Recruitment challenges in MRI studies of acute intracerebral haemorrhage: experience from the TICH-2 MRI substudy

BACKGROUND AND AIMS Magnetic Resonance Imaging (MRI) is widely used in clinical practice and in trials for ischaemic stroke; however, relatively few large multicentre trials for intracerebral haemorrhage have used MRI. We describe the main recruitment challenges faced in the TICH-2 MRI substudy, which is nested within TICH-2, a multi-centre randomised placebo-controlled trial of tranexamic acid in intracerebral haemorrhage (ISRCTN93732214). METHOD TICH-2 participants at recruiting centres were eligible for the substudy. Centres were asked to record, if applicable, the reason for non-recruitment. The recruitment window was day 2 to day 14 post-randomisation. RESULTS Figure 1 shows the distribution of reasons for non-recruitment (N=169). Clinical instability was the main reason for non-recruitment, accounting for 34.3% of the cases. The mean NIHSS scores (as per TICH-2 protocol) for unrecruited patients classified as clinically unstable were 19 (range 5-32,N=57), 21 (range 0-40,N=51) and 20 (range 1-38,N=37) for baseline, day 2 and day 7 post-randomisation, respectively. In contrast, for recruited patients (N=142) the mean scores were 10 (range 0-28,N=141), 8 (range 0-26,N=139) and 8 (range 0-31,N=132). Other important factors for non-recruitment include difficulty obtaining consent, patient refusal, claustrophobia and transfer to other hospitals. CONCLUSION Clinical instability in intracerebral haemorrhage poses a challenge for recruitment into MRI studies. This, and other factors, should be taken into consideration when designing clinical trials of intracerebral haemorrhage involving MRI

A robust similarity measure for volumetric image registration with outliers

Image registration under challenging realistic conditions is a very important area of research. In this paper, we focus on algorithms that seek to densely align two volumetric images according to a global similarity measure. Despite intensive research in this area, there is still a need for similarity measures that are robust to outliers common to many different types of images. For example, medical image data is often corrupted by intensity inhomogeneities and may contain outliers in the form of pathologies. In this paper we propose a global similarity measure that is robust to both intensity inhomogeneities and outliers without requiring prior knowledge of the type of outliers. We combine the normalised gradients of images with the cosine function and show that it is theoretically robust against a very general class of outliers. Experimentally, we verify the robustness of our measures within two distinct algorithms. Firstly, we embed our similarity measures within a proof-of-concept extension of the Lucas–Kanade algorithm for volumetric data. Finally, we embed our measures within a popular non-rigid alignment framework based on free-form deformations and show it to be robust against both simulated tumours and intensity inhomogeneities

Quantitative CT radiomics-based models for prediction of haematoma expansion and poor functional outcome in primary intracerebral haemorrhage

Objectives: To test radiomics-based features extracted from noncontrast CT of patients with spontaneous intracerebral haemorrhage for prediction of haematoma expansion and poor functional outcome and compare them with radiological signs and clinical factors.Materials and methods: Seven hundred fifty-four radiomics-based features were extracted from 1732 scans derived from the TICH-2 multicentre clinical trial. Features were harmonised and a correlation-based feature selection was applied. Different elastic-net parameterisations were tested to assess the predictive performance of the selected radiomics-based features using grid optimisation. For comparison, the same procedure was run using radiological signs and clinical factors separately. Models trained with radiomics-based features combined with radiological signs or clinical factors were tested. Predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC) score.Results: The optimal radiomics-based model showed an AUC of 0.693 for haematoma expansion and an AUC of 0.783 for poor functional outcome. Models with radiological signs alone yielded substantial reductions in sensitivity. Combining radiomics-based features and radiological signs did not provide any improvement over radiomics-based features alone. Models with clinical factors had similar performance compared to using radiomics-based features, albeit with low sensitivity for haematoma expansion. Performance of radiomics-based features was boosted by incorporating clinical factors, with time from onset to scan and age being the most important contributors for haematoma expansion and poor functional outcome prediction, respectively.Conclusion: Radiomics-based features perform better than radiological signs and similarly to clinical factors on the prediction of haematoma expansion and poor functional outcome. Moreover, combining radiomics-based features with clinical factors improves their performance.Key points: Linear models based on CT radiomics-based features perform better than radiological signs on the prediction of haematoma expansion and poor functional outcome in the context of intracerebral haemorrhage. Linear models based on CT radiomics-based features perform similarly to clinical factors known to be good predictors. However, combining these clinical factors with radiomics-based features increases their predictive performance

Automated segmentation of haematoma and perihaematomal oedema in MRI of acute spontaneous intracerebral haemorrhage

BackgroundSpontaneous intracerebral haemorrhage (SICH) is a common condition with high morbidity and mortality. Segmentation of haematoma and perihaematoma oedema on medical images provides quantitative outcome measures for clinical trials and may provide important markers of prognosis in people with SICH.MethodsWe take advantage of improved contrast seen on magnetic resonance (MR) images of patients with acute and early subacute SICH and introduce an automated algorithm for haematoma and oedema segmentation from these images. To our knowledge, there is no previously proposed segmentation technique for SICH that utilises MR images directly. The method is based on shape and intensity analysis for haematoma segmentation and voxel-wise dynamic thresholding of hyper-intensities for oedema segmentation.ResultsUsing Dice scores to measure segmentation overlaps between labellings yielded by the proposed algorithm and five different expert raters on 18 patients, we observe that our technique achieves overlap scores that are very similar to those obtained by pairwise expert rater comparison. A further comparison between the proposed method and a state-of-the-art Deep Learning segmentation on a separate set of 32 manually annotated subjects confirms the proposed method can achieve comparable results with very mild computational burden and in a completely training-free and unsupervised way.ConclusionOur technique can be a computationally light and effective way to automatically delineate haematoma and oedema extent directly from MR images. Thus, with increasing use of MR images clinically after intracerebral haemorrhage this technique has the potential to inform clinical practice in the future

Multiparametric cerebellar imaging and clinical phenotype in childhood ataxia telangiectasia

BackgroundAtaxia Telangiectasia (A-T) is an inherited multisystem disorder with cerebellar neurodegeneration. The relationships between imaging metrics of cerebellar health and neurological function across childhood in A-T are unknown, but may be important for determining timing and impact of therapeutic interventions.PurposeTo test the hypothesis that abnormalities of cerebellar structure, physiology and cellular health occur in childhood A-T and correlate with neurological disability, we performed multiparametric cerebellar MRI and establish associations with disease status in childhood A-T.MethodsProspective cross-sectional observational study. 22 young people (9 females / 13 males, age 6.6-17.8 years) with A-T and 24 matched healthy controls underwent 3-Tesla MRI with volumetric, diffusion and proton spectroscopic acquisitions. Participants with A-T underwent structured neurological assessment, and expression / activity of ataxia-telangiectasia mutated (ATM) kinase were recorded.ResultsAtaxia-telangiectasia participants had cerebellar volume loss (fractional total cerebellar volume: 5.3% vs 8.7%, P less than 0.0005, fractional 4th ventricular volumes: 0.19% vs 0.13%, P less than 0.0005), that progressed with age (fractional cerebellar volumes, r=-0.66, P=0.001), different from the control group (t=-4.88, P less than 0.0005). The relationship between cerebellar volume and age was similar for A-T participants with absent ATM kinase production and those producing non-functioning ATM kinase. Markers of cerebellar white matter injury were elevated in ataxia-telangiectasia vs controls (apparent diffusion coefficient: 0.89×10−3mm2s−1 vs 0.69×10−3mm2s−1, p less than 0.0005) and correlated (age-corrected) with neurometabolite ratios indicating impaired neuronal viability (N-acetylaspartate:creatine r=-0.70, P less than 0.001); gliosis (inositol:creatine r=0.50, P=0.018; combined glutamine/glutamate:creatine r=-0.55, P=0.008) and increased myelin turnover (choline:creatine r=0.68, P less than 0.001). Fractional 4th ventricular volume was the only variable retained in the regression model predicting neurological function (adjusted r2=0.29, P=0.015).ConclusionsQuantitative MRI demonstrates cerebellar abnormalities in children with A-T, providing non-invasive measures of progressive cerebellar injury and markers reflecting neurological status. These MRI metrics may be of value in determining timing and impact of interventions aimed at altering the natural history of A-T

Connectivity-guided intermittent theta burst versus repetitive transcranial magnetic stimulation for treatment-resistant depression: a randomized controlled trial

Disruption in reciprocal connectivity between the right anterior insula and the left dorsolateral prefrontal cortex is associated with depression and may be a target for neuromodulation. In a five-center, parallel, double-blind, randomized controlled trial we personalized resting-state functional magnetic resonance imaging neuronavigated connectivity-guided intermittent theta burst stimulation (cgiTBS) at a site based on effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. We tested its efficacy in reducing the primary outcome depression symptoms measured by the GRID Hamilton Depression Rating Scale 17-item over 8, 16 and 26 weeks, compared with structural magnetic resonance imaging (MRI) neuronavigated repetitive transcranial magnetic stimulation (rTMS) delivered at the standard stimulation site (F3) in patients with ‘treatment-resistant depression’. Participants were randomly assigned to 20 sessions over 4–6 weeks of either cgiTBS (n = 128) or rTMS (n = 127) with resting-state functional MRI at baseline and 16 weeks. Persistent decreases in depressive symptoms were seen over 26 weeks, with no differences between arms on the primary outcome GRID Hamilton Depression Rating Scale 17-item score (intention-to-treat adjusted mean, −0.31, 95% confidence interval (CI) −1.87, 1.24, P = 0.689). Two serious adverse events were possibly related to TMS (mania and psychosis). MRI-neuronavigated cgiTBS and rTMS were equally effective in patients with treatment-resistant depression over 26 weeks (trial registration no. ISRCTN19674644)

Connectivity guided theta burst transcranial magnetic stimulation versus repetitive transcranial magnetic stimulation for treatment-resistant moderate to severe depression: study protocol for a randomised double-blind controlled trial (BRIGhTMIND)

Introduction The BRIGhTMIND study aims to determine the clinical effectiveness, cost effectiveness and mechanism of action of connectivity guided intermittent Theta Burst Stimulation (cgiTBS) versus standard repetitive Transcranial Magnetic Stimulation (rTMS) in adults with moderate to severe treatment resistant depression. Methods and analysis The study is a randomised double-blind controlled trial with 1:1 allocation to either 20 sessions of (a) cgiTBS or (b) neuronavigated rTMS not using connectivity guidance. A total of 368 eligible participants with a diagnosis of current unipolar major depressive disorder that is both treatment resistant (defined as scoring 2 or more on the Massachusetts General Hospital (MGH) Staging Score) and moderate to severe (scoring >16 on the 17-item Hamilton Depression Rating Scale (HDRS-17)), will be recruited from primary and secondary care settings at four treatment centres in the United Kingdom. The primary outcome is depression response at 16 weeks (50% or greater reduction in HDRS-17 score from baseline). Secondary outcomes include assessments of self-rated depression, anxiety, psychosocial functioning, cognition and quality of life at 8, 16 and 26 weeks post randomisation. Cost effectiveness, patient acceptability, safety, mechanism of action and predictors of response will also be examined

Connectivity-Guided Theta Burst Transcranial Magnetic Stimulation Versus Repetitive Transcranial Magnetic Stimulation for Treatment-Resistant Moderate to Severe Depression: Magnetic Resonance Imaging Protocol and SARS-CoV-2–Induced Changes for a Randomized Double-blind Controlled Trial

Background:Depression is a significant health and economic burden. In approximately one third of patients, depression is resistant to first line treatments and therefore it is essential that alternative treatments are found. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the UK and the US in treatment resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness and mechanism of action between standard treatment repetitive TMS (rTMS) targeted at the F3 EEG site, with a newer treatment – a type of TMS called theta-burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines the brain imaging acquisition and analysis for the BRIGhTMIND trial that is used to create personalised TMS targets and answer the proposed mechanistic hypotheses.Objective:The objectives of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and cgiTBS and to identify imaging-based markers predicting response to treatment.Methods:The study is a randomised double-blind controlled trial with 1:1 allocation to either 20 sessions of a) TBS or b) standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired per participant at baseline (prior to TMS treatment) with T1-weighted and task-free functional MRI during rest (rsfMRI) utilised to estimate TMS targets. For participants enrolled in the mechanistic substudy additional diffusion-weighted, sequences are acquired at baseline and at post-treatment follow-up 16 weeks after treatment randomisation. Core datasets of T1-weighted and task-free functional MRI during rest (rsfMRI) are acquired for all participants and utilised to estimate TMS targets. Additional sequences of arterial spin labelling, magnetic resonance spectroscopy and diffusion-weighted images are acquired dependent on recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex whilst TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from a level of MRI-guidance but only TBS is provided with precision targeting based on functional brain connectivity.Results:Recruitment began January 2019 and is ongoing. Data collection is expected to continue until January 2023.Conclusions:This trial will determine the impact of precision MRI guidance on rTMS treatment, and furthermore, assess the neural mechanisms underlying this treatment in treatment resistant depressed patients. Clinical Trial: International Standard Randomized Controlled Trial Number (ISRCTN) 19674644; https://www.isrctn.com/ISRCTN19674644. Registered 2nd October 2018

Fast and robust methods for non-rigid registration of medical images

The automated analysis of medical images plays an increasingly significant part in many clinical applications. Image registration is an important and widely used technique in this context. Examples of its use include, but are not limited to: longitudinal studies, atlas construction, statistical analysis of populations and automatic or semi-automatic parcellation of structures. Although image registration has been subject of active research since the 1990s, it is a challenging topic with many issues that remain to be solved. This thesis seeks to address some of the open challenges of image registration by proposing fast and robust methods based on the widely utilised and well established registration framework of B-spline Free-Form Deformations (FFD). In this work, a statistical method has been incorporated into the FFD model, in order to obtain a fast learning-based method that produces results that are in accordance with the underlying variability of the population under study. Several comparisons between different statistical analysis methods that can be used in this context are performed. Secondly, a method to improve the convergence of the B-Spline FFD method by learning a gradient projection using principal component analysis and linear regression is proposed. Furthermore, a robust similarity measure is proposed that enables the registration of images affected by intensity inhomogeneities and images with pathologies, e.g. lesions and/or tumours. All the methods presented in this thesis have been extensively evaluated using both synthetic data and large datasets of real clinical data, such as Magnetic Resonance (MR) images of the brain and heart.Open Acces