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Editorial

ASME J of Medical Diagnostics. 2018;1(2):020201-020201-2. doi:10.1115/1.4039559.
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Understanding the influence of stress and strain on biological processes and the properties of biological materials is crucial in unraveling biological mechanisms. This insight came early for muscle physiologists, which is not surprising because they were dealing with a tissue whose function is primarily mechanical in nature. Archibald Hill, a mathematician turned physiologist, first described the relationship between shortening velocity of skeletal muscle as a function of load, and how the relationship was altered by the underlying chemical reactions which manifested themselves as heat production [1]. The hyperbolic force–velocity relationship of muscle contraction was later shown to be the consequence of the interaction between two contractile proteins, actin and myosin, under the physical constraint of a sarcomeric structure [2]. The stochastic process governing the cyclic interaction between actin and myosin is a classic example of mechanobiology where the rate of a chemical reaction (e.g., hydrolysis of adenosine triphosphate (ATP)) is controlled by mechanical strain on the myosin molecules, and the transition between two mechanical states (i.e., detachment of myosin from actin) is controlled by a chemical reaction (release of adenosine diphosphate (ADP) from, and binding of ATP to, myosin) [3]. The stochastic steps within the cross-bridge cycle represent a complex mechanobiochemical process that allow the muscle to contract and ensure the contraction to proceed at maximal efficiency [4]. Muscle, like many biological systems, is a machine that converts energy to mechanical work; we might liken this process to an internal combustion engine that uses gasoline to produce work. Understanding only the biochemistry of ATP hydrolysis without understanding the mechanical cross-bridge cycle to which the chemical reaction is coupled is akin to understanding the chemistry behind the burning of gasoline in open air and not understanding the burning of gasoline in an internal combustion engine.

Commentary by Dr. Valentin Fuster

Review Article

ASME J of Medical Diagnostics. 2018;1(2):020801-020801-7. doi:10.1115/1.4039105.

Bone-anchored prostheses represent a promising solution to numerous medical complications associated with conventional socket-suspended prostheses. The following technical overview was constructed for engineers and orthopedic surgeons interested in osseointegrated implants for transfemoral prosthesis-residuum interfacing. Existing osseointegrated implants comprise different biomaterial compositions (i.e., titanium alloy versus cobalt-chromium-molybdenum alloy) and mechanical designs (i.e., screw-fixated versus press-fixated devices). Perioperative systems of osseointegration surgery include preoperative assessments (i.e., alongside inclusion and exclusion criteria), intraoperative procedures, and postoperative rehabilitation (i.e., static loading and dynamic gait rehabilitation). The intraoperative procedures involve transecting and reorganizing the residual musculature, embedding the implant into the femoral intramedullary cavity, and coupling the osseointegrated implant to an external prosthesis. Postoperative clinical evaluations have demonstrated significant biomechanical, psychological, and physiological improvements in patients using bone-anchored prostheses compared to conventional socket-suspended prostheses. Nevertheless, bacterial infections surrounding the skin-implant bio-interface, often resulting from Staphylococcus aureus or other coagulase-negative staphylococci, remain a relatively frequent medical complication, which can culminate in periprosthetic osteomyelitis and/or implant extraction. The technical overview concludes with discussing the recent Food and Drug Administration humanitarian use device designations, financial analyses between bone-anchored prostheses and socket-suspended prostheses, and applications of vibrotactile osseoperception for augmenting walking and balance feedback control.

Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):020802-020802-23. doi:10.1115/1.4039417.

This is an informed assessment of the state of the art and an extensive inventory of modeling approaches and methods for soft tissue/medical cutting tool interaction and of the associated medical processes and phenomena. Modeling and simulation through numerical, theoretical, computational, experimental, and other methods was discussed in comprehensive review sections each of which is concluded with a plausible prospective discussion biased toward the development of so-called virtual reality (VR) simulator environments. The finalized prospective section reflects on the future demands in the area of soft tissue cutting modeling and simulation mostly from a conceptual angle with emphasis on VR development requirements including real-time VR simulator response, cost-effective “close-to-reality” VR implementations, and other demands. The review sections that serve as the basis for the suggested prospective needs are categorized based on: (1) Major VR simulator applications including virtual surgery education, training, operation planning, intraoperative simulation, image-guided surgery, etc. and VR simulator types, e.g., generic, patient-specific and surgery-specific and (2) Available numerical, theoretical, and computational methods in terms of robustness, time effectiveness, computational cost, error control, and accuracy of modeling of certain types of virtual surgical interventions and their experimental validation, geared toward ethically driven artificial “phantom” tissue-based approaches. Digital data processing methods used in modeling of various feedback modalities in VR environments are also discussed.

Commentary by Dr. Valentin Fuster

Research Papers

ASME J of Medical Diagnostics. 2018;1(2):021001-021001-5. doi:10.1115/1.4038448.

Where heterogeneous material considerations may yield more accurate estimates of long bones' modal characteristics, homogeneous description yields faster approximate solutions. Here, modal frequencies of (bovine) long tibia bones are numerically estimated using the finite element method (FEM) (ANSYS) starting from anatomically accurate computed tomography (CT) scans. Whole long bones are segmented into cortical and cancellous constituents based on Hounsfield (HU) values. Accurate three-dimensional (3D) models are consequently developed. Bones' cortical and cancellous constituents are first treated as heterogeneous material. Relative to stiffness–density relations, stiffness values are assigned for each element yielding a stiffness-graded structure. Calculated modal frequencies are compared to those measured from dynamic experiments. Analysis was repeated where bone properties are homogenized by averaging the stiffness properties of bone constituents. Compared with experimental values of one control long bone, the heterogeneous material assumption returned good estimates of the frequency values in the cranial–caudal (CC) plane with of +0.85% for mode 1 and +10.66% for mode 2. For homogeneous material assumption, underestimates were returned with error values of −13.25% and −0.13% differences for mode 2. In the medial–lateral (ML) plane, heterogeneous material assumption returned good frequency estimates with −8.89% for mode 1 and +1.01% for mode 2. Homogeneous material assumption underestimated the frequency values with error of −20.52% for mode 1 and −7.50% for mode 2. Homogeneous simplifications yielded faster and more memory-efficient FEM runs with heterogeneous modal analysis requiring 1.5 more running time and twice the utilized memory.

Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):021002-021002-8. doi:10.1115/1.4038791.

The aim of this study was to analyze five factors that are responsible for the ablation volume and maximum temperature during the procedure of irreversible electroporation (IRE). The five factors used in this study were the pulse strength (U), the electrode diameter (B), the distance between the electrode and the center (D), the electrode length (L), and the number of electrodes (N). A validated finite element model (FEM) of IRE was built to collect the data of the ablation volume and maximum temperature generated in a liver tissue. Twenty-five experiments were performed, in which the ablation volume and maximum temperature were taken as response variables. The five factors with ranges were analyzed to investigate their impacts on the ablation volume and maximum temperature, respectively, using analysis of variance. Response surface method (RSM) was used to optimize the five factors for the maximum ablation volume without thermal damage (the maximum temperature $≤$ 50 °C for 90 s). U and L were found with significant impacts on the ablation volume (P < 0.001, and P = 0.009, respectively) while the same conclusion was not found for B, D and N (P = 0.886, P = 0.075 and P = 0.279, respectively). Furthermore, U, D, and N had the significant impacts on the maximum temperature with P < 0.001, P < 0.001, and P = 0.003, respectively, while same conclusion was not found for B and L (P = 0.720 and P = 0.051, respectively). The maximum ablation volume of 2952.9960 mm3 without thermal damage can be obtained by using the following set of factors: U = 2362.2384 V, B = 1.4889 mm, D = 7 mm, L = 4.5659 mm, and N = 3. The study concludes that both B and N have insignificant impacts (P = 0.886, and P = 0.279, respectively) on the ablation volume; U has the most significant impact (P < 0.001) on the ablation volume; electrode configuration and pulse strength in IRE can be optimized for the maximum ablation volume without thermal damage using RSM.

Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):021003-021003-7. doi:10.1115/1.4039100.

We have obtained from the Bloch nuclear magnetic resonance (NMR) equations the correct dependence of the single component My and Mz at resonance (NMR/magnetic resonance imaging (MRI)) on relaxation times, rf B1 field (pulsed or continuous), blood(nuclear spin) flow velocity, etc., in the rotating frame of reference. We find that the new formulation for the first time uniquely describes the true relationship between individual single component My or Mz of magnetization of flowing nuclear spin with the above quantities (excluding diffusion and gradient fields) during NMR/MRI excitation. The equations are applicable for both continuous wave (CW) and pulsed NMR experiments with or without flow of spins. Our approaches can be extended easily to include gradient fields and diffusion of spins, if needed in NMR/MRI experiments. We also discuss the application of our equations to a specific case of magnetic resonance (MR) excitation scheme: Free induction decay. The new equations and further equations that can be derived with the methodologies used here can advance the techniques of noninvasive blood flow estimation by MR and also accurate extraction of parameters of clinical importance by enabling accurate simulation of the MR images (of blood flow and tissue) and comparison with experimental MR images. The detailed simulations from the equations will be published in the next paper.

Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):021004-021004-5. doi:10.1115/1.4039140.

The purpose of this paper is to describe novel experiments and methodologies utilizing a distinctive balance platform system to investigate postural responses for moderate to severe vestibular loss and invasive vestibular prosthesis-assisted nonhuman primates (rhesus monkeys). For several millions of vestibular loss sufferers in the U.S., daily living is severely affected in that common everyday tasks, such as getting out of bed at night, maintaining balance on a moving bus, or walking on an uneven surface, may cause a loss of stability leading to falls and injury. Aside from loss of balance, blurred vision and vertigo (perceived spinning sensation) are also debilitating in vestibular-impaired individuals. Although the need for vestibular rehabilitative solutions is apparent, postural responses for a broad range of peripheral vestibular function, and for various stationary and moving support conditions, have not been systematically investigated. For the investigation of implants and prostheses that are being developed toward implementation in humans, nonhuman primates are a key component. The measurement system used in this research was unique. Our platform system facilitated the study of rhesus monkey posture for stationary support surface conditions (quiet stance and head turns) and for dynamic support surface conditions (pseudorandom roll tilts of the support surface). Further, the platform system was used to systematically study postural responses that will serve as baseline measures for future vestibular-focused human and nonhuman primate posture studies.

Topics: Prostheses
Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):021005-021005-11. doi:10.1115/1.4039103.

Cardiovascular disease (CVD) continues to be a leading cause of death. Accordingly, risk models attempt to predict an individual's probability of developing the disease. Risk models are incorporated into calculators to determine the risk for a number of clinical conditions, including the ten-year risk of developing CVD. There is significant variability in the published models in terms of how the clinical measurements are converted to risk factors as well as the specific population used to determine b-weights of these risk factors. Adding to model variability is the fact that numbers are an imperfect representation of a person's health status. Acknowledgment of uncertainty must be addressed for reliable clinical decision-making. This paper analyzes 35 published risk calculators and then generalizes them into one “Super Risk formula” to form a common basis for uncertainty calculations to determine the best risk model to use for an individual. Special error arithmetic, the duals method, is used to faithfully propagate error from model parameters, population averages and patient-specific clinical measures to one risk number and its relative uncertainty. A set of sample patients show that the “best model” is specific to the individual and no one model is appropriate for every patient.

Topics: Errors , Uncertainty , Risk
Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):021006-021006-7. doi:10.1115/1.4039177.

Acute chest syndrome (ACS) is a leading cause of death for those with sickle cell disease (SCD). ACS is defined by the development of a new pulmonary infiltrate on chest X-ray, with fever and respiratory symptoms. Efforts have been made to apply various technologies in the hospital setting to provide earlier detection of ACS than X-ray, but they are expensive, increase radiation exposure to the patient, and are not technologies that are easily transferrable for home use to help with early diagnosis. We present preliminary studies on patients suggesting that acoustical measurements recorded quantitatively with contact sensors (electronic stethoscopes) and analyzed using advanced computational analysis methods may provide an earlier diagnostic indicator of the onset of ACS than is possible with current clinical practice. Novel in silico models of respiratory acoustics utilizing image-based and algorithmically developed lungs with full conducting airway trees support and help explain measured acoustic trends and provide guidance on the next steps in developing and translating a diagnostic approach. More broadly, the experimental and computational techniques introduced herein, while focused on monitoring and predicting the onset of ACS, could catalyze further advances in mobile health (mhealth)-enabled, computer-based auscultative diagnoses for a wide range of cardiopulmonary pathologies.

Topics: Acoustics , Lung
Commentary by Dr. Valentin Fuster
ASME J of Medical Diagnostics. 2018;1(2):021007-021007-11. doi:10.1115/1.4039211.

Exercise-induced fatigue evolves from the initiation of physical work. Nonetheless, the development of an objective method for detecting fatigue based on variation in ambulatory motion parameters measured during exercise is yet to be explored. In this study, the ambulatory motion parameters consisting of kinematic parameters of 23 body segments in addition to muscle tissue oxygen saturation (SmO2), heart rate, and vertical work of eight healthy male subjects during stair climbing tests (SCT) were measured before and after a fatigue protocol utilizing Wingate cycling test. The impacts of fatigue on ambulatory motion and postural behaviors were analyzed using an unsupervised machine learning method classifying angular joint motions. The average of total distance traveled by subjects and the overall body postural behavior showed about 25% decline and 90% variation after fatigue protocol, respectively. Also, higher relative desaturation in SCT1 −64.0 (1.1) compared SCT2 −54.8 (1.1) was measured. Measurements of differences in motion postural states and metabolic indexes after exercises-induced fatigue proved a strong correlation which validates the advantages of inertial motion analysis method for fatigue assessment.

Topics: Fatigue , Kinematics
Commentary by Dr. Valentin Fuster

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