Real-world persistence of multiple sclerosis disease-modifying therapies.

BACKGROUND AND PURPOSE: Treatment persistence is the continuation of therapy over time. It reflects a combination of treatment efficacy and tolerability. We aimed to describe real-world rates of persistence on disease-modifying therapies (DMTs) for people with multiple sclerosis (pwMS) and reasons for DMT discontinuation. METHODS: Treatment data on 4366 consecutive people with relapse-onset multiple sclerosis (MS) were pooled from 13 UK specialist centres during 2021. Inclusion criteria were exposure to at least one MS DMT and a complete history of DMT prescribing. PwMS in blinded clinical trials were excluded. Data collected included sex, age at MS onset, age at DMT initiation, DMT treatment dates, and reasons for stopping or switching DMT. For pwMS who had received immune reconstituting therapies (cladribine/alemtuzumab), discontinuation date was defined as starting an alternative DMT. Kaplan-Meier survival analyses were used to express DMT persistence. RESULTS: In 6997 treatment events (1.6 per person with MS), median time spent on any single maintenance DMT was 4.3 years (95% confidence interval = 4.1-4.5 years). The commonest overall reasons for DMT discontinuation were adverse events (35.0%) and lack of efficacy (30.3%). After 10 years, 20% of people treated with alemtuzumab had received another subsequent DMT, compared to 82% of people treated with interferon or glatiramer acetate. CONCLUSIONS: Immune reconstituting DMTs may have the highest potential to offer a single treatment for relapsing MS. Comparative data on DMT persistence and reasons for discontinuation are valuable to inform treatment decisions and in personalizing treatment in MS.

Microbial Control Agents for Fungus Gnats (Diptera: Sciaridae: Lycoriella) Affecting the Production of Oyster Mushrooms, Pleurotus spp.

Infestations of fungus gnats (Diptera: Sciaridae) can reduce the production of oyster mushrooms (Pleurotus spp.) grown as food crops within controlled environments. The objectives of this study were to assess the efficacy of Bacillus thuringiensis var. israelensis (Bti) and Steinernema feltiae against fungus gnat larvae. A bioassay was developed, whereby pasteurized straw was inoculated with Pleurotus columbinus and treated with Bti (Gnatrol®), S. feltiae (Nemashield®), or water. Fungus gnats (Lycoriella sp.) were released into each bioassay container for ovipositing onto the straw, thereby exposing the F1 larvae to treated or untreated substrate. Sticky cards within the containers entrapped fungus gnats emerging from the substrate as an indicator of larval survivorship. Following three bioassays, fewer fungus gnats emerged from straw treated with Bti compared to S. feltiae and the water control. Three additional bioassays using Pleurotus ostreatus also demonstrated that fewer fungus gnats emerged from straw treated with Bti compared to S. feltiae and the untreated control. Steinernema feltiae was generally ineffective. Monitoring substrate weight in the bioassay containers over time indicated that Bti and S. feltiae did not impede colonization by P. ostreatus. Incorporating Bti into straw substrate is a promising approach for managing fungus gnats infesting Pleurotus spp.

Aberrant white matter microstructure in treatment-resistant schizophrenia✰.

Treatment response in schizophrenia divides into three subcategories: treatment-responsive (first-line responders; FLR), treatment-resistant (TRS), and ultra-treatment-resistant schizophrenia (UTRS). White matter abnormalities could drive antipsychotic resistance but little work has investigated differences between TRS and UTRS. The current study aimed to establish whether differences in white matter structure are present across both treatment-resistant subtypes or if UTRS is distinct from TRS. Diffusion-weighted images were acquired for 18 individuals with TRS, 14 with UTRS, 18 FLR and 20 healthy controls. Measures of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) were obtained using tract-based spatial statistics. Analysis of variance and post-hoc t-tests were conducted for each measure. Those with TRS had lower FA than healthy controls in superior longitudinal fasciculus, corpus callosum, thalamic radiation, corticospinal tract, internal capsule, corona radiata and fronto-occipital fasciculus (p<.05 FWE-corrected). Lower FA was also observed in TRS compared with UTRS in the superior longitudinal fasciculus (p<.05 FWE-corrected). No post-hoc tests survived corrections for multiple comparisons and no differences in MD, AD or RD were observed. These data suggest that microstructural deficits in white matter could contribute to TRS but suggest that other mechanisms may be more relevant for UTRS.

Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia.

Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.

Does cognitive impairment in treatment-resistant and ultra-treatment-resistant schizophrenia differ from that in treatment responders?

This study aimed to investigate whether cognitive impairment is more pronounced in people with treatment-resistant schizophrenia compared with those who respond well to first-line antipsychotic medication. Fifty-one patients with schizophrenia were assigned to one of three groups dependent on their clinical history: (i) 16 people who had responded well to first-line antipsychotic medication, (ii) 20 people who were treatment-resistant but responding to clozapine monotherapy, (iii) 15 people who were ultra-treatment-resistant/clozapine-resistant but responding to antipsychotic polypharmacy. Twenty-two controls were also recruited. Groups were matched for age, sex, disease duration and psychopathology. All participants undertook a computerised battery of neuropsychological tests that assessed multiple cognitive domains. Raw data were converted to z-scores, and test performance was compared between groups. People with schizophrenia performed significantly worse than controls in the majority of neuropsychological tests, with verbal memory, sustained attention, and sensorimotor the most commonly impaired domains. No significant differences in performance between people deemed to be treatment-resistant or ultra-treatment-resistant, and those who responded well to first-line antipsychotic medication were observed. There was no significant relationship between antipsychotic dose and scores on any of the neuropsychological tests. Cognitive impairment is a central feature of schizophrenia, but our results suggest that treatment-resistance may not be associated with more severe deficits.

Extensive gray matter volume reduction in treatment-resistant schizophrenia.

BACKGROUND: Approximately one-third of people with schizophrenia are treatment-resistant and some do not achieve remission with clozapine, the gold-standard antipsychotic medication for treatment-resistant schizophrenia. This study compared global and regional brain volumes between treatment-respondent and treatment-resistant patients with schizophrenia, including a group of patients who were clozapine-resistant. METHODS: T1-weighted brain MRIs were obtained on a 3T scanner in 20 controls and 52 people with schizophrenia who were selected based on their symptomatic responses to antipsychotic medication: 18 responded well to first-line atypical antipsychotics (FLR), 19 were treatment-resistant but responsive to clozapine monotherapy (TR), and 15 were ultra-treatment-resistant and did not respond to clozapine (UTR). Treatment groups were matched for disease duration and current psychopathology. SIENAX and FSL-VBM were used to investigate differences in the global brain, gray matter (GM), white matter, ventricular cerebrospinal fluid volumes, and regional GM volumes. RESULTS: GM volume was significantly reduced in the TR and UTR groups compared with controls and the FLR group (p < 0.05). GM volume was significantly reduced in TR patients compared with FLRs in the superior, middle, and inferior temporal gyri, pre- and post-central gyri, middle and superior frontal gyri, right supramarginal gyrus, and right lateral occipital cortex. UTR patients showed reduced GM compared with FLRs in their right parietal operculum and left cerebellum. No significant volume differences were observed between TR and UTR groups. CONCLUSIONS: These differences are unlikely to be solely due to medication effects, and reduced GM volume in treatment-resistant schizophrenia may represent an accelerated disease course or a different underlying pathology.

ADvanced IMage Algebra (ADIMA): a novel method for depicting multiple sclerosis lesion heterogeneity, as demonstrated by quantitative MRI.

BACKGROUND: There are modest correlations between multiple sclerosis (MS) disability and white matter lesion (WML) volumes, as measured by T2-weighted (T2w) magnetic resonance imaging (MRI) scans (T2-WML). This may partly reflect pathological heterogeneity in WMLs, which is not apparent on T2w scans. OBJECTIVE: To determine if ADvanced IMage Algebra (ADIMA), a novel MRI post-processing method, can reveal WML heterogeneity from proton-density weighted (PDw) and T2w images. METHODS: We obtained conventional PDw and T2w images from 10 patients with relapsing-remitting MS (RRMS) and ADIMA images were calculated from these. We classified all WML into bright (ADIMA-b) and dark (ADIMA-d) sub-regions, which were segmented. We obtained conventional T2-WML and T1-WML volumes for comparison, as well as the following quantitative magnetic resonance parameters: magnetisation transfer ratio (MTR), T1 and T2. Also, we assessed the reproducibility of the segmentation for ADIMA-b, ADIMA-d and T2-WML. RESULTS: Our study's ADIMA-derived volumes correlated with conventional lesion volumes (p < 0.05). ADIMA-b exhibited higher T1 and T2, and lower MTR than the T2-WML (p < 0.001). Despite the similarity in T1 values between ADIMA-b and T1-WML, these regions were only partly overlapping with each other. ADIMA-d exhibited quantitative characteristics similar to T2-WML; however, they were only partly overlapping. Mean intra- and inter-observer coefficients of variation for ADIMA-b, ADIMA-d and T2-WML volumes were all < 6 % and < 10 %, respectively. CONCLUSION: ADIMA enabled the simple classification of WML into two groups having different quantitative magnetic resonance properties, which can be reproducibly distinguished.

Gray matter atrophy rate as a marker of disease progression in AD.

Global gray matter (GM) atrophy rates were quantified from magnetic resonance imaging (MRI) over 6- and 12-month intervals in 37 patients with Alzheimer's disease (AD) and 19 controls using: (1) nonlinear registration and integration of Jacobian values, and (2) segmentation and subtraction of serial GM volumes. Sample sizes required to power treatment trials using global GM atrophy rate as an outcome measure were estimated and compared between the 2 techniques, and to global brain atrophy measures quantified using the boundary shift integral (brain boundary shift integral; BBSI) and structural image evaluation, using normalization, of atrophy (SIENA). Increased GM atrophy rates (approximately 2% per year) were observed in patients compared with controls. Although mean atrophy rates provided by Jacobian integration were smaller than those from segmentation and subtraction of GM volumes, measurement variance was reduced. The number of patients required per treatment arm to detect a 20% reduction in GM atrophy rate over a 12-month follow-up (90% power) was 202 (95% confidence interval [CI], 118-423) using Jacobian integration and 2047 (95% CI 271 to > 10,000) using segmentation and subtraction. Comparable sample sizes for whole brain atrophy were 240 (95% CI, 142-469) using the BBSI and 196 (95% CI, 110-425) using SIENA. Jacobian integration could be useful for measuring GM atrophy rate in Alzheimer's disease as a marker of disease progression and treatment efficacy.

Gray matter atrophy is related to long-term disability in multiple sclerosis.

OBJECTIVE: To determine the relation of gray matter (GM) and white matter (WM) brain volumes, and WM lesion load, with clinical outcomes 20 years after first presentation with clinically isolated syndrome suggestive of multiple sclerosis (MS). METHODS: Seventy-three patients were studied a mean of 20 years from first presentation with a clinically isolated syndrome (33 of whom developed relapsing-remitting MS and 11 secondary-progressive MS, with the rest experiencing no further definite neurological events), together with 25 healthy control subjects. GM and WM volumetric measures were obtained from three-dimensional T1-weighted brain magnetic resonance images using Statistical Parametric Mapping 2. RESULTS: Significant GM (p < 0.001) and WM atrophy (p = 0.001) was seen in MS patients compared with control subjects. There was significantly more GM, but not WM atrophy, in secondary-progressive MS versus relapsing-remitting MS (p = 0.003), and relapsing-remitting MS versus clinically isolated syndrome (p < 0.001). GM, but not WM, fraction correlated with expanded disability status scale (r(s) = -0.48; p < 0.001) and MS Functional Composite scores (r(s) = 0.59; p < 0.001). WM lesion load correlated with GM (r(s) = -0.63; p < 0.001), but not with WM fraction. Regression modeling indicated that the GM fraction explained more of the variability in clinical measures than did WM lesion load. INTERPRETATION: In MS patients with a relatively long and homogeneous disease duration, GM atrophy is more marked than WM atrophy, and reflects disease subtype and disability to a greater extent than WM atrophy or lesions.

Volumetric MRI and cognitive measures in Alzheimer disease : comparison of markers of progression.

BACKGROUND: Both cognitive tests and MRI-based measures have been suggested as outcomes in trials assessing disease-modifying therapies in Alzheimer's disease (AD). OBJECTIVE: To compare changes in longitudinal MRI measures with changes in performance on cognitive tests routinely used in AD clinical trials. METHOD: Fifty-two subjects from the placebo-arm of a clinical trial in mild-to-moderate AD had volumetric T(1)-weighted scans and cognitive tests including the Mini-Mental State Examination (MMSE), AD Assessment Scale-Cognitive Subscale, Disability Assessment for Dementia, AD Cooperative Study-Clinical Global Impression of Change and Clinical Dementia Rating at baseline and one-year later. Rates of brain atrophy and ventricular enlargement were measured using the boundary shift integral. Hippocampal (Hc) atrophy was calculated from manual volume measurements. The relationships between MRI and cognitive measures were investigated. RESULTS: Rates of brain atrophy and/or ventricular enlargement were correlated with declining performance on cognitive scales. The strongest association was between brain atrophy rate and MMSE decline (r = 0.59, p < 0.0001). Hc atrophy rate was not significantly correlated with any of the cognitive scales. CONCLUSION: The lack of correlation between Hc atrophy and cognitive scales may reflect a combination of: the extensive functional damage to the Hc by the time AD is clinically established, the greater influence of ongoing cortical degeneration, and errors in Hc outlining. The strong correlations between brain atrophy and ventricular enlargement, and cognitive scales probably reflect the correspondence between these measures of overall cerebral loss and global cognitive measures in the moderate stages of AD.

Detecting treatment effects on brain atrophy in relapsing remitting multiple sclerosis: sample size estimates.

Brain atrophy, thought to reflect neuroaxonal degeneration, may be considered an objective marker of disease progression in multiple sclerosis (MS). Our objective was to estimate sample sizes required for parallel group placebo-controlled trials of disease-modifying treatments in relapsing remitting MS (RRMS), using brain atrophy on MRI as the outcome measure. In addition, we investigated how brain atrophy measurement method and trial duration affect sample sizes. Thirty-three patients with RRMS and 16 controls had T1-weighted volumetric MR imaging acquired at baseline and up to six repeat time-points (six monthly intervals). Brain atrophy was quantified between baseline and each repeat image using four methods: segmented brain volume difference, BBSI, SIENA and ventricular enlargement. Linear mixed models were fitted to data from each subject group and method. Sample size calculations were performed using mean and variance estimates from these models. For a 2 year trial, a treatment slowing atrophy rate by 30% required 123 subjects in each treatment arm if using SIENA to measure atrophy, 157 for the BBSI, 140 for ventricular enlargement and 763 for segmented brain volume difference. For a given effect size and method, sample sizes were statistically significantly reduced the longer the trial duration. Our estimations suggest that brain atrophy could provide an additional outcome measure to clinical assessment for monitoring treatment effects in RRMS although the relationship between atrophy and subsequent disability, and potential confounding factors to atrophy measurement must be further investigated.

Cerebral atrophy measurement in clinically isolated syndromes and relapsing remitting multiple sclerosis: a comparison of registration-based methods.

BACKGROUND AND PURPOSE: Brain atrophy is a proposed marker of disease progression in multiple sclerosis (MS). Many magnetic resonance imaging-based methods of atrophy quantification exist, but their relative sensitivity and precision is unclear. Our aim was to compare atrophy rates from the brain boundary shift integral (BBSI), structural image evaluation, using normalization of atrophy (SIENA) (both registration-based methods) and segmented brain volume difference, in patients with clinically isolated syndromes (CIS), relapsing remitting MS (RRMS), and controls. METHODS: Thirty-seven CIS patients, 30 with early RRMS and 16 controls had T1-weighted volumetric imaging at baseline and 1 year. Brain atrophy rates were determined using segmented brain volume difference, BBSI, and SIENA. RESULTS: BBSI and SIENA were more precise than subtraction of segmented brain volumes and were more sensitive distinguishing RRMS subjects from controls. A strong correlation was observed between BBSI and SIENA. Atrophy rates were greater in CIS and RRMS subjects than controls (RRMS P < .001). With all methods, significantly greater atrophy rates were observed in CIS patients who developed clinically definite MS relative to subjects who did not. CONCLUSION: Registration-based techniques are more precise and sensitive than segmentation-based methods in measuring brain atrophy, with BBSI and SIENA providing comparable results.

Magnetic resonance imaging measures of brain atrophy in multiple sclerosis.

Magnetic resonance imaging (MRI) has been widely used to diagnose and monitor multiple sclerosis (MS). Although MRI-visible lesions are a key feature of MS, they are thought to correlate poorly with clinical progression. Neurodegeneration is increasingly being recognized as an important factor in the pathogenesis of MS, and MRI measures of brain atrophy have been suggested as surrogate markers of neuroaxonal loss and disease progression. This pathology may be more relevant to the progression of disability than focal inflammation. A number of MRI-based methods have been developed for the measurement of global and regional brain atrophy. Natural-history studies of MS and clinically isolated syndromes suggestive of MS have observed atrophy in these subjects above that seen in controls, over periods ranging from three months to years. Brain atrophy has also been incorporated as an outcome measure in therapeutic trials of disease-modifying treatments. This paper considers neuroaxonal loss and the pathological basis of brain atrophy, methods developed to quantify brain atrophy, the findings of natural-history and therapeutic studies, the relationship of brain atrophy to disability and cognition, and the future research directions and clinical applications of brain atrophy measurements.

Visual assessment of atrophy on magnetic resonance imaging in the diagnosis of pathologically confirmed young-onset dementias.

OBJECTIVES: To investigate the diagnostic accuracy of visual inspection of magnetic resonance imaging (MRI) in a range of pathologically confirmed diseases causing young-onset dementia and to assess the sensitivity and specificity of atrophy patterns for Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD). DESIGN: Sixty-two patients with pathologically confirmed diseases that may present as young-onset dementia were selected from a biopsy and postmortem series. The first diagnostic T1-weighted volumetric MRI was obtained for each patient, together with images from 22 healthy control subjects. All MRIs were assessed for regional atrophy independently by 3 neuroradiologists, blinded to all clinical details except age. Observers were also asked to use their clinical judgment to form a diagnosis. RESULTS: Eighty-seven percent of dementia cases were distinguished from controls after visual inspection of MRI, and a correct pathologically confirmed diagnosis was given in 58% of cases. Hippocampal atrophy was noted in 92% of AD cases but was commonly seen in other dementias and controls. A bilateral symmetrical pattern of hippocampal atrophy discriminated AD from FTLD with 47% specificity, while posterior greater than anterior gradient of atrophy was 92% specific for AD. Atrophy of the anterior, inferior, and lateral temporal lobes was suggestive of FTLD pathology (> or =90% sensitivity), while anterior greater than posterior gradient of atrophy and hemispheric asymmetry of atrophy were each at least 85% specific for FTLD. CONCLUSION: Despite variation and overlap of atrophy patterns, visual inspection of regional atrophy on MRI may aid in discriminating AD and FTLD.

Longitudinal patterns of regional change on volumetric MRI in frontotemporal lobar degeneration.

The aim of this study was to assess the longitudinal patterns of regional change in the different syndromic variants of frontotemporal lobar degeneration (FTLD). Ten patients with semantic dementia, 7 with progressive non-fluent aphasia and 29 with frontotemporal dementia had two serial volumetric MR scans. Fluid registration was used to match serial scans from each individual. Voxel-level analysis of change across subject groups was performed using statistical parametric mapping. The analysis showed patterns of increased rates of volume loss (atrophy) in frontal, temporal and parietal regions in the whole FTLD group compared with controls. The different FTLD syndromes displayed different patterns of change. This technique gives an insight into disease evolution over time in these disorders and may be useful as a method of tracking change in clinical trials.