Radiological Features for Predicting the Status of CD8-Positive Lymphocytes in HER2 Positive Breast Cancer.

Background: The level of tumor-infiltrating lymphocytes (TILs) in human epidermal growth factor receptor type 2 (HER2)-positive breast cancer (BC) is positively correlated with pathological complete response. Aims: To investigate the relationship between ultrasound (US) and magnetic resonance imaging (MRI) features and the level of CD8-positive TILs (CD8+-TILs) in patients with HER2-positive BC. Study Design: Retrospective cohort study. Methods: This retrospective study included 155 consecutive women with HER2-positive BC. Patients were divided into two groups: CD8+-TILlow (< 35%) and CD8+-TILhigh (≥ 35%) groups. US and MRI features were evaluated using the BI-RADS lexicon, and the apparent diffusion coefficient (ADC) value was calculated using RadiAnt software. Univariate and multivariate analyses revealed the optimal US and MRI features for predicting CD8+-TIL levels. Receiver operating characteristic analysis and the Delong test were used to compare the diagnostic performance of US and MRI features. Furthermore, implementing a nomogram will increase clinical utility. Results: Univariate analysis of US features showed significant differences in shape, orientation, and posterior echo between the two groups; however, there were no significant differences in margins, internal echo, and microcalcification. Multifactorial analysis revealed that shape, orientation, and posterior echo were independent risk factors, with odds ratios of 11.62, 2.70, and 0.16, respectively. In terms of MRI features, ADC was an independent predictor of CD8+-TIL levels. These three US features and the ADC performed well, with area under the curve (AUC) values of 0.802 and 0.705, respectively. The combination of US and ADC values had higher predictive efficacy (AUC = 0.888) than either US or ADC alone (p = 0.009, US_ADC vs. US; p < 0.001, US_ADC vs. ADC). Conclusion: US features (shape, orientation, and posterior echo) and ADC value may be a valuable tool for estimating CD8+-TIL levels in HER2-positive BC. The nomogram may help clinicians in making decisions.

Status and perception of point-of-care ultrasound education in Korean medical schools: A national cross-sectional study.

As point-of-care ultrasound (POCUS) is increasingly being used in clinical settings, ultrasound education is expanding into student curricula. We aimed to determine the status and awareness of POCUS education in Korean medical schools using a nationwide cross-sectional survey. In October 2021, a survey questionnaire consisting of 20 questions was distributed via e-mail to professors in the emergency medicine (EM) departments of Korean medical schools. The questionnaire encompassed 19 multiple-choice questions covering demographics, current education, perceptions, and barriers, and the final question was an open-ended inquiry seeking suggestions for POCUS education. All EM departments of the 40 medical schools responded, of which only 13 (33%) reported providing POCUS education. The implementation of POCUS education primarily occurred in the third and fourth years, with less than 4 hours of dedicated training time. Five schools offered a hands-on education. Among schools offering ultrasound education, POCUS training for trauma cases is the most common. Eight schools had designated professors responsible for POCUS education and only 2 possessed educational ultrasound devices. Of the respondents, 64% expressed the belief that POCUS education for medical students is necessary, whereas 36%, including those with neutral opinions, did not anticipate its importance. The identified barriers to POCUS education included faculty shortages (83%), infrastructure limitations (76%), training time constraints (74%), and a limited awareness of POCUS (29%). POCUS education in Korean medical schools was limited to a minority of EM departments (33%). To successfully implement POCUS education in medical curricula, it is crucial to clarify learning objectives, enhance faculty recognition, and improve the infrastructure. These findings provide valuable insights for advancing ultrasound training in medical schools to ensure the provision of high-quality POCUS education for future healthcare professionals.

The state of point-of-care ultrasound training in pediatric anesthesia fellowship programs in the United States: A survey assessment.

BACKGROUND: Point-of-care ultrasound is an invaluable bedside tool for anesthesiologists and has been integrated into anesthesiology residency training and board certification in the United States. Little is known about point-of-care ultrasound training practices in pediatric anesthesia fellowship programs. AIMS: To describe the current state of point-of-care ultrasound education in pediatric anesthesia fellowship programs in the United States. METHODS: We conducted a cross-sectional survey study distributed to 60 American Accreditation Council for Graduate Medical Education-accredited pediatric anesthesia fellowship programs. Two programs were in their initial accreditation period and were excluded due to lack of historical data. Program directors or associate program directors were invited to complete this 23-item survey. RESULTS: Thirty-three of fifty-eight programs (57%) completed the survey. Of those, 15 programs (45%) reported having a point-of-care ultrasound curriculum. Programs with ≤3 fellows per year were less likely to have an ultrasound curriculum compared to programs with ≥4 fellows per year (30% programs 0-3 fellows/year vs. 69% programs ≥4 fellows/year, odds ratio 0.19 [95% confidence intervals 0.04-0.87]; p = .03). Program directors and associate program directors rated point-of-care ultrasound training as highly valuable to fellows' education. Barriers to use most commonly included lack of experience (64%), lack of oversight/interpretive guidance (58%), and lack of time (45%). Programs without point-of-care ultrasound training had significantly higher odds of listing lack of ultrasound access as a primary barrier (50% programs without vs. 13% programs with, odds ratio 6.5, [95% confidence intervals 1.3-50]; p = .04). CONCLUSIONS: This observational survey-based study suggests that fewer than half of pediatric anesthesia training programs in the United States offer point-of-care ultrasound education. Additional research is needed to optimize this education and training in pediatric anesthesia fellowship programs.

Sobreuso de ecografía transvaginal en un hospital universitario privado de Argentina: estudio de corte transversal / Transvaginal ultrasound overuse in a private university hospital in Argentina: a cross-sectional study

Introducción. Si bien contamos con recomendaciones basadas en la evidencia en contra de realizar tamizaje de cáncer ovárico con ecografía transvaginal debido a que aumenta el riesgo de resultados falsamente positivos y de cascadas diagnósticas, sin disminuir la mortalidad por esta enfermedad, su solicitud en mujeres sanas es frecuente. Sin embargo, no conocemos la magnitud de la implementación de esta práctica, que constituye un cuidado de bajo valor. Objetivo. Documentar el sobreuso de ecografías transvaginales realizadas en forma ambulatoria en un hospital universitario privado de Argentina. Métodos. Estudio de corte transversal de una muestra aleatoria de ecografías realizadas en forma ambulatoria durante 2017 y 2018. Mediante revisión manual de las historias clínicas, la solicitud de cada ecografía fue clasificada como apropiada cuando algún problema clínico justificaba su realización, o inapropiada cuando había sido realizada con fines de control de salud o por una condición clínica sin indicación de seguimiento ecográfico. Resultados. De un total de 1.997 ecografías analizadas, realizadas a 1.954 mujeres adultas (edad promedio 50 años),1.345 (67,4 %; intervalo de confianza [IC] 95 % 65,2 a 69,4) habían sido solicitadas en el contexto de un control de saludo sin un problema asociado en la historia clínica y otras 54 (8,3 %; IC 95 % 6,3 a 10,7), por condiciones de salud para las que no hay recomendaciones de realizar seguimiento ecográfico. Conclusiones. Esta investigación documentó una alta proporción de sobre utilización de la ecografías transvaginales en nuestra institución. Futuras investigaciones permitirán comprender los motivos que impulsan esta práctica y ayudarán a diseñar intervenciones para disminuir estos cuidados de bajo valor. (AU)

Background. Although we have evidence-based recommendations against screening for ovarian cancer with transvaginalultrasound because it increases the risk of false positive results and diagnostic cascades without reducing mortality from this disease, its request in healthy women is frequent. However, we do not know the magnitude of the implementation of this practice, which constitutes low-value care. Objective. To document the overuse of transvaginal ultrasounds performed on an outpatient basis in a private university hospital in Argentina. Methods. Cross-sectional study of a random sample of outpatient ultrasounds performed during 2017 and 2018. Through a manual review of the medical records, the request for each ultrasound was classified as appropriate when a clinical problem justified its performance or inappropriate when it was carried out for health control purposes or for a clinical condition that had no indication for ultrasound follow-up. Results. Of a total of 1997 ultrasounds analyzed, performed on 1954 adult women (average age 50 years), 1,345 (67.4 %;95 % confidence interval [CI] 65.2 to 69.4) had been requested in the context of a health check-up or without a documented problem in the medical history that would support its performance, and another 54 (8.3 %; 95 % CI 6.3 to 10.7), for health conditions for which there are no treatment recommendations to perform ultrasound follow-up. Conclusions. This research documented a high proportion of overuse of transvaginal ultrasound in our institution. Future research will allow us to understand the reasons that drive this practice and will help design interventions to reduce thislow-value care. (AU)

Disparities in Ultrasound Use for Diagnosing Pediatric Appendicitis Across United States Emergency Departments.

INTRODUCTION: An ultrasound (US)-first approach for evaluating appendicitis is recommended by the American College of Radiology. We sought to assess the access to and utilization of an US-first approach for children with acute appendicitis in United States Emergency Departments. METHODS: Utilizing the 2019 Nationwide Emergency Department Sample, we performed a retrospective cohort study of patients <18 y with a primary diagnosis of acute appendicitis based on International Classification of Disease 10th Edition Diagnosis codes. Our primary outcome was the presentation to a hospital that does not perform US for children with acute appendicitis. Our secondary outcome was the receipt of a US at US-capable hospital. We developed generalized linear models with inverse-probability weighting to determine the association between patient characteristics and outcomes. RESULTS: Of 49,703 total children, 24,102 (48%) received a US evaluation. The odds of presenting at a hospital with no US use were significantly higher for patients aged 11-17 compared to patients <6 y (adjusted odds ratio [aOR] [95% confidence interval (CI)]: 1.59, [1.19- 2.13], P = 0.002); lowest median household income quartile compared to highest (aOR [95% CI]: 2.50, [1.52-4.10], P < 0.001); rural locations compared to metropolitan (aOR [95% CI]: 8.36 [5.54-12.6], P < 0.001), and Hispanic compared to non-Hispanic White (aOR [95% CI]: 0.63 [0.45-0.90], P = 0.01). The odds of receiving a US at US-capable hospitals were significantly lower for patients >6 y, lowest median household income quartiles, and rural locations (P < 0.05). CONCLUSIONS: Rural, older, and poorer children are more likely to present to hospitals that do not utilize US in the diagnosis of acute appendicitis and are less likely to undergo US at US-capable hospitals.

Intelligent Algorithm-Based Ultrasound Image for Evaluating the Effect of Comprehensive Nursing Scheme on Patients with Diabetic Kidney Disease.

This study was aimed at exploring the effect of ultrasound image evaluation of comprehensive nursing scheme based on artificial intelligence algorithms on patients with diabetic kidney disease (DKD). 44 patients diagnosed with DKD were randomly divided into two groups: group A (no nursing intervention) and group B (comprehensive nursing). In the same period, 32 healthy volunteers were selected as the control group. Ultrasonographic images based on the K non-local-means (KNL-Means) filtering algorithm were used to perform imaging examinations in healthy people and DKD patients before and after care. The results suggested that compared with those of the SAE reconstruction algorithm and KAVD reconstruction algorithm, the PSNR value of artificial bee colony algorithm reconstruction of image was higher and the MSE value was lower. The resistant index (RI) of DKD patients in group B after nursing was 0.63 ± 0.06, apparently distinct from the RI of the healthy people (controls) in the same group (0.58 ± 0.06) and the RI of DKD patients in group A (0.68 ± 0.07) (P < 0.05). The incidence rate of complications in DKD patients in group B was apparently inferior to that in group A. After comprehensive nursing intervention (CNI), the scores of all dimensions of quality of life (QoL) in DKD patients in group B were obviously superior versus those in DKD patients in group A. It suggests that implementation of nursing intervention for DKD patients can effectively help patients improve and control the level of renal function, while ultrasound images based on intelligent algorithm can dynamically detect the changes in the level of renal function in patients, which has the value of clinical promotion.

Diagnostic Performance of Atherosclerotic Carotid Plaque Neovascularization with Contrast-Enhanced Ultrasound: A Meta-Analysis.

Objectives: To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) for atherosclerotic carotid plaque neovascularization. Methods: The electronic databases like PubMed, Embase, OVID, and Web of Science were used to search for the relevant studies, which are involved in the evaluation of the diagnostic parameters of QUS for atherosclerotic carotid plaque neovascularization. Review Manager 5.4 and Stata 14.0 were used to estimate the pooled diagnostic value of CEUS. Forest plots, sensitivity analysis, and Deeks' funnel plots were performed on the included studies. Results: Ten studies eventually met the final inclusion criteria. For diagnostic performance, CUES showed that the pooled values of sensitivity, specificity, positive likelihood odds ratios, negative likelihood odds ratios, and diagnostic odds ratios were 0.83 (95% CI 0.78-0.86), 0.77 (95% CI 0.68-0.84), 3.61 (95% CI 2.59-5.03), 0.23 (95% CI 0.18-0.28), and 16.02 (95% CI 10.02-25.60), respectively. The estimate of the area under curve (AUC) was 0.85 (95% CI 0.82-0.88). Conclusion: Our research supported that CEUS had high sensitivity and specificity in the diagnosis of atherosclerotic carotid plaque neovascularization. More high-quality prospective multicenter studies focusing on the accuracy of CEUS for carotid atherosclerotic plaque should be performed to verify our conclusions.

Ultrasonic Characteristics of Diastasis Recti Abdominis in Early Postpartum.

OBJECTIVE: Explore the ultrasound characteristics of early postpartum Diastasis Recti Abdominis (DRA) and provide effective data support for its clinical diagnosis and treatment. METHOD: A total of 458 parturients who were diagnosed with DRA in the Chongqing Maternal and Child Health Hospital from December 2017 to September 2020 underwent postpartum ultrasound examinations. All of which were located at four points: 6 cm above the umbilicus (point 1), 3 cm above the umbilicus (point 2), umbilicus (point 3), and 3 cm below the umbilicus (point 4) to detect the interrectus distance (IRD) in the resting and sit-up state of the parturients postpartum and to study the differences in maternal age, weight, and ultrasound diagnosis of IRD at different stages after delivery. RESULTS: The IRD values of the four measurement points in the resting state of the parturient were significantly greater than the IRD values in the sit-up state. And in the resting state, the IRD value (4.31 ± 1.07 cm) of the point 3 region was the largest, and there were significant differences at different stages of the postpartum women. At the same time, the IRD values of points 3 and 4 have significant differences in parturient of different ages. In addition, the IRD values of the four measurement points of overweight women were higher than those of nonoverweight women. CONCLUSION: The umbilicus is the best ultrasound evaluation point for early postpartum DRA. The IRD value at this point in the resting state can be used as reference data for evaluating early postpartum DRA, which provides a useful reference for rapid postpartum recovery of parturients.

Restoration Algorithm-Based Ultrasound Image in Evaluating the Effect of Dexmedetomidine on Patients with Neurological Disorder Anesthetized by Sevoflurane.

The study focused on the application value of ultrasound images processed by restoration algorithm in evaluating the effect of dexmedetomidine in preventing neurological disorder in patients undergoing sevoflurane anesthesia. 90 patients undergoing tonsillectomy anesthesia were randomly divided into normal saline group, propofol group, and dexmedetomidine group. The ultrasound images were processed by restoration algorithm, and during the postoperative recovery period, ultrasound images were used to evaluate. The results showed that the original ultrasonic image was fuzzy and contained interference noise, and that the image optimized by restoration algorithm was clear, without excess noise, and the image quality was significantly improved. In the dexmedetomidine group, the extubation time was 10.6 ± 2.3 minutes, the recovery time was 8.4 ± 2.2 minutes, the average pain score during the recovery period was 2.6 ± 0.7, and the average agitation score was 7.2 ± 2.4. Of 30 patients, there were 13 cases with vertigo and 1 case with nausea and vomiting. The vascular ultrasound imaging showed that, in the dexmedetomidine group, the peak systolic velocities (PSV) of the bilateral vertebral arteries during the recovery period were 67.7 ± 14.3 and 67.9 ± 15.2 cm/s, respectively; the end-diastolic velocities (EDV) of the bilateral vertebral arteries were 27.8 ± 6.7 and 24.69 ± 5.9 cm/s, respectively; the PSV in bilateral internal carotid artery systolic peak velocities were 67.2 ± 13.9 and 67.8 ± 12.7 cm/s, respectively; the EDV in bilateral internal carotid arteries were 27.7 ± 5.3 and 26.9 ± 4.9 cm/s, respectively; bilateral vertebral artery resistance indexes (RIs) were 0.6 ± 0.02 and 0.71 ± 0.08, respectively; the bilateral internal carotid artery RIs were 0.57 ± 0.04 and 0.58 ± 0.06, respectively, all better than the normal saline group (12.1 ± 2.5 minutes, 10.1 ± 2.3 minutes, 3.9 ± 0.6, 10.6 ± 3.7, 15 cases, 11 cases, 81.5 ± 13.6, 80.7 ± 11.6 cm/s, 29.3 ± 6.8, 28.9 ± 6.7 cm/s, 74.3 ± 10.2, 73.9 ± 12.5 cm/s, 29.1 ± 4.3, 29 ± 4.5 cm/s, 0.84 ± 0.06, 0.83 ± 0.05, 0.8 ± 0.04, and 0.81 ± 0.05) and the propofol group (11.4 ± 2.1 minutes, 9.0 ± 2.1 minutes, 3.4 ± 0.8, 8.5 ± 2.3, 12 cases, 9 cases, 72.5 ± 12.9, 73.4 ± 11.8 cm/s, 28.6 ± 5.4, 26.5 ± 5.1 cm/s, 72.1 ± 11.4, 73.5 ± 10.6 cm/s, 28.8 ± 5.6, 27.3 ± 4.7 cm/s, 0.78 ± 0.07, 0.82 ± 0.06, 0.76 ± 0.03, and 0.78 ± 0.05), and the differences were statistically significant (P < 0.05). In conclusion, ultrasound images processed by restoration algorithm have high image quality and high resolution. The dexmedetomidine can prevent neurological disorder in patients with sevoflurane anesthesia and is suggested in postoperative rehabilitation.

Random Forest Algorithm-Based Ultrasonic Image in the Diagnosis of Patients with Dry Eye Syndrome and Its Relationship with Tear Osmotic Pressure.

The study was to investigate the diagnostic value of ultrasound based on the random forest segmentation algorithm for dry eye disease and the relationship between dry eye degree and tear osmotic pressure. Specifically, 100 patients with dry eye syndrome were selected as the research subjects, and they were divided into group A (conventional ultrasonic detection) and group B (ultrasonic detection based on the random forest segmentation algorithm), with 50 patients in each group. An ultrasonic measurement was used as the gold standard to evaluate the effect of ultrasonic diagnosis. The degree of dry eye was determined by Ocular Surface Disease Index (OSDI) Questionnaire and DR-1 tear film lipid layer (TFLL) test. The tear osmotic pressure was measured, and the relationship between the degree of dry eye disease and the tear osmotic pressure was analyzed. The results showed that the ultrasonic imaging effect and each index based on random forest algorithm were better than the traditional graph cut algorithm. The average central corneal thickness (CCT) values of group A and group B were (27.8 ± 30.6) µm and (29.1 ± 30.9) µm, respectively. 95% confidence interval was 22.7-34.2 µm. In patients with moderate dry eye, the average CCT measured in group A was (-6.31 ± 2.82) µm, and that in group B was (-6.45 ± 3.06) µm. The 95% confidence interval of the difference between the two is -7.66~-5.43 µm. In patients with severe dry eye, the average CCT was (-3.78 ± 1.13) µm in group A and (-7.09 ± 2.05) µm in group B (P < 0.05). The 95% confidence interval of the difference between the two is -7.05~ -5.11 µm. In spearman correlation analysis, tear osmotic pressure increased with dry eye severity. There was a statistically significant difference between the moderate and the severe (P < 0.05). Tear osmotic pressure can be a rapid diagnostic index of dry eye severity. Ultrasound based on the random forest segmentation algorithm has high clinical application value in the diagnosis of dry eye syndrome.

Establishment and Verification of Logistic Regression Model for Qualitative Diagnosis of Ovarian Cancer Based on MRI and Ultrasound Signs.

OBJECTIVE: To explore the establishment and verification of logistic regression model for qualitative diagnosis of ovarian cancer based on MRI and ultrasonic signs. METHOD: 207 patients with ovarian tumors in our hospital from April 2018 to April 2021 were selected, of which 138 were used as the training group for model creation and 69 as the validation group for model evaluation. The differences of MRI and ultrasound signs in patients with ovarian cancer and benign ovarian tumor in the training group were analyzed. The risk factors were screened by multifactor unconditional logistic regression analysis, and the regression equation was established. The self-verification was carried out by subject working characteristics (ROC), and the external verification was carried out by K-fold cross verification. RESULT: There was no significant difference in age, body mass index, menstruation, dysmenorrhea, times of pregnancy, cumulative menstrual years, and marital status between the two groups (P > 0.05). After logistic regression analysis, the diagnostic model of ovarian cancer was established: logit (P) = -1.153 + [MRI signs : morphology × 1.459 + boundary × 1.549 + reinforcement × 1.492 + tumor components × 1.553] + [ultrasonic signs : morphology × 1.594 + mainly real × 1.417 + separated form × 1.294 + large nipple × 1.271 + blood supply × 1.364]; self-verification: AUC of the model is 0.883, diagnostic sensitivity is 93.94%, and specificity is 80.95%; K-fold cross validation: the training accuracy was 0.904 ± 0.009 and the prediction accuracy was 0.881 ± 0.049. CONCLUSION: Irregular shape, unclear boundary, obvious enhancement in MRI signs, cystic or solid tumor components and irregular shape, solid-dominated shape, thick septate shape, large nipple, and abundant blood supply in ultrasound signs are independent risk factors for ovarian cancer. After verification, the diagnostic model has good accuracy and stability, which provides basis for clinical decision-making.

Edge Detection Algorithm-Based Lung Ultrasound in Evaluation of Efficacy of High-Flow Oxygen Therapy on Critical Lung Injury.

The study focused on the therapeutic effects of high-flow oxygen therapy on patients with critical lung injury using edge detection-based ultrasound images. Firstly, the traditional Canny edge detection algorithm was improved, and the optimal threshold was obtained by optimizing the median filter and combining Otsu algorithm and threshold iteration method. Then, the optimized algorithm was compared with the traditional Canny edge detection algorithm and applied to process the lung ultrasound images of 120 cases of critical lung injury, to compare the efficacy of high-flow oxygen therapy and the traditional oxygen therapy. It was found that the peak signal-to-noise ratio (PSNR) (20.34~31.3), edge intensity value (17.89~27.34), and edge detection effect of the improved Canny algorithm were better than the traditional Canny algorithm (15.2~28.61, 9.44~18.56). The failure rate of extubation (4.1%), reintubation rate (0.8%), comfort (2.38 ± 0.15 points), dry humidity score (1.07 ± 0.21 points), antibiotic use (7.41 ± 0.74 days), and hospital stay (8.66 ± 1.02 days) in the experimental group were significantly lower than the corresponding indexes in the control group (11.7%, 5%, 4.25 ± 0.26 minutes, 4.94 ± 0.78 minutes, 19.29 ± 1.7 days, and 27.49 ± 2.22 days), and the difference was statistically significant (P < 0.05). In the experimental group, within 48 hours after extubation, the respiratory rate (RR), heart rate (HR), arterial partial pressure of carbon dioxide (PaCO2), and HCO3 - were significantly lower than those of the control group; and the values of transcutaneous oxygen saturation (SpO2), mean arterial pressure (MAP), arterial partial pressure of oxygen (PaO2), and pH were significantly higher than the control group, and the difference was statistically significant (P < 0.05). In conclusion, the algorithm in this study is superior to the traditional Canny algorithm, and the high-flow oxygen therapy can reduce the failure rate of extubation, strengthen patient comfort, improve the degree of gas humidification, stabilize the respiratory function and circulatory system, and shorten the time of antibiotic use and hospital stay.

Account of Deep Learning-Based Ultrasonic Image Feature in the Diagnosis of Severe Sepsis Complicated with Acute Kidney Injury.

This study was aimed at analyzing the diagnostic value of convolutional neural network models on account of deep learning for severe sepsis complicated with acute kidney injury and providing an effective theoretical reference for the clinical use of ultrasonic image diagnoses. 50 patients with severe sepsis complicated with acute kidney injury and 50 healthy volunteers were selected in this study. They all underwent ultrasound scans. Different deep learning convolutional neural network models dense convolutional network (DenseNet121), Google inception net (GoogLeNet), and Microsoft's residual network (ResNet) were used for training and diagnoses. Then, the diagnostic results were compared with professional image physicians' artificial diagnoses. The results showed that accuracy and sensitivity of the three deep learning algorithms were significantly higher than professional image physicians' artificial diagnoses. Besides, the error rates of the three algorithm models for severe sepsis complicated with acute kidney injury were significantly lower than professional physicians' artificial diagnoses. The areas under curves (AUCs) of the three algorithms were significantly higher than AUCs of doctors' diagnosis results. The loss function parameters of DenseNet121 and GoogLeNet were significantly lower than that of ResNet, with the statistically significant difference (P < 0.05). There was no significant difference in training time of ResNet, GoogLeNet, and DenseNet121 algorithms under deep learning, as the convergence was reached after 700 times, 700 times, and 650 times, respectively (P > 0.05). In conclusion, the value of the three algorithms on account of deep learning in the diagnoses of severe sepsis complicated with acute kidney injury was higher than professional physicians' artificial judgments and had great clinical value for the diagnoses and treatments of the disease.

Metabolic (Dysfunction)-Associated Fatty Liver Disease in Chinese Patients with Type 2 Diabetes from a Subcenter of the National Metabolic Management Center.

BACKGROUND: Few studies have investigated the epidemiological metabolic (dysfunction) associated with fatty liver disease (MAFLD) in China, especially among those with type 2 diabetes. METHODS: We recruited 3553 patients aged 18-75 years with type 2 diabetes who underwent abdominal ultrasound and serum biochemical analyses. Patient information including demographic and anthropometric parameters was also collected. RESULTS: Overall, 63.2% of type 2 diabetic patients had MAFLD. Among the MAFLD patients, the proportions of lean, nonobese, and obese MAFLD were 23.1%, 75.7%, and 24.3%, respectively, and the percentage of previously undiagnosed MAFLD was 42.2%. MAFLD patients were younger, had shorter diabetic duration, and had greater BMI, aspartate aminotransferase (AST), alanine aminotransferase (ALT), fasting insulin, postprandial insulin, total cholesterol, and insulin resistance levels (HOMA-IR and TyG index). Liver fibrosis diagnostic panels revealed that the proportions of elevated AST (≥40 U/L) and ALT (≥40 U/L) were 7.3% and 18.5%, respectively. The distributions of AST-to-platelet ratio index (APRI), fibrosis-4 (FIB-4) index, and nonalcoholic fatty liver disease fibrosis score (NFS) per stage were as follows: APRI-low 55.1%, indeterminate 35.3%, and high 9.5%; FIB-4-low 48.2%, indeterminate 45.3%, and high 6.5%; and NFS-low 15.0%, indeterminate 70.0%, and high 13.0%. CONCLUSIONS: MAFLD is a very common condition and generally had greater frequency of metabolic characteristics among type 2 diabetics in China. Many MAFLD patients were in the "indeterminate" or "high" stage when APRI, FIB-4, and NFS were assessed. Assessment of MAFLD should be included in the management of type 2 diabetes.

Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation.

This study was aimed at investigating the location of gastric cancer by using a gastroscope image based on an artificial intelligence algorithm for gastric cancer and the effect of ultrasonic-guided nerve block combined with general anesthesia on patients undergoing gastric cancer surgery. A total of 160 patients who were undergoing gastric cancer surgery from March 2019 to March 2021 were collected as the research objects, and the convolutional neural network (CNN) algorithm was used to segment the gastroscope image of gastric cancer. The patients were randomly divided into a simple general anesthesia group of 80 cases and a transversus abdominis plane block combined with rectus abdominis sheath block combined with the general anesthesia group of 80 cases. Then, compare the systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) at the four time points T0, T1, T2, and T3. The times of analgesic drug use within 48 hours after operation and postoperative adverse reactions were recorded. The visual analog scale (VAS) scores were also recorded at 4 h, 12 h, 24 h, and 48 h. The results show that the image quality after segmentation is good: the accuracy of tumor location is 75.67%, which is similar to that of professional endoscopists. Compared with the general anesthesia group, the transversus abdominis plane block combined with the rectus sheath block combined with the general anesthesia group had fewer anesthetics, and the difference was statistically significant (P < 0.05). Compared with the general anesthesia group, SBP, DBP, and HR were significantly reduced at T1, T2, and T3 in the transverse abdominis plane block combined with rectus sheath block and general anesthesia group (P < 0.05). Compared with the simple general anesthesia group, the VAS scores of the transversus abdominis plane block combined with rectus sheath block combined with the general anesthesia group decreased at 4 h, 12 h, and 24 h after surgery, and the difference was statistically significant (P < 0.05). The number of analgesics used in transversus abdominis plane block combined with the rectus sheath block combined with the general anesthesia group within 48 hours after operation was significantly less than that in the general anesthesia group, and the difference was statistically significant (P < 0.05). The average incidence of adverse reactions in the nerve block combined with the general anesthesia group was 2.5%, which was lower than the average incidence of 3.75% in the general anesthesia group. In summary, the CNN algorithm can accurately segment the lesions in the ultrasonic images of gastric cancer, which was convenient for doctors to make a more accurate judgment on the lesions, and provided a basis for the preoperative examination of radical gastrectomy for gastric cancer. Ultrasonic-guided nerve block combined with general anesthesia can effectively improve the analgesic effect of radical gastrectomy for gastric cancer, reduced intraoperative and postoperative adverse reactions and analgesic drug dosage, and had a good effect on postoperative recovery of patients. The combined application of these two methods can further improve the precision treatment of gastric cancer patients and accelerate postoperative recovery.

The Diagnostic Efficacy of the American College of Radiology (ACR) Thyroid Imaging Report and Data System (TI-RADS) and the American Thyroid Association (ATA) Risk Stratification Systems for Thyroid Nodules.

BACKGROUND: This study is aimed at evaluating the diagnostic efficacy of ultrasound-based risk stratification for thyroid nodules in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) risk stratification systems. METHODS: 286 patients with thyroid cancer were included in the tumor group, with 259 nontumor cases included in the nontumor group. The ACR TI-RADS and ATA risk stratification systems assessed all thyroid nodules for malignant risks. The diagnostic effect of ACR and ATA risk stratification system for thyroid nodules was evaluated by receiver operating characteristic (ROC) analysis using postoperative pathological diagnosis as the gold standard. RESULTS: The distributions and mean scores of ACR and ATA rating risk stratification were significantly different between the tumor and nontumor groups. The lesion diameter > 1 cm subgroup had higher malignant ultrasound feature rates detected and ACR and ATA scores. A significant difference was not found in the ACR and ATA scores between patients with or without Hashimoto's disease. The area under the receiver operating curve (AUC) for the ACR TI-RADS and the ATA systems was 0.891 and 0.896, respectively. The ACR had better specificity (0.90) while the ATA system had higher sensitivity (0.92), with both scenarios having almost the same overall diagnostic accuracy (0.84). CONCLUSION: Both the ACR TI-RADS and the ATA risk stratification systems provide a clinically feasible thyroid malignant risk classification, with high thyroid nodule malignant risk diagnostic efficacy.

Construction of a Computer-Aided Analysis System for Orthopedic Diseases Based on High-Frequency Ultrasound Images.

The area of medical diagnosis has been transformed by computer-aided diagnosis (CAD). With the advancement of technology and the widespread availability of medical data, CAD has gotten a lot of attention, and numerous methods for predicting different pathological diseases have been created. Ultrasound (US) is the safest clinical imaging method; therefore, it is widely utilized in medical and healthcare settings with computer-aided systems. However, owing to patient movement and equipment constraints, certain artefacts make identification of these US pictures challenging. To enhance the quality of pictures for classification and segmentation, certain preprocessing techniques are required. Hence, we proposed a three-stage image segmentation method using U-Net and Iterative Random Forest Classifier (IRFC) to detect orthopedic diseases in ultrasound images efficiently. Initially, the input dataset is preprocessed using Enhanced Wiener Filter for image denoising and image enhancement. Then, the proposed segmentation method is applied. Feature extraction is performed by transform-based analysis. Finally, obtained features are reduced to optimal subset using Principal Component Analysis (PCA). The classification is done using the proposed Iterative Random Forest Classifier. The proposed method is compared with the conventional performance measures like accuracy, specificity, sensitivity, and dice score. The proposed method is proved to be efficient for detecting orthopedic diseases in ultrasound images than the conventional methods.

E-Health Ultrasonic Diagnostic Monitoring for Analysis of Cardiac Insufficiency and Neuronal Regulation in Patients with Sepsis in Emergency Department under Image Reconstruction Algorithm.

An anisotropic diffusion filtering- (ADF-) ultrasound (ADF-U) for ultrasound reconstruction was constructed based on the ADF to explore the diagnostic application of ultrasound imaging based on electronic health (E-health) for cardiac insufficiency and neuronal regulation in patients with sepsis. The 144 patients with sepsis were divided into an experimental group (78 patients with cardiac insufficiency) and a control group (66 patients with normal cardiac function), and another 58 healthy people were included in a blank control. The ultrasound examination was performed on all patients. In addition, new ultrasound image reconstruction and diagnosis were performed based on ADF and E-health, and its reconstruction effects were compared with those of the Bilateral Filter-ultrasonic (BFU) algorithm and the Wavelet Threshold-ultrasonic (WTU) algorithm. The left and right ventricular parameters and neuropeptide levels were detected and recorded. The results show that the running time, average gradient (AG), and peak signal-to-noise ratio (SNR) (PSNR) of the ADF-U algorithm were greater than those of the Bilateral Filter-ultrasonic (BFU) and Wavelet Threshold-ultrasonic (WTU), but the mean square error (MSE) was opposite (P < 0.05); the left ventricular end-systolic volume (LVESV) and the vertical distance between the mitral valve E-point to septal separation (EPSS) in the experimental group were higher than those in the control and blank group, while the left ventricular ejection fraction (LVEF), stroke volume (SV), cardiac output (CO), and left ventricular fractional shortening (LVFS) were opposite (P < 0.05); the systolic peak velocity of right ventricular free wall tricuspid annulus (Sm) and pulmonary valve blood velocity (PVBV) in the experimental group were lower than those of the control group and blank group (P < 0.05); the messenger ribonucleic acid (mRNA) of Proopiomelanocortin (POMC) and Cocain and amphetamine-regulated transcript (CART) was higher than the mRNA IN control group and blank group (P < 0.05). In short, the ADF-U algorithm proposed in this study improved the resolution, SNR, and reconstruction efficiency of E-health ultrasound images and provided an effective reference value for the diagnosis of cardiac insufficiency and neuronal adjustment analysis in patients with sepsis in the emergency department.

Cystic fibrosis-related liver disease: Clinical presentations, diagnostic and monitoring approaches in the era of CFTR modulator therapies.

Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population. Cystic fibrosis-related liver disease (CFLD) is defined as the pathogenesis related to the underlying CFTR defect in biliary epithelial cells. CFLD needs to be distinguished from other liver manifestations that may not have any pathological significance. The clinical/histological presentation and severity of CFLD vary. The main histological presentation of CFLD is focal biliary fibrosis, which is usually asymptomatic. Portal hypertension develops in a minority of cases (about 10%) and may require specific management including liver transplantation for end-stage liver disease. Portal hypertension is usually the result of the progression of focal biliary fibrosis to multilobular cirrhosis during childhood. Nevertheless, non-cirrhotic portal hypertension as a result of porto-sinusoidal vascular disease is now identified increasingly more frequently, mainly in young adults. To evaluate the effect of new CFTR modulator therapies on the liver, the spectrum of hepatobiliary involvement must first be precisely classified. This paper discusses the phenotypic features of CFLD, its underlying physiopathology and relevant diagnostic and follow-up approaches, with a special focus on imaging.