Search Results (11)

Objective: This prospective study investigated the use of H-scan ultrasound (US) imaging as a novel component of a multiparametric radiomic analysis framework for characterizing human breast cancer response to neoadjuvant chemotherapy (NAC) before and early after treatment initiation. Methods: Thirty breast cancer patients scheduled for NAC were scanned using a clinical US system (Logiq E9, GE HealthCare) equipped with a 9L-D linear array transducer. Radiofrequency (RF) data was obtained at baseline (pre-NAC) and after 10% and 30% of the complete dose of chemotherapy. The RF data was analyzed by a bank of 256 frequency-shifted bandpass filters to form H-scan US frequency images. Grayscale texture features were extracted from both B-scan and H-scan US images. In addition, US attenuation coefficient and speckle statistics based on the Nakagami and Burr distributions were estimated from the RF data. Data classification of tumor and peri-tumoral regions was performed using a novel three-dimensional (3D) score map based on support vector machine (SVM) modeling. Unlike conventional classifiers that report only a single prediction score, a 3D score map provides a visual representation of the classifier decision space, enabling interpretation of class separation and treatment-induced shifts in multiparametric US measurements. Results: The dataset was split into 10 disjoint partitions (90% training, 10% testing) to compute area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy measures. Actual patient response to NAC was assessed at surgery and categorized as either pathologic complete response (pCR) or non-pCR. Multiparametric US and data classification results at pre-NAC found AUC values of 0.78 after using only tumor information (p < 0.01), which increased to 0.81 with inclusion of peri-tumoral information (p < 0.01). Significant differences in multiparametric US measures from both cancer response types was found after integration of patient data collected at 10% completion of the NAC regimen (i.e., first NAC cycle), yielding an improved AUC of 0.86 (p < 0.001). Conclusions: Multiparametric US imaging with radiomic features from both the tumor and peri-tumoral regions is a promising noninvasive approach for monitoring early breast cancer response to NAC. Full article

Breast cancer remains the most commonly diagnosed malignancy and a leading cause of cancer-related mortality among women worldwide. Neoadjuvant chemotherapy (NAC) is increasingly used, particularly in aggressive subtypes such as HER2-positive and triple-negative breast cancer, where achieving a pathological complete response (pCR) is strongly associated with improved outcomes. Early and accurate assessment of therapeutic response is therefore essential to enable timely treatment adaptation. Conventional imaging methods—including magnetic resonance imaging (MRI), computed tomography (CT), mammography, and B-mode ultrasound—mainly detect macroscopic tumor shrinkage and often lagging behind biological alterations, as they rely primarily on size-based assessment. Quantitative ultrasound (QUS) is an emerging, non-invasive technique that analyzes raw radiofrequency (RF) ultrasound data to extract spectral, scattering, and attenuation parameters, allowing detailed characterization of tumor microstructure. When combined with parametric mapping, texture analysis, and advanced radiomic or deep learning approaches, QUS can capture subtle tissue alterations at an early stage of therapy and help predict pathological response before conventional imaging detects morphologic change. Integration with molecular and clinical data further enhances predictive performance, enabling adaptive and personalized treatment strategies. This narrative review summarizes current evidence on the clinical utility of QUS in monitoring NAC response in breast cancer, outlines the methodological foundations of this technology, and discusses key challenges to its broader implementation—particularly the need for standardized acquisition and processing protocols, robust interpretive algorithms and large, prospective, multicenter validations to confirm its impact on clinical decision-making and patient outcomes, and to accelerate its translation into precision oncology practice. Full article

This paper proposes the use of quantitative methods for the characterization of tissues by linking, into a single approach, ideas coming from the spectral analysis methods commonly used to determine the attenuation coefficient with the envelope statistics formulation. Initially, the Homodyned K-distribution model used to fit data obtained from ultrasound signal envelopes was reviewed, and the necessary equations to further derive the attenuation coefficient from this model were developed. To test and discuss the performance of these methods, experimental work was conducted in phantoms. To this end, a series of tissue-mimicking materials composed of poly-vinyl alcohol (PVA) loaded with different particles (aluminium, alumina, cellulose) at varying concentrations were manufactured. A single-channel scanning system was employed to analyse these samples. It was verified that quantitative images obtained from the attenuation coefficient and from the scatterer clustering μ parameter (associated with scatterer concentration) effectively discriminate materials exhibiting similar echo envelope patterns, enhancing the information obtained in comparison with the conventional analysis based on B-scans. Additionally, the implementation of quantitative bi-parametric imaging mappings based on both the μ parameter and the attenuation coefficient, as a means to rapidly visualize results and identify areas characterized by specific acoustic features, was also proposed. Full article

This study investigates the application of Phased Array Corrosion Mapping (PACM) as a non-destructive testing (NDT) method for detecting and monitoring corrosion growth on hot stainless steel (SS) surfaces, specifically focusing on SS 304 and SS 316. Conducted across a temperature range of 30 °C to 250 °C, the research evaluates the effectiveness of PACM in high-temperature environments typical of the petrochemical industry. Experiments were conducted using specimens with machined slots and flat-bottom holes (FBHs) to simulate corrosion defects. The results demonstrate that PACM effectively detects and maps corrosion indicators, with color-coded C-scan data facilitating easy interpretation. Temperature variations significantly influenced ultrasound signal characteristics, leading to observable changes in FBH indications, particularly at elevated temperatures. Increased ultrasound attenuation necessitated adjustments in decibel settings to maintain accuracy. SS 304 and SS 316 exhibited distinct responses to temperature changes, with SS 316 showing higher dB values and unique signal behaviors, including increased scattering and noise echoes at elevated temperatures. Detected depths for slots and FBHs correlated closely with designed depths, with deviations generally less than 0.5 mm; however, some instances showed deviations exceeding 2 mm, underscoring the need for careful interpretation. At temperatures above 230 °C, the disbanding of probe elements led to weak or absent signals, complicating data interpretation and requiring adjustments in testing protocols. This study highlights the feasibility and effectiveness of PACM for corrosion detection on hot SS surfaces, providing critical insights into material behavior under thermal conditions. Future research should include physical examination of samples using Scanning Electron Microscopy (SEM) to validate and enhance the reliability of the findings. The integration of non-contact NDT methods and optimization of calibration techniques are essential for improving PACM performance at elevated temperatures. Full article

Angiomyolipoma (AML) are the most common benign solid renal mass. Differentiation from malignant tumours is essential. Imaging features in ultrasound may overlap between malignant lesions, especially between renal cell carcinoma (RCC) and AML. So far, sectional imaging has been necessary for reliable differentiation. The aim of this study is to evaluate the use of the ultrasound-guided attenuation parameter (UGAP), a recently established tool for assessing hepatic steatosis, in the differentiation of AMLs from other renal masses. Therefore, 27 patients with unknown solid renal masses were examined by ultrasound including UGAP. The attenuation was assessed qualitatively by attenuation map and quantitatively in comparison to the surrounding renal tissue. UGAP was applicable in 26/27 patients. Findings were compared with CT/MRI as the current imaging standard. A total of 18 AML and 9 other renal tumours were found. The diagnostic performance of B-Mode (hyperechogenic lesion) ultrasound was 77.8% in identifying AML. The diagnostic performance of the attenuation map showed a diagnostic performance of 92.6%, whereby UGAP measurements were successful in 76.9% of cases. Quantitatively, we found a significant difference (p < 0.034) in mean measured attenuation between AML (0.764 ± 0.162 dB/cm/MHz) vs. other renal tumours (0.658 ± 0.155 dB/cm/MHz). The best performance was found by a combined parameter of a hyperechogenic lesion with a positive attenuation map with an accuracy of 95.0%. In conclusion, UGAP may represent a possibility for differentiating solid renal lesions more accurately by ultrasound, especially classic hyperechoic AMLs from other renal lesions. Further studies are needed to increase the diagnostic reliability further. Full article

In nonlinear ultrasound testing, the relative nonlinear parameter is conveniently measured as a sensitive means of detecting and imaging overall variation of microstructures and damages. Compared to the quadratic nonlinear parameter (${\beta }^{\prime }$), the cubic nonlinear parameter (${\gamma }^{\prime }$), calculated as the third harmonic amplitude divided by the cube of the fundamental amplitude, has generally a higher value, providing better sensitivity in nonlinear parameter mapping. Since the third harmonic amplitude is about two orders of magnitude lower than the fundamental amplitude, efficient excitation and highly sensitive reception of third harmonic is very important. In this paper, we explore an odd harmonic thickness resonant transducer that meets the requirements for pulse-echo third harmonic generation (THG) measurements. We also address the problem of source nonlinearity that may be present in the measured amplitude of the third harmonic and propose a method to properly correct it. First, we measure ${\gamma }^{\prime }$ for a series of aluminum specimens using the through-transmission method to observe the behavior of ${\gamma }^{\prime }$ as a function of specimen thickness and input voltage, and examine the effects of various corrections such as attenuation, diffraction and source nonlinearity. Next, we apply the odd harmonic resonant transducer to pulse-echo THG measurements of precipitation heat-treated specimens. It is shown that such transducer is very effective in generation and detection of fundamental and third harmonics under finite amplitude toneburst excitation. The highly sensitive detectability of ${\gamma }^{\prime }$ are presented as a function of aging time, and the sensitivity of ${\gamma }^{\prime }$ is compared with that of ${\beta }^{\prime }$ and ${{\beta }^{\prime }}^2$. Full article

Systemic inflammation is associated with intestinal inflammation and neuroinflammation by imbalancing the gut–brain axis. Low-intensity pulsed ultrasound (LIPUS) has neuroprotective and anti-inflammatory effects. This study explored LIPUS’s neuroprotective effects against lipopolysaccharide (LPS)-induced neuroinflammation through transabdominal stimulation. Male C57BL/6J mice were intraperitoneally injected with LPS (0.75 mg/kg) daily for seven days, and abdominal LIPUS was applied to the abdominal area for 15 min/day during the last six days. One day after the last LIPUS treatment, biological samples were collected for microscopic and immunohistochemical analysis. Histological examination showed that LPS administration leads to tissue damage in the colon and brain. Transabdominal LIPUS stimulation attenuated colonic damage, reducing histological score, colonic muscle thickness, and villi shortening. Furthermore, abdominal LIPUS reduced hippocampal microglial activation (labeled by ionized calcium-binding adaptor molecule-1 [Iba-1]) and neuronal cell loss (labeled by microtubule-associated protein 2 [MAP2]). Moreover, abdominal LIPUS attenuated the number of apoptotic cells in the hippocampus and cortex. Altogether, our results indicate that abdominal LIPUS stimulation attenuates LPS-induced colonic inflammation and neuroinflammation. These findings provide new insights into the treatment strategy for neuroinflammation-related brain disorders and may facilitate method development through the gut–brain axis pathway. Full article

Background: Modern ultrasound (US) shear-wave dispersion (SWD) and attenuation imaging (ATI) can be used to quantify changes in the viscosity and signal attenuation of the liver parenchyma, which are altered in hepatic steatosis. We aimed to evaluate modern shear-wave elastography (SWE), SWD and ATI for the assessment of hepatic steatosis. Methods: We retrospectively analyzed the US data of 15 patients who underwent liver USs and MRIs for the evaluation of parenchymal disease/liver lesions. The USs were performed using a multifrequency convex probe (1–8 MHz). The quantitative US measurements for the SWE (m/s/kPa), the SWD (kPa-m/s/kHz) and the ATI (dB/cm/MHz) were acquired after the mean value of five regions of interest (ROIs) was calculated. The liver MRI (3T) quantification of hepatic steatosis was performed by acquiring proton density fat fraction (PDFF) mapping sequences and placing five ROIs in artifact-free areas of the PDFF scan, measuring the fat-signal fraction. We correlated the SWE, SWD and ATI measurements to the PDFF results. Results: Three patients showed mild steatosis, one showed moderate steatosis and eleven showed no steatosis in the PDFF sequences. The calculated SWE cut-off (2.5 m/s, 20.4 kPa) value identified 3/4 of patients correctly (AUC = 0.73, p > 0.05). The SWD cut-off of 18.5 m/s/kHz, which had a significant correlation (r = 0.55, p = 0.034) with the PDFF results (AUC = 0.73), identified four patients correctly (p < 0.001). The ideal ATI (AUC = 0.53 (p < 0.05)) cut-off was 0.59 dB/cm/MHz, which showed a significantly good correlation with the PDFF results (p = 0.024). Conclusion: Hepatic steatosis can be accurately detected using all the US-elastography techniques applied in this study, although the SWD and the SWE showed to be more sensitive than the PDFF. Full article

Presently, breast cancer diagnostic methods are dominated by mammography. Although drawbacks of mammography are present including ionizing radiation and patient discomfort, not many alternatives are available. Ultrasound (US) is another method used in the diagnosis of breast cancer, commonly performed on women with dense breasts or in differentiating cysts from solid tumors. Handheld ultrasound (HHUS) and automated breast ultrasound (ABUS) are presently used to generate reflection images which do not contain quantitative information about the tissue. This limitation leads to a subjective interpretation from the sonographer. To rectify the subjective nature of ultrasound, ultrasound tomography (UST) systems have been developed to acquire both reflection and transmission UST (TUST) images. This allows for quantitative assessment of tissue sound speed (SS) and acoustic attenuation which can be used to evaluate the stiffness of the lesions. Another imaging modality being used to detect breast cancer is photoacoustic tomography (PAT). Utilizing much of the same hardware as ultrasound tomography, PAT receives acoustic waves generated from tissue chromophores that are optically excited by a high energy pulsed laser. This allows the user to ideally produce chromophore concentration maps or extract other tissue parameters through spectroscopic PAT. Here, several systems in the area of TUST and PAT are discussed along with their advantages and disadvantages in breast cancer diagnosis. This overview of available systems can provide a landscape of possible intersections and future refinements in cancer diagnosis. Full article

Peripheral nerve blocking (PNB) is a standard procedure to support regional anesthesia. Still, correct localization of the nerve’s structure is needed to avoid adverse effects; thereby, ultrasound images are used as an aid approach. In addition, image-based automatic nerve segmentation from deep learning methods has been proposed to mitigate attenuation and speckle noise ultrasonography issues. Notwithstanding, complex architectures highlight the region of interest lacking suitable data interpretability concerning the learned features from raw instances. Here, a kernel-based deep learning enhancement is introduced for nerve structure segmentation. In a nutshell, a random Fourier features-based approach was utilized to complement three well-known semantic segmentation architectures, e.g., fully convolutional network, U-net, and ResUnet. Moreover, two ultrasound image datasets for PNB were tested. Obtained results show that our kernel-based approach provides a better generalization capability from image segmentation-based assessments on different nerve structures. Further, for data interpretability, a semantic segmentation extension of the GradCam++ for class-activation mapping was used to reveal relevant learned features separating between nerve and background. Thus, our proposal favors both straightforward (shallow) and complex architectures (deeper neural networks). Full article

Acquisition times and storage requirements have become increasingly important in signal-processing applications, as the sizes of datasets have increased. Hence, compressed sensing (CS) has emerged as an alternative processing technique, as original signals can be reconstructed using fewer data samples collected at frequencies below the Nyquist sampling rate. However, further analysis of CS data in both time and frequency domains requires the reconstruction of the original form of the time-domain data, as traditional signal-processing techniques are designed for uncompressed data. In this paper, we propose a signal-processing framework that extracts spectral properties for frequency-domain analysis directly from under-sampled ultrasound CS data, using an appropriate basis matrix, and efficiently converts this into the envelope of a time-domain signal, avoiding full reconstruction. The technique generates more accurate results than the traditional framework in both time- and frequency-domain analyses, and is simpler and faster in execution than full reconstruction, without any loss of information. Hence, the proposed framework offers a new standard for signal processing using ultrasound CS data, especially for small and portable systems handling large datasets. Full article