Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors

Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors. Am J Physiol Heart Circ Physiol 304: H1455-H1470, 2013. First published March 15, 2013; doi:10.1152/ajpheart.00539.2012.-Atherosclerosis is a systemic disease with local manifestations. Low-density lipoprotein (LDL) accumulation in the subendothelial layer is one of the hallmarks of atherosclerosis onset and ignites plaque development and progression. Blood flow-induced endothelial shear stress (ESS) is causally related to the heterogenic distribution of atherosclerotic lesions and critically affects LDL deposition in the vessel wall. In this work we modeled blood flow and LDL transport in the coronary arterial wall and investigated the influence of several hemodynamic and biological factors that may regulate LDL accumulation. We used a three-dimensional model of a stenosed right coronary artery reconstructed from angiographic and intravascular ultrasound patient data. We also reconstructed a second model after restoring the patency of the stenosed lumen to its nondiseased state to assess the effect of the stenosis on LDL accumulation

Data mining and healthcare decision support systems

The objective of the PhD thesis is the design and development of decision support systems, with knowledge derived using data mining techniques. Specifically, in the field of biomedicine we designed and developed a decision support system for ischeamia, by processing and analyzing the ECG signal. From the biology domain, we designed and developed a method for the classification of proteins into folds. Finally we created a novel methodology than can be applied in several sequential domains, for the creation of sequential classification models, if the data are described as discrete time series. In the first chapter we describe the fundamental issues of the healthcare decision support systems, data mining as well as their interconnection and relationship. A general data mining framework for creating decision support systems is also presented. At the end of the first chapter we provide a detailed literature review concerning the two applications we have developed: ischaemic beat detection and protein fold and class recognition. In the second chapter we present a literature review of decision support systems that have been developed and are widely used in the healthcare domain and provide algorithms that are used for data mining. Moreover, detailed state of the art in the domains of ischaemic beat detection and protein fold and class prediction are included. In chapters 3 and 4 we describe in detail the methods we followed for solving the real world applications – ischaemic beat detection and protein fold recognition and class prediction. The methods follow a general scheme that corresponds to four steps: a) data collection b) data preprocessing c) data analysis using data mining techniques and d) creation of the classification model – decision support system. Special attention is given in the third step, where we mainly used association rule and sequential pattern mining techniques. The results we have achieved show the effectiveness of these methods. In chapter 5 we present a methodology that can be used for the creation of sequence classification models. The methodology integrates sequential pattern mining techniques and optimization algorithms and is compared with two other similar methodologies. Finally in chapter 6 we provide conclusions, remarks and future development of out thesis. A future development that we have already identified is the creation of decision support systems using data mining techniques applied in data clinical and genetic. The integration of these two types of data can help in better describing the situation of the patient and thus in a more accurate diagnosis. The use and integration of clinical and genetic data can help in diseases like cancer. At the end of this chapter we present a system’s architecture that can achieve this integration and create the corresponding healthcare decision support systemsΟ στόχος της παρούσας διδακτορικής διατριβής είναι η δημιουργία συστημάτων υποστήριξης απόφασης με γνώση που παράγεται από τεχνικές εξόρυξης δεδομένων. Πιο συγκεκριμένα, στο χώρο της βιοιατρικής, σχεδιάσαμε και υλοποιήσαμε ένα σύστημα υποστήριξης απόφασης για την πάθηση της ισχαιμίας, με επεξεργασία του ΗΚΓκού σήματος. Από το χώρο της βιολογίας, σχεδιάσαμε και υλοποιήσαμε μια μέθοδο ταξινόμησης πρωτεϊνών σε πτυχές. Τέλος, αναπτύξαμε και μια καινοτόμα μεθοδολογία που μπορεί να εφαρμοστεί σε διάφορα πεδία, με την προϋπόθεση ότι είναι ακολουθιακά και περιγράφονται από διακριτές χρονοσειρές. Πιο συγκεκριμένα, στο πρώτο κεφάλαιο παρουσιάζουμε και περιγράφουμε τις γενικές έννοιες των ιατρικών συστημάτων υποστήριξης απόφασης, της εξόρυξης δεδομένων καθώς και τη σχέση μεταξύ των δυο εννοιών. Παρουσιάζεται η γενικότερη μεθοδολογία εξόρυξης δεδομένων που χρησιμοποιείται για τη δημιουργία συστημάτων υποστήριξης απόφασης. Στο τέλος του πρώτου κεφαλαίου γίνεται λεπτομερής ανασκόπηση στους τομείς και τις εφαρμογές που αναπτύχθηκαν στην παρούσα διδακτορική διατριβή, δηλαδή μεθοδολογίες εντοπισμού ισχαιμικών παλμών στο ηλεκτροκαρδιογράφημα, και συστήματα ταξινόμησης πρωτεϊνών σε πτυχές και κλάσεις. Στο κεφάλαιο 2 γίνεται βιβλιογραφική ανασκόπηση τόσο σε επιτυχημένα ιατρικά συστήματα υποστήριξης απόφασης που εφαρμόστηκαν στην κλινική πράξη όσο και σε αλγορίθμους εξόρυξης δεδομένων. Επίσης, γίνεται βιβλιογραφική ανασκόπηση στα επιμέρους πεδία της διδακτορικής διατριβής: ταξινόμηση ισχαιμικών παλμών και ταξινόμηση πρωτεϊνών. Στα κεφάλαια 3 και 4, γίνεται αναλυτική περιγραφή των μεθόδων που υλοποιήσαμε για την επίλυση των 2 εφαρμογών. Οι μέθοδοι ακολουθούν ένα γενικότερο σχήμα που αντιστοιχεί σε α)συλλογή δεδομένων β) προεπεξεργασία δεδομένων γ) ανάλυση δεδομένων με τεχνικές εξόρυξης δεδομένων και δ) δημιουργία του μοντέλου ταξινόμησης – συστήματος υποστήριξης απόφασης. Ιδιαίτερα στο βήμα γ, ιδιαίτερη έμφαση δόθηκε στην παρούσα διδακτορική διατριβή στις τεχνικές εξαγωγής κανόνων συσχέτισης και τεχνικές εξαγωγής ακολουθιακών προτύπων. Τα αποτελέσματα που σημειώθηκαν και στις 2 εφαρμογές δείχνουν την αποδοτικότητα αυτών των μεθόδων στην δημιουργία συστημάτων υποστήριξης απόφασης. Στο κεφάλαιο 5, παρουσιάζουμε μια μεθοδολογία που χρησιμοποιείται για την δημιουργία μοντέλων ταξινόμησης ακολουθιών. Η μεθοδολογία ενσωματώνει τεχνικές εξαγωγής ακολουθιακών προτύπων και βελτιστοποίησης και συγκρίνεται με ήδη υπάρχοντες αλγόριθμους που εκτελούν την ίδια δουλεία. Τέλος, στο κεφάλαιο 6 δίνουμε γενικά συμπεράσματα της διατριβής και μελλοντικές προεκτάσεις της. Μια προέκταση που έχει ήδη εντοπιστεί είναι η δημιουργία συστημάτων υποστήριξης απόφασης με τεχνικές εξόρυξης δεδομένων που εφαρμόζονται σε δεδομένα και κλινικά αλλά και γενετικά. Η σύνδεση αυτών των 2 τύπων δεδομένων μπορεί να βοηθήσει στην καλύτερη περιγραφή του ασθενή και άρα στην πιο ακριβής και αποτελεσματική διάγνωσή του. Η χρήση κλινικών και γενετικών δεδομένων έχει να προσφέρει πολλά σε παθήσεις όπως ο καρκίνος όπου τα γενετικά δεδομένα παίζουν τον κυριότερο ρόλο. Στο τέλος του κεφαλαίου προτείνουμε την αρχιτεκτονική ενός συστήματος που κάνει εφικτή αυτήν την ενσωμάτωση και τη δημιουργία των αντίστοιχων συστημάτων υποστήριξης απόφασης

Stable COPD Picture through Exhaled Breath Condensate, Questionnaires and Tests. A Proof of Concept Study

Background: Changes in lung structures persist in stable Chronic Obstructive Pulmonary Disease (COPD), but their correlation with the clinical picture remains unclear. The purpose of this study was to assess the stable COPD picture via the relationship between exhaled breath condensate (EBC) particle concentration and the Saint George Respiratory Questionnaire (SGRQ), COPD Assessment Test (CAT), and six-minute walking test (6 MWT). Methods: 12 stable COPD and 12 healthy subjects participated in the study. The EBC was collected with Rtube and analyzed using the Accusizer FxNano. Particle concentration was measured and correlated with the findings of the tools used to assess the health status and functional profile of COPD. The results’ analysis was performed with the Spearman’s test and the Mann-Whitney U - test.Results: The COPD group presented a worse picture of health status and functional profile compared to the healthy group. Correlations were observed between components of the SGRQ and CAT. The two groups presented similar levels of EBC particle concentrations, but the number of small particles was higher in COPD subjects. A correlation of the EBC particle concentration with the activity and total score of the SGRQ was only observed in the healthy group. Conclusion: The total particle number was similar in the COPD and healthy groups. A few correlations between the EBC particles and tools used were also observed. The use of EBC particle concentration to monitor COPD status cannot be claimed with confidence because of the small sample size. Further research is necessary, particularly in large-scale groups

Quantitative micro-CT based coronary artery profiling using interactive local thresholding and cylindrical coordinates

Micro-CT is an established imaging technique for high-resolution non-destructive assessment of vascular samples, which is gaining growing interest for investigations of atherosclerotic arteries both in humans and in animal models. However, there is still a lack in the definition of micro-CT image metrics suitable for comprehensive evaluation and quantification of features of interest in the field of experimental atherosclerosis (ATS). OBJECTIVE: A novel approach to micro-CT image processing for profiling of coronary ATS is described, providing comprehensive visualization and quantification of contrast agent-free 3D high-resolution reconstruction of full-length artery walls. METHODS: Accelerated coronary ATS has been induced by high fat cholesterol-enriched diet in swine and left coronary artery (LCA) harvested en bloc for micro-CT scanning and histologic processing. A cylindrical coordinate system has been defined on the image space after curved multiplanar reformation of the coronary vessel for the comprehensive visualization of the main vessel features such as wall thickening and calcium content. A novel semi-automatic segmentation procedure based on 2D histograms has been implemented and the quantitative results validated by histology. RESULTS: The potentiality of attenuation-based micro-CT at low kV to reliably separate arterial wall layers from adjacent tissue as well as identify wall and plaque contours and major tissue components has been validated by histology. Morphometric indexes from histological data corresponding to several micro-CT slices have been derived (double observer evaluation at different coronary ATS stages) and highly significant correlations (R2 < 0.90) evidenced. Semi-automatic morphometry has been validated by double observer manual morphometry of micro-CT slices and highly significant correlations were found (R2 < 0.92). CONCLUSION: The micro-CT methodology described represents a handy and reliable tool for quantitative high resolution and contrast agent free full length coronary wall profiling, able to assist atherosclerotic vessels morphometry in a preclinical experimental model of coronary ATS and providing a link between in vivo imaging and histology

Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: Effect of hemodynamic and biological factors

Atherosclerosis is a systemic disease with local manifestations. Low-density lipoprotein (LDL) accumulation in the subendothelial layer is one of the hallmarks of atherosclerosis onset and ignites plaque development and progression. Blood flow-induced endothelial shear stress (ESS) is causally related to the heterogenic distribution of atherosclerotic lesions and critically affects LDL deposition in the vessel wall. In this work we modeled blood flow and LDL transport in the coronary arterial wall and investigated the influence of several hemodynamic and biological factors that may regulate LDL accumulation. We used a three-dimensional model of a stenosed right coronary artery reconstructed from angiographic and intravascular ultrasound patient data. We also reconstructed a second model after restoring the patency of the stenosed lumen to its nondiseased state to assess the effect of the stenosis on LDL accumulation. Furthermore, we implemented a new model for LDL penetration across the endothelial membrane, assuming that endothelial permeability depends on the local lumen LDL concentration. The results showed that the presence of the stenosis had a dramatic effect on the local ESS distribution and LDL accumulation along the artery, and areas of increased LDL accumulation were observed in the downstream region where flow recirculation and low ESS were present. Of the studied factors influencing LDL accumulation, 1) hypertension, 2) increased endothelial permeability (a surrogate of endothelial dysfunction), and 3) increased serum LDL levels, especially when the new model of variable endothelial permeability was applied, had the largest effects, thereby supporting their role as major cardiovascular risk factors

Relationship of Endothelial Shear Stress with Plaque Features with Coronary CT Angiography and Vasodilating Capability with PET

Background Advances in three-dimensional reconstruction techniques and computational fluid dynamics of coronary CT angiography (CCTA) data sets make feasible evaluation of endothelial shear stress (ESS) in the vessel wall. Purpose To investigate the relationship between CCTA-derived computational fluid dynamics metrics, anatomic and morphologic characteristics of coronary lesions, and their comparative performance in predicting impaired coronary vasodilating capability assessed by using PET myocardial perfusion imaging (MPI). Materials and Methods In this retrospective study, conducted between October 2019 and September 2020, coronary vessels in patients with stable chest pain and with intermediate probability of coronary artery disease who underwent both CCTA and PET MPI with oxygen 15-labeled water or nitrogen 13 ammonia and quantification of myocardial blood flow were analyzed. CCTA images were used in assessing stenosis severity, lesion-specific total plaque volume (PV), noncalcified PV, calcified PV, and plaque phenotype. PET MPI was used in assessing significant coronary stenosis. The predictive performance of the CCTA-derived parameters was evaluated by using area under the receiver operating characteristic curve (AUC) analysis. Results There were 92 coronary vessels evaluated in 53 patients (mean age, 65 years ± 7; 31 men). ESS was higher in lesions with greater than 50% stenosis versus those without significant stenosis (mean, 15.1 Pa ± 30 vs 4.6 Pa ± 4 vs 3.3 Pa ± 3; P = .004). ESS was higher in functionally significant versus nonsignificant lesions (median, 7 Pa [interquartile range, 5-23 Pa] vs 2.6 Pa [interquartile range, 1.8-5 Pa], respectively; P ≤ .001). Adding ESS to stenosis severity improved prediction (change in AUC, 0.10; 95% CI: 0.04, 0.17; P = .002) for functionally significant lesions. Conclusion The combination of endothelial shear stress with coronary CT angiography (CCTA) stenosis severity improved prediction of an abnormal PET myocardial perfusion imaging result versus CCTA stenosis severity alone. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Kusmirek and Wieben in this issue

Relationship of Endothelial Shear Stress with Plaque Features with Coronary CT Angiography and Vasodilating Capability with PET

Background: Advances in three-dimensional reconstruction techniques and computational fluid dynamics of coronary CT angiography (CCTA) data sets make feasible evaluation of endothelial shear stress (ESS) in the vessel wall. Purpose: To investigate the relationship between CCTA-derived computational fluid dynamics metrics, anatomic and morphologic characteristics of coronary lesions, and their comparative performance in predicting impaired coronary vasodilating capability assessed by using PET myocardial perfusion imaging (MPI). Materials and Methods: In this retrospective study, conducted between October 2019 and September 2020, coronary vessels in patients with stable chest pain and with intermediate probability of coronary artery disease who underwent both CCTA and PET MPI with oxygen 15-labeled water or nitrogen 13 ammonia and quantification of myocardial blood flow were analyzed. CCTA images were used in assessing stenosis severity, lesion-specific total plaque volume (PV), noncalcified PV, calcified PV, and plaque phenotype. PET MPI was used in assessing significant coronary stenosis. The predictive performance of the CCTA-derived parameters was evaluated by using area under the receiver operating characteristic curve (AUC) analysis. Results: There were 92 coronary vessels evaluated in 53 patients (mean age, 65 years +/- 7; 31 men). ESS was higher in lesions with greater than 50% stenosis versus those without significant stenosis (mean, 15.1 Pa +/- 30 vs 4.6 Pa +/- 4 vs 3.3 Pa +/- 3; P = .004). ESS was higher in functionally significant versus nonsignificant lesions (median, 7 Pa [interquartile range, 5-23 Pa] vs 2.6 Pa [interquartile range, 1.8-5 Pa], respectively; P <= .001). Adding ESS to stenosis severity improved prediction (change in AUC, 0.10; 95% CI: 0.04, 0.17; P =.002) for functionally significant lesions. Conclusion: The combination of endothelial shear stress with coronary CT angiography (CCTA) stenosis severity improved prediction of an abnormal PET myocardial perfusion imaging result versus CCTA stenosis severity alone. (C) RSNA, 202