Not in my treatment center: Leadership's perception of barriers to MOUD adoption.

INTRODUCTION: Despite their well-established effectiveness, medications for opioid use disorder (MOUD) are widely underutilized across the United States. In the context of a large publicly funded behavioral health system, we examined the relationship between a range of implementation barriers and a substance use disorder treatment agency's level of adoption of MOUD. METHODS: We surveyed leadership of publicly funded substance use disorder treatment centers in Philadelphia about the significance of barriers to implementing MOUD related to their workforce, organization, funding, regulations, and beliefs about MOUD's efficacy and safety. We queried leaders on the percentage of their patients with opioid use disorder who receive MOUD and examined associations between implementation barriers and MOUD adoption. RESULTS: Ratings of regulatory, organizational, or funding barriers of respondents who led high MOUD adopting agencies (N = 20) were indistinguishable from those who led agencies that were low adopting of MOUD (N = 23). In contrast, agency leaders who denied MOUD-belief or workforce barriers were significantly more likely to lead high-MOUD-adopting organizations. CONCLUSIONS: These findings suggest that leadership beliefs about MOUD may be a key factor of the organizational decision to adopt and should be a target of implementation efforts to increase direct provision of these medications.

Integrated primary care behavioural health in a regional network of FQHC agencies during COVID-19.

Objectives: (1) Examine the ability to sustain integrated primary care behavioural health (eg, colocation, communication and coordination) in 40 community health centres, during the COVID-19 pandemic and (2) review adaptations and challenges to provide integrated behavioural health via telehealth. Methods and analysis: This qualitative investigation assessed 55 behavioural health consultants (BHCs), via semistructured interviews, spanning 40 practice sites and 10 organisations, on their adjustment to telehealth delivery, modified practice workflows and challenges of maintaining integration while displaced by the pandemic. Assessment of the level of integrated care was also conducted with available semistructured tools. Results: The results highlight rapid service adjustment, positive patient and provider satisfaction, increased but lowered ratings of remote BHC integration and collaboration with the primary care teams and reduced behavioural health screening, compared with prepandemic levels. This investigation also highlights the co-occurring importance of racial disparities and injustice in patient care. In several settings, BHCs had a significant support role for staff self-care. Conclusion: The COVID-19 pandemic, and its subsequent shelter-in-place mandates and telehealth care provision, has altered standard integrated behavioural health practice, yet harnessed the accessible, generalist and team-based spirit to meet the increasing behavioural health needs in this community.

Spatio-temporal activity in real time (STAR): optimization of regional fMRI feedback.

The use of real-time feedback has expanded fMRI from a brain probe to include potential brain interventions with significant therapeutic promise. However, whereas time-averaged blood oxygenation level-dependent (BOLD) signal measurement is usually sufficient for probing a brain state, the real-time (frame-to-frame) BOLD signal is noisy, compromising feedback accuracy. We have developed a new real-time processing technique (STAR) that combines noise-reduction properties of multi-voxel (e.g., whole-brain) techniques with the regional specificity critical for therapeutics. Nineteen subjects were given real-time feedback in a cognitive control task (imagining repetitive motor activity vs. spatial navigation), and were all able to control a visual feedback cursor based on whole-brain neural activity. The STAR technique was evaluated, retrospectively, for five a priori regions of interest in these data, and was shown to provide significantly better (frame-by-frame) classification accuracy than a regional BOLD technique. In addition to regional feedback signals, the output of the STAR technique includes spatio-temporal activity maps (movies) providing insight into brain dynamics. The STAR approach offers an appealing optimization for real-time fMRI applications requiring an anatomically-localized feedback signal.

Regionally distinct white matter lesions do not contribute to regional gray matter atrophy in patients with multiple sclerosis.

PURPOSE: To determine to what extent T1- and T2-regional lesion volumes (RLVs) contribute to total and/or regional gray matter (GM) atrophy in multiple sclerosis (MS). METHODS: We studied 110 (67 relapsing-remitting and 43 secondary-progressive) MS patients. SABRE program was used to parcel the brain into 13 regions per hemisphere. Total and regional GM fractions (GMFs) were determined in each region to correct for intraregional size variability. Partial correlations were used to determine associations (holding the converse constant) between RLVs, GMF, and regional GMFs (P < .001 to avoid Type 1 error). RESULTS: Partial correlations between RLVs and regional GMFs (controlling for total GMF) for the total MS group were not significant for any of the 26 regions for T2, whereas they were significant for two of the 26 regions for T1. Partial correlations between RLVs and total GMF (controlling for regional GMF) for the total MS group were significant in 9 of 26 regions for T2 (largest r = right lateral inferior frontal, -.45) and 5 of 26 regions for T1 (largest r = right inferior parietal, -.45). CONCLUSIONS: Results suggest a model whereby a distinct generalized disease process accounts for GM atrophy better than regionally distinct Wallerian degeneration.

Regional specificity of magnetization transfer imaging in multiple sclerosis.

BACKGROUND: The goal of this study was to develop and validate a method for generation of regional magnetization transfer ratio (MTR). We also studied the topography of MTR changes in multiple sclerosis (MS) and in normal controls (NC), and preliminarily examined the clinical usefulness of this method. METHODS: We examined 45 patients with MS (relapsing remitting [RR] = 28 and secondary progressive[SP] = 17] and 19 NC. Mean disease duration was 14.3 years and median Expanded Disability Status Scale was 3.0. Regions of the brain were determined using semiautomated brain region extraction (SABRE). Twenty-six regional masks were automatically applied to MTR maps that were further split into gray matter (GM) and white matter (WM)compartments. RESULTS: Mean MTR from 12 SABRE regions differed significantly between MS patients and NC. For WM, all regional mean MTRs differed significantly between RR, SP, and NC participants(P < .001). In regression analysis, only 3 regions remained significantly different when corrected for total T2-LV. The regression model predicting disability selected GM mean MTR of the right medial inferior frontal region (P = .031). CONCLUSIONS: The study results showed that this regional MTR approach is reproducible, reliable and clinically relevant. MTI changes occur selectively in specific sub-regions.

Reproducibility and accuracy of quantitative magnetic resonance imaging techniques of whole-brain atrophy measurement in multiple sclerosis.

BACKGROUND AND PURPOSE: Whole-brain atrophy is of growing interest as an outcome measure in multiple sclerosis (MS) clinical trials. The authors compared the reproducibility and accuracy of 3 quantitative techniques of measurement in patients with MS. METHODS: Thirty-four patients with relapsing-remitting MS (median Expanded Disability Status Scale disability score = 1.5) were studied. Brain parenchymal fraction (BPF) was quantified on spin-echo 2-dimensional T1-weighted axial 5-mm slice thickness sequences by semiautomated (Buffalo, Trieste) or automated (SIENAX) algorithms. RESULTS: Mean +/- SD BPFs were 0.830 +/- 0.04 with Buffalo, 0.824 +/- 0.04 with Trieste, and 0.826 +/- 0.04 with SIENAX methods (P = nonsignificant [NS]). Mean BPF scan-rescan coefficient of variation (COV) was 0.41% for Buffalo, 0.44% for Trieste, and 0.32% for SIENAX (P =NS).The semiautomated methods showed higher accuracy than the automated method in brain extraction (masking; P = .001). The errors of skull stripping included scalp, skull bone marrow, inferior parts of temporal lobes anterior to the brain stem, face structures, sagittal sinuses, eyes, and optic nerves. Buffalo (r = -0.37, P = .034) and Trieste (r = -.36, P = .039) BPFs showed stronger cor relation with disability than SIENAX (r = -0.16, P = .219). These differences were statistically significant (P = .0031 for Buffalo and P = .0037 for Trieste BPF). CONCLUSIONS: This study showed a high reproducibility of both semiautomated and automated methods for brain atrophy measurement. The semiautomated methods showed higher accuracy than the automated SIENAX method did in the evaluation of brain extraction, especially in infratentorial and cortical regions, where operator interaction during the masking processes was essential.

Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden.

BACKGROUND: Cognition and magnetic resonance imaging correlations are well established in patients with multiple sclerosis (MS), but it is unclear whether lesion burden or atrophy accounts for most of the predictive variance. These indices have been directly compared in only a few studies. No such study included measurement of the third ventricle, which was strongly predictive of neuropsychological competence in the early literature. Furthermore, few studies accounted for the influence of age, premorbid intelligence, or depression. OBJECTIVE: To determine if conventional measures of lesion burden or atrophy predict cognitive dysfunction in MS while accounting for age, premorbid intelligence, and depression. METHODS: We studied 37 patients with MS and 27 controls matched according to demographic variables. Correlations between neuropsychological tests and the following magnetic resonance imaging indices were considered: T1 hypointense lesion volume, fluid-attenuated inversion recovery hyperintense lesion volume, third ventricle width, bicaudate ratio, and brain parenchymal fraction. Regression models predicting neuropsychological performance controlled for the effects of age, premorbid intelligence, and depression. We included only those tests discriminating patients with MS from controls. RESULTS: In each regression model, third ventricle width was the sole magnetic resonance imaging measure retained. When this variable was removed from consideration, brain parenchymal fraction was retained in all analyses. CONCLUSIONS: Brain atrophy accounts for more variance than lesion burden in predicting cognitive impairment in MS, and central atrophy in particular is strongly associated with neuropsychological morbidity. This finding may be explained in part by atrophy of the thalamus, a deep gray matter structure that mediates cognitive function via cortical and subcortical pathways. Enthusiasm for the clinical utility of third ventricle width is tempered by modest intraobserver and interobserver reliability.

Selective caudate atrophy in multiple sclerosis: a 3D MRI parcellation study.

Deep gray matter damage may be an important component of the multiple sclerosis (MS) disease process. We tested whether caudate atrophy occurs in MS, and whether it correlates with conventional MRI or clinical markers of disease progression. Caudate nuclei of 24 MS patients and 10 age-matched healthy controls were traced, normalized, reconstructed and visualized from MRI scans. Normalized bicaudate volume was 19% lower in MS controls ( p< 0.001), an effect that persisted after adjusting for whole-brain atrophy ( p< 0.008). Caudate volume did not correlate with disease duration, physical disability score, whole-brain atrophy, or total T2 hyperintense or T1 hypointense lesion load (all p > 0.05). We conclude that selective caudate atrophy is associated with MS and may occur through direct mechanisms.

A semiautomated measure of whole-brain atrophy in multiple sclerosis.

Brain atrophy is a proposed MRI marker of irreversible pathologic damage in multiple sclerosis (MS). The brain parenchymal fraction (BPF) is the ratio of brain parenchymal volume to the total volume within the surface contour. We developed a semiautomated measure of BPF using commercially available edge-finding and thresholding software (30-min analysis time per patient). We measured BPF in 78 patients with MS and 17 healthy controls. BPF was lower in a cohort of patients with MS (n=50) (0.843+/-0.042, range 0.743-0.906) age-matched to controls (0.877+/-0.020, range 0.835-0.901) (p<0.001). BPF correlated inversely with third ventricular width (r=-0.785, p<0.001), and total T1 hypointense lesion volume (r=-0.347, p=0.011), but not with total T2 hyperintense lesion volume (r=-0.213, p=0.13). BPF correlated negatively with expanded disability status scale (EDSS) score (r=-0.391, p=0.0006) and disease duration (r=-0.281, p=0.01). Stepwise regression compared the relative abilities of MRI variables to predict clinical data. By regression of age, BPF, third ventricular width, T2 lesions, and T1 lesions, BPF was the best predictor of disability score (R(2)=0.204, p<0.001). Third ventricular width was the best predictor of disease duration (R(2)=0.316, p<0.001). None of the MRI variables differed between relapsing-remitting (RR) (n=60) and secondary progressive (SP) (n=18) disease course (p>0.05). The intrarater, interrater, and scan-rescan BPF variability (COV) was 0.31%, 0.34%, and 0.41% and the accuracy against a phantom was 99.1%. We conclude that whole-brain atrophy in MS can be reliably and readily quantified by a semiautomated approach. Longitudinal studies are warranted to determine if this method provides a sensitive biologic marker of the MS disease process.

T2 hypointensity in the deep gray matter of patients with multiple sclerosis: a quantitative magnetic resonance imaging study.

CONTEXT: While gray matter T2 hypointensity in multiple sclerosis (MS) has been associated with physical disability and clinical course, previous studies have relied on visual magnetic resonance imaging (MRI) assessments. OBJECTIVE: To quantitatively determine if T2 hypointensity is associated with conventional MRI and clinical findings in MS. DESIGN: Case-control study. SETTING: University-affiliated community-based hospital. SUBJECTS: Sixty patients with MS and 50 controls. MAIN OUTCOME MEASURES: T2 intensities of the substantia nigra, red nucleus, thalamus, putamen, globus pallidus, and caudate; third ventricular width; total brain T1 (hypointense) and T2 (hyperintense) lesion volumes; Expanded Disability Status Scale (physical disability) score; and disease course. RESULTS: Deep gray matter T2 hypointensity was present in patients with MS in all structures (P<.005) except for the substantia nigra. T2 hypointensity was associated with third ventricle enlargement and higher T2 but not T1 plaque load. The regression model predicting third ventricle width included caudate T2 hypointensity (P =.006). The model predicting T2 lesion load included globus pallidus T2 hypointensity (P =.001). Caudate T2 hypointensity was the only variable associated with disability score in regression modeling (P =.03). All T2 hypointensities differentiated the secondary progressive from the relapsing-remitting clinical courses. The final model (P<.001) predicting clinical course retained T2 hypointensity of the thalamus, caudate, and putamen but not MRI plaques or atrophy. CONCLUSIONS: Gray matter T2 hypointensity in MS is associated with brain atrophy and is a stronger predictor of disability and clinical course than are conventional MRI findings. While longitudinal studies are warranted, these results suggest that pathologic iron deposition is a surrogate marker of the destructive disease process.