Target sign in COVID-19, radiological interpretation and diagnostic contribution of digital thoracic tomosynthesis.

INTRODUCTION: Our objectives are: To describe the radiological semiology, clinical-analytical features and prognosis related to the target sign (TS) in COVID-19. To determine whether digital thoracic tomosynthesis (DTT) improves the diagnostic ability of radiography. MATERIAL AND METHODS: Retrospective, descriptive, single-centre, case series study, accepted by our ethical committee. Radiological, clinical, analytical and follow-up characteristics of patients with COVID-19 and TS on radiography and DTT between November 2020 and January 2021 were analysed. RESULTS: Eleven TS were collected in 7 patients, median age 35 years, 57% male. All TS presented with a central nodule and a peripheral ring, and in at least 82%, the lung in between was of normal density. All TS were located in peripheral, basal regions and 91% in posterior regions. TS were multiple in 43%. Contiguous TS shared the peripheral ring. Other findings related to pneumonia were associated in 86% of patients. DTT detected 82% more TS than radiography. Only one patient underwent a CT angiography of the pulmonary arteries, positive for acute pulmonary thromboembolism. Seventy-one per cent presented with pleuritic pain. No distinctive laboratory findings or prognostic worsening were detected. CONCLUSIONS: TS in COVID-19 predominates in peripheral and declining regions and can be multiple. Pulmonary thromboembolism was detected in one case. It occurs in young people, frequently with pleuritic pain and does not worsen the prognosis. DTT detects more than 80 % of TS than radiography.

¿Es necesario utilizar protectores de gónadas durante la realización de radiografías de tórax en los lactantes? / Is the use of gonad protection protectors necessary during infants chest radiography?

Introducción y objetivos: Comparar las dosis de radiación en las gónadas con y sin protector gonadal y optimizar el uso de estos protectores al realizar radiografías de tórax a lactantes. Materiales y métodos: Se utilizan 2 maniquíes antropomórficos pediátricos, un sistema de rayos X KXO-50SS/DRX-3724HD, y un sistema de radiografía digital CALNEO Smart C12, con y sin protector de gónadas durante la realización de radiografías de tórax. Se coloca un dosímetro cutáneo en tiempo real en el sistema de rayos X y se inserta un dosímetro cutáneo en tiempo real en la cara anterior de la glándula mamaria, en la cara anterior y posterior de la pelvis verdadera, y en los ovarios y testículos. El sistema de rayos X se irradia 15 veces con maniquíes, con y sin el protector de gónadas. Se comparan los valores de las dosis de entrada del paciente medidos por el dosímetro cutáneo en tiempo real para cada maniquí, con y sin el protector de gónadas. Resultados: Los valores medios de las dosis a la entrada del paciente medidos para la cara anterior a nivel de la pelvis verdadera, con y sin el protector, son 10,00 y 5,00μGy en el recién nacido, y 10,00 y 0,00μGy al año, respectivamente. Los valores medios de las dosis a la entrada del paciente medidos para la cara posterior a nivel de la pelvis verdadera con y sin el protector son de 0,00 y 0,00μGy tanto en el recién nacido como al año, respectivamente. Las dosis a la entrada del paciente medidas no se pueden detectar en los ovarios y los testículos ni con el protector ni sin él. No se observan diferencias significativas en los valores de las dosis a la entrada del paciente medidas en la cara anterior y posterior de la pelvis, los ovarios y los testículos en el recién nacido y al año, con y sin el protector (p>0,05).(AU)

Introduction and objectives: To compare gonad doses with and without a gonad protector and to optimize the use of gonadal protectors in infants thorax radiography. Materials and methods: Two pediatric anthropomorphic phantoms are used: an X-ray system for KXO-50SS/DRX-3724HD, and a digital radiography system for CALNEO Smart C12, with and without a gonad protector during infants thorax radiography. A real time skin dosimeter is placed on the X-ray system, and a real time skin dosimeter is inserted on the front side of the mammary gland, the front and back sides of the true pelvis level, and on the ovaries and testes. The X-ray system is irradiated 15 times using phantoms with and without a gonad protector. The measured entrance patient doses values of for the real time skin dosimeter are compared for each phantom, with and without the gonad protector. Results: The medium of measured entrance patient doses values for front side dose of the true pelvis level with and without the protector are 10.00 and 5.00μGy at newborn, and 10.00 and 0.00μGy at one year, respectively. The medium of measured entrance patient doses values for the back side dose of the true pelvis level with and without the protector are 0.00 and 0.00μGy at both newborn one year, respectively. The measured entrance patient doses cannot be detected in the ovaries and testes with or without the protector. No significant differences are observed in the measured entrance patient doses values for the front and back side doses of the pelvis, ovaries, and testes at newborn and one year, with and without the protector (p>0.05). Conclusions: No significant difference was observed in gonad dose measurements with and without the gonad protector during infants chest radiography. We believe that gonadal protector wearing is not necessary.(AU)

Deep learning model for pleural effusion detection via active learning and pseudo-labeling: a multisite study.

BACKGROUND: The study aimed to develop and validate a deep learning-based Computer Aided Triage (CADt) algorithm for detecting pleural effusion in chest radiographs using an active learning (AL) framework. This is aimed at addressing the critical need for a clinical grade algorithm that can timely diagnose pleural effusion, which affects approximately 1.5 million people annually in the United States. METHODS: In this multisite study, 10,599 chest radiographs from 2006 to 2018 were retrospectively collected from an institution in Taiwan to train the deep learning algorithm. The AL framework utilized significantly reduced the need for expert annotations. For external validation, the algorithm was tested on a multisite dataset of 600 chest radiographs from 22 clinical sites in the United States and Taiwan, which were annotated by three U.S. board-certified radiologists. RESULTS: The CADt algorithm demonstrated high effectiveness in identifying pleural effusion, achieving a sensitivity of 0.95 (95% CI: [0.92, 0.97]) and a specificity of 0.97 (95% CI: [0.95, 0.99]). The area under the receiver operating characteristic curve (AUC) was 0.97 (95% DeLong's CI: [0.95, 0.99]). Subgroup analyses showed that the algorithm maintained robust performance across various demographics and clinical settings. CONCLUSION: This study presents a novel approach in developing clinical grade CADt solutions for the diagnosis of pleural effusion. The AL-based CADt algorithm not only achieved high accuracy in detecting pleural effusion but also significantly reduced the workload required for clinical experts in annotating medical data. This method enhances the feasibility of employing advanced technological solutions for prompt and accurate diagnosis in medical settings.

Improving Computer-Aided Thoracic Disease Diagnosis through Comparative Analysis Using Chest X-ray Images Taken at Different Times.

Medical professionals in thoracic medicine routinely analyze chest X-ray images, often comparing pairs of images taken at different times to detect lesions or anomalies in patients. This research aims to design a computer-aided diagnosis system that enhances the efficiency of thoracic physicians in comparing and diagnosing X-ray images, ultimately reducing misjudgments. The proposed system encompasses four key components: segmentation, alignment, comparison, and classification of lung X-ray images. Utilizing a public NIH Chest X-ray14 dataset and a local dataset gathered by the Chiayi Christian Hospital in Taiwan, the efficacy of both the traditional methods and deep-learning methods were compared. Experimental results indicate that, in both the segmentation and alignment stages, the deep-learning method outperforms the traditional method, achieving higher average IoU, detection rates, and significantly reduced processing time. In the comparison stage, we designed nonlinear transfer functions to highlight the differences between pre- and post-images through heat maps. In the classification stage, single-input and dual-input network architectures were proposed. The inclusion of difference information in single-input networks enhances AUC by approximately 1%, and dual-input networks achieve a 1.2-1.4% AUC increase, underscoring the importance of difference images in lung disease identification and classification based on chest X-ray images. While the proposed system is still in its early stages and far from clinical application, the results demonstrate potential steps forward in the development of a comprehensive computer-aided diagnostic system for comparative analysis of chest X-ray images.

Paciente varón de tres años con sibilancias y tos crónica / Three-Year-Old Male with Wheezing and Chronic Cough

Se presenta el caso de un niño de 3 años con diagnóstico de asma, rinitis alérgica, características craneofaciales dismórficas e infecciones respiratorias altas y bajas recurrentes, manejado como asma desde un inicio. Como parte del estudio de comorbilidades, se decide realizar una prueba del sudor que sale en rango intermedio y más tarde se encuentra una mutación, donde se obtiene un resultado positivo para una copia que se asocia a fibrosis quística. Se revisará el caso, así como el diagnóstico, clínica y tratamiento del síndrome metabólico relacionado con el regulador de conductancia transmembrana de fibrosis quística (CRMS).

We present the case of a 3-year-old boy with a diagnosis of asthma, allergic rhinitis, dysmorphic craniofacial characteristics and recurrent upper and lower respiratory infections, managed as asthma from the beginning. As part of the study of comorbidi-ties, it was decided to carry out a sweat test that came out in the intermediate range and later one mutation was found, where a positive result was obtained for a copy that is associated with cystic fibrosis. The case will be reviewed, as well as the diagnosis, symptoms and treatment of the metabolic syndrome related to the cystic fibrosis trans-membrane conductance regulator (CRMS).

X-ray interpretation in emergency department in the Kingdom of Saudi Arabia. Do we need the radiologist?

INTRODUCTION: Chest x-rays are widely used for diagnosing chest pathology worldwide. Pediatricians frequently interpret chest radiographs in the emergency department, guiding patient management. This study aims to assess the competency of non-radiologists in interpreting emergency chest x-rays and compare it with trainees of different levels to determine the necessity of radiologist input. METHODOLOGY: A cross-sectional online survey was conducted in Saudi Arabia from September to October 2023, involving 385 participants, including pediatricians and medical interns from various regions. Carefully selected questions addressed a range of x-ray abnormalities in pediatric emergencies, assessing fundamental understanding of x-ray interpretation, such as inspiratory vs. expiratory and AP or PA films. RESULTS: The study included 385 participants, primarily Saudi nationals in the eastern region, with an equal gender distribution and ages ranging from 20 to 29 years. Approximately 29.09% demonstrated fair knowledge, with 28% being Junior Pediatrics Residents, 18% Pediatric Consultants, and 15% Senior Pediatrics Residents. Fair knowledge was significantly associated with individuals aged 20-29 years, residents of the western region, and Junior Pediatrics Residents. Clinical knowledge varied among different groups, with 59% correctly identifying atypical pneumonia and 65% recognizing asymmetrical hyperinflation. However, rates for other conditions differed, with low identification of potential foreign body aspiration and film type. Accuracy in identifying tension pneumothorax and hyperlucency varied among clinicians. Pleural effusion films had a 65% identification rate for the diagnosis, but only 28% accurately described the X-ray and selected the correct answer for lung opacity. CONCLUSION: The study concluded that 29.9% of the participating physicians exhibited fair knowledge of common pediatric emergency radiological films. Junior pediatric residents showed the best knowledge, and Tetralogy of Fallot, asymmetrical hyperinflation, and pleural effusion had the highest recognition rates. In conclusion, there is still a need for radiologists in the pediatric emergency department to ensure optimal functioning.

Physical examination and CT to assess thoracic injury in 137 cats presented to UK referral hospitals after trauma.

OBJECTIVES: The aim of the study was to describe clinical examination and thoracic CT (TCT) findings in cats after trauma, and to identify physical examination findings associated with both abnormalities on TCT and the need for therapeutic interventions. METHODS: A multicentre, retrospective, observational study was conducted. Cats admitted to the participating hospitals with a history of blunt trauma and that underwent TCT were eligible. Data were collected on signalment, history, physical examination, TCT findings and subsequent interventions. RESULTS: In total, 137 cats were included. Road traffic accidents (RTAs) were the most frequently reported cause of trauma (69%). Tachypnoea (32%), pale mucous membranes (22%) and dyspnoea (20%) were the most common abnormal findings on thoracic examination. The most frequently identified thoracic pathologies on TCT were atelectasis (34%), pulmonary contusions (33%), pneumothorax (29%) and pleural effusion (20%). Thoracocentesis was the most commonly performed intervention (12%), followed by chest drain placement (7%). A total of 45 (33%) cats had no physical examination abnormalities but did have abnormalities detected on TCT; six of these cats required interventions. Increasing numbers of thoracic abnormalities on clinical examination were associated with increasing likelihood of having abnormal findings on TCT (odds ratio [OR] 2.04, 95% confidence interval [CI] 1.21-3.44, P = 0.008) and of requiring an intervention (OR 1.82, 95% CI 1.32-2.51, P <0.001). CONCLUSIONS AND RELEVANCE: RTAs were the most common reported cause of blunt trauma. Atelectasis, pulmonary contusions and pneumothorax were the most common abnormalities identified on TCT, and thoracic drainage was the most utilised intervention. TCT may be useful in identifying cats with normal thoracic physical examination findings that have significant thoracic pathology, and a high number of abnormal findings on thoracic examination should raise suspicion for both minor and major thoracic pathology. The results of this study can be used to assist in selecting appropriate cases for TCT after blunt trauma.

Portable Dynamic Chest Radiography: Literature Review and Potential Bedside Applications.

Dynamic digital radiography (DDR) is a high-resolution radiographic imaging technique using pulsed X-ray emission to acquire a multiframe cine-loop of the target anatomical area. The first DDR technology was orthostatic chest acquisitions, but new portable equipment that can be positioned at the patient's bedside was recently released, significantly expanding its potential applications, particularly in chest examination. It provides anatomical and functional information on the motion of different anatomical structures, such as the lungs, pleura, rib cage, and trachea. Native images can be further analyzed with dedicated post-processing software to extract quantitative parameters, including diaphragm motility, automatically projected lung area and area changing rate, a colorimetric map of the signal value change related to respiration and motility, and lung perfusion. The dynamic diagnostic information along with the significant advantages of this technique in terms of portability, versatility, and cost-effectiveness represents a potential game changer for radiological diagnosis and monitoring at the patient's bedside. DDR has several applications in daily clinical practice, and in this narrative review, we will focus on chest imaging, which is the main application explored to date in the literature. However, studies are still needed to understand deeply the clinical impact of this method.

Temporal evolution of chest radiographic appearances in COVID-19 with clinicoradiological associations: a multicentre United Kingdom resident-led study.

AIM: To describe the (a) frequency of improving, static, and worsening chest radiograph (CXR) appearances; (b) differences in demographic, initial rudimentary haematological and CXR variables and these patterns; and (c) frequency of different trajectories of serial CXR evolution, in COVID-19 patients presenting consecutively. MATERIALS AND METHODS: This multicentre retrospective study included all COVID-19 patients admitted from 1-30 April 2020, meeting the inclusion criteria across 24 (blinded) hospitals. Follow-up CXRs on admission, the subsequent (where available), and at 4-8 weeks were scored for the presence of parenchymal opacities across six zones. Three cohorts were defined: improved, static, and/or worsened. The chi-squared and Kruskal-Wallis tests were used to compare demographic, laboratory, and CXR variables. Trajectories of CXR evolution were assessed when all three CXRs were available (226 patients). RESULTS: Of 452 included patients (median age 66 years, interquartile range 54.3-79, 262 men), 211 (46.7%) improved, 140 (31%) were static, and 101 (22.3%) worsened. Improving patients were more likely younger, with a classic COVID-19 radiograph and higher initial CXR zonal severity scores (both p<0.001), while worsening patients had lower initial lymphocyte counts (p=0.008). The most frequent trajectory was worsened then improved (n=63, 27.9%) followed by static then improved (n=46, 20.4%) and static (n=42, 18.6%). CONCLUSION: Most patients with COVID-19 during the first wave of the pandemic demonstrated radiographic improvement; these patients were more likely younger with classic COVID-19 appearances and initially more extensive abnormality. Conversely, radiographic deterioration was associated with lower lymphocyte counts. The three most common trajectories were worsening then improvement, static then improvement, and static throughout.

Consideraciones anestésicas en el manejo perioperatorio del paciente con síndrome de Jarcho-Levin / Anesthetic considerations in the perioperative management of the patient with Jarcho-Levin syndrome

El síndrome de Jarcho-Levin es un epónimo usado para describir un espectro de displasias esqueléticas de tórax pequeño con el compromiso variable de vertebras y costillas. Inicialmente considerado letal, actualmente es compatible con la vida en sus presentaciones más leves. Las alteraciones óseas que conllevan un patrón respiratorio restrictivo, las infecciones respiratorias de repetición y el fenotipo particular pueden dificultar el manejo anestésico perioperatorio. Es de especial interés la adecuada valoración de la vía aérea por presentar predictores de vía aérea difícil, así como la prevención, el diagnóstico precoz y el tratamiento adecuado de la insuficiencia respiratoria. Presentamos el caso de un paciente con síndrome de Jarcho-Levin intervenido de distracción vertebral, con sus implicaciones más destacables en el manejo anestésico.(AU)

Jarcho-Levin syndrome is an eponym used to describe a spectrum of small thoracic skeletal dysplasias with variable involvement of vertebrae and ribs. Initially considered lethal, it is currently compatible with life in its mildest forms. Bone alterations that lead to a restrictive respiratory pattern, recurrent respiratory infections and particular phenotype can make perioperative anesthetic management difficult. The proper assessment of the airway is of special interest because it presents predictors of a difficult airway, as well as the prevention, early diagnosis and adequate treatment of respiratory failure. We present the case of a patient with Jarcho-Levin syndrome who underwent vertebral distraction surgery, with its most notable implications in anesthetic management.(AU)

Radiographic Imaging of Community-Acquired Pneumonia: A Case-Based Review.

The chest radiograph is the most common imaging examination performed in most radiology departments, and one of the more common indications for these studies is suspected infection. Radiologists must therefore be aware of less common radiographic patterns of pulmonary infection if they are to add value in the interpretation of chest radiographs for this indication. This review uses a case-based format to illustrate a range of imaging findings that can be associated with acute pulmonary infection and highlight findings that should prompt investigation for diseases other than community-acquired pneumonia to prevent misdiagnosis and delays in appropriate management.

Evaluation of the diagnostic performance of physician lung ultrasound versus chest radiography for pneumonia diagnosis in a peri-urban South African cohort.

BACKGROUND: Lung ultrasound (US), which is radiation-free and cheaper than chest radiography (CXR), may be a useful modality for the diagnosis of pediatric pneumonia, but there are limited data from low- and middle-income countries. OBJECTIVES: The aim of this study was to evaluate the diagnostic performance of non-radiologist, physician-performed lung US compared to CXR for pneumonia in children in a resource-constrained, African setting. MATERIALS AND METHODS: Children under 5 years of age enrolled in a South African birth cohort study, the Drakenstein Child Health Study, who presented with clinically defined pneumonia and had a CXR performed also had a  lung US performed by a study doctor. Each modality was reported by two readers, using standardized methodology. Agreement between modalities, accuracy (sensitivity and specificity) of lung US and inter-rater agreement were assessed. Either consolidation or any abnormality (consolidation or interstitial picture) was considered as endpoints. In the 98 included cases (median age: 7.2 months; 53% male; 69% hospitalized), prevalence was 37% vs. 39% for consolidation and 52% vs. 76% for any abnormality on lung US and CXR, respectively. Agreement between modalities was poor for consolidation (observed agreement=61%, Kappa=0.18, 95% confidence interval [95% CI]: - 0.02 to 0.37) and for any abnormality (observed agreement=56%, Kappa=0.10, 95% CI: - 0.07 to 0.28). Using CXR as the reference standard, sensitivity of lung US was low for consolidation (47%, 95% CI: 31-64%) or any abnormality (5%, 95% CI: 43-67%), while specificity was moderate for consolidation (70%, 95% CI: 57-81%), but lower for any abnormality (58%, 95% CI: 37-78%). Overall inter-observer agreement of CXR was poor (Kappa=0.25, 95% CI: 0.11-0.37) and was significantly lower than the substantial agreement of lung US (Kappa=0.61, 95% CI: 0.50-0.75). Lung US demonstrated better agreement than CXR for all categories of findings, showing a significant difference for consolidation (Kappa=0.72, 95% CI: 0.58-0.86 vs. 0.32, 95% CI: 0.13-0.51). CONCLUSION: Lung US identified consolidation with similar frequency to CXR, but there was poor agreement between modalities. The significantly higher inter-observer agreement of LUS compared to CXR supports the utilization of lung US by clinicians in a low-resource setting.

Retrospectively assessing evaluation and management of artificial-intelligence detected nodules on uninterpreted chest radiographs in the era of radiologists shortage.

PURPOSE: High volumes of chest radiographs (CXR) remain uninterpreted due to severe shortage of radiologists. These CXRs may be informally reported by non-radiologist physicians, or not reviewed at all. Artificial intelligence (AI) software can aid lung nodule detection. Our aim was to assess evaluation and management by non-radiologists of uninterpreted CXRs with AI detected nodules, compared to retrospective radiology reports. MATERIALS AND METHODS: AI detected nodules on uninterpreted CXRs of adults, performed 30/6/2022-31/1/2023, were evaluated. Excluded were patients with known active malignancy and duplicate CXRs of the same patient. The electronic medical records (EMR) were reviewed, and the clinicians' notes on the CXR and AI detected nodule were documented. Dedicated thoracic radiologists retrospectively interpreted all CXRs, and similarly to the clinicians, they had access to the AI findings, prior imaging and EMR. The radiologists' interpretation served as the ground truth, and determined if the AI-detected nodule was a true lung nodule and if further workup was required. RESULTS: A total of 683 patients met the inclusion criteria. The clinicians commented on 386 (56.5%) CXRs, identified true nodules on 113 CXRs (16.5%), incorrectly mentioned 31 (4.5%) false nodules as real nodules, and did not mention the AI detected nodule on 242 (35%) CXRs, of which 68 (10%) patients were retrospectively referred for further workup by the radiologist. For 297 patients (43.5%) there were no comments regarding the CXR in the EMR. Of these, 77 nodules (11.3%) were retrospectively referred for further workup by the radiologist. CONCLUSION: AI software for lung nodule detection may be insufficient without a formal radiology report, and may lead to over diagnosis or misdiagnosis of nodules.

Performance of artificial intelligence-based software for the automatic detection of lung lesions on chest radiographs of patients with suspected lung cancer.

PURPOSE: This study aimed to evaluate the performance of the commercially available artificial intelligence-based software CXR-AID for the automatic detection of pulmonary nodules on the chest radiographs of patients suspected of having lung cancer. MATERIALS AND METHODS: This retrospective study included 399 patients with clinically suspected lung cancer who underwent CT and chest radiography within 1 month between June 2020 and May 2022. The candidate areas on chest radiographs identified by CXR-AID were categorized into target (properly detected areas) and non-target (improperly detected areas) areas. The non-target areas were further divided into non-target normal areas (false positives for normal structures) and non-target abnormal areas. The visibility score, characteristics and location of the nodules, presence of overlapping structures, and background lung score and presence of pulmonary disease were manually evaluated and compared between the nodules detected or undetected by CXR-AID. The probability indices calculated by CXR-AID were compared between the target and non-target areas. RESULTS: Among the 450 nodules detected in 399 patients, 331 nodules detected in 313 patients were visible on chest radiographs during manual evaluation. CXR-AID detected 264 of these 331 nodules with a sensitivity of 0.80. The detection sensitivity increased significantly with the visibility score. No significant correlation was observed between the background lung score and sensitivity. The non-target area per image was 0.85, and the probability index of the non-target area was lower than that of the target area. The non-target normal area per image was 0.24. Larger and more solid nodules exhibited higher sensitivities, while nodules with overlapping structures demonstrated lower detection sensitivities. CONCLUSION: The nodule detection sensitivity of CXR-AID on chest radiographs was 0.80, and the non-target and non-target normal areas per image were 0.85 and 0.24, respectively. Larger, solid nodules without overlapping structures were detected more readily by CXR-AID.