Improving ultrasound-based bone registration using the iterative closest point algorithm paired with a complex optimization solver.

The Iterative Close Point (ICP) algorithm is used for bone registrations based on ultrasound measurements. However, the ICP has been shown to suffer from local minima. The Complex optimization, as a more robust routine compared to the commonly used gradient-based algorithms, could be an alternative for solving the ICP problem. In this study, we investigated the effect of the initial estimate and the number of registration points on bone registrations achieved using the ICP and a Complex optimization routine and we compared it against using Quadratic Sequential Programming (SQP). Ultrasound measurements were performed with an A-mode probe on a bovine humerus and an ovine femur embedded into ballistic gel. Simultaneously, the bones and the probe were tracked in 3D space using retroreflective markers. Kinematic, ultrasound and geometrical data obtained from scans of the specimens and the probe served as input to a bone registrations routine. Registrations were performed using two ICP solvers for different initial estimates and number of registration points. On average, 68 % of the Complex optimization registrations had less than 1 mm translation error and less than 1° rotational error for perturbations of the initial estimate from the reference measurements compared to the 35 % of the SQP ones. Similar medians of registration errors were observed between the two methods for variations of the number of the employed registration points. Although the Complex optimization provided accurate bone registrations for all cases, the objective function could not always determine the registrations with the smallest registration error. Future research should explore methodologies to overcome this challenge.

MSK-TIM: A Telerobotic Ultrasound System for Assessing the Musculoskeletal System.

The aim of this paper is to investigate technological advancements made to a robotic tele-ultrasound system for musculoskeletal imaging, the MSK-TIM (Musculoskeletal Telerobotic Imaging Machine). The hardware was enhanced with a force feedback sensor and a new controller was introduced. Software improvements were developed which allowed the operator to access ultrasound functions such as focus, depth, gain, zoom, color, and power Doppler controls. The device was equipped with Wi-Fi network capability which allowed the master and slave stations to be positioned in different locations. A trial assessing the system to scan the wrist was conducted with twelve participants, for a total of twenty-four arms. Both the participants and radiologist reported their experience. The images obtained were determined to be of satisfactory quality for diagnosis. The system improvements resulted in a better user and patient experience for the radiologist and participants. Latency with the VPN configuration was similar to the WLAN in our experiments. This research explores several technologies in medical telerobotics and provides insight into how they should be used in future. This study provides evidence to support larger-scale trials of the MSK-TIM for musculoskeletal imaging.

Convolutional neural network deep learning model accurately detects rectal cancer in endoanal ultrasounds.

BACKGROUND: Imaging is vital for assessing rectal cancer, with endoanal ultrasound (EAUS) being highly accurate in large tertiary medical centers. However, EAUS accuracy drops outside such settings, possibly due to varied examiner experience and fewer examinations. This underscores the need for an AI-based system to enhance accuracy in non-specialized centers. This study aimed to develop and validate deep learning (DL) models to differentiate rectal cancer in standard EAUS images. METHODS: A transfer learning approach with fine-tuned DL architectures was employed, utilizing a dataset of 294 images. The performance of DL models was assessed through a tenfold cross-validation. RESULTS: The DL diagnostics model exhibited a sensitivity and accuracy of 0.78 each. In the identification phase, the automatic diagnostic platform achieved an area under the curve performance of 0.85 for diagnosing rectal cancer. CONCLUSIONS: This research demonstrates the potential of DL models in enhancing rectal cancer detection during EAUS, especially in settings with lower examiner experience. The achieved sensitivity and accuracy suggest the viability of incorporating AI support for improved diagnostic outcomes in non-specialized medical centers.

Muscular Function Recovery from General Anesthesia in 132 Patients Undergoing Surgery with Acceleromyography, Combined Acceleromyography, and Ultrasonography, and without Monitoring Muscular Function.

BACKGROUND Diaphragmatic thickness fraction (DTF), measured by ultrasound, can predict the occurrence of postoperative residual neuromuscular blockade (RNMB). We hypothesized that the utilization of diaphragmatic ultrasound during the postoperative awakening phase of anesthesia in patients offers a successful means of avoiding RNMB in a notably comfortable manner, as compared to the use of acceleromyograph. MATERIAL AND METHODS Patients who underwent elective thyroid cancer radical surgery were enrolled in this prospective clinical study. Eligible participants were randomly assigned to 1 of 3 groups: 1) combined ultrasonography with acceleromyography group (the US+AMG group), 2) the AMG group, or 3) the usual clinical practice group (the UCP group). The primary outcomes of the study were the incidence of RNMB and hypoxemia after tracheal extubation. RESULTS The study included a total of 127 patients (43 in the US+AMG group, 44 in the AMG group, and 40 in the UCP group). The incidence of RNMB and hypoxemia was higher in the UCP group than in the US+AMG and AMG groups at 15 and 30 min after extubation, respectively. The mean area under the receiver operating characteristic curve, and the decision curve of the recovery rate of DTF (DTF) was greater than that of DTF. CONCLUSIONS The use of diaphragm ultrasound during the postoperative awakening phase of anesthesia can significantly reduce the incidence of RNMB. This method was non-inferior to the use of AMG during the entire perioperative period.

Ultrasound diagnosis of cystic echinococcosis: updates and implications for clinical management.

The diagnosis of cystic echinococcosis (CE) is based on imaging. Detection of a focal lesion with morphological characteristics of Echinococcus granulosus sensu lato metacestode is the starting point for the diagnostic workup. In organs explorable with ultrasound (US), this is the method of choice for both aetiological diagnosis of CE and staging of the CE cyst. Staging in terms of lesion morphology is also needed when serology is added to the diagnostic workflow when imaging alone is inconclusive. Finally, staging guides the clinical management of uncomplicated CE, especially in the liver. This commentary provides an overview of the most up-to-date evidence backing the above-mentioned role of US in the diagnosis and clinical management of CE. Finally, we outline future perspectives for the improvement of CE diagnosis.

Meta-analysis comparing different ultrasound detection methods to accurately assess wound healing and scar formation after caesarean section.

The accurate assessment of wound healing post-caesarean section, especially in twin pregnancies, remains a pivotal concern in obstetrics, given its implications for maternal health and recovery. Traditional methods, including conventional abdominal ultrasonography (CU), have been challenged by the advent of transvaginal ultrasonography (TU), offering potentially enhanced sensitivity and specificity. This meta-analysis directly compares the efficacy of TU and CU in evaluating wound healing and scar formation, crucial for optimizing postoperative care. Results indicate that TU is associated with significantly better outcomes in wound healing, demonstrated by lower REEDA scores (SMD = -20.56, 95% CI: [-27.34.20, -13.77], p < 0.01), and in scar formation reduction, evidenced by lower Manchester Scar Scale scores (SMD = -25.18, 95% CI: [-29.98, -20.39], p < 0.01). These findings underscore the potential of integrating TU into routine post-caesarean evaluation protocols to enhance care quality and patient recovery.

Effect of different positive end expiratory pressure levels on optic nerve sheath diameter in patients with or without midline shift who are undergoing supratentorial craniotomy.

PURPOSE: In general, high levels of PEEP application is avoided in patients undergoing craniotomy to prevent a rise in ICP. But that approach would increase the risk of secondary brain injury especially in hypoxemic patients. Because the optic nerve sheath is distensible, a rise in ICP is associated with an increase in the optic nerve sheath diameter (ONSD). The cutoff value for elevated ICP assessed by ONSD is between 5.6 and 6.3 mm. We aimed to evaluate the effect of different PEEP levels on ONSD and compare the effect of different PEEP levels in patients with and without intracranial midline shift. METHODS: This prospective observational study was performed in aged 18-70 years, ASA I-III, 80 patients who were undergoing supratentorial craniotomy. After the induction of general anesthesia, the ONSD's were measured by the linear transducer from 3 mm below the globe at PEEP values of 0-5-10 cmH2O. The ONSD were compered between patients with (n = 7) and without midline shift (n = 73) at different PEEP values. RESULTS: The increases in ONSD due to increase in PEEP level were determined (p < 0.001). No difference was found in the comparison of ONSD between patients with and without midline shift in different PEEP values (p = 0.329, 0.535, 0.410 respectively). But application of 10 cmH2O PEEP in patients with a midline shift increased the mean ONSD value to 5.73 mm. This value is roughly 0.1 mm higher than the lower limit of the ONSD cutoff value. CONCLUSIONS: The ONSD in adults undergoing supratentorial tumor craniotomy, PEEP values up to 5 cmH2O, appears not to be associated with an ICP increase; however, the ONSD exceeded the cutoff for increased ICP when a PEEP of 10 cmH2O was applied in patients with midline shift.

Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.

BACKGROUND: Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multiclass prediction algorithm for differentiating between benign, borderline, and malignant ovarian tumours. METHODS: We randomised data from 849 patients with ovarian tumours into training and testing sets in a ratio of 8:2. The regions of interest on the US images were segmented and handcrafted radiomics features were extracted and screened. We applied the one-versus-rest method in multiclass classification. We inputted the best features into machine learning (ML) models and constructed a radiomic signature (Rad_Sig). US images of the maximum trimmed ovarian tumour sections were inputted into a pre-trained convolutional neural network (CNN) model. After internal enhancement and complex algorithms, each sample's predicted probability, known as the deep transfer learning signature (DTL_Sig), was generated. Clinical baseline data were analysed. Statistically significant clinical parameters and US semantic features in the training set were used to construct clinical signatures (Clinic_Sig). The prediction results of Rad_Sig, DTL_Sig, and Clinic_Sig for each sample were fused as new feature sets, to build the combined model, namely, the deep learning radiomic signature (DLR_Sig). We used the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) to estimate the performance of the multiclass classification model. RESULTS: The training set included 440 benign, 44 borderline, and 196 malignant ovarian tumours. The testing set included 109 benign, 11 borderline, and 49 malignant ovarian tumours. DLR_Sig three-class prediction model had the best overall and class-specific classification performance, with micro- and macro-average AUC of 0.90 and 0.84, respectively, on the testing set. Categories of identification AUC were 0.84, 0.85, and 0.83 for benign, borderline, and malignant ovarian tumours, respectively. In the confusion matrix, the classifier models of Clinic_Sig and Rad_Sig could not recognise borderline ovarian tumours. However, the proportions of borderline and malignant ovarian tumours identified by DLR_Sig were the highest at 54.55% and 63.27%, respectively. CONCLUSIONS: The three-class prediction model of US-based DLR_Sig can discriminate between benign, borderline, and malignant ovarian tumours. Therefore, it may guide clinicians in determining the differential management of patients with ovarian tumours.

Bridging the gap: understanding Belgian anesthesiologists' proficiency and training demands in gastric point-of-care ultrasound, a case-based survey.

BACKGROUND: Pulmonary aspiration syndrome remains a significant complication of general anesthesia, particularly in unfasted patients. Gastric point-of-care ultrasound (POCUS) allows for both qualitative and quantitative assessment of gastric content, providing a safe and reliable method to assess gastric emptying and reduce the risk of aspiration during general anesthesia. METHODS: The survey was distributed to Belgian certified anesthesiologists and trainees between April 2020 and June 2021. Participants received a simulated clinical case of a patient at risk of gastric aspiration, created and approved by two certified anesthesiologists trained to perform gastric POCUS. The objectives of this study were to assess recognition of high-risk clinical situations for gastric aspiration, awareness of the gastric POCUS and its indications, and knowledge of the technical and practical conditions of the procedure among respondents trained in the technique. Furthermore, the study assessed the state of training in gastric POCUS, the desire for education, and the practical availability of ultrasound equipment. The survey used conditional branching to ensure unbiased responses to POCUS-related questions. It included multiple-choice questions, quantitative variables, and 5-point Likert scales. The margin of error was calculated using Daniel's formula, corrected for a finite population. RESULTS: The survey was conducted among 323 anesthesiologists. Only 20.8% (27) recognized the risk of a full stomach based on the patient's history. Anesthesiologists who recognized the indication for gastric POCUS and were trained in the procedure demonstrated good recall of the practical conditions for performing the procedure and interpreting the results. Only 13.08% (31) of all respondents had received training in gastric POCUS, while 72.57% (172) expressed interest in future training. Furthermore, 80.17% (190) of participants had access to adequate ultrasound equipment and 78.90% (187) supported teaching gastric POCUS to anesthesia trainees. CONCLUSIONS: This survey offers insight into the epidemiology, clinical recognition, knowledge, and utilization of gastric POCUS among Belgian anesthesia professionals. The results emphasize the significance of proper equipment and training to ensure the safe and effective implementation of gastric POCUS in anesthesia practice. Additional efforts should focus on improving training and promoting the integration of gastric POCUS into daily clinical practice.

Comparison of estimations of urinary bladder volume in different scanning positions using 2D linear dimension formula and 3D bladder circumference tracing in client-owned cats.

Urinary bladder volume (UBV) can be estimated using point-of-care ultrasound. The purpose of this study was to compare 2 UBV estimation methods, i.e., three-dimensional (3D) bladder circumference tracing and 2-dimensional (2D) linear bladder dimension formula, against actual bladder volumes in awake client-owned cats and identify the best scanning position for UBV estimations. Up to 3 paired sets of orthogonal longitudinal and transverse bladder ultrasound images were acquired by a trained clinician from 21 cats positioned in dorsal, right lateral, and left lateral recumbency. UBV estimation was performed with these images by 2 different observers using both methods. Actual bladder volumes were measured through urethral catheterization and compared to the estimated UBV using Lin's concordance correlation coefficient and Bland-Altman analyses. Considering all positions, both methods showed substantial strength-of-agreement with actual bladder volumes; the 3D bladder circumference method (ρc = 0.963, 95% CI: 0.952 to 0.974) with a significant median bias of -4.08 mL (P < 0.001, IQR -7.63 to -0.68 mL, LOA -48.55 to 21.75 mL) and the 2D linear dimension method (ρc = 0.974, 95% CI: 0.966 to 0.982) with a median bias of -0.82 mL (P = 0.686, IQR -3.89 to 4.05 mL, LOA -35.23 to 35.21 mL). Scanning in left lateral recumbency provided the strongest strengths-of-agreement and precision against actual bladder volumes for both methods. Regardless of scanning positions, the 2D linear dimension method is more accurate than the 3D bladder circumference method, although both methods are imprecise with increasing volumes and UBV assessment through urinary catheterization remains the gold standard.

Le volume vésical (UBV) peut être estimé à l'aide de l'échographie au point d'intervention. L'objectif de cette étude fut de comparer 2 méthodes d'estimation du UBV, i.e., le tracé tridimensionnel (3D) de la circonférence de la vessie et la formule de dimension linéaire en 2 dimensions (2D), aux volumes vésicaux réels chez des chats éveillés appartenant à des clients, ainsi que d'identifier la meilleure position de balayage pour l'estimation du UBV. Jusqu'à 3 séries appariées d'images ultrasonores longitudinales et transverses orthogonales ont été acquises par une clinicienne qualifiée sur 21 chats positionnés en décubitus dorsal, latéral droit et latéral gauche. L'estimation du UBV a été réalisée à partir de ces images par 2 observateurs différents utilisant les 2 méthodes. Les volumes vésicaux réels ont été mesurés par cathétérisme urétral et comparés aux UBV estimés à l'aide du coefficient de corrélation de concordance de Lin et d'analyses de Bland-Altman. Toutes positions confondues, les 2 méthodes ont montré une concordance considérable avec les volumes vésicaux réels; la méthode de la circonférence vésicale 3D (ρc = 0,963, 95 % CI : 0,952 à 0,974) avec un biais médian significatif de −4,08 mL (P < 0,001, IQR −7,63 à −0,68 mL, LOA −48,55 à 21,75 mL) et la méthode de la dimension linéaire 2D (ρc = 0,974, 95 % CI : 0,966 à 0,982) avec un biais médian de −0,82 mL (P = 0,686, IQR −3,89 à 4,05 mL, LOA −35,23 à 35,21 mL). Le balayage en décubitus latéral gauche a démontré les meilleures concordance et précision par rapport aux volumes vésicaux réels pour les 2 méthodes. Quelle que soit la position de balayage, la méthode de la dimension linéaire 2D est plus précise que la méthode de circonférence vésicale 3D, bien que les 2 méthodes deviennent imprécises avec des volumes vésicaux plus élevés et que l'évaluation du UBV par cathétérisme urinaire demeure l'étalon d'or.(Traduit par les auteurs).

Distal hamstrings tendons mechanical properties at rest and contraction using free-hand 3-D ultrasonography.

Tendon properties impact human locomotion, influencing sports performance, and injury prevention. Hamstrings play a crucial role in sprinting, particularly the biceps femoris long head (BFlh), which is prone to frequent injuries. It remains uncertain if BFlh exhibits distinct mechanical properties compared to other hamstring muscles. This study utilized free-hand three-dimensional ultrasound to assess morphological and mechanical properties of distal hamstrings tendons in 15 men. Scans were taken in prone position, with hip and knee extended, at rest and during 20%, 40%, 60%, and 80% of maximal voluntary isometric contraction of the knee flexors. Tendon length, volume, cross-sectional area (CSA), and anteroposterior (AP) and mediolateral (ML) widths were quantified at three locations. Longitudinal and transverse deformations, stiffness, strain, and stress were estimated. The ST had the greatest tendon strain and the lowest stiffness as well as the highest CSA and AP and ML width strain compared to other tendons. Biceps femoris short head (BFsh) exhibited the least strain, AP and ML deformation. Further, BFlh displayed the highest stiffness and stress, and BFsh had the lowest stress. Additionally, deformation varied by region, with the proximal site showing generally the lowest CSA strain. Distal tendon mechanical properties differed among the hamstring muscles during isometric knee flexions. In contrast to other bi-articular hamstrings, the BFlh high stiffness and stress may result in greater energy absorption by its muscle fascicles, rather than the distal tendon, during late swing in sprinting. This could partly account for the increased incidence of hamstring injuries in this muscle.

Development and validation of a clinical and ultrasound features-based nomogram for preoperative differentiation of renal urothelial carcinoma and central renal cell carcinoma.

PURPOSE: This study aimed to develop and validate an ultrasound (US)-based nomogram for the preoperative differentiation of renal urothelial carcinoma (rUC) from central renal cell carcinoma (c-RCC). METHODS: Clinical data and US images of 655 patients with 655 histologically confirmed malignant renal tumors (521 c-RCCs and 134 rUCs) were collected and divided into training (n = 455) and validation (n = 200) cohorts according to examination dates. Conventional US and contrast-enhanced US (CEUS) tumor features were analyzed to determine those that could discriminate rUC from c-RCC. Least absolute shrinkage and selection operator regression was applied to screen clinical and US features for the differentiation of rUC from c-RCC. Using multivariate logistic regression analysis, a diagnostic model of rUC was constructed and visualized as a nomogram. The diagnostic model's performance was assessed in the training and validation cohorts by calculating the area under the receiver operating characteristic curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness of the US-based nomogram. RESULTS: Seven features of both clinical features and ultrasound imaging were selected to build the diagnostic model. The nomogram achieved favorable discrimination in the training (AUC = 0.996, 95% CI: 0.993-0.999) and validation (AUC = 0.995, 95% CI: 0.974, 1.000) cohorts, and good calibration (Brier scores: 0.019 and 0.016, respectively). DCA demonstrated the clinical usefulness of the US-based nomogram. CONCLUSION: A noninvasive clinical and US-based nomogram combining conventional US and CEUS features possesses good predictive value for differentiating rUC from c-RCC.

Society of Radiologists in Ultrasound Consensus on Routine Pelvic US for Endometriosis.

Endometriosis is a prevalent and potentially debilitating condition that mostly affects individuals of reproductive age, and often has a substantial diagnostic delay. US is usually the first-line imaging modality used when patients report chronic pelvic pain or have issues of infertility, both common symptoms of endometriosis. Other than the visualization of an endometrioma, sonologists frequently do not appreciate endometriosis on routine transvaginal US images. Given a substantial body of literature describing techniques to depict endometriosis at US, the Society of Radiologists in Ultrasound convened a multidisciplinary panel of experts to make recommendations aimed at improving the screening process for endometriosis. The panel was composed of experts in the imaging and management of endometriosis, including radiologists, sonographers, gynecologists, reproductive endocrinologists, and minimally invasive gynecologic surgeons. A comprehensive literature review combined with a modified Delphi technique achieved a consensus. This statement defines the targeted screening population, describes techniques for augmenting pelvic US, establishes direct and indirect observations for endometriosis at US, creates an observational grading and reporting system, and makes recommendations for additional imaging and patient management. The panel recommends transvaginal US of the posterior compartment, observation of the relative positioning of the uterus and ovaries, and the uterine sliding sign maneuver to improve the detection of endometriosis. These additional techniques can be performed in 5 minutes or less and could ultimately decrease the delay of an endometriosis diagnosis in at-risk patients.

The Value of Intraoperative Ultrasound in Brain Surgery.

Favorable clinical outcomes in adult and pediatric neurosurgical oncology generally depend on the extent of tumor resection (EOR). Maximum safe resection remains the main aim of surgery in most intracranial tumors. Despite the accuracy of intraoperative magnetic resonance imaging (iMRI) in the detection of residual intraoperatively, it is not widely implemented worldwide owing to enormous cost and technical difficulties. Over the past years, intraoperative ultrasound (IOUS) has imposed itself as a valuable and reliable intraoperative tool guiding neurosurgeons to achieve gross total resection (GTR) of intracranial tumors.Being less expensive, feasible, doesn't need a high level of training, doesn't need a special workspace, and being real time with outstanding temporal and spatial resolution; all the aforementioned advantages give a superiority for IOUS in comparison to iMRI during resection of brain tumors.In this chapter, we spot the light on the technical nuances, advanced techniques, outcomes of resection, pearls, and pitfalls of the use of IOUS during the resection of brain tumors.

Correlation of US-7 and US-9 Scores with Disease Activity Score using 28 Joint Counts (DAS28) in Patients with Rheumatoid Arthritis.

Background: The attentive management of rheumatoid arthritis (RA) has attracted particular attention. The German 7-joint Ultrasound (US-7) is the first scoring system that combines bone erosions and soft tissue lesions in a single composite scoring system. This study aimed to assess the correlation between US-7 and Disease Activity Score Using 28 Joint Counts (DAS28) in clinically active RA patients. The efficacy of a novel ultrasound score-based system, the US-9 score (joints assessed with US-7 plus knees), was also compared with the standard US-7 score. Methods: All the RA patients referred to the outpatient rheumatology clinic of Ghaem Hospital, Mashhad, Iran, during 2019-2020 were included. 28 joints were clinically examined to calculate DAS28. Nine joints were assessed comprising the German US-7 plus knees using grayscale ultrasonography (GSUS) and power Doppler ultrasonography (PDUS). Retrieved data were analyzed by SPSS software, version 22. The Spearman Correlation test was used to find the correlation between DAS28 and ultrasonographic findings. The statistical significance level was set at P<0.05. Results: This study was composed of thirty-five RA patients with a mean age of 49.1±12.0 years. US-7 synovitis scores in GSUS and PDUS were significantly correlated with DAS28 (P=0.02, r=0.38 and P=0.003, r=0.48, respectively). US-9 synovitis scores in GSUS and PDUS were also significantly correlated with DAS28 (P=0.003, r=0.49 and P=0.006, r=0.45, respectively). The synovitis score measured by GSUS was significantly correlated with the GSUS knee synovial score (P=0.01, r=0.42). Conclusion: Ultrasound assessment of large joints such as knees can be an effective approach to determining RA severity. However, it can be proposed that adding more involved joints into the sonographic assessment does not necessarily provide a better clinical correlation.