Magnetic Resonance Imaging Technology Research Articles

Long-term effects of childhood single-parent family structure on brain connectivity and psychological well-being.

The high and increasing proportion of single-parent families is considered a risk factor associated with various childhood trauma experiences. Consequently, concerns have been raised regarding the potential long-term effects of the childhood single-parent family structure. In this study, we employed advanced magnetic resonance imaging technology, including morphometric similarity mapping, functional connectivity density, and network-based analysis, to investigate brain connectivity and behavioral differences among young adults who were raised in single-parent families. Our study also aimed to explore the relationship between these differences and childhood trauma experiences. The results showed that individuals who grew up in single-parent families exhibited higher levels of anxiety, depression, and harm-avoidant personality. The multimodal MRI analysis further showed differences in regional and network-based connectivity properties in the single-parent family group, including increased functional connectivity density in the left inferior parietal lobule, enhanced cortical structural connectivity between the left isthmus cingulate cortex and peri-calcarine cortex, and an increase in temporal functional connectivity. Moreover, elevated levels of anxiety and depression, along with heightened functional connectivity density in the left inferior parietal lobule and increased temporal functional connectivity, were found to be correlated with a greater number of childhood trauma experiences. Through analyzing multiple data patterns, our study provides objective neuropsychobiological evidence for the enduring impact of childhood single-parent family structure on psychiatric vulnerability in adulthood.

Visualization of dynamic micro-migration of shale oil and investigation of shale oil movability by NMRI combined oil charging/water flooding experiments: A novel approach

Investigating the micro-migration processes of hydrocarbons within interbedded shale reservoirs, and quantitatively characterizing the movability of shale oil, are highly important for the exploration and development of continental shale oil. However, due to complex pore-fracture structures, the characterization of the micro-migration and movability of shale oil presents significant difficulties, and the lack of suitable technology restricts the understanding of shale oil accumulation mechanisms and the evaluation of movability. This study employs nuclear magnetic resonance imaging (NMRI) technology in conjunction with oil charging and water flooding experiments, to innovatively visualize and quantitatively characterize the dynamic micro-migration features and movability of hydrocarbons within the pore-fracture structures of shale. The results indicate a significant increase in oil saturation within the interbedded shale oil reservoir during the oil charging process, with the oil phase primarily accumulating in larger pores (T2 = 1–100 ms). The micro-migration and accumulation process of interbedded shale oil can be divided into three stages: the initial stage dominated by water phases in the pore spaces due to insufficient oil filling pressure, the intermediate stage marked by a rapid increase in hydrocarbons in the pore spaces, and the final stage where oil fills the entire pore system resulting in high oil saturation. The movability of different types of shale oil during water flooding varies significantly and is mainly influenced by pore-fracture structures. Interbedded shale oil reservoirs with larger pores exhibits a higher movable oil saturation (approximately 36.94%), while matrix-type shale oil reservoirs shows greater heterogeneity and lower fluid movability (approximately 14%). However, the shale oil movability of matrix-type shale oil reservoir with developed microfractures can reach 40%. More specifically, the fluid movability in smaller pore-microfracture structures (T2 < 0.5 ms) is as high as 56.88%, surpassing that in larger pores (T2 > 0.5 ms) (32.78%). Larger pores and microfractures substantially enhance the movability of hydrocarbons in the shale matrix, thus improving shale oil recoverability. In contrast, due to the higher capillary pressure (Pc) and flow resistance (Pv), smaller pores contribute less to the movability of shale oil. Overall, the outcomes of this study not only advance our understanding of the micro-migration and accumulation patterns of interbedded shale oil but also offer new insights for geological and engineering integration research on shale oil.

High-Order line graphs of fMRI data in major depressive disorder.

Resting-state functional magnetic resonance imaging (rs-fMRI) technology and the complex network theory can be used to elucidate the underlying mechanisms of brain diseases. The successful application of functional brain hypernetworks provides new perspectives for the diagnosis and evaluation of clinical brain diseases; however, many studies have not assessed the attribute information of hyperedges and could not retain the high-order topology of hypergraphs. In addition, the study of multi-scale and multi-layered organizational properties of the human brain can provide richer and more accurate data features for classification models of depression. This work aims to establish a more accurate classification framework for the diagnosis of major depressive disorder (MDD) using the high-order line graph algorithm. And accuracy, sensitivity, specificity, precision, F1 score are used to validate its classification performance. Based on rs-fMRI data from 38 MDD subjects and 28 controls, we constructed a human brain hypernetwork and introduced a line graph model, followed by the construction of a high-order line graph model. The topological properties under each order line graph were calculated to measure the classification performance of the model. Finally, intergroup features that showed significant differences under each order line graph model were fused, and a support vector machine classifier was constructed using multi-kernel learning. The Kolmogorov-Smirnov nonparametric permutation test was used as the feature selection method and the classification performance was measured with the leave-one-out cross-validation method. The high-order line graph achieved a better classification performance compared with other traditional hypernetworks (accuracy=92.42%, sensitivity=92.86%, specificity=92.11%, precision=89.66%, F1=91.23%). Furthermore, the brain regions found in the present study have been previously shown to be associated with the pathology of depression. This work validated the classification model based on the high-order line graph, which can better express the topological features of the hypernetwork by comprehensively considering the hyperedge information under different connection strengths, thereby significantly improving the classification accuracy of MDD. Therefore, this method has potential for use in the clinical diagnosis of MDD.

Clinical usability of 3D gradient-echo-based ultrashort echo time imaging: Is it enough to facilitate diagnostic decision in real-world practice?

Background With recent advances in magnetic resonance imaging (MRI) technology, the practical role of lung MRI is expanding despite the inherent challenges of the thorax. The purpose of our study was to evaluate the current status of the concurrent dephasing and excitation (CODE) ultrashort echo-time sequence and the T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence in the evaluation of thoracic disease by comparing it with the gold standard computed tomography (CT). Methods Twenty-four patients with lung cancer and mediastinal masses underwent both CT and MRI including T1-weighted VIBE and CODE. For CODE images, data were acquired in free breathing and end-expiratory images were reconstructed using retrospective respiratory gating. All images were evaluated through qualitative and quantitative approaches regarding various anatomical structures and lesions (nodule, mediastinal mass, emphysema, reticulation, honeycombing, bronchiectasis, pleural plaque and lymphadenopathy) inside the thorax in terms of diagnostic performance in making specific decisions. Results Depiction of the lung parenchyma, mediastinal and pleural lesion was not significant different among the three modalities (p &gt; 0.05). Intra-tumoral and peritumoral features of lung nodules were not significant different in the CT, VIBE or CODE images (p &gt; 0.05). However, VIBE and CODE had significantly lower image quality and poorer depiction of airway, great vessels, and emphysema compared to CT (p &lt; 0.05). Image quality of central airways and depiction of bronchi were significantly better in CODE than in VIBE (p &lt; 0.001 and p = 0.005). In contrast, the depiction of the vasculature was better for VIBE than CODE images (p = 0.003). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were significant greater in VIBE than CODE except for SNRlung and SNRnodule (p &lt; 0.05). Conclusions Our study showed the potential of CODE and VIBE sequences in the evaluation of localized thoracic abnormalities including solid pulmonary nodules.

Monolayer, Open-Mesh, Pristine PEDOT:PSS-based Conformal Brain Implants for Fully MRI-Compatible Neural Interfaces

Understanding brain function is essential for advancing our comprehension of human cognition, behavior, and neurological disorders. Magnetic resonance imaging (MRI) stands out as a powerful tool for exploring brain function, providing detailed insights into its structure and physiology. Combining MRI technology with electrophysiological recording system can enhance the comprehension of brain functionality through synergistic effects. However, the integration of neural implants with MRI technology presents challenges because of its strong electromagnetic (EM) energy during MRI scans. Therefore, MRI-compatible neural implants should facilitate detailed investigation of neural activities and brain functions in real-time in high resolution, without compromising patient safety and imaging quality. Here, we introduce the fully MRI-compatible monolayer pristine open-mesh PEDOT:PSS neural interface. This approach addresses the challenges encountered while using traditional metal-based electrodes in the MRI environment such as induced heat or imaging artifacts. PEDOT:PSS has a diamagnetic property with lower electrical conductivity and negative magnetic susceptibility similar to human tissues. Furthermore, by adopting the optimized open-mesh structure, the induced currents generated by EM energy are significantly diminished, leading to optimized MRI compatibility. Through simulations and experiments, our PEDOT:PSS-based open-mesh electrodes showed improved performance in reducing heat generation and eliminating imaging artifacts in an MRI environment. The electrophysiological recording capability was also validated by measuring the local field potential (LFP) from the somatosensory cortex with an in vivo experiment. The development of neural implants with maximized MRI compatibility indicates the possibility of potential tools for future neural diagnostics.

Advanced neuroimaging techniques to explore the effects of motor and cognitive rehabilitation in multiple sclerosis.

Progress in magnetic resonance imaging (MRI) technology and analyses is improving our comprehension of multiple sclerosis (MS) pathophysiology. These advancements, which enable the evaluation of atrophy, microstructural tissue abnormalities, and functional plasticity, are broadening our insights into the effectiveness and working mechanisms of motor and cognitive rehabilitative treatments. This narrative review with selected studies discusses findings derived from the application of advanced MRI techniques to evaluate structural and functional neuroplasticity modifications underlying the effects of motor and cognitive rehabilitative treatments in people with MS (PwMS). Current applications as outcome measure in longitudinal trials and observational studies, their interpretation and possible pitfalls and limitations in their use are covered. Finally, we examine how the use of these techniques could evolve in the future to improve monitoring of motor and cognitive rehabilitative treatments. Despite substantial variability in study design and participant characteristics in rehabilitative studies for PwMS, improvements in motor and cognitive functions accompanied by structural and functional brain modifications induced by rehabilitation can be observed. However, significant enhancements to refine rehabilitation strategies are needed. Future studies in this field should strive to implement standardized methodologies regarding MRI acquisition and processing, possibly integrating multimodal measures. This will help identifying relevant markers of treatment response in PwMS, thus improving the use of rehabilitative interventions at individual level. The combination of motor and cognitive strategies, longer periods of treatment, as well as adequate follow-up assessments will contribute to enhance the quality of evidence in support of their routine use.

Effects of mini-basketball training program on social communication impairments and regional homogeneity of brain functions in preschool children with autism spectrum disorder

BackgroundSocial communication impairments (SCI) is a core symptom of autism spectrum disorder (ASD) and is marked by challenges in social interaction. Although physical exercise has been shown to improve SCI, this finding has not been supported by comprehensive scientific evidence. Existing research has established a strong link between the SCI in children with ASD and abnormalities in regional homogeneity (ReHo). Therefore, investigating the effects of physical exercise on SCI and Reho in patients with ASD may help to elucidate the neurological mechanisms involved.MethodsThe present study included 30 preschool children diagnosed with ASD, with 15 participants in each group (experimental and control). The experimental group underwent a 12-week mini-basketball training program (MBTP) based on routine behavioral rehabilitation, while the control group only received routine behavioral rehabilitation. The Social Responsiveness Scale-Second Edition (SRS-2) was employed to assess SCI in both groups. Resting-state functional magnetic resonance imaging technology was used to evaluate ReHo in both groups.ResultsAfter 12-week of MBTP, significant group × time interactions were observed between the experimental and control groups in total SRS-2 scores (F = 14.514, p < 0.001, ηp2 = 0.341), as well as in the domains of social cognition (F = 15.620, p < 0.001, ηp2 = 0.358), social communication (F = 12.460, p < 0.01, ηp2 = 0.308), and autistic mannerisms (F = 9.970, p < 0.01, ηp2 = 0.263). No statistical difference was found in the scores for the social awareness subscale and social motivation subscale in the group × time interaction (all p > 0.05). The experimental group exhibited increased ReHo in the right Cerebellum_Crus1 and right parahippocampal gyrus, coupled with decreased ReHo in the left middle frontal gyrus (orbital part), left superior frontal gyrus (dorsolateral), left postcentral gyrus, and right superior parietal gyrus. Furthermore, a decrease in ReHo in the left postcentral gyrus positively correlated with changes in social communication scores in SCI behaviors (p < 0.05).ConclusionsOur study underscores the effectiveness of a 12-week MBTP in ameliorating SCI and abnormalities in ReHo among preschool children with ASD.Trial registrationThe trial is retrospectively registered on the Chinese Clinical Trial Registry (ChiCTR1900024973; August 5, 2019).

Measuring synovial thickness on knee MRI in pediatric patients with arthritis: is contrast necessary?

The use of contrast-enhanced imaging has long been standard for magnetic resonance imaging (MRI) assessments of synovitis in juvenile idiopathic arthritis (JIA). However, advancements in MRI technology have allowed for reliable identification of synovium without contrast. To assess the equivalence of unenhanced MRI with contrast-enhanced MRI in evaluating synovial thickness. This is an institutional review board approved, retrospective study performed in a tertiary children's hospital. Pediatric JIA patients under 21 years old were included who underwent knee MRI scans (1.5 T or 3 T) without and with contrast between January 2012 and January 2022. Two radiologists independently measured synovial thickness at 6 knee sites on contrast-enhanced and unenhanced sequences. Numerical measurements and ordinal scores based on juvenile idiopathic arthritis magnetic resonance imaging scoring (JAMRIS) system were recorded, and tests of equivalence were conducted, as well as between-reader and within-reader reliability by concordance correlation coefficient (CCC). All tests were considered significant at the 5% level. A total of 38 studies from 35 patients (25 females, median age 14 years; interquartile range 7 to 15.7) were included. Equivalence was demonstrated at each of the 6 sites for both continuous measurements (P-values < 0.05) and ordinal scores (P-values < 0.05) based on the average over readers. Within-reader reliability was moderate to high (CCC 0.50-0.89), except for the cruciate ligaments site. Averaged over the 6 sites, reliability between readers was low for unenhanced (CCC 0.47, with 95% CI: [0.41, 0.53]) and moderate for contrast-enhanced (CCC 0.64, with 95% CI: [0.59, 0.69]) sequences. Unenhanced knee MRI is equivalent to contrast-enhanced MRI in assessment of synovial thickness using conventional MRI sequences. Contrast material helped improve inter-reader reliability.

Reduced myelin content in bipolar disorder: A study of inhomogeneous magnetization transfer

BackgroundPrevious neuroimaging and pathological studies have found myelin-related abnormalities in bipolar disorder (BD), which prompted the use of magnetic resonance (MR) imaging technology sensitive to neuropathological changes to explore its neuropathological basis. We holistically investigated alterations in myelin within BD patients by inhomogeneous magnetization transfer (ihMT), which is sensitive and specific to myelin content. MethodsThirty-one BD and 42 healthy controls (HC) were involved. Four MR metrics, i.e., ihMT ratio (ihMTR), pseudo-quantitative ihMT (qihMT), magnetization transfer ratio and pseudo-quantitative magnetization transfer (qMT), were compared between groups using analysis methods based on whole-brain voxel-level and white matter regions of interest (ROI), respectively. ResultsThe voxel-wise analysis showed significantly inter-group differences of ihMTR and qihMT in the corpus callosum. The ROI-wise analysis showed that ihMTR, qihMT, and qMT values in BD group were significantly lower than that in HC group in the genu and body of corpus callosum, left anterior limb of the internal capsule, left anterior corona radiate, and bilateral cingulum (p < 0.001). And the qihMT in genu of corpus callosum and right cingulum were negatively correlated with depressive symptoms in BD group. LimitationsThis study is based on cross-sectional data and the sample size is limited. ConclusionThese findings suggest the reduced myelin content of anterior midline structure in the bipolar patients, which might be a critical pathophysiological feature of BD.

Wearable Coaxially-Shielded Metamaterial for Magnetic Resonance Imaging.

Recent advancements in metamaterials have yielded the possibility of a wireless solution to improve signal-to-noise ratio (SNR) in magnetic resonance imaging (MRI). Unlike traditional closely packed local coil arrays with rigid designs and numerous components, these lightweight, cost-effective metamaterials eliminate the need for radio frequency cabling, baluns, adapters, and interfaces. However, their clinical adoption is limited by their low sensitivity, bulky physical footprint, and limited, specific use cases. Herein, a wearable metamaterial developed using commercially available coaxial cable, designed for a 3.0T MRI system is introduced. This metamaterial inherits the coaxially-shielded structure of its constituent cable, confining the electric field within and mitigating coupling to its surroundings. This ensures safer clinical adoption, lower signal loss, and resistance to frequency shifts. Weighing only 50g, the metamaterial maximizes its sensitivity by conforming to the anatomical region of interest. MRI images acquired using this metamaterial with various pulse sequences achieve an SNR comparable or even surpass that of a state-of-the-art 16-channel knee coil. This work introduces a novel paradigm for constructing metamaterials in the MRI environment, paving the way for the development of next-generation wireless MRI technology.

The influence of modern computer and magnetic resonance imaging technologies on the preoperative staging of pancreatic cancer

Цель исследования: обзор и анализ зарубежной и отечественной литературы, клинических рекомендаций, посвященных оценке распространенности опухоли протоковой аденокарциномы поджелудочной железы и тактике лечения пациентов с выявленным новообразованием поджелудочной железы.Материал и методы. Проведен анализ отечественных и зарубежных источников литературы по базам PubMed с использованием ключевых слов “pancreatic cancer”, “vascular invasion”, “locally advanced cancer”, “cancer statistics”, “CT”, “MRI”, “neoadjuvant therapy” за последние 5–10 лет.В данном обзоре рассмотрены основные методы визуализации, используемые для определения взаимоотношения опухоли с прилежащими магистральными сосудами и оценки резектабельности рака поджелудочной железы.Заключение. Компьютерная томография и магнитно-резонансная томография с контрастным усилением – первоочередные методы диагностики протоковой аденокарциномы поджелудочной железы. Они высокоинформативны для оценки контакта/вовлечения сосудистых структур, распространенности опухолевого процесса, однако стандартные критерии неинформативны для оценки ответа на химиотерапевтическое лечение, поэтому требуется внедрение альтернативных способов его оценки, одним из которых является радиомика, лежащая в основе работы искусственного интеллекта и программ глубокого машинного обучения.

Intolerance of uncertainty affects the behavioral and neural mechanisms of higher generalization.

Intolerance of uncertainty (IU) is associated with several anxiety disorders. In this study, we employed rewards and losses as unconditioned positive and negative stimuli, respectively, to explore the effects of an individual's IU level on positive and negative generalizations using magnetic resonance imaging technology. Following instrumental learning, 48 participants (24 high IU; 24 low IU) were invited to complete positive and negative generalization tasks; their behavioral responses and neural activities were recorded by functional magnetic resonance imaging. The behavior results demonstrated that participants with high IUs exhibited higher generalizations to both positive and negative cues as compared with participants having low IUs. Neuroimaging results demonstrated that they exhibited higher activation levels in the right anterior insula and the default mode network (i.e. precuneus and posterior cingulate gyrus), as well as related reward circuits (i.e. caudate and right putamen). Therefore, higher generalization scores and the related abnormal brain activation may be key markers of IU as a vulnerability factor for anxiety disorders.

Navigating Neural Landscapes: A Comprehensive Review of Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) Applications in Epilepsy.

This review comprehensively explores the evolving role of neuroimaging, specifically magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS), in epilepsy research and clinical practice. Beginning with a concise overview of epilepsy, the discussion emphasizes the crucial importance of neuroimaging in diagnosing and managing this complex neurological disorder. The review delves into the applications of advanced MRI techniques, including high-field MRI, resting-state fMRI, and connectomics, highlighting their impact on refining our understanding of epilepsy's structural and functional dimensions. Additionally, it examines the integration of machine learning in the analysis of intricate neuroimaging data. Moving to the clinical domain, the review outlines the utility of neuroimaging in pre-surgical evaluations and the monitoring of treatment responses and disease progression. Despite significant strides, challenges and limitations are discussed in the routine clinical incorporation of neuroimaging. The review explores promising developments in MRI and MRS technology, potential advancements in imaging biomarkers, and the implications for personalized medicine in epilepsy management. The conclusion underscores the transformative potential of neuroimaging and advocates for continued exploration, collaboration, and technological innovation to propel the field toward a future where tailored, effective interventions improve outcomes for individuals with epilepsy.

Development of a patient specific cartilage graft using magnetic resonance imaging and 3D printing

ObjectivesThe goal of this project was to develop and validate a patient-specific, anatomically correct graft for cartilage restoration using magnetic resonance imaging (MRI) data and 3-dimensional (3D) printing technology. The specific aim was to test the accuracy of a novel method for 3D printing and implanting individualized, anatomically shaped bio-scaffolds to treat cartilage defects in a human cadaveric model. We hypothesized that an individualized, anatomic 3D-printed scaffold designed from MRI data would provide a more optimal fill for a large cartilage defect compared to a generic flat scaffold. MethodsFour focal cartilage defects (FCDs) were created in paired human cadaver knees, age <40 years, in the weight-bearing surfaces of the medial femoral condyle (MFC), lateral femoral condyle (LFC), patella, and trochlea of each knee. MRIs were obtained, anatomic grafts were designed and 3D printed for the left knee as an experimental group, and generic flat grafts for the right knee as a control group. Grafts were implanted into corresponding defects and fixed using tissue adhesive. Repeat post-implant MRIs were obtained. Graft step-off was measured as the distance in mm between the surface of the graft and the native cartilage surface in a direction perpendicular to the subchondral bone. Graft contour was measured as the gap between the undersurface of the graft and the subchondral bone in a direction perpendicular to the joint surface. ResultsGraft step-off was statistically significantly better for the anatomic grafts compared to the generic grafts in the MFC (0.0 ​± ​0.2 ​mm vs. 0.7 ​± ​0.5 ​mm, p ​< ​0.001), LFC (0.1 ​± ​0.3 ​mm vs. 1.0 ​± ​0.2 ​mm, p ​< ​0.001), patella (−0.2 ​± ​0.3 ​mm vs. −1.2 ​± ​0.4 ​mm, p ​< ​0.001), and trochlea (−0.4 ​± ​0.3 vs. 0.4 ​± ​0.7, p ​= ​0.003). Graft contour was statistically significantly better for the anatomic grafts in the LFC (0.0 ​± ​0.0 ​mm vs. 0.2 ​± ​0.4 ​mm, p ​= ​0.022) and trochlea (0.0 ​± ​0.0 ​mm vs. 1.4 ​± ​0.7 ​mm, p ​< ​0.001). The anatomic grafts had an observed maximum step-off of −0.9 ​mm and a maximum contour mismatch of 0.8 ​mm. ConclusionThis study validates a process designed to fabricate anatomically accurate cartilage grafts using MRI and 3D printing technology. Anatomic grafts demonstrated superior fit compared to generic flat grafts. Level of evidenceLevel IV.

Brain mechanism of acupuncture for children with anisometropic amblyopia: a resting functional magnetic resonance imaging study based on voxel-mirrored homotopic connectivity.

To explore the brain mechanism of acupuncture for children with anisometropic amblyopia using the voxel-mirror homotopic connectivity (VMHC) analysis method of resting functional magnetic resonance imaging (rs-fMRI) technology based on clinical effectiveness. Eighty children with anisometropic monocular amblyopia were randomly divided into two groups: control (40 cases, 1 case of shedding) and acupuncture (40 cases, 1 case of shedding) groups. The control group was treated with glasses, red flash, grating, and visual stimulations, with each procedure conducted for 5min per time. Based on routine treatment, the acupuncture group underwent acupuncture of "regulating qi and unblocking meridians to bright eyes", Jingming (BL1), Cuanzhu (BL2), Guangming (GB37), Fengchi (GB20) acupoints were taken on both sides, with the needle kept for 30min each time. Both groups were treated once every other day, three times per week, for a total of 4wk. After the treatment, the overall curative effect of the two groups and the latency and amplitude changes of P100 wave of pattern visual-evoked potential were counted. At the same time, nine children with left eye amblyopia were randomly selected from the two groups and were scanned with rs-fMRI before and after treatment. The differences in the brain regions between the two groups were compared and analyzed with VMHC. Chi-square test showed a notable difference in the total efficiency rate between the acupuncture (94.87%) and control groups (79.49%). Regarding the P100 wave latency and amplitude, the acupuncture group had significantly shorter latency and higher amplitude of P100 wave than the control group. Moreover, the VMHC values of the bilateral temporal lobe, superior temporal gyrus, and middle temporal gyrus were notably increased in the acupuncture group after treatment. Acupuncture combined with conventional treatment can significantly improve the corrected visual acuity and optic nerve conduction in children with anisometropic amblyopia. Compared with the conventional treatment, the regulation of acupuncture on the functional activities of the relevant brain areas in the anterior cerebellum may be an effective acupuncture mechanism for anisometropic amblyopia.

Narrative review of magnetic resonance imaging in quantifying liver iron load.

To summarize the research progress of magnetic resonance imaging (MRI) in quantifying liver iron load. To summarize the current status and progress of MRI technology in the quantitative study of liver iron load through reviewing the relevant literature at home and abroad. Different MRI sequence examination techniques have formed a series of non-invasive methods for the examination of liver iron load. These techniques have important clinical significance in the imaging diagnosis of liver iron load. So far, the main MRI methods used to assess liver iron load are: signal intensity measurement method (signal intensity, SI) [signal intensity ratio (SIR) and difference in in-phase and out-of-phase signal intensity], T2/R2 measurement (such as FerriScan technique), ultra-short echo time (UTE) imaging technique, and susceptibility weighted imaging (including conventional susceptibility weighted imaging) (SWI), quantitative susceptibility mapping (QSM), T2*/R2* measurement, Dixon and its derivative techniques. MRI has become the first choice for the non-invasive examination of liver iron overload, and it is helpful to improve the early detection of liver injury, liver fibrosis, liver cirrhosis and liver cancer caused by liver iron overload.

AI-Enhanced Detection of Clinically Relevant Structural and Functional Anomalies in MRI: Traversing the Landscape of Conventional to Explainable Approaches.

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of commonly used metrics. Further, this paper explores the latest developments in ensemble methods and explainable AI, offering insights into future directions and potential breakthroughs. This review synthesizes current insights, offering a valuable guide for researchers, clinicians, and medical imaging experts. It highlights AI's crucial role in improving the precision and speed of detecting key structural and functional irregularities in MRI. Our exploration of innovative techniques and trends furthers MRI technology development, aiming to refine diagnostics, tailor treatments, and elevate patient care outcomes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.

Pregnancy-induced remodeling of the murine reproductive tract: a longitudinal in vivo magnetic resonance imaging study

Mammalian pregnancy requires gradual yet extreme remodeling of the reproductive organs to support the growth of the embryos and their birth. After delivery, the reproductive organs return to their non-pregnant state. As pregnancy has traditionally been understudied, there are many unknowns pertaining to the mechanisms behind this remarkable remodeling and repair process which, when not successful, can lead to pregnancy-related complications such as maternal trauma, pre-term birth, and pelvic floor disorders. This study presents the first longitudinal imaging data that focuses on revealing anatomical alterations of the vagina, cervix, and uterine horns during pregnancy and postpartum using the mouse model. By utilizing advanced magnetic resonance imaging (MRI) technology, T1-weighted and T2-weighted images of the reproductive organs of three mice in their in vivo environment were collected at five time points: non-pregnant, mid-pregnant (gestation day: 9–10), late pregnant (gestation day: 16–17), postpartum (24–72 h after delivery) and three weeks postpartum. Measurements of the vagina, cervix, and uterine horns were taken by analyzing MRI segmentations of these organs. The cross-sectional diameter, length, and volume of the vagina increased in late pregnancy and then returned to non-pregnant values three weeks after delivery. The cross-sectional diameter of the cervix decreased at mid-pregnancy before increasing in late pregnancy. The volume of the cervix peaked at late pregnancy before shortening by 24–72 h postpartum. As expected, the uterus increased in cross-sectional diameter, length, and volume during pregnancy. The uterine horns decreased in size postpartum, ultimately returning to their average non-pregnant size three weeks postpartum. The newly developed methods for acquiring longitudinal in vivo MRI scans of the murine reproductive system can be extended to future studies that evaluate functional and morphological alterations of this system due to pathologies, interventions, and treatments.

DAFNet: A dual attention-guided fuzzy network for cardiac MRI segmentation

&lt;abstract&gt; &lt;sec&gt;&lt;title&gt;Background&lt;/title&gt;&lt;p&gt;In clinical diagnostics, magnetic resonance imaging (MRI) technology plays a crucial role in the recognition of cardiac regions, serving as a pivotal tool to assist physicians in diagnosing cardiac diseases. Despite the notable success of convolutional neural networks (CNNs) in cardiac MRI segmentation, it remains a challenge to use existing CNNs-based methods to deal with fuzzy information in cardiac MRI. Therefore, we proposed a novel network architecture named DAFNet to comprehensively address these challenges.&lt;/p&gt; &lt;/sec&gt; &lt;sec&gt;&lt;title&gt;Methods&lt;/title&gt;&lt;p&gt;The proposed method was used to design a fuzzy convolutional module, which could improve the feature extraction performance of the network by utilizing fuzzy information that was easily ignored in medical images while retaining the advantage of attention mechanism. Then, a multi-scale feature refinement structure was designed in the decoder portion to solve the problem that the decoder structure of the existing network had poor results in obtaining the final segmentation mask. This structure further improved the performance of the network by aggregating segmentation results from multi-scale feature maps. Additionally, we introduced the dynamic convolution theory, which could further increase the pixel segmentation accuracy of the network.&lt;/p&gt; &lt;/sec&gt; &lt;sec&gt;&lt;title&gt;Result&lt;/title&gt;&lt;p&gt;The effectiveness of DAFNet was extensively validated for three datasets. The results demonstrated that the proposed method achieved DSC metrics of 0.942 and 0.885, and HD metricd of 2.50mm and 3.79mm on the first and second dataset, respectively. The recognition accuracy of left ventricular end-diastolic diameter recognition on the third dataset was 98.42%.&lt;/p&gt; &lt;/sec&gt; &lt;sec&gt;&lt;title&gt;Conclusion&lt;/title&gt;&lt;p&gt;Compared with the existing CNNs-based methods, the DAFNet achieved state-of-the-art segmentation performance and verified its effectiveness in clinical diagnosis.&lt;/p&gt; &lt;/sec&gt; &lt;/abstract&gt;

A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging.

Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts extensive research interests. Recent deep learning has shown its great potential in improving image quality and reconstruction speed. Faithful coil sensitivity estimation is vital for MRI reconstruction. However, most deep learning methods still rely on pre-estimated sensitivity maps and ignore their inaccuracy, resulting in the significant quality degradation of reconstructed images. In this work, we propose a Joint Deep Sensitivity estimation and Image reconstruction network, called JDSI. During the image artifacts removal, it gradually provides more faithful sensitivity maps with high-frequency information, leading to improved image reconstructions. To understand the behavior of the network, the mutual promotion of sensitivity estimation and image reconstruction is revealed through the visualization of network intermediate results. Results on in vivo datasets and radiologist reader study demonstrate that, for both calibration-based and calibrationless reconstruction, the proposed JDSI achieves the state-of-the-art performance visually and quantitatively, especially when the acceleration factor is high. Additionally, JDSI owns nice robustness to patients and autocalibration signals.