Experimental investigation of inter-element isolation in a medical array transducer at various manufacturing stages

This work presents the experimental investigation of vibration maps of a linear array transducer with 192 piezoelements by means of a laser Doppler vibrometer at various manufacturing finishing steps in air and in water. Over the years, many researchers have investigated cross-coupling in fabricated prototypes but not in arrays at various manufacturing stages. Only the central element of the array was driven at its working frequency of 5 MHz. The experimental results showed that the contributions of cross-coupling depend on the elements of the acoustic stack: Lead Zirconate Titanate (PZT), kerf, filler, matching layer, and lens. The oscillation amplitudes spanned from (6 ± 38%) nm to (110 ± 40%) nm when the energized element was tested in air and from (6 ± 57%) nm to (80 ± 67%) nm when measurements were obtained under water. The best inter-element isolation of -22 dB was measured in air after cutting the kerfs, whereas the poorest isolation was -2 dB under water with an acoustic lens (complete acoustic stack). The vibration pattern in water showed a higher standard deviation on the displacement measurements than the one obtained in air, due to the influence of acousto-optic interactions. The amount increased to 30% in water, as estimated by a comparison with the measurements in air. This work describes a valuable method for manufacturers to investigate the correspondence between the manufacturing process and the quantitative evaluations of the resulting effects

Water uptake and swelling in single trabeculæ from human femur head.

The swelling of air-dried single trabeculae from human femur heads was obtained by complete immersion in water and the dimensional changes of the samples were measured over time. The experimental results were analyzed under the viewpoint of the diffusion through a porous material. The dimensional changes of the single trabeculae were 0.26 ± 0.15 percent (length), 0.45 ± 0.25 percent (width) and 1.86 ± 0.97 percent (thickness). The diffusion coefficients were then calculated from the swelling recorded over time and a value of (4.12 ± 0.8) x 10(-10)(m (2)s(-1)) (mean ± standard deviation) was found.   Since the dimensional variations of the specimens is due to the swelling of the collagen bone matrix, this technique could offer new insights for (1) a selective characterization of bone microstructure at the collagen matrix level and (2) the dynamics of diffusion through bone tissue

3D tortuosity and diffusion characterization in the human mineralized collagen fibril using a random walk model

Bone tissue is mainly composed at the nanoscale of apatite minerals, collagen molecules and water that form the mineralized collagen fibril (MCF). In this work, we developed a 3D random walk model to investigate the influence of bone nanostructure on water diffusion. We computed 1000 random walk trajectories of water molecules within the MCF geometric model. An important parameter to analyse transport behaviour in porous media is tortuosity, computed as the ratio between the effective path length and the straight-line distance between initial and final points. The diffusion coefficient is determined from the linear fit of the mean squared displacement of water molecules as a function of time. To achieve more insight into the diffusion phenomenon within MCF, we estimated the tortuosity and diffusivity at different quotes in the longitudinal direction of the model. Tortuosity is characterized by increasing values in the longitudinal direction. As expected, the diffusion coefficient decreases as tortuosity increases. Diffusivity outcomes confirm the findings achieved by experimental investigations. The computational model provides insights into the relation between the MCF structure and mass transport behaviour that may contribute to the improvement of bone-mimicking scaffolds

Finite element model set-up of colorectal tissue for analyzing surgical scenarios

Finite Element Analysis (FEA) has gained an extensive application in the medical field, such as soft tissues simulations. In particular, colorectal simulations can be used to understand the interaction with the surrounding tissues, or with instruments used in surgical procedures. Although several works have been introduced considering small displacements, as a result of the forces exerted on adjacent tissues, FEA applied to colorectal surgical scenarios is still a challenge. Therefore, this work aims to provide a sensitivity analysis on three geometric models, taking in mind different bioengineering tasks. In this way, a set of simulations has been performed using three mechanical models named Linear Elastic, Hyper-Elastic with a Mooney-Rivlin material model, and Hyper-Elastic with a YEOH material model

Influence of wall thickness and diameter on arterial shear wave elastography: a phantom and finite element study

Quantitative, non-invasive and local measurements of arterial mechanical properties could be highly beneficial for early diagnosis of cardiovascular disease and follow up of treatment. Arterial shear wave elastography (SWE) and wave velocity dispersion analysis have previously been applied to measure arterial stiffness. Arterial wall thickness (h) and inner diameter (D) vary with age and pathology and may influence the shear wave propagation. Nevertheless, the effect of arterial geometry in SWE has not yet been systematically investigated. In this study the influence of geometry on the estimated mechanical properties of plates (h = 0.5–3 mm) and hollow cylinders (h = 1, 2 and 3 mm, D = 6 mm) was assessed by experiments in phantoms and by finite element method simulations. In addition, simulations in hollow cylinders with wall thickness difficult to achieve in phantoms were performed (h = 0.5–1.3 mm, D = 5–8 mm). The phase velocity curves obtained from experiments and simulations were compared in the frequency range 200–1000 Hz and showed good agreement (R2 = 0.80 ± 0.07 for plates and R2 = 0.82 ± 0.04 for hollow cylinders). Wall thickness had a larger effect than diameter on the dispersion curves, which did not have major effects above 400 Hz. An underestimation of 0.1–0.2 mm in wall thickness introduces an error 4–9 kPa in hollow cylinders with shear modulus of 21–26 kPa. Therefore, wall thickness should correctly be measured in arterial SWE applications for accurate mechanical properties estimation

Digital design of medical replicas via desktop systems: shape evaluation of colon parts

In this paper, we aim at providing results concerning the application of desktop systems for rapid prototyping of medical replicas that involve complex shapes, as, for example, folds of a colon. Medical replicas may assist preoperative planning or tutoring in surgery to better understand the interaction among pathology and organs. Major goals of the paper concern with guiding the digital design workflow of the replicas and understanding their final performance, according to the requirements asked by the medics (shape accuracy, capability of seeing both inner and outer details, and support and possible interfacing with other organs). In particular, after the analysis of these requirements, we apply digital design for colon replicas, adopting two desktop systems. ,e experimental results confirm that the proposed preprocessing strategy is able to conduct to the manufacturing of colon replicas divided in self-supporting segments, minimizing the supports during printing. ,is allows also to reach an acceptable level of final quality, according to the request of having a 3D presurgery overview of the problems. ,ese replicas are compared through reverse engineering acquisitions made by a structured-light system, to assess the achieved shape and dimensional accuracy. Final results demonstrate that low-cost desktop systems, coupled with proper strategy of preprocessing, may have shape deviation in the range of ±1 mm, good for physical manipulations during medical diagnosis and explanation

Harnessing biofabrication strategies to re-surface osteochondral defects. Repair, enhance, and regenerate

Osteochondral tissue (OC) is a complex and multiphasic system comprising cartilage and subchondral bone. The discrete OC architecture is layered with specific zones characterized by different compositions, morphology, collagen orientation, and chondrocyte phenotypes. To date, the treatment of osteochondral defects (OCD) remains a major clinical challenge due to the low self-regenerative capacity of damaged skeletal tissue, as well as the critical lack of functional tissue substitutes. Current clinical approaches fail to fully regenerate damaged OC recapitulating the zonal structure while granting long-term stability. Thus, the development of new biomimetic treatment strategies for the functional repair of OCDs is urgently needed. Here, we review recent developments in the preclinical investigation of novel functional approaches for the resurfacing of skeletal defects. The most recent studies on preclinical augmentation of OCDs and highlights on novel studies for the in vivo replacement of diseased cartilage are presented

Phenotyping the histopathological subtypes of non-small-cell lung carcinoma: how beneficial is radiomics?

The aim of this study was to investigate the usefulness of radiomics in the absence of well-defined standard guidelines. Specifically, we extracted radiomics features from multicenter computed tomography (CT) images to differentiate between the four histopathological subtypes of non-small-cell lung carcinoma (NSCLC). In addition, the results that varied with the radiomics model were compared. We investigated the presence of the batch effects and the impact of feature harmonization on the models' performance. Moreover, the question on how the training dataset composition influenced the selected feature subsets and, consequently, the model's performance was also investigated. Therefore, through combining data from the two publicly available datasets, this study involves a total of 152 squamous cell carcinoma (SCC), 106 large cell carcinoma (LCC), 150 adenocarcinoma (ADC), and 58 no other specified (NOS). Through the matRadiomics tool, which is an example of Image Biomarker Standardization Initiative (IBSI) compliant software, 1781 radiomics features were extracted from each of the malignant lesions that were identified in CT images. After batch analysis and feature harmonization, which were based on the ComBat tool and were integrated in matRadiomics, the datasets (the harmonized and the non-harmonized) were given as an input to a machine learning modeling pipeline. The following steps were articulated: (i) training-set/test-set splitting (80/20); (ii) a Kruskal-Wallis analysis and LASSO linear regression for the feature selection; (iii) model training; (iv) a model validation and hyperparameter optimization; and (v) model testing. Model optimization consisted of a 5-fold cross-validated Bayesian optimization, repeated ten times (inner loop). The whole pipeline was repeated 10 times (outer loop) with six different machine learning classification algorithms. Moreover, the stability of the feature selection was evaluated. Results showed that the batch effects were present even if the voxels were resampled to an isotropic form and whether feature harmonization correctly removed them, even though the models' performances decreased. Moreover, the results showed that a low accuracy (61.41%) was reached when differentiating between the four subtypes, even though a high average area under curve (AUC) was reached (0.831). Further, a NOS subtype was classified as almost completely correct (true positive rate similar to 90%). The accuracy increased (77.25%) when only the SCC and ADC subtypes were considered, as well as when a high AUC (0.821) was obtained-although harmonization decreased the accuracy to 58%. Moreover, the features that contributed the most to models' performance were those extracted from wavelet decomposed and Laplacian of Gaussian (LoG) filtered images and they belonged to the texture feature class.. In conclusion, we showed that our multicenter data were affected by batch effects, that they could significantly alter the models' performance, and that feature harmonization correctly removed them. Although wavelet features seemed to be the most informative features, an absolute subset could not be identified since it changed depending on the training/testing splitting. Moreover, performance was influenced by the chosen dataset and by the machine learning methods, which could reach a high accuracy in binary classification tasks, but could underperform in multiclass problems.It is, therefore, essential that the scientific community propose a more systematic radiomics approach, focusing on multicenter studies, with clear and solid guidelines to facilitate the translation of radiomics to clinical practice

Model-optimizing radiofrequency parameters of 3D finite element analysis for ablation of benign thyroid nodules

Radiofrequency (RF) ablation represents an efficient strategy to reduce the volume of thyroid nodules. In this study, a finite element model was developed with the aim of optimizing RF parameters, e.g., input power and treatment duration, in order to achieve the target volume reduction rate (VRR) for a thyroid nodule. RF ablation is modelled as a coupled electro-thermal problem wherein the electric field is applied to induce tissue heating. The electric problem is solved with the Laplace equation, the temperature distribution is estimated with the Pennes bioheat equation, and the thermal damage is evaluated using the Arrhenius equation. The optimization model is applied to RF electrode with different active tip lengths in the interval from 5 mm to 40 mm at the 5 mm step. For each case, we also explored the influence of tumour blood perfusion rate on RF ablation outcomes. The model highlights that longer active tips are more efficient as they require lesser power and shorter treatment time to reach the target VRR. Moreover, this condition is characterized by a reduced transversal ablation zone. In addition, a higher blood perfusion increases the heat dispersion, requiring a different combination of RF power and time treatment to achieve the target VRR. The model may contribute to an improvement in patient-specific RF ablation treatment