Ultrasound Imaging In Patients Research Articles

Analysis of the Characteristics and Intricacies of Arrangement of Neural Elements in the Costoclavicular Block Using Ultrasound: A Retrospective Qualitative Study

Abstract Background: Ultrasound (US)-guided costoclavicular block (CCB) is a promising new approach to brachial plexus (BP) block which is increasingly being utilized. Conventionally, the costoclavicular space (CCS) has been described to contain three cords. However, there may be variations in the neural pattern of the BP which is important to know to prevent inadvertent injury. We intend to describe the variations in neural patterns from retrospective scans of patients receiving costoclavicular BP block. Methods: The stored US images of patients who had received BP block using the CCB for surgery at the level of the elbow or below in the last year (from March 2021 to March 2022) were analyzed by two investigators independently. The clinical data were retrieved from the records of the same patients for the study outcomes. We collated the variations of the neural pattern, the number of neural structures seen, and the echogenicity of the structures in the costoclavicular BP space. Results: In the CCS, the median number of neural structures was 4.5 (minimum of 3 to maximum of 8). With the BP lateral to the axillary artery and sandwiched between the subclavius-pectoralis minor superiorly and the serratus anteriorly inferiorly, numerous variations in the neural structures were noted. The most common arrangement was caterpillar-like (28.6%) and pecker-like (20.3%). The neural structures were found to be hypoechoic in the majority (66%). Conclusion: The CCS hosts several mostly hypoechoic neural structures which may be the variations of the cords or the extension of BP divisions. These new findings have been unreported in the recent past.

Ultrasound imaging in spinal cord injury patients with shoulder pain

Objective To examine shoulder ultrasound imaging in both tetraplegic and paraplegic spinal cord injury (SCI) patients with shoulder pain. Methods All 28 individuals with SCI with shoulder pain were enrolled in this study. Fifty-six shoulders were evaluated by ultrasound (US) imaging. Results Fourteen tetraplegics and 14 paraplegics were enrolled (age 45.4 ± 13.8 years [mean ± SD]). Median time post-SCI was 8.6 years. Twenty-three individuals (82.1%) were independent in transfer and four individuals (14.3%) were partially independent in transfer. The prevalence of shoulder pain was 78.6% in manual wheelchair ambulators, 10.7% in gait aids users, 7.1% in wheelchair sitters, and 3.6% in no assistive device individuals. Abnormal US imaging was found in 24/28 (85.7%) individuals. Total shoulder US abnormalities were 38 units. Most common abnormal US imaging was supraspinatous tendinosis (42.1%), biceps tendon effusion (23.7%), positive dynamic supraspinatus impingement (21.1%), and subdeltoid bursitis (18.4%). Conclusions Shoulder ultrasonographic abnormalities were common in the patients with SCI with shoulder pain. The supraspinatus tendinosis is the most common abnormal US imaging in patients with SCI with shoulder pain.

A transvaginal ultrasound-based deep learning model for the noninvasive diagnosis of myometrial invasion in patients with endometrial cancer: Comparison with radiologists

ObjectiveThis study aimed to determine the feasibility of using the deep learning (DL) method to determine the degree (whether MI > 50%) of myometrial invasion (MI) in patients with endometrial cancer (EC) based on ultrasound (US) images. MethodsFrom September 2017 to April 2023, 1289 US images of 604 patients with EC who underwent surgical resection at Center 1, Center 2 or Center 3 were obtained and divided into a training set and an internal validation set. Ninety-five patients from Center 4 and Center 5 were randomly selected as the external testing set according to the same criteria as those for the primary cohort. This study evaluated three DL models trained on the training set and tested them on the validation and testing sets. The models’ performance was analyzed based on accuracy, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC), and the performance of the models was subsequently compared with that of 15 radiologists. ResultsIn the final clinical diagnosis of MI in patients with EC, EfficientNet-B6 showed the best performance in the testing set in terms of area under the curve (AUC) [0.814, 95% CI (0.746-0.882]; accuracy [0.802, 95% CI (0.733-0.855]; sensitivity [0.623]; specificity [0.879]; positive likelihood ratio [PLR] [6.750]; and negative likelihood ratio [NLR] [0.389]. The diagnostic efficacy of EfficientNet-B6 was significantly better than that of the 15 radiologists, with an average diagnostic accuracy of 0.681, average AUC of 0.678, AUC of the best performance of 0.739, accuracy of 0.716, sensitivity of 0.806, specificity 0.672, PLR2.457, and NLR 0.289. ConclusionBased on the preoperative US images of patients with EC, the DL model can accurately determine the degree of endometrial MI; the performance of this model is significantly better than that of radiologists, and it can effectively assist in clinical treatment decisions.

Reproducibility of Femoropopliteal Artery Intravascular Ultrasound Imaging in Patients With Peripheral Artery Disease

Despite increased use of intravascular ultrasound (IVUS) during peripheral artery interventions, evidence for reproducibility of IVUS measurements and its relation to angiography is lacking. Forty cross-sectional IVUS images of the femoropopliteal artery from 20 randomly selected patients enrolled in the XLPAD (Excellence in Peripheral Artery Disease) registry who underwent peripheral artery interventions and met criteria based on IVUS consensus guidelines were independently assessed by 2 blinded readers. IVUS images from 6 patients (40 images) were selected for angiographic correlation and met criteria for identifiable landmarks (e.g., stent edge and bifurcation). Lumen cross-sectional area (CSA), external elastic membrane (EEM) CSA, luminal diameter, and reference vessel diameter were repeatedly measured. The Lumen CSA and EEM CSA intra-observer agreement by Spearman rank-order correlation (ρ) was >0.993, intraclass correlation coefficient was >0.997, and repeatability coefficient was <1.34. For the interobserver measurement of luminal CSA and EEM CSA, the ρ=0.742 and 0.764; intraclass correlation coefficient=0.888 and 0.885; and repeatability coefficient=7.24 and 11.34, respectively. A Bland-Altman plot for lumen and EEM CSA showed good reproducibility. For angiographic comparison, the ρ for luminal diameter, luminal area, and vessel area were 0.419, 0.414, and 0.649, respectively. Femoropopliteal IVUS measurements showed strong intra-observer and interobserver agreement; IVUS and angiographic measurements did not demonstrate a similar strong agreement.

Complications and Technical Consideration of Ultrasound-Guided Rectus Sheath Blocks: A Retrospective Analysis of 4033 Patients.

Although the ultrasound-guided rectus sheath block (RSB) is usually regarded as an easy and safe procedure in clinical settings, there is currently no report on complications incidence. Therefore, the present study investigated complications in a large cohort and described the technical considerations to minimize complications of real-time ultrasound-guided RSBs. This was a retrospective cohort study of patients who underwent real-time ultrasound-guided RSBs for perioperative pain control in laparoscopic surgery with an umbilical port between February 1, 2017, and February 28, 2021, at the Asan Medical Center in South Korea. All RSBs were performed bilaterally using a 23-gauge Quincke needle, and a bilateral 2-block placement was regarded as 1 RSB. Patient data, including demographics, preoperative laboratory data, preoperative antiplatelet or anticoagulant medication with the duration of discontinuation, and type of surgery, were collected to show the study population characteristics and explore potential factors associated with adverse events such as hematoma. Ultrasound images of patients and adverse events of RSBs, including extrarectus sheath injections, vascular injuries, bowel injury, or local anesthetic systemic toxicity, were also analyzed accordingly. A total of 4033 procedures were analyzed. The mean body mass index of the patients was 24.1 (21.8-26.5) kg/m2. The preoperative laboratory data were within normal range in 4028 (99.9%) patients. Preoperative antiplatelets or anticoagulants were administered in 17.3% of the patients. Overall, 96 complications (2.4%) were observed. Among them, extrarectus sheath injection occurred in 88 cases (2.2%), which included preperitoneal injection (0.9%) and intraperitoneal injection (1.3%). Vascular injuries constituted 8 cases (0.2%) and all vascular injuries resulted in hematoma: 7 cases of inferior epigastric artery injury with rectus sheath hematoma and 1 of inferior mesenteric artery injury with retroperitoneal hematoma. Bowel injury or local anesthetic systemic toxicity was not reported. In this study of RSBs performed on 4033 patients using a 23-gauge Quincke needle in patients with low body mass index, there were 8 cases (0.2%) of vascular injury, all of which accompanied hematoma.

Increased diaphragm echodensity correlates with postoperative pulmonary complications in patients after major abdominal surgery: a prospective observational study

BackgroundAssociated with increased morbidity and mortality, postoperative pulmonary complications (PPCs) often occur after major abdominal surgery. Diaphragmatic dysfunction is suggested to play an important role in the development of PPCs and diaphragm echodensity can be used as an indicator of diaphragm function. This study aimed to determine whether diaphragm echodensity could predict the occurrence of PPCs in patients after major abdominal surgery.MethodsDiaphragm ultrasound images of patients after major abdominal surgery were collected during spontaneous breathing trials. Echodensity was quantified based on the right-skewed distribution of grayscale values (50th percentile, ED50; 85th percentile, ED85; mean, EDmean). Intra- and inter-analyzer measurement reproducibility was determined. Outcomes including occurrence of PPCs, reintubation rate, duration of ventilation, and length of ICU stay were recorded.ResultsDiaphragm echodensity was measured serially in 117 patients. Patients who developed PPCs exhibited a higher ED50 (35.00 vs. 26.00, p < 0.001), higher ED85 (64.00 vs. 55.00, p < 0.001) and higher EDmean (39.32 vs. 33.98, p < 0.001). In ROC curve analysis, the area under the curve of ED50 for predicting PPCs was 0.611. The optimal ED50 cutoff value for predicting the occurrence of PPCs was 36. According to this optimal ED50 cutoff value, patients were further divided into a high-risk group (ED50 > 36, n = 35) and low-risk group (ED50 ≤ 36, n = 82). Compared with the low-risk group, the high-risk group had a higher incidence of PPCs (unadjusted p = 0.003; multivariate-adjusted p < 0.001).ConclusionDiaphragm echodensity can be feasibly and reproducibly measured in mechanically ventilated patients. The increase in diaphragm echodensity during spontaneous breathing trials was related to an increased risk of PPCs in patients after major abdominal surgery.

High systemic immune-inflammation index is associated with carotid plaque vulnerability: New findings based on carotid ultrasound imaging in patients with acute ischemic stroke.

Vulnerable carotid plaque is closely related to the occurrence of Ischemic stroke. Therefore, accurate and rapid identification of the nature of carotid plaques is essential. AS is a chronic immune inflammatory process. Systemic immune-inflammation index (SII) is a novel index of immune inflammation obtained from routine whole blood cell count analysis, which comprehensively reflects the state of inflammation and immune balance in the body. This study sought to explore the relationship between SII level and carotid plaque vulnerability, plaque composition characteristics, and acute ischemic stroke (AIS) severity. A total of 131 patients diagnosed with AIS presenting with a carotid atherosclerotic plaque were enrolled in this study. Using carotid ultrasound (CDU) to assess the carotid-responsible plaque properties, we divided the patients into stable plaques group and vulnerable plaques group, and analyzed the correlation between SII levels and plaque vulnerability. And we further analyzed to evaluate the correlation between high SII levels and plaque characteristics and AIS severity. In addition, Cohen's Kappa statistics was used to detect the consistency of Carotid ultrasound (US) and cervical High-resolution magnetic resonance imaging (HRMRI) in evaluating plaque vulnerability. The findings showed that the vulnerable group had higher levels of SII compared with the stable group. The high SII group had more vulnerable plaques and a high frequency of plaque fibrous cap rupture compared with the low SII group. Logistic analysis showed that a high SII level was an independent risk factor for vulnerable plaques (odds ratio [OR] = 2.242) and plaque fibrous cap rupture (OR=3.462). The results also showed a high consistency between Carotid US and HRMRI methods in the assessment of plaque vulnerability [Cohen's kappa value was 0.89 (95% CI = 0.78–0.97)] and the level of SII was positively associated with NIHSS score (r = 0.473, P < 0.001). Our study suggests that elevated levels of SII may have adverse effects on the vulnerability of carotid plaques, especially in stroke patients with vulnerable plaques with ruptured fibrous caps, which may aggravate the severity of AIS.

Ultrasound Radiomics-Guided Iliac Fascia Block on Postoperative Cognitive Dysfunction in Elderly Patients Undergoing Hip Surgery.

Objective Elderly patients with hip surgery are prone to postoperative cognitive dysfunction (POCD), leading to health management difficulties. This study is aimed at investigating the effect of ultrasound radiomics-guided iliac fascia block on POCD. Methods A total of 67 cases of patients who had undergone hip joint surgery were divided into a training set (n = 47) and a validation set (radiomics-guided group, n = 20). The patients were intervened with ultrasound radiomics-guided iliac fascia block, and the maximum relevance minimum redundancy sifts out the image omics features obtained from 2D ultrasound images of patients. Another 20 patients undergone general anesthesia served as control. The incidence of POCD, the total amount of fentanyl, the visual analogue score (VAS) at different time points, and the levels of CRP and NSE in plasma were compared between the two groups. Results The AUC on the training and validation sets were higher than 0.940. The incidence of POCD in the radiomics-guided and general anesthesia group was 5% and 30%, respectively (P = 0.037). Compared with the general anesthesia group, the dosage of fentanyl in the radiomics-guided was lower, the VAS score at 6 h, 1 d, and 2 d after operation was smaller, and the levels of CRP and NSE were lower (all P < 0.05). Conclusions For elderly patients with hip surgery, the ultrasound radiomics-guided iliac fascia block can reduce the incidence of POCD and improve the effect of nerve block.

Automated measurement of total kidney volume from 3D ultrasound images of patients affected by polycystic kidney disease and comparison to MR measurements

PurposeTotal kidney volume (TKV) is the most important imaging biomarker for quantifying the severity of autosomal-dominant polycystic kidney disease (ADPKD). 3D ultrasound (US) can accurately measure kidney volume compared to 2D US; however, manual segmentation is tedious and requires expert annotators. We investigated a deep learning-based approach for automated segmentation of TKV from 3D US in ADPKD patients.MethodWe used axially acquired 3D US-kidney images in 22 ADPKD patients where each patient and each kidney were scanned three times, resulting in 132 scans that were manually segmented. We trained a convolutional neural network to segment the whole kidney and measure TKV. All patients were subsequently imaged with MRI for measurement comparison.ResultsOur method automatically segmented polycystic kidneys in 3D US images obtaining an average Dice coefficient of 0.80 on the test dataset. The kidney volume measurement compared with linear regression coefficient and bias from human tracing were R2 = 0.81, and − 4.42%, and between AI and reference standard were R2 = 0.93, and − 4.12%, respectively. MRI and US measured kidney volumes had R2 = 0.84 and a bias of 7.47%.ConclusionThis is the first study applying deep learning to 3D US in ADPKD. Our method shows promising performance for auto-segmentation of kidneys using 3D US to measure TKV, close to human tracing and MRI measurement. This imaging and analysis method may be useful in a number of settings, including pediatric imaging, clinical studies, and longitudinal tracking of patient disease progression.Graphical abstract

Classification and Recognition of Doppler Ultrasound Images of Patients with Atrial Fibrillation under Machine Learning

This study was aimed to explore the value of the twin neural network model in the classification and recognition of cardiac ultrasound images of patients with atrial fibrillation. 80 patients with cardiac atrial fibrillation were selected and randomly divided into experimental group (40 cases) and control group (40 cases). The twin neural network (TNN) model was combined with traditional ultrasound, Doppler spectrum, tissue velocity, and strain imaging technology to obtain the patient’s cardiac structure parameters and analyze and compare related indicators. The results showed that the total atrial emptying fraction (TA-EF value) of the experimental group was 53.08%, which was significantly lower than that of the control group ( P &lt; 0.05 ). There were no significant differences in left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD), left atrial maximum volume (LAVmax), and left ventricular ejection fraction (LVEF) between the two groups. In the experimental group, the average peak velocity of mitral valve annulus (Em) was 8.49 cm/s, the peak velocity of lateral wall systole (Vs) was 6.82 cm/s, and the propagation velocity of left ventricular blood flow (Vp) was 51.2 cm/s, which were significantly reduced ( P &lt; 0.05 ). The average values of peak strains in the middle and upper left atrium of the experimental group were significantly lower than those of the control group ( P &lt; 0.05 ). It can be concluded that the combined use of the TNN model can more accurately and quickly classify and recognize ultrasound images.

Evaluation of Pulmonary Edema Using Ultrasound Imaging in Patients With COVID-19 Pneumonia Based on a Non-local Channel Attention ResNet.

Recent research has revealed that COVID-19 pneumonia is often accompanied by pulmonary edema. Pulmonary edema is a manifestation of acute lung injury (ALI), and may progress to hypoxemia and potentially acute respiratory distress syndrome (ARDS), which have higher mortality. Precise classification of the degree of pulmonary edema in patients is of great significance in choosing a treatment plan and improving the chance of survival. Here we propose a deep learning neural network named Non-local Channel Attention ResNet to analyze the lung ultrasound images and automatically score the degree of pulmonary edema of patients with COVID-19 pneumonia. The proposed method was designed by combining the ResNet with the non-local module and the channel attention mechanism. The non-local module was used to extract the information on characteristics of A-lines and B-lines, on the basis of which the degree of pulmonary edema could be defined. The channel attention mechanism was used to assign weights to decisive channels. The data set contains 2220 lung ultrasound images provided by Huoshenshan Hospital, Wuhan, China, of which 2062 effective images with accurate scores assigned by two experienced clinicians were used in the experiment. The experimental results indicated that our method achieved high accuracy in classifying the degree of pulmonary edema in patients with COVID-19 pneumonia by comparison with previous deep learning methods, indicating its potential to monitor patients with COVID-19 pneumonia.

The Role of Lung Ultrasound in Diagnosing COVID-19-Related Multisystemic Inflammatory Disease: A Preliminary Experience.

Background: To date, there are no data regarding the systematic application of Point-of-Care Lung Ultrasound (PoC-LUS) in children with Multisystem Inflammatory Syndrome in Children (MIS-C). The main aim of this study is to show the role of Point-of-Care Lung Ultrasound as an additional aid in the diagnosis of COVID-19-related Multisystem Inflammatory Syndrome in Children (MIS-C). Methods: Between April 2020 and April 2021, patients aged 0–18 years referred to our emergency department for fever, and later hospitalized without a specific diagnosis, underwent PoC-LUS. Ultrasound images of patients with a final diagnosis of MIS-C were retrospectively evaluated. Results: Ten patients were enrolled. All were described to have pleural irregularities and B-lines. In particular: 8/10 children presented with isolated B-lines in at least half of the lung areas of interest; 8/10 presented with multiple B-lines and 3/8 had them in at least 50% of lung areas; 5/10 had a white lung appearance in at least one lung area and 1/5 had them in half of the areas of interest. Pleural effusion was described in 9/10. Conclusions: During the ongoing COVID-19 pandemic, we suggest performing PoC-LUS in febrile patients with high levels of inflammatory indices and clinical suspicion of MIS-C, or without a certain diagnosis; the finding of many B-lines and pleural effusion would support the diagnosis of a systemic inflammatory disease.

Intelligent Noise Reduction Algorithm to Evaluate the Correlation between Human Fat Deposits and Uterine Fibroids under Ultrasound Imaging.

This study aimed to realize the automatic diagnosis of fatty degeneration of uterine fibroids. In this study, the traditional nonlocal means (NLM) algorithm was improved by changing the Euclidean distance and introducing a cosine function and applied to the ultrasonic imaging intelligent diagnosis of patients with fatty degeneration of uterine fibroids. Then, the noise reduction effect of the improved NLM algorithm was evaluated based on several indicators, such as peak signal-to-noise ratio (PSNR), mean square error (MSE), contrast-to-noise ratio (CNR), figure of merit (FOM), and structural similarity (SSIM). The accuracy, sensitivity, specificity, and F1 score were adopted to evaluate the improved NLM algorithm for diagnosing fatty degeneration of uterine fibroids, and the Perona–Malik (PM) algorithm and NLM algorithm were used for comparative analysis. The results showed that after the ultrasound images of patients with uterine fibroids were denoised using the improved NLM algorithm, the PSNR, MSE, CNR, FOM, and SSIM were obviously better than the same indicators of the image processed with the PM algorithm and the NLM algorithm, and the differences were statistically significant (P < 0.05). The diagnosis results of patients with fatty degeneration of uterine fibroids found that there was only one patient with missed diagnosis after the ultrasound image was processed with NLM algorithm, and there was no statistical difference between the improved NLM algorithm and the assisted diagnosis accuracy of the pathological examination results (P > 0.05). The average noise reduction time of the PM algorithm, NLM algorithm, and the improved NLM algorithm was 16.38 ± 4.33 s, 18.01 ± 5.14 s, and 23.81 ± 4.62 s, respectively. The diagnosis rate before improvement was 75.0%, the diagnosis accuracy rate for PM was 79.69%, and that after improvement was 85.94%. In summary, the improved NLM algorithm showed a good noise reduction effect on ultrasound images of patients with uterine fibroids, could improve the diagnosis accuracy of fatty degeneration of uterine fibroids, and could assist clinicians in the ultrasound imaging diagnosis of patients with uterine fibroids.

High-intensity statin treatment is associated with reduced plaque structural stress and remodelling of artery geometry and plaque architecture.

AimsPlaque structural stress (PSS) is a major cause of atherosclerotic plaque rupture and major adverse cardiovascular events (MACE). We examined the predictors of changes in peak and mean PSS (ΔPSSpeak, ΔPSSmean) in three studies of patients receiving either standard medical or high-intensity statin (HIS) treatment.Methods and resultsWe examined changes in PSS, plaque size, and composition between 7348 co-registered baseline and follow-up virtual-histology intravascular ultrasound images in patients receiving standard medical treatment (controls, n = 18) or HIS (atorvastatin 80 mg, n = 20, or rosuvastatin 40 mg, n = 22). The relationship between changes in PSSpeak and plaque burden (PB) differed significantly between HIS and control groups (P < 0.001). Notably, PSSpeak increased significantly in control lesions with PB >60% (P = 0.04), but not with HIS treatment. However, ΔPSSpeak correlated poorly with changes in lumen and plaque area or PB, plaque composition, or lipid lowering. In contrast, ΔPSSpeak correlated significantly with changes in lumen curvature, irregularity, and roughness (P < 0.05), all of which were reduced in HIS patients. ΔPSSmean correlated with changes in lumen area, PA, PB, and circumferential calcification, and was unchanged with either treatment.ConclusionOur observational study shows that PSSpeak changes over time were associated with baseline disease severity and treatment. The PSSpeak increase seen in advanced lesions with standard treatment was associated with remodelling artery geometry and plaque architecture, but this was not seen after HIS treatment. Smoothing plaques by reducing plaque/lumen roughness, irregularity, and curvature represents a novel mechanism whereby HIS may reduce PSS and, thus may protect against plaque rupture and MACE.

Internet of Things-Based Ultrasound-Guided Erector Spinae Plane Block Combined with Edaravone Anesthesia in Thoracoscopic Lobectomy.

This paper aimed to study the application value of Internet of Things (IoT) edge computing algorithm-based ultrasound-guided erector spinae plane block combined with edaravone anesthesia in thoracoscopic lobectomy. A total of 110 patients undergoing thoracoscopic resection were selected as subjects. The patients were anesthetized with erector spinae plane block combined with edaravone before surgery and underwent chest ultrasound scan. IoT edge computing algorithm was constructed and applied to ultrasound images of patients to enhance and denoise the images. It was found that, in different mixed noise mixtures (Gaussian noise 10% + speckle noise 90%; Gaussian noise 30% + speckle noise 70%), the edge computing algorithm can still maintain the edge information of the output image, showing better performance on edge information detection and denoising compared with the Prewitt and Canny operator. In addition, visual analog scale (VAS) scores decreased with postoperative time after edaravone anesthesia induction and erector spinae plane block lobectomy and reached the lowest level after five days. In short, erector spinae plane block combined with edaravone showed good sedative and analgesic effects on patients undergoing thoracoscopic lobectomy. Ultrasound images processed by IoT edge computing algorithm showed high accuracy in the identification of lung lesions, which was worth applying to clinical diagnosis.

Speckle Tracking Algorithm-Based Cardiac Color Ultrasound in Diagnosis of Patients with Atrial Fibrillation Combined with Heart Failure

The study focused on the application of speckle tracking algorithm in the segmentation of cardiac color ultrasound images of patients with atrial fibrillation combined with heart failure. First, the optical flow method and block matching method were introduced on the basis of multiphase level set algorithm. Then, the pyramid block matching method was applied to build a pyramid model from bottom to top according to each image, and thus a new segmentation algorithm of cardiac color ultrasound image was constructed. The speckle tracking algorithm based on the pyramid block matching method was applied to segment cardiac color ultrasound images of 136 patients with atrial fibrillation and heart failure and compared with the traditional diagnosis for the sensitivity, specificity, and accuracy. It was found that the curve smoothness and accuracy of the algorithm in this study were better than the traditional level set algorithm, and it made up for the shortcomings of the traditional method. The proportion of patients of class III-IV cardiac function was significantly higher than that of non-atrial fibrillation patients, and the difference was statistically significant ( P &lt; 0.05 ); patients of classes III-IV showed better left ventricular ejection fraction (LVEF) (42.4 ± 2.8%), left ventricular end-diastolic diameter (LVED) (58.7 ± 7.4 mm), left ventricular end-systolic diameter (LVSD) (49.3 ± 5.6 mm), and left atrial inner diameter (LAD) (55.0 ± 1.4 mm) versus those of classes I-II, of whom the corresponding indexes were 58.8 ± 3.3%, 48.5 ± 5.9 mm, 33.5 ± 4.5 mm, and 45.2 ± 2.0 mm. The accuracy of diagnosis based on the algorithm of this study (93.22%) was significantly higher than that of traditional method (79.23%), and the differences were statistically significant ( P &lt; 0.05 ). In conclusion, the algorithm in this study improves the segmentation accuracy and smoothness of the curve, which is suggested in clinic.

Artificial Bee Colony Algorithm-Based Ultrasound Image Features in the Analysis of the Influence of Different Anesthesia Methods on Lung Air Volume in Orthopedic Surgery Patients

This study aimed to provide a quantitative evaluation of the lung gas content in orthopedic surgery patients under different anesthesia using ultrasound images based on the artificial bee colony algorithm. The ultrasound image features based on an artificial bee colony algorithm were applied to analyze segmentation images to investigate the influence of different anesthesia methods on the lung air content of patients undergoing orthopedic surgery and the clinical features of such patients. They were also adopted for the anesthesia in orthopedic surgery to assist clinicians in the diagnosis of diseases. 160 orthopedic surgery patients who were hospitalized were treated with different anesthesia methods. The first group (traditional general anesthesia group) received general anesthesia and traditional ultrasound; the second group (ABC general anesthesia group) was used for ultrasound image analysis based on the artificial bee colony algorithm; the third group (traditional sclerosis group) was anesthetized with combined sclerosis block; ultrasound images of patients from the fourth group (ABC sclerosis group) were analyzed based on the artificial bee colony algorithm. Analysis was conducted at three time points. The LUS score of the traditional sclerosis group and ABC sclerosis group was hugely higher than the score of the traditional general anesthesia group and ABC general anesthesia group at T2 time, with statistical significance ( P &lt; 0.005 ). At time point T3, the score of the traditional sclerosis group rose greatly compared with the general anesthesia group, and that of the ABC group was generally higher than that of the traditional ultrasound group ( P &lt; 0.005 ). When the threshold value was 4, the fitness value of ABC algorithm was 2680.4461, and the fitness value of the control group was 1736.815. The difference between the two groups was 943.6311 ( P &lt; 0.05 ). The operation time of ABC algorithm was 1.83, while that of the control group was 1.05, and the difference between the two groups was 0.78 ( P &lt; 0.05 ). In conclusion, the feature analysis of ultrasonic images based on the artificial bee colony algorithm could effectively improve the accuracy of ultrasonic images and the accuracy of focus recognition. It can promote medical efficiency and accurately identify the lung air content of patients in future clinical case measurement and auxiliary treatment of fracture, which has great application potential in improving surgical anesthesia effect.

Evaluation of Changes in Condylar Cartilage Thickness Using MRI and Ultrasound Imaging in Patients Treated by Mandibular Advancement With Myofunctional Appliance: An In-Vivo Pilot Study.

IntroductionThe changes occurring due to growth modulation of the condylar cartilage act as an important mechanism for mandibular advancement using myofunctional appliance therapy. So this study aims to evaluate the condylar cartilage thickness by using MRI and USG in patients undergoing myofunctional appliance therapy for mandibular advancement with the null hypothesis being that there are no changes seen in the thickness of condylar cartilage in growing children.Materials and methodsA prospective evaluation of samples having skeletal Class-II malocclusion ranging between cervical vertebral maturation index (CVMI) stage II and III, requiring twin block functional therapy was performed. Ten patients were selected randomly who underwent MRI and USG in the open and close positions for the evaluation of condylar cartilage thickness and the dimensional changes in the width of the right and left condyle in mm at T0 and T1.ResultThere was no statistically significant difference between the values interpreted by MRI or USG imaging when compared at T0 and T1 and in the open and closed mouth on the left and right sides. At T0, the mean thickness noted was 0.49 mm and 0.48 mm during opening and closing on the left side and 0.52 mm in both positions on the right side. At T1, the mean thickness noted was 0.8 and 0.79mm during opening and closing on the left side, whereas it was 0.81 mm in both positions on the right side.ConclusionThe condylar cartilage thickness increases significantly after twin block therapy suggestive of mandibular growth in skeletal class II malocclusion. It can be inferred that both MRI and USG carry equal diagnostic interpretation, as there was no statistically significant difference between the two imaging modalities.

Low incidence of focal lesions in the thyroid glands of patients with hereditary haemochromatosis — a single-centre study from Poland

Hereditary hemochromatosis (HH) is a disease characterized by the excessive absorption of iron and its deposition in various organs. Late complications of this disease include cirrhosis, hepatocellular carcinoma and endocrine disorders. Data from literature on thyroid disorders in patients with HH are inconsistent and ambiguous and no research has been done to determine the relationship between excessive accumulation of iron and the thyroid volume. Therefore, the aim of this study was to characterize thyroid function and ultrasound image in patients with clinically overt hereditary hemochromatosis. We studied 40 patients who were diagnosed with hereditary hemochromatosis with one of the mutation of HFE gene and iron deposites in liver in specimen from liver biopsy (graded G2 to G4) or in MRI. To assess the thyroid function, the ultrasound examination of the thyroid gland was performed and serum TSH concentrations were measured. We showed in our study that patients with HH have diagnosed with nodular goiters statistically less frequent than in control group. We did not reveal any statistically significant differences in TSH concentrations between patients with HH and the general population. However patients with more severe iron deposits in liver showed lower TSH. Our results indicate that iron overload syndromes and iron deposition could have prevent from formation of focal lesions in thyroid gland. Excess iron may act as a "protective" factor against the formation of nodular lesions in the thyroid gland through the production of peripheral thyroid hormones, i.e. thyroxine (T4) and triiodothyronine (T3), and the reduction of TSH concentration.

What Is the Diagnosis in Patients with Type 2 Diabetes Who Have a Painful Shoulder? Results from a Prospective Cross-Sectional Study.

Background: Patients with diabetes mellitus have higher risk of developing shoulder pathology. However, only adhesive capsulitis is addressed in shoulder pain guidelines as a disorder associated with diabetes. Yet, patients with diabetes are at risk of having several other shoulder disorders, including focal neuropathy. Our aim was to quantify the presence of shoulder disorders using physical examination and ultrasound imaging in patients with type 2 diabetes (T2DM) suffering from shoulder pain in general practice. Methods: In this prospective cross-sectional study, patients with T2DM who had had a painful shoulder for at least four weeks were included. Patients filled out a questionnaire and underwent a physical examination of the shoulders and feet and ultrasound imaging of the shoulder. Results: A total of 66 patients were included, of whom 40.9% (n = 27) had bilateral complaints resulting in 93 symptomatic shoulders. Subacromial pain syndrome was most frequently diagnosed by physical examination (66.6%, 95% CI 51.6–72.0%; p < 0.0001), while ultrasound imaging showed that subacromial disorders were statistically significantly the most prevalent (90.3%, 95% CI 81.9–95.2%). Only two patients (3%) were diagnosed with neuropathic shoulder pain. Conclusion: When choosing treatment, general practitioners should be aware that in patients with T2DM the subacromial region is most frequently affected.