Ανίχνευση κρίσεων επιληψίας σε δεδομένα ηλεκτροεγκεφαλογράφου

Βασικός τομέας ενασχόλησης της παρούσας διπλωματικής εργασίας είναι η ανίχνευση επιληπτικών κρίσεων με χρήση μεθόδων μηχανικής μάθησης. Τα δεδομένα που χρησιμοποιήθηκαν προέρχονται από επιφανειακά ηλεκτροεγκεφαλογραφήματα (EEG). Πρόκειται για τη CHB-MIT βάση δεδομένων που διατίθεται δωρεάν στην πλατφόρμα PhysioNet. Στα πλαίσια της υλοποίησης εξετάστηκε όλη η διαδικασία διαχείρισης των δεδομένων από τη λήψη τους, την εξαγωγή χαρακτηριστικών (μέση τιμή, διακύμανση, ασυμμετρία, κύρτωση, τυπική απόκλιση, διάμεσος, διασχίσεις μηδενικού άξονα, ενεργός τιμή, εύρος μεταβολής, εντροπία δείγματος, ισχύς μέσω PSD στις συχνότητες δέλτα, θήτα (theta), άλφα (alpha), βήτα (beta), γάμμα (gamma), μέγιστη αλληλοσυσχέτιση) σε αυτά, την κανονικοποίησή τους (z-score), τη μείωση διαστάσεων (PCA) με διατήρηση τής εγγενούς πληροφορίας τους, την εξισορρόπηση των δειγμάτων (Cluster Centroids, ADASYN), επιληπτικών και μη, έως την εκπαίδευση, τη βελτιστοποίηση (αναζήτηση πλέγματος) και την εφαρμογή των ταξινομητών (SVM, kNN, Απλοϊκός Bayes, Δέντρα Απόφασης, Τυχαίο Δάσος, LDA, Λογιστική Παλινδρόμηση, Νευρωνικό Δίκτυο με LSTM), την αξιολόγηση τους (ακρίβεια, ευαισθησία, ειδικότητα, αξιοπιστία, βαθμολογία F1, συντελεστής συσχέτισης Matthews, συντελεστής κ του Cohen) και τη σύγκριση των αποτελεσμάτων. Διενεργούνται τρία διαφορετικά πειράματα είτε χρησιμοποιώντας τις μετρήσεις από όλα τα ηλεκτρόδια είτε τμήμα αυτών. Η βασική διαφορά της μεθόδου μας σε σχέση με τη βιβλιογραφία είναι ότι εξετάζονται τα αποτελέσματα της γενίκευσης σε αντίθεση με τις εστιασμένες στον κάθε ασθενή μεθόδους που συνήθως συναντάται. Η υλοποίηση όλων των παραπάνω γίνεται μέσω της γλώσσας Python, που είναι η δημοφιλέστερη για εφαρμογές μηχανικής μάθησης, και της πλατφόρμας Jupyter.The main field of work of this thesis is the detection of seizures using machine learning methods. The data we used came from scalp electroencephalograms (EEGs). This is the CHB-MIT database, which is available for free, from the PhysioNet platform. In the context of the implementation, the whole process of data management was examined from their download, the extraction of characteristics (mean, variance, skewness, kurtosis, standard deviation, median, zero crossings, root mean square, peak to peak, sample entropy, power via PSD in the delta, theta, alpha, beta, gamma frequencies, maximum correlation) from them, their normalization (z-score), the reduction of dimensions (PCA) by preserving their inherent information, the balancing of epileptic and non-epileptic samples (Cluster Centroids, ADASYN) to training, optimization (grid search) and classifier implementation (SVM, kNN, Naive Bayes, Decision Trees, Random Forest, LDA, Logistic Regression, Neural Network with LSTM), their evaluation (accuracy, sensitivity/recall, specificity, precision, F1 score, Matthews correlation coefficient, Cohen's Kappa coefficient) and comparison of results. Three different experiments are performed either by using the measurements of all the electrodes or part of them. The main difference of our method in relation to the bibliography is that the results of the generalization of the methods are examined in contrast to the focused ones on each patient that is usually encountered. All of the above is done using Python, which is the most popular of machine learning applications, and the Jupyter platform

Παράλληλη Επιτάχυνση αλγορίθμων Dictionary Learning και Παραγοντοποίησης με εφαρμογή σε fMRI: k-SVD, αλγόριθμος MM, PARAFAC2

Η αξιοσημείωτη πρόοδος που παρατηρείται στην Ιατρική με την πάροδο των χρόνων σχετίζεται άμεσα με την ταχεία και ευρεία εξάπλωση της χρήσης των υπολογιστών στις επιστήμες υγείας (Ιατρική, Βιολογία, Βιοτεχνολογία). Οι πολύπλοκοι υπολογισμοί που απαιτούνται σε ερευνητικό και πειραματικό στάδιο καθιστούν τον τομέα της Ιατρικής άρρηκτα συνδεδεμένο με εκείνον της Πληροφορικής. Ένα από τα φλέγοντα και ενδιαφέροντα ερευνητικά ζητήματα στον τομέα της Ιατρικής – συγκεκριμένα της νευρολογίας - είναι η λειτουργία του ανθρώπινου εγκεφάλου. Μια διαδεδομένη μέθοδος ανάλυσης της εγκεφαλικής δραστηριότητας τού ανθρώπου είναι η Λειτουργική Απεικόνιση Μαγνητικού Συντονισμού (fMRI). Είναι μη επεμβατική μέθοδος μέσω της οποίας μπορούμε να μελετήσουμε τις περιοχές του εγκεφάλου που ενεργοποιούνται κατά τη διάρκεια εκτέλεσης μιας ενέργειας (π.χ. ομιλία, παρατήρηση μιας εικόνας). Στην εργασία μας ασχολούμαστε με την εφαρμογή αλγορίθμων Dictionary Learning και Factorization σε fMRI. Πιο συγκεκριμένα επικεντρωνόμαστε στους αλγορίθμους k-SVD, MM και PARAFAC2. Στόχος μας είναι η επιτάχυνση των παραπάνω αλγορίθμων μέσω της χρήσης κάρτας γραφικών, η οποία παρέχει τη δυνατότητα πολλαπλών παράλληλων πράξεων πάνω σε ογκώδη δεδομένα. Τα πειράματα μας διενεργήθηκαν με χρήση CUDA και Matlab.The remarkable progress observed in medicine over the years is related to the rapid and widespread deployment of computer use in health sciences (Medicine, Biology, Biotechnology). The complex calculations required at the research and experimental stages make the field of medicine inextricably linked to that of computer technology. One of the burning and interesting research issues in the medical field is the function of the human brain. A widespread method of analyzing human brain activity is functional Magnetic Resonance Imaging (fMRI). It is a non-invasive method through which we can study the brain regions that are activated during the performance of an activity (for example speech, observation of an image). In our thesis we deal with the implementation of Dictionary Learning and Factorization algorithms in fMRI. Specifically, we focus on k-SVD, MM and PARAFAC2 algorithms. Our goal is to accelerate the above algorithms through the use of GPU, which offers the capability of multiple parallel operations over big data. Our experiments were conducted using CUDA and Matlab

How Innocent is the Restenosis of the Infarct-related Coronary Artery After Successful Initial Recanalization?

The present case report describes a patient who sustained an acute inferior wall myocardial infarction, but initially remained clinically stable, then he underwent a successful coronary angioplasty and stenting procedure of a totally occluded right coronary artery, subsequently developing a dramatic clinical course with cardiogenic shock and cardiac arrest due to acute stent thrombosis which was successfully managed with repeat coronary angioplasty. We attributed this discrepant clinical manifestation of acute coronary occlusion to coronary collaterals, initially being present and then disappearing following the recanalization procedure, as being responsible for the dramatic clinical picture following the stent thrombosis

Clinical and echocardiographic features of aorto-atrial fistulas

Aorto-atrial fistulas (AAF) are rare but important pathophysiologic conditions of the aorta and have varied presentations such as acute pulmonary edema, chronic heart failure and incidental detection of the fistula. A variety of mechanisms such as aortic dissection, endocarditis with pseudoaneurysm formation, post surgical scenarios or trauma may precipitate the fistula formation. With increasing survival of patients, particularly following complex aortic reconstructive surgeries and redo valve surgeries, recognition of this complication, its clinical features and echocardiographic diagnosis is important. Since physical exam in this condition may be misleading, echocardiography serves as the cornerstone for diagnosis. The case below illustrates aorto-left atrial fistula formation following redo aortic valve surgery with slowly progressive symptoms of heart failure. A brief review of the existing literature of this entity is presented including emphasis on echocardiographic diagnosis and treatment

Giant pedunculated hepatocellular carcinoma with hemangioma mimicking intestinal obstruction

<p>Abstract</p> <p>Background</p> <p>Pedunculated hepatocellular carcinoma (P-HCC) has rarely been reported and is characteristically large and encapsulated. Only sporadic cases have been published, in which P-HCC was combined with other liver tumors (mostly benign), making the diagnosis difficult.</p> <p>Case presentation</p> <p>We report a patient who was admitted to our hospital with clinical features of intestinal obstruction and a palpable mass in the right iliac fossa. Ultrasound, computed tomography and magnetic resonance imaging demonstrated an encapsulated mass of unclear origin and characteristics of liver hemangioma. Laboratory tests revealed elevated α-fetoprotein (> 800 ng/ml) and cancer antigen 125 (> 51.2 U/ml). With a possible diagnosis of giant liver hemangioma, we proceeded to surgery. During surgery, a giant pedunculated tumor was discovered on the inferior surface of the right lobe of the liver, hanging free in the right abdominal cavity towards the right iliac fossa. The macroscopic appearance of the tumor was compatible with liver hemangioma. Tumor resection was performed at a safe distance, including the pedicle. The rest of the liver appeared normal. Histopathological examination revealed grade II and III HCC (according to Edmondson-Steiner's classification) with nodular configuration, central necrosis, and infiltration of the capsule. Underneath the tumor capsule, residual tissue of a cavernous hemangioma was recognized. The resection margins were free of neoplastic tissue.</p> <p>Conclusion</p> <p>This rare presentation of a giant P-HCC combined with a hemangioma with features of intestinal obstruction confirmed the diagnostic difficulties of similar cases, and required prompt surgical treatment. Therefore, patients benefit from surgical resection because both the capsule and the pedicle prevent vascular invasion, therefore improving prognosis.</p

Cushing's syndrome in pregnancy: a review of reported cases

Cushing’s syndrome (CS) causes hypogonadotropic hypogonadism and anovulatory infertility due to hypercortisolism, and it is very rare in pregnancy. CS in pregnancy is associated with important maternal-foetal morbidity and mortality, such as preeclampsia and premature delivery. A systematic search was conducted in the MEDLINE library to retrieve articles reporting cases of CS in pregnant women, during the period between 2010 and 2020.Thirty-five reported cases are presented focusing on the ability of diagnosis, treatment therapies, and foetal outcomes. Diagnosis of CS during pregnancy can be challenging and is often delayed, adrenal adenoma being the predominant cause. Both medical treatment and surgery aiming at restoring the cortisol balance reduce maternal and foetal complications

Changing outcomes following pelvic exenteration for locally advanced and recurrent rectal cancer

Background Pelvic exenteration for locally advanced rectal cancer (LARC) and locally recurrent rectal cancer (LRRC) is technically challenging but increasingly performed in specialist centres. The aim of this study was to compare outcomes of exenteration over time. Methods This was a multicentre retrospective study of patients who underwent exenteration for LARC and LRRC between 2004 and 2015. Surgical outcomes, including rate of bone resection, flap reconstruction, margin status and transfusion rates, were examined. Outcomes between higher- and lower-volume centres were also evaluated. Results Some 2472 patients underwent pelvic exenteration for LARC and LRRC across 26 institutions. For LARC, rates of bone resection or flap reconstruction increased from 2004 to 2015, from 3.5 to 12.8 per cent, and from 12.0 to 29.4 per cent respectively. Fewer units of intraoperative blood were transfused over this interval (median 4 to 2 units; P = 0.040). Subgroup analysis showed that bone resection and flap reconstruction rates increased in lower- and higher-volume centres. R0 resection rates significantly increased in low-volume centres but not in high-volume centres over time (low-volume: from 62.5 to 80.0 per cent, P = 0.001; high-volume: from 83.5 to 88.4 per cent, P = 0.660). For LRRC, no significant trends over time were observed for bone resection or flap reconstruction rates. The median number of units of intraoperative blood transfused decreased from 5 to 2.5 units (P < 0.001). R0 resection rates did not increase in either low-volume (from 51.7 to 60.4 per cent; P = 0.610) or higher-volume (from 48.6 to 65.5 per cent; P = 0.100) centres. No significant differences in length of hospital stay, 30-day complication, reintervention or mortality rates were observed over time. Conclusion Radical resection, bone resection and flap reconstruction rates were performed more frequently over time, while transfusion requirements decreased

Perioperative management and anaesthetic considerations in pelvic exenterations using Delphi methodology: Results from the PelvEx Collaborative

Background: The multidisciplinary perioperative and anaesthetic management of patients undergoing pelvic exenteration is essential for good surgical outcomes. No clear guidelines have been established, and there is wide variation in clinical practice internationally. This consensus statement consolidates clinical experience and best practice collectively, and systematically addresses key domains in the perioperative and anaesthetic management. Methods: The modified Delphi methodology was used to achieve consensus from the PelvEx Collaborative. The process included one round of online questionnaire involving controlled feedback and structured participant response, two rounds of editing, and one round of web-based voting. It was held from December 2019 to February 2020. Consensus was defined as more than 80 per cent agreement, whereas less than 80 per cent agreement indicated low consensus. Results: The final consensus document contained 47 voted statements, across six key domains of perioperative and anaesthetic management in pelvic exenteration, comprising preoperative assessment and preparation, anaesthetic considerations, perioperative management, anticipating possible massive haemorrhage, stress response and postoperative critical care, and pain management. Consensus recommendations were developed, based on consensus agreement achieved on 34 statements. Conclusion: The perioperative and anaesthetic management of patients undergoing pelvic exenteration is best accomplished by a dedicated multidisciplinary team with relevant domain expertise in the setting of a specialized tertiary unit. This consensus statement has addressed key domains within the framework of current perioperative and anaesthetic management among patients undergoing pelvic exenteration, with an international perspective, to guide clinical practice, and has outlined areas for future clinical research

Contemporary Management of Locally Advanced and Recurrent Rectal Cancer: Views from the PelvEx Collaborative

Pelvic exenteration is a complex operation performed for locally advanced and recurrent pelvic cancers. The goal of surgery is to achieve clear margins, therefore identifying adjacent or involved organs, bone, muscle, nerves and/or vascular structures that may need resection. While these extensive resections are potentially curative, they can be associated with substantial morbidity. Recently, there has been a move to centralize care to specialized units, as this facilitates better multi-disciplinary care input. Advancements in pelvic oncology and surgical innovation have redefined the boundaries of pelvic exenterative surgery. Combined with improved neoadjuvant therapies, advances in diagnostics, and better reconstructive techniques have provided quicker recovery and better quality of life outcomes, with improved survival This article provides highlights of the current management of advanced pelvic cancers in terms of surgical strategy and potential future developments