Magnetic Resonance Imaging Techniques Research Articles

Changes in the central nervous system in football players: an MRI study.

Football (soccer) is the world's most popular team sport. To comprehensively examine the brain in football (soccer) players, with the use of magnetic resonance imaging (MRI) techniques. The study involved 65 football players and 62 controls. The MR examinations were performed using MR 1.5-T system (Optima MR 360; GE Medical Systems). The examinations were carried out in the 3D Bravo, CUBE, FSEpropeller, and diffusion-weighted imaging (DWI) sequences. The 1HMRS signal was obtained from the volume of interest in the frontal and occipital lobes on both sides. The present study, based on structural MRI, shows some changes in the brains of the group of football players. The findings show asymmetry of the ventricular system in four football players, arachnoid cysts in the parieto-occipital region, and pineal cysts. NAA/Cr concentration in the right frontal lobe was lower in the football players than in the controls, and the Glx/Cr concentration in the right occipital lobe was higher. The apparent diffusion coefficient value is lower in football players in the occipital lobes. Playing football can cause measurable changes in the brain, known to occur in patients diagnosed with traumatic brain injury. The present findings fill the gap in the literature by contributing evidence showing that playing football may lead to changes in the brain, without clinical symptoms of concussion.

A comprehensive review on role of magnetic resonance imaging in the precise measurement of corpus callosum

Magnetic Resonance Imaging (MRI) has emerged as a powerful and non-invasive imaging technique, playing a pivotal role in neuroimaging research and clinical diagnosis. This comprehensive review explores the significance of MRI in the precise measurement of the corpus callosum, a key structure connecting the two hemispheres of the brain. The corpus callosum plays a crucial role in inter hemispheric communication and is implicated in various neurological and psychiatric disorders. The review begins by elucidating the anatomy and functions of the corpus callosum, emphasizing its importance in facilitating seamless communication between the cerebral hemispheres. Subsequently, the paper delves into the historical evolution of MRI techniques and how advancements have enhanced the visualization and measurement capabilities of the corpus callosum. A detailed examination of various MRI modalities, including structural MRI, diffusion tensor imaging (DTI), and functional MRI, is presented in the context of corpus callosum analysis. Structural MRI provides high-resolution images for accurate morphological assessments, while DTI offers insights into white matter microstructure and fiber tractography, allowing for a more comprehensive understanding of the corpus callosum's integrity. The review also highlights the role of MRI in investigating alterations in the corpus callosum associated with neurological disorders such as multiple sclerosis, epilepsy, and neurodevelopmental disorders. Additionally, the paper explores how functional MRI contributes to understanding the functional connectivity and inter hemispheric interactions mediated by the corpus callosum. Challenges and limitations in the measurement of the corpus callosum using MRI are discussed, including methodological considerations, image artifacts, and potential sources of variability. The review concludes by outlining future directions in corpus callosum imaging research, including the integration of advanced imaging techniques, artificial intelligence, and large-scale multi-center studies to enhance the precision and reliability of measurements.In summary, this comprehensive review underscores the pivotal role of MRI in advancing our understanding of the corpus callosum, providing valuable insights into both normal brain function and pathological conditions. The continual evolution of MRI techniques holds promise for further refining the assessment of the corpus callosum, ultimately contributing to improved diagnostic accuracy and therapeutic interventions in neurological and psychiatric disorders.

Ultrahigh field diffusion magnetic resonance imaging uncovers intriguing microstructural changes in the adult zebrafish brain caused by Toll-like receptor 2 genomic deletion.

Toll-like receptor 2 (TLR2) belongs to the TLR protein family that plays an important role in the immune and inflammation response system. While TLR2 is predominantly expressed in immune cells, its expression has also been detected in the brain, specifically in microglia and astrocytes. Recent studies indicate that genomic deletion of TLR2 can result in impaired neurobehavioural function. It is currently not clear if the genomic deletion of TLR2 leads to any alterations in the microstructural features of the brain. In the current study, we noninvasively assess microstructural changes in the brain of TLR2-deficient (tlr2-/-) zebrafish using state-of-the art magnetic resonance imaging (MRI) methods at ultrahigh magnetic field strength (17.6 T). A significant increase in cortical thickness and an overall trend towards increased brain volumes were observed in young tlr2-/- zebrafish. An elevated T2 relaxation time and significantly reduced apparent diffusion coefficient (ADC) unveil brain-wide microstructural alterations, potentially indicative of cytotoxic oedema and astrogliosis in the tlr2-/- zebrafish. Multicomponent analysis of the ADC diffusivity signal by the phasor approach shows an increase in the slow ADC component associated with restricted diffusion. Diffusion tensor imaging and diffusion kurtosis imaging analysis revealed diminished diffusivity and enhanced kurtosis in various white matter tracks in tlr2-/- compared with control zebrafish, identifying the microstructural underpinnings associated with compromised white matter integrity and axonal degeneration. Taken together, our findings demonstrate that the genomic deletion of TLR2 results in severe alterations to the microstructural features of the zebrafish brain. This study also highlights the potential of ultrahigh field diffusion MRI techniques in discerning exceptionally fine microstructural details within the small zebrafish brain, offering potential for investigating microstructural changes in zebrafish models of various brain diseases.

Validity of dynamic contrast-enhanced magnetic resonance imaging of the breast versus diffusion-weighted imaging and magnetic resonance spectroscopy in predicting the malignant nature of non-mass enhancement lesions

BackgroundBreast cancer is the commonest cancer affecting women worldwide. So, it is important to accurately detect and classify different breast lesions. Noninvasive methods for tissue characterization have increased interest, particularly for early diagnosis. Non-mass enhancement (NME) breast lesions are described in magnetic resonance imaging (MRI) as the presence of enhancement without space-occupying lesions. Several studies have described that certain characteristics can be used as new indicators of malignancy in breast NME lesions. We aimed to study the role of multiparametric-MRI (Mp-MRI) as diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) in assessment of NME lesions and to suggest which one offers the greatest diagnostic accuracy.MethodsThis retrospective study was conducted from March 2017 to December 2023 on 220 NME breast lesions. All lesions were analyzed to study the features of benign and malignant NME lesions using different MRI techniques including dynamic contrast-enhanced MRI (DCE-MRI), DWI, and MRS. Breast MRI was performed at 1.5 Tesla, findings were correlated with histopathological results of all cases.ResultsPatients’ mean age was 46.56 years with 220 NME breast lesions (54 were benign and 166 were malignant). Invasive ductal carcinoma with ductal carcinoma in situ was the most malignant type representing 93 cases. We found that segmental distribution, heterogeneous enhancement, type III curve, restricted diffusion, lower apparent diffusion coefficient, and positive choline peak were more with malignancy (P = 0.008, 0.02, 0.004, 0.001, and < 0.001). We detected that Mp-MRI has higher diagnostic accuracy than DCE-MRI and combined other functional sequences (DWI, MRS), it was 91.2% with sensitivity 89.9%, specificity 87.8%, positive predictive value 89.2%, and negative predictive value 82.2%.ConclusionsFunctional MRI techniques, such as DWI and MRS, can provide helpful information in assessment of NME lesions. They have high diagnostic accuracy, sensitivity, and specificity in characterizing NME breast lesions as benign or malignant. However, DCE-MRI is mandatory for lesion characterization and delineation of its nature and cannot be replaced by them alone in cases of lesion visualization. So, multiparametric-MRI can improve the diagnostic accuracy of NME breast lesions when combined with dynamic contrast-enhanced MRI and can help in reducing negative biopsy rates.

Brain structure comparison among Parkinson disease, essential tremor, and healthy controls using 7T MRI.

Both Parkinson disease (PD) and Essential tremor (ET) are movement disorders causing tremors in elderly individuals. Although PD and ET are different disease, they often present with similar initial symptoms, making their differentiation challenging with magnetic resonance imaging (MRI) techniques. This study aimed to identify structural brain differences among PD, ET, and health controls (HCs) using 7-Tesla (T) MRI. We assessed the whole-brain parcellation in gray matter volume, thickness, subcortical volume, and small regions of basal ganglia in PD (n = 18), ET (n = 15), and HCs (n = 18), who were matched for age and sex. Brain structure analysis was performed automatic segmentation through Freesurfer software. Small regions of basal ganglia were manually segmented by ITK-SNAP. Additionally, we examined the associations between clinical indicators (symptom duration, unified Parkinson diseases rating scale (UPDRS), and clinical rating scale for tremor (CRST)) and brain structure. PD showed a significant reduction in gray matter volume in the postcentral region compared to ET. ET showed a significant reduction in cerebellum volume compared to HCs. There was a negative correlation between CRST scores (B and C) and gray matter thickness in right superior frontal in ET. This study demonstrated potential of 7T MRI in differentiating brain structure differences among PD, ET, and HCs. Specific findings, such as parietal lobe atrophy in PD compared to ET and cerebellum atrophy in ET compared to HCs, the importance of advanced imaging techniques in accurately diagnosing and distinguishing between movement disorders that present with similar initial symptoms.

Identification of diffusion, kurtosis, and propagator MRI markers of Alzheimer’s disease pathology in post-mortem human tissue

Abstract Alzheimer’s disease (AD) is an irreversible degenerative brain disease affecting 6.7 million Americans and while the hallmark AD pathologies of plaques and tangles follow a stereotyped progression during the course of the disease, clinical markers for early diagnosis are lacking and approximately 20% of all AD cases are ultimately misdiagnosed. Conventional clinical MRI is capable of reporting severe brain atrophy, but fails to recognize earlier biomarkers associated with more subtle cellular and molecular changes. Microstructural Magnetic Resonance Imaging (MRI) techniques are promising to address this challenge and may sensitively detect and distinguish tissue degeneration, tauopathies, and beta amyloid plaques to improve accuracy of diagnosis and enable early detection. The objective of this study was to identify and compare the most promising microstructural markers of AD pathology over a range of diffusion and relaxometry-based MRI techniques from conventional to advanced. To accomplish this, we performed MRI microscopy of post-mortem human temporal lobe specimens (n = 14) at high resolution and image quality and evaluated the relative influence of metrics across multiple microstructural MRI frameworks using principal component analysis (PCA). We performed additional correlation analysis between metrics identified by PCA and clinical neuropathology scores of Braak stage and plaque and tangle load. Hippocampal diffusion and restriction metrics contributed most to the first principal component, and the correlation with Braak score was positive for diffusivity and negative for restriction metrics. Additionally, the MAP-MRI propagator anisotropy (PA) metric of microscale anisotropy was strongly and negatively correlated with AD pathology while the conventional fractional anisotropy (FA) metric showed little or no correspondence and there was not a strong association between FA and PA by PCA. Entorhinal cortex findings were minimal except for reported increases in restriction due to plaque content. Taken together, our findings suggest that microstructural MRI metrics of restriction and diffusion are most prominent and may reflect degenerative processes in AD brain tissue and that microscale anisotropy may be more advantageous than conventional FA for the detection of subtle and earlier cellular changes in AD.

"Feed-and-wrap" technique versus deep sedation for neonatal magnetic resonance imaging: a retrospective comparative study.

Neonatal MRI is usually performed under deep sedation, which is challenging-especially in low-weight premature patients. In addition, long-term side effects, such as neurotoxicity, are of concern. An alternative to sedation is to induce natural sleep by feeding and immobilising the child, the "feed-and-wrap" technique (FWT). The objective of this study was to evaluate differences in image quality between neonates examined under sedation and by using the FWT during the first four months of life. We retrospectively assessed image quality (based on a 4-point semiquantitative scale) of all MRI examinations in neonates performed at our institution between July 2009 and August 2022. Differences in image quality between examinations under sedation versus FWT were evaluated. We included 432 consecutive patients, 243 (56%) using sedation and 189 (44%) using the FWT. Corrected age and body weight (mean ± SD: 3.7 ± 1.1 versus 4.5 ± 1.3 kg, p < 0.001) were significantly lower in the FWT group. The overall success rate in the FWT group was 95%. Image quality was slightly lower when using the FWT (mean ± SD: 3.7 ± 0.43 versus 3.96 ± 0.11, p < 0.001). Multivariate analysis showed a higher risk of acquiring sequences with diagnostic limitations in the FWT group (p < 0.001), increasing with corrected age (p = 0.048). The FWT is a highly successful method to perform MRI scans in term and preterm neonates. Overall image quality is only slightly lower than under sedation. Especially in immature low-weight preterm patients, the FWT is a reliable option to perform MRI studies without exposing the child to risks associated with sedation. The "feed-and-wrap" technique enables high-quality MRI examinations in neonates, including low-weight premature patients. Deep sedation for diagnostic MRI procedures in this age group, which has the risk of short- and long-term complications, can often be avoided. Deeply sedating neonates for MR examinations comes with risks. Image quality is only slightly lower when using the "feed-and-wrap" technique. The "feed-and-wrap" technique is feasible even in low-weight premature infants.

Diffusion magnetic resonance imaging of cerebrospinal fluid dynamics: Current techniques and future advancements.

Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para-arterial spaces, interstitial spaces, and para-venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion-based imaging, especially when differentiating between tissue- and fluid-related changes or elucidating structural versus functional alterations.

Assessment of Hypoxia in Breast Cancer: Emerging Functional MR Imaging and Spectroscopy Techniques and Clinical Applications.

Breast cancer is one of the most prevalent forms of cancer affecting women worldwide. Hypoxia, a condition characterized by insufficient oxygen supply in tumor tissues, is closely associated with tumor aggressiveness, resistance to therapy, and poor clinical outcomes. Accurate assessment of tumor hypoxia can guide treatment decisions, predict therapy response, and contribute to the development of targeted therapeutic interventions. Over the years, functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS) techniques have emerged as promising noninvasive imaging options for evaluating hypoxia in cancer. Such techniques include blood oxygen level-dependent (BOLD) MRI, oxygen-enhanced MRI (OE) MRI, chemical exchange saturation transfer (CEST) MRI, and proton MRS (1H-MRS). These may help overcome the limitations of the routinely used dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) techniques, contributing to better diagnosis and understanding of the biological features of breast cancer. This review aims to provide a comprehensive overview of the emerging functional MRI and MRS techniques for assessing hypoxia in breast cancer, along with their evolving clinical applications. The integration of these techniques in clinical practice holds promising implications for breast cancer management. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Improved Cerebral Glymphatic Flow after Transvenous Embolization of CSF-Venous Fistula.

Spontaneous intracranial hypotension is characterized by symptoms of low intracranial CSF volume due to various mechanisms of CSF leakage. One such mechanism is a CSF-venous fistula, treatable with transvenous embolization resulting in substantial radiographic and clinical improvement. However, the exact mechanisms underlying these improvements, including the potential involvement of the glymphatic system, remain unclear. To noninvasively assess glymphatic clearance in spontaneous intracranial hypotension, we used an advanced MR imaging technique called the DTI along the perivascular spaces in 3 patients with CSF-venous fistula before and after embolization. All 3 patients with spontaneous intracranial hypotension initially had low glymphatic flow, which improved postembolization. Two patients with symptomatic improvement exhibited a more substantial increase in glymphatic flow compared with a patient with minimal improvement. These findings suggest a possible link between cerebral glymphatics in spontaneous intracranial hypotension pathophysiology and symptomatic improvement, warranting larger studies to explore the role of the glymphatic system in spontaneous intracranial hypotension.

Accelerating cardiac diffusion tensor imaging using Swin transformer with octave convolution

AbstractCardiac diffusion tensor imaging (cDTI) is a promising and noninvasive magnetic resonance imaging (MRI) technique for assessing myocardial fiber microstructure. However, its clinical application is hampered by lengthy scanning and susceptibility to motion artifacts. This study proposes a cDTI reconstruction model (OSDTI), which leverages octave convolution (OctConv) and Swin Transformer to reconstruct diffusion‐weighted (DW) images from undersampled k‐space data. Our model capitalizes on the strengths of both OctConv and Swin Transformers. Specifically, the OctConv module excels at capturing intricate details and texture information within DW images, while the residual‐connected Swin Transformer module facilitates information retention across various feature extraction stages, thereby enhancing overall image comprehension and reconstruction accuracy. The evaluation of OSDTI using a human ex vivo heart dataset robustly validated the generalization ability of the model. Comparative analyze against existing deep‐learning methods demonstrated OSDTI's superior performance in both DW image quality and diffusion tensor metrics.

Scan With Me (SWiM): A train-the-trainer program to upskill MRI personnel in low- and middle- income countries.

PurposeAccess to magnetic resonance imaging (MRI) in low-and-middle-income countries (LMICs) remains among the poorest in the world. The lack of skilled MRI personnel exacerbates access gaps, reinforcing longstanding health disparities. The SWiM Program aims to sustainably create a network of highly skilled MRI technologists in LMICs who will facilitate the transfer of MRI knowledge and skills to their peers and contribute to implementation of highly valuable imaging protocols for impactful clinical and research use. MethodsThe program introduces a case-based curriculum designed using a novel train-the-trainer approach, integrated with peer collaborative learning to upskill practicing MRI technologists in LMICs. The six-week curriculum uses the Teach-Try-Use approach, which combines self-paced didactic lectures covering the basics of MR image acquisition (teach) with hands-on expert-guided scanning experience (try), and implementation of protocols tailored to provide the best possible images on their infrastructures (use). Each program includes research translation skills training using an established advanced MRI technique relevant to LMICs. A pilot program focused on cardiac MRI (CMR) was conducted to assess the program’s curriculum, delivery, and evaluation methods. ResultsForty-three MRI technologists from 16 LMICs participated in the pilot CMR program and over the course of the training, implemented optimized CMR protocols that reduced acquisition times while improving image quality. The training resources and scanner-specific standardized protocols are published openly for public use on an online repository. In general, at the end of the program, learners reported considerable improvements in CMR knowledge and skills. All respondents to the program evaluation survey agreed to recommend the program to their colleagues, while 87% indicated interest in returning to help train others. DiscussionThe SWiM Program is the first masterclass in MRI acquisition for practicing imaging technologists in LMICS. The program holds the potential to help reduce disparities in MRI expertise and access. The support of the MRI community, imaging societies, and funding agencies will increase its reach and further its impact in democratizing MRI.

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.

Electroacupuncture modulates abnormal brain connectivity after ischemia reperfusion injury in rats: A graph theory-based approach.

Electroacupuncture (EA) has been shown to facilitate brain plasticity-related functional recovery following ischemic stroke. The functional magnetic resonance imaging technique can be used to determine the range and mode of brain activation. After stroke, EA has been shown to alter brain connectivity, whereas EA's effect on brain network topology properties remains unclear. An evaluation of EA's effects on global and nodal topological properties in rats with ischemia reperfusion was conducted in this study. There were three groups of adult male Sprague-Dawley rats: sham-operated group (sham group), middle cerebral artery occlusion/reperfusion (MCAO/R) group, and MCAO/R plus EA (MCAO/R+EA) group. The differences in global and nodal topological properties, including shortest path length, global efficiency, local efficiency, small-worldness index, betweenness centrality (BC), and degree centrality (DC) were estimated. Graphical network analyses revealed that, as compared with the sham group, the MCAO/R group demonstrated a decrease in BC value in the right ventral hippocampus and increased BC in the right substantia nigra, accompanied by increased DC in the left nucleus accumbens shell (AcbSh). The BC was increased in the right hippocampus ventral and decreased in the right substantia nigra after EA intervention, and MCAO/R+EA resulted in a decreased DC in left AcbSh compared to MCAO/R. The results of this study provide a potential basis for EA to promote cognitive and motor function recovery after ischemic stroke.

Automatic brain-tumor diagnosis using cascaded deep convolutional neural networks with symmetric U-Net and asymmetric residual-blocks

The use of various kinds of magnetic resonance imaging (MRI) techniques for examining brain tissue has increased significantly in recent years, and manual investigation of each of the resulting images can be a time-consuming task. This paper presents an automatic brain-tumor diagnosis system that uses a CNN for detection, classification, and segmentation of glioblastomas; the latter stage seeks to segment tumors inside glioma MRI images. The structure of the developed multi-unit system consists of two stages. The first stage is responsible for tumor detection and classification by categorizing brain MRI images into normal, high-grade glioma (glioblastoma), and low-grade glioma. The uniqueness of the proposed network lies in its use of different levels of features, including local and global paths. The second stage is responsible for tumor segmentation, and skip connections and residual units are used during this step. Using 1800 images extracted from the BraTS 2017 dataset, the detection and classification stage was found to achieve a maximum accuracy of 99%. The segmentation stage was then evaluated using the Dice score, specificity, and sensitivity. The results showed that the suggested deep-learning-based system ranks highest among a variety of different strategies reported in the literature.

A genetic optimisation and iterative reconstruction framework for sparse multi-dimensional diffusion–relaxation correlation MRI

Multi-dimensional diffusion–relaxation correlation (DRC) magnetic resonance imaging (MRI) techniques have recently been developed to investigate tissue microstructures. Sub-voxel tissue heterogeneity is resolved from the local correlation distributions of relaxation time and molecular diffusivity. However, the implementation of these techniques considerably increases the total acquisition time, and simply reducing the scan time may be at the expense of detailed structural resolution. To overcome these limitations, an optimised framework was proposed for acquiring microstructural maps of the human brain on a clinically feasible timescale. First, the acquisition parameters of the multi-dimensional DRC MRI method were sparsely optimised using a genetic algorithm with a fitness function according to the spectral resolution of the correlation map, hardware requirements, and total scan time. Next, the acquired DRC MRI data were processed using a proposed numerical algorithm based on the dynamic inverse Laplace transform (ILT). Prior knowledge from one-dimensional data was then utilised in the iterative procedure to improve the spectral resolution. Finally, the proposed framework was validated using Monte Carlo simulations and experimental data acquired from healthy participants on an MRI scanner. The results demonstrated that the suggested approach is feasible for offering high-resolution DRC maps that correspond to distinct microstructures with a limited amount of optimised acquisition data from two-dimensional DRC sampling space. By significantly reducing scan time while retaining structural resolution, this approach may enable multi-dimensional DRC MRI to be more widely used for quantitative evaluation in biological and medical settings.

DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain.

Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susceptibility distribution from the measured local field obtained from the MR phase. Although existing deep learning based QSM methods can produce high-quality reconstruction, they are highly biased toward training data distribution with less scope for generalizability. This work proposes a hybrid two-step reconstruction approach to improve deep learning based QSM reconstruction. The susceptibility map prediction obtained from the deep learning methods has been refined in the framework developed in this work to ensure consistency with the measured local field. The developed method was validated on existing deep learning and model-based deep learning methods for susceptibility mapping of the brain. The developed method resulted in improved reconstruction for MRI volumes obtained with different acquisition settings, including deep learning models trained on constrained (limited) data settings.

Precision Identification of Locally Advanced Rectal Cancer in Denoised CT Scans Using EfficientNet and Voting System Algorithms.

Local advanced rectal cancer (LARC) poses significant treatment challenges due to its location and high recurrence rates. Accurate early detection is vital for treatment planning. With magnetic resonance imaging (MRI) being resource-intensive, this study explores using artificial intelligence (AI) to interpret computed tomography (CT) scans as an alternative, providing a quicker, more accessible diagnostic tool for LARC. In this retrospective study, CT images of 1070 T3-4 rectal cancer patients from 2010 to 2022 were analyzed. AI models, trained on 739 cases, were validated using two test sets of 134 and 197 cases. By utilizing techniques such as nonlocal mean filtering, dynamic histogram equalization, and the EfficientNetB0 algorithm, we identified images featuring characteristics of a positive circumferential resection margin (CRM) for the diagnosis of locally advanced rectal cancer (LARC). Importantly, this study employs an innovative approach by using both hard and soft voting systems in the second stage to ascertain the LARC status of cases, thus emphasizing the novelty of the soft voting system for improved case identification accuracy. The local recurrence rates and overall survival of the cases predicted by our model were assessed to underscore its clinical value. The AI model exhibited high accuracy in identifying CRM-positive images, achieving an area under the curve (AUC) of 0.89 in the first test set and 0.86 in the second. In a patient-based analysis, the model reached AUCs of 0.84 and 0.79 using a hard voting system. Employing a soft voting system, the model attained AUCs of 0.93 and 0.88, respectively. Notably, AI-identified LARC cases exhibited a significantly higher five-year local recurrence rate and displayed a trend towards increased mortality across various thresholds. Furthermore, the model's capability to predict adverse clinical outcomes was superior to those of traditional assessments. AI can precisely identify CRM-positive LARC cases from CT images, signaling an increased local recurrence and mortality rate. Our study presents a swifter and more reliable method for detecting LARC compared to traditional CT or MRI techniques.

Peak Resembling N-acetylaspartate (NAA) on Magnetic Resonance Spectroscopy of Brain Metastases.

Background and Objectives: Differentiating between a high-grade glioma (HGG) and solitary cerebral metastasis presents a challenge when using standard magnetic resonance imaging (MRI) alone. Magnetic resonance spectroscopy (MRS), an advanced MRI technique, may assist in resolving this diagnostic dilemma. N-acetylaspartate (NAA), an amino acid found uniquely in the central nervous system and in high concentrations in neurons, typically suggests HGG over metastatic lesions in spectra from ring-enhancing lesions. This study investigates exceptions to this norm. Materials and Methods: We conducted an MRS study on 49 histologically confirmed and previously untreated patients with brain metastases, employing single-voxel (SVS) techniques with short and long echo times, as well as magnetic resonance spectroscopic imaging (MRSI). Results: In our cohort, 44 out of 49 (90%) patients demonstrated a typical MR spectroscopic profile consistent with secondary deposits: a Cho peak, very low or absent Cr, absence of NAA, and the presence of lipids. A peak at approximately 2 ppm, termed the "NAA-like peak", was present in spectra obtained with both short and long echo times. Among the MRS data from 49 individuals, we observed a peak at 2.0 ppm in five brain metastases from mucinous carcinoma of the breast, mucinous non-small-cell lung adenocarcinoma, two metastatic melanomas, and one metastatic non-small-cell lung cancer. Pathohistological verification of mucin in two of these five cases suggested this peak likely represents N-acetyl glycoproteins, indicative of mucin expression in cancer cells. Conclusions: The identification of a prominent peak at 2.0 ppm could be a valuable diagnostic marker for distinguishing single ring-enhancing lesions, potentially associated with mucin-expressing metastases, offering a new avenue for diagnostic specificity in challenging cases.

Latest Developments in Magnetic Resonance Imaging for Evaluating the Molecular Microenvironment of Gliomas.

The 2021 World Health Organization (WHO) Classification of Tumors of the Central Nervous System has brought a transformative shift in the categorization of adult gliomas. Departing from traditional histological subtypes, the new classification system is guided by molecular genotypes, particularly the Isocitrate Dehydrogenase (IDH) mutation. This alteration reflects a pivotal change in understanding tumor behavior, emphasizing the importance of molecular profiles over morphological characteristics. Gliomas are now categorized into IDH-mutant and IDH wildtype, with significant prognostic implications. For IDH-mutant gliomas, the concurrent presence of Alpha-Thalassemia/mental retardation syndrome X-linked (ATRX) gene expression and co-deletion of 1p19q genes further refine classification. In the absence of 1p19q co-deletion, further categorization depends on the phenotypic expression of CDKN2A/B. Notably, IDH wildtype gliomas exhibit a poorer prognosis, particularly when associated with TERT promoter mutations, EGFR amplification, and +7/-10 co-deletion. Although not part of the new guidelines, the methylation status of the MGMT gene is crucial for guiding alkylating agent treatment. The integration of structural and functional Magnetic Resonance Imaging (MRI) techniques may play a vital role in evaluating these genetic phenotypes, offering insights into tumor microenvironment changes. This multimodal approach may enhance diagnostic precision, aid in treatment planning, and facilitate effective prognosis evaluation of glioma patients.