Ultrasound-guided core needle biopsy of deep fascia: A cadaveric study evaluating feasibility, accuracy and reliability.

Over the past few decades, researchers and clinicians have dedicated significant attention to fascial tissues. Current interest focuses on their anatomical and pathophysiological features. Breakthroughs in ultrasound (US) and magnetic resonance imaging (MRI) have enhanced our ability to study the dynamics and alterations of the tissue structures. However, a microscopic perspective is also essential for a comprehensive understanding of some pathologies of the fasciae. The aim of this study was to investigate, using a cadaveric study: (1) the ease of visualization of the landmarks used for the US-guided fascial core needle biopsy (CNB); (2) the consistency and accuracy of needle placement inside fascial layers using US guidance and confirmed by histological examination; (3) inter-rater reliability. We assessed the feasibility of US-guided CNB in different topographical regions of human cadavers: the thoracolumbar fascia (TLF), fascia lata (FL), and crural fascia (CF). The results, confirmed by histological examination, revealed no significant difference in needle placements between the in-plane approaches in the long and short axes for all locations and fasciae studied (long axis: 91.88%; short axis: 96.22%); p > 0.05. US-guided core needle biopsy with the in-plane approach is feasible, consistent and reliable. It could provide most or all of high-quality fascial tissue samples required for pathological examination. It could also reveal changes in fascial pathologies, capturing the exact site of pathology thanks to US guidance, in particular in patchy diseases such as eosinophilic fasciitis.

Beamforming-integrated neural networks for ultrasound imaging.

Sparse matrix beamforming (SMB) is a computationally efficient reformulation of delay-and-sum (DAS) beamforming as a single sparse matrix multiplication. This reformulation can potentially dovetail with machine learning platforms like TensorFlow and PyTorch that already support sparse matrix operations. In this work, using SMB principles, we present the development of beamforming-integrated neural networks (BINNs) that can rationally infer ultrasound images directly from pre-beamforming channel-domain radiofrequency (RF) datasets. To demonstrate feasibility, a toy BINN was first designed with two 2D-convolution layers that were respectively placed both before and after an SMB layer. This toy BINN correctly updated kernel weights in all convolution layers, demonstrating efficiency in both training (PyTorch - 133 ms, TensorFlow - 22 ms) and inference (PyTorch - 4 ms, TensorFlow - 5 ms). As an application demonstration, another BINN with two RF-domain convolution layers, an SMB layer, and three image-domain convolution layers was designed to infer high-quality B-mode images in vivo from single-shot plane-wave channel RF data. When trained using 31-angle compounded plane wave images (3000 frames from 22 human volunteers), this BINN showed mean-square logarithmic error improvements of 21.3 % and 431 % in the inferred B-mode image quality respectively comparing to an image-to-image convolutional neural network (CNN) and an RF-to-image CNN with the same number of layers and learnable parameters (3,777). Overall, by including an SMB layer to adopt prior knowledge of DAS beamforming, BINN shows potential as a new type of informed machine learning framework for ultrasound imaging.

Differences in Abdominal and Lumbar Muscle Thickness and Contractile Function Between Nulliparous, Primiparous, and Multiparous Women 6 Months Postpartum.

OBJECTIVE: The purpose of this study was to evaluate the differences between primiparous and multiparous women at 6 months postpartum and nulliparous women regarding the thickness (including thickness pattern) and contractile function of the abdominal and lumbar muscles. METHODS: A cross-sectional observational study of 80 women, both primiparous (n = 29) and multiparous (n = 25), as well as including nulliparous as a comparison group (n = 26), was conducted. B-mode ultrasound imaging was used for the measurement of abdominal and lumbar muscle thickness in 2 conditions (resting and activation). Moreover, the contractile function of these muscles was determined by the thickness ratio. RESULTS: Significant differences between groups were observed in abdominal muscle thickness. During activation, the obliques showed a lower thickness in both groups of postpartum women compared to nulliparous women, while lower values for the thickness for the transverse abdominis (TrA) were only observed in primiparous women. The thickness pattern observed in nulliparous women both in resting and in activation (internal oblique [IO] > external oblique [EO] > TrA) was also achieved among postpartum women, despite no statistical differences observed between IO and EO in these groups. No significant differences between groups were observed for contractile function, showing the TrA greater values, followed by IO and EO in both nulliparous and postpartum women. CONCLUSIONS: This study suggests that the thickness (and the thickness pattern) of the abdominal muscles in women at 6 months postpartum differs from nulliparous, while for the lumbar muscles, it is comparable to nulliparous. However, despite the obliques being thinner in postpartum women, the abdominal muscles are functionally competent. IMPACT: This is believed to be the first study to compare abdominal and lumbar muscles thickness and contractile function specifically between primiparous and multiparous women. Although at 6 months' postpartum abdominal thickness differs from nulliparous women, these muscles are functionally competent. These findings provide valuable insights for use in the development of postpartum interventions.

Advancements in sarcopenia diagnosis: from imaging techniques to non-radiation assessments.

Sarcopenia is a prevalent condition with significant clinical implications, and it is expected to escalate globally, demanding for effective diagnostic strategies, possibly at an early stage of the disease. Imaging techniques play a pivotal role in comprehensively evaluating sarcopenia, offering insights into both muscle quantity and quality. Among all the imaging techniques currently used for the diagnosis and follow up of sarcopenia, it is possible to distinguish two classes: Rx based techniques, using ionizing radiations, and non-invasive techniques, which are based on the use of safe and low risk diagnostic procedures. Dual-energy x-ray Absorptiometry and Computed Tomography, while widely utilized, entail radiation exposure concerns. Ultrasound imaging offers portability, real-time imaging, and absence of ionizing radiation, making it a promising tool Magnetic Resonance Imaging, particularly T1-weighted and Dixon sequences, provides cross- sectional and high-resolution images and fat-water separation capabilities, facilitating precise sarcopenia quantification. Bioelectrical Impedance Analysis (BIA), a non-invasive technique, estimates body composition, including muscle mass, albeit influenced by hydration status. Standardized protocols, such as those proposed by the Sarcopenia through Ultrasound (SARCUS) Working Group, are imperative for ensuring consistency across assessments. Future research should focus on refining these techniques and harnessing the potential of radiomics and artificial intelligence to enhance diagnostic accuracy and prognostic capabilities in sarcopenia.

Role of Radiology in the Diagnosis and Treatment of Breast Cancer in Women: A Comprehensive Review.

Breast cancer remains a leading cause of morbidity and mortality among women worldwide. Early detection and precise diagnosis are critical for effective treatment and improved patient outcomes. This review explores the evolving role of radiology in the diagnosis and treatment of breast cancer, highlighting advancements in imaging technologies and the integration of artificial intelligence (AI). Traditional imaging modalities such as mammography, ultrasound, and magnetic resonance imaging have been the cornerstone of breast cancer diagnostics, with each modality offering unique advantages. The advent of radiomics, which involves extracting quantitative data from medical images, has further augmented the diagnostic capabilities of these modalities. AI, particularly deep learning algorithms, has shown potential in improving diagnostic accuracy and reducing observer variability across imaging modalities. AI-driven tools are increasingly being integrated into clinical workflows to assist in image interpretation, lesion classification, and treatment planning. Additionally, radiology plays a crucial role in guiding treatment decisions, particularly in the context of image-guided radiotherapy and monitoring response to neoadjuvant chemotherapy. The review also discusses the emerging field of theranostics, where diagnostic imaging is combined with therapeutic interventions to provide personalized cancer care. Despite these advancements, challenges such as the need for large annotated datasets and the integration of AI into clinical practice remain. The review concludes that while the role of radiology in breast cancer management is rapidly evolving, further research is required to fully realize the potential of these technologies in improving patient outcomes.

Expanding generalized contrast-to-noise ratio into a clinically relevant measure of lesion detectability by considering size and spatial resolution.

Purpose: Early image quality metrics were often designed with clinicians in mind, and ideal metrics would correlate with the subjective opinion of practitioners. Over time, adaptive beamformers and other post-processing methods have become more common, and these newer methods often violate assumptions of earlier image quality metrics, invalidating the meaning of those metrics. The result is that beamformers may "manipulate" metrics without producing more clinical information. Approach: In this work, Smith et al.'s signal-to-noise ratio (SNR) metric for lesion detectability is considered, and a more robust version, here called generalized SNR (gSNR), is proposed that uses generalized contrast-to-noise ratio (gCNR) as a core. It is analytically shown that for Rayleigh distributed data, gCNR is a function of Smith et al.'s C ψ (and therefore can be used as a substitution). More robust methods for estimating the resolution cell size are considered. Simulated lesions are included to verify the equations and demonstrate behavior, and it is shown to apply equally well to in vivo data. Results: gSNR is shown to be equivalent to SNR for delay-and-sum (DAS) beamformed data, as intended. However, it is shown to be more robust against transformations and report lesion detectability more accurately for non-Rayleigh distributed data. In the simulation included, the SNR of DAS was 4.4 ± 0.8 , and minimum variance (MV) was 6.4 ± 1.9 , but the gSNR of DAS was 4.5 ± 0.9 , and MV was 3.0 ± 0.9 , which agrees with the subjective assessment of the image. Likewise, the DAS 2 transformation (which is clinically identical to DAS) had an incorrect SNR of 9.4 ± 1.0 and a correct gSNR of 4.4 ± 0.9 . Similar results are shown in vivo. Conclusions: Using gCNR as a component to estimate gSNR creates a robust measure of lesion detectability. Like SNR, gSNR can be compared with the Rose criterion and may better correlate with clinical assessments of image quality for modern beamformers.

Ultrasound Evaluation of Onset Core Muscle Activity in Subjects with Non-Specific Lower Back Pain and Without Lower Back Pain: An Observational Case-Control Study.

Lower back pain (LBP) has been the leading cause of disability since 1990. Objectives: The main objective of this observational case-control study was to evaluate, using ultrasound, whether there were differences in the onset and ratio of core muscle contraction between subjects with non-specific chronic lower back pain and healthy subjects. Methods: A total of 60 participants (52% women), split between those with non-specific chronic lower back pain (n = 26) and healthy (n = 34) subjects, were recruited. Initial muscle contraction of the lateral abdominal wall, pelvic floor, lumbar multifidus, and respiratory diaphragm was measured using ultrasound. The abdominal drawing-in maneuver, contralateral arm elevation, the Valsalva maneuver, and voluntary contraction of the pelvic floor in seated and standing positions were performed. The muscle thickness of the lateral abdominal wall and lumbar multifidus and excursion of the pelvic floor and diaphragm at rest and during testing were also analyzed. Results: No differences were found between the groups in the initial contraction. Statistically significant differences were found in the following variables: diaphragm excursion (p = 0.032, r = 0.277) and lumbar multifidus ratio (p = 0.010, r = 0.333) in the standing-abdominal retraction maneuver; pelvic floor excursion (p = 0.012, r = 0.325) in the standing-contralateral arm raise; and transverse abdominis ratio (p = 0.033, r = 0.275) in the sitting-contralateral arm raise. A statistically significant interaction between the groups and body mass index was observed in resting diaphragm excursion (p = 0.018, partial eta squared = 0.096) during sitting-voluntary pelvic floor contraction. Conclusions: It cannot be concluded that there is a specific pattern of core activation in any of the groups. However, statistically significant differences were found in the contraction indexes of the lumbopelvic musculature.

Size-Sorted Superheated Nanodroplets for Dosimetry and Range Verification of Carbon-Ion Radiotherapy.

Nanodroplets have demonstrated potential for the range detection of hadron radiotherapies. Our formulation uses superheated perfluorobutane (C4F10) stabilized by a poly(vinyl-alcohol) shell. High-LET (linear energy transfer) particles vaporize the nanodroplets into echogenic microbubbles. Tailored ultrasound imaging translates the generated echo-contrast into a dose distribution map, enabling beam range retrieval. This work evaluates the response of size-sorted nanodroplets to carbon-ion radiation. We studied how thesize of nanodroplets affects their sensitivity at various beam-doses and energies, as a function of concentration and shell cross-linking. First, we show the physicochemical characterization of size-isolated nanodroplets by differential centrifugation. Then, we report on the irradiations of the nanodroplet samples in tissue-mimicking phantoms. We compared the response of large (≈900 nm) and small (≈400 nm) nanodroplets to different carbon-ions energies and evaluated their dose linearity and concentration detection thresholds by ultrasound imaging. Additionally, we verified the beam range detection accuracy for the nanodroplets samples. All nanodroplets exhibited sensitivity to carbon-ions with high range verification precision. However, smaller nanodroplets required a higher concentration sensitivity threshold. The vaporization yield depends on the carbon-ions energy and dose, which are both related to particle count/spot. These findings confirm the potential of nanodroplets for range detection, with performance depending on nanodroplets' properties and beam parameters.

Relationship Between Early and Established Rheumatoid Arthritis Vascular Change of the Dorsalis Pedis Artery Observed with Ultrasound Imaging.

BACKGROUND: Despite early treatment of rheumatoid arthritis (RA) being well established to prevent erosive joint damage, studies report persistent moderate to high disease activity. Other pathologies, for example, rheumatoid vasculitis (RV) may contribute symptoms that may not be captured by existing clinical assessment. OBJECTIVES: To investigate ultrasound-observed changes in the proximal dorsalis pedis artery (DPA) between early (≤ 5 y) and established (>5 y) RA and the RA Disease Activity Index-5 (RADAI-5). METHODS: Participants with early (n = 20) and established RA (n = 20) were recruited. Five parameters of the DPA were examined with a previously established ultrasound method. Independent t-tests and Cohen d statistics assessed differences and effect size between ultrasound parameters and RADAI-5, and the two groups. Pearson correlation assessed associations between ultrasound parameters and RADAI-5. RESULTS: Majority of participants (98%) demonstrated arterial wall thickening regardless of disease duration. However, lumen diameter (Cohen's d = 0.972, p = 0.004) and artery diameter (Cohen's d = 0.694, p = 0.034) were decreased in established RA compared to early RA. No strong associations were found between RADAI-5 and ultrasound parameters, except for lumen diameter in early RA demonstrating a fair association to RADAI-5 (r = 0.445). The mean RADAI-5 score indicated moderate to high disease activity with no difference between early and established RA (p = 0.283). CONCLUSION: Arterial wall thickening of the DPA indicating the precursory changes of RV was observed in most RA participants, with reductions in artery and lumen diameter occurring in established disease. However, the long-standing instrument RADAI-5 may not reflect symptoms and clinical impacts related to vascular changes among people with RA.

In vivo Multi-perspective 3D + t Ultrasound Imaging and Motion Estimation of Abdominal Aortic Aneurysms.

Time-resolved three-dimensional ultrasound (3D + t US) is a promising imaging modality for monitoring abdominal aortic aneurysms (AAAs), providing their 3D geometry and motion. The lateral contrast of US is poor, a well-documented drawback which multi-perspective (MP) imaging could resolve. This study aims to show the feasibility of in vivo multi-perspective 3D + t ultrasound imaging of AAAs for improving the image contrast and displacement accuracy. To achieve this, single-perspective (SP) aortic ultrasound images from three different angles were spatiotemporally registered and fused, and the displacements were compounded. The fused MP had a significantly higher wall-lumen contrast than the SP images, for both patients and volunteers (P < .001). MP radial displacements patterns are smoother than SP patterns in 67% of volunteers and 92% of patients. The MP images from three angles have a decreased tracking error (P < .001 for all participants), and an improved SNRe compared to two out of three SP images (P < .05). This study has shown the added value of MP 3D + t US, improving both image contrast and displacement accuracy in AAA imaging. This is a step toward using multiple or large transducers in the clinic to capture the 3D geometry and strain more accurately, for patient-specific characterization of AAAs.

A Comparative Study on the Consistency of Ultrasound and X-Ray in Assessing Risser Sign.

OBJECTIVES: Adolescent idiopathic scoliosis (AIS) is a 3-dimensional spinal deformity involving lateral curvature, sagittal plane imbalance, and vertebral rotation. In China, AIS affects over 3 million individuals, with 300,000 new cases annually. AIS impacts physical and psychological well-being, necessitating tailored treatment plans based on growth risk factors. This study evaluates the consistency of ultrasound and X-ray assessments of the Risser sign in AIS patients and explores correlations between iliac crest distance and pelvic rotation degree. METHODS: This prospective study enrolled 80 patients diagnosed with AIS from June to September 2023 at Changzhou Sports Hospital. Eligible participants were aged 10-18 with a Cobb angle >10°. Ultrasonographic examinations were conducted by 3 experienced physicians using the VINNO V10 portable ultrasound system. The primary outcome was the Risser stage determined by X-ray and ultrasound, with secondary outcomes including thoracic and thoracic-lumbar segment rotation angles. Statistical analyses included kappa statistics, correlation analyses, and multiple regression. RESULTS: Among the 77 valid cases, 154 iliac wings were evaluated, with a high concordance rate of 77% between ultrasound and X-ray assessments. kappa values for left and right iliac crests were 0.723 and 0.808, respectively. Grouping Risser grades (0-1, 2-3, and 4-5) into 3 categories yielded kappa values of 0.93, 0.96, and 0.93, indicating high consistency. Significant correlations were found between iliac crest distances and rotation angles (left iliac crest distance and left thoracic rotation angle, r = 0.56, P < .001; right iliac crest distance and right thoracic-lumbar rotation angle, r = 0.69, P < .001; right iliac crest distance and right thoracic rotation angle, r = 0.39, P < .01). CONCLUSIONS: Ultrasound is a reliable, radiation-free alternative to X-ray for assessing the Risser sign in AIS patients. Despite observed inconsistencies in intermediate Risser grades, ultrasound's ability to reduce radiation exposure and provide consistent results makes it a valuable tool in clinical practice. Further research is needed to optimize ultrasound techniques and explore its potential for early detection and intervention in scoliosis management.

Ultrasound for infantile midgut malrotation: Techniques, pearls, and pitfalls.

Midgut malrotation with volvulus is a surgical emergency with potentially devastating outcomes which include short gut syndrome necessitating long-term parenteral nutrition, overwhelming sepsis, and death. The clinical presentation is most frequently with bilious vomiting in the first days-weeks of life, which is non-specific and common. Timely imaging investigation is therefore crucial to prevent delays to diagnosis and treatment and avoid unnecessary surgical exploration in infants with non-surgical bilious vomiting. Fluoroscopic upper gastrointestinal contrast series (UGI) has been the first-line imaging modality to investigate midgut malrotation at pediatric surgical centers worldwide. However, there is a growing body of evidence to indicate that ultrasound (US) has greater diagnostic accuracy than UGI in this context. Furthermore, US offers the benefits of accessibility, portability, lack of ionizing radiation, and the ability to identify alternative diagnoses, and is beginning to attract significant attention and consideration in the literature. Over the last 3 years, we have transitioned to an "US-first" pathway for the investigation of midgut malrotation in infants with bilious vomiting. This pictorial essay illustrates our comprehensive approach, describes unique troubleshooting techniques, and highlights the variably published pitfalls we have encountered with the aim of encouraging wider adoption.

ANN uncertainty estimates in assessing fatty liver content from ultrasound data.

Background and objective: This article uses three different probabilistic convolutional architectures applied to ultrasound image analysis for grading Fatty Liver Content (FLC) in Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) patients. Steatosis is a new silent epidemic and its accurate measurement is an impelling clinical need, not only for hepatologists, but also for experts in metabolic and cardiovascular diseases. This paper aims to provide a robust comparison between different uncertainty quantification strategies to identify advantages and drawbacks in a real clinical setting. Methods: We used a classical Convolutional Neural Network, a Monte Carlo Dropout, and a Bayesian Convolutional Neural Network with the goal of not only comparing the goodness of the predictions, but also to have access to an evaluation of the uncertainty associated with the outputs. Results: We found that even if the prediction based on a single ultrasound view is reliable (relative RMSE [5.93%-12.04%]), networks based on two ultrasound views outperform them (relative RMSE [5.35%-5.87%]). In addition, the results show that the introduction of a "not confident" category contributes to increase the percentage of correctly predicted cases and to decrease the percentage of mispredicted cases, especially for semi-intrusive methods. Conclusions: The possibility of having access to information about the confidence with which the network produces its outputs is a great advantage, both from the point of view of physicians who want to use neural networks as computer-aided diagnosis, and for developers who want to limit overfitting and obtain information about dataset problems in terms of out-of-distribution detection.

Venous Thromboembolism (VTE) in May-Thurner Syndrome: Decision-Making Related to Long-Term Anticoagulation.

May-Thurner syndrome (MTS) involves the compression of the left iliac vein between the right iliac artery anteriorly and the lumbar vertebrae posteriorly. Patients may remain asymptomatic throughout their lives or experience unilateral lower limb swelling and symptoms of deep vein thrombosis (DVT), such as redness and pain in the limb, or features of its complication (pulmonary embolism) such as chest pain or shortness of breath. We present the case of a 34-year-old female exhibiting acute pain and tightness in her left leg, due to DVT of the left common femoral vein, extending up to the pelvic veins, which, on further diagnostic imaging, was found to be due to MTS. The patient was initiated on lifelong anticoagulation to prevent further complications. The rising incidence of MTS, coupled with frequent delays in its diagnosis, highlights the need to raise awareness among healthcare providers, especially acute medics (who are often the first point of contact for the patient) to expand their diagnostic umbrella of differentials to include MTS as a potential cause of such presentations and to look and think beyond DVT of the lower limb. This is especially important in females presenting with non-specific DVT symptoms, as early suspicion and referral to the respective medical teams including vascular medicine, can improve diagnostic accuracy and provide more management options, thereby improving long-term outcomes.

Texture-Based Classification of Fetal Growth Restriction From Intrauterine Neurosonographic Image.

OBJECTIVE: Fetal growth restriction (FGR) is a condition where fetuses fail to reach their genetic potential for growth, posing a significant health challenge for newborns. The aim of this research was to explore the efficacy of texture-based analysis of neurosonographic images in identifying FGR in fetuses, which may provide a promising tool for early assessment of FGR. METHODS: A retrospective analysis collected 100 intrauterine neurosonographic images from 50 FGR and 50 gestational age-appropriate fetuses. Using MaZda software, approximately 300 texture features were extracted from occipital white matter (OWM) and cerebellum of intrauterine neurosonographic images, respectively. Then 10 optimal features were separately selected by 3 algorithms, including the Fisher coefficient method, the method of minimizing classification error probability and average correlation coefficients, and the mutual information coefficient method. Further, the 10 statistically most significant features were selected from these sets to form the mixed feature set. After nonlinear discriminant analysis was performed to reduce feature dimensionality, the artificial neural network (ANN) classifier was conducted, respectively. RESULTS: For OWM and cerebellum, a total of 11 and 14 statistically significant features were selected. When the mixed feature sets of OWM and cerebellum were applied to ANN classifier, classification accuracy were 90.00% (κ = 0.800; P < .001) and 93.00% (κ = 0.860; P < .001), and the receiver operating characteristic curve for identifying FGR showed an area under the curve of 0.82 and 0.87. CONCLUSIONS: Texture analysis of fetal intrauterine neurosonographic images is a feasible and noninvasive strategy for evaluating FGR fetuses.

Analysis of Fetal Growth and Pregnancy Outcome in Pregnant Women Infected with Novel Coronavirus in Mid-Pregnancy.

Purpose: To investigate whether fetal prenatal ultrasound, fetal growth rate, and pregnancy outcome statistically differ between women infected with novel coronavirus (COVID-19) in mid-pregnancy and an uninfected control group. Patients and Methods: A retrospective analysis of biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL), and z-scores for each among 46 pregnant women diagnosed with COVID-19 in mid-pregnancy between December 01, 2022 and June 31, 2023 was conducted. A control group included 92 pregnant women negative for COVID-19 during the same period and was also analyzed. To examine fetal growth, rate of increase in BPD, HC, AC, FL, and estimated fetal weight (EFW) between second and third trimester scans were analyzed. In addition, pregnancy outcome, maternal comorbidities, and neonatal prognosis were assessed. Results: The occurrence of gestational diabetes differed significantly between groups, but the fetal growth rate and EFW did not. Similarly, pregnancy outcomes and neonatal prognoses did not differ significantly between groups. Conclusion: Gestational diabetes was a complication that differed between patients with and without COVID-19 in this study. COVID-19 in pregnant women did not affect fetal development. Therefore, these preliminary data suggest that increased fetal monitoring is not necessary for women infected with COVID-19 during the second trimester, and these women should be reassured of the low risk of adverse fetal outcomes.

A water-immersible scanning mirror with hybrid polymer and elastomer hinges for high-speed and wide-field 3D ultrasound imaging.

This paper reports a new water-immersible single-axis scanning mirror using hybrid polymer and elastomer hinges to achieve both high scanning resonance frequencies and large tilting angles for high-speed and wide-field 3D ultrasound imaging. To demonstrate the concept, a prototype scanning mirror is designed, fabricated, and characterized. The fast- and slow-scanning were achieved by integrating stiff BoPET (biaxially oriented polyethylene terephthalate) and soft elastomer PDMS (Polydimethylsiloxane) hinges, respectively. The testing results have shown a resonance frequency of 270 Hz for the BoPET hinges and a resonance frequency of 10 Hz for the PDMS hinges when the scanning mirror was immersed in water. 3D ultrasound imaging is demonstrated by combining the fast- and slow-scanning together to provide both an augmented field of view (FoV) and high local imaging volume rate.

Utility of ultrasound imaging in monitoring fracture healing in rat femur: Comparison with other imaging modalities.

Objective: Fractures are common injuries and various imaging modalities are employed to diagnose and monitor bone union. However, the follow-up of fracture healing using ultrasound imaging (US) remains a topic of debate. In this study, we analyzed of fracture healing process and compared US and radiological analyses with histological analyses to clarify the characteristics and limitations of each modality. Methods: An osteotomy model was created using the femur of Wistar rats, and US, radiological (radiography and micro-computed tomography (micro-CT)), and histological analyses were performed. Radiological assessments were conducted for the evaluation of calcified tissue. The gap between the bony callus and cartilaginous callus was measured. Results: US effectively captured changes on the fracture surface, potentially reflecting the early healing processes. Both US and radiographic findings showed strong correlation in terms of the decrease in the bony callus gap. US was unable to distinguish cartilaginous callus from the surrounding soft tissue. During the remodeling stage, micro-CT offered a detailed assessment of the internal fracture surface, whereas US was limited to evaluating the outer bone surface and lacked accuracy in visualizing the entire fracture site. Radiography provided a general overview of the fractures. The decrease in the bony callus gap measured using US correlated with the reduction in cartilaginous callus observed histologically. Conclusion: This study demonstrated that US could be a valuable tool for evaluating fracture healing. Combining fracture management with US and radiological examinations may provide a more accurate assessment of healing progress.

Doppler ultrasound imaging and shear wave elastography for evaluation of interstitial fibrosis/tubular atrophy in IgA nephropathy.

PURPOSE: The purpose of this study was to explore the value of Doppler ultrasound imaging and shear wave elastography (SWE) in evaluating renal interstitial fibrosis/tubular atrophy (IFTA). METHODS: During April 2019 and November 2023, biopsy-proven IgA nephropathy (IgAN) patients were enrolled in our study. Conventional ultrasound, Doppler ultrasound imaging and SWE measurements were performed, and related parameters were collected. According to the Oxford classification of IgAN, interstitial fibrosis/tubular atrophy (T) lesions were grouped into T0, T1 and T2 group. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic accuracy of SWE in identifying IFTA. RESULTS: A total of 100 IgAN patients were enrolled in the final cohort. 67 patients were in the T0 group, and 33 patients were in the T1/T2 group. The average SWE values were 42.17 ± 9.11 kPa in the T0 group and 36.83 ± 10.32 kPa in the T1/T2 group (p = 0.01). Multivariate logistic regression revealed that the SWE value and end diastolic velocity (EDV) of the interlobar artery were found to be independent risk factors for IFTA. For the diagnosis of IFTA, the area under the ROC curve (AUC) of SWE alone was 0.652, whereas the AUC of SWE in combination with the EDV was 0.807 (p = 0.008). CONCLUSION: The combination of Doppler ultrasound imaging and SWE measurements could improve the diagnostic performance of quantitative assessment of IFTA in IgAN patients.

Recent Advancements in High-Frequency Ultrasound Applications from Imaging to Microbeam Stimulation.

Ultrasound is a versatile and well-established technique using sound waves with frequencies higher than the upper limit of human hearing. Typically, therapeutic and diagnosis ultrasound operate in the frequency range of 500 kHz to 15 MHz with greater depth of penetration into the body. However, to achieve improved spatial resolution, high-frequency ultrasound (>15 MHz) was recently introduced and has shown promise in various fields such as high-resolution imaging for the morphological features of the eye and skin as well as small animal imaging for drug and gene therapy. In addition, high-frequency ultrasound microbeam stimulation has been demonstrated to manipulate single cells or microparticles for the elucidation of physical and functional characteristics of cells with minimal effect on normal cell physiology and activity. Furthermore, integrating machine learning with high-frequency ultrasound enhances diagnostics, including cell classification, cell deformability estimation, and the diagnosis of diabetes and dysnatremia using convolutional neural networks (CNNs). In this paper, current efforts in the use of high-frequency ultrasound from imaging to stimulation as well as the integration of deep learning are reviewed, and potential biomedical and cellular applications are discussed.