Magnetic Resonance Imaging Sequences Research Articles

Efficient segmentation of fetal brain MRI based on the physical resolution.

The image resolution of fetal brain magnetic resonance imaging (MRI) is a critical factor in brain development measures, which is mainly determined by the physical resolution configured in the MRI sequence. However, fetal brain MRI are commonly reconstructed to 3D images with a higher apparent resolution, compared to the original physical resolution. This work is to demonstrate that accurate segmentation can be achieved based on the MRI physical resolution, and the high apparent resolution segmentation can be achieved by a simple deep learning module. This retrospective study included 150 adult and 80 fetal brain MRIs. The adult brain MRIs were acquired at a high physical resolution, which were downsampled to visualize and quantify its impacts on the segmentation accuracy. The physical resolution of fetal images was estimated based on MRI acquisition settings and the images were downsampled accordingly before segmentation and restored using multiple upsampling strategies. Segmentation accuracy of ConvNet models were evaluated on the original and downsampled images. Dice coefficients were calculated, and compared to the original data. When the apparent resolution was higher than the physical resolution, the accuracy of fetal brain segmentation had negligible degradation (accuracy reduced by 0.26%, 1.1%, and 1.8% with downsampling factors of 4/3, 2, and 4 in each dimension, without significant differences from the original data). Using a downsampling factor of 4 in each dimension, the proposed method provided 7× smaller and 10× faster models. Efficient and accurate fetal brain segmentation models can be developed based on the physical resolution of MRI acquisitions.

Magnetic Resonance Imaging in Uremic Encephalopathy: Identifying Key Imaging Patterns and Clinical Correlations

Background/Objectives: Magnetic Resonance Imaging (MRI) is essential in diagnosing neurological conditions, offering detailed insights into brain pathology. Uremic encephalopathy (UE) is a severe neurological disorder resulting from renal failure, characterized by cognitive impairments and brain abnormalities due to the accumulation of uremic toxins (UTs). Despite extensive research on UTs, there is a significant gap in the detailed characterization of MRI findings in UE patients. This study aims to bridge this gap by conducting a comprehensive literature review of cerebral MRI findings in UE. We hypothesize that specific MRI patterns correlate with the severity and clinical manifestations of UE, thereby enhancing diagnostic accuracy and improving patient outcomes. Methods: A literature review was performed using PubMed, Cochrane Library, and Google Scholar. The search terms included “uremic encephalopathy MRI”, “uremia and kidney failure MRI”, and “toxic and metabolic or acquired encephalopathies MRI”. The inclusion criteria were original articles on UE and MRI findings published in English. Results: Common MRI sequences include T1-weighted, T2-weighted, FLAIR, and DWI. Frequent MRI findings in UE are cytotoxic and vasogenic brain edema in regions such as the basal ganglia and periventricular white matter. Patterns like the “lentiform fork sign” and basal ganglia involvement are key indicators of UE. Conclusions: MRI plays a crucial role in diagnosing UE by identifying characteristic brain edema and specific patterns. A comprehensive diagnostic approach, incorporating clinical, laboratory, and imaging data, is essential for accurate diagnosis and management. The study calls for larger well-designed cohorts with long-term follow-up to improve the understanding and treatment of UE.

Arterial Spin-Labeling MR Imaging in the Detection of Intracranial Arteriovenous Malformations in Patients with Hereditary Hemorrhagic Telangiectasia.

Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant disease that causes vascular malformations in a variety of organs and tissues, including brain AVMs. Because brain AVMs have the potential to cause disabling or fatal intracranial hemorrhage, detection of these lesions before rupture is the goal of screening MR imaging/MRA examinations in patients with HHT. Prior studies have demonstrated superior sensitivity for HHT-related brain AVMs by using postcontrast MR imaging sequences as compared with MRA alone. We now present data regarding the incremental benefit of including arterial spin-labeling (ASL) perfusion sequences as part of MR imaging/MRA screening in patients with this condition. We retrospectively analyzed 831 patients at the UCSF Hereditary Hemorrhagic Telangiectasia Center of Excellence. Of these, 42 patients had complete MR imaging/MRA, ASL perfusion scans, and criterion-standard DSA data. Two neuroradiologists reviewed imaging studies and a third provided adjudication when needed. Eight patients had no brain AVMs detected on DSA. The remaining 34 patients had 57 brain AVMs on DSA. Of the 57 identified AVMs, 51 (89.5%) were detected on ASL and 43 (75.4%) were detected on conventional MR imaging/MRA sequences (P = .049), with 8 lesions detected on ASL perfusion but not on conventional MR imaging. ASL provides increased sensitivity for brain AVMs in patients with HHT. Inclusion of ASL should be considered as part of comprehensive MR imaging/MRA screening protocols for institutions taking care of patients with HHT.

A 3D-printed, dynamic, patient-specific knee simulator

Purpose 3D-printed devices proved their efficacy across different clinical applications, helping personalize medical treatments. This paper aims to present the procedure for the design and production of patient-specific dynamic simulators of the human knee. The scope of these simulators is to improve surgical outcomes, investigate the motion and load response of the human knee and standardize in-vitro experiments for testing orthopedic devices through a personalized physical representation of the patient’s joint. Design/methodology/approach This paper tested the approach on three volunteers. For each, a patient-specific mathematical joint model was defined from an magnetic resonance imaging (MRI) of the knee. The model guided the CAD design of the simulators, which was then realized through stereolithography printing. Manufacturing accuracy was tested by quantifying the differences between 3D-printed and CAD geometry. To assess the simulator functionality, its motion was measured through a stereophotogrammetric system and compared with the natural tibio-femoral motion of the volunteers, measured as a sequence of static MRI. Findings The 3D-printing accuracy was very high, with average differences between ideal and printed parts below ± 0.1 mm. However, the assembly of different 3D-printed parts resulted in a higher average error of 0.97 mm and peak values of 2.33 mm. Despite that, the rotational and translational accuracy of the simulator was about 5° and 4 mm, respectively. Originality/value Although improvements in the production process are needed, the proposed simulators successfully replicated the individual articular behavior. The proposed approach is general and thus extendible to other articulations.

A 3D-printed, dynamic, patient-specific knee simulator

Purpose 3D-printed devices proved their efficacy across different clinical applications, helping personalize medical treatments. This paper aims to present the procedure for the design and production of patient-specific dynamic simulators of the human knee. The scope of these simulators is to improve surgical outcomes, investigate the motion and load response of the human knee and standardize in-vitro experiments for testing orthopedic devices through a personalized physical representation of the patient’s joint. Design/methodology/approach This paper tested the approach on three volunteers. For each, a patient-specific mathematical joint model was defined from an magnetic resonance imaging (MRI) of the knee. The model guided the CAD design of the simulators, which was then realized through stereolithography printing. Manufacturing accuracy was tested by quantifying the differences between 3D-printed and CAD geometry. To assess the simulator functionality, its motion was measured through a stereophotogrammetric system and compared with the natural tibio-femoral motion of the volunteers, measured as a sequence of static MRI. Findings The 3D-printing accuracy was very high, with average differences between ideal and printed parts below ± 0.1 mm. However, the assembly of different 3D-printed parts resulted in a higher average error of 0.97 mm and peak values of 2.33 mm. Despite that, the rotational and translational accuracy of the simulator was about 5° and 4 mm, respectively. Originality/value Although improvements in the production process are needed, the proposed simulators successfully replicated the individual articular behavior. The proposed approach is general and thus extendible to other articulations.

EEG-fMRI in awake rat and whole-brain simulations show decreased brain responsiveness to sensory stimulations during absence seizures

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain responds to external stimuli during and outside of seizures. This study aimed to investigate responsiveness to visual and somatosensory stimulation in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established rat model for absence epilepsy. Animals were imaged under non-curarized awake state using a quiet, zero echo time, functional magnetic resonance imaging (fMRI) sequence. Sensory stimulations were applied during interictal and ictal periods. Whole-brain hemodynamic responses were compared between these two states. Additionally, a mean-field simulation model was used to explain the changes of neural responsiveness to visual stimulation between states. During a seizure, whole-brain responses to both sensory stimulations were suppressed and spatially hindered. In the cortex, hemodynamic responses were negatively polarized during seizures, despite the application of a stimulus. The mean-field simulation revealed restricted propagation of activity due to stimulation and agreed well with fMRI findings. Results suggest that sensory processing is hindered or even suppressed by the occurrence of an absence seizure, potentially contributing to decreased responsiveness during this absence epileptic process.

EEG-fMRI in awake rat and whole-brain simulations show decreased brain responsiveness to sensory stimulations during absence seizures

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain responds to external stimuli during and outside of seizures. This study aimed to investigate responsiveness to visual and somatosensory stimulation in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established rat model for absence epilepsy. Animals were imaged under non-curarized awake state using a quiet, zero echo time, functional magnetic resonance imaging (fMRI) sequence. Sensory stimulations were applied during interictal and ictal periods. Whole-brain hemodynamic responses were compared between these two states. Additionally, a mean-field simulation model was used to explain the changes of neural responsiveness to visual stimulation between states. During a seizure, whole-brain responses to both sensory stimulations were suppressed and spatially hindered. In the cortex, hemodynamic responses were negatively polarized during seizures, despite the application of a stimulus. The mean-field simulation revealed restricted propagation of activity due to stimulation and agreed well with fMRI findings. Results suggest that sensory processing is hindered or even suppressed by the occurrence of an absence seizure, potentially contributing to decreased responsiveness during this absence epileptic process.

EEG-fMRI in awake rat and whole-brain simulations show decreased brain responsiveness to sensory stimulations during absence seizures.

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain responds to external stimuli during and outside of seizures. This study aimed to investigate responsiveness to visual and somatosensory stimulation in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established rat model for absence epilepsy. Animals were imaged under non-curarized awake state using a quiet, zero echo time, functional magnetic resonance imaging (fMRI) sequence. Sensory stimulations were applied during interictal and ictal periods. Whole-brain hemodynamic responses were compared between these two states. Additionally, a mean-field simulation model was used to explain the changes of neural responsiveness to visual stimulation between states. During a seizure, whole-brain responses to both sensory stimulations were suppressed and spatially hindered. In the cortex, hemodynamic responses were negatively polarized during seizures, despite the application of a stimulus. The mean-field simulation revealed restricted propagation of activity due to stimulation and agreed well with fMRI findings. Results suggest that sensory processing is hindered or even suppressed by the occurrence of an absence seizure, potentially contributing to decreased responsiveness during this absence epileptic process.

Comparison and precision of visceral adipose tissue measurement techniques in a multisite longitudinal study using MRI

BackgroundMeasurement of visceral adipose tissue (VAT) using magnetic resonance imaging (MRI) is considered accurate and safe. Single slice measurements perform similar to volumetric measurements for cross-sectional observation studies but may not perform as well for longitudinal studies. This study compared the performance of single slice to volumetric VAT measurements in a prospective longitudinal study. Consistency of results across sites and over time was also evaluated. MethodsA total of 935 healthy participants were recruited and scanned with MRI twice, approximately six months apart as part of a randomized, controlled, parallel arm, unblinded study conducted at four clinical centers in the United States. A 3D Dixon MRI sequence was used to image the abdomen, and visceral fat volumes were quantified for the abdomen, reduced coverage volumes (11 and 25 slices), and at single slices positioned at anatomical landmarks. A traveling phantom was scanned twice at all imaging sites. ResultsThe correlation of single slice VAT measurement to full abdomen volumetric measurements ranged from 0.78 to 0.93 for cross-sectional observation measurements and 0.30 to 0.55 for longitudinal change. Reduced coverage volumetric measurement outperformed single slice measurements but still showed improved precision with more slices with cross-sectional observation and longitudinal correlations of 0.94 and 0.66 for 11 slices and 0.94 and 0.70 for 25 slices, respectively. No significant differences were observed across sites or over time with the traveling phantom and the volume measurements had a standard deviation of 14.1 mL, 2.6% of the measured volume. ConclusionSingle slice VAT measurements had significantly lower correlation with abdomen VAT volume for longitudinal change than for cross-sectional observation measurements and may not be suitable for longitudinal studies. Data from multiple sites, different scanners, and over time did not show significant differences.

Advantages of cone beam computed tomography for evaluation of subchondral insufficiency fractures of the knee compared to MRI

To determine the diagnostic yield of cone beam computed tomography (CBCT) compared with 3 T magnetic resonance imaging (MRI) for the evaluation of subchondral insufficiency fractures of the knee. Consecutive patients with subchondral insufficiency fractures of the knee examined by 3 T MRI and CBCT of the femoral condyles were reviewed. Two experienced raters graded the lesion severity on 3 T MRI and CBCT images: grade 1: no signs of a subchondral bone lesion; grade 2: subchondral trabecular fracture or cystic changes, but without infraction of the subchondral bone plate; grade 3: collapse of the subchondral bone plate. Ratings were repeated after six weeks to determine reliability. In addition, the bone lesion size was measured as elliptical area (mm2) and compared between CBCT and T1-weighted MRI sequences. Among 30 patients included (43.3% women; mean age: 60.9 ± 12.8 years; body mass index (BMI) 29.0 ± 12.8 kg/m2), the medial femoral condyle was affected in 21/30 patients (70%). The grading of subchondral lesions between MRI and CBCT did not match in 12 cases (40%). Based on MRI images, an underestimation (i.e., undergrading) compared with CBCT was observed in nine cases (30%), whereas overgrading occurred in three cases (10%). Compared to CBCT, routine T1-weighted 3 T sequences significantly overestimated osseus defect zones in sagittal (84.7 ± 68.9 mm2 vs. 35.9 ± 38.2 mm2, p < 0.01, Cohen’s d = 1.14) and coronal orientation (53.1 ± 24.0 mm2 vs. 22.0 ± 15.2 mm2, p < 0.01, Cohen’s d = 1.23). The reproducibility of the grading determined by intra- and inter-rater agreement was very high in MRI (intra-class correlation coefficient (ICC) 0.78 and 0.90, respectively) and CBCT (ICC 0.96 and 0.96, respectively). In patients with subchondral insufficiency fractures of the knee, the use of CBCT revealed discrepancies in lesion grading compared with MRI. These findings are clinically relevant, as precise determination of subchondral bone plate integrity may influence the decision about conservative or surgical treatment. CBCT represents our imaging modality of choice for grading the lesion and assessing subchondral bone plate integrity. MRI remains the gold standard modality to detect especially early stages.

Four-Hour-Delayed Gadolinium 3D REAL IR and SPACE FLAIR MRI Correlated to Meniere Disease Histology.

Objectives: This study aims to showcase the complementary nature of utilizing both histopathology and magnetic resonance imaging (MRI) in understanding the otologic pathophysiology of Meniere disease. In addition, it seeks to raise awareness of the value of preserving and curating historical temporal bone collections which continue to inform our understanding of otologic diseases. Methods: The essential anatomical feature of Meniere disease-the distended membranous labyrinth-is explored through a comparison of early temporal bone studies with contemporary MRI techniques. The histopathologic photomicrographs are of inner ear specimens from deceased patients with symptoms consistent with Meniere disease. The MRI sequences from living patients exhibiting classic Meniere disease symptoms during life are captured 4 hours post-administration of gadolinium. Results: Both histopathologic examination and MRI imaging reveal consistent distention of the saccule, utricle, and scala media in patients with Meniere disease. The study shows the histologic photomicrographs of actual Meniere patients compared to the MRIs and successfully demonstrates the correlation between postmortem histological findings and MRI evidence of distension in living patients. Conclusions: A corresponding distension of the membranous labyrinth is seen in both the histologic specimens and the Meniere MRIs. This correlation suggests the potential utility of utilizing MRI to aid in diagnosing atypical Meniere disease and distinguishing it from other disease processes, such as migraine equivalent vertigo. The integration of historical temporal bone studies with modern MRI techniques offers valuable insights into the pathophysiology of otologic diseases. In addition, it emphasizes the importance of preserving and curating historical temporal bone collections for continued research and medical education purposes. Previous studies of delayed MRIs did not use Meniere disease temporal bone histopathology images.

Convolutional neural network and glioma genotyping: A systematic review.

e14038 Background: Gliomas are the most common primary intracranial tumors. Overall, there are 23 different glioma types, and the grading and prognosis of each type are determined by their specific mutations. Several identified mutations are IDH gene status, CDKN2A/B homozygote delegation, PTEN mutation, p53 mutation, TERT promotor mutation, H3K27M mutation, MGMT promotor methylation, trisomy 7/monozomy10, EGFR amplification, ATRX mutation, 1p/19q codeletion, and BRAF mutation. These specific mutations and genomic features can have their distinctive radiologic features seen in different magnetic resonance imaging (MRI) sequences. By using a Convolutional Neural Network (CNN) for feature extraction, the genotyping power of MRI for glioma could be increased. To address this, we systematically reviewed the use of different CNN-based models to detect the genetic context of glioma based on the MRI images. Methods: We conducted a systematic search in PubMed, Embase, Scopus, Web of Science, and Google Scholar. We included original peer-reviewed human studies (retrospective or prospective), focusing on the use of CNN in individuals with glioma. We excluded animal studies, studies with no CNN-based models, reviews, book chapters, conference abstracts, and case reports. JBI checklists were utilized for quality assessment. Results: The initial search resulted in 973 articles. after removing duplicates, 563 studies entered the screening process by title and abstract. 59 studies met our inclusion criteria (56 retrospective and 3 prospective cohort studies) with a total of 26434 glioma patients included (studies ranged from 21 – 2648 individuals). 31 studies used CNN methods only in different stages of image processing (tumor segmentation, feature extraction, image encoder) and 28 studies used CNN as a classifier and mutation predictor. ResNet was the most commonly used CNN-based model (n = 14). U-net (n = 7) and DenseNet models (n = 4) were other commonly used CNN-based models. Included studies targeted IDH status (n=44), 1p/19q codeletion (n=18), MGMT promotor methylation (n=11), ATRX mutation (n=5), TERT promotor mutation (n=5), CDKN2A/B homozygote deletion (n=3), PTEN mutation (n=3), p53 mutation (n=3), H3K27M mutation (n=2), trisomy 7/monozomy10 (n=2), EGFR amplification (n=2), and BRAF mutation (n=1). Highly severe methodological heterogeneity among these studies excluded the possibility of meta-analysis. Conclusions: Current studies have shown that, as a non-invasive method, using CNN-based models on multiple MRI sequences increases the power of early detection and prediction of glioma genetic types before pathological confirmation and has promising results. However, DL performance varies among mutations. Combining multiple DL models with clinical and radiomic features in different and larger databases can further increase the final results.

Neoadjuvant immunochemotherapy and new radiomic predictor for resectable locally advanced oral squamous cell carcinoma.

6090 Background: The effectiveness of neoadjuvant immunochemotherapy (NAIC) in treating resectable locally advanced oral squamous cell carcinoma (LAOSCC) remains uncertain, with a notable lack of precise prognostic markers for NAIC outcomes. Methods: A single-arm prospective phase II trial was performed to assess the efficacy and safety of NAIC, consisting of 2 cycles of intravenous camrelizumab (200 mg), albumin paclitaxel (260 mg/m²), and cisplatin (75 mg/m²) administered every 3 weeks prior to radical surgery in LAOSCC patients. Adjuvant radiotherapy or chemoradiotherapy was determined by post-surgical pathology. Patients with previously untreated, stage III-IVB LAOSCC (the 8th edition of UICC/AJCC staging system), aged 18-75 years were enrolled. The primary endpoints were major pathological response (MPR, defined as ≤10% residual viable tumour (%RVT) cells) and safety, the second primary point was objective response rate (ORR) according to RECIST 1.1. To identify potential radiomic markers predictive of NAIC benefit, oscillating-gradient spin-echo (OGSE) magnetic resonance imaging sequences were obtained before and after NAIC. Results: From Feb 1, 2023 to Jan 1, 2024, 30 patients were enrolled, among which, 26 patients have received NAIC followed by surgery. The MPR rate was 65.4% (17/26), including a 34.6% (9/26) pathological complete response. Patients with PD-L1 (Combined Positive Score) ≥ 1 had higher MPR (80.0%, 16/20) than those with PD-L1 &lt; 1 (16.7%, 1/6). NAIC was well-tolerated, without adverse effects on subsequent surgery, only two patients experienced grade 3 or 4 adverse events during NAIC, including one with grade 4 neutropenia (3.8%), and one with grade 3 thrombocytopenia (3.8%). The ORR was 80.8% (21/26), with 15.4% (4/26) complete response, 65.4% (17/26) partial response, and with no cases of progressive disease observed. The mean cell diameters of the whole tumor were calculated based on the OGSE sequences, twenty patients completed the OGSE scaning pre- and post-NAIC treatment. Pearson correlation analyses found that small post-NAIC mean cell diameter significantly related with fewer %RVT ( p = 0.026), supporting its potential as new radiomic predictors of NAIC efficacy. Among patients with MPR, the cell diameters were significantly decreased after NAIC, with a mean cell diameter of 18.87 ± 2.49 μm and 14.77 ± 1.85 μm for pre- and post-NAIC tumor, respectively ( p = 0.001). Conclusions: Camrelizumab combined with albumin paclitaxel/cisplatin as NAIC for LAOSCC demonstrates promising MPR and well safety. Mean cell diameter of tumor, derived from OGSE sequences, emerges as a potential new radiomic marker for predicting NAIC efficacy. Ongoing follow-ups on long-term survival and the development of a bio-radiomic prediction model integrating pathological features with OGSE data are underway. Clinical trial information: ChiCTR2200066119.

Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)Ⓡ study in two sites, and across four MRI scanners.Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated.The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

Optimising needle depth in temporomandibular joint arthrocentesis: a magnetic resonance-based study for safety and efficacy

The aim of this paper was to determine the optimal needle depth for temporomandibular joint (TMJ) arthrocentesis using magnetic resonance imaging (MRI), with the aim of improving procedural safety and efficacy in clinical practice. A retrospective analysis of 264 TMJ MRIs from 132 patients at Istanbul Medipol Mega University Hospital was conducted. T2-weighted MRI sequences were utilised to measure distances from skin to joint capsules at varying needle entry points, applying the double puncture technique. The study adhered to ethical standards with appropriate approvals. The analysis revealed significant gender-related variations in needle depths (females showing shorter distances than males, p < 0.05). No significant gender differences were found in condylar angles. An inverse correlation between age and condylar angle suggested age-related anatomical changes. Crucially, a 20 mm needle depth was identified as safer and more effective than the previously recommended 25 mm. This study underscores the necessity of revising needle depth to 20 mm in TMJ arthrocentesis. These findings hold significant implications for improving procedural safety and catering to demographic variations.

Atlantoaxial intra-articular cage fusion by posterior intermuscular approach for treating reducible atlantoaxial dislocation: a technique note with case series.

To evaluate the clinical feasibility of atlantoaxial intra-articular cage (AIC) fusion via intermuscular approach for treating reducible atlantoaxial dislocation (AAD). An analysis was conducted on the data of 10 patients who underwent C1-C2 segmental fixation and AIC fusion for AAD by unilateral intermuscular approach and contralateral open approach. Outcome assessments included Japanese Orthopaedic Association score (JOA) and Visual Analog Scale Score for Neck Pain (VASSNP). The duration of surgical exposure, screw insertion and cage insertion, and postoperative drainage volume were also compared between two approaches. Bone fusion was evaluated through computed tomography (CT) reconstruction. Postoperative paravertebral tissue edema was evaluated by paravertebral tissue cross-sectional area (CSA) and signal intensity on T2 weighted sequence of magnetic resonance imaging (MRI) at 3 days postoperatively. The intermuscular approach exhibited a longer exposure time but lower drainage postoperatively compared to the open approach (P < 0.05). After operation, JOA scores significant improved (P < 0.05), while VASSNP scores significantly decreased (P < 0.05). There was no significant difference in preoperative CSA between two approaches (P > 0.05). However, compared to the open approach, the intermuscular approach exhibited less CSA (P < 0.05) and lower T2 signal intensity on MRI postoperatively, indicating less invasive to the paravertebral tissues. AIC fusion by intermuscular approach is an effective and safe technique in the treatment of reducible AAD. Intermuscular approach could reduce the postoperative drainage volume and the extent of paravertebral tissue edema compared to open approach.

Deep learning-based magnetic resonance imaging analysis for chronic cerebral hypoperfusion risk.

Chronic cerebral hypoperfusion (CCH) is a frequently encountered clinical condition that poses a diagnostic challenge due to its nonspecific symptoms. To enhance the diagnosis of CCH and non-CCH through Magnetic Resonance Imaging (MRI), offering support in clinical decision-making and recommendations to ultimately elevate diagnostic accuracy and optimize patient treatment outcomes. In the retrospective research, we collected 204 routine brain magnetic resonance imaging (MRI) from March 1 to September 10 2022, as training and testing cohorts. And a validation cohort with 108 samples was collected from November 14 2022 to August 4 2023. MRI sequences were processed to obtain T1-weighted (T1WI) and T2-weighted (T2WI) sequence images for each patient. We propose CCH-Network (CCHNet), an end-to-end deep learning model, integrating convolution and Transformer modules to capture local and global structural information. Our novel adversarial training method improves feature knowledge capture, enhancing both generalization ability and efficiency in predicting CCH risk. We assessed the classification performance of the proposed model CCHNet by comparing it with existing state-of-the-art deep learning algorithms, including ResNet34, DenseNet121, VGG16, Convnext, ViT, Coat, and TransFG. To better validate model performance, we compared the results of the proposed model with eight neurologists to evaluate their consistency. CCHNet achieved an AUC of 91.6% (95% CI: 86.8-99.1), with an accuracy (ACC) of 85.0% (95% CI: 75.6-95.2). It demonstrated a sensitivity (SE) of 80.0% (95% CI: 71.6-95.6) and a specificity (SP) of 90.0% (95% CI: 82.3-97.8) in the testing cohort. In the validation cohort, the model demonstrated an AUC of 86.0% (95% CI: 80.3-93.0), an ACC of 84.2% (95% CI: 70.2-93.6), a SE of 83.3% (95% CI: 68.3-95.5), and a SP of 84.7% (95% CI: 70.3-96.8). The model improved the diagnostic performance of MRI with high SE and SP, providing a promising method for the diagnosis of CCH.

Modeling cerebrospinal fluid dynamics across the entire intracranial space through integration of four-dimensional flow and intravoxel incoherent motion magnetic resonance imaging

BackgroundBidirectional reciprocal motion of cerebrospinal fluid (CSF) was quantified using four-dimensional (4D) flow magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) MRI. To estimate various CSF motions in the entire intracranial region, we attempted to integrate the flow parameters calculated using the two MRI sequences. To elucidate how CSF dynamics deteriorate in Hakim’s disease, an age-dependent chronic hydrocephalus, flow parameters were estimated from the two MRI sequences to assess CSF motion in the entire intracranial region.MethodsThis study included 127 healthy volunteers aged ≥ 20 years and 44 patients with Hakim’s disease. On 4D flow MRI for measuring CSF motion, velocity encoding was set at 5 cm/s. For the IVIM MRI analysis, the diffusion-weighted sequence was set at six b-values (i.e., 0, 50, 100, 250, 500, and 1000 s/mm2), and the biexponential IVIM fitting method was adapted. The relationships between the fraction of incoherent perfusion (f) on IVIM MRI and 4D flow MRI parameters including velocity amplitude (VA), absolute maximum velocity, stroke volume, net flow volume, and reverse flow rate were comprehensively evaluated in seven locations in the ventricles and subarachnoid spaces. Furthermore, we developed a new parameter for fluid oscillation, the Fluid Oscillation Index (FOI), by integrating these two measurements. In addition, we investigated the relationship between the measurements and indices specific to Hakim’s disease and the FOIs in the entire intracranial space.ResultsThe VA on 4D flow MRI was significantly associated with the mean f-values on IVIM MRI. Therefore, we estimated VA that could not be directly measured on 4D flow MRI from the mean f-values on IVIM MRI in the intracranial CSF space, using the following formula; e0.2(f−85) + 0.25. To quantify fluid oscillation using one integrated parameter with weighting, FOI was calculated as VA × 10 + f × 0.02. In addition, the FOIs at the left foramen of Luschka had the strongest correlations with the Evans index (Pearson’s correlation coefficient: 0.78). The other indices related with Hakim’s disease were significantly associated with the FOIs at the cerebral aqueduct and bilateral foramina of Luschka. FOI at the cerebral aqueduct was also elevated in healthy controls aged ≥ 60 years.ConclusionsWe estimated pulsatile CSF movements in the entire intracranial CSF space in healthy individuals and patients with Hakim’s disease using FOI integrating VA from 4D flow MRI and f-values from IVIM MRI. FOI is useful for quantifying the CSF oscillation.

Iron deposition in subcortical nuclei of Parkinson's disease: A meta-analysis of quantitative iron-sensitive magnetic resonance imaging studies.

Iron deposition plays a crucial role in the pathophysiology of Parkinson's disease (PD), yet the distribution pattern of iron deposition in the subcortical nuclei has been inconsistent across previous studies. We aimed to assess the difference patterns of iron deposition detected by quantitative iron-sensitive magnetic resonance imaging (MRI) between patients with PD and patients with atypical parkinsonian syndromes (APSs), and between patients with PD and healthy controls (HCs). A systematic literature search was conducted on PubMed, Embase, and Web of Science databases to identify studies investigating the iron content in PD patients using the iron-sensitive MRI techniques (R2* and quantitative susceptibility mapping [QSM]), up until May 1, 2023. The quality assessment of case-control and cohort studies was performed using the Newcastle-Ottawa Scale, whereas diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. Standardized mean differences and summary estimates of sensitivity, specificity, and area under the curve (AUC) were calculated for iron content, using a random effects model. We also conducted the subgroup-analysis based on the MRI sequence and meta-regression. Seventy-seven studies with 3192 PD, 209 multiple system atrophy (MSA), 174 progressive supranuclear palsy (PSP), and 2447 HCs were included. Elevated iron content in substantia nigra (SN) pars reticulata (P <0.001) and compacta (P <0.001), SN (P <0.001), red nucleus (RN, P <0.001), globus pallidus (P <0.001), putamen (PUT, P=0.009), and thalamus (P=0.046) were found in PD patients compared with HCs. PD patients showed lower iron content in PUT (P <0.001), RN (P=0.003), SN (P=0.017), and caudate nucleus (P=0.027) than MSA patients, and lower iron content in RN (P=0.001), PUT (P <0.001), globus pallidus (P=0.004), SN (P=0.015), and caudate nucleus (P=0.001) than PSP patients. The highest diagnostic accuracy distinguishing PD from HCs was observed in SN (AUC: 0.85), and that distinguishing PD from MSA was found in PUT (AUC: 0.90). In addition, the best diagnostic performance was achieved in the RN for distinguishing PD from PSP (AUC: 0.84). Quantitative iron-sensitive MRI could quantitatively detect the iron content of subcortical nuclei in PD and APSs, while it may be insufficient to accurately diagnose PD. Future studies are needed to explore the role of multimodal MRI in the diagnosis of PD. PROSPERO; CRD42022344413.

Advanced MRI techniques in abdominal imaging.

Magnetic resonance imaging (MRI) is a crucial modality for abdominal imaging evaluation of focal lesions and tissue properties. However, several obstacles, such as prolonged scan times, limitations in patients' breath-hold capacity, and contrast agent-associated artifacts, remain in abdominal MR images. Recent techniques, including parallel imaging, three-dimensional acquisition, compressed sensing, and deep learning, have been developed to reduce the scan time while ensuring acceptable image quality or to achieve higher resolution without extending the scan duration. Quantitative measurements using MRI techniques enable the noninvasive evaluation of specific materials. A comprehensive understanding of these advanced techniques is essential for accurate interpretation of MRI sequences. Herein, we therefore review advanced abdominal MRI techniques.