Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.

BACKGROUND: The role of isocitrate dehydrogenase (IDH) mutation status for glioma stratification and prognosis is established. While structural magnetic resonance image (MRI) is a promising biomarker, it may not be sufficient for non-invasive characterisation of IDH mutation status. We investigated the diagnostic value of combined diffusion tensor imaging (DTI) and structural MRI enhanced by a deep radiomics approach based on convolutional neural networks (CNNs) and support vector machine (SVM), to determine the IDH mutation status in Central Nervous System World Health Organization (CNS WHO) grade 2-4 gliomas. METHODS: This retrospective study analyzed the DTI-derived fractional anisotropy (FA) and mean diffusivity (MD) images and structural images including fluid attenuated inversion recovery (FLAIR), non-enhanced T1-, and T2-weighted images of 206 treatment-naïve gliomas, including 146 IDH mutant and 60 IDH-wildtype ones. The lesions were manually segmented by experienced neuroradiologists and the masks were applied to the FA and MD maps. Deep radiomics features were extracted from each subject by applying a pre-trained CNN and statistical description. An SVM classifier was applied to predict IDH status using imaging features in combination with demographic data. RESULTS: We comparatively assessed the CNN-SVM classifier performance in predicting IDH mutation status using standalone and combined structural and DTI-based imaging features. Combined imaging features surpassed stand-alone modalities for the prediction of IDH mutation status [area under the curve (AUC) = 0.846; sensitivity = 0.925; and specificity = 0.567]. Importantly, optimal model performance was noted following the addition of demographic data (patients' age) to structural and DTI imaging features [area under the curve (AUC) = 0.847; sensitivity = 0.911; and specificity = 0.617]. CONCLUSIONS: Imaging features derived from DTI-based FA and MD maps combined with structural MRI, have superior diagnostic value to that provided by standalone structural or DTI sequences. In combination with demographic information, this CNN-SVM model offers a further enhanced non-invasive prediction of IDH mutation status in gliomas.

Age-related enhancement of the association between episodic memory and gray matter volume in medial temporal and frontal lobes.

BACKGROUND: Episodic memory (EM) deteriorates as a result of normal aging as well as Alzheimer's disease. The neural underpinnings of such age-related memory impairments in older individuals are not well-understood. Although previous research has unveiled the association between gray matter volume (GMV) and EM in the elderly population, such findings exhibit variances across distinct age cohorts. Consequently, an investigation into the dynamic evolution of this relationship with advancing age is imperative. RESULT: The present study utilized a sliding window approach to examine how the correlation between EM and GMV varied with age in a cross-sectional sample of 926 Chinese older adults. We found that both verbal EM (VEM) and spatial EM (SEM) exhibited positive correlations with GMV in extensive areas primarily in the temporal and frontal lobes and that these correlations typically became stronger with older age. Moreover, there were variations in the strength of the correlation between EM and GMV with age, which differed based on sex and the specific type of EM. Specifically, the association between VEM and GMVs in the insula and parietal regions became stronger with age for females but not for males, whereas the association between SEM and GMVs in the parietal and occipital regions became stronger for males but not for females. At the brain system level, there is a significant age-related increase in the correlations between both types of EM and the GMV of both the anterior temporal (AT) system and the posterior medial (PM) system in male group. In females, both types of EM show stronger age-related correlations with the GMV of the AT system compared to males. CONCLUSIONS: Our study revealed a significant positive correlation between GMV in most regions associated with EM and age, particularly in the frontal and temporal lobes. This discovery offers new insights into the connection between brain structure and the diminishing episodic memory function among older individuals.

Combined in vivo MRI assessment of locus coeruleus and nucleus basalis of Meynert integrity in amnestic Alzheimer's disease, suspected-LATE and frontotemporal dementia.

BACKGROUND: The locus coeruleus (LC) and the nucleus basalis of Meynert (NBM) are altered in early stages of Alzheimer's disease (AD). Little is known about LC and NBM alteration in limbic-predominant age-related TDP-43 encephalopathy (LATE) and frontotemporal dementia (FTD). The aim of the present study is to investigate in vivo LC and NBM integrity in patients with suspected-LATE, early-amnestic AD and FTD in comparison with controls. METHODS: Seventy-two participants (23 early amnestic-AD patients, 17 suspected-LATE, 17 FTD patients, defined by a clinical-biological diagnosis reinforced by amyloid and tau PET imaging, and 15 controls) underwent neuropsychological assessment and 3T brain MRI. We analyzed the locus coeruleus signal intensity (LC-I) and the NBM volume as well as their relation with cognition and with medial temporal/cortical atrophy. RESULTS: We found significantly lower LC-I and NBM volume in amnestic-AD and suspected-LATE in comparison with controls. In FTD, we also observed lower NBM volume but a slightly less marked alteration of the LC-I, independently of the temporal or frontal phenotype. NBM volume was correlated with the global cognitive efficiency in AD patients. Strong correlations were found between NBM volume and that of medial temporal structures, particularly the amygdala in both AD and FTD patients. CONCLUSIONS: The alteration of LC and NBM in amnestic-AD, presumed-LATE and FTD suggests a common vulnerability of these structures to different proteinopathies. Targeting the noradrenergic and cholinergic systems could be effective therapeutic strategies in LATE and FTD.

Evaluating lumbar disc degeneration by MRI quantitative metabolic indicators: the perspective of factor analysis.

PURPOSE: This study aimed to investigate an early diagnostic method for lumbar disc degeneration (LDD) and improve its diagnostic accuracy. METHODS: Quantitative biomarkers of the lumbar body (LB) and lumbar discs (LDs) were obtained using nuclear magnetic resonance (NMR) detection technology. The diagnostic weights of each biological metabolism indicator were screened using the factor analysis method. RESULTS: Through factor analysis, common factors such as the LB fat fraction, fat content, and T2* value of LDs were identified as covariates for the diagnostic model for the evaluation of LDD. This model can optimize the accuracy and reliability of LDD diagnosis. CONCLUSION: The application of biomarker quantification methods based on NMR detection technology combined with factor analysis provides an effective means for the early diagnosis of LDD, thereby improving diagnostic accuracy and reliability.

Predicting balloon shape in percutaneous microcompression : an observational comparative analysis of Meckel's cave imaging and balloon morphology.

Achieving a pear-shaped balloon holds pivotal significance in the context of successful percutaneous microcompression procedures for trigeminal neuralgia. However, inflated balloons may assume various configurations, whether it is inserted into Meckel's cave or not. The absence of an objective evaluation metric has become apparent. To investigate the relationship between the morphology of Meckel's Cave and the balloon used in percutaneous microcompression for trigeminal neuralgia and establish objective criteria for assessing balloon shape in percutaneous microcompression procedures. This retrospective study included 58 consecutive patients with primary trigeminal neuralgia. Data included demographic, clinical outcomes, and morphological features of Meckel's cave and the balloon obtained from MRI and Dyna-CT imaging. MRI of Meckel's cave and Dyna-CT of intraoperative balloon were modeled, and the morphological characteristics and correlation were analyzed. The reconstructed balloon presented a fuller morphology expanding outward and upward on the basis of Meckel's cave. The projected area of balloon was strongly positively correlated with the projected area of Meckel's cave. The Pearson correlation coefficients were 0.812 (P<0.001) for axial view, 0.898 (P<0.001) for sagittal view and 0.813 (P<0.001) for coronal view. Similarity analysis showed that the sagittal projection image of Meckel's cave and that of the balloon had good similarity. This study reveals that the balloon in percutaneous microcompression essentially represents an expanded morphology of Meckel's cave, extending outward and upward. There is a strong positive correlation between the volume and projected area of the balloon and that of Meckel's cave. Notably, the sagittal projection image of Meckel's cave serves as a reliable predictor of the intraoperative balloon shape. This method has a certain generalizability and can help providing objective criteria for judging balloon shape during percutaneous microcompression procedures.

Radiologic-Pathologic Correlation of Cardiac Tumors: Updated 2021 WHO Tumor Classification.

Cardiac tumors, although rare, carry high morbidity and mortality rates. They are commonly first identified either at echocardiography or incidentally at thoracoabdominal CT performed for noncardiac indications. Multimodality imaging often helps to determine the cause of these masses. Cardiac tumors comprise a distinct category in the World Health Organization (WHO) classification of tumors. The updated 2021 WHO classification of tumors of the heart incorporates new entities and reclassifies others. In the new classification system, papillary fibroelastoma is recognized as the most common primary cardiac neoplasm. Pseudotumors including thrombi and anatomic variants (eg, crista terminalis, accessory papillary muscles, or coumadin ridge) are the most common intracardiac masses identified at imaging. Cardiac metastases are substantially more common than primary cardiac tumors. Although echocardiography is usually the first examination, cardiac MRI is the modality of choice for the identification and characterization of cardiac masses. Cardiac CT serves as an alternative in patients who cannot tolerate MRI. PET performed with CT or MRI enables metabolic characterization of malignant cardiac masses. Imaging individualized to a particular tumor type and location is crucial for treatment planning. Tumor terminology changes as our understanding of tumor biology and behavior evolves. Familiarity with the updated classification system is important as a guide to radiologic investigation and medical or surgical management. ©RSNA, 2024 Supplemental material is available for this article.

Whole-body magnetic resonance imaging at 0.05 Tesla.

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

Modern Magnetic Resonance Imaging Modalities to Advance Neuroimaging in Astronauts.

INTRODUCTION: The rapid development of the space industry requires a deeper understanding of spaceflight's impact on the brain. MRI research reports brain volume changes following spaceflight in astronauts, potentially affecting cognition. Recently, we have demonstrated that this evidence of volumetric changes, as measured by typical T1-weighted sequences (e.g., magnetization-prepared rapid gradient echo sequence; MPRAGE), is error-prone due to the microgravity-related redistribution of cerebrospinal fluid in the brain. More modern neuroimaging methods, particularly dual-echo MPRAGE (DEMPRAGE) and magnetization-prepared rapid gradient echo sequence utilizing two inversion pulses (MP2RAGE), have been suggested to be resilient to this error. Here, we tested if these imaging modalities offered consistent segmentation performance improvements in some commonly employed neuroimaging software packages.METHODS: We conducted manual gray matter tissue segmentation in traditional T1w MRI images to utilize for comparison. Automated tissue segmentation was performed for traditional T1w imaging, as well as on DEMPRAGE and MP2RAGE images from the same subjects. Statistical analysis involved a comparison of total gray matter volumes for each modality, and the extent of tissue segmentation agreement was assessed using a test of similarity (Dice coefficient).RESULTS: Neither DEMPRAGE nor MP2RAGE exhibited consistent segmentation performance across all toolboxes tested.DISCUSSION: This research indicates that customized data collection and processing methods are necessary for reliable and valid structural MRI segmentation in astronauts, as current methods provide erroneous classification and hence inaccurate claims of neuroplastic brain changes in the astronaut population.Berger L, Burles F, Jaswal T, Williams R, Iaria G. Modern magnetic resonance imaging modalities to advance neuroimaging in astronauts. Aerosp Med Hum Perform. 2024; 95(5):245-253.

Spatial functional reorganizations can serve as potential biomarkers of post facial palsy synkinesis.

Facial palsy can result in a serious complication known as facial synkinesis, causing both physical and psychological harm to the patients. There is growing evidence that patients with facial synkinesis have brain abnormalities, but the brain mechanisms and underlying imaging biomarkers remain unclear. Here, we employed functional magnetic resonance imaging (fMRI) to investigate brain function in 31 unilateral post facial palsy synkinesis patients and 25 healthy controls during different facial expression movements and at rest. Combining surface-based mass-univariate analysis and multivariate pattern analysis, we identified diffused activation and intrinsic connection patterns in the primary motor cortex and the somatosensory cortex on the patient's affected side. Further, we classified post facial palsy synkinesis patients from healthy subjects with favorable accuracy using the support vector machine based on both task-related and resting-state functional magnetic resonance imaging data. Together, these findings indicate the potential of the identified functional reorganizations to serve as neuroimaging biomarkers for facial synkinesis diagnosis.

Biomechanical testing of ex vivo porcine tendons following high intensity focused ultrasound thermal ablation.

INTRODUCTION: Magnetic resonance-guided focused ultrasound (MRgFUS) has been demonstrated to be able to thermally ablate tendons with the aim to non-invasively disrupt tendon contractures in the clinical setting. However, the biomechanical changes of tendons permitting this disrupting is poorly understood. We aim to obtain a dose-dependent biomechanical response of tendons following magnetic resonance-guided focused ultrasound (MRgFUS) thermal ablation. METHODS: Ex vivo porcine tendons (n = 72) were embedded in an agar phantom and randomly assigned to 12 groups based on MRgFUS treatment. The treatment time was 10, 20, or 30s, and the applied acoustic power was 25, 50, 75, or 100W. Following each MRgFUS treatment, tendons underwent biomechanical tensile testing on an Instron machine, which calculated stress-strain curves during tendon elongation. Rupture rate, maximum treatment temperature, Young's modulus and ultimate strength were analyzed for each treatment energy. RESULTS: The study revealed a dose-dependent response, with tendons rupturing in over 50% of cases when energy delivery exceeded 1000J and 100% disruption at energy levels beyond 2000J. The achieved temperatures during MRgFUS were directly proportional to energy delivery. The highest recorded temperature was 56.8°C ± 9.34 (3000J), while the lowest recorded temperate was 18.6°C ± 0.6 (control). The Young's modulus was highest in the control group (47.3 MPa ± 6.5) and lowest in the 3000J group (13.2 MPa ± 5.9). There was no statistically significant difference in ultimate strength between treatment groups. CONCLUSION: This study establishes crucial thresholds for reliable and repeatable disruption of tendons, laying the groundwork for future in vivo optimization. The findings prompt further exploration of MRgFUS as a non-invasive modality for tendon disruption, offering hope for improved outcomes in patients with musculotendinous contractures.

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches do not well link neural networks and attention networks within brain networks. Our objective is to investigate the neural mechanisms related to attention and explore neuroimaging biological tags that can be generalized within the attention networks. In this paper, we utilized resting-state functional magnetic resonance imaging data to examine the differential functional connectivity network between ADHD and typically developing individuals. We employed a graph convolutional neural network model to identify individuals with ADHD. After classification, we visualized brain regions with significant contributions to the classification results. Our results suggest that the frontal, temporal, parietal, and cerebellar regions are likely the primary areas of dysfunction in individuals with ADHD. We also explored the relationship between regions of interest and attention networks, as well as the connection between crucial nodes and the distribution of positively and negatively correlated connections. This analysis allowed us to pinpoint the most discriminative brain regions, including the right orbitofrontal gyrus, the left rectus gyrus and bilateral insula, the right inferior temporal gyrus and bilateral transverse temporal gyrus in the temporal region, and the lingual gyrus of the occipital lobe, multiple regions of the basal ganglia and the upper cerebellum. These regions are primarily involved in the attention executive control network and the attention orientation network. Dysfunction in the functional connectivity of these regions may contribute to the underlying causes of ADHD.

Noninvasive release of tendons using MRI guided focused ultrasound: a hybrid therapy using long-pulse focused ultrasound followed by thermal ablation.

INTRODUCTION: Magnetic Resonance-guided Focused Ultrasound (MRgFUS) thermal ablation is an effective noninvasive ultrasonic therapy to disrupt in vivo porcine tendon but is prone to inducing skin burns. We evaluated the safety profile of a novel hybrid protocol that minimizes thermal spread by combining long-pulse focused ultrasound followed by thermal ablation. METHODS: In-vivo Achilles tendons (hybrid N = 15, thermal ablation alone N = 21) from 15 to 20 kg Yorkshire pigs were randomly assigned to 6 treatment groups in two studies. The first (N = 21) was ablation (600, 900, or 1200 J). The second (N = 15) was hybrid: pulsed FUS (13.5 MPa peak negative pressure) followed by ablation (600, 900, or 1200 J). Measurements of ankle range of motion, tendon temperature, thermal dose (240 CEM43), and assessment of skin burn were performed in both groups. RESULTS: Rupture was comparable between the two protocols: 1/5 (20%), 5/5 (100%) and 5/5 (100%) for hybrid protocol, compared to 2/7 (29%), 6/7 (86%) and 7/7 (100%) for the ablation-only protocol with energies of 600, 900, and 1200 J, respectively. The hybrid protocol produced lower maximum temperatures, smaller areas of thermal dose, fewer thermal injuries to the skin, and fewer full-thickness skin burns. The standard deviation for the area of thermal injury was also smaller for the hybrid protocol, suggesting greater predictability. CONCLUSION: This study demonstrated a hybrid MRgFUS protocol combining long-pulse FUS followed by thermal ablation to be noninferior and safer than an ablation-only protocol for extracorporeal in-vivo tendon rupture for future clinical application for noninvasive release of contracted tendon.

Prescription Opioids and Brain Structure in Community-Dwelling Older Adults.

OBJECTIVE: To evaluate the associations between prescription opioid exposures in community-dwelling older adults and gray and white matter structure by magnetic resonance imaging. METHODS: Secondary analysis was conducted of a prospective, longitudinal population-based cohort study employing cross-sectional imaging of older adult (≥65 years) enrollees between November 1, 2004, and December 31, 2017. Gray matter outcomes included cortical thickness in 41 structures and subcortical volumes in 6 structures. White matter outcomes included fractional anisotropy in 40 tracts and global white matter hyperintensity volumes. The primary exposure was prescription opioid availability expressed as the per-year rate of opioid days preceding magnetic resonance imaging, with a secondary exposure of per-year total morphine milligram equivalents (MME). Multivariable models assessed associations between opioid exposures and brain structures. RESULTS: The study included 2185 participants; median (interquartile range) age was 80 (75 to 85) years, 47% were women, and 1246 (57%) received opioids. No significant associations were found between opioids and gray matter. Increased opioid days and MME were associated with decreased white matter fractional anisotropy in 15 (38%) and 16 (40%) regions, respectively, including the corpus callosum, posterior thalamic radiation, and anterior limb of the internal capsule, among others. Opioid days and MME were also associated with greater white matter hyperintensity volume (1.02 [95% CI, 1.002 to 1.036; P=.029] and 1.01 [1.001 to 1.024; P=.032] increase in the geometric mean, respectively). CONCLUSION: The duration and dose of prescription opioids were associated with decreased white matter integrity but not with gray matter structure. Future studies with longitudinal imaging and clinical correlation are warranted to further evaluate these relationships.

Achilles tendon assessment on quantitative MRI: Sources of variability and relationships to tendinopathy.

Quantitative MRI (qMRI) measures are useful in assessing musculoskeletal tissues, but application to tendon has been limited. The purposes of this study were to optimize, identify sources of variability, and establish reproducibility of qMRI to assess Achilles tendon. Additionally, preliminarily estimates of effect of tendon pathology on qMRI metrics and structure-function relationships between qMRI measures and ankle performance were examined. T1, T1ρ, T2, and T2* maps of the Achilles tendon were obtained using a 3T MRI scanner. In participants with asymptomatic tendons (n = 21), MRI procedures were repeated twice, and region of interest selection was performed by three raters. Variance decomposition and reproducibility statistics were completed. To estimate the effect of pathology, qMRI measures from individuals with asymptomatic tendons were compared to qMRI measures from a pilot group of individuals with Achilles tendinopathy (n = 7). Relationships between qMRI and ankle performance measures were assessed. Between-participant variation accounted for the majority of variability (46.7%-64.0%) in all qMRI measures except T2*. ICCs met or exceeded 0.7 for all qMRI measures when averaged across raters or scans. Relaxation times were significantly longer in tendinopathic tendons (mean (SD) T1: 977.8 (208.6) ms, T1ρ: 35.4 (7.1) ms, T2: 42.8 (7.9) ms, T2*: 14.1 (7.6) ms, n = 7) compared to asymptomatic control tendons (T1: 691.7 (32.4) ms, T1ρ: 24.0 (3.6) ms, T2: 24.4 (7.5) ms, T2*: 9.5 (3.4) ms, n = 21) (p < 0.011 for all comparisons). T1 related to functional performance measures in symptomatic and asymptomatic groups. Study findings suggest that qMRI is reliable to assess the Achilles tendon. qMRI quantitatively assesses the presence of tendon pathology and relates to functional performance outcomes, supporting the utility of incorporating qMRI in research and clinic.

Enhanced MRI Radiomics Based Model for Predicting Recurrence or Metastasis of Nasopharyngeal Cancer (NC) Undergoing Concurrent Chemoradiotherapy: A Retrospective Study.

Nasopharyngeal Carcinoma (NC) refers to the malignant tumor that occurs at the top and side walls of the nasopharyngeal cavity. The NC incidence rate always dominates the first among the malignant tumors of the ear, nose and throat, and mainly occurs in Asia. NC cases are mainly concentrated in southern provinces in China, with about 4 million existing NC. With the pollution of environment and pickled diet, and the increase of life pressure, the domestic NC incidence rate has reached 4.5-6.5/100000 and is increasing year by year. It was reported that the known main causes of NC include hereditary factor, genetic mutations, and EB virus infection, common clinical symptoms of NC include nasal congestion, bloody mucus, etc. About 90% of NC is highly sensitive to radiotherapy which is regard as the preferred treatment method; However, for NC with lower differentiation, larger volume, and recurrence after treatment, surgical resection and local protons and heavy ions therapy are also indispensable means. According to reports, the subtle heterogeneity and diversity exists in some NC, with about 80% of NC undergone radiotherapy and about 25% experienced recurrence and death within five years after radiotherapy in China. Therefore, screening the NC population with suspected recurrence after concurrent chemoradiotherapy may improve survival rates in current clinical decision-making.

NC is one of the prevalent malignancies of the head and neck region with poor prognosis. The aim of this study is to establish a predictive model for assessing NC prognosis using clinical and MR radiomics data.

Multi-institutional validation of a radiomics signature for identification of postoperative progression of soft tissue sarcoma.

BACKGROUND: To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression. METHODS: We retrospectively enrolled 335 patients with STS (training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences. Among 12 machine learning-predicted signatures, the best signature was selected, and its prediction score was inputted into Cox regression analysis to build the radiomics signature. A nomogram was created by combining the radiomics signature with a clinical model constructed using MRI and clinical features. Progression-free survival was analyzed in all patients. We assessed performance and clinical utility of the models with reference to the time-dependent receiver operating characteristic curve, area under the curve, concordance index, integrated Brier score, decision curve analysis. RESULTS: For the combined features subset, the minimum redundancy maximum relevance-least absolute shrinkage and selection operator regression algorithm + decision tree classifier had the best prediction performance. The radiomics signature based on the optimal machine learning-predicted signature, and built using Cox regression analysis, had greater prognostic capability and lower error than the nomogram and clinical model (concordance index, 0.758 and 0.812; area under the curve, 0.724 and 0.757; integrated Brier score, 0.080 and 0.143, in the validation and The Cancer Imaging Archive sets, respectively). The optimal cutoff was - 0.03 and cumulative risk rates were calculated. DATA CONCLUSION: To assess the risk of STS progression, the radiomics signature may have better prognostic power than a nomogram/clinical model.

Minimum spanning tree analysis of EEG resting-state functional networks in schizophrenia.

Schizophrenia is a serious and complex mental disease, known to be associated with various subtle structural and functional deviations in the brain. Recently, increased attention is given to the analysis of brain-wide, global mechanisms, strongly altering the communication of long-distance brain areas in schizophrenia. Data of 32 patients with schizophrenia and 28 matched healthy control subjects were analyzed. Two minutes long 64-channel EEG recordings were registered during resting, eyes closed condition. Average connectivity strength was estimated with Weighted Phase Lag Index (wPLI) in lower frequencies: delta and theta, and Amplitude Envelope Correlation with leakage correction (AEC-c) in higher frequencies: alpha, beta, lower gamma and higher gamma. To analyze functional network topology Minimum Spanning Tree (MST) algorithms were applied. Results show that patients have weaker functional connectivity in delta and alpha frequency bands. Concerning network differences, the result of lower diameter, higher leaf number, and also higher maximum degree and maximum betweenness centrality in patients suggest a star-like, and more random network topology in patients with schizophrenia. Our findings are in accordance with some previous findings based on resting-state EEG (and fMRI) data, suggesting that MST network structure in schizophrenia is biased towards a less optimal, more centralized organization.

Analysis on efficacy of magnetic resonance lymphangiography using INV-001 in healthy beagle dogs.

We aimed to conduct a proof-of-concept study of INV-001 in visualizing lymphatic vessels and nodes without venous contamination and to determine the optimal dose condition of INV-001 for magnetic resonance lymphangiography (MRL) in healthy beagles. MRL was performed using a 3.0-Tesla (T) whole body clinical magnetic resonance imaging (MRI) scanner. A dose-finding study of INV-001 for MRL in beagles (N = 6) was carried out according to an adaptive optimal dose finding design. For the reproducibility study (N = 6), MRL was conducted at selected INV-001 doses (0.056 and 0.112 mg Fe/kg) with a 15 mM concentration. Additionally, an excretion study (N = 3) of INV-001 was conducted by analyzing T1, T2, and T2* maps of the liver and kidney 48 h post-administration. INV-001 administration at doses of 0.056 and 0.112 mg Fe/kg (concentration: 15 mM) consistently demonstrated the visualization of contrast-enhanced lymphatic vessels and nodes without venous contamination in the beagles. The contrast enhancement effect was highest at 30 min after INV-001 administration, then gradually decreasing. No toxicity-related issues were identified during the study. After 48 h, the T1, T2, and T2* values in the liver and both kidneys were found to be comparable to the pre-administration values, indicating thorough INV-001 excretion. The optimal dosing conditions of INV-001 for MRL for contrast-enhanced visualization of lymphatic vessels and nodes exclusively with no venous contamination in beagles was determined to be 0.056 mg Fe/kg with a 15 mM concentration.

Neurodevelopmental outcome in preterm infants with intraventricular hemorrhages: the potential of quantitative brainstem MRI.

OBJECTIVES: This retrospective study aimed to identify quantitative magnetic resonance imaging markers in the brainstem of preterm neonates with intraventricular hemorrhages. It delves into the intricate associations between quantitative brainstem magnetic resonance imaging metrics and neurodevelopmental outcomes in preterm infants with intraventricular hemorrhage, aiming to elucidate potential relationships and their clinical implications. MATERIALS AND METHODS: Neuroimaging was performed on preterm neonates with intraventricular hemorrhage using a multi-dynamic multi-echo sequence to determine T1 relaxation time, T2 relaxation time, and proton density in specific brainstem regions. Neonatal outcome scores were collected using the Bayley Scales of Infant and Toddler Development. Statistical analysis aimed to explore potential correlations between magnetic resonance imaging metrics and neurodevelopmental outcomes. RESULTS: Sixty preterm neonates (mean gestational age at birth 26.26 ± 2.69 wk; n = 24 [40%] females) were included. The T2 relaxation time of the midbrain exhibited significant positive correlations with cognitive (r = 0.538, P < 0.0001, Pearson's correlation), motor (r = 0.530, P < 0.0001), and language (r = 0.449, P = 0.0008) composite scores at 1 yr of age. CONCLUSION: Quantitative magnetic resonance imaging can provide valuable insights into neurodevelopmental outcomes after intraventricular hemorrhage, potentially aiding in identifying at-risk neonates. Multi-dynamic multi-echo sequence sequences hold promise as an adjunct to conventional sequences, enhancing the sensitivity of neonatal magnetic resonance neuroimaging and supporting clinical decision-making for these vulnerable patients.

UMobileNetV2 model for semantic segmentation of gastrointestinal tract in MRI scans.

Gastrointestinal (GI) cancer is leading general tumour in the Gastrointestinal tract, which is fourth significant reason of tumour death in men and women. The common cure for GI cancer is radiation treatment, which contains directing a high-energy X-ray beam onto the tumor while avoiding healthy organs. To provide high dosages of X-rays, a system needs for accurately segmenting the GI tract organs. The study presents a UMobileNetV2 model for semantic segmentation of small and large intestine and stomach in MRI images of the GI tract. The model uses MobileNetV2 as an encoder in the contraction path and UNet layers as a decoder in the expansion path. The UW-Madison database, which contains MRI scans from 85 patients and 38,496 images, is used for evaluation. This automated technology has the capability to enhance the pace of cancer therapy by aiding the radio oncologist in the process of segmenting the organs of the GI tract. The UMobileNetV2 model is compared to three transfer learning models: Xception, ResNet 101, and NASNet mobile, which are used as encoders in UNet architecture. The model is analyzed using three distinct optimizers, i.e., Adam, RMS, and SGD. The UMobileNetV2 model with the combination of Adam optimizer outperforms all other transfer learning models. It obtains a dice coefficient of 0.8984, an IoU of 0.8697, and a validation loss of 0.1310, proving its ability to reliably segment the stomach and intestines in MRI images of gastrointestinal cancer patients.