Computed tomography angiography-based analysis of high-risk intracerebral haemorrhage patients by employing a mathematical model.
Ontology highlight
ABSTRACT: Background
Haemorrhagic stroke accounts for approximately 31.52% of all stroke cases, and the most common origin is hypertension. However, little is known about the method to identify high-risk populations of hypertensive intracerebral haemorrhage.Results
The results showed that the angle between the middle cerebral artery and the internal carotid artery (AMIC), the distance between the beginning of the median artery and superior trunk (DMS), and the density (CT value) of the lenticulostriate artery (CTL) were statistically significant enough to cause intracerebral haemorrhage. In addition, we chose these three potential features for the ensemble learning classification model. Our developed ensemble-learning method outperforms not only previous work but also three other classic classification methods based on accuracy measurements.Conclusions
The developed mathematical model in the present study is efficient in predicting the probability of intracerebral haemorrhage.
SUBMITTER: Zhang L
PROVIDER: S-EPMC6509873 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature
Publications
Computed tomography angiography-based analysis of high-risk intracerebral haemorrhage patients by employing a mathematical model.
Zhang Le L Li Jin J Yin Kaikai K Jiang Zhouyang Z Li Tingting T Hu Rong R Yu Zheng Z Feng Hua H Chen Yujie Y
BMC bioinformatics 20190501 Suppl 7
<h4>Background</h4>Haemorrhagic stroke accounts for approximately 31.52% of all stroke cases, and the most common origin is hypertension. However, little is known about the method to identify high-risk populations of hypertensive intracerebral haemorrhage.<h4>Results</h4>The results showed that the angle between the middle cerebral artery and the internal carotid artery (AMIC), the distance between the beginning of the median artery and superior trunk (DMS), and the density (CT value) of the len ...[more]
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| S-EPMC10498225 | biostudies-literature
Project description:Background and purposePatients with intracerebral hemorrhage (ICH) who present with a spot sign on computed tomography angiography are at increased risk of hematoma expansion and poor outcome. Because primary ICH is the acute manifestation of chronic cerebral small vessel disease, we investigated whether different clinical or imaging characteristics predict spot sign presence, using ICH location as a surrogate for arteriolosclerosis- and cerebral amyloid angiopathy-related ICH.MethodsPatients with primary ICH and available computed tomography angiography at presentation were included. Predictors of spot sign were assessed using uni- and multivariable regression, stratified by ICH location.ResultsSeven hundred forty-one patients were eligible, 335 (45%) deep and 406 (55%) lobar ICH. At least one spot sign was present in 76 (23%) deep and 102 (25%) lobar ICH patients. In multivariable regression, warfarin (odds ratio [OR], 2.42; 95% confidence interval [CI], 1.01-5.71; P=0.04), baseline ICH volume (OR, 1.20; 95% CI, 1.09-1.33, per 10 mL increase; P<0.001), and time from symptom onset to computed tomography angiography (OR, 0.89; 95% CI, 0.80-0.96, per hour; P=0.009) were associated with the spot sign in deep ICH. Predictors of spot sign in lobar ICH were warfarin (OR, 3.95; 95% CI, 1.87-8.51; P<0.001) and baseline ICH volume (OR, 1.20; 95% CI, 1.10-1.31, per 10 mL increase; P<0.001).ConclusionsThe most potent associations with spot sign are shared between deep and lobar ICH, suggesting that the acute bleeding process that arises in the setting of different chronic small vessel diseases shares commonalities.
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Project description:Background High-risk plaque (HRP) features as detected by coronary computed tomography angiography (CTA) predict acute coronary syndrome (ACS). We sought to determine whether coronary CTA-specific definitions of HRP improve discrimination of patients with ACS as compared with definitions from intravascular ultrasound (IVUS). Methods and Results In patients with suspected ACS, randomized to coronary CTA in the ROMICAT II (Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography II) trial, we retrospectively performed semiautomated quantitative analysis of HRP (including remodeling index, plaque burden as derived by plaque area, low computed tomography attenuation plaque volume) and degree of luminal stenosis and analyzed the performance of traditional IVUS thresholds to detect ACS. Furthermore, we derived CTA-specific thresholds in patients with ACS to detect culprit lesions and applied those to all patients to calculate the discriminatory ability to detect ACS in comparison to IVUS thresholds. Of 472 patients, 255 patients (56±7.8 years; 63% men) had coronary plaque. In 32 patients (6.8%) with ACS, culprit plaques (n=35) differed from nonculprit plaques (n=172) with significantly greater values for all HRP features except minimal luminal area (significantly lower; all P<0.01). IVUS definitions showed good performance while minimal luminal area (odds ratio: 6.82; P=0.014) and plaque burden (odds ratio: 5.71; P=0.008) were independently associated with ACS but not remodeling index (odds ratio: 0.78; P=0.673). Optimized CTA-specific thresholds for plaque burden (area under the curve: 0.832 versus 0.676) and degree of stenosis (area under the curve: 0.826 versus 0.721) showed significantly higher diagnostic performance for ACS as compared with IVUS-based thresholds (all P<0.05) with borderline significance for minimal luminal area (area under the curve: 0.817 versus 0.742; P=0.066). Conclusions CTA-specific definitions of HRP features may improve the discrimination of patients with ACS as compared with IVUS-based definitions. CLINICAL TRIAL REGISTRATION URL: https://www.clinicaltrials.gov . Unique identifier: NCT01084239.
| S-EPMC6205220 | biostudies-literature
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| S-EPMC7668337 | biostudies-literature
Project description:Vulnerable carotid atherosclerotic plaque (CAP) significantly contributes to ischemic stroke. Neovascularization within plaques is an emerging biomarker linked to plaque vulnerability that can be detected using contrast-enhanced ultrasound (CEUS). Computed tomography angiography (CTA) is a common method used in clinical cerebrovascular assessments that can be employed to evaluate the vulnerability of CAPs. Radiomics is a technique that automatically extracts radiomic features from images. This study aimed to identify radiomic features associated with the neovascularization of CAP and construct a prediction model for CAP vulnerability based on radiomic features. CTA data and clinical data of patients with CAPs who underwent CTA and CEUS between January 2018 and December 2021 in Beijing Hospital were retrospectively collected. The data were divided into a training cohort and a testing cohort using a 7:3 split. According to the examination of CEUS, CAPs were dichotomized into vulnerable and stable groups. 3D Slicer software was used to delineate the region of interest in CTA images, and the Pyradiomics package was used to extract radiomic features in Python. Machine learning algorithms containing logistic regression (LR), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and multi-layer perception (MLP) were used to construct the models. The confusion matrix, receiver operating characteristic (ROC) curve, accuracy, precision, recall, and f-1 score were used to evaluate the performance of the models. A total of 74 patients with 110 CAPs were included. In all, 1,316 radiomic features were extracted, and 10 radiomic features were selected for machine-learning model construction. After evaluating several models on the testing cohorts, it was discovered that model_RF outperformed the others, achieving an AUC value of 0.93 (95% CI: 0.88-0.99). The accuracy, precision, recall, and f-1 score of model_RF in the testing cohort were 0.85, 0.87, 0.85, and 0.85, respectively. Radiomic features associated with the neovascularization of CAP were obtained. Our study highlights the potential of radiomics-based models for improving the accuracy and efficiency of diagnosing vulnerable CAP. In particular, the model_RF, utilizing radiomic features extracted from CTA, provides a noninvasive and efficient method for accurately predicting the vulnerability status of CAP. This model shows great potential for offering clinical guidance for early detection and improving patient outcomes.
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Project description:AimsPhoton-counting detector computed tomography (PCD-CT), which allows the exclusion of electronic noise, shows promise for significant dose reduction in coronary CT angiography (CCTA). This study aimed to assess the radiation dose and image quality of CCTA using PCD-CT, combined with high-pitch helical scanning and an ultra-low tube potential of 70 kVp, and investigate the effect of a sharp kernel on image quality and stenosis assessment in such an ultra-low-dose CCTA setting.Methods and resultsForty patients (65% male) with stable heart rates and no prior coronary interventions were included. Data on CT dose index volume (CTDIvol) and dose-length product (DLP) were collected, with effective radiation dose estimated using a conversion factor of 0.014. Images were reconstructed using kernels of Bv64 and Bv40 for image quality and stenosis assessment. The mean CTDIvol, DLP, and effective dose of CCTA were 1.72 ± 0.38 mGy, 29.1 ± 6.8 mGy·cm, and 0.41 ± 0.09 mSv, respectively. Image quality was similar (P = 0.75) between the two kernels, with over 95% of segments achieving a rating of good image quality for both kernels. The per-segment stenosis score distribution between Bv40 and Bv64 reconstruction images showed significant differences for both non-calcified and calcified plaques (P < 0.001 for both).ConclusionPCD-CT technology with high-pitch helical scanning and the tube potential of 70 kVp can provide CCTA with ultra-low radiation exposure (DLP, 29 mGy·cm). The noise reduction capability of PCD-CT allows the use of a sharp kernel even in this low-dose CCTA setting without compromising image quality, potentially improving the evaluation of coronary artery stenosis.
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| S-EPMC6635103 | biostudies-literature
Project description:AimTo improve delivery of acute therapies for acute ischaemic stroke (AIS).MethodWe identified factors influencing the speed of diagnosis and delivery of acute therapies in a prospective cohort of 21 children with suspected AIS (eight with AIS, 13 stroke mimics) and explored them in a retrospective cohort with confirmed AIS.ResultsApproximately half of the prospective and total AIS cohorts presented with acute, sustained hemiparesis, and were diagnosed relatively quickly. AIS was suspected and diagnosed more slowly in the half presenting with symptoms other than sustained hemiparesis. Thirty-one out of 51 patients with AIS (19 females, 32 males, mean age 8 years 6 months, SD 5 years 4 months) had arterial abnormalities identified by computed tomography angiography (CTA) or magnetic resonance angiography (MRA): 11 with large vessel occlusion, six with dissection, five with moyamoya disease, nine with other arteriopathies. Among these patients, those initially imaged with CTA were diagnosed more quickly than those with initial magnetic resonance imaging/angiography, which facilitated thrombectomy and thrombolytic therapy. Twenty out of 51 had AIS without arterial abnormalities on CTA or MRA: eight with lenticulostriate vasculopathy and 12 with other small-vessel AIS. Among these patients, 80% were ineligible for thrombolysis for reasons beyond delay to diagnosis, and all showed good outcomes with supportive treatments alone.InterpretationClinical features at presentation influence rapidity with which childhood AIS is suspected and diagnosed. Readily available CTA can direct thrombectomy in patients with large vessel occlusion and thrombolysis in most, but not all, eligible patients.What this paper addsChildren with acute ischaemic stroke (AIS) commonly present with symptoms other than sustained hemiparesis. Stroke is more slowly recognized in these patients, which limits potential therapies. Computed tomography angiography (CTA) accurately identifies AIS with large vessel occlusion, enabling timely endovascular thrombectomy. CTA is sufficient to direct thrombolytic therapy in most eligible children. Most childhood AIS without arterial abnormalities identified by CTA had good outcomes.
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Project description:BackgroundCoronary computed tomography angiography (CCTA) is used to assess plaque characteristics, remodelling, and progression and regression. Few papers address standard operating procedures that ensure achievement of high interobserver reproducibility. Moreover, assessment of coronary artery bypass grafts has not been reported.MethodsA training set of images was created of native coronary segments, spanning the full range of atheromatous disease from normal to severe, excluding totally occluded segments, and including segments with or without calcification (n = 24) and completely normal-appearing bypass grafts (n = 16). Three observers used a validated software program during a training phase to establish standard operating procedures and then to achieve high intraobserver performance based on Pearson's correlation coefficient. Subsequently, interobserver variability for the laboratory as a whole was determined with a focus on measures of plaque volume, low- attenuation plaque (LAP), mixed plaque (MP), and calcified plaque (CP).ResultsWe found no substantive differences in analytical issues between grafts and native vessels and emphasize the aggregated data. The range of mean total plaque percent was approximately 55% of total vessel volume with maximal interobserver mean absolute differences of 2% or less. Percent of LAP, MP, and CP demonstrated interobserver standard errors of 1% to 2% and interobserver mean absolute differences of 0% to 1%. Pearson's correlations were all highly significant and ranged from 0.969 to 0.999.ConclusionsCCTA provides a rich diversity of measures of atherosclerosis in coronary and bypass segments that are highly reproducible with experience and adherence to standard operating procedures.
| S-EPMC8843959 | biostudies-literature
Project description:BackgroundHigh-altitude pulmonary hypertension (HAPH), as the group 3 pulmonary hypertension, has been less studied so far. The limited medical conditions in the high-altitude plateau are responsible for the delay of the clinical management of HAPH.ObjectivesThis study aims to identify the imaging characteristics of HAPH and explore noninvasive assessment of mean pulmonary arterial pressure (mPAP) based on computed tomography angiography (CTA).MethodsTwenty-five patients with suspected HAPH were enrolled. Right heart catheterization (RHC) and pulmonary angiography were performed. Echocardiography and CTA image data were collected for analysis. A multivariable linear regression model was fit to estimate mPAP (mPAPpredicted). A Bland-Altman plot and pathological analysis were performed to assess the diagnostic accuracy of this model.ResultsPatients with HAPH showed slow blood flow and coral signs in lower lobe pulmonary artery in pulmonary arteriography, and presented trend for dilated pulmonary vessels, enlarged right atrium, and compressed left atrium in CTA (P for trend <0.05). The left lower pulmonary artery-bronchus ratio (odds ratio: 1.13) and the ratio of right to left atrial diameter (odds ratio: 1.09) were significantly associated with HAPH, and showed strong correlation with mPAPRHC, respectively (r = 0.821 and r = 0.649, respectively; all P < 0.0001). The mPAPpredicted model using left lower artery-bronchus ratio and ratio of right to left atrial diameter as covariates showed high correlation with mPAPRHC (r = 0.907; P < 0.0001). Patients with predicted HAPH also had the typical pathological changes of pulmonary hypertension.ConclusionsNoninvasive mPAP estimation model based on CTA image data can accurately fit mPAPRHC and is beneficial for the early diagnosis of HAPH.
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