Progress in the Application of Lung Ultrasound for the Evaluation of Neonates with Respiratory Distress Syndrome

Neonatal respiratory distress syndrome (NRDS) is a common critical disease in neonates. Early diagnosis and timely treatment are crucial. Historically, X-ray imaging was the primary method for diagnosing NRDS. However, this method carries radiation exposure risks, making it unsuitable for dynamic lung condition monitoring. In addition, neonates who are critically ill require bedside imaging, but diagnostic delays are often unavoidable due to equipment transportation and positioning limitations. These challenges have been resolved with the introduction of lung ultrasound (LUS) in neonatal intensive care. The diagnostic efficacy and specificity of LUS for NRDS is superior to that of X-ray. The non-invasive, dynamic, and real-time benefits of LUS also allow for real-time monitoring of lung changes throughout treatment for NRDS, yielding important insights for guiding therapy. In this paper, we examine the ultrasonographic characteristics of NRDS and the recent progress in the application of ultrasound in the diagnosis and treatment of NRDS while aiming to promote wider adoption of this method.

Lung ultrasound to diagnose infectious pneumonia of newborns: A prospective multicenter study

INTRODUCTION

Whether lung ultrasound (LUS) can be used for pathogenic diagnosis remains controversial. This study was conducted to clarify whether ultrasound has diagnostic value for etiology.

METHODS

A total of 135 neonatal pneumonia patients with an identified pathogen were enrolled from the newborn intensive care units of 10 tertiary hospitals in China. The study ran from November 2020 to December 2021. The infants were divided into various groups according to pathogens, time of infection, gestational age, and disease severity. The distribution of pleural line abnormalities, B-line signs, and pulmonary consolidation, as well as the incidence of air bronchogram and pleural effusion based on LUS, were compared between these groups.

RESULTS

There were significant differences in pulmonary consolidation. The sensitivity and specificity of the diagnosis of severe pneumonia based on the extent of pulmonary consolidation were 83.3% and 85.2%, respectively. The area under the receiver operating characteristic curve for the identification of mild or severe pneumonia based on the distribution of pulmonary consolidation was 0.776.

CONCLUSION

LUS has good performance in diagnosing and differentiating the severity of neonatal pneumonia but cannot be used for pathogenic identification in the early stages of pneumonia.

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning

Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve increased accuracy in diagnosis with higher efficiency. Purpose To determine the feasibility of using a DL approach to predict clinically negative axillary lymph node metastasis from US images in patients with primary breast cancer. Materials and Methods A data set of US images in patients with primary breast cancer with clinically negative axillary lymph nodes from Tongji Hospital (974 imaging studies from 2016 to 2018, 756 patients) and an independent test set from Hubei Cancer Hospital (81 imaging studies from 2018 to 2019, 78 patients) were collected. Axillary lymph node status was confirmed with pathologic examination. Three different convolutional neural networks (CNNs) of Inception V3, Inception-ResNet V2, and ResNet-101 architectures were trained on 90% of the Tongji Hospital data set and tested on the remaining 10%, as well as on the independent test set. The performance of the models was compared with that of five radiologists. The models' performance was analyzed in terms of accuracy, sensitivity, specificity, receiver operating characteristic curves, areas under the receiver operating characteristic curve (AUCs), and heat maps. Results The best-performing CNN model, Inception V3, achieved an AUC of 0.89 (95% confidence interval [CI]: 0.83, 0.95) in the prediction of the final clinical diagnosis of axillary lymph node metastasis in the independent test set. The model achieved 85% sensitivity (35 of 41 images; 95% CI: 70%, 94%) and 73% specificity (29 of 40 images; 95% CI: 56%, 85%), and the radiologists achieved 73% sensitivity (30 of 41 images; 95% CI: 57%, 85%; P = .17) and 63% specificity (25 of 40 images; 95% CI: 46%, 77%; P = .34). Conclusion Using US images from patients with primary breast cancer, deep learning models can effectively predict clinically negative axillary lymph node metastasis. Artificial intelligence may provide an early diagnostic strategy for lymph node metastasis in patients with breast cancer with clinically negative lymph nodes. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Bae in this issue.

Diagnostic Performance Using Automated Breast Ultrasound System for Breast Cancer in Chinese Women Aged 40 Years or Older: A Comparative Study

The purpose of this study was to investigate the diagnostic performance of the automated breast ultrasound system (ABUS) compared with hand-held ultrasonography (HHUS) and mammography (MG) for breast cancer in women aged 40 y or older. A total of 594 breasts in 385 patients were enrolled in the study. HHUS, ABUS and MG exams were performed for these patients. Follow-up and pathologic findings were used as the reference standard. Based on the reference standard, 519 units were benign or normal and 75 were malignant. The sensitivity, specificity, accuracy and Youden index were 97.33%, 89.79%, 90.74% and 0.87 for HHUS; 90.67%, 92.49%, 92.26% and 0.83 for ABUS; 84.00%, 92.87%, 91.75% and 0.77 for MG, respectively. The specificity of ABUS was significantly superior to that of HHUS (p = 0.024). The area under the receiver operating characteristic curve was 0.936 for HHUS, which was the highest, followed by 0.916 for ABUS and 0.884 for MG. However, the difference was not statistically significant (p > 0.05). In conclusion, the diagnostic performance of ABUS for breast cancer was equivalent to HHUS and MG and potentially can be used as an alternative method for breast cancer diagnosis.

Protein kinase C isoform expression and function in transformed and non-transformed pancreatic acinar cell lines

Members of the protein kinase C (PKC) family of multifunctional serine/threonine phosphorylating enzymes are believed to play a role in regulating cellular differentiation and proliferation in many cell types. In the present study, we examined the expression of PKC isoforms in non-transformed (BMRPA.430) and transformed (TUC3) rat pancreatic acinar cell lines and compared this to PKC expression in freshly dispersed acini from rat pancreas. BMRPA.430 cells maintain characteristics of normal acini and are not tumorigenic, whereas TUC3 cells do not express tight junctions or polygonal morphology and are tumorigenic. As reported previously, PKC alpha, delta, epsilon, and zeta are expressed in freshly prepared acini. Likewise, these isoforms were detected in both the BMRPA.430 and TUC3 cell lines. In addition, PKC theta, a novel isoform, was detected in all three cell types at low levels. We used two PKC inhibitors to examine the role of PKC in acinar cell proliferation. CGP 41 251, a selective PKC inhibitor, and Go 6976, an agent which specifically inhibits calcium-dependent PKC isoforms, inhibited cell proliferation of both cell lines. Translocation of PKC alpha to the membrane was not observed in either cell line. Hence, our data indicate that ras-induced transformation does not alter PKC isoform expression in pancreatic acinar cells and that activation of PKC alpha is involved with acinar cell growth.

Activation of chemical carcinogens by cultured human fetal liver, esophagus and stomach

Cultured fetal human stomach, esophagus and liver activated benzo[a]pyrene (BP), aflatoxin B1 (AFB) and certain N-nitrosamines into metabolites that bound to cellular DNA. When the 3 organs were compared the highest level of activity was observed in the stomach. The interindividual variation was 10-fold and the amount of carcinogen-DNA adducts did not correlate with the sex or age of the fetus. The reaction products between BP or AFB and cellular DNA were investigated in liver explants. The carcinogen-DNA adduct patterns were identical to those observed in adult human tissues; BPDEI-Gua being the major adduct formed by BP and 2,3-dihydro-2-(7'-guanyl)-3-hydroxy-AFB by AFB. The results indicate that fetal organs can metabolize those oncogenic compounds at an early stage of the development, and that the metabolic pathways and DNA adducts are quite similar to those in experimental animals in which the compounds are carcinogenic.