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1.
PeerJ ; 12: e17005, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38435997

RESUMO

Various segmentation networks based on Swin Transformer have shown promise in medical segmentation tasks. Nonetheless, challenges such as lower accuracy and slower training convergence have persisted. To tackle these issues, we introduce a novel approach that combines the Swin Transformer and Deformable Transformer to enhance overall model performance. We leverage the Swin Transformer's window attention mechanism to capture local feature information and employ the Deformable Transformer to adjust sampling positions dynamically, accelerating model convergence and aligning it more closely with object shapes and sizes. By amalgamating both Transformer modules and incorporating additional skip connections to minimize information loss, our proposed model excels at rapidly and accurately segmenting CT or X-ray lung images. Experimental results demonstrate the remarkable, showcasing the significant prowess of our model. It surpasses the performance of the standalone Swin Transformer's Swin Unet and converges more rapidly under identical conditions, yielding accuracy improvements of 0.7% (resulting in 88.18%) and 2.7% (resulting in 98.01%) on the COVID-19 CT scan lesion segmentation dataset and Chest X-ray Masks and Labels dataset, respectively. This advancement has the potential to aid medical practitioners in early diagnosis and treatment decision-making.


Assuntos
COVID-19 , Humanos , COVID-19/diagnóstico por imagem , Fontes de Energia Elétrica , Pessoal de Saúde , Pemolina , Tórax
2.
Respir Res ; 25(1): 111, 2024 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-38443957

RESUMO

BACKGROUND: Access to timely and accurate diagnostic imaging is essential for high-quality healthcare. Point-of-care ultrasound has been shown to be accessible and effective in many aspects of healthcare, including assessing changes in lung pathology. However, few studies have examined self-administered at-home lung ultrasound (SAAH-LUS), in particular performed by non-clinical patients (NCPs). RESEARCH QUESTION: Are NCPs able to perform SAAH-LUS using remote teleguidance and produce interpretable images? STUDY DESIGN: Patients were enrolled to the study in a mix of in-person and virtual recruitment, and shipped a smartphone as well as a point of care ultrasound device. Tele-guidance was provided by a remote physician using software integrated with the point of care ultrasound device, allowing real-time remote visualization and guidance of a patient scanning their own chest. A post-intervention survey was conducted to assess patient satisfaction, feasibility, and acceptability of SAAH-LUS. Two POCUS expert reviewers reviewed the scans for interpretability, and inter-rater agreement between the two reviewers was also computed. RESULTS: Eighteen patients successfully underwent 7-14 days of daily telemedicine in parallel to daily SAAH-LUS. Across 1339 scans obtained from ten different lung zones, the average proportion of interpretability was 96% with a chance-corrected agreement, or Cohen's kappa, reported as κ = 0.67 (significant agreement). 100% of NCPs surveyed found SAAH-LUS to be a positive experience, particularly for its ease of operation and ability to increase access to healthcare services. INTERPRETATION: This study demonstrates that NCPs can obtain interpretable LUS images at home, highlighting the potential for SAAH-LUS to increase diagnostic capacity, particularly for rural and remote regions where complex imaging and healthcare providers are difficult to obtain. Trial registration The clinical trials has been registered (clinicaltrials.gov). REGISTRATION NUMBER: NCT04967729.


Assuntos
Pessoal de Saúde , Tórax , Humanos , Pulmão/diagnóstico por imagem , Satisfação do Paciente , Ultrassonografia
3.
Kyobu Geka ; 77(3): 206-209, 2024 Mar.
Artigo em Japonês | MEDLINE | ID: mdl-38465492

RESUMO

We report a case of bioprosthetic valve dysfunction and acute aortic valve regurgitation. The case was a 75-year-old female who had sudden onset chest pain. ST-segment depression in several leads on electrocardiogram( ECG) suggested acute coronary syndrome. Coronary angiography showed no significant stenosis in coronary arteries. Transesophageal echocardiography revealed severe aortic regurgitation, suggesting that angina was caused by myocardial ischemia associated with acute aortic regurgitation. She was diagnosed as having bioprosthetic valve dysfunction, and underwent redo aortic valve replacement. One leaflet of the bioprosthetic valve was torn along the stent post and caused bioprosthetic valve dysfunction. Failed bioprosthetic valve was removed and replaced by a mechanical valve.


Assuntos
Insuficiência da Valva Aórtica , Bioprótese , Implante de Prótese de Valva Cardíaca , Próteses Valvulares Cardíacas , Feminino , Humanos , Idoso , Insuficiência da Valva Aórtica/diagnóstico por imagem , Insuficiência da Valva Aórtica/etiologia , Insuficiência da Valva Aórtica/cirurgia , Valva Aórtica/diagnóstico por imagem , Valva Aórtica/cirurgia , Tórax , Próteses Valvulares Cardíacas/efeitos adversos , Dor no Peito/etiologia , Bioprótese/efeitos adversos , Implante de Prótese de Valva Cardíaca/efeitos adversos
5.
Biomed Eng Online ; 23(1): 29, 2024 Mar 06.
Artigo em Inglês | MEDLINE | ID: mdl-38448872

RESUMO

OBJECTIVE: To explore the predictive value of bedside lung ultrasound score in the severity of neonatal respiratory distress syndrome (NRDS) and mechanical ventilation and extubation. METHODS: The clinical data of 65 neonates with NRDS and invasive mechanical ventilation diagnosed in the neonatal intensive care unit of our hospital from July 2021 to July 2022 were retrospectively analyzed. 65 neonates were included in the NRDS group, and 40 neonates with other common lung diseases were selected as the other lung disease groups. All neonates underwent lung ultrasound and X-ray examination. The correlation between lung ultrasound scores and arterial blood gas indexes was analyzed by Pearson. The efficacy of successful evacuation of mechanical ventilation was evaluated by lung ultrasound analysis by ROC curve analysis. RESULTS: The positive rates of lung consolidation and white lung in NRDS group were higher than the other lung disease groups (P < 0.05). The positive rates of bronchial inflation sign and double lung points were lower than these in the other lung disease groups (P < 0.05). The ultrasound scores of both lungs, left lung, right lung, bilateral lung and double basal lung in the NRDS group were significantly higher than those in the other lung disease groups (P < 0.05). There was a significant positive correlation between lung ultrasound score and X-ray grade (r = 0.841, P < 0.001). The area under the curve (AUC) of lung ultrasound score for the differential diagnosis of NRDS and common lung diseases was 0.907. The AUC of lung ultrasound score in the differential diagnosis of mild and moderate, and moderate and severe NRDS were 0.914 and 0.933, respectively, which had high clinical value. The lung ultrasound score was positively correlated with the level of PaCO2 (r = 0.254, P = 0.041), and negatively correlated with the levels of SpO2 and PaO2 (r = - 0.459, - 0.362, P = 0.001, 0.003). The AUC of successful mechanical ventilation withdrawal predicted by the pulmonary ultrasound score before extubation was 0.954 (95% CI 0.907-1.000). The predictive value of successful extubation was 10 points of the pulmonary ultrasound score, with a sensitivity of 93.33% and a specificity of 88.00%. CONCLUSION: The bedside lung ultrasound score can intuitively reflect the respiratory status of neonates, which provides clinicians with an important basis for disease evaluation.


Assuntos
Síndrome do Desconforto Respiratório do Recém-Nascido , Recém-Nascido , Humanos , Estudos Retrospectivos , Síndrome do Desconforto Respiratório do Recém-Nascido/diagnóstico por imagem , Tórax , Brônquios , Ultrassonografia
6.
Georgian Med News ; (346): 119-123, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-38501633

RESUMO

The constant increase in the level of traumatic brain injuries in recent years, the frequent cases of disability and mortality associated with them require in-depth comprehensive research to study the problem on the ground, its medical, social, and economic aspects, which is very important for improving organizational measures to reduce traumatization among all age groups of the population. Objectives - to determine the presence and nature of structural damage associated with traumatic brain injury. The presence and nature of structural damage associated with traumatic brain injury. The studies included data on the treatment of victims with traumatic brain injuries from 2016 to 2020 on the basis of the Surgical Clinic of the Azerbaijan Medical University. Among the victims, men accounted for 77.9% and women 22.1%. In a prospective comparative study, after signing informed consent, 299 people of different sexes were included, of which 90 were victims with isolated TBI. The inclusion criteria for the study were as follows: victims with a verified diagnosis of TBI; age over 18; patients without concomitant somatic pathology. In a gender-comparative analysis of the revealed data, an injury combined with fractures of the bones of the extremities was recorded in 77 (81.1%) males and 18 of their female opponents, who also received TBI and accounted for 18.9%. Also high, especially in the male half of the examined injured persons, was the frequency of occurrence of TBI combinations with rib fractures and injuries of the chest organs, such injuries were registered in 41 victims, which accounted for 77.4% of all the above combined TBI. Somewhat less in both sex groups was TBI in combination with traumatic injuries of organs and tissues of the abdominal region, as well as with mixed injuries (χ2 criterion is 2.066; Df=4; p=0.724). The lowest level of TBI was observed in people under the age of 20 and older than 70 years, in other groups this figure increased sharply, reaching a maximum at the age of 20-29 and 40-49 years, and stabilized in the age groups over 49 years. The maximum number of cases associated with partial or complete loss of consciousness was recorded in persons aggravated by simultaneous traumatization of the upper or lower extremities and chest, as well as in isolated TBI.


Assuntos
Lesões Encefálicas Traumáticas , Lesões Encefálicas , Fraturas Ósseas , Humanos , Masculino , Feminino , Idoso , Pessoa de Meia-Idade , Estudos Prospectivos , Lesões Encefálicas Traumáticas/diagnóstico , Lesões Encefálicas Traumáticas/epidemiologia , Tórax
7.
Comput Biol Med ; 171: 108203, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38430741

RESUMO

The value of coarsely labeled datasets in learning transferable representations for medical images is investigated in this work. Compared to fine labels which require meticulous effort to annotate, coarse labels can be acquired at a significantly lower cost and can provide useful training signals for data-hungry deep neural networks. We consider coarse labels in the form of binary labels differentiating a normal (healthy) image from an abnormal (diseased) image and propose CAMContrast, a two-stage representation learning framework for medical images. Using class activation maps, CAMContrast makes use of the binary labels to generate heatmaps as positive views for contrastive representation learning. Specifically, the learning objective is optimized to maximize the agreement within fixed crops of image-heatmap pair to learn fine-grained representations that are generalizable to different downstream tasks. We empirically validate the transfer learning performance of CAMContrast on several public datasets, covering classification and segmentation tasks on fundus photographs and chest X-ray images. The experimental results showed that our method outperforms other self-supervised and supervised pretrain methods in terms of data efficiency and downstream performance.


Assuntos
Aprendizagem , Redes Neurais de Computação , Tórax
8.
Physiol Meas ; 45(3)2024 Mar 21.
Artigo em Inglês | MEDLINE | ID: mdl-38430565

RESUMO

Objective. Unobtrusive long-term monitoring of cardiac parameters is important in a wide variety of clinical applications, such as the assesment of acute illness severity and unobtrusive sleep monitoring. Here we determined the accuracy and robustness of heartbeat detection by an accelerometer worn on the chest.Approach. We performed overnight recordings in 147 individuals (69 female, 78 male) referred to two sleep centers. Two methods for heartbeat detection in the acceleration signal were compared: one previously described approach, based on local periodicity, and a novel extended method incorporating maximumaposterioriestimation and a Markov decision process to approach an optimal solution.Main results. The maximumaposterioriestimation significantly improved performance, with a mean absolute error for the estimation of inter-beat intervals of only 3.5 ms, and 95% limits of agreement of -1.7 to +1.0 beats per minute for heartrate measurement. Performance held during posture changes and was only weakly affected by the presence of sleep disorders and demographic factors.Significance. The new method may enable the use of a chest-worn accelerometer in a variety of applications such as ambulatory sleep staging and in-patient monitoring.


Assuntos
Sono , Tórax , Humanos , Masculino , Feminino , Frequência Cardíaca , Monitorização Fisiológica , Acelerometria , Processamento de Sinais Assistido por Computador
9.
Zhonghua Jie He He Hu Xi Za Zhi ; 47(3): 244-248, 2024 Mar 12.
Artigo em Chinês | MEDLINE | ID: mdl-38448176

RESUMO

Following the global outbreak of COVID-19, many patients have suffered from multi-system complications and long-term sequelae caused by the virus. Diaphragm dysfunction is an obscure post-COVID-19 symptom. Although a few cases of diaphragm dysfunction caused by COVID-19 infection have been reported abroad, there are no relevant reports in China. Herein, we present two cases of patients with respiratory distress after COVID-19 infection. On admission, dynamic chest radiographs revealed diaphragm dysfunction in these patients. Further investigations including diaphragm ultrasound, neurophysiological examinations, transdiaphragmatic pressure measurements cranial MRI, and antibody testing for autoimmune diseases, were conducted. The final diagnoses were severe myasthenia gravis induced by COVID-19 infection and diaphragmatic nerve and muscle involvement caused by COVID-19 infection. Both patients showed improvement in symptoms after treatment. Therefore, we summarized our case, with a review of the relevant literature to improve the understanding of the disease and to provide clinical evidence for future diagnosis and treatment.


Assuntos
Doenças Autoimunes , COVID-19 , Humanos , Diafragma , Tórax , China
10.
Radiat Oncol ; 19(1): 34, 2024 Mar 12.
Artigo em Inglês | MEDLINE | ID: mdl-38475815

RESUMO

BACKGROUND: FLASH therapy is a treatment technique in which radiation is delivered at ultra-high dose rates (≥ 40 Gy/s). The first-in-human FAST-01 clinical trial demonstrated the clinical feasibility of proton FLASH in the treatment of extremity bone metastases. The objectives of this investigation are to assess the toxicities of treatment and pain relief in study participants with painful thoracic bone metastases treated with FLASH radiotherapy, as well as workflow metrics in a clinical setting. METHODS: This single-arm clinical trial is being conducted under an FDA investigational device exemption (IDE) approved for 10 patients with 1-3 painful bone metastases in the thorax, excluding bone metastases in the spine. Treatment will be 8 Gy in a single fraction administered at ≥ 40 Gy/s on a FLASH-enabled proton therapy system delivering a single transmission proton beam. Primary study endpoints are efficacy (pain relief) and safety. Patient questionnaires evaluating pain flare at the treatment site will be completed for 10 consecutive days post-RT. Pain response and adverse events (AEs) will be evaluated on the day of treatment and on day 7, day 15, months 1, 2, 3, 6, 9, and 12, and every 6 months thereafter. The outcomes for clinical workflow feasibility are the occurrence of any device issues as well as time on the treatment table. DISCUSSION: This prospective clinical trial will provide clinical data for evaluating the efficacy and safety of proton FLASH for palliation of bony metastases in the thorax. Positive findings will support the further exploration of FLASH radiation for other clinical indications including patient populations treated with curative intent. REGISTRATION: ClinicalTrials.gov NCT05524064.


Assuntos
Neoplasias Ósseas , Prótons , Humanos , Neoplasias Ósseas/radioterapia , Dor , Estudos Prospectivos , Tórax
12.
Sci Rep ; 14(1): 5890, 2024 03 11.
Artigo em Inglês | MEDLINE | ID: mdl-38467705

RESUMO

In the realm of healthcare, the demand for swift and precise diagnostic tools has been steadily increasing. This study delves into a comprehensive performance analysis of three pre-trained convolutional neural network (CNN) architectures: ResNet50, DenseNet121, and Inception-ResNet-v2. To ensure the broad applicability of our approach, we curated a large-scale dataset comprising a diverse collection of chest X-ray images, that included both positive and negative cases of COVID-19. The models' performance was evaluated using separate datasets for internal validation (from the same source as the training images) and external validation (from different sources). Our examination uncovered a significant drop in network efficacy, registering a 10.66% reduction for ResNet50, a 36.33% decline for DenseNet121, and a 19.55% decrease for Inception-ResNet-v2 in terms of accuracy. Best results were obtained with DenseNet121 achieving the highest accuracy at 96.71% in internal validation and Inception-ResNet-v2 attaining 76.70% accuracy in external validation. Furthermore, we introduced a model ensemble approach aimed at improving network performance when making inferences on images from diverse sources beyond their training data. The proposed method uses uncertainty-based weighting by calculating the entropy in order to assign appropriate weights to the outputs of each network. Our results showcase the effectiveness of the ensemble method in enhancing accuracy up to 97.38% for internal validation and 81.18% for external validation, while maintaining a balanced ability to detect both positive and negative cases.


Assuntos
COVID-19 , Tórax , Humanos , Raios X , Tórax/diagnóstico por imagem , COVID-19/diagnóstico por imagem , Entropia , Instalações de Saúde
14.
Comput Med Imaging Graph ; 113: 102344, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38320336

RESUMO

Cone Beam Computed Tomography (CBCT) plays a crucial role in Image-Guided Radiation Therapy (IGRT), providing essential assurance of accuracy in radiation treatment by monitoring changes in anatomical structures during the treatment process. However, CBCT images often face interference from scatter noise and artifacts, posing a significant challenge when relying solely on CBCT for precise dose calculation and accurate tissue localization. There is an urgent need to enhance the quality of CBCT images, enabling a more practical application in IGRT. This study introduces EGDiff, a novel framework based on the diffusion model, designed to address the challenges posed by scatter noise and artifacts in CBCT images. In our approach, we employ a forward diffusion process by adding Gaussian noise to CT images, followed by a reverse denoising process using ResUNet with an attention mechanism to predict noise intensity, ultimately synthesizing CBCT-to-CT images. Additionally, we design an energy-guided function to retain domain-independent features and discard domain-specific features during the denoising process, enhancing the effectiveness of CBCT-CT generation. We conduct numerous experiments on the thorax dataset and pancreas dataset. The results demonstrate that EGDiff performs better on the thoracic tumor dataset with SSIM of 0.850, MAE of 26.87 HU, PSNR of 19.83 dB, and NCC of 0.874. EGDiff outperforms SoTA CBCT-to-CT synthesis methods on the pancreas dataset with SSIM of 0.754, MAE of 32.19 HU, PSNR of 19.35 dB, and NCC of 0.846. By improving the accuracy and reliability of CBCT images, EGDiff can enhance the precision of radiation therapy, minimize radiation exposure to healthy tissues, and ultimately contribute to more effective and personalized cancer treatment strategies.


Assuntos
Tomografia Computadorizada de Feixe Cônico Espiral , Reprodutibilidade dos Testes , Tórax , Imagens de Fantasmas
15.
PLoS One ; 19(2): e0299040, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38408041

RESUMO

Understanding the dynamic deformation pattern and biomechanical properties of breasts is crucial in various fields, including designing ergonomic bras and customized prostheses, as well as in clinical practice. Previous studies have recorded and analyzed the dynamic behaviors of the breast surface using 4D scanning, which provides a sequence of 3D meshes during movement with high spatial and temporal resolutions. However, these studies are limited by the lack of robust and automated data processing methods which result in limited data coverage or error-prone analysis results. To address this issue, we identify revealing inter-frame dense correspondence as the core challenge towards conducting reliable and consistent analysis of the 4D scanning data. We proposed a fully-automatic approach named Ulta-dense Motion Capture (UdMC) using Thin-plate Spline (TPS) to augment the sparse landmarks recorded via motion capture (MoCap) as initial dense correspondence and then rectified it with a sophisticated post-alignment scheme. Two downstream tasks are demonstrated to validate its applicability: virtual landmark tracking and deformation intensity analysis. For evaluation, a dynamic 4D human breast anthropometric dataset DynaBreastLite was constructed. The results show that our approach can robustly capture the dynamic deformation characteristics of the breast surfaces, significantly outperforms baselines adapted from previous works in terms of accuracy, consistency, and efficiency. For 10 fps dataset, average error of 0.25 cm on control-landmarks and 0.33 cm on non-control (arbitrary) landmarks were achieved, with 17-70 times faster computation time. Evaluation was also carried out on 60 fps and 120 fps datasets, with consistent and large performance gaining being observed. The proposed method may contribute to advancing research in breast anthropometry, biomechanics, and ergonomics by enabling more accurate tracking of the breast surface deformation patterns and dynamic characteristics.


Assuntos
Captura de Movimento , Movimento , Humanos , Movimento (Física) , Tórax
16.
BMC Pulm Med ; 24(1): 101, 2024 Feb 27.
Artigo em Inglês | MEDLINE | ID: mdl-38413932

RESUMO

BACKGROUND: Pulmonary arterial hypertension is a serious medical condition. However, the condition is often misdiagnosed or a rather long delay occurs from symptom onset to diagnosis, associated with decreased 5-year survival. In this study, we developed and tested a deep-learning algorithm to detect pulmonary arterial hypertension using chest X-ray (CXR) images. METHODS: From the image archive of Chiba University Hospital, 259 CXR images from 145 patients with pulmonary arterial hypertension and 260 CXR images from 260 control patients were identified; of which 418 were used for training and 101 were used for testing. Using the testing dataset for each image, the algorithm outputted a numerical value from 0 to 1 (the probability of the pulmonary arterial hypertension score). The training process employed a binary cross-entropy loss function with stochastic gradient descent optimization (learning rate parameter, α = 0.01). In addition, using the same testing dataset, the algorithm's ability to identify pulmonary arterial hypertension was compared with that of experienced doctors. RESULTS: The area under the curve (AUC) of the receiver operating characteristic curve for the detection ability of the algorithm was 0.988. Using an AUC threshold of 0.69, the sensitivity and specificity of the algorithm were 0.933 and 0.982, respectively. The AUC of the algorithm's detection ability was superior to that of the doctors. CONCLUSION: The CXR image-derived deep-learning algorithm had superior pulmonary arterial hypertension detection capability compared with that of experienced doctors.


Assuntos
Aprendizado Profundo , Hipertensão Arterial Pulmonar , Humanos , Inteligência Artificial , Hipertensão Arterial Pulmonar/diagnóstico por imagem , Raios X , Tórax
17.
PLoS One ; 19(2): e0298015, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38421996

RESUMO

The evaluation of the structural integrity of mechanically dynamic organs such as lungs is critical for the diagnosis of numerous pathologies and the development of therapies. This task is classically performed by histology experts in a qualitative or semi-quantitative manner. Automatic digital image processing methods appeared in the last decades, and although immensely powerful, tools are highly specialized and lack the versatility required in various experimental designs. Here, a set of scripts for the image processing software ImageJ/Fiji to easily quantify fibrosis extend and alveolar airspace availability in Sirius Red or Masson's trichrome stained samples is presented. The toolbox consists in thirteen modules: sample detection, particles filtration (automatic and manual), border definition, air ducts identification, air ducts walls definition, parenchyma extraction, MT-staining specific pre-processing, fibrosis detection, fibrosis particles filtration, airspace detection, and visualizations (tissue only or tissue and airspace). While the process is largely automated, critical parameters are accessible to the user for increased adaptability. The modularity of the protocol allows for its adjustment to alternative experimental settings. Fibrosis and airspace can be combined as an evaluation of the structural integrity of the organ. All settings and intermediate states are saved to ensure reproducibility. These new analysis scripts allow for a rapid quantification of fibrosis and airspace in a large variety of experimental settings.


Assuntos
Corantes , Tórax , Reprodutibilidade dos Testes , Filtração , Pulmão
18.
NEJM Evid ; 3(1): EVIDmr2300293, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-38320515

RESUMO

A 14-Year-Old Girl with Dyspnea and Chest PainA 14-year-old girl presented for evaluation of shortness of breath and chest pain after recent travel to the Caribbean. How do you approach the evaluation, and what is the diagnosis?


Assuntos
Dor no Peito , Dispneia , Feminino , Humanos , Adolescente , Tórax , Diagnóstico Diferencial , Região do Caribe
19.
Zhonghua Jie He He Hu Xi Za Zhi ; 47(2): 172-177, 2024 Feb 12.
Artigo em Chinês | MEDLINE | ID: mdl-38309970

RESUMO

The use of lung ultrasound in the screening, diagnosis, and evaluation of interstitial lung disease has been relatively well studied, but has not been widely accepted and applied in clinical practice. There are also some differences in the examination methods applied in these studies. This paper summarized the application, advantages, and disadvantages of lung ultrasound in the diagnosis and follow-up of interstitial lung disease by comprehensively reviewing the examination methods, research results and progress of new technologies of lung ultrasound in interstitial lung disease.


Assuntos
Doenças Pulmonares Intersticiais , Humanos , Doenças Pulmonares Intersticiais/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Ultrassonografia/métodos , Tórax
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