Axial Magnetic Resonance Imaging Research Articles

Temporal muscle thickness has no prognostic relevance in patients with high-grade glioma compared to functional scales.

GBM research is constantly assessing potential valuable prognostic biomarkers to better understand the disease and prognosticate future outcomes. Measuring temporal muscle thickness (TMT) has appeared to be a promising new surrogate marker for skeletal muscle mass and sarcopenia, which further indicates frailty and predicts overall survival (OS). The aim of this study was to determine its usefulness as a prognostic marker in patients with high-grade glioma compared to functional status scales. TMT was measured in preoperative axial T1-weighted contrast-enhanced magnetic resonance images in 277 patients who received surgical treatment of newly diagnosed WHO III and IV gliomas in our institution between 2015 and 2020. Clinical Frailty Scale (CFS) and Karnofsky Performance Scale (KPS) were assessed preoperatively and during a follow-up visit. Female gender has shown significant correlation with TMT, while TMT did not correlate with preoperative and follow-up functional scores, age, WHO classification, IDH mutation, MGMT promoter methylation, EGFR and ATRX expression, or 1p/19q co-deletion. No significant prognostic value of TMT could be shown in 6, 12, and 24 months OS, while changes in CFS and KPS proved to have a significant impact. Only female gender, but no other clinical, histological, or molecular marker showed any interrelation with TMT. Functional scores outclass measuring TMT as a reliable prognostic factor for predicting OS in patients with high-grade glioma.

Deep learning-based detection and classification of lumbar disc herniation on magnetic resonance images.

The severity assessment of lumbar disc herniation (LDH) on MR images is crucial for selecting suitable surgical candidates. However, the interpretation of MR images is time-consuming and requires repetitive work. This study aims to develop and evaluate a deep learning-based diagnostic model for automated LDH detection and classification on lumbar axial T2-weighted MR images. A total of 1115 patients were analyzed in this retrospective study; both a development dataset (1015 patients, 15 249 images) and an external test dataset (100 patients, 1273 images) were utilized. According to the Michigan State University (MSU) classification criterion, experts labeled all images with consensus, and the final labeled results were regarded as the reference standard. The automated diagnostic model comprised Faster R-CNN and ResNeXt101 as the detection and classification network, respectively. The deep learning-based diagnostic performance was evaluated by calculating mean intersection over union (IoU), accuracy, precision, sensitivity, specificity, F1 score, the area under the receiver operating characteristics curve (AUC), and intraclass correlation coefficient (ICC) with 95% confidence intervals (CIs). High detection consistency was obtained in the internal test dataset (mean IoU = 0.82, precision = 98.4%, sensitivity = 99.4%) and external test dataset (mean IoU = 0.70, precision = 96.3%, sensitivity = 97.8%). Overall accuracy for LDH classification was 87.70% (95% CI: 86.59%-88.86%) and 74.23% (95% CI: 71.83%-76.75%) in the internal and external test datasets, respectively. For internal testing, the proposed model achieved a high agreement in classification (ICC = 0.87, 95% CI: 0.86-0.88, P < 0.001), which was higher than that of external testing (ICC = 0.79, 95% CI: 0.76-0.81, P < 0.001). The AUC for model classification was 0.965 (95% CI: 0.962-0.968) and 0.916 (95% CI: 0.908-0.925) in the internal and external test datasets, respectively. The automated diagnostic model achieved high performance in detecting and classifying LDH and exhibited considerable consistency with experts' classification.

Empirical Quantification of Optic Nerve Strain Due to Horizontal Duction.

Magnetic resonance imaging (MRI) was used to measure in vivo local strains in the optic nerve (ON) associated with horizontal duction in humans. Axial and coronal MRI were collected in target-controlled gazes in 24 eyes of 12 normal adults (six males and six females, 59 ± 16 years) during large (~28°) and moderate (~24°) ductions. The ON, globe, and extraocular muscles were manually identified, and the pixels were converted to point-sets that were registered across different imaging planes and eye positions. Shape of the ON was parameterized based on point-sets. Displacements and strains were computed by comparing deformed with initial ON configurations. Displacements were the largest in the most anterior region. However, strains from adduction were uniform along the length of the ON, while those during abduction increased with distance from the globe and were maximal near the orbital apex. For large gaze angles, ON strain during abduction was primarily due to bending near the orbital apex that is less transmitted to the eye, but during adduction the ON undergoes uniform stretching that transmits much greater loading to the posterior eye, implied by greater strain on the ON.

An investigation of machine learning algorithms for prediction of lumbar disc herniation.

The prevalence of lumbar disc herniation (LDH), which makes patients' daily activities more difficult and reduces their quality of life, has tended to increase recently. Many risk factors associated with LDH have been reported. In this study, LDH was predicted using machine learning techniques using measures of the lumbar paraspinal muscles, lumbar vessels cross-sectional area (CSA), and lumbar sagittal curve. Three hundred and forty-four individuals' MR scans were prospectively enrolled (264 with LDH and 80 healthy). Predictive factors were the lumbar sagittal curve and the cross-sectional areas of the lumbar paraspinal muscles and vessels from sagittal and axial MR images. The measurements have been analyzed via ten different and most common machine learning algorithms by considering a comprehensive parameter tuning and cross-validation process. The variable importance results have been also presented. XGBoost algorithm among all algorithms has provided the best results in terms of different classification metrics including f-score ([Formula: see text]), AUC ([Formula: see text]), accuracy ([Formula: see text]), and kappa ([Formula: see text]). The findings of this study demonstrated that cross-sectional areas of the quadratus lumborum and abdominal aorta can be utilized as a reliable indicator of LDH. Consequently, the developed model and the variables found to be important may guide to healthcare professionals to make more accurate and effective decisions in terms of prediction the LDH.

Radiomics for the Detection of Active Sacroiliitis Using MR Imaging.

Detecting active inflammatory sacroiliitis at an early stage is vital for prescribing medications that can modulate disease progression and significantly delay or prevent debilitating forms of axial spondyloarthropathy. Conventional radiography and computed tomography offer limited sensitivity in detecting acute inflammatory findings as these methods primarily identify chronic structural lesions. Conversely, Magnetic Resonance Imaging (MRI) is the preferred technique for detecting bone marrow edema, although it is a complex process requiring extensive expertise. Additionally, ascertaining the origin of lesions can be challenging, even for experienced medical professionals. Machine learning (ML) has showcased its proficiency in various fields by uncovering patterns that are not easily perceived from multi-dimensional datasets derived from medical imaging. The aim of this study is to develop a radiomic signature to aid clinicians in diagnosing active sacroiliitis. A total of 354 sacroiliac joints were segmented from axial fluid-sensitive MRI images, and their radiomic features were extracted. After selecting the most informative features, a number of ML algorithms were utilized to identify the optimal method for detecting active sacroiliitis, leading to the selection of an Extreme Gradient Boosting (XGBoost) model that accomplished an Area Under the Receiver-Operating Characteristic curve (AUC-ROC) of 0.71, thus further showcasing the potential of radiomics in the field.

Association between history of lumbar spine surgery and paralumbar muscle health: a propensity score-matched analysis

Prior studies have suggested that muscle strength and quality may be associated with low back pain. Recently, a novel magnetic resonance imaging (MRI)-based lumbar muscle health grade was shown to correlate with health-related quality of life scores after spine surgery. However, the potential association between history of lumbar spine surgery and paralumbar muscle health requires further investigation. To compare MRI-based paralumbar muscle health parameters between patients with versus without a history of surgery for degenerative lumbar spinal disease. Retrospective cohort study. Consecutive series of patients who presented to the spine surgery clinic of a single surgeon. MRI-based measurements of paralumbar cross-sectional area (PL-CSA), Goutallier grade, lumbar indentation value (LIV). A retrospective analysis was performed on a consecutive series of patients of a single surgeon, and patients were included based on availability of lumbar MRI. Axial T2-weighted lumbar MRIs were analyzed for PL-CSA, Goutallier classification, and LIV. Measurements were performed at the center of disc spaces from L1 to L5. Patients with and without history of spine surgery were matched based on age, sex, race, ethnicity, and body mass index (BMI) via propensity score matching. Normality of each muscle health variable was assessed using Kolmogorov-Smirnov test. Mann-Whitney U test or independent t-test performed to compare the matched cohorts, as appropriate. A total of 615 patients were assessed. For final analysis, 89 patients with a history of previous spine surgery were matched with 89 patients without a history of spine surgery. There were no statistically significant differences in age, sex, race, ethnicity, or BMI between the matched cohorts. History of spine surgery was generally associated with worse lumbar muscle health. At all 4 intervertebral levels between L1-L5, PL-CSA was significantly smaller among patients with history of spine surgery. At L4-L5, patients with prior spine surgery had significantly smaller PL-CSA/BMI. Patients with prior spine surgery were found to have greater fatty infiltration of the muscles, with higher average Goutallier grades at levels L1-L2, L2-L3, and L4-L5. In addition, history of spine surgery was associated with smaller LIV at L1-L2, L3-L4, and L4-L5. The current study demonstrates that history of lumbar spine surgery is associated with worse paralumbar muscle health based on quantitative and qualitative measurements on MRI. On average, patients with history of spine surgery were found to have smaller cross-sectional areas of the paralumbar muscles, greater amounts of fatty infiltration based on Goutallier classification, and smaller lumbar indentation values.

Basilar artery diameter as neuroimaging biomarker in Chinese Fabry disease patients

BackgroundFabry disease (FD) is an X-linked lysosomal storage disease resulting from mutations of α-galactosidase A gene, and has been emphasized as one of the etiologies of young stroke and leukoencephalopathy. Vertebrobasilar dolichoectasia (VBD) is a highlighted finding in FD. We aim to examine the utility of VBD in Chinese FD by comparing the differences in basilar artery (BA) diameter of Chinese FD patients against age-matched controls with and without stroke.MethodsThis was a matched case-control study involving 37 Chinese FD patients. The BA diameters were evaluated on axial T2-weighted magnetic resonance imaging and compared to two age-and-gender matched control groups, one with stroke and one without. The association between BA diameter and stroke occurrences and white matter hyperintensities (WMH) were analyzed among all FD patients.ResultsPatients with FD had significantly increased BA diameter compared to controls with and without stroke (p < 0.001). A BA diameter of 4.16 mm could distinguish FD from controls in the stroke subgroup (ROC AUC 0.870, p = 0.001, sensitivity 80% specificity 100%), and with a cut-off of 3.21 mm in the non-stroke subgroup (ROC AUC 0.846, p < 0.001, sensitivity 77.8% specificity 88.9%). Larger BA diameter had more stroke occurrences and was moderately associated with heavier WMH load in terms of higher total FAZEKAS scores. (Spearman’s rho = 0.423, p = 0.011).ConclusionVBD was also present in Chinese FD patients. BA diameter has high diagnostic utility in identifying FD from a mixed cohort of stroke and normal controls, and carried predictive value in evaluating neurological complications of FD.

Lumbar Spinal Canal Segmentation in Cases with Lumbar Stenosis Using Deep-U-Net Ensembles

Narrowing of the lumbar spinal canal, or lumbar stenosis (LS), may cause debilitating radicular pain or muscle weakness. It is the most frequent indication for spinal surgery in the elderly population. Modern diagnosis relies on magnetic resonance imaging and its inherently subjective interpretation. Diagnostic rigor, accuracy, and speed may be improved by automation. In this work, we aimed to determine whether a deep-U-Net ensemble trained to segment spinal canals on a heterogeneous mix of clinical data is comparable to radiologists' segmentation of these canals in patients with LS. The deep U-nets were trained on spinal canals segmented by physicians on 100 axial T2 lumbar magnetic resonance imaging selected randomly from our institutional database. Test data included a total of 279 elderly patients with LS that were separate from the training set. Machine-generated segmentations (MA) were qualitatively similar to expert-generated segmentations (ME1, ME2). Machine- and expert-generated segmentations were quantitatively similar, as evidenced by Dice scores (MA vs. ME1: 0.88 ± 0.04, MA vs. ME2: 0.89 ± 0.04), the Hausdorff distance (MA vs. ME1: 11.7 mm ± 13.8, MA vs. ME2: 13.1 mm ± 16.3), and average surface distance (MAvs. ME1: 0.18 mm ± 0.13, MA vs. ME2 0.18 mm ± 0.16) metrics. These metrics are comparable to inter-rater variation (ME1 vs. ME2 Dice scores: 0.94 ± 0.02, the Hausdorff distances: 9.3 mm ± 15.6, average surface distances: 0.08 mm ± 0.09). We conclude that machine learning algorithms can segment lumbar spinal canals in LS patients, and automatic delineations are both qualitatively and quantitatively comparable to expert-generated segmentations.

Prevalence of amyloid in ligamentum flavum of patients with lumbar spinal stenosis

Background Transthyretin (ATTR) amyloidosis is often diagnosed in an advanced stage, when irreversible cardiac damage has occurred. Lumbar spinal stenosis (LSS) may precede cardiac ATTR amyloidosis by many years, offering the opportunity to detect ATTR already at the time of LSS surgery. We prospectively assessed the prevalence of ATTR in the ligamentum flavum by tissue biopsy in patients aged >50 years undergoing surgery for LSS. Methods Ligamentum flavum thickness was assessed pre-operatively on axial T2 magnetic resonance imaging (MRI) slices. Tissue samples from ligamentum flavum were screened centrally by Congo red staining and immunohistochemistry (IHC). Results Amyloid in the ligamentum flavum was detected in 74/94 patients (78.7%). IHC revealed ATTR in 61 (64.9%), whereas amyloid subtyping was inconclusive in 13 (13.8%). Mean thickness of ligamentum flavum was significantly higher at all levels in patients with amyloid (p < .05). Patients with amyloid deposits were older (73.1 ± 9.2 vs. 64.6 ± 10.1 years, p = .01). No differences in sex, comorbidities, previous surgery for carpal tunnel syndrome or LSS were observed. Conclusions Amyloid, mostly of the ATTR subtype, was found in four out of five patients with LSS and is associated with age and ligamentum flavum thickness. Histopathological work-up of ligamentum flavum might inform future decision making.

Poster 265: The Risk of Iatrogenic Posterior Neurovascular Injury in Lateral Meniscal Repair Based on Real Arthroscopic Position: An MRI Study

Objectives: Posterior horn of lateral meniscal repair using an all-inside meniscal repair device involves a risk of iatrogenic posterior neurovascular injury. Some studies have evaluating the injury risk in this area but most were based on preoperative MRIs and landmarks which are difficult to clearly see under actual arthroscopic surgery. To our knowledge, there have been no studies to date evaluating the risk of injury based on MRIs with the knee in the standard operational figure-of-4 position with joint dilatation in arthroscopic lateral meniscal repair related to the lateral border of the lateral meniscal root which is easy to identify during surgery. The objective of this study was to evaluate and compare the risk of posterior neurovascular injury and establish the safe and danger zones in repairing the lateral meniscus through the anterolateral and anteromedial portals in relation to the medial and lateral borders of the lateral meniscal root (LMR) using standard operational figure-of-4 position with joint dilatation MRIs. Methods: This study was descriptive laboratory study. Using 29 axial magnetic resonance imaging (MRI) studies of knees in the figure-of-4 position with joint fluid dilatation at the level of the lateral meniscus, direct lines were drawn to simulate a straight all-inside meniscal repair device deployed from the anteromedial and anterolateral portals to the medial and lateral borders of the LMR extending 14 mm beyond the joint capsule. If the line passed through or touched the posterior neurovascular structure, a risk of iatrogenic injury was noted, and measurements were made to determine the safe zones in relation to the medial or lateral border of the LMR. Results: Repairing the lateral meniscus through the anterolateral portal in relation to the lateral border of the LMR had a significantly greater risk of posterior neurovascular injury than repairing through the anteromedial portal, of which the incidences were 68.97% and 10.35%, respectively (p-value = 0.001). The “safe zones” of lateral meniscal repair in relation to the lateral border of the LMR through the anterolateral and anteromedial portals were 4.15 ± 1.87 mm and 6.57 ± 0.98 mm lateral to the lateral border of the LMR, respectively. Conclusions: Our study found a risk of iatrogenic posterior neurovascular injury when repairing the posterior lateral meniscus tissue through both the anterolateral and anteromedial portals in relation to both the lateral and medial borders of the LMR, with repairs through the anterolateral portal having greater risk than through the anteromedial portal. To reduce this risk, the surgeon can use the “safe zones” as described in this study to decrease the potential risk of iatrogenic posterior neurovascular injury during arthroscopic lateral meniscal repair. Clinical Relevance: Iatrogenic injury is always a concern in any surgery, and the results of this study can be a guide to reducing iatrogenic posterior neurovascular injury during posterior horn of lateral meniscal repair.

Deep Learning Algorithm Trained on Cervical Magnetic Resonance Imaging to Predict Outcomes of Transforaminal Epidural Steroid Injection for Radicular Pain from Cervical Foraminal Stenosis.

A convolutional neural network (CNN) is one of the representative deep learning (DL) model that is especially useful for image recognition and classification. In the current study, using cervical axial magnetic resonance imaging (MRI) data obtained prior to transforaminal epidural steroid injection (TFESI), we developed a CNN model to predict the therapeutic outcome of cervical TFESI in patients with cervical foraminal stenosis. We retrospectively recruited 288 patients with cervical foraminal stenosis who received cervical TFESI due to cervical radicular pain. We collected single T2-axial spine MR image obtained from each patient. The image showing narrowest width of the neural foramen in the level at which TFESI was performed was used for input data. A "favor outcome" was defined as a ≥ 50% reduction in the NRS score at 2 months post-TFESI vs the pretreatment NRS score. A "poor outcome" was defined as a < 50% reduction in the NRS score at 2 months post-TFESI vs the pretreatment score. The area under the curve of our developed model for predicting therapeutic outcome of cervical TFESI in patients with cervical spinal stenosis was 0.801. We showed that a CNN model trained using cervical axial MRI could be helpful for predicting therapeutic outcome after cervical TFESI in patients with cervical foraminal stenosis.

Paper 31: Quantitative MRI of the Hamstring Muscles Ten Years After Autograft Hamstring ACLR

Paper 31: Quantitative MRI of the Hamstring Muscles Ten Years After Autograft Hamstring ACLR

Case series: Noninfectious myositis of temporal muscle: a report of 2 cases.

Noninfectious myositis (NIM) of the masticatory muscles is uncommon local myalgia disorder persisted by a centrally-mediated neurogenic mechanism. Due to the rarity of this condition and the lack of appropriate data regarding it, diagnosing this pathology when it affects the temporal muscle (TM) is challenging. Clinical signs and symptoms, diagnostic process, and treatment outcome of 2 rare cases of NIM of the TM were presented. The signs and symptoms of the patients were not pathognomonic. There were restrictions on the mouth opening and lateral excursion of the mandible. The duration of the symptoms may not be chronic. The findings of clinical evaluation may indicate the diagnosis of anterior disc displacement (DD) without reduction of the temporomandibular joint (TMJ) and/or local myalgia. Swelling of the involved muscle could be evident and identified on palpation depending on the involved site of myositis. The axial T2-weighted magnetic resonance (MR) imaging was important for the accurate diagnosis of this rare condition. Application of non-surgical conservative treatment modalities such as administration of non-steroidal anti-inflammatory analgesics for a sufficient period of time, control of oral parafunctional habits, and jaw exercises were effective for the management of NIM of the TM. A thorough clinical examination and MR imaging including the axial T2-weighted view are required for accurate diagnosis and effective management of NIM of the TM.

Difference between Anterior and Posterior Cord Compression and Its Clinical Implication in Patients with Degenerative Cervical Myelopathy.

In degenerative cervical myelopathy (DCM), the low anteroposterior compression ratio of the spinal cord is known to be associated with a neurologic deficit. However, there is little detailed analysis of spinal cord compression. Axial magnetic resonance images of 183 DCM patients at normal C2-C3 and maximal cord compression segments were analyzed. The anterior (A), posterior (P), and anteroposterior length and width (W) of the spinal cord were measured. Correlation analyses between radiographic parameters and each section of Japanese Orthopedic Association (JOA) scores and comparisons of the patients divided by A (below or above 0, 1, or 2 mm) were performed. Between C2-C3 and maximal compression segments, the mean differences of A and P were 2.0 (1.2) and 0.2 (0.8) mm. The mean anteroposterior compression ratios were 0.58 (0.13) at C2-C3 and 0.32 (0.17) at maximal compression. The A and A/W ratio were significantly correlated with four sections and the total JOA scores (p < 0.05), but the P and P/W ratio did not demonstrate any correlations. Patients with A < 1 mm had significantly lower JOA scores than those with A ≥ 1 mm. In patients with DCM, spinal cord compression occurs mainly in the anterior part and the anterior cord length of <1 mm is particularly associated with neurologic deficits.

Deep learning for image classification between primary central nervous system lymphoma and glioblastoma in corpus callosal tumors.

It can be challenging in some situations to distinguish primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM) based on magnetic resonance imaging (MRI) scans, especially those involving the corpus callosum. The objective of this study was to assess the diagnostic performance of deep learning (DL) models between PCNSLs and GBMs in corpus callosal tumors. The axial T1-weighted gadolinium-enhanced MRI scans of 274 individuals with pathologically confirmed PCNSL (n = 94) and GBM (n = 180) were examined. After image pooling, pre-operative MRI scans were randomly split with an 80/20 procedure into a training dataset (n = 709) and a testing dataset (n = 177) for DL model development. Therefore, the DL model was deployed as a web application and validated with the unseen images (n = 114) and area under the receiver operating characteristic curve (AUC); other outcomes were calculated to assess the discrimination performance. The first baseline DL model had an AUC of 0.77 for PCNSL when evaluated with unseen images. The 2nd model with ridge regression regularization and the 3rd model with drop-out regularization increased an AUC of 0.83 and 0.84. In addition, the last model with data augmentation yielded an AUC of 0.57. DL with regularization may provide useful diagnostic information to help doctors distinguish PCNSL from GBM.

Evaluation of the degeneration of the multifidus and erector spinae muscles in patients with low back pain and healthy individuals.

Although several studies have been conducted to determine the cause of low back pain (LBP), a sufficient correlation has not been found between research findings and symptoms. Therefore there seems to be a need for studies to explain the relationship between pain and morphological changes in the paraspinal muscles of patients with LBP through comparisons with healthy control subjects. The aim of this study was to examine degeneration in the lumbar musculus multifidus (LMF) and lumbar musculus erector spinae (LES) muscles in patients with chronic LBP with non-radiculopathy lumbar disc herniation (LDH), patients with mechanical LBP, and healthy individuals. The study included 35 patients with mechanical LBP, 38 patients with non-radiculopathy LDH, and a control group of 36 healthy participants. In all patients and the control group, evaluations were made on axial magnetic resonance imaging slices at L3-S1 level of the LMF and LES cross-sectional areas (CSA), total CSA (TCSA = LMF+LES), fat infiltrations and asymmetries. The mean CSA values of the right and left LMF and LES showed significant differences between the groups (p< 0.001, p= 0.002, p= 0.002, p= 0.010, respectively). Fat infiltrations showed a difference between the right-left LMF and left LES groups (p= 0.007, p< 0.001, p= 0.026, respectively). Asymmetry was not observed between the CSA and TCSA of the right and left sides. A correlation was found between fat infiltration in the LMF and mechanical LBP and LDH. However, no significant correlation was determined between LBP and the CSA and TCSA of the LMF and LES. This was thought to be due to an incorrect result of CSA and TCSA in the evaluation of muscle mass. Therefore, for a more accurate evaluation of muscle mass, it can be considered necessary to measure muscle atrophy associated with fat infiltration or functional CSA.

Symptoms: Sudden Sensorineural Hearing Loss and Aural Fullness

Symptoms: Sudden Sensorineural Hearing Loss and Aural Fullness

Two-Dimensional Magnetic Resonance Imaging in Preparation for Autograft Anterior Cruciate Ligament Reconstruction Demonstrates Quadriceps Tendon Is Thicker Than Patellar Tendon

The purpose of this study was to assess patellar tendon (PT) and quadriceps tendon (QT) thickness on preoperative magnetic resonance imaging (MRI), in both the sagittal and axial planes, at multiple points along each tendon, and to correlate these findings to anthropometric patient data before anterior cruciate ligament (ACL) surgery. Patients who underwent PT or QT autograft ACL reconstruction between 2020 and 2022 and who had preoperative MRIs with adequate visualization of the proximal QT and distal PT were retrospectively identified. Patient demographics were recorded (age, height, weight, sex, injury side). Preoperative MRI measurements were performed by 3 independent examiners using standardized protocol. Preoperative MRI measurements were the QT anterior-posterior (AP) thickness at 1, 2, and 4 cm from the proximal patella on axial and sagittal MRI images at the central aspect of the tendon, as well as PT AP thickness at 1, 2, and 4 cm from the distal patella on axial and sagittal MRI images at the central aspect of the tendon. Forty-one patients (21 females, 20 males) were evaluated, with a mean age of 33.4 years. The quadriceps tendon was significantly thicker than the patellar tendon at all measured locations (P < .0001) with average QT versus PT thickness (in mm) at each level sagittal 1 cm (7.13 vs 4.35), sagittal 2 cm (7.41 vs 4.44), sagittal 4 cm (7.26 vs 4.81), axial 1 cm (7.35 vs 4.50), axial 2 cm (7.63 vs 4.47), axial 4 cm (7.46 vs 4.62), respectively. There were no significant correlations between tendon size and patient body mass index. The quadriceps tendon is significantly thicker than the patellar tendon at 1, 2, and 4 cm from the patella in both males and females based on preoperative MRI before ACL surgery. Investigating the thickness of the tendons available for autograft harvest before surgery will give us a better understanding of tendon anatomy in the setting of ACL reconstruction.

Marked central canal T2-hyperintensity in MOGAD myelitis and comparison to NMOSD and MS

ObjectiveTo assess marked central canal T2-hyperintensity in patients with myelin-oligodendrocyte glycoprotein antibody-associated disease (MOGAD) myelitis compared to myelitis patients with aquaporin-4-antibody-positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD) and multiple sclerosis (MS). Material/methodsTwo blinded raters evaluated spinal cord magnetic resonance imaging (MRIs) of myelitis patients with MOGAD (n = 63), AQP4 + NMOSD (n = 37), and MS (n = 26), assessing for marked central canal T2-hyperintensity and its evolution. If there were conflicting results, a third neurologist assessed the MRI. ResultsMarked central canal T2-hyperintensity was more frequent in patients with MOGAD (18/63[29%]) than MS (1/26[4%]; p = 0.01) myelitis but did not differ from AQP4 + NMOSD (13/37[35%]; p = 0.49). Marked central canal T2-hyperintensity had completely resolved on follow-up axial MRI for most MOGAD (12/14[86%]) and AQP4 + NMOSD (10/10[100%]; p = 0.49) patients. ConclusionsMarked central canal T2-hyperintensity is a common transient radiologic accompaniment of MOGAD and AQP4 + NMOSD myelitis, but not MS myelitis.

Menière's Syndrome Associated With Fibrous Dysplasia of the Temporal Bone.

Menière's Syndrome Associated With Fibrous Dysplasia of the Temporal Bone.