Correlations between the alpha angle and femoral head asphericity: Implications and recommendations for the diagnosis of cam femoroacetabular impingement

pre-printObjective: To determine the strength of common radiographic and radial CT views for measuring true femoral head asphericity. Patients and Methods: In 15 patients with cam femoroacetabular impingement (FAI) and 15 controls, alpha angles were measured by two observers using radial CT (0º, 30º, 60º, 90º) and digitally reconstructed radiographs (DRRs) for the: anterior-posterior (AP), standing frog-leg lateral, 45° Dunn with neutral rotation, 45° Dunn with 40°external rotation, and cross-table lateral views. A DRR validation study was performed. Alpha angles were compared between groups. Maximum deviation from a sphere of each subject was obtained from a previous study. Alpha angles from each view were correlated with maximum deviation. Results: There were no significant differences between alpha angles measured on radiographs and the corresponding DRRs (p = 0.72). Alpha angles were significantly greater in patients for all views (p ≤0.002). Alpha angles from the 45° Dunn with 40° external rotation, cross-table lateral, and 60° radial views had the strongest correlations with maximum deviation (r = 0.831; r 20 = 0.823; r=0.808, respectively). The AP view had the weakest correlation (r = 0.358). Conclusion: DRRs were a validated means to simulate hip radiographs. The 45° Dunn with 40° external rotation, cross-table lateral, and 60º radial views best visualized femoral asphericity. Although commonly used, the AP view did not visualize cam deformities well. Overall, the magnitude of the alpha angle may not be indicative of the size of the deformity. Thus, 3D reconstructions and measurements of asphericity could improve the diagnosis of cam FAI. Key Words: Cam Femoroacetabular Impingement Alpha Angle, Femur Asphericity, Digitally Introduction Cam-type femoroacetabular impingement (FAI) has been implicated as a cause of chondrolabral damage, hip osteoarthritis (OA), and musculoskeletal pain in young adults [1-3]. Cam FAI is characterized by an aspherical femoral head and/or insufficient femoral head-neck offset [4,5]. Identifying the degree of femoral head asphericity is important as the underlying goal of surgery to correct cam FAI is to restore a more normal, spherical morphology to the femoral head. The alpha angle is a two-dimensional (2D) radiographic measure of femoral head asphericity that is commonly used to diagnose cam FAI [6-8]. Although, first proposed by Notzli et al. for only an oblique axial view of the femur, use of the alpha angle has been extended to several radiographic projections and radial computed tomography (CT) or magnetic resonance (MR) views [7,9-14]. Unfortunately, alpha angle measurements can vary between views of the same femur [10,15,16]. Consequently, the ideal view to diagnose cam FAI remains unknown [15,17]. One approach to identify the optimal view in which to measure the alpha angle has been to quantify observer repeatability. However, reports of repeatability have not been consistent and repeatability is not necessarily a measure of effectiveness [18,19]. Another approach has been to correlate alpha angles from standard radiographic views to oblique axial or radial MRI/CT views [12,14,15,17]. Still, alpha angle measurements from radial views are not generated automatically, and thus do not provide a true reference standard. In addition, radial views do not consider the geometry of the entire femoral head. Alternatively, subject-specific 3D reconstructions of femur morphology, generated from volumetric CT or MR images, can be used to visualize the anatomy of the entire femoral head. By fitting the 3D reconstruction to a sphere, UU IR Author Manuscript UU IR Author Manuscript University of Utah Institutional Repository Author Manuscript one can quantify the size of a deformity as maximum deviation from the sphere, herein referred to as 'true femoral head asphericity' [20,21]

Individual differences in striatum activity to food commercials predict weight gain in adolescents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109559/1/oby20882.pd

Functional changes in GABA and glutamate during motor learning

Functional magnetic resonance spectroscopy (fMRS) of GABA at 3 T poses additional challenges compared with fMRS of other metabolites because of the difficulties of measuring GABA levels; GABA is present in the brain at relatively low concentrations, and its signal is overlapped by higher concentration metabolites. Using 7 T fMRS, GABA levels have been shown to decrease specifically during motor learning (and not during a control task). Though the use of 7 T is appealing, access is limited. For GABA fMRS to be widely accessible, it is essential to develop this method at 3 T. Nine healthy right-handed participants completed a motor learning and a control button-pressing task. fMRS data were acquired from the left sensorimotor cortex during the task using a continuous GABA-edited MEGA-PRESS acquisition at 3 T. We found no significant changes in GABA+/tCr, Glx/tCr, or Glu/tCr levels in either task; however, we show a positive relationship between motor learning and glutamate levels both at rest and at the start of the task. Though further refinement and validation of this method is needed, this study represents a further step in using fMRS at 3 T to probe GABA levels in both healthy cognition and clinical disorders.publishedVersio

Neural responses to a modified Stroop paradigm in patients with complex chronic musculoskeletal pain compared to matched controls: an experimental functional magnetic resonance imaging study

Background: Chronic musculoskeletal pain (CMSKP) is attentionally demanding, complex and multi-factorial; neuroimaging research in the population seen in pain clinics is sparse. A better understanding of the neural activity underlying attentional processes to pain related information compared to healthy controls may help inform diagnosis and management in the future. Methods: Blood oxygenation level dependent functional magnetic resonance imaging (BOLD fMRI) compared brain responses in patients with CMSKP (n=15) and healthy controls (n=14) while completing a modified Stroop task using pain-related, positive-emotional, and neutral control words. Results: Response times in the Stroop task were no different for CMSKP patients compared with controls, but patients were less accurate in their responses to all word types. BOLD fMRI responses during presentation of pain-related words suggested increases in neural activation in patients compared to controls in regions previously reported as being involved in pain perception and emotion: the anterior cingulate cortex, insula and primary and secondary somatosensory cortex. No fMRI differences were seen between groups in response to positive or control words. Conclusions: Using this modified Stroop tasks, specific differences were identified in brain activity between CMSKP patients and controls in response to pain-related information using fMRI. This provided evidence of differences in the way that pain-related information is processed in those with chronic complex musculoskeletal pain that were not detectable using the behavioural measures of speed and accuracy. The study may be helpful in gaining new insights into the impact of attention in those living with chronic pai

Comparison of different approaches to manage multi-site magnetic resonance spectroscopy clinical data analysis

IntroductionThe effects caused by differences in data acquisition can be substantial and may impact data interpretation in multi-site/scanner studies using magnetic resonance spectroscopy (MRS). Given the increasing use of multi-site studies, a better understanding of how to account for different scanners is needed. Using data from a concussion population, we compare ComBat harmonization with different statistical methods in controlling for site, vendor, and scanner as covariates to determine how to best control for multi-site data.MethodsThe data for the current study included 545 MRS datasets to measure tNAA, tCr, tCho, Glx, and mI to study the pediatric concussion acquired across five sites, six scanners, and two different MRI vendors. For each metabolite, the site and vendor were accounted for in seven different models of general linear models (GLM) or mixed-effects models while testing for group differences between the concussion and orthopedic injury. Models 1 and 2 controlled for vendor and site. Models 3 and 4 controlled for scanner. Models 5 and 6 controlled for site applied to data harmonized by vendor using ComBat. Model 7 controlled for scanner applied to data harmonized by scanner using ComBat. All the models controlled for age and sex as covariates.ResultsModels 1 and 2, controlling for site and vendor, showed no significant group effect in any metabolites, but the vendor and site were significant factors in the GLM. Model 3, which included a scanner, showed a significant group effect for tNAA and tCho, and the scanner was a significant factor. Model 4, controlling for the scanner, did not show a group effect in the mixed model. The data harmonized by the vendor using ComBat (Models 5 and 6) had no significant group effect in both the GLM and mixed models. Lastly, the data harmonized by the scanner using ComBat (Model 7) showed no significant group effect. The individual site data suggest there were no group differences.ConclusionUsing data from a large clinical concussion population, different analysis techniques to control for site, vendor, and scanner in MRS data yielded different results. The findings support the use of ComBat harmonization for clinical MRS data, as it removes the site and vendor effects

Barriers to Implementation of a Technology-Based Mental Health Intervention in a Rural Setting

This study utilized qualitative focus groups with rural health providers and patients to explore barriers to implementation of a technology-based mental health intervention for the treatment of depression in a primary care setting. A randomized controlled trial (RCT) was implemented in both urban and rural primary care practices to test the feasibility and effectiveness of computerized cognitive behavioral therapy (CCBT) for depression. Early implementation identified lower rates of willingness to participate in the intervention by rural patients. Subsequently, focus groups were conducted with rural providers and patients to explore barriers to participation and strategies to overcome these barriers in future implementation efforts. Two focus groups of five to seven participants each were conducted to understand patient experiences. Groups lasted approximately one hour and were recorded and transcribed for coding purposes. Key themes identified about barriers to use of CCBT by rural patients emerged included: 1) technical barriers, 2) stigma, 3) distrust of outsiders, 4) effort/motivational barriers, and 5) staff resistance/frustration. Conversely, several positive themes related to supports for CCBT also emerged, including: 1) readiness to change/symptom severity, 2) program supports and incentives, 3) clinician support, 4) components of the intervention, and 5) individual patient characteristics

Spectro-ViT: A Vision Transformer Model for GABA-edited MRS Reconstruction Using Spectrograms

Purpose: To investigate the use of a Vision Transformer (ViT) to reconstruct/denoise GABA-edited magnetic resonance spectroscopy (MRS) from a quarter of the typically acquired number of transients using spectrograms. Theory and Methods: A quarter of the typically acquired number of transients collected in GABA-edited MRS scans are pre-processed and converted to a spectrogram image representation using the Short-Time Fourier Transform (STFT). The image representation of the data allows the adaptation of a pre-trained ViT for reconstructing GABA-edited MRS spectra (Spectro-ViT). The Spectro-ViT is fine-tuned and then tested using \textit{in vivo} GABA-edited MRS data. The Spectro-ViT performance is compared against other models in the literature using spectral quality metrics and estimated metabolite concentration values. Results: The Spectro-ViT model significantly outperformed all other models in four out of five quantitative metrics (mean squared error, shape score, GABA+/water fit error, and full width at half maximum). The metabolite concentrations estimated (GABA+/water, GABA+/Cr, and Glx/water) were consistent with the metabolite concentrations estimated using typical GABA-edited MRS scans reconstructed with the full amount of typically collected transients. Conclusion: The proposed Spectro-ViT model achieved state-of-the-art results in reconstructing GABA-edited MRS, and the results indicate these scans could be up to four times faster

GABA levels in left and right sensorimotor cortex correlate across individuals

Differences in -aminobutyric acid (GABA) levels measured with Magnetic Resonance Spectroscopy have been shown to correlate with behavioral performance over a number of tasks and cortical regions. These correlations appear to be regionally and functionally specific. In this study, we test the hypothesis that GABA levels will be correlated within individuals for functionally related regions—the left and right sensorimotor cortex. In addition, we investigate whether this is driven by bulk tissue composition. GABA measurements using edited MRS data were acquired from the left and right sensorimotor cortex in 24 participants. T1-weighted MR images were also acquired and segmented to determine the tissue composition of the voxel. GABA level is shown to correlate significantly between the left and right regions (r = 0.64, p < 0.03). Tissue composition is highly correlated between sides, but does not explain significant variance in the bilateral correlation. In conclusion, individual differences in GABA level, which have previously been described as functionally and regionally specific, are correlated between homologous sensorimotor regions. This correlation is not driven by bulk differences in voxel tissue composition

Examining the Relationship Between Trait Energy and Fatigue and Feelings of Depression in Young Healthy Adults

Depression is usually co-morbid with fatigue. However, we are unaware of studies exploring the relationship between trait energy and fatigue and feelings of depression. Recent evidence suggests that energy and fatigue are two distinct moods. PURPOSE: To examine the association between trait mental and physical energy and fatigue and feelings of depression, within an otherwise healthy young adult cohort. METHODS: Using a cross-sectional design, healthy respondents (n=495) completed a series of self-reported surveys measuring depression, lifestyle factors (sleep, diet, physical activity), and trait mental and physical energy and fatigue. Using a step-wise regression, we controlled for demographics and lifestyle and added trait mental and physical energy and fatigue to the second model. RESULTS: When trait mental and physical energy and fatigue were added to the models, the adjusted R2 increased by 5% (R2 = .112, F(13, 457) = 4.455, p \u3c .001). In our second model, trait mental fatigue was the only significant predictor of depressive mood states (Β = .159, t (457) = 2.512, p = 0.01). CONCLUSION: Young adults, who struggle with high mental fatigue, may also be more likely to report feeling depressed suggesting that fatigue and depression are co-morbid, while low energy and depression are not. Future research should aim to identify epigenetic/genetic factors that influence mental fatigue and how those may be associated with feelings of depression