Chemothermal therapy is a new hyperthermia treatment on tumor using heat released from exothermic chemical reaction between the injected reactants and the diseased tissues. With the highly minimally invasive feature and localized heating performance, this method is expected to overcome the ubiquitous shortcomings encountered by many existing hyperthermia approaches in ablating irregular tumor. This review provides a relatively comprehensive review on the latest advancements and state of the art in chemothermal therapy. The basic principles and features of two typical chemothermal ablation strategies (acid-base neutralization-reaction-enabled thermal ablation and alkali-metal-enabled thermal/chemical ablation) are illustrated. The prospects and possible challenges facing chemothermal ablation are analyzed. The chemothermal therapy is expected to open many clinical possibilities for precise tumor treatment in a minimally invasive way.

Zhong-Shan Deng

Jing Liu

Chemothermal Therapy for Localized Heating and Ablation of Tumor

Whole heart segmentation from magnetic resonance imaging or computed tomography is a prerequisite for many clinical applications. Since manual delineation can be tedious and subject to bias, automating such segmentation becomes increasingly popular in the image computing field. However, fully automatic whole heart segmentation is challenging and only limited studies were reported in the literature. This article reviews the existing techniques and analyzes the challenges and methodologies. The techniques are classified in terms of the types of the prior models and the algorithms used to fit the model to unseen images. The prior models include the atlases and the deformable models, and the fitting algorithms are further decomposed into four key techniques including localization of the whole heart, initialization of substructures, refinement of boundary delineation, and regularization of shapes. Finally, the validation issues, challenges, and future directions are discussed.

Xiahai Zhuang

Challenges and Methodologies of Fully Automatic Whole Heart Segmentation: A Review

Cardiovascular disease is the leading cause of morbidity and mortality in the Western World. The inability of fully differentiated, load-bearing cardiovascular tissues to in vivo regenerate and the limitations of the current treatment therapies greatly motivate the efforts of cardiovascular tissue engineering to become an effective clinical strategy for injured heart and vessels. For the effective production of organized and functional cardiovascular engineered constructs in vitro, a suitable dynamic environment is essential, and can be achieved and maintained within bioreactors. Bioreactors are technological devices that, while monitoring and controlling the culture environment and stimulating the construct, attempt to mimic the physiological milieu. In this study, a review of the current state of the art of bioreactor solutions for cardiovascular tissue engineering is presented, with emphasis on bioreactors and biophysical stimuli adopted for investigating the mechanisms influencing cardiovascular tissue development, and for eventually generating suitable cardiovascular tissue replacements.

Diana Massai

Giulia Cerino

Diego Gallo

Francesco Pennella

Marco A. Deriu

Andres Rodriguez

Franco M. Montevecchi

Cristina Bignardi

Alberto Audenino

Umberto Morbiducci

Bioreactors as Engineering Support to Treat Cardiac Muscle and Vascular Disease

The use of a rotary Left Ventricular Assist Device (LVAD) as a bridge-to-recovery treatment is gaining considerable attention in the LVAD research community. Using a mathematical model of the cardiovascular-LVAD system, this paper intends to define the critical control parameters in terms of power and rotational speed of the LVAD to ensure normal dynamics of the aortic valve for different levels of patient's activity and severity of heart failure. The effects of permanent closure of the aortic valve on the hemodynamics of the patient and the pump flow characteristics, if the critical control values are exceeded, are also examined. Additionally, LVAD power and speed control parameters that yield a given percentage of the cardiac cycle during which the aortic valve remains open are examined indicating that the severity of the heart failure is a very important factor in deciding the appropriateness of the LVAD as a bridge-to recovery treatment.

George Faragallah

Marwan A. Simaan

An Engineering Analysis of the Aortic Valve Dynamics in Patients with Rotary Left Ventricular Assist Devices

The orthopedic outpatient department (OPD) ward in a large Thai public hospital is modeled using Discrete-Event Stochastic (DES) simulation. Key Performance Indicators (KPIs) are used to measure effects across various clinical operations during different shifts throughout the day. By considering various KPIs such as wait times to see doctors, percentage of patients who can see a doctor within a target time frame, and the time that the last patient completes their doctor consultation, bottlenecks are identified and resource-critical clinics can be prioritized. The simulation model quantifies the chronic, high patient congestion that is prevalent amongst Thai public hospitals with very high patient-to-doctor ratios. Our model can be applied across five different OPD wards by modifying the model parameters. Throughout this work, we show how DES models can be used as decision-support tools for hospital management.

Waressara Weerawat

Juta Pichitlamken

Peerapong Subsombat

A Generic Discrete-Event Simulation Model for Outpatient Clinics in a Large Public Hospital

Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF) and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM), bagging, and random forest) on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression) increase the prediction accuracy as compared to using gene expression alone.

Hussein Hijazi

Christina Chan

A Classification Framework Applied to Cancer Gene Expression Profiles

Ultrasound is an emerging modality for drug delivery in chemotherapy. This paper reviews this novel technology by first introducing the designs and characteristics of three classes of drug/gene vehicles, microbubble (including nanoemulsion), liposomes, and micelles. In comparison to conventional free drug, the targeted drug-release and delivery through vessel wall and interstitial space to cancerous cells can be activated and enhanced under certain sonication conditions. In the acoustic field, there are several reactions of these drug vehicles, including hyperthermia, bubble cavitation, sonoporation, and sonodynamics, whose physical properties are illustrated for better understanding of this approach. In vitro and in vivo results are summarized, and future directions are discussed. Altogether, ultrasound-mediated drug/gene delivery under imaging guidance provides a promising option in cancer treatment with enhanced agent release and site specificity and reduced toxicity.

Yufeng Zhou

Ultrasound-Mediated Drug/Gene Delivery in Solid Tumor Treatment

Minimally invasive measurement of cardiac output as a central component of advanced haemodynamic monitoring has been increasingly recognised as a potential means of improving perioperative outcomes in patients undergoing major surgery. Methods based upon pulmonary carbon dioxide elimination are among the oldest techniques in this field, with comparable accuracy and precision to other techniques. Modern adaptations of these techniques suitable for use in the perioperative and critical are environment are based on the differential Fick approach, and include the partial carbon dioxide rebreathing method. The accuracy and precision of this approach to cardiac output measurement has been shown to be similar to other minimally invasive techniques. This paper reviews the underlying principles and evolution of the method, and future directions including recent adaptations designed to deliver continuous breath-by-breath monitoring of cardiac output.

Philip J. Peyton

Pulmonary Carbon Dioxide Elimination for Cardiac Output Monitoring in Peri-operative and Critical Care Patients: History and Current Status

Various filtering strategies have been adopted and investigated to suppress the cardiopulmonary resuscitation (CPR) artifact. In this article, two types of artifact removal methods are reviewed: one is the method that removes CPR artifact using only ECG signals, and the other is the method with additional reference signals, such as acceleration, compression depth and transthoracic impedance. After filtering, the signal-to-noise ratio is improved from 0 dB to greater than 2.8 dB, the sensitivity is increased to &gt; 90% as recommended by the American Heart Association, whereas the specificity was far from the recommended 95%, which is considered to be the major drawback of the available artifact removal methods. The overall performance of the adaptive filtering methods with additional reference signal outperforms the methods using only ECG signals. Further research should focus on the refinement of artifact filtering methods and the improvement of shock advice algorithms with the presence of CPR.

Yushun Gong

Bihua Chen

Yongqin Li

A Review of the Performance of Artifact Filtering Algorithms for Cardiopulmonary Resuscitation

Imaging is an essential tool for effective cancer management. Endoscopes are important medical instruments for performing in vivo imaging in hollow organs. Early detection of cancer can be achieved with surveillance using endoscopy, and has been shown to reduce mortality and to improve outcomes. Recently, great advancements have been made in endoscopic instruments, including new developments in optical designs, light sources, optical fibers, miniature scanners, and multimodal systems, allowing for improved resolution, greater tissue penetration, and multispectral imaging. In addition, progress has been made in the development of highly-specific optical probes, allowing for improved specificity for molecular targets. Integration of these new endoscopic instruments with molecular probes provides a unique opportunity for significantly improving patient outcomes and has potential to further improve early detection, image guided therapy, targeted therapy, and personalized medicine. This work summarizes current and evolving endoscopic technologies, and provides an overview of various promising optical molecular probes.

Supang Khondee

Thomas D. Wang

Progress in Molecular Imaging in Endoscopy and Endomicroscopy for Cancer Imaging

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Journal of Healthcare Engineering provides a vehicle for the exchange of advanced knowledge, emerging technologies, and innovative ideas related to all aspects of engineering involved in healthcare delivery processes and systems.

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Journal of Healthcare Engineering - Table of contents 2013

Journal of Healthcare Engineering | Hindawi

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Journal of Healthcare Engineering provides a vehicle for the exchange of advanced knowledge, emerging technologies, and innovative ideas related to all aspects of engineering involved in healthcare delivery processes and systems.

Journal of Healthcare Engineering