Search Results (142)

Background/Objectives: Whole-gland surgery or radiotherapy for localized prostate cancer (PCa) can cure the disease but often impair urinary and sexual function. Focal therapy with high-intensity focused ultrasound (HIFU) seeks to eradicate the tumor while sparing uninvolved tissue. We prospectively evaluated oncological control, functional outcomes and safety of MRI-guided focal HIFU in patients with low- or intermediate-risk PCa. Methods: In this prospective, single-arm, phase II feasibility trial (three Austrian centres, 2021–2024), treatment-naive patients with D’Amico low/intermediate-risk, PSA ≤ 15 ng/mL, clinical stage ≤ T2 and MRI-targeted, biopsy-confirmed index lesions underwent lesion-targeted HIFU (Focal One™). The primary endpoint was failure-free survival (FFS: absence of salvage whole-gland or systemic therapy, metastasis or PCa-specific death). Secondary endpoints included biopsy-proven cancer, prostate-specific antigen (PSA), patient-reported symptoms as International Prostate Symptom Score (IPSS), 5-item International Index of Erectile Function (IIEF), Gaudenz Incontinence Questionnaire and adverse events. Planned follow-up was 24 months with PSA every 3 months, mpMRI and biopsies at 12 months, and imaging- or PSA-triggered biopsies thereafter. Results: Fifty-one men were analysed in the per-protocol cohort (median age 67 years, median PSA 7.55 ng/mL). Median treated volume was 12 mL; median procedure time 85 min. At 24 months, FFS was 94.1%: 3/51 patients (5.9%) required salvage radiotherapy. Among 31 patients who underwent follow-up biopsy, 26 (83.9%) had no cancer; the five positives included three ISUP 1, one ISUP2 and one ISUP 4 lesion. Mean PSA fell by 69% at 3 months (to 2.3 ng/mL) and then stabilized under 3 ng/mL, with a mean of 2.7 ± 1.5 ng/mL at 24 months. Transient acute urinary retention occurred in 11/51 (21.6%); no Clavien–Dindo grade ≥ 4 events were reported. IPSS returned to or improved beyond baseline, erectile function largely recovered by 6–12 months, and only one new case of grade 2 incontinence was observed. Conclusions: MRI-guided focal HIFU achieved high two-year failure-free survival with low morbidity and preserved quality of life in carefully selected patients with low- or intermediate-risk PCa. These data support further randomized and longer-term investigations of focal HIFU as an organ-sparing alternative to whole-gland treatment. Full article

Doppler tomography (DT) is a relatively new method that allows the imaging of cross-sections of an object. The method uses a two-transducer ultrasound probe that moves around or along the object in a specific way. Image reconstruction is performed on the basis of the detection of the so-called Doppler signal, which contains Doppler frequencies that identify the stationary heterogeneous structures inside the imaged cross-section of the object. The Doppler tomography method differs significantly from the popular blood flow velocity detection method and should not be confused with it. It can potentially be used to reconstruct 2D and 3D cross-sectional images of structures that reflect the ultrasound wave well, either in medicine for diagnostics or in industry for so-called non-destructive testing. This paper presents simulations of imaging using Doppler tomography. The method and algorithms that can be used for Doppler tomography imaging without the need for complicated measurement systems and calculations were proposed. The influence of selected parameters on DT imaging quality was investigated, and their optimal compromise values for specific conditions were determined. Ways to improve image quality were also discussed. Full article

The aim of this retrospective clinical pilot study is to evaluate multiparametric ultrasound liver parenchyma assessments in the diagnosis of Osler’s disease, and to detect micro-shunts using SRCEUS with quantifications at the capillary level. Material/Method: All examinations were performed by an experienced examiner with a multi-frequency probe on a high-resolution matrix ultrasound device (SC 7-1U), convex probe (Mindray A 20), and were stored digitally in the PACS system. Vascular ultrasound was performed using colour-coded Doppler ultrasound (CCDS) and ultrasound microangiography (UMA). The recent M-Ref tool was utilised for the purpose of liver tissue characterisation, encompassing the domains of shear wave elastography, fat evaluation, and viscosity. Dynamic CEUS, HiFR CEUS, and SR CEUS were performed after the intravenous bolus injection of 1–2.4 mL of ultrasound contrast agent (SonoVue^®). Measurements of SR CEUS capillary changes were performed independently by PACS-stored digital cine loops up to 5 s. Results: In the context of angiomas or haemangiomas, the initial contrast enhancement of echogenic or almost echogenic foci within 25 s without late wash-out was observed in 5/10 cases. In the evaluation of microvasculature, the presence of capsule-proximal shunts in Osler’s disease was observed, resulting in the identification of increased numbers of dilated capillaries within both peripheral and central shunts. In the control group, general liver tissue changes (20 cases) were observed in instances of inflammation (3/20 cases), peripherally in 4/20 cases with micro-shunts in altered parenchyma. In the context of multiparametric ultrasound, 16 out of 30 cases exhibited elevated fibrosis values, with a maximum recorded as high as 1.7 m/s, and in 13 out of 30 cases, there was an increase in fat values up to 0.65 dB/cm/MHz, indicative of moderate steatosis. Additionally, in seven cases, there was an increase in viscosity values up to 2.7 Pa·s, suggesting reactive changes. Conclusions: Recent advancements in medical imaging technology, specifically SR CEUS contrast ultrasound imaging, have led to the development of novel diagnostic tools that facilitate the evaluation of tissue and haemodynamic changes, in addition to capillary alterations, associated with Osler’s disease. Full article

Arthritis and arthrosis are prevalent joint diseases that cause pain and disability, and their early diagnosis is crucial for preventing irreversible damage. Conventional diagnostic methods such as X-ray, ultrasound, and MRI have limitations in early detection, prompting interest in alternative techniques. This work presents the design and clinical evaluation of a prototype device for non-invasive early diagnosis of arthritis (inflammatory joint disease) and arthrosis (osteoarthritis) using infrared thermography and deep neural networks. The portable prototype integrates a Raspberry Pi 4 microcomputer, an infrared thermal camera, and a touchscreen interface, all housed in a 3D-printed PLA enclosure. A custom Flask-based application enables two operational modes: (1) thermal image acquisition for training data collection, and (2) automated diagnosis using a pre-trained ResNet50 deep learning model. A clinical study was conducted at a university clinic in a temperature-controlled environment with 100 subjects (70% with arthritic conditions and 30% healthy). Thermal images of both hands (four images per hand) were captured for each participant, and all patients provided informed consent. The ResNet50 model was trained to classify three classes (healthy, arthritis, and arthrosis) from these images. Results show that the system can effectively distinguish healthy individuals from those with joint pathologies, achieving an overall test accuracy of approximately 64%. The model identified healthy hands with high confidence (100% sensitivity for the healthy class), but it struggled to differentiate between arthritis and arthrosis, often misclassifying one as the other. The prototype’s multiclass ROC (Receiver Operating Characteristic) analysis further showed excellent discrimination between healthy vs. diseased groups (AUC, Area Under the Curve ~1.00), but lower performance between arthrosis and arthritis classes (AUC ~0.60–0.68). Despite these challenges, the device demonstrates the feasibility of AI-assisted thermographic screening: it is completely non-invasive, radiation-free, and low-cost, providing results in real-time. In the discussion, we compare this thermography-based approach with conventional diagnostic modalities and highlight its advantages, such as early detection of physiological changes, portability, and patient comfort. While not intended to replace established methods, this technology can serve as an early warning and triage tool in clinical settings. In conclusion, the proposed prototype represents an innovative application of infrared thermography and deep learning for joint disease screening. With further improvements in classification accuracy and broader validation, such systems could significantly augment current clinical practice by enabling rapid and non-invasive early diagnosis of arthritis and arthrosis. Full article

Due to its portability, non-invasiveness, and real-time capabilities, ultrasound imaging has been widely adopted for liver disease detection. However, conventional ultrasound examinations heavily rely on operator expertise, leading to high workload and inconsistent imaging quality. To address these challenges, we propose a Robotic Ultrasound Scanning System (RUSS) based on reinforcement learning to automate the localization of standard liver planes. It can help reduce physician burden while improving scanning efficiency and accuracy. The reinforcement learning agent employs a Deep Q-Network (DQN) integrated with LSTM to control probe movements within a discrete action space, utilizing the cross-sectional area of the abdominal aorta region as the criterion for standard plane determination. System performance was comprehensively evaluated against a target standard plane, achieving an average Peak Signal-to-Noise Ratio (PSNR) of 24.51 dB and a Structural Similarity Index (SSIM) of 0.70, indicating high fidelity in the acquired images. Furthermore, a mean Dice coefficient of 0.80 for the abdominal aorta segmentation confirmed high anatomical localization accuracy. These preliminary results demonstrate the potential of our method for achieving consistent and autonomous ultrasound scanning. Full article

We report a low-cost protocol and platform for whole-abdomen 3D dynamic contrast-enhanced ultrasound (DCE-US) imaging in mice using a clinical matrix-array transducer. Background/Objectives: This platform addresses common limitations of preclinical ultrasound systems. In particular, these systems often lack real-time volumetric and molecular imaging capabilities. Methods: Using a modified silicone cup and water bath configuration, mice with dual subcutaneous tumors were imaged in vivo on a clinical EPIQ 7 system equipped with an X6-1 transducer. Results: Intravenous administration of targeted microbubbles enabled high-resolution, contrast-mode 3D imaging at multiple time points. Volumetric reconstructions captured both tumors and surrounding anatomy in a single scan, while time–intensity curves and Differential Targeted Enhancement (DTE) analysis revealed greater microbubble uptake in irradiated tumors, consistent with elevated P-selectin expression. Conclusions: This standardized imaging platform enables whole-abdomen molecular DCE-US in preclinical studies, facilitating intra-animal comparisons of vascular and molecular features across lesions or organs. Full article

Background/Objectives: Cystic hygroma is a congenital lymphatic malformation often identified during early pregnancy and frequently associated with chromosomal abnormalities and adverse outcomes. We aimed to appraise the genetic and clinical characteristics of fetuses diagnosed with cystic hygroma in the first/early second trimester, assess the resolution patterns in chromosomally normal cases, and provide insights into prognosis—based on data collected over a 30-year period. Methods: A retrospective cohort study was conducted on 405 consecutive fetuses diagnosed with nuchal cystic hygroma between 8.0 and 14.0 weeks of gestation from 1993 to 2023 at two tertiary care centers. Diagnoses were established using high-resolution transabdominal and transvaginal 3D/4D ultrasonography. All cases underwent prenatal cytogenetic analysis, including karyotyping. Fetuses with a normal karyotype were observed through serial ultrasounds through the remainder of the pregnancy to verify the eventual resolution of hygromas. Both descriptive and inferential statistical methods were used, with p < 0.05 as a cut-off (two-tailed). Results: Of the 405 fetuses, 210 (51.9%) had chromosomal abnormalities, most commonly trisomy 21, while 195 (48.1%) had a normal karyotype. A significantly higher frequency of trisomy 21 was observed compared to other identified chromosomal abnormalities (p < 0.001). In the chromosomally normal group, 85 (43.6%) showed spontaneous resolution of the hygroma within four weeks, and these pregnancies resulted in phenotypically normal live births. Septated hygromas were significantly more frequent in the abnormal karyotype group (71.4%). Conclusions: The finding and diagnosis of cystic hygroma in first trimester and early second-trimester pregnancy represent a strong predictor of chromosomal aneuploidy and warrant comprehensive prenatal genetic testing and close follow-up. However, in the absence of genetic abnormalities and additional malformations, spontaneous resolution is common, and neonatal outcomes are generally favorable. Health systems should provide equitable access to genetic testing and fetal imaging to support accurate diagnosis and informed decisions. Full article

Background/Objectives: Patients with breast cancer who do not achieve a complete response to neoadjuvant chemotherapy (NAC) may benefit from intensified adjuvant systemic therapy. However, such treatment escalation is typically delayed until after tumour resection, which occurs several months into the treatment course. Quantitative ultrasound (QUS) can detect early microstructural changes in tumours and may enable timely identification of non-responders during NAC, allowing for earlier treatment intensification. In our previous prospective observational study, 100 breast cancer patients underwent QUS imaging before and four times during NAC. Machine learning algorithms based on QUS texture features acquired in the first week of treatment were developed and achieved 78% accuracy in predicting treatment response. In the current study, we aimed to validate these algorithms in an independent prospective cohort to assess reproducibility and confirm their clinical utility. Methods: We included breast cancer patients eligible for NAC per standard of care, with tumours larger than 1.5 cm. QUS imaging was acquired at baseline and during the first week of treatment. Tumour response was defined as a ≥30% reduction in target lesion size on the resection specimen compared to baseline imaging. Results: A total of 51 patients treated between 2018 and 2021 were included (median age 49 years; median tumour size 3.6 cm). Most were estrogen receptor–positive (65%) or HER2-positive (33%), and the majority received dose-dense AC-T (n = 34, 67%) or FEC-D (n = 15, 29%) chemotherapy, with or without trastuzumab. The support vector machine algorithm achieved an area under the curve of 0.71, with 86% accuracy, 91% specificity, 50% sensitivity, 93% negative predictive value, and 43% positive predictive value for predicting treatment response. Misclassifications were primarily associated with poorly defined tumours and difficulties in accurately identifying the region of interest. Conclusions: Our findings validate QUS-based machine learning models for early prediction of chemotherapy response and support their potential as non-invasive tools for treatment personalization and clinical trial development focused on early treatment intensification. Full article

Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. While extensively characterized in breast MRI, the role of BPE in contrast-enhanced mammography (CEM) remains uncertain due to inconsistent findings regarding its correlation with breast density and cancer risk. Unlike breast density—standardized through the ACR BI-RADS lexicon—BPE lacks a uniform classification system in CEM, leading to variability in clinical interpretation and research outcomes. To address this gap, we introduce the BPE-CEM Standard Scale (BCSS), a structured four-tiered classification system specifically tailored to the two-dimensional characteristics of CEM, aiming to improve consistency and diagnostic alignment in BPE evaluation. Materials and Methods: In this retrospective single-center study, 213 patients who underwent mammography (MG), ultrasound (US), and contrast-enhanced mammography (CEM) between May 2022 and June 2023 at the “A. Perrino” Hospital in Brindisi were included. Breast density was classified according to ACR BI-RADS (categories A–D). BPE was categorized into four levels: Minimal (< 10% enhancement), Light (10–25%), Moderate (25–50%), and Marked (> 50%). Three radiologists independently assessed BPE in a subset of 50 randomly selected cases to evaluate inter-observer agreement using Cohen’s kappa. Correlations between BPE, breast density, and age were examined through regression analysis. Results: BPE was Minimal in 57% of patients, Light in 31%, Moderate in 10%, and Marked in 2%. A significant positive association was found between higher breast density (BI-RADS C–D) and increased BPE (p < 0.05), whereas lower-density breasts (A–B) were predominantly associated with minimal or light BPE. Regression analysis confirmed a modest but statistically significant association between breast density and BPE (R² = 0.144), while age showed no significant effect. Inter-observer agreement for BPE categorization using the BCSS was excellent (κ = 0.85; 95% CI: 0.78–0.92), supporting its reproducibility. Conclusions: Our findings indicate that breast density is a key determinant of BPE in CEM. The proposed BCSS offers a reproducible, four-level framework for standardized BPE assessment tailored to the imaging characteristics of CEM. By reducing variability in interpretation, the BCSS has the potential to improve diagnostic consistency and facilitate integration of BPE into personalized breast cancer risk models. Further prospective multicenter studies are needed to validate this classification and assess its clinical impact. Full article

Background: Peyronie’s disease (PD) is a chronic inflammatory condition that affects the penile albuginea. Oxidative stress (OS) plays a crucial role in the development of the disease, prompting us to investigate OS levels at the site of the disease and in peripheral blood. This article presents our second study in which the OS was evaluated by calculating the OS index (OSI) in blood samples taken directly from the penile corpora cavernosa of patients with PD. Our innovative diagnostic method, which focuses on the analysis of oxidative stress (OS) in the corpora cavernosa of the penis, allows us to accurately identify the “chemical” signals (OS levels) of the pathology in the area where it is present. Methods: Our study included 102 PD patients from our Peyronie’s care center and 100 control cases. To conduct a comprehensive OS analysis, we measured both the total oxidant status (TOS) and total antioxidant status (TAS) and calculated the oxidative stress index (OSI) as OSI = TOS/TAS × 100. Blood samples were collected from the penis and a vein in the upper extremity, and OS was measured using d-ROMs and PATs (FRAS kit). Results: Pearson’s analyses revealed a significant statistical correlation between penile OSI values and PD plaque volumes (p = 0.003), while no correlation was found between systemic OSI values and plaque volumes (p = 0.356). Penile OSI values decreased significantly after PD plaque removal (p < 0.0001). A comparison of penile OSI values in PD patients (post plaque removal) and the control group showed no significant differences (p = 0.418). Conclusions: The lack of correlation between systemic OSI values and Peyronie’s plaque volume suggests that direct sampling from the site of the disease is preferable for OS studies. Conducting a penile OSI study could provide a precise oxidative marker dependent on plaque volume. In addition, the penile OSI study can biochemically monitor the therapeutic result, alongside penile ultrasound imaging. Full article

This paper presents the PRONOBIS project, an ultrasound-only, robotically assisted, deep learning-based system for prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate segmentation, reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time CNN-transformer-based image processing, 3D prostate reconstruction, and biopsy needle position planning. Fully automated prostate scanning is achieved by using a robotic arm equipped with an ultrasound system. Real-time ultrasound image processing utilizes state-of-the-art deep learning algorithms with intelligent post-processing techniques for precise prostate segmentation. To create a high-quality prostate segmentation dataset, this paper proposes a deep learning-based medical annotation platform, MedAP. For precise segmentation of the entire prostate sweep, DAF3D and MicroSegNet models are evaluated, and additional image post-processing methods are proposed. Three-dimensional visualization and prostate reconstruction are performed by utilizing the segmentation results and robotic positional data, enabling robust, user-friendly biopsy treatment planning. The real-time sweep scanning and segmentation operate at 30 Hz, which enable complete scan in 15 to 20 s, depending on the size of the prostate. The system is evaluated on prostate phantoms by reconstructing the sweep and by performing dimensional analysis, which indicates 92% and 98% volumetric accuracy on the tested phantoms. Three-dimansional prostate reconstruction takes approximately 3 s and enables fast and detailed insight for precise biopsy needle position planning. Full article

Medical phantoms are essential to imaging calibration, clinician training, and the validation of therapeutic procedures. However, most ultrasound phantoms prioritize acoustic realism while neglecting the viscoelastic and anisotropic properties of fibrous soft tissues. This gap limits their effectiveness in modeling realistic biomechanical behavior, especially in wave-based diagnostics and therapeutic ultrasound. Current materials like gelatine and agarose fall short in reproducing the complex interplay between the solid and fluid components found in biological tissues. To address this, we developed a soft, anisotropic composite whose dynamic mechanical properties resemble fibrous biological tissues such as skin and skeletal muscle. This material enables wave propagation and vibration studies in controllably anisotropic media, which are rare and highly valuable. We demonstrate the tunability of damping and stiffness aligned with fiber orientation, providing a versatile platform for modeling soft-tissue dynamics and validating biomechanical simulations. The phantoms achieved Young’s moduli of 7.16–11.04 MPa for skin and 0.494–1.743 MPa for muscles, shear wave speeds of 1.51–5.93 m/s, longitudinal wave speeds of 1086–1127 m/s, and sound absorption coefficients of 0.13–0.76 dB/cm/MHz, with storage, loss, and complex moduli reaching 1.035–6.652 kPa, 0.1831–0.8546 kPa, and 2.138–10.82 kPa. These values reveal anisotropic response patterns analogous to native tissues. This novel natural fibrous composite system affords sustainable, low-cost ultrasound phantoms that support both mechanical fidelity and acoustic realism. Our approach offers a route to next-gen tissue-mimicking phantoms for elastography, wave propagation studies, and dynamic calibration across diverse clinical and research applications. Full article

Objectives: To evaluate the reproducibility of measurements of breech progression angle (BPA) by transperineal ultrasound (US) before and after its standardization by applying an image-based checklist. Methods: Eighteen 3-dimensional (3D) volumes of transperineal US from women at 36–40 weeks of gestation with a singleton fetus in breech presentation were provided to eight operators from four maternity units in Spain and Italy. All operators measured the BPA using 3D US volume processing software, and interobserver reproducibility was evaluated using the intraclass correlation coefficient (ICC). Following an online live review of all measurements by the operators, and the identification of sources of disagreement, an image-based scoring system for BPA measurement was collaboratively developed. The checklist included the following: (1) acquisition in the midsagittal plane, avoiding the posterior shadow of the pubic ramus; (2) visualization of the complete “almond-shaped” pubic symphysis; (3) drawing a first line along the longitudinal axis of the symphysis, dividing it equally; (4) extending this line to the inferior edge of the bone; and (5) drawing a second line tangentially from the lower edge of the symphysis to the lowest recognizable fetal part. The BPA measurements were then repeated using this checklist, and reproducibility was reassessed. Results: Eighteen volumes were analyzed by the eight operators, achieving a moderate reproducibility (ICC: 0.70, 95% confidence interval (CI): 0.48 to 0.86). A score was developed to include a series of landmarks for the appropriate assessment of BPA. Subsequently, the same eighteen volumes were reassessed using the new score, resulting in improved reproducibility (ICC: 0.81, 95% CI: 0.66 to 0.92). Conclusions: The measurement of BPA is feasible and reproducible when using a standardized image-based score. Full article

Pelvic organ prolapse (POP) is a common pelvic floor disorder with substantial impact on women’s quality of life, necessitating accurate and reproducible diagnostic methods. This study investigates the use of three-dimensional (3D) transperineal ultrasound, integrated with artificial intelligence (AI), to evaluate pelvic floor biomechanics and identify correlations between biometric parameters and prolapse severity. Thirty-seven female patients diagnosed with genital prolapse (mean age: 65.3 ± 10.6 years; mean BMI: 29.5 ± 3.8) were enrolled. All participants underwent standardized 3D transperineal ultrasound using the Mindray Smart Pelvic system, an AI-assisted imaging platform. Key biometric parameters—anteroposterior diameter, laterolateral diameter, and genital hiatus area—were measured under three functional states: rest, maximal Valsalva maneuver, and voluntary pelvic floor contraction. Additionally, two functional indices were derived: the distensibility index (ratio of Valsalva to rest) and the contractility index (ratio of contraction to rest), reflecting pelvic floor elasticity and muscular function, respectively. Statistical analysis included descriptive statistics and univariate correlation analysis using Pelvic Organ Prolapse Quantification (POP-Q) system scores. Results revealed a significant correlation between laterolateral diameter and prolapse severity across multiple compartments and functional states. In apical prolapse, the laterolateral diameter measured at rest and during both Valsalva and contraction showed positive correlations with POP-Q point C, indicating increasing transverse pelvic dimensions with more advanced prolapse (e.g., r = 0.42 to 0.58; p < 0.05). In anterior compartment prolapse, the same parameter measured during Valsalva and contraction correlated significantly with POP-Q point AA (e.g., r = 0.45 to 0.61; p < 0.05). Anteroposterior diameters and genital hiatus area were also analyzed but showed weaker or inconsistent correlations. AI integration facilitated real-time image segmentation and automated measurement, reducing operator dependency and increasing reproducibility. These findings highlight the laterolateral diameter as a strong, reproducible anatomical marker for POP severity, particularly when assessed dynamically. The combined use of AI-enhanced imaging and functional indices provides a novel, standardized, and objective approach for assessing pelvic floor dysfunction. This methodology supports more accurate diagnosis, individualized management planning, and long-term monitoring of pelvic floor disorders. Full article

Knee rotational stability is crucial for anterior cruciate ligament (ACL) procedures, yet, current clinical assessments are subjective and lack precision. This study evaluates the accuracy and repeatability of the GATOR system, developed by PreciX Pte Ltd. and integrating ultrasound with inertial measurement units (IMUs), against a reference IMU (Xsens DOTS) for measuring knee flexion and rotation in six cadaveric specimens secured in an Oxford Knee Jig. Two experiments were conducted: (A) knee flexion from 0° to 120°, and (B) internal/external rotation at 0°, 30°, 60°, 90°, and 120° flexion. Analysis using Bland–Altman plots, root mean square error (RMSE: 3.93° for internal rotation, 6.90° for external rotation), mean biases, and paired t-tests (Bonferroni corrected) revealed that GATOR recorded lower peak flexion angles (91.49–114.65°) compared to the reference (110.31–118.49°). For rotation, internal rotation showed narrower limits of agreement than external rotation (biases: 1.91–6.88°). Over 60% of trials had errors < 5°, and 80% < 10°, indicating good agreement. Despite no isolated comparison of GATOR’s ultrasound component, findings suggest reduced soft tissue artifact due to bone-referenced sensor alignment. With optimal placement (10–15 cm from the knee center), GATOR shows promise in ACL assessment and remote rehabilitation. Full article