High-resolution Magnetic Resonance Imaging Research Articles

3D balanced SSFP UTE MRI for multiple contrasts whole brain imaging.

This study aimed to develop a new high-resolution MRI sequence for the imaging of the ultra-short transverse relaxation time (uT2) components in the brain, while simultaneously providing proton density (PD) contrast for reference and quantification. The sequence combines low flip angle balanced SSFP (bSSFP) and UTE techniques, together with a 3D dual-echo rosette k-space trajectory for readout. The expected image contrast was evaluated by simulations. A study cohort of six healthy volunteers and eight multiple sclerosis (MS) patients was recruited to test the proposed sequence. Subtraction between two TEs was performed to extract uT2 signals. In addition, conventional longitudinal relaxation time (T1) weighted, T2-weighted, and PD-weighted MRI sequences were also acquired for comparison. Typical PD-contrast was found in the second TE images, while uT2 signals were selectively captured in the first TE images. The subtraction images presented signals primarily originating from uT2 components, but only if the first TE is short enough. Lesions in the MS subjects showed hyperintense signals in the second TE images but were hypointense signals in the subtraction images. The lesions had significantly lower signal intensity in subtraction images than normal white matter (WM), which indicated a reduction of uT2 components likely associated with myelin. 3D isotropic sub-millimeter (0.94 mm) spatial resolution images were acquired with the novel bSSFP UTE sequence within 3 min. It provided easy extraction of uT2 signals and PD-contrast for reference within a single acquisition.

High-resolution diffusion-weighted MRI plus mammography for detecting clinically occult breast cancers in women with dense breasts

PurposeTo compare the performance of mammography, high-resolution DW-MRI, DCE-MRI, and their combinations in detecting clinically occult breast cancer in women with dense breasts. Method544 breasts from 281 consecutive asymptomatic women with dense breasts were retrospectively identified. They underwent breast MRI for preoperative evaluation of breast cancers (n = 214) or as supplemental screening (n = 67) including DCE-MRI and DW-MRI (b values, 0 and 1000 sec/mm2; in-plane resolution, 1.1 × 1.1 mm2 and 1.3 × 1.3 mm2; section thickness, 3 mm), in addition to mammography. Three readers independently reviewed each examination on a per-breast basis. Histopathology and at least two year of imaging follow-up served as the gold standard. The sensitivities and specificities of different imaging modalities were compared using McNemar test. Results230 of 544 breasts (42 %) had malignant lesions. The sensitivity of DW-MRI was higher than that of mammography (77.0 % vs 57.9 %; adjusted p < 0.001), but lower than that of DCE-MRI (84.8 %; adjusted p = 0.014). The specificity of DW-MRI was comparable to those of mammography (98.1 % vs 99.1 %; adjusted p > 0.999) and DCE-MRI (97.1 %; adjusted p > 0.999). DW-MRI plus mammography had a comparable sensitivity and specificity to those of DCE-MRI plus mammography (88.6 % vs 90.9 % and 97.1 % vs 96.2 %; adjusted p > 0.999 for both). ConclusionsHigh-resolution DW-MRI had a sensitivity higher than mammography and lower than DCE-MRI. Nevertheless, DW-MRI plus mammography showed a comparable sensitivity and specificity to DCE-MRI plus mammography for detecting clinically occult cancers in women with dense breasts.

Association of in utero HIV exposure with child brain structure and language development: a South African birth cohort study

BackgroundThere is a growing population of children with in utero HIV exposure who are at risk of poor neurodevelopmental outcomes despite avoiding HIV infection. However, the underlying neurobiological pathways are not understood and neuroimaging studies are lacking. We aimed to investigate the cortical brain structure of children who are HIV-exposed and uninfected (HEU) compared to HIV-unexposed (HU) children and to examine the relationship with neurodevelopment.MethodsThe Drakenstein Child Health birth cohort study enrolled pregnant women from a high HIV prevalence area in South Africa with longitudinal follow-up of mother–child pairs. High-resolution magnetic resonance imaging scans from 162 children (70 HEU; 92 HU) were acquired at 2–3 years of age. All HEU children were born to mothers taking antiretroviral therapy. Measures of brain structure (cortical thickness and surface area) in the prefrontal cortex regions were extracted from T1-weighted images and compared between groups using multivariate analysis of variance and linear regression. Child development, assessed using the Bayley Scales of Infant and Toddler Development-III, was correlated with cortical structure, and mediation analyses were performed.ResultsAnalyses demonstrated an association between HIV exposure and cortical thickness across the prefrontal cortex (p = 0.035). Children who were HEU had thicker cortices in prefrontal regions, with significantly greater cortical thickness in the medial orbitofrontal cortex (mOFC) bilaterally compared to HU children (3.21 mm versus 3.14 mm, p = 0.009, adjusted effect size 0.44 [95% CI 0.12 to 0.75]). Estimates held across multiple sensitivity analyses. There were no group differences in cortical surface area. Language scores, which were lower in HEU versus HU children (81.82 versus 86.25, p = 0.011, effect size − 0.44 [95% CI − 0.78 to − 0.09]), negatively correlated with prefrontal cortical thickness in both groups. Cortical thickness in the mOFC mediated the relationship between HIV exposure and poor language outcomes (Sobel test p = 0.032).ConclusionsIn this cohort study, exposure to HIV during pregnancy was associated with altered cortical structure in early life. Our findings indicate that differences in cortical thickness development in the prefrontal region in children who are HEU may be a pathway leading to language impairment. Longitudinal studies are needed to determine the lasting impact.

MRI atlas of the pituitary gland in young female adults.

The probabilistic topography and inter-individual variability of the pituitary gland (PG) remain undetermined. The absence of a standardized reference atlas hinders research on PG volumetrics. In this study, we aimed at creating maximum probability maps for the anterior and posterior PG in young female adults. We manually delineated the anterior and posterior parts of the pituitary glands in 26 healthy subjects using high-resolution MRI T1 images. A three-step procedure and a cost function-masking approach were employed to optimize spatial normalization for the PG. We generated probabilistic atlases and maximum probability maps, which were subsequently coregistered back to the subjects' space and compared to manual delineations. Manual measurements led to a total pituitary volume of 705 ± 88mm³, with the anterior and posterior volumes measuring 614 ± 82mm³ and 91 ± 20mm³, respectively. The mean relative volume difference between manual and atlas-based estimations was 1.3%. The global pituitary atlas exhibited an 80% (± 9%) overlap for the DICE index and 67% (± 11%) for the Jaccard index. Similarly, these values were 77% (± 13%) and 64% (± 14%) for the anterior pituitary atlas and 62% (± 21%) and 47% (± 17%) for the posterior PG atlas, respectively. We observed a substantial concordance and a significant correlation between the volume estimations of the manual and atlas-based methods for the global pituitary and anterior volumes. The maximum probability maps of the anterior and posterior PG lay the groundwork for automatic atlas-based segmentation methods and the standardized analysis of large PG datasets.

The differences between carotid web and carotid web with plaque: based on multimodal ultrasonic and clinical characteristics.

This study aimed to examine the clinical and multimodal ultrasonic characteristics differences between carotid web (CW) and CW with plaque as well as the potential risk factors for stroke caused by CW. We retrospectively enrolled patients diagnosed with CW by CTA or high-resolution MRI (HRMRI) and simultaneously underwent contrast enhanced ultrasound (CEUS) and superb microvascular imaging examinations from January 2015 to October 2022. The CW angle was measured using computer-aided software. The variations between CW and CW with plaque were evaluated, and univariable and multivariable logistic regressions were utilized to identify possible risk predictors for stroke caused by CW. Two hundred ninety-nine patients with an average age of 60.85 (± 8.77) years were included. Sex, age, history of smoking, alcohol, hypertension, diabetes mellitus, homocysteine level, and treatment, as well as web length and thickness, luminal stenosis, location wall, number, CW angle, and CEUS enhancement, were quite different among CW and CW with plaque patients (p < 0.05). The logistic regression analysis showed that web length was an independent predictor of luminal stenosis in CW patients. For patients with CW and plaque, plaque and web thickness, as well as plaque enhancement, were associated with stenosis. Furthermore, luminal stenosis and plaque length were risk factors for symptoms. The multimodal ultrasonic and clinical manifestations of CW and CW with plaque are quite different. Web length is an independent risk factor for carotid artery stenosis in CW patients, whereas luminal stenosis and plaque length were risk factors for symptoms in CW with plaque patients. Exploring the similarities and differences between the carotid web and the carotid web with plaque, based on the stereo-geometric spatial position relationship and hemodynamic changes, may provide further insights into the underlying mechanisms of stroke occurrence caused by the carotid web. 1. Multimodal ultrasonic and clinical manifestations of carotid web and carotid web with plaque are substantially different. 2. A thin triangular endoluminal defect is identified as a typical feature of the web on superb microvascular imaging, and two kinds of typical ultrasonic features of CW with plaque are also identified. 3. Web length is an independent risk factor for carotid stenosis in carotid web patients, whereas luminal stenosis and plaque length are risk factors for symptoms in patients with CW and plaque.

Divergent effects of sex on hippocampal subfield alterations in drug-naive patients with major depressive disorder

BackgroundThe hippocampus is a crucial brain structure in etiological models of major depressive disorder (MDD). It remains unclear whether sex differences in the incidence and symptoms of MDD are related to differential illness-associated brain alterations, including alterations in the hippocampus. This study investigated divergent the effects of sex on hippocampal subfield alterations in drug-naive patients with MDD. MethodsHigh-resolution structural MR images were obtained from 144 drug-naive individuals with MDD early in their illness course and 135 age- and sex-matched healthy controls (HCs). Hippocampal subfields were segmented using FreeSurfer software and analyzed in terms of both histological subfields (CA1–4, dentate gyrus, etc.) and more integrative larger functional subregions (head, body and tail). ResultsWe observed a significant overall reduction in hippocampal volume in MDD patients, with deficits more prominent deficits in the posterior hippocampus. Differences in anatomic alterations between male and female patients were observed in the CA1-head, presubiculum-body and fimbria in the left hemisphere. Exploratory analyses revealed different patterns of clinical and memory function correlations with histological subfields and functional subregions between male and female patients primarily in the hippocampal head and body. LimitationsThis cross-sectional study cannot clarify the causality of hippocampal alterations or their association with illness risk or onset. ConclusionsThese findings represent the first reported sex-specific alterations in hippocampal histological subfields in patients with MDD early in the illness course prior to treatment. Sex-specific hippocampal alterations may contribute to diverse sex differences in the clinical presentation of MDD.

The Prepetrous Segment of the Internal Carotid Artery as a Neglected Site of Symptomatic Atherosclerosis: A Single-Center Series.

(1) Background: Non-stenotic complicated plaques are a neglected cause of stroke, in particular in young patients. Atherosclerosis has some preferential sites in extracranial arteries and the prepetrous segment of the internal carotid artery has been rarely described as site of atheroma in general and of complicated atheroma in stroke patients. The aim of this study is to describe the rate of the prepetrous internal carotid artery's (ICA) involvement in a single-center case series of young stroke patients. (2) Methods: All patients < 50 years old with acute ischemic stroke admitted to a single-center Stroke Unit during two time periods (the first one from 1 January 2018 to 31 December 2019, and the second one from 1 January 2021 to 30 June 2022), were prospectively investigated as part of a screening protocol of the Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Etiology, Triggers, and Outcome (SECRETO) study [ClinicalTrials.gov ID NCT01934725], including extracranial vascular examination by using computed tomography (CT) or magnetic resonance imaging (MRI). (3) Results: Two out of ninety-three consecutive patients (2.15%) had a complicated atheroma in the prepetrous ICA as the cause of stroke and both CT angiography and high-resolution vessel wall MRI were applied to document the main features of positive remodeling, cap rupture, ulceration, intraplaque hemorrhage, and a transient thrombus superimposed on the atheroma. The two patients had a different evolution of healing in the first case and a persisting ulceration at 12 months in the second case. (4) Conclusions: The prepetrous ICA is a rarely described location of complicated atheroma in stroke patients at all ages and it represents roughly 2% of causes of acute stroke in this single-center case series in young people.

Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

Brain MR image simulation for deep learning based medical image analysis networks

Background and ObjectiveAs large sets of annotated MRI data are needed for training and validating deep learning based medical image analysis algorithms, the lack of sufficient annotated data is a critical problem. A possible solution is the generation of artificial data by means of physics-based simulations. Existing brain simulation data is limited in terms of anatomical models, tissue classes, fixed tissue characteristics, MR sequences and overall realism. MethodsWe propose a realistic simulation framework by incorporating patient-specific phantoms and Bloch equations-based analytical solutions for fast and accurate MRI simulations. A large number of labels are derived from open-source high-resolution T1w MRI data using a fully automated brain classification tool. The brain labels are taken as ground truth (GT) on which MR images are simulated using our framework. Moreover, we demonstrate that the T1w MR images generated from our framework along with GT annotations can be utilized directly to train a 3D brain segmentation network. To evaluate our model further on larger set of real multi-source MRI data without GT, we compared our model to existing brain segmentation tools, FSL-FAST and SynthSeg. ResultsOur framework generates 3D brain MRI for variable anatomy, sequence, contrast, SNR and resolution. The brain segmentation network for WM/GM/CSF trained only on T1w simulated data shows promising results on real MRI data from MRBrainS18 challenge dataset with a Dice scores of 0.818/0.832/0.828. On OASIS data, our model exhibits a close performance to FSL, both qualitatively and quantitatively with a Dice scores of 0.901/0.939/0.937. ConclusionsOur proposed simulation framework is the initial step towards achieving truly physics-based MRI image generation, providing flexibility to generate large sets of variable MRI data for desired anatomy, sequence, contrast, SNR, and resolution. Furthermore, the generated images can effectively train 3D brain segmentation networks, mitigating the reliance on real 3D annotated data.

A multimodal submillimeter MRI atlas of the human cerebellum

The human cerebellum is engaged in a broad array of tasks related to motor coordination, cognition, language, attention, memory, and emotional regulation. A detailed cerebellar atlas can facilitate the investigation of the structural and functional organization of the cerebellum. However, existing cerebellar atlases are typically limited to a single imaging modality with insufficient characterization of tissue properties. Here, we introduce a multifaceted cerebellar atlas based on high-resolution multimodal MRI, facilitating the understanding of the neurodevelopment and neurodegeneration of the cerebellum based on cortical morphology, tissue microstructure, and intra-cerebellar and cerebello-cerebral connectivity.

Evaluation of the structural integrity of different spinal cord tracts with magnetization transfer ratio in degenerative cervical myelopathy.

Degenerative cervical myelopathy (DCM) is a common cause of spinal cord dysfunction. In this study, we explored the potential of magnetization transfer ratio (MTR) for evaluating the structural integrity of spinal cord tracts in patients with clinically significant DCM. Fifty-three patients with DCM and 41 patients with cervical radiculopathy were evaluated using high-resolution cervical spinal cord magnetic resonance imaging (MRI), which included the magnetization transfer technique. MRI data were analyzed with the Spinal Cord Toolbox (v5.5); MTR values in each spinal tract were calculated and compared between groups after correction for patient age and sex. Correlations between MTR values and patients' clinical disability rate were also evaluated. A statistically significant reduction in the average MTR of the spinal cord white matter, as well as the MTR of the ventral columns and lateral funiculi, was revealed in the DCM group (adjusted p < 0.01 for all comparisons). Furthermore, reductions in MTR values in the fasciculus cuneatus, spinocerebellar, rubrospinal, and reticulospinal tracts were found in patients with DCM (adjusted p < 0.01 for all comparisons). Positive correlations between the JOA score and the MTR within the ventral columns of the spinal cord (R = 0.38, adjusted p < 0.05) and the ventral spinocerebellar tract (R = 0.41, adjusted p < 0.05) were revealed. The findings of our study indicate that demyelination in patients with DCM primarily affects the spinal tracts of the extrapyramidal system, and the extent of these changes is related to the severity of the condition.

Assessment of arterial pulsatility of cerebral perforating arteries using 7T high-resolution dual-VENC phase-contrast MRI.

Directly imaging the function of cerebral perforating arteries could provide valuable insight into the pathology of cerebral small vessel diseases (cSVD). Arterial pulsatility has been identified as a useful biomarker for assessing vascular dysfunction. In this study, we investigate the feasibility and reliability of using dual velocity encoding (VENC) phase-contrast MRI (PC-MRI) to measure the pulsatility of cerebral perforating arteries at 7 T. Twenty participants, including 12 young volunteers and 8 elder adults, underwent high-resolution 2D PC-MRI scans with VENCs of 20 cm/s and 40 cm/s at 7T. The sensitivity of perforator detection and the reliability of pulsatility measurement of cerebral perforating arteries using dual-VENC PC-MRI were evaluated by comparison with the single-VENC data. The effects of temporal resolution in the PC-MRI acquisition and aging on the pulsatility measurements were investigated. Compared to the single VENCs, dual-VENC PC-MRI provided improved sensitivity of perforator detection and more reliable pulsatility measurements. Temporal resolution impacted the pulsatility measurements, as decreasing temporal resolution led to an underestimation of pulsatility. Elderly adults had elevated pulsatility in cerebral perforating arteries compared to young adults, but there was no difference in the number of detected perforators between the two age groups. Dual-VENC PC-MRI is a reliable imaging method for the assessment of pulsatility of cerebral perforating arteries, which could be useful as a potential imaging biomarker of aging and cSVD.

Evaluation of high temporal resolution magnetic resonance imaging of the liver with gadoxetate disodium in combination with compressed sensing and parallel imaging under single breath-holding using a 1.5-T magnetic resonance system

BackgroundThis study aimed to determine the optimal scan time for high temporal resolution magnetic resonance (MR) imaging of the liver with gadoxetate disodium injection in combination with compressed sensing (CS) and parallel imaging (PI) techniques under single breath-holding using a 1.5-T MR system.MethodsSixty-two participants underwent multiple arterial phases of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the liver with gadoxetate disodium using fat-suppressed GRE T1-weighted imaging—liver acquisition with volume acceleration (LAVA)—in combination with CS and PI using a 1.5-T MR system. Forty-six and 22 participants underwent 6-s and 10-s scans, respectively. Pre-contrast, multiple arterial, portal venous, and hepatobiliary phase images were acquired. Two radiologists evaluated the visual scores for the outline of the liver, inferior right hepatic vein (IRHV), right portal vein, right hepatic artery, appropriateness of the arterial phase, and overall image quality using a 4- or 5-point scale.ResultsThe overall image quality and the image quality of the outline of the liver in the pre-contrast and arterial phases and IRHV in the pre-contrast phase were significantly better (P < 0.05) in the 10-s scan group than those in the 6-s scan group. No significant difference was observed between the two groups in terms of the appropriateness of the arterial phase (obtaining the optimal arterial phase) (P = 0.731).ConclusionsA 10-s scan protocol is recommended for high temporal resolution DCE-MRI of the liver with gadoxetate disodium injection in combination with CS and PI under single breath-holding using a 1.5-T MR system.

Feasibility and efficiency of a new classification based on high-resolution MRI for carotid artery pseudo-occlusion and occlusion: Hybrid revascularization pilot study

Background and purposeStudies on changes in the distal internal carotid artery based on high resolution magnetic resonance imaging (HRMRI) are scarce. Herein, we propose a histological classification system for patients with carotid artery pseudo-occlusion or occlusion based on preoperative HRMRI, for which we evaluated the feasibility and clinical implications. Materials and methodsFrom January 2017 to June 2021, 40 patients with Doppler ultrasound, CTA or MRA suggesting carotid artery occlusion were enrolled in this study. A new classification system based on HRMRI was established and subsequently verified by postoperative specimens. We recorded and analyzed patient characteristics, HRMRI data, recanalization rate, requirements of additional endovascular procedures, complications, and outcomes. ResultsFour histological classifications (type Ⅰ–Ⅳ) were identified. According to our classification system, 20 patients (50.00%) were type I, nine (22.50%) were type II, 7 (17.50%) were type III, and four (10.00%) were type Ⅳ. The success rate of recanalization was 88.89% (32/36) in type I–III patients. Four (44.44%) type Ⅱ patients and five (71.43%) type Ⅲ patients suffered from intraoperative dissection. ConclusionPatients identified as types I (pseudo-occlusion) and II (thrombotic-occlusion) were able to be treated via hybrid revascularization with relatively low risk, while patients identified as type III (fibrous-occlusion) required more careful treatment. Recanalization is not suitable for patients identified as type Ⅳ. Our proposed classification system based on HRMRI data can be used as an adjunctive guide to predict the technical feasibility and success of revascularization via a hybrid technique.

An MR-compatible fiber-optic probe for measuring focused ultrasound-induced temperature rises without viscous heating artifacts

Focused ultrasound (FUS) beam interactions with thermocouples and fiber optic (FO) probes cause a “viscous heating artifact” (VHA), which prevent accurate temperature measurements during acoustic sonication. This work demonstrates a novel fiber-optic temperature probe which is insensitive to VHA, validated in an MR-guided FUS treatment setting. The FO probe (OSENSA Innovations; PRB-140, 0.14 mm diameter) was inserted with an 18G catheter into a tissue-mimicking gelatin phantom. The FO probe tip was located with high-resolution MR images (0.25 × 0.25 × 0.5 mm3) for targeting with FUS. Continuous-wave FUS sonications (50 W, 20 s) were delivered at a distance of ∼1.5 mm from the FO probe tip using a 256 phased-array transducer (Imasonic, France; 1 MHz, 2.1 × 2.3 × 9.8 FWHM spot size) and FUS-induced heating was measured with 3D MR temperature imaging (MRTI; 0.5 × 0.5 × 1 mm3 resolution, 3.9 s acquisition). The VHA effect was not observed in the PRB-140 FO probe measurement data. The FO probe heating and cooling curves closely matched those measured by MRTI, with a root mean-squared error (RMSE) of 0.61 °C. In contrast, the RMSE of VHA-sensitive FO probe was 6.00 °C for a similar acoustic power output. This ultrasound artifact-immune FO temperature probe is highly advantageous for MR temperature sequence development and precise temperature monitoring in FUS treatment applications.

Communicative impairment and its neural correlates in Alzheimer's disease and frontotemporal dementia.

Communication skills can deteriorate in neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia (FTD); however, their clinical assessment and treatment in patient care can be challenging. In the present study, we aimed to quantify the distinctive communication resources and barriers reported by patients and their relatives in AD and FTD and associated these communicative characteristics with clinical parameters, such as the degree of cognitive impairment and atrophy in language-associated brain areas. We assessed self-reported communication barriers and resources in 33 individuals with AD and FTD through an interview on daily-life communication, using the Aachener KOMPASS questionnaire. We correlated reported communication barriers and resources with atrophy from high-resolution 3T brain magnetic resonance imaging, neuropsychological assessment, and neurodegenerative markers from cerebrospinal fluid. Communicative impairment was higher in FTD compared to AD. Increased reported communication barriers in our whole sample were associated with the atrophy rate in the left middle temporal lobe, a critical site within the neuronal language network, and with depressive symptoms as well as the semantic word fluency from neuropsychological assessment. The best model for prediction of communicative impairment included the diagnosis (AD or FTD), semantic word fluency, and depressive symptoms. Our study demonstrates that communication barriers and resources can be successfully assessed via a structured interview based on self-report and report of patients' relatives in practice and are reflected in neuroimaging specific for AD and FTD as well as in further clinical parameters specific for these neurodegenerative diseases. This can potentially open new treatment options for clinical practice and patient care.

Does CISS MRI Reliably Depict the Endolymphatic Duct in Children with and without Vestibular Aqueduct Enlargement?

High-resolution CT is the mainstay for diagnosing an enlarged vestibular aqueduct (EVA), but MR imaging may be an appealing alternative, given its lack of ionizing radiation exposure. The purpose of this study was to determine how reliably MR imaging demonstrates the endolymphatic duct and endolymphatic duct enlargement in hearing-impaired children. We performed a retrospective review of temporal bone high-resolution CT and MR imaging of hearing-impaired children evaluated between 2017 and 2020. Vestibular aqueduct diameter was measured on high-resolution CT. The vestibular aqueducts were categorized as being enlarged (EVA+) or nonenlarged (EVA-) using the Cincinnati criteria. The endolymphatic ducts were assessed on axial high-resolution CISS MR imaging. We categorized endolymphatic duct visibility into the following: type 1 (not visible), type 2 (faintly visible), and type 3 (easily visible). Mixed-effect logistic regression was used to identify associations between endolymphatic duct visibility and EVA. Interreader agreement for the endolymphatic duct among 3 independent readers was assessed using the Fleiss κ statistic. In 196 ears from 98 children, endolymphatic duct visibility on MR imaging was type 1 in 74.0%, type 2 in 14.8%, and type 3 in 11.2%; 20.4% of ears were EVA+ on high-resolution CT. There was a significant association between EVA+ status and endolymphatic duct visibility (P < .01). Endolymphatic duct visibility was type 1 in 87.1%, type 2 in 12.8%, and type 3 in 0% of EVA- ears and type 1 in 22.5%, type 2 in 22.5%, and type 3 in 55.0% of EVA+ ears. The predicted probability of a type 3 endolymphatic duct being EVA+ was 0.997. There was almost perfect agreement among the 3 readers for distinguishing type 3 from type 1 or 2 endolymphatic ducts. CISS MR imaging substantially underdiagnoses EVA; however, when a type 3 endolymphatic duct is evident, there is a >99% likelihood of an EVA.

Detection and classification of progressive supranuclear palsy from MRI images using deep learning

A timely and reliable computer aided MR image-based evaluations is required for the detection and classification of Progressive supranuclear palsy (PSP). It is a neurodegenerative ailment that is clinically very difficult to identify due to a high degree of overlap in characterized symptoms. Unlike other ailments, the primary constraint regarding PSP is the limited research work in this area. The main aim of our study is to establish a generalized model by comparing traditional custom CNN and transfer learning models such as DenseNet121, ResNet50, InceptionV3, VGG16, EfficientNetB0, Xception, MobileNet and InceptionResNetV2 which are fine tuned for the detection and classification of PSP with higher accuracy rates. Existing research has primarily focused on reducing the time complexity of neural networks and has only had success with low-level features. Furthermore, obtaining a significant volume of distributed labelled data is difficult. In our research, 125 T1 protocol based high resolution MRI images of 65 PSP and 60 normal control patients were considered. The image dataset is pre-processed, normalized and augmented before deploying them to the respective networks. The results propose that ‘InceptionResNetV2’ model can be considered as a generalised model for the detection and classification of PSP. The network offered a classification accuracy of 95%, Precision of 100%, Sensitivity of 92.8%, F1 score of 96.2% and a Specificity of 100% which is significantly higher compared to other models considered in the study and also the existing conventional ML models, thereby providing a prerequisite for significant diagnostic implementation.

High-Q metasurface signal isolator for 1.5T surface coil magnetic resonance imaging on the go.

The combination of surface coils and metamaterials remarkably enhance magnetic resonance imaging (MRI) performance for significant local staging flexibility. However, due to the coupling in between, impeded signal-to-noise ratio (SNR) and low-contrast resolution, further hamper the future growth in clinical MRI. In this paper, we propose a high-Q metasurface decoupling isolator fueled by topological LC loops for 1.5T surface coil MRI system, increasing the magnetic field up to fivefold at 63.8 MHz. We have employed a polarization conversion mechanism to effectively eliminate the coupling between the MRI metamaterial and the radio frequency (RF) surface transmitter-receiver coils. Furthermore, a high-Q metasurface isolator was achieved by taking advantage of bound states in the continuum (BIC) for extremely high-resolution MRI and spectroscopy. An equivalent physical model of the miniaturized metasurface design was put forward through LC circuit analysis. This study opens up a promising route for the easy-to-use and portable surface coil MRI scanners.

Discrete residual diffusion model for high-resolution prostate MRI synthesis

Objective. High-resolution magnetic resonance imaging (HR MRI) is an effective tool for diagnosing PCa, but it requires patients to remain immobile for extended periods, increasing chances of image distortion due to motion. One solution is to utilize super-resolution (SR) techniques to process low-resolution (LR) images and create a higher-resolution version. However, existing medical SR models suffer from issues such as excessive smoothness and mode collapse. In this paper, we propose a novel generative model avoiding the problems of existing models, called discrete residual diffusion model (DR-DM). Approach. First, the forward process of DR-DM gradually disrupts the input via a fixed Markov chain, producing a sequence of latent variables with increasing noise. The backward process learns the conditional transit distribution and gradually match the target data distribution. By optimizing a variant of the variational lower bound, training diffusion models effectively address the issue of mode collapse. Second, to focus DR-DM on recovering high-frequency details, we synthesize residual images instead of synthesizing HR MRI directly. The residual image represents the difference between the HR and LR up-sampled MR image, and we convert residual image into discrete image tokens with a shorter sequence length by a vector quantized variational autoencoder (VQ-VAE), which reduced the computational complexity. Third, transformer architecture is integrated to model the relationship between LR MRI and residual image, which can capture the long-range dependencies between LR MRI and the synthesized imaging and improve the fidelity of reconstructed images. Main results. Extensive experimental validations have been performed on two popular yet challenging magnetic resonance image super-resolution tasks and compared to five state-of-the-art methods. Significance. Our experiments on the Prostate-Diagnosis and PROSTATEx datasets demonstrate that the DR-DM model significantly improves the signal-to-noise ratio of MRI for prostate cancer, resulting in greater clarity and improved diagnostic accuracy for patients.