Use of magnetic resonance imaging to predict outcome after stroke: a review of experimental and clinical evidence.
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ABSTRACT:
SUBMITTER: Farr TD
PROVIDER: S-EPMC2949172 | biostudies-other | 2010 Apr
REPOSITORIES: biostudies-other
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Project description:ImportancePredicting infarct size and location is important for decision-making and prognosis in patients with acute stroke.ObjectivesTo determine whether a deep learning model can predict final infarct lesions using magnetic resonance images (MRIs) acquired at initial presentation (baseline) and to compare the model with current clinical prediction methods.Design, setting, and participantsIn this multicenter prognostic study, a specific type of neural network for image segmentation (U-net) was trained, validated, and tested using patients from the Imaging Collaterals in Acute Stroke (iCAS) study from April 14, 2014, to April 15, 2018, and the Diffusion Weighted Imaging Evaluation for Understanding Stroke Evolution Study-2 (DEFUSE-2) study from July 14, 2008, to September 17, 2011 (reported in October 2012). Patients underwent baseline perfusion-weighted and diffusion-weighted imaging and MRI at 3 to 7 days after baseline. Patients were grouped into unknown, minimal, partial, and major reperfusion status based on 24-hour imaging results. Baseline images acquired at presentation were inputs, and the final true infarct lesion at 3 to 7 days was considered the ground truth for the model. The model calculated the probability of infarction for every voxel, which can be thresholded to produce a prediction. Data were analyzed from July 1, 2018, to March 7, 2019.Main outcomes and measuresArea under the curve, Dice score coefficient (DSC) (a metric from 0-1 indicating the extent of overlap between the prediction and the ground truth; a DSC of ≥0.5 represents significant overlap), and volume error. Current clinical methods were compared with model performance in subgroups of patients with minimal or major reperfusion.ResultsAmong the 182 patients included in the model (97 women [53.3%]; mean [SD] age, 65 [16] years), the deep learning model achieved a median area under the curve of 0.92 (interquartile range [IQR], 0.87-0.96), DSC of 0.53 (IQR, 0.31-0.68), and volume error of 9 (IQR, -14 to 29) mL. In subgroups with minimal (DSC, 0.58 [IQR, 0.31-0.67] vs 0.55 [IQR, 0.40-0.65]; P = .37) or major (DSC, 0.48 [IQR, 0.29-0.65] vs 0.45 [IQR, 0.15-0.54]; P = .002) reperfusion for which comparison with existing clinical methods was possible, the deep learning model had comparable or better performance.Conclusions and relevanceThe deep learning model appears to have successfully predicted infarct lesions from baseline imaging without reperfusion information and achieved comparable performance to existing clinical methods. Predicting the subacute infarct lesion may help clinicians prepare for decompression treatment and aid in patient selection for neuroprotective clinical trials.
| S-EPMC7068232 | biostudies-literature
Project description:The pattern of vascular remodelling in relation to recovery after stroke remains largely unclear. We used steady-state contrast-enhanced magnetic resonance imaging to assess the development of cerebral blood volume and microvascular density in perilesional and exofocal areas from (sub)acutely to chronically after transient stroke in rats. Microvascular density was verified histologically after infusion with Evans Blue dye. At day 1, microvascular cerebral blood volume and microvascular density were reduced in and around the ischemic lesion (intralesional borderzone: microvascular cerebral blood volume?=?72?±?8%; microvascular density?=?76?±?8%) (P?<?0.05), while total cerebral blood volume remained relatively unchanged. Perilesional microvascular cerebral blood volume and microvascular density subsequently normalized (day 7) and remained relatively stable (day 70). In remote ipsilateral areas in the thalamus and substantia nigra - not part of the ischemic lesion - microvascular density gradually increased between days 1 and 70 (thalamic ventral posterior nucleus: microvascular density?=?119?±?9%; substantia nigra: microvascular density?=?122?±?8% (P?<?0.05)), which was confirmed histologically. Our data indicate that initial microvascular collapse, with maintained collateral flow in larger vessels, is followed by dynamic revascularization in perilesional tissue. Furthermore, progressive neovascularization in non-ischemic connected areas may offset secondary neuronal degeneration and/or contribute to non-neuronal tissue remodelling. The complex spatiotemporal pattern of vascular remodelling, involving regions outside the lesion territory, may be a critical endogenous process to promote post-stroke brain reorganization.
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Project description:Simultaneous electroencephalography/functional magnetic resonance imaging (EEG/fMRI) recording can noninvasively map in the whole brain the hemodynamic response following an interictal epileptic discharge. EEG/fMRI is gaining interest as a presurgical evaluation tool. This study aims to determine how hemodynamic responses related to epileptic activity can help predict surgical outcome in patients considered for epilepsy surgery.Thirty-five consecutive patients with focal epilepsy who had significant hemodynamic responses and eventually surgical resection, were studied. The statistical map of hemodynamic responses were generated and co-registered to postoperative anatomic imaging. Patients were classified into four groups defined by the relative relationship between the location of the maximum hemodynamic response and the resection: group 1, fully concordant; group 2, partially concordant; group 3, partially discordant; and group 4, fully discordant. These findings were correlated with surgical outcome with at least 12-month follow-up.Ten patients in group 1 had the maximum t value (t-max) inside the resection; nine in group 2 had the t-max outside but close to the resection and the cluster with t-max overlapped the resection; five in group 3 had the t-max remote from resection, but with another less significant cluster in the resection; and 11 in group 4 had no response in the resection. The degree of concordance correlated largely with surgical outcome: a good surgical outcome (Engel's class I) was found in 7 of 10 patients of group 1, 4 of 9 of group 2, 3 of 5 of group 3, and only 1 of 11 of group 4. These results indicate that the partially concordant and partially discordant groups are best considered as inconclusive. In contrast, in the fully concordant and fully discordant groups, the sensitivity, specificity, positive predictive value, and negative predictive value were high, 87.5%, 76.9%, 70%, and 90.9%, respectively.This study demonstrates that hemodynamic responses related to epileptic activity can help delineate the epileptogenic region. Full concordance between maximum response and surgical resection is indicative of seizure freedom, whereas a resection leaving the maximum response intact is likely to lead to a poor outcome. EEG/fMRI is noninvasive but is limited to patients in whom interictal epileptic discharges can be recorded during the 60-90 min scan.
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Project description:Functional magnetic resonance imaging (fMRI) is a non-invasive technique that can be used to examine neural responses with and without the use of a functional task. Indeed, fMRI has been used in clinical trials and pharmacological research studies. In mental health, it has been used to identify brain areas linked to specific symptoms but also has the potential to help identify possible treatment targets. Despite fMRI's many advantages, such findings are rarely the primary outcome measure in clinical trials or research studies. This article reviews fMRI studies in depression that sought to assess the efficacy and mechanism of action of compounds with antidepressant effects. Our search results focused on selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed treatments for depression and ketamine, a fast-acting antidepressant treatment. Normalization of amygdala hyperactivity in response to negative emotional stimuli was found to underlie successful treatment response to SSRIs as well as ketamine, indicating a potential common pathway for both conventional and fast-acting antidepressants. Ketamine's rapid antidepressant effects make it a particularly useful compound for studying depression with fMRI; its effects on brain activity and connectivity trended toward normalizing the increases and decreases in brain activity and connectivity associated with depression. These findings highlight the considerable promise of fMRI as a tool for identifying treatment targets in depression. However, additional studies with improved methodology and study design are needed before fMRI findings can be translated into meaningful clinical trial outcomes.
| S-EPMC10406217 | biostudies-literature
Project description:MRI produces better soft tissue contrast than does ultrasonography or computed tomography for visualizing male pelvic anatomy and prostate cancer. Better visualization of the tumor and organs at risk could allow better conformation of the dose to the target volumes while at the same time minimizing the dose to critical structures and the associated toxicity. Although the use of MRI for prostate brachytherapy would theoretically result in an improved therapeutic ratio, its implementation been slow, mostly because of technical challenges. In this review, we describe the potential role of MRI at different steps in the treatment workflow for prostate brachytherapy: for patient selection, treatment planning, in the operating room, or for postimplant assessment. We further present the current clinical experience with MRI-guided prostate brachytherapy, both for permanent seed implantation and high-dose-rate brachytherapy.
| S-EPMC6075683 | biostudies-literature
Project description:BackgroundCurrent chemoradiation regimens for locally advanced cervical cancer are fairly uniform despite a profound diversity of treatment response and recurrence patterns. The wide range of treatment responses and prognoses to standardized concurrent chemoradiation highlights the need for a reliable tool to predict treatment outcomes. We investigated pretreatment magnetic resonance (MR) imaging features of primary tumor and involved lymph node for predicting clinical outcome in cervical cancer patients.MethodsWe included 93 node-positive cervical cancer patients treated with definitive chemoradiotherapy at our institution between 2006 and 2017. The median follow-up period was 38?months (range, 5-128). Primary tumor and involved lymph node were manually segmented on axial gadolinium-enhanced T1-weighted images as well as T2-weighted images and saved as 3-dimensional regions of interest (ROI). After the segmentation, imaging features related to histogram, shape, and texture were extracted from each ROI. Using these features, random survival forest (RSF) models were built to predict local control (LC), regional control (RC), distant metastasis-free survival (DMFS), and overall survival (OS) in the training dataset (n?=?62). The generated models were then tested in the validation dataset (n?=?31).ResultsFor predicting LC, models generated from primary tumor imaging features showed better predictive performance (C-index, 0.72) than those from lymph node features (C-index, 0.62). In contrast, models from lymph nodes showed superior performance for predicting RC, DMFS, and OS compared to models of the primary tumor. According to the 3-year time-dependent receiver operating characteristic analysis of LC, RC, DMFS, and OS prediction, the respective area under the curve values for the predicted risk of the models generated from the training dataset were 0.634, 0.796, 0.733, and 0.749 in the validation dataset.ConclusionsOur results suggest that tumor and lymph node imaging features may play complementary roles for predicting clinical outcomes in node-positive cervical cancer.
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Project description:Less than 50% of patients with Major Depressive Disorder (MDD) reach symptomatic remission with their initial antidepressant medication (ADM). There are currently no objective measures with which to reliably predict which individuals will achieve remission to ADMs.157 participants with MDD from the International Study to Predict Optimized Treatment in Depression (iSPOT-D) underwent baseline MRIs and completed eight weeks of treatment with escitalopram, sertraline or venlafaxine-ER. A score at week 8 of 7 or less on the 17 item Hamilton Rating Scale for Depression defined remission. Receiver Operator Characteristics (ROC) analysis using the first 50% participants was performed to define decision trees of baseline MRI volumetric and connectivity (fractional anisotropy) measures that differentiated non-remitters from remitters with maximal sensitivity and specificity. These decision trees were tested for replication in the remaining participants.Overall, 35% of all participants achieved remission. ROC analyses identified two decision trees that predicted a high probability of non-remission and that were replicated: 1. Left middle frontal volume < 14 · 8 mL & right angular gyrus volume > 6 · 3 mL identified 55% of non-remitters with 85% accuracy; and 2. Fractional anisotropy values in the left cingulum bundle < 0 · 63, right superior fronto-occipital fasciculus < 0 · 54 and right superior longitudinal fasciculus < 0 · 50 identified 15% of the non-remitters with 84% accuracy. All participants who met criteria for both decision trees were correctly identified as non-remitters.Pretreatment MRI measures seem to reliably identify a subset of patients who do not remit with a first step medication that includes one of these commonly used medications. Findings are consistent with a neuroanatomical basis for non-remission in depressed patients.Brain Resource Ltd is the sponsor for the iSPOT-D study (NCT00693849).
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Project description:Because of the large variation in the response to psychoactive medication, many studies have attempted to uncover genetic factors that determine response. While considerable knowledge exists on the large effects of genetic polymorphisms on pharmacokinetics and plasma concentrations of drugs, effects of the concentration at the target site and pharmacodynamic effects on brain functions in disease are much less known. This article reviews the role of magnetic resonance imaging (MRI) to visualize response to medication in brain behaviour circuits in vivo in humans and assess the influence of pharmacogenetic factors. Two types of studies have been used to characterize effects of medication and genetic variation. In task-related activation studies the focus is on changes in the activity of a neural circuit associated with a specific psychological process. The second type of study investigates resting state perfusion. These studies provide an assessment of vascular changes associated with bioavailability of drugs in the brain, but may also assess changes in neural activity after binding of centrally active agents. Task-related pharmacogenetic studies of cognitive function have characterized the effects in the prefrontal cortex of genetic polymorphisms of dopamine receptors (DRD2), metabolic enzymes (COMT) and in the post-synaptic signalling cascade under the administration of dopamine agonists and antagonists. In contrast, pharmacogenetic imaging with resting state perfusion is still in its infancy. However, the quantitative nature of perfusion imaging, its non-invasive character and its repeatability might be crucial assets in visualizing the effects of medication in vivo in man during therapy.
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Project description:Baclofen is a promising treatment for alcohol use disorders (AUD), although its clinical response in humans is mixed. The present study aimed at investigating the impact of baclofen treatment on cue-induced brain activation pattern and its relationship with relapse outcomes.Twenty-three inpatients with AUD underwent a functional magnetic resonance imaging cue-reactivity task before beginning medication with baclofen and 2 weeks later. Twelve additional inpatients with AUD, who did not receive any anticraving medications, formed the control group. All subjects were prospectively followed up for 90 days post-discharge or until lapse to first alcohol use.Whole-brain linear mixed effects analysis revealed a significant group-by-time interaction with greater activation of the bilateral dorsolateral pre-frontal cortex and right anterior cingulate cortex (ACC) following baclofen treatment in comparison with the control group. Further, cox regression analysis revealed that increased activation of ACC and deactivation of insular cortex (IC) was associated with longer time to first alcohol use only in the baclofen treatment group but not in the control group.This study provides preliminary evidence for the neural predictors of baclofen treatment response in AUD. Baclofen treatment in AUD was associated with changes in cue-reactivity at critical brain regions within the incentive-salience network. Importantly, baclofen treatment-related specific activation of regions involved in cognitive control (ACC) and deactivation of regions involved in reward anticipation (IC) prolonged the time to first alcohol drink.
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Project description:BackgroundHuman papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) have better prognosis and treatment response compared to HPV-negative OPSCC. This study aims to noninvasively predict HPV status of OPSCC using clinical and/or radiological variables.MethodsSeventy-seven magnetic resonance radiomic features were extracted from T1-weighted postcontrast images of the primary tumor of 153 patients. Logistic regression models were created to predict HPV status, determined with immunohistochemistry, based on clinical variables, radiomic features, and its combination. Model performance was evaluated using area under the curve (AUC).ResultsModel performance showed AUCs of 0.794, 0.764, and 0.871 for the clinical, radiomic, and combined models, respectively. Smoking, higher T-classification (T3 and T4), larger, less round, and heterogeneous tumors were associated with HPV-negative tumors.ConclusionModels based on clinical variables and/or radiomic tumor features can predict HPV status in OPSCC patients with good performance and can be considered when HPV testing is not available.
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