Assesment of Stroke Risk Based on Morphological Ultrasound Image Analysis With Conformal Prediction

Non-invasive ultrasound imaging of carotid plaques allows for the development of plaque image analysis in order to assess the risk of stroke. In our work, we provide reliable confidence measures for the assessment of stroke risk, using the Conformal Prediction framework. This framework provides a way for assigning valid confidence measures to predictions of classical machine learning algorithms. We conduct experiments on a dataset which contains morphological features derived from ultrasound images of atherosclerotic carotid plaques, and we evaluate the results of four different Conformal Predictors (CPs). The four CPs are based on Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Naive Bayes classification (NBC), and k-Nearest Neighbours (k-NN). The results given by all CPs demonstrate the reliability and usefulness of the obtained confidence measures on the problem of stroke risk assessment

Comparison of multidetector-row computed tomography and duplex Doppler ultrasonography in detecting atherosclerotic carotid plaques complicated with intraplaque hemorrhage [Usporedba višeslojne kompjuterizirane tomografije i duplex Doppler ultrazvuka u otkrivanju aterosklerotskih karotidnih plakova kompliciranih krvarenjem u plak ]

This study compared sensitivity and specificity of multidetector-row computed tomography and duplex Doppler ultrasonography in detecting atherosclerotic carotid plaques complicated with intraplaque hemorrhage. Carotid plaques from 50 patients operated for carotid artery stenosis were analyzed. Carotid endarterectomy was performed within one week of diagnostic evaluation. Results of multidetector-row computed tomography and duplex Doppler ultrasonography diagnostic evaluation were compared with results of histological analysis of the same plaque areas. American Heart Association classification of atherosclerotic plaques was applied for histological classification. Median tissue density of carotid plaques complicated with intraplaque hemorrhage was 14.7 Hounsfield units. Median tissue density of noncalcified segments of uncomplicated plaques was 54.3 Hounsfield units (p = 0.00003). The highest tissue density observed for complicated plaques was 31.8 Hounsfield units. Multidetector-row computed tomography detected plaques complicated with hemorrhage with sensitivity of 100% and specificity of 70.4%, with tissue density of 33.8 Hounsfield units as a threshold value. Duplex Doppler ultrasonography plaque analysis based on visual in-line classification showed sensitivity of 21.7% and specificity of 89.6% in detecting plaques complicated with intraplaque hemorrhage. Multidetector-row computed tomography showed a very high level of sensitivity and a moderate level of specificity in detecting atherosclerotic carotid plaques complicated with hemorrhage. Duplex Doppler ultrasonography plaque analysis based on visual in-line classification showed a low level of sensitivity and a moderate-high level of specificity in detecting atherosclerotic carotid plaques complicated with hemorrhage

Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application

Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most

Preliminary comparisons between in vivo ultrasonographic virtual histology and histopathological findings of endarterectomized carotid plaque

BACKGROUND:Extracranial carotid artery atherosclerosis is a major preventable cause of strokes, the second most common cause of death in developed countries. The degree of arterial lumen stenosis is the basis for surgical indications, but does not provide information about other plaque aspects. Studies in the literature suggest that the morphological characteristics of the plaque and its composition should also be included in the assessment of this disease.OBJECTIVE:Investigate the correlation between atherosclerotic plaque composition defined by computer-assisted analysis of ultrasound images (virtual histology - USVH) and conventional histology.METHOD:The images of twelve plaques, obtained during preoperative ultrasound scanning, were analyzed by computer, and the grey scale images were correlated with the plaque components and subsequently compared with the histological findings of the analysis of the endarterectomy specimens.RESULTS:The amount of lipids and fibromuscular tissue were strongly correlated in the two tests (R=0.83 and 0.91). There were no significant correlations with amount of blood or calcium (R=0.05 and 0.19).CONCLUSION:This study confirmed the usefulness of noninvasive USVH. Further technical improvements and software developments may promote the clinical application of this method.CONTEXTO:A doença aterosclerótica da carótida extracraniana é uma das principais causas evitáveis de acidente vascular cerebral isquêmico (AVCi), sendo este a segunda causa mais comum de morte nos países desenvolvidos. Nos grandes estudos sobre a cirurgia carotídea, a indicação estava embasada fundamentalmente no grau de estenose arterial. Analisar somente o grau de estenose, entretanto, não revela todas as características da placa, na medida em que a morfologia e a composição da placa complementam a avaliação da doença carotídea avançada e são fundamentais para a análise e o acompanhamento da maioria das placas carotídeas tratadas clinicamente.OBJETIVO:Correlacionar a caracterização dos componentes da placa de ateroma pela histologia virtual ultrassonográfica (HVUS) com a histologia.MÉTODOS:As imagens pré-operatórias obtidas por ultrassonografia transcutânea de 12 placas de ateroma de bifurcação carotídea foram submetidas a um programa de computador, o qual correlacionou os níveis de cinza com os prováveis componentes da placa da bifurcação carotídea (HVUS). Estes achados foram correlacionados com o exame anatomopatológico das placas coletadas pela cirurgia de endarterectomia.RESULTADOS:O coeficiente de correlação de Pearson para os conteúdos de lipídeos e músculo/tecido fibroso foram, respectivamente, R=0,83 para gordura e R=0,91 para músculo/tecido fibroso. Quanto ao cálcio e ao sangue, foram R=0,05 e R=0,19, respectivamente.CONCLUSÕES:O presente trabalho corrobora a literatura demonstrando que a histologia virtual computadorizada baseada em ultrassonografia transcutânea apresenta boa correlação com os achados da histologia quanto ao conteúdo da placa. Maiores estudos para a padronização da técnica e o aperfeiçoamento do programa de análise permitirão maior uso clínico deste método.19320

Carotid plaque vulnerability assessment by microscopic morphology analysis, ultrasound and 3D model reconstruction

This thesis was submitted for the degree of Docter of Philosophy and awarded by Brunel University.Research suggests that plaque morphology plays a crucial role in determining plaque vulnerability. However the relationship between plaque morphology and rupture is still not clearly understood due to the limited information of plaque morphology. The aim of this study is to improve our understanding of the relationship between plaque morphology and rupture, and to use this to predict the risk of plaque rupture from the morphology at the molecular level. This can enable the identification of culprit lesions in clinical situations for assessing plaque rupture risk. Histological assessments were carried out on 18 carotid plaque specimens. The 3-D collagen, lipid and macrophage distributions along the entire length of the plaque were analysed in both ruptured and non-ruptured symptomatic plaques. In addition, plaque morphology on the rupture sites were examined and compared with the surrounding regions. It was found that ruptured plaques had thinner fibrous caps and larger lipid cores compared to non-ruptured plaques. Also, ruptured plaques had lower collagen content compared to non-ruptured plaques, and higher collagen contents upstream compared to downstream region from the plaque throat. At the rupture site there was lower collagen content, and a larger lipid core thickness behind a thin fibrous cap compared with the mean for the longitudinally adjacent and circumferential regions. Macrophage cells were located nearer to the boundary of the luminal wall in ruptured plaques. For both groups, the area occupied by macrophages is greater at the upstream shoulder of the plaque. There is a positive correlation between macrophage area and lipid core area, a negative correlation between macrophage area and collagen content, and between lipid core size and collagen content for both plaque groups. 3D reconstruction of ex-vivo specimens of carotid plaques were carried out by a combined analysis of US imaging and histology. To reconstruct accurate 3D plaque morphology, the non-linear tissue distortion in histological images caused by specimen preparation was corrected by a finite element (FE) based deformable registration procedure. This study shows that it is possible to generate a 3D patient specific plaque model using this method. In addition, the study also quantitatively assesses the tissue distortion caused by histological procedures. It shows that at least 30% tissue shrinkage is expected for plaque tissues. The histology analysis result was also used to evaluate ultrasound (US) tissue characterization accuracy. An ex-vivo 2D ultrasound scan set-up was used to obtain serial transverse images through an atherosclerotic plaque. The different plaque component region obtained from ultrasound images was compared with the associated histology result and photograph of the sections. Plaque tissue characterisation using ex-vivo US can be performed qualitatively, whereas lipid core assessment from ultrasound scan can be semi-quantitative. This finding combined with the negative correlation between lipid core size and collagen content, suggests the ability of US to indirectly quantify plaque collagen content. This study may serve as a platform for future studies on improving ultrasound tissue characterization, and may also potentially be used in risk assessment of plaque rupture