Clinical Engineering Research Articles

ACCE News

Following are excerpts from the November-December issue of ACCE News, the official newsletter of the American College of Clinical Engineering. (This article originally appeared in the November-December 2022 issue of ACCE News and is reprinted with permission.)

US Food and Drug Administration

Corresponding author: Arif Subhan, MS, CCE, FACCE, AAMIF, is the chief biomedical engineer at VA Greater Los Angeles Healthcare System, Los Angeles, CA, and past president of the American College of Clinical Engineering. 11301 Wilshire Blvd, Los Angeles, CA 90073 ([email protected]). The suggestions and views expressed in this article are those of the author. They do not represent the views of the Department of Veterans Affairs or American College of Clinical Engineering. The author declares no conflicts of interest.

Shoulder Rehabilitation Exercises With Kinematic Biofeedback After Arthroscopic Rotator Cuff Repair: Protocol for a New Integrated Rehabilitation Program.

The recovery of scapular and humeral physiological kinematic parameters, as well as the sensorimotor control of movement, plays a primary role in the rehabilitation process after arthroscopic rotator cuff repair. A highly customized rehabilitation approach is required to achieve this aim. Biofeedback can be a useful tool, but there is poor evidence of its application in the rehabilitation after arthroscopic rotator cuff tear repair. The aim of this paper is to outline an innovative exercise-based rehabilitation program exploiting visual biofeedback for the recovery of patients arthroscopically treated for rotator cuff repair. For establishment of the innovative program, a multidisciplinary team involving experts in shoulder surgery, rehabilitation medicine, physical therapy, and biomedical and clinical engineering was formed. Starting from a conventional rehabilitation program, the team selected a set of exercises to be integrated with a biofeedback tool, named the INAIL (National Institute for Insurance against Accidents at Work) Shoulder and Elbow Outpatient program (ISEO program). ISEO is a motion analysis system based on inertial wearable sensors positioned over the thorax, scapula, humerus, and forearm. ISEO can return a visual biofeedback of humerus and scapula angles over time or of the scapula-humeral coordination, with possible overlap of patient-specific or asymptomatic reference values. A set of 12 progressive exercises was defined, divided into four groups based on humerus and scapula movements. Each group comprises 2-4 of the 12 exercises with an increasing level of complexity. Exercises can require the use of a ball, stick, rubber band, and/or towel. For each exercise, we present the starting position of the patient, the modality of execution, and the target position, together with notes about the critical factors to observe. The type of visual biofeedback to adopt is specified, such as the coordination between angles or the variation of a single angle over time. To guide the therapist in customizing the patient's rehabilitation program, a list of operative guidelines is provided. We describe various applications of the ISEO exercise program in terms of frequency and intensity. An innovative rehabilitation program to restore scapular and humeral kinematics after rotator cuff repair based on kinematic biofeedback is presented. Biofeedback is expected to increase patient awareness and self-correction under therapist supervision. Randomized controlled trials are needed to investigate the potential effect of the exercise-based biofeedback in comparison with conventional rehabilitation programs. DERR1-10.2196/35757.

Assessing the Social and Environmental Impact of Healthcare Technologies: Towards an Extended Social Return on Investment

Stroke is the third leading cause of death and disability overall worldwide. Upper limb impairment is a common consequence for stroke survivors, having negative impact on their quality of life. Robotic rehabilitation, through repetitive and monitored movements, can improve their status. Developed by a team of researchers at Politecnico di Milano, AGREE is an exoskeleton for upper limb rehabilitation at the stage gate between translational research and clinical validation. Since the cost of this device is particularly high, the present study aimed to provide a framework for assessing its value. The Social Return on Investment (SROI) method, able to grasp the economic, social and environmental impact of an activity, was applied, using expert opinions of a pool of clinical engineers and healthcare professionals from different Italian hospitals to obtain information. Environmental impacts were estimated through Life Cycle Assessment in terms of CO2 emissions and incorporated in the analysis. Considering a 5-year period, the SROI for a single exoskeleton was 3.75:1, and the SROI for the number of exoskeletons projected to be sold was 2.868:1, thus resulting largely in value for money. This study provides a model for combining economic, social and environmental outcomes that, besides contributing to theory, could be useful for decision-making.

Modeling Under-Dispersed Count Data by the Generalized Poisson Distribution via Two New MM Algorithms

Under-dispersed count data often appear in clinical trials, medical studies, demography, actuarial science, ecology, biology, industry and engineering. Although the generalized Poisson (GP) distribution possesses the twin properties of under- and over-dispersion, in the past 50 years, many authors only treat the GP distribution as an alternative to the negative binomial distribution for modeling over-dispersed count data. To our best knowledge, the issues of calculating maximum likelihood estimates (MLEs) of parameters in GP model without covariates and with covariates for the case of under-dispersion were not solved up to now. In this paper, we first develop a new minimization–maximization (MM) algorithm to calculate the MLEs of parameters in the GP distribution with under-dispersion, and then we develop another new MM algorithm to compute the MLEs of the vector of regression coefficients for the GP mean regression model for the case of under-dispersion. Three hypothesis tests (i.e., the likelihood ratio, Wald and score tests) are provided. Some simulations are conducted. The Bangladesh demographic and health surveys dataset is analyzed to illustrate the proposed methods and comparisons with the existing Conway–Maxwell–Poisson regression model are also presented.

Development of Low-Cost Portable Defibrillator for Sudden Cardiac Arrest Management

Defibrillation is the mainstay of treatment of cardiac arrest especially ventricular fibrillation (VF) which occurs in more than 70%. The survival in out of hospital cardiac arrest is 30–35% in the western world whereas it is low in low socioeconomic countries. At present patients/persons suffering from cardiac arrest especially outside the hospital settings has high mortality of 70% or more. As per American Heart Association guidelines, early defibrillation within minutes is the prime treatment to improve the survival. In a country like India, defibrillators are not available and it may take hours for a victim to reach appropriate centres for defibrillation causing loss of life. However, defibrillators are currently expensive, not readily available. In a vast country, it is difficult for patient to access the major hospitals, lack of beds and other facility causes delay in treatment and death of patients. Hence there is high demand for the development of an alternate defibrillator readily available everywhere. The aim of this paper is development of a low-cost portable disposable defibrillator for the management of cardiac arrest victims. The design consists of an encasing a portable battery with capacitor which stores and delivers biphasic shock of 50 J for paediatric and 150 J for adult via two paddles attached to the assembly. Up to 6 shocks can be delivered with the stored energy. The casing will have a facility to view the heart rhythm such as VF and sinus rhythm via small display. Hence the project is aimed to develop a low-cost ultraportable defibrillator that aims to provide widespread availability, early defibrillation and improve survival. The proposed diagnosing system in hardware design was tested on safety analyser and defibrillator analysers in Clinical Engineering department of Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST) and the accuracy was achieved of 98.03%.

Explainable deep learning-based clinical decision support engine for MRI-based automated diagnosis of temporomandibular joint anterior disk displacement

Background and Objective: MRI is considered the gold standard for diagnosing anterior disc displacement (ADD), the most common temporomandibular joint (TMJ) disorder. However, even highly trained clinicians find it difficult to integrate the dynamic nature of MRI with the complicated anatomical features of the TMJ. As the first validated study for MRI-based automatic TMJ ADD diagnosis, we propose a clinical decision support engine that diagnoses TMJ ADD using MR images and provides heat maps as the visualized rationale of diagnostic predictions using explainable artificial intelligence. Methods: The engine builds on two deep learning models. The first deep learning model detects a region of interest (ROI) containing three TMJ components (i.e., temporal bone, disc, and condyle) in the entire sagittal MR image. The second deep learning model classifies TMJ ADD into three classes (i.e., normal, ADD without reduction, and ADD with reduction) within the detected ROI. In this retrospective study, the models were developed and tested on the dataset acquired between April 2005 to April 2020. The additional independent dataset acquired at a different hospital between January 2016 to February 2019 was used for the external test of the classification model. Detection performance was assessed by mean average precision (mAP). Classification performance was assessed by the area under the receiver operating characteristic (AUROC), sensitivity, specificity, and Youden’s index. 95% confidence intervals were calculated via non-parametric bootstrap to assess the statistical significance of model performances. Results: The ROI detection model achieved mAP of 0.819 at 0.75 intersection over union (IoU) thresholds in the internal test. In internal and external tests, the ADD classification model achieved AUROC values of 0.985 and 0.960, sensitivities of 0.950 and 0.926, and specificities of 0.919 and 0.892, respectively. Conclusions: The proposed explainable deep learning-based engine provides clinicians with the predictive result and its visualized rationale. The clinicians can make the final diagnosis by integrating primary diagnostic prediction obtained from the proposed engine with the patient’s clinical examination findings.

The Larry Tube: Customized 3D Printed Laryngectomy Tubes Following Total Laryngectomy.

To determine whether a custom laryngectomy tube can improve airway symptoms in total laryngectomy patients with atypical anatomy who are unable to use commercial laryngectomy tubes. Furthermore, to exemplify the power of customizable 3D printed medical devices when combined with the expanded access pathway through the FDA. A custom-fabricated laryngectomy tube, manufactured at in-house clinical engineering labs, was utilized for each patient following typical laryngectomy tube protocols. All participants had previously undergone a total laryngectomy. Patients were selected based on critical airway obstruction posing potentially life-threatening scenarios while using commercially available laryngectomy tubes. For all patients involved, there were no further airway obstruction complications or events, and they reported a subjective, significant improvement in comfort after placement of the custom laryngectomy tube. Custom laryngectomy tubes can provide patients with atypical anatomy relief from airway obstructions and improve comfort when commercial options fail to address the anatomic restriction. The process used to develop custom laryngectomy tubes may be relevant for other diseases and patients with atypical anatomies through the expanded access pathway.

The digitization process and the evolution of Clinical Risk Management concept: The role of Clinical Engineering in the operational management of biomedical technologies.

Digital transformation and technological innovation which have influenced several areas of social and productive life in recent years, are now also a tangible and concrete reality in the vast and strategic sector of public healthcare. The progressive introduction of digital technologies and their widespread diffusion in many segments of the population undoubtedly represent a driving force both for the evolution of care delivery methods and for the introduction of new organizational and management methods within clinical structures. The CS Clinical Engineering of the "Spedali Civili Hospital in Brescia" decided to design a path that would lead to the development of a software for the management of biomedical technologies within its competence inside the hospital. The ultimate aim of this path stems from the need of Clinical Engineering Department to have up-to-date, realistic, and systematic control of all biomedical technologies present in the company. "Spedali Civili Hospital in Brescia" is not just one of the most important corporate realities in the city, but it is also the largest hospital in Lombardy and one of the largest in Italy. System development has followed the well-established phases: requirement analysis phase, development phase, release phase and evaluating and updating phase. Finally, cooperation between the various figures involved in the multidisciplinary working group led to the development of an innovative management software called "SIC Brescia". The contribution of the present paper is to illustrate the development of a complex implementation model for the digitization of processes, information relating to biomedical technologies and their management throughout the entire life cycle. The purpose of sharing this path is to highlight the methodologies followed for its realization, the results obtained and possible future developments. This may enable other realities in the healthcare context to undertake the same type of pathway inspired by an accomplished model. Furthermore, future implementation and data collection related to the proposed Key Performance Indicators, as well as the consequent development of new operational management models for biomedical technologies and maintenance processes will be possible. In this way, the Clinical Risk Management concept will also be able to evolve into a more controlled, safe, and efficient system for the patient and the user.

Značaj biomedicinskih inženjera u zdravstvenom sistemu

In order for the Health Technology Management Policy at the state level to be successfully implemented, first of all, adequate personnel are necessary, and among these, biomedical engineers play an important role. Biomedical engineers (clinical engineers) work in a wide range of settings and disciplines in the health sector and play a key role in: innovation, design and development of new technologies in health care; testing, implementation and development of new diagnostic tools and medical equipment; defining safety standards for medical equipment; maintenance of (complex) medical equipment. The Ministry of Health of the Republic of Serbia labeled the biomedical engineering workforce as a "critical workforce". This critical workforce is defined as "a workforce that contributes to critical and essential elements of health technology management, especially in the domain of maintenance and replacement of (complex) medical equipment, now and in the future".

Mesenchymal Stromal/Stem Cell (MSC)-Based Vector Biomaterials for Clinical Tissue Engineering and Inflammation Research: A Narrative Mini Review.

Mesenchymal stromal/stem cells (MSCs) have the ability of self-renewal, the potential of multipotent differentiation, and a strong paracrine capacity, which are mainly used in the field of clinical medicine including dentistry and orthopedics. Therefore, tissue engineering research using MSCs as seed cells is a current trending directions. However, the healing effect of direct cell transplantation is unstable, and the paracrine/autocrine effects of MSCs cannot be effectively elicited. Tumorigenicity and heterogeneity are also concerns. The combination of MSCs as seed cells and appropriate vector materials can form a stable cell growth environment, maximize the secretory features of stem cells, and improve the biocompatibility and mechanical properties of vector materials that facilitate the delivery of drugs and various secretory factors. There are numerous studies on tissue engineering and inflammation of various biomaterials, mainly involving bioceramics, alginate, chitosan, hydrogels, cell sheets, nanoparticles, and three-dimensional printing. The combination of bioceramics, hydrogels and cell sheets with stem cells has demonstrated good therapeutic effects in clinical applications. The application of alginate, chitosan, and nanoparticles in animal models has also shown good prospects for clinical applications. Three-dimensional printing technology can circumvent the shortage of biomaterials, greatly improve the properties of vector materials, and facilitate the transplantation of MSCs. The purpose of this narrative review is to briefly discuss the current use of MSC-based carrier biomaterials to provide a useful resource for future tissue engineering and inflammation research using stem cells as seed cells.

A digital patient-reported outcome (electronic patient-reported outcome) system for patients with severe psychiatric disorders: User-centered development study and study protocol of a multicenter-controlled trial.

The effective treatment of patients with severe psychiatric disorders primarily relies on subjective reporting of symptoms and side-effects. This information is crucial for a clinician's decision regarding medication adjustment. Treatment adjustment usually happens at a low frequency (∼4-8 weeks). In between points of care, patients are left alone with their symptoms and side-effects. This leads to uncertainty regarding the treatment, non-adherence, possible relapse, and rehospitalization. We aim to design a flexible electronic patient-reported outcome (ePRO) system, which allows patients with severe psychiatric disorders to: (a) record their symptoms using an app; (b) share the data with the clinical team at points of care; and (c) utilize the data to support therapy decisions. In this article, we describe the development process which included the following steps: (a) formation of a co-design team; (b) stakeholder interviews with patients, practitioners, and digital health experts to access needs, requirements, and barriers; (c) prototype conceptualization and design; (d) user acceptance testing and refinement; and (e) finalization of the system for testing in a pilottrial. We included input from patients with lived experience of psychiatric disorders, clinical team members, software engineers, and researchers. A prototype system was refined, and iterative changes were made before finalization during a series of operational meetings. The system allows patients to digitally self-report their symptoms and provides longitudinal ePRO symptom data for export into the electronic health record. Routine ePRO collection has the potential to improve outcomes and hereby also reduce health service costs. We have successfully developed a trial-ready ePRO system for severe psychiatric disorders. The findings were incorporated in the planning of a feasibility pilot trial. Assuming feasibility will be established, the system might be subjected to a certification process evaluation of safety and efficacy including a randomized controlled trial.

Need for Improvements in Medical Device Management in Low- and Middle-Income Countries: Applying Learnings from Japan's Experience.

Medical devices provide important infrastructural support in modern healthcare systems. However, in low- and middle-income countries (LMICs), inadequate maintenance and management of devices due to a shortage of healthcare personnel (not only doctors and nurses but also other professionals including biomedical engineers [BMEs]) has resulted in inefficient and weak healthcare systems. High-income countries, including Japan, have resolved these problems by developing human resources and technologies to maintain and manage these systems. In this paper, we discuss the possibility of mitigating these problems in LMICs through human resource development and technology, based on lessons from Japan's experience. The problem of medical device management in LMICs stems from the fact that there are few professionals, such as BMEs, in charge of the management of medical devices and that clinical engineering departments in charge of device management have not been established. Since the 1980s, Japan has introduced a licensing system for BMEs, establishing operational guidelines to clarify their responsibilities within hospitals and using technology to utilize data and reduce workloads. Nevertheless, workload problems and high costs required to introduce computerized management systems persist. Moreover, it would be difficult to implement the same measures as those adopted in Japan in LMICs where there is an overwhelming shortage of medical personnel. It may be necessary to further reduce workloads for data entry and device management; use up-to-date, inexpensive, and user-friendly technology; and train non-BME personnel to operate and maintain equipment.

Retrospective View of Clinical Engineer’s Development Path

Retrospective View of Clinical Engineer’s Development Path

Correlation of the degenerative stage of a disc with magnetic resonance imaging, chemical content, and biomechanical properties of the nucleus pulposus.

Intervertebral disc degeneration (IDD) is closely related to changes in the intervertebral disc (IVD) composition and the resulting viscoelastic properties. IDD is a severe condition because it decreases the disc's ability to resist mechanical loads. Our research aims to understand IDD at the cellular level, specifically the changes in the viscoelastic properties of the nucleus pulposus (NP), which are poorly understood. This study employed a system integrating nanoindentation with Raman spectrometry to correlate biomechanics with subtle changes in the biochemical makeup of the NP. The characterization was, in turn, correlated with the degenerative severity of IVD as assessed using magnetic resonance imaging (MRI) of different patients with spinal stenosis, degenerative spondylolisthesis, and degenerative scoliosis. It is shown that there is an increase in the crosslinking ratio in collagen, a reduction in proteoglycan, and a build-up of minerals upon the rise in the severity level of the disc damage in the NP. Assessment of mechanical characteristics reveals that the increasing disc degeneration makes the NP lose its elasticity, becoming more viscous. This shows that the tissue undergoes abnormalities in weight-bearing ability, which contributes to spinal instability. The correlation of the individual discs shows that grades III and IV have similarities in the changes of Amide I and III toward the storage modulus. In contrast, grades IV and V correlate with mineralization toward the storage modulus. Reduction of proteoglycan has the highest impact on the changes of the storage modulus in all grades of IDD. Connecting compositional alterations to IVD micromechanics at various degrees of degeneration expands our understanding of tissue behavior and provides critical insight into clinical diagnostics, treatment, and tissue engineering.

Global Clinical Engineering Status: Post-COVID19 Review

Many colleagues have written about the global reliance on health technologies whose innovation, deployment and supportcontinue to improve worldwide healthcare and its delivery. The World Health Organization’s-WHO 2007 Resolution WHA60.29called for the effective use of health technologies (HT), in particular medical devices, through proper planning, assessment,acquisition and management.The community of professional clinical engineering (CE) practitioners’ pre-COVID19 stories are captured in the Global ClinicalEngineering Journal. An article from 2022 shows the reasons for the increased contributions of this community especially duringthe pandemic in The Growing Role of Clinical Engineering: Merging Technology at the Point of Care.This article will answer questions such as to how this global reliance was demonstrated during the COVID19 period. How thestatus of the Clinical/Biomedical Engineering (CE/BME) profession that serves at the point of care changed as the world emergesfrom the huge stresses of the pandemic. The article reviews the evolution of the CE profession since 2020, how it partneredwith WHO between 2020-2022 and what lessons were learned in the process. It reports future CE priorities to improve country,regional, and global practice in 2023 and beyond. This timely preliminary report shares important findings related to patientcare support services.

A Review on Understanding the Crystallization Process of Bioglass in Recent Decade

Bioglass is extensively used in clinical and bone tissue engineering, more specifically in orthopaedic as bone substitute in the form of granules or powders because of their excellent bioactivity, biodegradability and biocompatibility. They have the capability to form an integrated bond with bone through degradation and biomineralization at the surface of the living tissues. These activities are mainly driven by the composition, synthesis method and crystallinity of the bioglass. Therefore, in this paper we aimed at reviewing the basics and methods used in assessing the crystallization process of bioglasses and a few insights into crystallization revealed in the recent years. This critical review helps in tailoring and controlling crystallinity for their better applicability.

Fault Analysis and Treatment of GE Brivo MR355 1.5 T Magnetic Resonance Gradient System and Cooling System

The GE Brivo MR355 1.5 T magnetic resonance system is difficult to maintain due to its complex structure and principle. Clinical engineers should be familiar with the basic structure and operation principle of the equipment. After the failure of the equipment occurs, they should first check the error information, combine the fault phenomenon and maintenance manual, clear their thoughts and carefully analyze the possible causes of the failure, and adopt the method of step-by-step elimination, principle analysis and exchange of the same principle. After replacing the chip tantalum capacitor and sumitomo cold head of the same model, the equipment resumed normal operation. As a clinical engineer, regular equipment inspection and preventive maintenance should be done for large equipment, which is conducive to reducing the equipment failure rate.

Abstract 12221: Work Improvement With Novel Remote Monitoring System (Impella Connect) in Clinical Engineer Involving Acute Mechanical Circulatory Support

Introduction: Recent innovations in mechanical circulatory support (MCS) enable physicians to deal with challenging cases with cardiogenic shock. As the number of MCS has increased, the excessive workload of clinical engineers (CEs) who manage MCS has become a serious problem. To overcome such situation, we introduced innovative remote monitoring system of circulatory assist pump catheters (Impella) called Impella Connect (IC) from 2020, which allows medical staff to monitor driving status and alarms of Impella in their mobile devices. Here we reported our experience of IC and the safety and efficacy of our protocol using IC for management of Impella. Methods: We identified 63 Impella cases for cardiogenic shock from 2018 to 2021 in our institution. We utilized Impella 2.5/CP in 53 cases and Impella 5.0 in 10 cases depending on their hemodynamic condition. Before introducing IC (nIC period: n=17), CEs were responsible for Impella management in all time periods and needed to work overtime to manage devices in night time. However, after introducing IC (IC periods: n=46), CEs were responsible only in daytime and non-MCS expert medical stuff were responsible in night time supporting by CEs’ remote monitoring with IC. We retrospectively evaluated the safety and efficacy of our management using IC. Results: Impella insertion was performed emergently in all cases and the 34 cases (53.9 %) were inserted in night time. Average support time was 6.5±0.6 days (nIC 7.7 vs. 6.0 days). We encountered 13 device trouble in nIC periods (purge system in 8, pressure sensor in 4 and pump malfunction in 1) and 14 in IC periods (purge system in 9, pressure sensor in 3 and pump malfunction in 2). Device trouble requiring intervention was not significantly different in both periods (nIC/IC 10 vs. 11 cases, p=0.85) and adverse event related to delayed or inappropriate response was not observed in both periods. The average of overtime working hours of CEs per month was significantly decreasing in IC periods (53.1±16.8 vs. 8.6±2.6 hours per month, p<0.05). Conclusions: Our Impella management using novel remote monitoring system with Impella Connect was safe with no adverse events and effective to reduce overtime work of CEs, which resulted in work improvement of medical stuff involving MCS.

Priority assessment of procuring medical equipment in Turkish hospitals using input-weighted fuzzy logic architecture

Medical devices, which are very expensive in general, are frequently used in all stages of the healthcare. However, as similar to every electronic device, they have a particular lifetime. Over the time, devices may lose their functions and give continuous malfunctions with a need to renew. In addition, outdated technology treats the hospital budget by consuming more energy and requiring more maintenance (and repair) costs. Therefore, hospitals need to be re-equipped with recent high-technology devices by the time. However, several factors may challenge determining the priorities of the medical devices properly. Today, many decision support systems are available and very useful in various fields of clinics. Hence, a decision support system may also be helpful to assist prioritizing renewal requests of medical devices. In this study, an input-weighted fuzzy logic model was designed and implemented using the Matlab programming environment to help clinical engineers in prioritizing the clinicians’ renewal requests. The proposed fuzzy logic model accepts four main criteria of technical service features, financial features, hospital features, and device features by combining twenty sub-criteria from user inputs. 12 field experts obtained these features, feature weights to construct main criteria, fuzzy membership functions, rule base repository, and fuzzification/defuzzification methods of the proposed system. The performance of the developed model was evaluated with a total of 50 authority decisions given in 5 different hospitals. As a result, the proposed input-weighted fuzzy logic model and the field experts reached the same procurement priorities. By utilizing the analysis of variance (ANOVA) test, we found no statistically significant difference between experts’ decisions and simulation results. In addition, the experts reported the efficiency of the proposed system. By comparing the existing studies, we conclude that our approach provides a pioneer model and a Matlab application to determine the procurement priorities for medical devices. However, although the achieved results are impressive, we note that the model needs to be supported by other studies that cover more experienced participants before clinical common use. In the present form the proposed model and the application can give an idea to clinical engineers and managers who are responsible to the procurement processes in clinics. This study has a potential to start studies to develop national-wide procurement decision support systems, in our opinion.