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Applied Sciences
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Current Updates on Ultrasound for Biomedical Applications
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Current Updates on Ultrasound for Biomedical Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 5710

Special Issue Editors

Dr. Andrea Cafarelli

E-Mail Website
Guest Editor
The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
Interests: therapeutic ultrasound; regenerative medicine;ultrasound imaging; targeted drug delivery
Dr. Allegra Conti

E-Mail Website
Guest Editor
Medical Physics Section, Department of Biomedicine and Prevention, University of Rome Tor Vergata, 00133 Roma, RM, Italy
Interests: therapeutic ultrasound; nanoparticle-based theranostics; drug delivery; ultrasound; preclinical models; molecular imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The biomedical applications of ultrasound are experiencing rapid advancements, as technologies, methodologies, and applications are continuously developing. This Special Issue aims to showcase the latest progress in ultrasound research for biomedical purposes, encompassing its diagnostic and therapeutic applications.

We invite contributions that span a wide range of topics including, but not limited to:

  • Diagnostic imaging techniques: advancements in ultrasound imaging methodologies for medical diagnosis.
  • Therapeutic ultrasound: innovations in ultrasound technologies for therapeutic interventions, such as high-intensity focused ultrasound (HIFU) and low-intensity pulsed ultrasound (LIPUS).
  • Ultrasound-triggered drug delivery systems.
  • Interdisciplinary approaches to integrating ultrasound with other biomedical tools.

This Special Issue welcomes high-quality, original research papers addressing the multifaceted significance of ultrasound in biomedical applications. We encourage contributions from experts in academia and industry, aiming to foster a comprehensive dialogue on the current state and future directions of ultrasound technology in the biomedical field.

Dr. Andrea Cafarelli
Dr. Allegra Conti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • therapeutic ultrasound
  • high-intensity focused ultrasound (HIFU)
  • low-intensity pulsed ultrasound (LIPUS)
  • ultrasound-triggered drug delivery
  • ultrasound-responsive materials
  • ultrasound imaging
  • medical ultrasound
  • ultrasound-guided therapies
  • quantitative ultrasound
  • artificial intelligence in ultrasound

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Published Papers (4 papers)

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Research

12 pages, 1769 KiB  
Article
Effect of Controlled Expiratory Pressures on Cerebrovascular Changes During Valsalva Maneuver
by Ju-Yeon Jung, Yeong-Bae Lee and Chang-Ki Kang
Appl. Sci. 2024, 14(22), 10132; https://doi.org/10.3390/app142210132 - 5 Nov 2024
Viewed by 1146
Abstract
This study aimed to investigate the effects of Valsalva maneuver (VM) with the controlled expiratory pressures on vascular stiffness of common carotid artery (CCA) and cerebral hemodynamic changes using diagnostic ultrasonography. Twenty-seven healthy participants (mean and standard deviation of age = 22.78 ± [...] Read more.
This study aimed to investigate the effects of Valsalva maneuver (VM) with the controlled expiratory pressures on vascular stiffness of common carotid artery (CCA) and cerebral hemodynamic changes using diagnostic ultrasonography. Twenty-seven healthy participants (mean and standard deviation of age = 22.78 ± 1.89) performed 30 and 40 mmHg VM. The right CCA stiffness index and pulse wave velocity (PWV) were measured before (PRE) and after (POST) VM. The peak systolic velocity (PSV), resistance index (RI), and heart rate (HR) were measured before (PRE) and after (POST1 and POST2 during the first and the second 15 s, respectively) VM. Near-infrared spectroscopy (NIRS) was utilized to measure regional oxygen saturation (rSO2) and oxyhemoglobin (HbO) on the left and right prefrontal cortex. Stiffness index decreased by 1.76 (p < 0.001) from PRE to POST only after 30 mmHg VM. PWV decreased by 0.69 m/s (p < 0.001, 30 mmHg) and 0.34 m/s (p = 0.022, 40 mmHg) in POST. Conversely, PSV increased by 5.36 cm/s (p = 0.031, 30 mmHg) and 4.77 cm/s (p = 0.04, 40 mmHg) in POST2. Increase in RI (p = 0.017) and decrease in HR (p = 0.003) occurred only after the 40 mmHg VM. Right HbO decreased after 30 mmHg VM (p = 0.023) from PRE to POST1, and right rSO2 increased after 40 mmHg VM (p = 0.036) from VM (during) to POST1. Both 30 and 40 mmHg VM showed a significant improvement in PWV and an increase in PSV. However, at 30 mmHg VM, a significant decrease in HbO was observed after VM owing to increased cerebral oxygen exchange, and at 40 mmHg VM, an rSO2 increase was observed after VM owing to high vascular pressure. Additionally, the increased pressure and rSO2 at 40 mmHg may have been caused by increased RI. The results indicated that the 30 mmHg VM was more effective on CCA stiffness than the 40 mmHg VM. Full article
(This article belongs to the Special Issue Current Updates on Ultrasound for Biomedical Applications)
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17 pages, 6429 KiB  
Article
Element Array Optimization for Skin-Attachable Ultrasound Probes to Improve the Robustness against Positional and Angular Errors
by Takumi Noda, Takashi Azuma, Ichiro Sakuma and Naoki Tomii
Appl. Sci. 2024, 14(20), 9320; https://doi.org/10.3390/app14209320 - 12 Oct 2024
Viewed by 1199
Abstract
Skin-attachable ultrasound probes face challenges in imaging the intended cross-section due to the difficulty in precisely adjusting the position and angle of attachment. While matrix element arrays are capable of imaging any cross-section within a three-dimensional field of view, their implementation presents a [...] Read more.
Skin-attachable ultrasound probes face challenges in imaging the intended cross-section due to the difficulty in precisely adjusting the position and angle of attachment. While matrix element arrays are capable of imaging any cross-section within a three-dimensional field of view, their implementation presents a challenge due to the significant number of required ultrasound elements. We propose a method for optimizing the coordinates and shapes of elements based on the focusing quality onto the imaging points under the positional and angular errors in the element array. A 128-element array was optimized through the proposed method and its imaging performance was evaluated with simulated phantoms. The optimized array demonstrated the ability to clearly visualize the simulated wires, cysts, and blood vessels even with the positional error of 3 mm and the angular error of 20°. These results indicate the feasibility of developing a skin-attachable ultrasound probe that can be easily used in daily life without requiring precise positional and angular accuracy. Full article
(This article belongs to the Special Issue Current Updates on Ultrasound for Biomedical Applications)
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17 pages, 8142 KiB  
Article
DeepSarc-US: A Deep Learning Framework for Assessing Sarcopenia Using Ultrasound Images
by Bahareh Behboodi, Jeremy Obrand, Jonathan Afilalo and Hassan Rivaz
Appl. Sci. 2024, 14(15), 6726; https://doi.org/10.3390/app14156726 - 1 Aug 2024
Cited by 1 | Viewed by 1347
Abstract
Sarcopenia, the age-related loss of skeletal muscle mass, is a core component of frailty that is associated with functional decline and adverse health events in older adults. Unfortunately, the available tools to diagnose sarcopenia are often inaccessible or not user-friendly for clinicians. Point-of-care [...] Read more.
Sarcopenia, the age-related loss of skeletal muscle mass, is a core component of frailty that is associated with functional decline and adverse health events in older adults. Unfortunately, the available tools to diagnose sarcopenia are often inaccessible or not user-friendly for clinicians. Point-of-care ultrasound (US) is a promising tool that has been used to image the quadriceps muscle and measure its thickness (QMT) as a diagnostic criterion for sarcopenia. This measurement can be challenging for clinicians, especially when performed at the bedside using handheld systems or phased-array probes not designed for this use case. In this paper, we sought to automate this measurement using deep learning methods to improve its accuracy, reliability, and speed in the hands of untrained clinicians. In the proposed framework, which aids in better training, particularly when limited data are available, convolutional and transformer-based deep learning models with generic or data-driven pre-trained weights were compared. We evaluated regression (QMT as a continuous output in cm) and classification (QMT as an ordinal output in 0.5 cm bins) approaches, and in the latter, activation maps were generated to interpret the anatomical landmarks driving the model predictions. Finally, we evaluated a segmentation approach to derive QMT. The results showed that both transformer-based models and convolutional neural networks benefit from the proposed framework in estimating QMT. Additionally, the activation maps highlighted the interface between the femur bone and the quadriceps muscle as a key anatomical landmark for accurate predictions. The proposed framework is a pivotal step to enable the application of US-based measurement of QMT in large-scale clinical studies seeking to validate its diagnostic performance for sarcopenia, alone or with ancillary criteria assessing muscle quality or strength. We believe that implementing the proposed framework will empower clinicians to conveniently diagnose sarcopenia in clinical settings and accordingly personalize the care of older patients, leading to improved patient outcomes and a more efficient allocation of healthcare resources. Full article
(This article belongs to the Special Issue Current Updates on Ultrasound for Biomedical Applications)
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9 pages, 1440 KiB  
Article
Difference in Stiffness between Biceps Brachii Muscle Bellies Using Shear Wave Elastography
by Jacqueline Roots, Gabriel S. Trajano, Adam Bretherton, Christopher Drovandi and Davide Fontanarosa
Appl. Sci. 2024, 14(8), 3456; https://doi.org/10.3390/app14083456 - 19 Apr 2024
Viewed by 1298
Abstract
The Shear Wave Elastography of muscles can provide real-time information on the stiffness of muscles; however, the difference in stiffness between biceps brachii muscle bellies requires more research. Understanding the variables that affect muscle stiffness will assist in the development of Shear Wave [...] Read more.
The Shear Wave Elastography of muscles can provide real-time information on the stiffness of muscles; however, the difference in stiffness between biceps brachii muscle bellies requires more research. Understanding the variables that affect muscle stiffness will assist in the development of Shear Wave Elastography as a diagnostic tool for muscle stiffness pathologies. This study’s aim is to determine the Shear Wave Velocity of the short and long head of biceps brachii and the change in stiffness with elbow flexion to create a reliable protocol for pathological muscle assessment. The muscle belly of the short and long heads of bilateral biceps brachii of 38 healthy participants were scanned supine with the arm at full extension and at 30° and 60° elbow flexion. A log transform of the SWV was used as the response variable in the regression analysis, and the intraclass correlation coefficient was determined for reliability. The Shear Wave Velocity of the short head was lower than the long head on average. By fitting Bayesian mixed effect regression models to the data, the estimated posterior predictive mean velocities for the short head at full extension, 30°, and 60° were 3.14 m/s, 2.65 m/s, and 2.62 m/s, respectively; and 3.91 m/s, 3.02 m/s, and 3.15 m/s, respectively, for the long head of the biceps brachii. The intraclass correlation coefficients (0.64–0.92) were good to excellent. Shear Wave Elastography can detect the consistent difference in the stiffness of the two muscle bellies of the biceps brachii at multiple elbow angles. The assessment of muscle stiffness with Shear Wave Elastography should consider the morphology of the muscles. Full article
(This article belongs to the Special Issue Current Updates on Ultrasound for Biomedical Applications)
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