Coronal Magnetic Resonance Imaging Research Articles

Fatty infiltration of extraocular muscles on magnetic resonance imaging

ABSTRACT Purpose To investigate the prevalence of fatty infiltration in normal orbits using magnetic resonance imaging (MRI) and its impact on muscle diameters. Methods A retrospective analysis was conducted on normal orbits in patients who underwent coronal T1-weighted MRI. Fatty infiltration was defined by a hyperintense signal within the extraocular muscle. Fatty infiltration area was calculated by dividing the cross-sectional fat area by the sum of the muscle and fat area in the coronal plane. Muscle diameters were measured perpendicular to the muscle belly at their maximum and the mean diameters of the infiltrated muscles were compared with the non-infiltrated muscles. Results Seventy-six orbits from 76 participants with a mean age of 55.7 ± 18 years were included. Fatty infiltration in at least one muscle was seen in 57 (75%) of participants. When infiltration was present, inferior rectus was most commonly involved (98%). The area of fatty infiltration ranged from 6% to 42%, with 5 participants in the <10% group, 36 in the 10–20% group, 20 in the 20–30% group, 9 in the 30–40% group and 2 in the 40–50% group. Participants with fatty infiltration were significantly older (mean 61 ± 15 years vs 40 ± 16 years, p < .01) and had a higher proportion of males (56% vs 16%, p < .01). No significant difference in muscle diameters were found between infiltrated and healthy muscles. Conclusion Fatty infiltration of the extraocular muscles is a reasonably common finding in normal orbits, most commonly involves the inferior rectus muscle and is associated with increasing age.

Integration Of Fuzzy Logic And Deep Learning For Medical Image Analysis In Neuroimaging

Input from magnetic resonance imaging (MRI) scans is used by contemporary deep learning algorithms to assess changes in brain structure. Over the past several years, a variety of deep learning techniques have gained popularity for their application in the process of feature learning and the enhancement of the responsiveness of systems for learning. We are able to apply a deep learning classifier to identify structural changes in the brain and express the spatial information in this study. This is made possible by integrating the transfer learning model with a fuzzy convolutional neural network (CNN) that performed 3D convolutions at earlier levels. Through the utilisation of ResNet and 2D fuzzy convolutional layers, the model makes use of MCI, which is more often referred to as AD, in order to enhance class separability. To facilitate binary classification in the study, the suggested model is trained and evaluated over a collection of sagittal, coronal, or transverse MRI slices. This is done in order to facilitate the job. An approach known as 5-fold cross-valuation is utilised in this research project in order to investigate the accuracy that was achieved via the use of classification issues during testing and training. In terms of accuracy, the suggested technique achieves a rate of 99%, which is higher than both existing methods and methods that do not use ResNet and 2D Fuzzy convolutional layers. This is according to the data obtained from simulations.

An Examination of Temporomandibular Joint Disc Displacement through Magnetic Resonance Imaging by Integrating Artificial Intelligence: Preliminary Findings

Background and Objectives: This research was aimed at constructing a complete automated temporomandibular joint disc position identification system that could assist with magnetic resonance imaging disc displacement diagnosis on oblique sagittal and oblique coronal images. Materials and Methods: The study included fifty subjects with magnetic resonance imaging scans of the temporomandibular joint. Oblique sagittal and coronal sections of the magnetic resonance imaging scans were analyzed. Investigations were performed on the right and left coronal images with a closed mouth, as well as right and left sagittal images with closed and open mouths. Three hundred sagittal and coronal images were employed to train the artificial intelligence algorithm. Results: The accuracy ratio of the completely computerized articular disc identification method was 81%. Conclusions: An automated and accurate evaluation of temporomandibular joint disc position was developed by using both oblique sagittal and oblique coronal magnetic resonance imaging images.

Impact of Emerging Deep Learning-Based MR Image Reconstruction Algorithms on Abdominal MRI Radiomic Features.

This study aims to evaluate, on one MRI vendor's platform, the impact of deep learning (DL)-based reconstruction techniques on MRI radiomic features compared to conventional image reconstruction techniques. Under IRB approval and informed consent, we prospectively collected undersampled coronal T2-weighted MR images of the abdomen (1.5 T; Philips Healthcare) from 17 pediatric and adult subjects and reconstructed them using a conventional image reconstruction technique (compressed sensitivity encoding [C-SENSE]) and two DL-based reconstruction techniques (SmartSpeed [Philips Healthcare, US FDA cleared] and SmartSpeed with Super Resolution [SmartSpeed-SuperRes, not US FDA cleared to date]). Eight regions of interest (ROIs) across organs/tissues (liver, spleen, kidney, pancreas, fat, and muscle) were manually placed. Eighty-six MRI radiomic features were then extracted. Pearson's correlation coefficients (PCCs) and intraclass correlation coefficients (ICCs) were calculated between (A) C-SENSE versus SmartSpeed, and (B) C-SENSE versus SmartSpeed-SuperRes. To quantify the impact from the perspective of the whole MR image, cross-ROI mean PCCs and ICCs were calculated for individual radiomic features. The impact of image reconstruction on individual radiomic features in different organs/tissues was evaluated using ANOVA analyses. According to cross-ROI mean PCCs, 50 out of 86 radiomic features were highly correlated (PCC, ≥0.8) between SmartSpeed and C-SENSE, whereas only 15 radiomic features were highly correlated between SmartSpeed-SuperRes and C-SENSE reconstructions. According to cross-ROI mean ICCs, 58 out of 86 radiomic features had high agreements (ICC ≥0.75) between SmartSpeed and C-SENSE, whereas only 9 radiomic features had high agreements between SmartSpeed-SuperRes and C-SENSE reconstructions. For SmartSpeed reconstruction, the psoas muscle ROI appeared to be impacted most with the lowest median (IQR) correlation of 0.57 (0.25). The circular liver ROI was impacted most by SmartSpeed-SuperRes (PCC, 0.60 [0.22]). ANOVA analyses suggest that the impact of DL reconstruction algorithms on radiomic features varies significantly among different organs/tissues (P < 0.001). MRI radiomic features are significantly altered by DL-based reconstruction compared to a conventional reconstruction technique. The impact of DL reconstruction algorithms on radiomic features varies significantly between different organs/tissues.

The posterior condyle grows in the direction of the increasing posterior condylar offset and the inclination angle of the ACL changes accordingly.

The purpose of this study was to reveal the changes in the shape of the posterior femoral condyle and the morphology of the ACL, both before and after epiphyseal closure. The hypothesis of this study is that the morphological change of the posterior femoral condyle and that of the ACL may be correlated to some extent. Eighty-one patients who underwent surgery for the knee joint (meniscal repair, arthroscopic synovectomy, medial patellofemoral ligament reconstruction) between 2016 and 2021 were included in this study, 48 patients aged 13 years or under (before epiphysis closure; mean age: 10.9 (range: 7-13) and 33 patients aged over 18 years or over (after epiphysis closure; mean age: 21.7 (range: 18-30). The shape of the posterior femoral condyle was evaluated via lateral view radiographs, and the morphology of the ACL was measured via sagittal and coronal magnetic resonance imaging (MRI) images. The morphology of the posterior condyle in the lateral view radiograph in patients aged 13 and under was larger in the direction of the short axis of the femur compared with that in those aged 18 and over (p < 0.001). The mean value of the inclination angle of the anterior cruciate ligament (ACL) in the sagittal plane was significantly smaller in patients aged 13 and under (41.7° ± 3.7) than in those aged 18 and over (48.5° ± 4.2) (p < 0.001). The mean values of the inclination angle of the ACL in the coronal plane were significantly smaller in patients aged 13 and under (55.7° ± 6.4) than in those aged 18 and over (63.4° ± 4.4) (p < 0.001). This study evaluates and compares the shape of the posterior femoral condyle and the morphology of the ACL fiber before and after epiphyseal closure. The posterior femoral condyle grew posteriorly rather than longitudinally, and the inclination of the ACL fibers was thought to change accordingly. Level Ⅲ.

Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning.

Pancreatic cysts in autosomal dominant polycystic kidney disease (ADPKD) correlate with PKD2 mutations, which have a different phenotype than PKD1 mutations. However, pancreatic cysts are commonly overlooked by radiologists. Here, we automate the detection of pancreatic cysts on abdominal MRI in ADPKD. Eight nnU-Net-based segmentation models with 2D or 3D configuration and various loss functions were trained on positive-only or positive-and-negative datasets, comprising axial and coronal T2-weighted MR images from 254 scans on 146 ADPKD patients with pancreatic cysts labeled independently by two radiologists. Model performance was evaluated on test subjects unseen in training, comprising 40 internal, 40 external, and 23 test-retest reproducibility ADPKD patients. Two radiologists agreed on 52% of cysts labeled on training data, and 33%/25% on internal/external test datasets. The 2D model with a loss of combined dice similarity coefficient and cross-entropy trained with the dataset with both positive and negative cases produced an optimal dice score of 0.7 ± 0.5/0.8 ± 0.4 at the voxel level on internal/external validation and was thus used as the best-performing model. In the test-retest, the optimal model showed superior reproducibility (83% agreement between scan A and B) in segmenting pancreatic cysts compared to six expert observers (77% agreement). In the internal/external validation, the optimal model showed high specificity of 94%/100% but limited sensitivity of 20%/24%. Labeling pancreatic cysts on T2 images of the abdomen in patients with ADPKD is challenging, deep learning can help the automated detection of pancreatic cysts, and further image quality improvement is warranted.

Comparative evaluation and correlation of variations in articular disc morphology as assessed by automated segmentation using deep learning on magnetic resonance imaging (MRI) images in Class II (vertical) TMD cases, Class II (horizontal) TMD cases and Class I non-TMD cases

Introduction: Temporomandibular disorder (TMD) encompasses several clinical manifestations, which are characterized by temporomandibular joint and masticatory muscle discomfort and dysfunction (TMJ). The best imaging technique for evaluating TMJ is magnetic resonance imaging (MRI), which makes it possible to see the anatomical and pathological characteristics of every joint component. In recent years, convolutional neural networks -based deep learning algorithms have been favoured because of their outstanding capability in recognizing objects in medical images. The objective of this study is to assess, compare and co-rrelate articular disc morphology by automated segmentation using deep learning on MRI images in skeletal Class II (vertical growth pattern) TMD cases as compared to skeletal Class II (horizontal growth pattern) TMD cases and Class I non-TMD cases Methods: Grading of skeletal Class II (vertical growth pattern) cases and skeletal Class II (horizontal growth pattern) cases based on severity of TMD will be carried out using diagnostic criteria for temporomandibular disorders. Bilateral sagittal as well as coronal MRI images will be obtained. A convolutional neural network (CNN) encoder-decoder named U-Net will be used to segment the articular disc on MRI. Understanding the nature of variations between Class I and both types of Class IIs will help orthodontists to better predict the potential risk for the development of TMDs and accordingly take precautions while doing treatment in such cases. Moreover, it can be used to automate TMD diagnosis and other smart applications. Conclusions: This study will aid in identifying articular disc morphology on MRI. The deep learning algorithms with effective data augmentation may perform better in MRI readings than human clinicians when using the same data, which will be advantageous for TMD diagnosis.

The relationship between the duration and the retraction and atrophy grades in traumatic isolated full-thickness supraspinatus tears in young patients

BackgroundThe study aimed to determine the grade of retraction and atrophy according to the time elapsed in traumatic isolated full-thickness supraspinatus (SS) tears in young patients.MethodsOne thousand twenty-six patients, who underwent arthroscopic shoulder surgery, were retrospectively reviewed. Pre-operative magnetic resonance imaging (MRI) of 69 patients aged 18 to 40 years with isolated traumatic full-thickness SS lesions remaining after exclusion criteria were evaluated for tendon retraction and atrophy grades. SS retraction was determined from a T2-weighted oblique coronal MRI slice, and the atrophy grade was determined from the T1-weighted oblique sagittal MRI slice. The patients were divided into four groups 0–1 month, 1–3 months, 3–6 months, and 6–12 months according to the time between trauma and MRI. The relationship of tendon retraction and muscle atrophy with elapsed time was evaluated, in addition, comparisons between groups were made.ResultsThirty-one (45%) of the patients were female and their mean age was 30 ± 7.3 (18–40) years. The mean age of men was 30.5 ± 6.9 (18–39) years (p = 0.880). The time between rupture and MRI was moderately correlated with retraction and strongly correlated with atrophy grades (r = 0.599, 0.751, respectively). It was observed that there was a statistically significant difference between the 1st (0–1 month) and 2nd (1–3 months) groups (p = 0.003, 0.001, respectively), and between the 2nd and 3rd (3–6 months) groups (p = 0.032, 0.002, respectively), but there was no significant difference between the 3rd and 4th (6–12 months) groups (p = 0.118, 0.057, respectively). In addition, there was a moderate correlation between tendon retraction and atrophy grades (r = 0.668). Power (1- b) in post hoc analysis was calculated as 0.826.ConclusionsThe current study, supported by arthroscopy, showed that there is a moderate and strong positive correlation between the time elapsed after trauma and the level of retraction and degree of atrophy in traumatic full-thickness SS tears, and demonstrated the importance of early surgical intervention in young patients.

#2115 Phase-contrast magnetic resonance imaging (PC-MRI) for quantification of volumetric flow in renal transplant arteries: an observational cohort study

Abstract Background and Aims Impaired renal transplant blood flow, a manifestation of severe transplant renal artery stenosis (TRAS), can negatively impact transplant function and survival. Phase-contrast magnetic resonance imaging (PC-MRI) is a non-invasive method of quantifying blood flow volume. Recent work has demonstrated the utility of this technique in measuring native renal blood flow, whilst validating the use of flow measurements taken on the aorta above and below the origin of the renal arteries to calculate flow in the renal arteries [1]. As part of a quality improvement study incorporating PC-MRI into renal transplant assessment, this study set out to (a) establish the normal range for transplant renal blood flow volume and (b) assess whether PC-MRI improved screening for TRAS. Method Between January 2019 and February 2021, PC-MRI sequences were included in the protocols for all magnetic resonance angiograms (MRA) performed as part of clinically-indicated renal transplant assessment. As part of the MRA study, using a coronal localizer MR image, planes were prescribed on the external iliac artery (EIA) both proximal and distal to the transplant artery anastomosis site in a perpendicular orientation (Fig. 1A). Using CV142 software [2], arterial cross-sections were highlighted manually at the pre-determined planes (Fig. 1B) to generate flow curves that coincided with the cardiac cycle (Fig. 1C). Studies were excluded if: the EIA flow waveform was incongruous with the cardiac cycle, contemporaneous heart rate data was not recorded, or the calculated flow volume was a negative value. Results During the study period 392 transplant MRAs were performed, of which 218 were included in this analysis. Potential TRAS was identified in 49 (22.5%) studies, with 19 (8.7%) having this diagnosis confirmed by intra-arterial digital subtraction angiography (IADSA). In the 169 (77.5%) studies without evidence of TRAS, the mean flow in the proximal EIA was 0.90 L/min (95% CI 0.85-0.94 L/min) and in the distal EIA 0.47 L/min (95% CI 0.44-0.50 L/min). The difference between the two measurement points, that is the flow in the transplant renal artery, was 0.42 L/min (95% CI 0.39-0.45 L/min) (Fig. 2A). In the 19 studies with TRAS confirmed by IADSA, mean flow at the time of the initial MRA was 0.34 L/min (95% CI 0.25-0.43 L/min); there was no difference when compared with the group without evidence of TRAS on MRA (p = 0.09) (Fig. 2B). Of the patients who had potential TRAS identified on MRA, 30 patients proceeded to IADSA; there was no difference in PC-MRI flow volume in the 11 who had a diagnosis of TRAS refuted on IADSA and the 19 who had diagnosis of TRAS confirmed (p = 0.97). ROC curve analysis of PC-MRI arterial flow measurement as a diagnostic test for TRAS, whereby the positive group of 19 had IADSA confirmed TRAS, the negative group of 176 had either normal MRA artery appearances or normal IADSA, and the disease prevalence is 13.7% [3], shows AUC 0.62 (95% CI 0.55-0.69) P = 0.09, sensitivity 57.9 specificity 67.1 (Fig. 2C). Conclusion This is the largest study to incorporate functional PC-MRI sequences into MRA protocols for the assessment of people with any form of kidney disease. The results suggest that the blood flow volume in healthy transplant renal arteries lies between 0.39–0.45 L/min. In comparative analysis between patients with healthy transplant arteries and those with IADSA-confirmed TRAS, there was no difference in arterial flow volume, though the study was limited by the small population in the group with IADSA-confirmed TRAS. PC-MRI does not appear to improve the screening accuracy of MRA in identifying TRAS. However, there may be a future role for PC-MRI as part of multi-parametric MR protocols for comprehensive assessment of patients with kidney transplants.

More than 3 mm of preoperative medial meniscal extrusion is identified as a key risk factor for varus progression in limb alignment after arthroscopic repair of medial meniscus posterior root tear.

To investigate the risk factors for varus progression after arthroscopic medial meniscal posterior root tear (MMPRT) repair and to compare the clinical outcomes between two groups: one with more varus progression and the other with less varus progression. Patients who underwent isolated arthroscopic repair of MMPRT between 2015 and 2020 were enroled, and 2-year follow-up data were collected. Participants were categorized into two groups based on preoperative values of the weight-bearing line (WBL) ratio: group A with <5.9% increase and group B with ≥5.9% increase. Various factors, including demographic features and radiological findings, were analysed and compared between the two groups. Intra-meniscal signal intensity, meniscal healing, medial meniscal extrusion (MME), and articular cartilage grade were assessed preoperatively and 1-year postoperatively using coronal magnetic resonance imaging. The final cohort consisted of 34 patients in group A and 46 in group B, with a mean age of 55.8 ± 11.2 and 59.8 ± 6.6 years, respectively. Preoperative WBL ratio and cartilage lesions in the medial compartment did not differ between the groups. Preoperative MME were significantly lower in group A than those in group B (2.6 ± 0.6 mm in group A and 3.5 ± 0.7 mm in group B, p < 0.05). Patient-reported outcomes at the 2-year follow-up did not differ between the two groups (n. s.). In a logistic analysis, the odds ratio of MME was 2.1 (p < 0.05), and the cutoff value of MME was 3.02 mm. Preoperative MME is a risk factor for varus progression. However, no differences in patient-reported outcomes were observed at 2-year follow-up, even in the group with greater varus progression. Level IV.

Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.

Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD. A convolutional neural network was trained using manually corrected, filter-based segmentations (n = 1000) to automatically segment the PVS in the centrum semiovale from interpolated, coronal T2-weighted magnetic resonance imaging scans (n = 894). These scans were sourced from the national German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study. Convolutional neural network-based segmentations and those performed by a human rater were compared in terms of segmentation volume, identified PVS clusters, as well as Dice score. The comparison revealed good segmentation quality (Pearson correlation coefficient r = 0.70 with P < 0.0001 for PVS volume, detection rate in cluster analysis = 84.3%, and Dice score = 59.0%). Subsequent multivariate linear regression analysis, adjusted for participants' age, was performed to correlate PVS volume with clinical diagnoses, disease progression, cerebrospinal fluid biomarkers, lifestyle factors, and cognitive function. Cognitive function was assessed using the Mini-Mental State Examination, the Comprehensive Neuropsychological Test Battery, and the Cognitive Subscale of the 13-Item Alzheimer's Disease Assessment Scale. Multivariate analysis, adjusted for age, revealed that participants with AD and MCI, but not those with SCD, had significantly higher PVS volumes compared with CU participants without SCD ( P = 0.001 for each group). Furthermore, CU participants who developed incident MCI within 4.5 years after the baseline assessment showed significantly higher PVS volumes at baseline compared with those who did not progress to MCI ( P = 0.03). Cognitive function was negatively correlated with PVS volume across all participant groups ( P ≤ 0.005 for each). No significant correlation was found between PVS volume and any of the following parameters: cerebrospinal fluid biomarkers, sleep quality, body mass index, nicotine consumption, or alcohol abuse. The very early changes of PVS volume may suggest that alterations in PVS function are involved in the pathophysiology of AD. Overall, the volumetric assessment of centrum semiovale PVS represents a very early imaging biomarker for AD.

Factors associated with medial meniscal extrusion in non-osteoarthritic knees with medial meniscus tears: A cross-sectional study.

Medial meniscal extrusion (MME) plays an important role in the progression of knee osteoarthritis. Exploring the factors associated with MME in non-osteoarthritic knees may assist in the prevention of osteoarthritis. To identify the factors associated with pathologic MME in non-osteoarthritic knees with medial meniscus tears (MMTs). A cross-sectional study. One hundred fifty patients with non-osteoarthritic knees who underwent arthroscopic surgery for MMT. Patients were divided into a pathologic MME group (n = 54) and a control group (n = 96) based on whether a pathologic MME was present on magnetic resonance (MR) images. Tertiary medical institution. Not applicable. The MME distance was measured on a coronal MR image obtained at the midpoint of the medial femoral condyle. An MME distance ≥3 mm was considered to indicate pathologic MME. Demographic and clinical data were collected as variables. Multivariable logistic regression analysis was performed to identify factors associated with pathologic MME. After multivariable adjustment, body mass index (BMI) and the type of MMT were associated significantly with pathologic MME in the multivariable logistic regression model. Each unit higher in BMI was associated with a 13% higher risk of pathologic MME (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.01-1.28, p = .04). The odds of pathologic MME were approximately four times and three times higher for radial tears (OR 4.34, 95% CI 1.25-15.03, p = .02) and complex tears (OR 3.07, 95% CI 1.17-8.05, p = .02) than for horizontal and longitudinal tears. BMI and the type of MMT were independent factors associated with pathologic MME in non-osteoarthritic knees with MMT. A higher BMI, radial tears, and complex tears were predisposed to pathologic MME.

Diameters of the optic sheath and superior ophthalmic vein can expand and contract at positional changes: a magnetic resonance imaging study.

This study aimed to explore the diameters of the optic sheath (OSD) and superior ophthalmic vein (SOVD) in response to positional changes using magnetic resonance imaging (MRI). Fifty adult outpatients who presented to the hospital underwent thin-slice coronal T2-weighted MRI in the supine position followed by the prone position. The OS and SOV were well delineated in all the patients. The OSD in the anterior orbit was measured in the supine and prone positions on both sides. In addition, the SOVD in the anterior and posterior orbits was measured in the supine and prone positions on both sides. The OSD demonstrated an increase on both sides in 100% of the cases. The SOVD demonstrated an increase on both sides in 94% of the cases, whereas the remaining 6% demonstrated a decrease. The OSD measured at the anterior orbit and the SOVD at the anterior and posterior orbits significantly increased on both sides with positional changes from the supine to the prone position. OSD and SOVD may expand and contract in response to alterations in the intracranial pressure and venous flow patterns. MRI examination in the supine position combined with positional changes can help to better understand the OS and SOV as dynamic structures.

A Practical Screening Combination for the Discrimination of Alzheimer’s Type Memory Impairment Continuum: The 5-word Test and Magnetic Resonance Imaging-visual Rating Scale

Introduction: Alzheimer’s disease (AD) is a continuum with four clinical stages: asymptomatic, subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD dementia (ADD). Identification of the predementia stages had become particularly essential after the recent approval of three anti-amyloid-β monoclonal antibodies. This study aimed to evaluate their contribution to the diagnosis of AD by using two practical instruments: The 5-word test (5WT) and medial temporal atrophy (MTA) scoring together. Materials and Methods: Twenty six ADD, 29 MCI, and 25 SCI patients matched for age, sex, and education were included. The Addenbrooke’s Cognitive Examination-Revised version, which includes the Mini-Mental Status Examination, and 5WT were applied. MTA is scored on coronal T1 magnetic resonance images, between 0 and 4 (0: Severe atrophy, 4: No atrophy). A receiver operating characteristic curve analysis was performed to test the success of the MTA score, screening tests, and scores formed from various combinations of these two in classifying the groups. Results: MTA + 5WT had the highest area under curve (AUC) differentiating SCI versus MCI with a sensitivity of 0.80 and a specificity of 0.83, and differentiating SCI versus ADD with a sensitivity and specificity of 1.0. For differentiating MCI versus ADD, MTA + 5WT had a very good performance with an AUC of 0.93, a specificity of 0.96, and a moderate sensitivity of 0.76. Conclusion: Combining 5WT for memory test with MTA for atrophy rating becomes a perfect method in a clinical setting for evaluating patients with memory complaints and thus carefully selecting the candidates for advanced biological diagnosis.

Femoral Head Remodeling After Surgical Reduction of Developmental Hip Dislocations.

Developmental dysplasia of the hip is prevalent and is associated with dysplasia of both the femoral head and acetabulum. There is a paucity of literature describing femoral head remodeling after surgical reduction of developmentally dislocated hips. The purpose of this study was to describe and quantify changes in femoral head sphericity after closed or open reduction for developmental dysplasia of the hip. A retrospective cohort study was performed including patients with typical developmental hip dislocations who underwent closed or open reduction from 2009 to 2022 at a single institution and had immediate postoperative and average 3-week follow-up magnetic resonance imaging (MRI) scans. A subset of patients also had 3-year follow-up MRI scans. Patients with insufficient imaging or bony procedures at the time of reduction were excluded. We developed a technique to quantify femoral head "sphericity" by comparing differences in measured radii of the femoral head on axial and coronal plane MRI slices. We then calculated the variance of the radii for each plane and averaged these to calculate a combined variance. The variance was used to represent "sphericity," with a larger variance indicating a wider distribution of radii and thus a less spherical shape. A total of 74 patients (69 females) with 96 hips were included in this series. The median age of the child at the time of reduction was 8.7 months [interquartile range (IQR): 2.2]. Over half (58.3%) of the hips had a closed reduction, whereas the remaining were open reduced (41.7%). Immediately postoperatively, at the 3-week time point, and at the 3-year time point the median combined variance was 1.1 (IQR: 3.93), 0.51 (IQR: 1.32), and 0.31 (IQR: 0.50), respectively, indicating improved sphericity over time. Sphericity of the femoral head in developmental hip dislocations improves in both the immediate postoperative period, as well as the first few years after reduction. Further research is needed to evaluate the mechanism of remodeling, the ideal timing of reduction, and the relationship between femoral head and acetabular remodeling. Level IV-case series, therapeutic study.

Automatic Quantification of Normal Brain Gyrification Patterns and Changes in Fetuses with Polymicrogyria and Lissencephaly Based on MRI.

The current imaging assessment of fetal brain gyrification is performed qualitatively and subjectively using sonography and MR imaging. A few previous studies have suggested methods for quantification of fetal gyrification based on 3D reconstructed MR imaging, which requires unique data and is time-consuming. In this study, we aimed to develop an automatic pipeline for gyrification assessment based on routinely acquired fetal 2D MR imaging data, to quantify normal changes with gestation, and to measure differences in fetuses with lissencephaly and polymicrogyria compared with controls. We included coronal T2-weighted MR imaging data of 162 fetuses retrospectively collected from 2 clinical sites: 134 controls, 12 with lissencephaly, 13 with polymicrogyria, and 3 with suspected lissencephaly based on sonography, yet with normal MR imaging diagnoses. Following brain segmentation, 5 gyrification parameters were calculated separately for each hemisphere on the basis of the area and ratio between the contours of the cerebrum and its convex hull. Seven machine learning classifiers were evaluated to differentiate control fetuses and fetuses with lissencephaly or polymicrogyria. In control fetuses, all parameters changed significantly with gestational age (P < .05). Compared with controls, fetuses with lissencephaly showed significant reductions in all gyrification parameters (P ≤ .02). Similarly, significant reductions were detected for fetuses with polymicrogyria in several parameters (P ≤ .001). The 3 suspected fetuses showed normal gyrification values, supporting the MR imaging diagnosis. An XGBoost-linear algorithm achieved the best results for classification between fetuses with lissencephaly and control fetuses (n = 32), with an area under the curve of 0.90 and a recall of 0.83. Similarly, a random forest classifier showed the best performance for classification of fetuses with polymicrogyria and control fetuses (n = 33), with an area under the curve of 0.84 and a recall of 0.62. This study presents a pipeline for automatic quantification of fetal brain gyrification and provides normal developmental curves from a large cohort. Our method significantly differentiated fetuses with lissencephaly and polymicrogyria, demonstrating lower gyrification values. The method can aid radiologic assessment, highlight fetuses at risk, and may improve early identification of fetuses with cortical malformations.

Microsurgical and fiber tract anatomy of the interthalamic adhesion.

The authors of this study aimed to define the microanatomy of the interthalamic adhesion (ITA) using microfiber dissection, magnetic resonance (MR) tractography, and histological analysis. Sagittal, coronal, and axial MR images from 160 healthy individuals 2-82 years of age were examined. The relationships between age range and ITA morphology as well as between gender and ITA morphology were evaluated statistically. Among these 160 individuals, 100 who had undergone MR tractography were examined. In this group, the presence of fiber tracts in the ITA and the relationship with ITA morphological types were examined. Thirty formalin-fixed human cadaveric brains were also examined endoscopically, and 6 hemispheres were dissected from the medial to lateral and superior to inferior directions under the microscope. Sections taken from one of the brains with an ITA type 2 with both thalami were examined histologically. Anti-neurofilament antibody was used in the histological examination. Four morphological types of ITA were observed. Type 1 had an adhesion/adherent appearance, type 2 had a bridge/commissure appearance, type 3 showed no adhesion, and type 4 had a double bridge. Tractographic examination revealed that 28% had no fiber tract transition in the ITA, 21% had a significant transition, and 51% had an indistinct transition. Statistically, the presence of the ITA was significantly higher in the pediatric (age) and female (gender) groups. In specimens with ITAs of a bridge/commissure appearance (type 2), fiber tracts showed clear transitions between thalami. In type 1 (adherent/adhesive appearance), fiber tracts were observed within the ITA, but a reciprocal transition was unclear. Dissection showed that these fiber tracts in the ITA reach the nucleus accumbens, caudate nucleus, and frontoorbital region anteriorly and the lateral habenula and posterior commissure posteriorly. Some fibers also joined the ansa peduncularis. In histological studies, axonal fibers moving in the ITA were observed with anti-neurofilament antibody staining. This is the first study to demonstrate fiber tracts of the ITA through fiber dissection and transillumination techniques as well as radiological and histological study. Statistical data were obtained by comparing the morphological group with age and gender groups. The anatomy of this structure, which has been neglected for many years, was reexamined. This study showed that the ITA has fibers connecting different parts of the brain, in contrast to previous studies suggesting that it was a simple massa.

Correlation between mental well-being and severity of class II temporomandibular joint disorders, compared to non-temporomandibular joint disorders

Temporomandibular joint disorders (TMDs) are one of the most common ailments encountered in the craniofacial region, with various clinical, radiological and psychological manifestations but often go undiagnosed due to lack of a diagnostic protocol to assess and correlate all these factors in order to create an effective management plan based on early diagnosis. The objectives of this research are to assess, compare and co-relate the severity of clinical and radiological findings with mental well-being in class II (vertical growth pattern) TMD cases as compared to class I non-TMD cases. Grading of skeletal class II cases on the severity of TMD will be done using Diagnostic Criteria for TMDs (DC/TMD). Bilateral sagittal as well as coronal magnetic resonance imaging (MRI) images will be obtained. Evaluation and grading of mental well-being and anxiety will be done using the Warwick-Edinburgh and Hamilton scales, respectively. The expected results are a probable positive correlation between the severity of clinical and radiological symptoms of TMDs and deteriorating mental well-being in the form of stress, anxiety and depression. A cause-effect relationship may be evaluated with the aim of early diagnosis and management of TMDs as improving the quality of life of these cases. This study will aid in identifying the clinical symptoms and articular disc position on MRI as they correlate with the mental well-being status and anxiety levels in TMD cases. Further management and early intervention can be undertaken in such cases to prevent or stall the progression of TMD into severe forms while improving the quality of life (QoL) in such cases.

Assessment of Daily Target Motion to Optimize ITV Margins in Online Adaptive Plan for Liver and Pancreatic SBRT on MR-LINAC

Accurate measurement of daily target motion on online plan adaptation is essential for re-optimizing the internal target volume (ITV) margins. In this study, by analyzing 2D cine MR images acquired in a 1.5T MR-Linac, we assessed daily target motion and its inter-fractional variations, which is then used to customize ITV margins for MR-based online adaptive plan of liver and pancreatic stereotactic body radiotherapy (SBRT). Twenty-threepatients, enrolled in this study, underwent MR-guided online adaptive SBRT on 1.5 T MR-Linac: liver (n = 12 without compression belt (CB), n = 2 with CB) and pancreas (n = 9 with CB). Target motion in a 2D coronal and sagittal MR images (> 200 cine images to cover multiple breathing cycles), as well as a set of 4D-CT images during the simulation, was analyzed to determine patient specific ITV margins for a reference plan. On every fraction of online adaptive SBRT, the 2D MR images were exported to commercially available software along with a planning MR images: a T1-wighted MR image set for pancreas and or a navigated T2-wighted MR image set for liver. Daily target motion was then measured by overlaying the orthogonal cine image set on the T1- or T2-wighted image set. The ITV margin was adjusted when required prior to online plan optimization RESULTS: Thisstudy successfully assessed the daily target motion and inter-fractional variations in 23 liver or pancreatic cancer patients. We found a discrepancy of daily target motion of orthogonal 2D cine MR images from that of 4D-CT, required to adjust the ITV margin for online plan adaptation. In liver SBRT without CB, 15 out of 45 fractions from 12 patients (33.3 %) went through adjusted ITV margin. The tumor motion was large up to a 2.2 cm along the inferior direction in a patient without CB and thus the patient was treated on a conventional Linac with the active breathing control (ABC) unit for breath-hold. On the other hand, no adjustments were necessary for 2 liver patients with CB. In 9 patients with pancreatic cancers, we found the inter-fractional ITV variations in 3 out of 45 fractions (6.7 %) adjusted the ITV margin. The daily target motion in the pancreatic patients with CB was more stable and relatively smaller than that of the liver patients. Theorthogonal 2D cine MR images are evidently essential for assessing daily target motion to evaluate the inter-fractional variation and achieve daily ITV-customized liver and pancreatic SBRT in the 1.5 T MR-Linac. The customized ITV approach will improve the treatment outcome of the MR-guided online adaptive therapy.

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.