A Review on Machine Learning Applications: CVI Risk Assessment

Comprehensive literature has been published on the development of digital health applications using machine learning methods in cardiovascular surgery. Many machine learning methods have been applied in clinical decision-making processes, particularly for risk estimation models. This review of the literature shares an update on machine learning applications for cardiovascular intervention (CVI) risk assessment. This study selected peer-reviewed scientific publications providing sufficient detail about machine learning methods and outcomes predicting short-term CVI risk in cardiac surgery. Thirteen articles fulfilling pre-set criteria were reviewed and tables were created presenting the relevant characteristics of the studies. The review demonstrates the usefulness of machine learning methods in high-risk CVI applications, identifies the need for improvement, and provides efficient support for future prediction models for the healthcare system

Doğumsal kalp hastalıklarının tamiri için akışkanlar dinamiği hesaplamaları ile ameliyat öncesi planlama

The treatment of complex congenital heart diseases (CHD) requires a careful patient-specific approach and surgical correction plan. In this thesis, a large radiological database was created to provide supportive information for the treatment planning of patients undergoing aortic hypoplasia, pulmonary stenosis, ventricular septal defect (VSD) and Fontan procedure. State-of-the-art repair alternatives using customized baffle and patch designs were virtually generated in the computer through image-based three-dimensional (3D) modeling, and their structural and hemodynamic analysis are evaluated. In aortic repair section, different virtual repair methods were performed for each selected hypopilastic aortic arch models. Blood flow analyzes were compared in preoperative, postoperative and virtual repair models. The methods were examined by computational fluid dynamics analysis in terms of velocity, wall shear stress and pressure distributions. In the pulmonary artery stenosis section, the deformation of the patch material was evaluated by computational structural analysis. In Fontan cases, the aim was to determine the geometry giving the optimum flow distribution from hepatic veins to the lungs. In VSD cases, virtual models obtained after segmentation provided information that could not be obtained from the image data to facilitate the decision whether the obtimum treatment by catheter intervention or surgery. It has been observed that the findings obtained by 3D modeling, virtual repair and numerical analysis can make significant contributions to the process of determining the repair method. Overall this dissertation aims to provide solution-oriented information to planning procedures in CHD treatment and to present more objective, case-specific and reproducible planning options with computerized modeling and numerical simulation techniques in the light of concrete data.Kompleks doğumsal kalp hastalıklarının (CHD) tedavisi hastaya özel dikkatli bir yaklaşım ve onarım planı gerektirir. Bu tez çalışmasında, geniş bir radyolojik veri tabanı oluşturulmuş; aort hipoplazisi, pulmoner darlık, ventrikül septal defekt (VSD) ve Fontan prosedürü uygulanan hastaların tedavi planlamasına mühendislik yaklaşımlarıyla destekleyen yardımcı bilgi sağlamak amaçlı bir yöntem geliştirilmiştir. Görüntü tabanlı üç boyutlu (3B) modelleme, yapıya özel şant ve yama tasarımı, hızlı prototipleme, bilgisayarlı yapısal ve hemodinamik analiz yardımı ile çeşitli sanal tamir yöntemleri ile oluşturulan modeller sonlu eleman analizleri sonrasında karşılaştırılmıştır. Seçilen aort hipopilazisi vakalarının her biri için birbirinden farklı sanal tamirler uygulanarak; kan akışı analizleri ameliyat öncesi, sonrası ve sanal tamir modellerinde karşılaştırılmıştır. Hastaya özel damar geometrisine uygun tamir yöntemi hız, kayma gerilimi ve basınç dağılımları açısından hesaplamalı akışkanlar dinamiği analizi ile irdelenmiştir. Pulmoner arter darlığı bölümünde hastaya özel yamanın deformasyonu da hesaplamalı yapısal analiz ile değerlendirilerek elde edilen modellerde akış simülasyonları yapılmıştır. Fontan vakalarında hasta için ortalama on farklı sanal şant konfigürasyonu oluşturlarak hesaplamalı akış görelleştirmeleri ile optimum akış dağılımını veren geometrinin belirlenmesi amaçlanmıştır. VSD vakalarında segmentasyon sonrası elde edilen sanal modeller ile görüntü verisinden sağlanamayan enformasyon sağlanabilmiş ve tedavinin kateter girişimi ile ya da cerrahi olarak çözümlenmesi kararını kolaylaştıracak bulgular elde edilmiştir. Üç boyutlu modelleme, sanal tamir ve sonlu eleman analizi ile elde edilen bulguların CHD tedavisini belirleme sürecine anlamlı katkılar sağlayabildiği birbirinden farklı hastalıklarda ve farklı damarlarda örnekler ile gözlemlenmiştir. Bu tez, CHD tedavisinde planlama prosedürlerine çözüm odaklı bilgi sağlamayı, bilgisayarlı modelleme ve nümerik simülasyon teknikleriyle daha objektif, vakaya özel ve tekrarlanabilir planlama seçeneklerini somut veriler eşliğinde sunmayı amaçlamaktadır

In vitro measurement of hepatic flow distribution in Fontan vascular conduits: Towards rapid validation techniques

Fontan operation is the last stage of single-ventricle surgical reconstructions that connects superior and inferior vena cava (SVC, IVC) to the pulmonary arteries. The key design objectives in total cavopulmonary connections (TCPC) are to achieve low power loss (PL) and balanced hepatic flow distribution (HFD). Computational fluid dynamics (CFD) played a pivotal role in pre-surgical design of single-ventricle patients. However, the clinical application of current CFD techniques is limited due to their complexity, high computational time and untested accuracy for HFD prediction. This study provides a performance assessment of computationally low-cost steady Reynolds-Averaged Navier-Stokes (RANS) k-ɛ turbulent models for simulation of Fontan hemodynamics. The performance is evaluated based on prediction accuracy for three clinically important Fontan hemodynamic indices: HFD, PL and total pulmonary flow split (TPFS). For this purpose, a low-cost experimental technique is developed for rapid quantification of Fontan performance indices. Experiments and simulations are performed for both an idealized and a complex 3D reconstructed patient-specific TCPC. Time-averaged flow data from phase contrast MRI was used as the boundary conditions for the patient-specific model. For the idealized model, different SVC/IVC flow ratios corresponding to different cardiac outputs and Reynolds’ numbers were examined. This study revealed that steady RANS k-ɛ models are able to estimate the Fontan hemodynamic indices with acceptable accuracy within minutes. Among these, standard k-ɛ two-layer was found to deliver the best agreement with the in vitro data with an average error percentage of 1.7, 2.0 and, 3.9 for HFD, TPFS and, PL, respectively for all cases

Clinical evaluation of decompressive craniectomy in malignant middle cerebral artery infarction using 3d area and volume calculations

Objective: We aimed to measure the craniectomy area using three-dimensional (3D) anatomic area and volume calculations to demonstrate that it can be an effective criterion for evaluating survival and functional outcomes of patients with malignant middle cerebral artery (MCA) infarction. Material and Methods: The patients diagnosed with malignant ischemic stroke between 2013 and 2018, for which they underwent surgery due to deterioration in their neurological function, were retrospectively reviewed. Radiological images of all patients were evaluated; total brain tissue volume, ischemic brain tissue volume, total calvarial bone area, and decompression bone area were measured using 3D anatomical area and volume calculations. Results: In total, 45 patients (27 males and 18 females) had been treated with decompressive craniectomy (DC). The removed bone area was found to be significantly related to the outcome in patients with MCA infarction. The average decompression bone area and mean bone removal rate for patients who died after DC were 112 ± 27 cm2and 20%, whereas these values for surviving patients were 149 ± 29 cm2and 26% (P = 0.001), respectively. At the 6-month follow-up, the average decompression bone area and mean bone removal rate for patients with severe disability were 126 ± 30 cm2and 22.2%, whereas these values for patients without severe disability were 159 cm2± 26 and 28.4% (P = 0.001), respectively. Conclusion: In patients with malignant MCA infarction, the decompression area is associated with favorable functional outcomes, first, survival and second, 6-month modified Rankin scale score distribution after craniectomy