients, with a specific focus on the degree of susceptibility artifacts. Methods: This single-center retrospective study included post-hip arthroplasty patients who underwent 1.5T prostate MRIs between 2021 and 2023, as well as comparative 3T prostate MRIs. Three blinded abdominal radiologists retrospectively reviewed their diffusion-weighted imaging (DWI, 50 s/mm2), T2-weighted imaging (T2WI), and dynamic contrast-enhanced imaging (DCE) to evaluate the image quality. The degree of susceptibility artifacts was categorized using a three-point scale, with 3 indicating the least artifact and 1 indicating the most. Image quality was also evaluated using Prostate Imaging Quality (PI-QUAL) version 2. The median of the three raters' scores was compared between 1.5T and 3T prostate MRIs using the Wilcoxon signed-rank test. The inter-rater agreement was evaluated using the multi-rater generalized kappa. Results: Twenty pairs of 1.5T and 3T prostate MRI examinations from 20 unique patients were included. The DWI susceptibility artifact score at 1.5T was significantly higher than at 3T (mean score ± standard deviation, 2.80 ± 0.41 vs. 2.35 ± 0.93, p = 0.014). In contrast, no significant differences were observed in the susceptibility artifact scores in T2WI and DCE, or in the PI-QUAL score. The inter-reader agreement in the susceptibility artifact score was moderate (multi-rater generalized kappa: 0.60) in DWI, perfect in T2WI (not applicable), and substantial (0.65) in DCE. The inter-reader agreement was fair (0.27) in the PI-QUAL score. Conclusion: Using 1.5T scanners may be preferable to reduce susceptibility artifacts from hip prostheses in DWI. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the ability of the Intravoxel Incoherent Motion (IVIM) and monoexponentially ADC in renal allograft function in the early and late phases of transplantation, and to predict their effectiveness in discrimination of the graft pathology. Methods: This is a prospective study included participants scanned with quantitative diffusion and perfusion sequences on a 3-T MR scanner (Philips, Ingenia); the ADC and IVIM parameters; were calculated. Correlations and regression analysis with the eGFR, transplantation periods, and pathology were assessed. Results: This study included 105 renal allograft recipients (85 males, and 20 females with mean age = 32.4 ± 11.9 years and age range = 22–61 years). There was a significant positive correlation between the whole parameters of the ADC and IVIM with eGFR however, the cortical parameters showed higher significant correlation coefficients (p < 0.001). Regression analysis revealed the most significant model can predict eGFR groups included cortical pseudo diffusion (D*) and cortical ADC (p < 0.001). In graft dysfunction eGFR was 61.5 ml/min and normal graft was 64 ml/min. This model demonstrates a high performance of an AUC 96% [0.93–0.97]. In the late transplantation, there is a higher correlation with D* compared to ADC, p-values = 0.001. Conclusion: IVIM and ADC Values are significant biomarkers for renal allograft function assessment, cortical ADC, and D* had the highest performance even in situations with mild impairment that is not affect the eGFR yet as cases of proteinuria with normal eGFR. Furthermore, D* is superior to ADC in the late assessment of the renal transplant. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the imaging features of pancreatic ductal adenocarcinoma (PDAC) with histological large duct pattern. Methods: Our study included 37 patients (mean age, 66.5 years; 22 women) with surgically proven PDAC with histological large duct pattern, whose imaging features were classified into four types: Type I, solid mass; Type II, predominantly cystic mass with intracystic solid components; Type III, predominantly solid mass with intratumoral cysts; and Type IV, solid mass with peritumoral retention cysts or pseudocysts. Two radiologists independently analyzed both CT and MRI images for the morphological type, presence of abrupt main pancreatic duct (MPD) cutoff, adjacent vascular invasion, diffusion restriction, and reached consensus. Results: On CT, 26 patients (70.3%) had Type I tumors, five (13.5%) had Type II, three (8.1%) had Type III, and three (8.1%) had Type IV. Among the 26 patients with Type I tumors on CT, 16 had tumors with multiple intratumoral cysts within the solid mass on MRI and were subsequently classified as Type III. Accordingly, 10 patients (27.0%) were classified as Type I, five (13.5%) as Type II, 19 (51.7%) as Type III, and three (8.1%) as Type IV on MRI. Of the 37 patients, 27 (73.0%) had an abrupt MPD cutoff, 15 (40.5%) had adjacent vascular invasion, and 25 (67.6%) had diffusion restriction on MRI. Conclusions: Predominantly solid pancreatic masses with small intratumoral cysts visualized on MRI may be a characteristic imaging finding of PDAC with histological large duct pattern, and differentiate it from conventional PDAC or other cystic pancreatic tumors. Clinical relevance statement: Radiologists should be familiar with the various imaging features of PDAC with histological large duct pattern and should be aware that it may mimic other solid or cystic tumors of the pancreas. Key Points: Imaging features of pancreatic ductal adenocarcinoma with histological large duct pattern can be classified into four types. This pathology more frequently appears as a predominantly solid mass with intratumoral cysts on MRI than on CT. Adding MRI to CT may help identify pancreatic ductal adenocarcinoma with histological large duct pattern. [ABSTRACT FROM AUTHOR]

Objectives: To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC). Methods: Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors. Results: Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = −0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = −0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02). Conclusions: Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment. Clinical relevance statement: Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy. Key Points: Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment. [ABSTRACT FROM AUTHOR]

Objectives: Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the value of diffusion-weighted imaging (DWI) for predicting pTERT mutation status in WHO grade IV glioma. Methods: MRI data and molecular information were obtained for 266 patients with WHO grade IV glioma at the hospital and divided into training and validation sets. The ratio of training to validation set was approximately 10:3. We trained the same residual convolutional neural network (ResNet) for each MR modality, including structural MRIs (T1-weighted, T2-weighted, and contrast-enhanced T1-weighted) and DWI*, to compare the predictive capacities between DWI and conventional structural MRI. We also explored the effects of different regions of interest on pTERT mutation status prediction outcomes. Results: Structural MRI modalities poorly predicted the pTERT mutation status (accuracy = 51%-54%; area under the curve [AUC]=0.545-0.571), whereas DWI combined with its apparent diffusive coefficient maps yielded the best predictive performance (accuracy = 85.2%, AUC = 0.934). Including the radiological and clinical characteristics did not further improve the performance for predicting pTERT mutation status. The entire tumour volume yielded the best prediction performance. Conclusions: DWI technology shows promising potential for predicting pTERT mutations in WHO grade IV glioma and should be included in the MRI protocol for WHO grade IV glioma in clinical practice. Advances in knowledge: This is the first large-scale model study to validate the predictive value of DWI for pTERT in WHO grade IV glioma. [ABSTRACT FROM AUTHOR]

Objectives: To compare prostate monoparametric MRI (monoMRI), which uses only diffusion-weighted imaging (DWI), with biparametric (bpMRI) and multiparametric MRI (mpMRI) in detecting clinically significant cancer (CSC) and to evaluate the effect of the combination of monoMRI results and prostate-specific antigen (PSA) level. Methods: In this study, 193 patients (average age 70.5 years; average PSA 7.9 ng/mL) underwent prebiopsy MRI and subsequent prostate biopsy from January 2020 to February 2022. Two radiologists independently reviewed the 3 MRI protocols using the Prostate Imaging Reporting and Data System (PI-RADS). Interreader agreement was assessed using the intraclass correlation coefficient (ICC), and diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. The Youden index was used to determine the new cutoff value of PSA for detecting CSCs in patients with negative monoMRI results. Results: CSC was confirmed in 109 patients (56.5%). The interreader agreement on monoMRI (ICC = 0.798) was comparable to that on bpMRI and mpMRI (ICC = 0.751 and 0.714, respectively). ROC curve analysis of the 3 protocols revealed no difference in detecting CSCs (P > 0.05). Applying a new PSA cutoff value (9.5 and 7.4 ng/mL, respectively) in monoMRI-negative patients improved the sensitivity of monoMRI from 89.9% to 96.3% for Reader 1, and from 95.4% to 99.1% for Reader 2. Conclusions: MonoMRI based solely on DWI demonstrated similar diagnostic performance to bpMRI and mpMRI in detecting CSCs, and the combination of PSA level with monoMRI has the potential to effectively triage patients with a high likelihood of CSCs. Advances in knowledge: Monoparametric MRI conducted only with diffusion-weighted imaging (DWI), may show comparable performance to biparametric and multiparametric MRI in detecting clinically significant prostate cancer. In patients with negative monoparametric MRI results, implementing a new PSA cutoff value to determine the need for a biopsy could decrease the number of missed prostate cancer. [ABSTRACT FROM AUTHOR]

Objective: Glymphatic system is a recently discovered macroscopic waste clearance system associated with numerous neurological diseases. However, little is known about glymphatic system development in neonates. We sought to evaluate diffusion along the perivascular space (ALPS) index, a proxy for glymphatic system function, in neonates and investigate its potential associations with maturation, sex, and preterm birth. Methods: Diffusion magnetic resonance imaging (MRI) data in 418 neonates, including 92 preterm neonates (57 males) and 326 term neonates (175 males), from the Developing Human Connectome Project were used for evaluating ALPS index. Linear regression modeling was performed to assess group differences in the ALPS index according to preterm birth and sex. Pearson's and partial correlation analysis were performed to assess the association between the ALPS index and gestational age (GA) as well as postmenstrual age (PMA) at MRI. Moderation analysis was performed to assess the moderation effect of preterm birth on the relationship between the ALPS index and PMA. Results: Compared to term neonates, preterm neonates exhibited lower ALPS indices (p < 0.001). The ALPS index positively correlated with PMA (p = 0.004) and GA (p < 0.001). Preterm birth (p = 0.013) had a significant moderation effect on the relationship between the ALPS index and PMA. Sex had no significant direct effect (p = 0.639) or moderation effect (p = 0.333) on ALPS index. Interpretation: Glymphatic system development is a dynamic process in neonates, which can be moderated by preterm birth, the ALPS index could serve as a sensitive biomarker for monitoring this process. ANN NEUROL 2024;96:970–980 [ABSTRACT FROM AUTHOR]

Chronic pain is common in young people and can have a major life impact. Despite the burden of chronic pain, mechanisms underlying chronic pain development and persistence are still poorly understood. Specifically, white matter (WM) connectivity has remained largely unexplored in pediatric chronic pain. Using diffusion-weighted imaging, this study examined WM microstructure in adolescents (age M 5 15.8 years, SD 5 2.8 years) with chronic pain (n 5 44) compared with healthy controls (n 5 24). Neurite orientation dispersion and density imaging modeling was applied, and voxel-based whole-white-matter analyses were used to obtain an overview of potential alterations in youth with chronic pain and tract-specific profile analyses to evaluate microstructural profiles of tracts of interest more closely. Our main findings are that (1) youth with chronic pain showed widespread elevated orientation dispersion compared with controls in several tracts, indicative of less coherence; (2) signs of neurite density tract-profile alterations were observed in several tracts of interest, with mainly higher density levels in patients; and (3) several WM microstructural alterations were associated with pain catastrophizing in the patient group. Implicated tracts include both those connecting cortical and limbic structures (uncinate fasciculus, cingulum, anterior thalamic radiation), which were associated with pain catastrophizing, as well as sensorimotor tracts (corticospinal tract). By identifying alterations in the biologically informative WM microstructural metrics orientation dispersion and neurite density, our findings provide important and novel mechanistic insights for understanding the pathophysiology underlying chronic pain. Taken together, the data support alterations in fiber organization as a meaningful characteristic, contributing process to the chronic pain state. [ABSTRACT FROM AUTHOR]

The editorial "Towards multi-modal, multi-species brain atlases: part two" discusses the era of big data in neuroanatomy, with advancements in data collection and analysis across various species. The article highlights challenges in sharing methods and results due to specialized techniques and terminology. It also emphasizes the importance of frameworks that integrate diverse data types and species. The special issue of Brain Structure and Function aims to bring together researchers working on these issues, showcasing contributions that range from connectivity blueprints to whole-brain atlases in different species. The article underscores the significance of comparative neuroanatomy in understanding brain organization and evolution. [Extracted from the article]

Diffusion MRI tractography (dMRI) has fundamentally transformed our ability to investigate white matter pathways in the human brain. While long-range connections have extensively been studied, superficial white matter bundles (SWMBs) have remained a relatively underexplored aspect of brain connectivity. This study undertakes a comprehensive examination of SWMB connectivity in both the human and chimpanzee brains, employing a novel combination of empirical and geometric methodologies to classify SWMB morphology in an objective manner. Leveraging two anatomical atlases, the Ginkgo Chauvel chimpanzee atlas and the Ginkgo Chauvel human atlas, comprising respectively 844 and 1375 superficial bundles, this research focuses on sparse representations of the morphology of SWMBs to explore the little-understood superficial connectivity of the chimpanzee brain and facilitate a deeper understanding of the variability in shape of these bundles. While similar, already well-known in human U-shape fibers were observed in both species, other shapes with more complex geometry such as 6 and J shapes were encountered. The localisation of the different bundle morphologies, putatively reflecting the brain gyrification process, was different between humans and chimpanzees using an isomap-based shape analysis approach. Ultimately, the analysis aims to uncover both commonalities and disparities in SWMBs between chimpanzees and humans, shedding light on the evolution and organization of these crucial neural structures. [ABSTRACT FROM AUTHOR]

Non-human primates are extensively used in neuroscience research as models of the human brain, with the rhesus macaque being a prominent example. We have previously introduced a set of tractography protocols (XTRACT) for reconstructing 42 corresponding white matter (WM) bundles in the human and the macaque brain and have shown cross-species comparisons using such bundles as WM landmarks. Our original XTRACT protocols were developed using the F99 macaque brain template. However, additional macaque template brains are becoming increasingly common. Here, we generalise the XTRACT tractography protocol definitions across five macaque brain templates, including the F99, D99, INIA, Yerkes and NMT. We demonstrate equivalence of such protocols in two ways: (a) Firstly by comparing the bodies of the tracts derived using protocols defined across the different templates considered, (b) Secondly by comparing the projection patterns of the reconstructed tracts across the different templates in two cross-species (human–macaque) comparison tasks. The results confirm similarity of all predictions regardless of the macaque brain template used, providing direct evidence for the generalisability of these tractography protocols across the five considered templates. [ABSTRACT FROM AUTHOR]

The recent development of methods for constructing directly comparable white matter atlases in primate brains from diffusion MRI allows us to probe specializations unique to humans, great apes, and other primate taxa. Here, we constructed the first white matter atlas of a lesser ape using an ex vivo diffusion-weighted scan of a brain from a young adult (5.5 years) male lar gibbon. We find that white matter architecture of the gibbon temporal lobe suggests specializations that are reminiscent of those previously reported for great apes, specifically, the expansion of the arcuate fasciculus and the inferior longitudinal fasciculus in the temporal lobe. Our findings suggest these white matter expansions into the temporal lobe were present in the last common ancestor to hominoids approximately 16 million years ago and were further modified in the great ape and human lineages. White matter atlases provide a useful resource for identifying neuroanatomical differences and similarities between humans and other primate species and provide insight into the evolutionary variation and stasis of brain organization. [ABSTRACT FROM AUTHOR]

To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE), for diagnosing osteomyelitis in the diabetic foot. A thorough search was carried out to identify suitable studies published up to September 2023. The quality of the studies involved was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The diagnostic sensitivity and specificity of each imaging modality/method for each specific cut point were summarized. The summary receiver operating characteristic (SROC) curve was calculated using bivariate mixed effects models. Five studies investigating 187 patients and 234 bone lesions with 110 diagnosed osteomyelitis were enrolled. Four studies used DWI (172 lesions), three studies used DCE techniques (140 lesions) and two studies presented results of conventional MRI (66 lesions). The sensitivity ranges using conventional MRI, DWI and DCE were 65%-100%, 65%-100% and 64%-100%, respectively. The specificity ranges were 50%-61%, 56%-95%, and 66%-93%, respectively. The SROC curve of DWI and DCE was 0.89 (95% CI, 0.86–0.92) and 0.90 (95% CI, 0.87–0.92), respectively. Combining DWI and DCE methods, alongside conventional MRI, can improve the reliability and accuracy of diabetic foot osteomyelitis diagnosis. However, the study recognizes result variability due to varying protocols and emphasizes the need for well-designed studies with standardized approaches. To optimize diagnostic performance, the study recommends considering low ADC values, Ktrans or rapid wash-in rate from DCE such as iAUC60, along with using large ROIs that cover the entire lesion while excluding normal bone marrow. [ABSTRACT FROM AUTHOR]

Combining computed diffusion-weighted imaging (DWI) with readout-segmented echo-planar-imaging may shorten acquisition time and improve imaging quality. This study aimed to compare computed vs. acquired DWI qualitatively and quantitatively in visualizing scrotal or testicular lesions. We retrospectively enrolled 57 consecutive men who underwent scrotal MRI. Four computed DWI sets (cDWI 800 , cDWI 1000 , cDWI 1200 , and cDWI 1400) were generated from acquired DWI with two lower b-values (150 and 600 s/mm2). Acquired DWI (DWI 800 and DWI 1000) and computed DWI were compared through qualitative (susceptibility artifact, signal loss artifact, anatomic clarity, and lesion conspicuity) and quantitative assessment (signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and lesion-to-testicular parenchyma contrast ratio (CR)). Computed DWI was prone to signal loss artifact and slightly lower assessment scores in terms of anatomic clarity and lesion conspicuity, comparing with acquired DWI. The SNR of computed and acquired DWI decreased with increasing b value. Under the same b-values (800 and 1,000 s/mm2), there was no difference in the median SNR and CR between computed and acquired DWI. The median CR of cDWI 1400 was significantly higher than that of the other DWI sets excepting cDWI 1200 (P =1.000). The median CNR tended to be lower for computed vs. acquired DWI, while no significant difference (P =0.233). Computed and acquired DWI were nearly equivalent in both qualitative and quantitative evaluations at the b values of 800 and 1,000 s/mm2. Computed DWI could enhance the contrast of scrotal or testicular lesions. • Computed vs. acquired DWI are equivalent at the b values of 800 and 1,000 s/mm2. • Computed DWI could enhance the contrast of scrotal or testicular lesions. • Computed DWI can serve visual aid to radiologists without increasing scan time. [ABSTRACT FROM AUTHOR]

The utility of the apparent diffusion coefficient (ADC) of diffusion-weighted image (DWI) magnetic resonance imaging was examined for evaluating malignancy and prognosis in gallbladder tumors. A total of 63 patients (benign tumors, n=33; cancer, n=30) were included after surgical resection for gallbladder tumors, and their mean ADC values by DWI were obtained. Cases of advanced gallbladder cancer (n=25) were divided into ADCHigh and ADCLow groups, and clinicopathological factors were compared. In 63 cases, ADC values in advanced gallbladder cancer were significantly lower compared with benign tumors and non-advanced gallbladder cancer (P<0.05), and ADC values in early gallbladder cancer were also significantly lower compared with benign tumors (P<0.05). In 25 advanced gallbladder cancer cases, the ADCLow group tended to have a higher rate of advanced stage disease (P=0.09). Disease-free survival and overall survival (OS) of the ADCLow group were worse compared with the ADCHigh group (P<0.01). In the multivariate analysis of OS, poor differentiation and low ADC value were independent prognostic factors. ADC values may be useful for evaluating tumor malignancies in gallbladder tumors. [ABSTRACT FROM AUTHOR]

This document discusses a case of a painless knee mass in a young adult. The MRI showed a soft tissue lesion in the posterior recess of the knee, closely related to the anterior cruciate ligament. A provisional diagnosis of a complex ACL ganglion was made based on the MRI findings. However, an aspiration biopsy revealed a synovial sarcoma, a rare and aggressive soft tissue sarcoma. The document emphasizes the importance of histopathological analysis in cases of ganglion aspiration to avoid misdiagnosis. The management of synovial sarcoma involves surgical resection and, in some cases, radiotherapy or neoadjuvant chemoradiotherapy. [Extracted from the article]

Apolipoprotein E ε4 (APOE4) is a strong genetic risk factor of Alzheimer's disease and metabolic dysfunction. However, whether APOE4 and markers of metabolic dysfunction synergistically impact the deterioration of white matter (WM) integrity in older adults remains unknown. In the UK Biobank data, we conducted a multivariate analysis to investigate the interactions between APOE4 and 249 plasma metabolites (measured using nuclear magnetic resonance spectroscopy) with whole-brain WM integrity (measured by diffusion-weighted magnetic resonance imaging) in a cohort of 1917 older adults (aged 65.0–81.0 years; 52.4 % female). Although no main association was observed between either APOE4 or metabolites with WM integrity (adjusted P > 0.05), significant interactions between APOE4 and metabolites with WM integrity were identified. Among the examined metabolites, higher concentrations of low-density lipoprotein and very low-density lipoprotein were associated with a lower level of WM integrity (b= − 0.12 , CI= − 0.14 , − 0.10 ) among APOE4 carriers. Conversely, among non-carriers, they were associated with a higher level of WM integrity (b=0.05, CI= 0.04,0.07 ), demonstrating a significant moderation role of APOE4 (b = − 0.18 , CI= − 0.20 , − 0.15 , P<0.00001). • LDL is negatively associated with white matter integrity in older APOE4 carriers. • This association, although weak, is positive in APOE4 non-carriers. • APOE4 carriers with high LDL show a stronger negative age-cognition correlation. [ABSTRACT FROM AUTHOR]

PURPOSE To evaluate the diagnostic efficacy of multishot echo-planar imaging (EPI) [RESOLVE (RS)] and non- EPI (HASTE) diffusion-weighted imaging (DWI) in detecting cholesteatoma (CHO), and to explore the role of signal intensity (SI) ratio measurements in addressing diagnostic challenges. METHODS We analyzed RS-EPI and non-EPI DWI images from 154 patients who had undergone microscopic middle ear surgery, with pathological confirmation of their diagnoses. Two radiologists, referred to as Reader A and Reader B, independently reviewed the images without prior knowledge of the outcomes. Their evaluation focused on lesion location, T1-weighted (T1W) signal characteristics, and contrast enhancement in temporal bone magnetic resonance imaging. Key parameters included lesion hyperintensity, size, SI, SI ratio, and susceptibility artifact scores across both imaging modalities. RESULTS Of the patients, 62.3% (96/154) were diagnosed with CHO, whereas 37.7% (58/154) were found to have non-CHO conditions. In RS-EPI DWI, Reader A achieved 89.6% sensitivity, 79.3% specificity, 87.8% positive predictive value (PPV), and 82.1% negative predictive value (NPV). Non-EPI DWI presented similar results with sensitivities of 89.6%, specificities of 86.2%, PPVs of 91.5%, and NPVs of 83.3%. Reader B's results for RS-EPI DWI were 82.3% sensitivity, 84.5% specificity, 89.8% PPV, and 74.2% NPV, whereas, for non-EPI DWI, they were 86.5% sensitivity, 89.7% specificity, 93.3% PPV, and 80% NPV. The interobserver agreement was excellent (RS-EPI, κ: 0.84; non-EPI, κ: 0.91). The SI ratio measurements were consistently higher in non-EPI DWI (Reader A: 2.51, Reader B: 2.46) for the CHO group compared with RS-EPI. The SI ratio cut-off (>1.98) effectively differentiated hyperintense lesions between CHO and non-CHO groups, demonstrating 82.9% sensitivity and 100% specificity, with an area under the curve of 0.901 (95% confidence interval: 0.815-0.956; P < 0.001). Susceptibility artifact scores averaged 1.18 ± 0.7 (Reader A) and 1.04 ± 0.41 (Reader B) in RS-EPI, with non-EPI DWI recording a mean score of 0. CONCLUSION Both RS-EPI and non-EPI DWI exhibited high diagnostic accuracy for CHO. While RS-EPI DWI cannot replace non-EPI DWI, their combined use improves sensitivity. SI ratio measurement in non-EPI DWI was particularly beneficial in complex diagnostic scenarios. CLINICAL SIGNIFICANCE This study refines CHO diagnostic protocols by showcasing the diagnostic capabilities of both RSEPI and non-EPI DWI and highlighting the utility of SI measurements as a diagnostic tool. These findings may reduce false positives and aid in more accurate treatment planning, offering substantial insights for clinicians in managing CHO. [ABSTRACT FROM AUTHOR]

Filter exchange imaging (FEXI) is a double diffusion‐encoding (DDE) sequence that is specifically sensitive to exchange between sites with different apparent diffusivities. FEXI uses a diffusion‐encoding filtering block followed by a detection block at varying mixing times to map the exchange rate. Long mixing times enhance the sensitivity to exchange, but they pose challenges for imaging applications that require a stimulated echo sequence with crusher gradients. Thin imaging slices require strong crushers, which can introduce significant diffusion weighting and bias exchange rate estimates. Here, we treat the crushers as an additional encoding block and consider FEXI as a triple diffusion‐encoding sequence. This allows the bias to be corrected in the case of multi‐Gaussian diffusion, but not easily in the presence of restricted diffusion. Our approach addresses challenges in the presence of restricted diffusion and relies on the ability to independently gauge sensitivities to exchange and restricted diffusion for arbitrary gradient waveforms. It follows two principles: (i) the effects of crushers are included in the forward model using signal cumulant expansion; and (ii) timing parameters of diffusion gradients in filter and detection blocks are adjusted to maintain the same level of restriction encoding regardless of the mixing time. This results in the tuned exchange imaging (TEXI) protocol. The accuracy of exchange mapping with TEXI was assessed through Monte Carlo simulations in spheres of identical sizes and gamma‐distributed sizes, and in parallel hexagonally packed cylinders. The simulations demonstrate that TEXI provides consistent exchange rates regardless of slice thickness and restriction size, even with strong crushers. However, the accuracy depends on b‐values, mixing times, and restriction geometry. The constraints and limitations of TEXI are discussed, including suggestions for protocol adaptations. Further studies are needed to optimize the precision of TEXI and assess the approach experimentally in realistic, heterogeneous substrates. [ABSTRACT FROM AUTHOR]

Diffusion‐tensor (DT)‐MRI tractography provides information about properties relevant to muscle health and function, including estimates of architectural properties such as fascicle length, pennation angle, and curvature and diffusion properties such as mean diffusivity (MD) and fractional anisotropy (FA). Tractography settings, including integration algorithms, thresholds for early tract termination, and tract smoothing approaches, impact the accuracy of the muscle property estimates. However, muscle DT‐MRI tractography is performed using a variety of these settings, complicating comparisons between different studies. The effects of different tractography settings on muscle architecture estimates have not been fully explored, and optimized settings for muscle tractography have not yet been determined. We examined the influence of integration algorithm and termination check settings combined with a range of step sizes, termination criteria, and smoothing polynomial orders on tract characteristics, completion/reason for termination, and goodness of fit between fiber tracts and smoothing polynomials using 3‐T DT‐MR images of the lower leg muscles of seven healthy adults. We found that tract length and completion were highly sensitive to strict FA and intersegment angle thresholds (25%–69% reduction in complete fiber tracts from lowest to highest minimum FA threshold and 11%–36% reduction from highest to lowest intersegment angle threshold). Higher order polynomials (third and fourth order vs. second order) better fit the muscle fiber trajectories, but curvature estimates were highly sensitive to smoothing polynomial order (3.9–6.6 m−1 increase for second‐ vs. fourth‐order fitting polynomials). Step size impacted curvature estimates, albeit to a lesser degree. Integration algorithm had little impact, and mean pennation angle, and tract‐based FA and MD, were relatively insensitive to all parameters. The results demonstrate which muscle diffusion measures and architectural estimates are most sensitive to varying tractography settings and support the need for consistent reporting of tractography details to aid interpretation and comparison of results between studies. [ABSTRACT FROM AUTHOR]

Early tumor response prediction can help avoid overtreatment with unnecessary chemotherapy sessions. It is important to determine whether multiple apparent diffusion coefficient indices (S index, ADC‐diff) are effective in the early prediction of pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Patients with stage II and III BCs who underwent T1WI, diffusion‐weighted imaging (DWI), and dynamic contrast‐enhanced MRI using a 3 T system were included. They were divided into two groups: major histological responders (MHRs, Miller–Payne G4/5) and nonmajor histological responders (nMHRs, Miller–Payne G1–3). Three b values were used for DWI to derive the S index; ADC‐diff values were obtained using b = 0 and 1000 s/mm2. The different interquartile ranges of percentile S‐index and ADC‐diff values after treatment were calculated and compared. The assessment was performed at baseline and after two and four NAC cycles. A total of 59 patients were evaluated. There are some correlations of interquartile ranges of S‐index parameters and ADC‐diff values with histopathological prognostic factors (such as estrogen receptor and human epidermal growth factor receptor 2 expression, all p < 0.05), but no significant differences were found in some other interquartile ranges of S‐index parameters or ADC‐diff values between progesterone receptor positive and negative or for Ki‐67 tumors (all P > 0.05). No differences were found in the dynamic contrast‐enhanced MRI characteristics between the two groups. HER‐2 expression and kurtosis of the S‐index distribution were screened out as independent risk factors for predicting MHR group (p < 0.05, area under the curve (AUC) = 0.811) before NAC. After early NAC (two cycles), only the 10th percentile S index was statistically significant between the two groups (p < 0.05, AUC = 0.714). No significant differences were found in ADC‐diff value at any time point of NAC between the two groups (P > 0.1). These findings demonstrate that the S‐index value may be used as an early predictor of pathological response to NAC in BC; the value of ADC‐diff as an imaging biomarker of NAC needs to be further confirmed by ongoing multicenter prospective trials. [ABSTRACT FROM AUTHOR]

Purpose: To fully characterize the orientation dependence of magnetization transfer (MT) and inhomogeneous MT (ihMT) measures in the whole white matter (WM), for both single‐fiber and crossing‐fiber voxels. Methods: A characterization method was developed using the fiber orientation obtained from diffusion MRI (dMRI) with diffusion tensor imaging (DTI) and constrained spherical deconvolution. This allowed for characterization of the orientation dependence of measures in all of WM, regardless of the number of fiber orientation in a voxel. Furthermore, the orientation dependence inside 31 different WM bundles was characterized to evaluate the homogeneity of the effect. Variation of the results within and between‐subject was assessed from a 12‐subject dataset. Results: Previous results for single‐fiber voxels were reproduced and a novel characterization was produced in voxels of crossing fibers, which seems to follow trends consistent with single‐fiber results. Heterogeneity of the orientation dependence across bundles was observed, but homogeneity within similar bundles was also highlighted. Differences in behavior between MT and ihMT measures, as well as the ratio and saturation versions of these, were noted. Conclusion: Orientation dependence characterization was proven possible over the entirety of WM. The vast range of effects and subtleties of the orientation dependence on MT measures showed the need for, but also the challenges of, a correction method. [ABSTRACT FROM AUTHOR]

Purpose: Demonstrating and assessing self‐supervised machine‐learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer. Methods: We derive a self‐supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning. We do this quantitatively on simulated data by comparing the Pearson's correlation coefficient, mean‐squared error, bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed‐rank test. Results: In simulations, ssVERDICT outperforms the baseline methods (nonlinear least squares and supervised deep learning) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and mean‐squared error. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods. Conclusion: ssVERDICT significantly outperforms state‐of‐the‐art methods for VERDICT model fitting and shows, for the first time, fitting of a detailed multicompartment biophysical diffusion MRI model with machine learning without the requirement of explicit training labels. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to develop a model‐based deep learning architecture to accurately reconstruct fiber orientation distributions (FODs) from a reduced number of diffusion‐weighted images (DWIs), facilitating accurate analysis with reduced acquisition times. Methods: Our proposed architecture, Spherical Deconvolution Network (SDNet), performed FOD reconstruction by mapping 30 DWIs to fully sampled FODs, which have been fit to 288 DWIs. SDNet included DWI‐consistency blocks within the network architecture, and a fixel‐classification penalty within the loss function. SDNet was trained on a subset of the Human Connectome Project, and its performance compared with FOD‐Net, and multishell multitissue constrained spherical deconvolution. Results: SDNet achieved the strongest results with respect to angular correlation coefficient and sum of squared errors. When the impact of the fixel‐classification penalty was increased, we observed an improvement in performance metrics reliant on segmenting the FODs into the correct number of fixels. Conclusion: Inclusion of DWI‐consistency blocks improved reconstruction performance, and the fixel‐classification penalty term offered increased control over the angular separation of fixels in the reconstructed FODs. [ABSTRACT FROM AUTHOR]

Purpose: This study compared field-of-view (FOV) optimized and constrained undistorted single-shot diffusion-weighted imaging (FOCUS DWI) with deep-learning-based reconstruction (DLR) to conventional DWI for breast imaging. Methods: This study prospectively enrolled 49 female patients suspected of breast cancer from July to December 2023. The patients underwent conventional and FOCUS breast DWI and data were reconstructed with and without DLR. Two radiologists independently evaluated three images per patient using a 5-point Likert scale. Objective evaluations, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC), were conducted using manual region of interest-based analysis. The subjective and objective evaluations were compared using the Friedman test. Results: The scores for the overall image quality, anatomical details, lesion conspicuity, artifacts, and distortion in FOCUS-DLR DWI were higher than in conventional DWI (all P < 0.001). The SNR of FOCUS-DLR DWI was higher than that of conventional and FOCUS DWI (both P < 0.001), while FOCUS and conventional DWI were similar (P = 0.096). Conventional, FOCUS, and FOCUS-DLR DWI had similar CNR and ADC values. Conclusion: Our findings indicate that images produced by FOCUS-DLR DWI were superior to conventional DWI, supporting the applicability of this technique in clinical practice. DLR provides a new approach to optimize breast DWI. [ABSTRACT FROM AUTHOR]

Our case demonstrated unique cytomegalovirus (CMV) encephalitis post-haploidentical donor hematopoietic stem cell transplantation (HID-HSCT), with early findings on diffusion-weighted brain magnetic resonance imaging (MRI) in the absence of any neurologic symptoms. A 54-year-old Chinese man with acute lymphoblastic leukemia (Philadelphia chromosome-negative) underwent HID-HSCT. After HSCT, the patient developed CMV viremia and severe acute graft-versus-host disease. Recurrence of CMV viremia was observed. On day 129, brain MRI was performed to determine the cause for the intermittent fever. Diffusion-weighted imaging (DWI) revealed several bright spots in the cortex of the frontal lobes and anterior angle of the left lateral ventricle. Subsequently, he developed transplant-associated thrombotic microangiopathy, posterior reversible encephalopathy syndrome, and enlargement of lesions alongside the ventricular wall on a brain MRI series. Metagenomic next-generation sequencing (NGS) of the cerebrospinal fluid (CSF) led to the final diagnosis of CMV encephalitis. Although ganciclovir combined with foscarnet was administered, the patient’s consciousness deteriorated, followed by respiratory failure. The patient died on day 198. Additionally, we performed a systematic review to comprehensively analyze this disease. Regarding treatment, immunological therapies, including virus-specific T cells from a third donor and CMV-cytotoxic T lymphocytes, may be more effective. This case report and systematic review underscores the complexities of managing CMV ventriculoencephalitis in HSCT recipients and emphasizes the importance of early diagnosis by brain MRI and CSF polymerase chain reaction or NGS and ongoing research in improving outcomes. [ABSTRACT FROM AUTHOR]

Diffusion-weighted magnetic resonance imaging (DW-MRI) performed before target temperature management, within 6 h of return of spontaneous circulation (ROSC), is defined as ultra-early DW-MRI. In previous studies, high-signal intensity (HSI) on ultra-early DW-MRI can predict poor neurological outcomes (Cerebral Performance Category 3–5 at 6-months post-ROSC). We aimed to assess the optimal-timing for ultra-early DW-MRI to avoid false-negative outcomes post out-of-hospital cardiac arrest, considering cardiopulmonary resuscitation (CPR) factors. The primary outcomes were HSI in the cerebral cortex or deep gray matter on ultra-early DW-MRI. The impact of CPR factors and ROSC to DW-MRI scan-interval on HSI-presence was assessed. Of 206 included patients, 108 exhibited HSI-presence, exclusively associated with poor neurological outcomes. In multivariate regression analysis, ROSC to DW-MRI scan-interval (adjusted odds ratio [aOR], 1.509; 95% confidence interval (CI): 1.113–2.046; P = 0.008), low-flow time (aOR, 1.176; 95%CI: 1.121–1.233; P < 0.001), and non-shockable rhythm (aOR, 9.974; 95%CI: 3.363–29.578; P < 0.001) were independently associated with HSI-presence. ROSC to DW-MRI scan-interval cutoff of ≥ 2.2 h was particularly significant in low-flow time ≤ 21 min or shockable rhythm group. In conclusion, short low-flow time and shockable rhythm require a longer ROSC to DW-MRI scan-interval. Prolonged low-flow time and non-shockable rhythm reduce the need to consider scan-interval. [ABSTRACT FROM AUTHOR]

Background and purpose: Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional magnetic resonance imaging (MRI) remains challenging due to their similar imaging features. This study aimed to evaluate the diagnostic performance of advanced diffusion models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator magnetic resonance imaging (MAP-MRI), in comparison to traditional techniques like diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) for distinguishing HGGs from SBMs. Methods: In total, 17 patients with HGGs and 26 patients with SBMs were prospectively recruited based on the established inclusion and exclusion criteria. Structural MRI sequences and diffusion spectrum imaging (DSI) were utilized to assess quantitative parameter models, including NODDI, MAP-MRI, DWI, DTI, and DKI. Quantitative parameters were measured for both the tumor parenchymal area and the peritumoral edema area. The quantitative parameters of the two patient groups were compared using either the independent Student's t-test or the Mann--Whitney U test. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Finally, the DeLong test was employed to compare the diagnostic performance of each model through pairwise comparisons of ROC curves. Results: Isotropic volume fraction (Viso) based on NODDI; mean squared displacement (MSD) and the return to plane probabilities (RTPP) based on MAP-MRI; radial diffusivity (RDk) and mean diffusivity (MDk) based on DKI; and axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) based on DTI of the peritumoral edema tumor were significantly different between HGGs and SBMs (p < 0.05). The optimal single discriminant parameters for each model are NODDI_Viso, MAP-MRI_MSD, DKI_MDk, and DTI_AD. Among these, the AUC of Viso (0.809) exceeds that of MSD (0.733), MDk (0.718), and AD (0.779). The combined model, which incorporates DTI_AD, DKI_RD, and NODDI_Viso, demonstrated superior diagnostic performance (0.897). Conclusions: Advanced diffusion MRI quantitative parameters derived from NODDI, such as Viso, have the potential to enhance the differentiation between HGGs and SBMs. The integrated utilization of these models is anticipated to enhance diagnostic accuracy and refine MRI protocols for brain tumor assessment. [ABSTRACT FROM AUTHOR]