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Journal articles on the topic 'Chest - Radiography'

Author: Grafiati

Published: 4 June 2021

Last updated: 27 February 2023

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1

Vyborny, C., P. Bunch, H. Chotas, J. Dobbins, L. Niklason, and C. Schaefer-Prokop. "Image Quality in Chest Radiography: Abstract." Journal of the ICRU 3, no. 2 (July 2003): 13. http://dx.doi.org/10.1093/jicru_3.2.13.

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Image quality in chest radiography is an important, but complex, subject. The complicated anatomy of the chest, as well as the various ways that chest disease may manifest itself, require careful consideration of radiographic technique. The manner in which human observers deal with the complexity of chest images adds further dimensions to image analysis that are not found in other radiography examinations. This report describes many issues that are related to the quality of chest radiographic images. In so doing, it relies upon the very extensive literature on this topic, a topic that has been one of the most thoroughly studied in all of radiography. Strategies that are generally agreed to improve the quality of chest radiographs are described, as are approaches to the assessment of image quality.

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Hayabuchi, N., W. J. Russell, and J. Murakami. "Problems in Radiographic Detection and Diagnosis of Lung Cancer." Acta Radiologica 30, no. 2 (March 1989): 163–67. http://dx.doi.org/10.1177/028418518903000209.

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All chest radiographs of 107 proven lung cancer patients who received consecutive biennial chest radiography were reviewed to elucidate problems detecting their cancers, and diagnosing them when initially radiographically detected. Subjects, members of a fixed population sample, originally numbered 20000 persons, 17000 of whom consistently received consecutive biennial chest radiography during examinations for late effects of atomic-bomb radiation. Among the 107 subjects, 64 had radiographic manifestations of cancer; 47 were initially correctly diagnosed; 17 were not. Eleven of the 17 were initially equivocal, diagnosable only after subsequent radiography and retrospective review of serial radiographs. Diagnostic problems consisted of 1) six detection errors with cancer images superimposed on musculoskeletal and cardiovascular structures, reducible by stereoscopic p.a. instead of single p.a. radiography; immediate tentative interpretations; and by comparing earlier with current radiographs. 2) Eight decision errors, wherein cancers mimicked other diseases, were reducible by greater index of suspicion and scrutiny during interpretations.

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Kehler, M., U. Albrechtsson, B. Andersson, H. Lárusdóttir, A. Lundin, and H. Pettersson. "Assessment of Digital Chest Radiography Using Stimulable Phosphor." Acta Radiologica 30, no. 6 (November 1989): 581–86. http://dx.doi.org/10.1177/028418518903000603.

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In this pilot study, conventional and digital radiography of the chest was compared in 170 patients. Two digitized radiographs, one frequency modified and one simulating the conventional film-screen combination, and the conventional films were reviewed independently by 5 radiologists with different experience. In spite of the smaller size and lower spatial resolution of the digitized compared with the conventional radiograph, only slight differences were revealed in the observation of different pulmonary and mediastinal changes. Digitized radiography is therefore considered suitable for chest examinations.

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Liu, Yunbi, Wei Yang, Guangnan She, Liming Zhong, Zhaoqiang Yun, Yang Chen, Ni Zhang, et al. "Soft Tissue/Bone Decomposition of Conventional Chest Radiographs Using Nonparametric Image Priors." Applied Bionics and Biomechanics 2019 (June 24, 2019): 1–17. http://dx.doi.org/10.1155/2019/9806464.

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Background and Objective. When radiologists diagnose lung diseases in chest radiography, they can miss some lung nodules overlapped with ribs or clavicles. Dual-energy subtraction (DES) imaging performs well because it can produce soft tissue images, in which the bone components in chest radiography were almost suppressed but the visibility of nodules and lung vessels was still maintained. However, most routinely available X-ray machines do not possess the DES function. Thus, we presented a data-driven decomposition model to perform virtual DES function for decomposing a single conventional chest radiograph into soft tissue and bone images. Methods. For a given chest radiograph, similar chest radiographs with corresponding DES soft tissue and bone images are selected from the training database as exemplars for decomposition. The corresponding fields between the observed chest radiograph and the exemplars are solved by a hierarchically dense matching algorithm. Then, nonparametric priors of soft tissue and bone components are constructed by sampling image patches from the selected soft tissue and bone images according to the corresponding fields. Finally, these nonparametric priors are integrated into our decomposition model, the energy function of which is efficiently optimized by an iteratively reweighted least-squares scheme (IRLS). Results. The decomposition method is evaluated on a data set of posterior-anterior DES radiography (503 cases), as well as on the JSRT data set. The proposed method can produce soft tissue and bone images similar to those produced by the actual DES system. Conclusions. The proposed method can markedly reduce the visibility of bony structures in chest radiographs and shows potential to enhance diagnosis.

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Yu, Qian, Lifeng He, Tsuyoshi Nakamura, Yuyan Chao, and Kenji Suzuki. "A Mutual-Information-Based Global Matching Method for Chest-Radiography Temporal Subtraction." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 7 (November 20, 2012): 841–50. http://dx.doi.org/10.20965/jaciii.2012.p0841.

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Lung cancer is the most common cancer in the world. Early detection is most important for reducing death due to lung cancer. Chest radiography has been widely and frequently used for the detection and diagnosis of lung cancer. To assess pathological changes in chest radiographs, radiologists often compare the previous chest radiograph and the current one from the same patient at different times. A temporal subtraction image, which is constructed from the previous and current radiographs, is often used to support this comparison work. This paper presents a Mutual-Information (MI)-based global matching method for chest-radiography temporal subtraction. We first make a preliminary transformation on the previous radiograph to make the center line of the lungs in the previous radiograph coincide with that of the current one. Then, we specify areas of the lungs to be used for mutual information registration and extract rib edges in these areas. We transform the rib edge image of the previous radiograph until mutual information between the rib edge image of the previous radiograph and that of the current radiograph becomes maximal. Finally, we use the same transform parameters to transform the previous radiograph, and then use the current radiograph and the transformed previous radiograph to construct the temporal subtraction image. The experimental result demonstrates that our proposed method can enhance pathological changes and reduces misregistration artifacts.

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McCollum, Eric D., Melissa M. Higdon, Nicholas S. S. Fancourt, Jack Sternal, William Checkley, John De Campo, and Anita Shet. "Training physicians in India to interpret pediatric chest radiographs according to World Health Organization research methodology." Pediatric Radiology 51, no. 8 (March 11, 2021): 1322–31. http://dx.doi.org/10.1007/s00247-021-04992-2.

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Abstract Background Chest radiography is the standard for diagnosing pediatric lower respiratory infections in low-income and middle-income countries. A method for interpreting pediatric chest radiographs for research endpoints was recently updated by the World Health Organization (WHO) Chest Radiography in Epidemiological Studies project. Research in India required training local physicians to interpret chest radiographs following the WHO method. Objective To describe the methodology for training Indian physicians and evaluate the training’s effectiveness. Materials and methods Twenty-nine physicians (15 radiologists and 14 pediatricians) from India were trained by two WHO Chest Radiography in Epidemiological Studies members over 3 days in May 2019. Training materials were adapted from WHO Chest Radiography in Epidemiological Studies resources. Participants followed WHO methodology to interpret 60 unique chest radiographs before and after the training. Participants needed to correctly classify ≥80% of radiographs for primary endpoint pneumonia on the post-training test to be certified to interpret research images. We analyzed participant performance on both examinations. Results Twenty-six of 29 participants (89.7%) completed both examinations. The average score increased by 9.6% (95% confidence interval [CI] 5.0–14.1%) between examinations (P<0.001). Participants correctly classifying ≥80% of images for primary endpoint pneumonia increased from 69.2% (18/26) on the pretraining to 92.3% (24/26) on the post-training examination (P=0.003). The mean scores of radiologists and pediatricians on the post-training examination were not statistically different (P=0.43). Conclusion Our results demonstrate this training approach using revised WHO definitions and tools was successful, and that non-radiologists can learn to apply these methods as effectively as radiologists. Such capacity strengthening is important for enabling research to support national policy decision-making in these settings. We recommend future research incorporating WHO chest radiograph methodology to consider modelling trainings after this approach.

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Fatmawati, Heni, Zhafirah Rana Labibah, and Jauhar Firdaus. "The Relationship of Risk Factors and Comorbidity with Chest Radiography Features of COVID-19 Confirmed Patients." Journal Of The Indonesian Medical Association 72, no. 3 (August 30, 2022): 109–15. http://dx.doi.org/10.47830/jinma-vol.72.3-2022-629.

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Introduction: COVID-19 is a worldwide health problem with a high mortality rate, especially in patients with risk factors. One type of examination to inspect the severity of COVID-19 patients is a chest radiograph. There is a lack of studies on chest radiography features in Indonesia. This study aims to observe the relationship between age, gender, and comorbid conditions with chest radiography features in COVID-19 confirmed.Method: This study was conducted at dr. Soebandi General Hospital uses a cross-sectional design with medical records as the instrument. Chest radiography examination was performed using BSTI classification. Meanwhile, data were analyzed using Chi-Square and contingency coefficient C.Result: The study included 173 patients: 52% were 40-59 years old, 36,4% were 20-39 years old, and 11,6% were ≥ 60 years old; 56,1% were female and 53,9% were male; 50,9% have comorbidities, with hypertension, diabetes, and COPD were the most type of comorbidities. About 48,6% sample had a normal chest radiograph, 27,7% had a mild severity, 17,3% had a moderate severity, and 6,4% had a severe severity. There was a correlation between age and comorbidity with chest radiography features. Otherwise, no correlation was found between sex and chest radiography features.Conclusion: Age and comorbidity were found as significant risk factors for the severity of chest radiograph in COVID-19 with a moderate correlation. However, no correlation was found between sex and chest radiography features.

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Suwal, Sundar, Surakshya Koirala, and Dinesh Chataut. "Evaluation of the Diagnostic Quality of Chest Radiographs." Nepalese Journal of Radiology 12, no. 1 (June 30, 2022): 13–17. http://dx.doi.org/10.3126/njr.v12i1.42266.

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Introduction: With the advancement of conventional radiography to digital, digital radiography of the chest is commonly performed these days. The role and importance of diagnostic quality of radiographs are to help the radiologists and the clinicians in the diagnosis of diseases and their management, as well as to prevent the misdiagnosis of any pathology. This study was an attempt to quantify the diagnostic quality of chest radiographs by evaluating the quality of depiction of the anatomical details as well as other technical factors. Method: A total of 450 chest radiographs, produced at Tribhuvan University Teaching Hospital, were selected for study over two months period. Five image quality criteria i.e. anatomical coverage, rotation, adequate penetration, adequate inspiration, and scapula out of lung fields were evaluated and tabulated. Results: Out of the 450 radiographs taken for study, only 22.2% of the radiographs fulfilled all the image quality criteria, the rest 77.8% either lacked one or more of the quality criteria. Conclusion: Many technical factors affect the image quality of digital chest radiographs. However, the radiographer/technologist should always try to maintain adequate image quality of the radiographs.

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Kobes, Kevin J., Annemarie Budau-Bymoen, Yogesh Thakur, and Charlotte J. Yong-Hing. "Multidisciplinary Development of Mobile Radiography Guidelines Reduced the Number of Inappropriate Mobile Exams in Patients Receiving Chest Radiographs in British Columbia." Canadian Association of Radiologists Journal 71, no. 1 (January 27, 2020): 110–16. http://dx.doi.org/10.1177/0846537119888357.

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Aim: To decrease the number of mobile chest radiograph requests for inpatients in British Columbia who are medically able to tolerate transport to the main department by introducing and implementing request criteria. Method: Concerns regarding inappropriate mobile exam requests in patients receiving chest radiography were surveyed at 28 medical imaging sites. In response, a multidisciplinary team composed a set of mobile radiography request guidelines incorporating feedback from all sites. These were successfully implemented along with in-person education to 21 sites. The number of adult annual mobile chest radiographs was tracked from 2014 to 2018, and informal feedback was obtained from participating sites. Results: The percentage of mobile chest radiographs of all chest radiographs performed between 2014 and 2018 decreased by 3.2%, while the total number of all chest radiographs performed during this time, including both departmental and mobile, increased by 1.9%. Sites reported positive engagement with the initiative and expressed need for ongoing education to optimize its effect. Conclusion: Implementation of request guidelines with in-person education helped to reduce inappropriate mobile exams in patients receiving chest radiographs in British Columbia between 2014 and 2018. These guidelines promote patient safety through reduced radiation exposure, empower radiographers to mitigate inappropriate requests, and help to optimize use of limited hospital resources by reducing inappropriate mobile exams where routine departmental exams are more suitable.

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Beam, Craig, and Daniel C. Sullivan. "Chest Radiography." Investigative Radiology 27, no. 4 (April 1992): 331. http://dx.doi.org/10.1097/00004424-199204000-00018.

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11

Ravin, C. E., and H. G. Chotas. "Chest radiography." Radiology 204, no. 3 (September 1997): 593–600. http://dx.doi.org/10.1148/radiology.204.3.9280231.

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Tsuei, Betty J., and Peter E. Lyu. "Chest radiography." Atlas of the Oral and Maxillofacial Surgery Clinics 10, no. 2 (September 2002): 189–211. http://dx.doi.org/10.1016/s1061-3315(02)00006-9.

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13

Bequet, Angga Yosainto, Luthfi Rusyadi, and Fatimah Fatimah. "Nilai Contrast to Noise Ratio (CNR) Radiograf Thorax PA antara menggunakan Grid dengan tanpa Menggunakan Grid." Jurnal Imejing Diagnostik (JImeD) 6, no. 2 (July 1, 2020): 60–64. http://dx.doi.org/10.31983/jimed.v6i2.5653.

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Background: Chest radiographic examination often does not use a grid even though the thorax is an object that has a thickness of more than 10 cm so it must use a grid. This study aims to determine the differences and the degree of change in Contrast to Noise Ratio on PA radiographs between using a grid and without using a grid.Methods: This type of research is a pre-experimental quantitative. The research subject is a radiological image of PA thorax made using the grid (50 patients) and without using the grid (patient). The image is analyzed by pixel value using Dicom softwareResults: There is a difference in contrast values on the PA radiographs between those using the Grid and without using the Grid (p-value 0.001). The average value of the contrast on the chest radiograph using a Grid is 2283.60, while the one without using a Grid is 1878.58. Noise value also shows that there is a difference between chest radiographs of PA images using Grid without using Grid (p-value = 0.001). The average thorax photo noise using Grid is 25.32, paired using Grid is 17.84. Statistical test on the value of Contrast to Noise Ratio (CNR) shows that there is a difference between radiographs of PA chest radiography using Grid without Grid (p-value 0.001). The average CNR radiograph of the PA thorax PA using Grid is 100.79, while the CNR value of the radiograph of thorax PA without using Grid is 125.62.Conclusions: There is a Contrast difference between using a grid and without using a grid (p-value 0.001). There is a Noise difference in PA radiographs between using a grid and without using a grid (p-value = 0.001). There is a difference in Contrast to Noise Ratio on the PA chest radiograph between using a grid and without using a grid (p-value 0.001).

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Hess, Erik P., Jeffrey J. Perry, Pam Ladouceur, George A. Wells, and Ian G. Stiell. "Derivation of a clinical decision rule for chest radiography in emergency department patients with chest pain and possible acute coronary syndrome." CJEM 12, no. 02 (March 2010): 128–34. http://dx.doi.org/10.1017/s148180350001215x.

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ABSTRACTObjective:We derived a clinical decision rule to determine which emergency department (ED) patients with chest pain and possible acute coronary syndrome (ACS) require chest radiography.Methods:We prospectively enrolled patients over 24 years of age with a primary complaint of chest pain and possible ACS over a 6-month period. Emergency physicians completed standardized clinical assessments and ordered chest radiographs as appropriate. Two blinded investigators independently classified chest radiographs as “normal,” “abnormal not requiring intervention” and “abnormal requiring intervention,” based on review of the radiology report and the medical record. The primary outcome was abnormality of chest radiographs requiring acute intervention. Analyses included interrater reliability assessment (with κ statistics), univariate analyses and recursive partitioning.Results:We enrolled 529 patients during the study period between Jul. 1, 2007, and Dec. 31, 2007. Patients had a mean age of 59.9 years, 60.3% were male, 4.0% had a history of congestive heart failure and 21.9% had a history of acute myocardial infarction. Only 2.1% (95% confidence interval [CI] 1.1%–3.8%) of patients had radiographic abnormality of the chest requiring acute intervention. The κ statistic for chest radiograph classification was 0.81 (95% CI 0.66–0.95). We derived the following rule: patients can forgo chest radiography if they have no history of congestive heart failure, no history of smoking and no abnormalities on lung auscultation. The rule was 100% sensitive (95% CI 32.0%–10.4%) and 36.1% specific (95% CI 32.0%–40.4%).Conclusion:This rule has potential to reduce health care costs and enhance ED patient flow. It requires validation in an independent patient population before introduction into clinical practice.

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Dasegowda, Giridhar, Mannudeep K. Kalra, Alain S. Abi-Ghanem, Chiara D. Arru, Monica Bernardo, Luca Saba, Doris Segota, et al. "Suboptimal Chest Radiography and Artificial Intelligence: The Problem and the Solution." Diagnostics 13, no. 3 (January 23, 2023): 412. http://dx.doi.org/10.3390/diagnostics13030412.

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Chest radiographs (CXR) are the most performed imaging tests and rank high among the radiographic exams with suboptimal quality and high rejection rates. Suboptimal CXRs can cause delays in patient care and pitfalls in radiographic interpretation, given their ubiquitous use in the diagnosis and management of acute and chronic ailments. Suboptimal CXRs can also compound and lead to high inter-radiologist variations in CXR interpretation. While advances in radiography with transitions to computerized and digital radiography have reduced the prevalence of suboptimal exams, the problem persists. Advances in machine learning and artificial intelligence (AI), particularly in the radiographic acquisition, triage, and interpretation of CXRs, could offer a plausible solution for suboptimal CXRs. We review the literature on suboptimal CXRs and the potential use of AI to help reduce the prevalence of suboptimal CXRs.

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Warren-Forward, H. M., and J. S. Millar. "Optimization of radiographic technique for chest radiography." British Journal of Radiology 68, no. 815 (November 1995): 1221–29. http://dx.doi.org/10.1259/0007-1285-68-815-1221.

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Sverzellati, Nicola, Christopher J. Ryerson, Gianluca Milanese, Elisabetta A. Renzoni, Annalisa Volpi, Paolo Spagnolo, Francesco Bonella, et al. "Chest radiography or computed tomography for COVID-19 pneumonia? Comparative study in a simulated triage setting." European Respiratory Journal 58, no. 3 (February 11, 2021): 2004188. http://dx.doi.org/10.1183/13993003.04188-2020.

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IntroductionFor the management of patients referred to respiratory triage during the early stages of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic, either chest radiography or computed tomography (CT) were used as first-line diagnostic tools. The aim of this study was to compare the impact on the triage, diagnosis and prognosis of patients with suspected COVID-19 when clinical decisions are derived from reconstructed chest radiography or from CT.MethodsWe reconstructed chest radiographs from high-resolution CT (HRCT) scans. Five clinical observers independently reviewed clinical charts of 300 subjects with suspected COVID-19 pneumonia, integrated with either a reconstructed chest radiography or HRCT report in two consecutive blinded and randomised sessions: clinical decisions were recorded for each session. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and prognostic value were compared between reconstructed chest radiography and HRCT. The best radiological integration was also examined to develop an optimised respiratory triage algorithm.ResultsInterobserver agreement was fair (Kendall's W=0.365, p<0.001) by the reconstructed chest radiography-based protocol and good (Kendall's W=0.654, p<0.001) by the CT-based protocol. NPV assisted by reconstructed chest radiography (31.4%) was lower than that of HRCT (77.9%). In case of indeterminate or typical radiological appearance for COVID-19 pneumonia, extent of disease on reconstructed chest radiography or HRCT were the only two imaging variables that were similarly linked to mortality by adjusted multivariable modelsConclusionsThe present findings suggest that clinical triage is safely assisted by chest radiography. An integrated algorithm using first-line chest radiography and contingent use of HRCT can help optimise management and prognostication of COVID-19.

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Eisenhuber, E., C. M. Schaefer-Prokop, H. Prosch, and W. Schima. "Bedside Chest Radiography." Respiratory Care 57, no. 3 (March 1, 2012): 427–43. http://dx.doi.org/10.4187/respcare.01712.

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MacMahon, Heber, and Kunio Doi. "Digital Chest Radiography." Clinics in Chest Medicine 12, no. 1 (March 1991): 19–32. http://dx.doi.org/10.1016/s0272-5231(21)00724-3.

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Wandtke, J. C. "Bedside chest radiography." Radiology 190, no. 1 (January 1994): 1–10. http://dx.doi.org/10.1148/radiology.190.1.8043058.

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Paulin, S. "Bedside chest radiography." Radiology 192, no. 1 (July 1994): 282–84. http://dx.doi.org/10.1148/radiology.192.1.8208957.

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WANDTKE, JOHN C. "Portable Chest Radiography." Contemporary Diagnostic Radiology 19, no. 19 (1996): 1–5. http://dx.doi.org/10.1097/00219246-199619190-00001.

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Wandtke, John C., and Donald B. Plewes. "Chest equalization radiography." Journal of Thoracic Imaging 1, no. 1 (December 1985): 14–20. http://dx.doi.org/10.1097/00005382-198512000-00004.

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Schaefer-Prokop, Cornelia. "Digital Chest Radiography." Journal of Thoracic Imaging 18, no. 3 (July 2003): 123. http://dx.doi.org/10.1097/00005382-200307000-00001.

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Mann, Howard. "Preoperative Chest Radiography." Radiology 167, no. 1 (April 1988): 282. http://dx.doi.org/10.1148/radiology.167.1.282-c.

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Orgill, Richard D., Thomas R. Pasic, Walter W. Peppler, and Mark D. Hoffman. "Radiographic Evaluation of Aspirated Metallic Foil Foreign Bodies." Annals of Otology, Rhinology & Laryngology 114, no. 6 (June 2005): 419–24. http://dx.doi.org/10.1177/000348940511400601.

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Objectives: Aspirated objects generally represent items accessible to children. When metallic candy wrapper aspiration is questioned, radiographic studies may aid diagnosis. An infant with repeated chest radiographs negative for a metallic foreign body was found to have a multi-layer metallic candy wrapper in the left main bronchus. The purpose of this study was to determine whether conventional and dual-energy radiographic techniques exclude the presence of aspirated metallic foil wrappers. Methods: Single-layer and multi-layer metallic candy wrappers were radiographically studied with conventional and dual-energy radiographic techniques in 3 tissue models. Results: No single-layer metallic samples were detectable with conventional or dual-energy radiography. The multi-layer samples were not detectable at less than 8 layers (pulmonary tissue model) or 16 layers (mediastinal model) by either conventional or dual-energy radiography. Conclusions: Conventional and dual-energy chest radiographic techniques do not reliably exclude the presence of aspirated metallic foil wrappers.

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Huang, Xin, Yu Fang, Mingming Lu, Fengqi Yan, Jun Yang, and Yilu Xu. "Dual-Ray Net: Automatic Diagnosis of Thoracic Diseases Using Frontal and Lateral Chest X-rays." Journal of Medical Imaging and Health Informatics 10, no. 2 (February 1, 2020): 348–55. http://dx.doi.org/10.1166/jmihi.2020.2901.

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Computer-aided diagnosis (CAD) is an important work which can improve the working efficiency of physicians. With the availability of large-scale data sets, several methods have been proposed to classify pathology on chest X-ray images. However, most methods report performance based on a frontal chest radiograph, ignoring the effect of the lateral chest radiography on the diagnosis. This paper puts forward a kind of model, Dual-Ray Net, of a deep convolutional neural network which can deal with the front and lateral chest radiography at the same time by referring the method of using lateral chest radiography to assist diagnose during the diagnosis used by radiologists. Firstly, we evaluated the performance of parameter migration to small data after pre-training for large datasets. The data sets for pre-training are chest X-ray 14 and ImageNet respectively. The results showed that pre-training with chest X-ray 14 performed better than with the generic dataset ImageNet. Secondly, We evaluated the performance of the Frontal and lateral chest radiographs in different modes of input model for the diagnosis of assisted chest disease. Finally, by comparing different feature fusion methods of addition and concatenation, we found that the fusion effect of concatenation is better, which average AUC reached 0.778. The comparison results show that whether it is a public or a non-public dataset, our Dual-Ray Net (concatenation) architecture shows improved performance in recognizing findings in CXR images when compared to applying separate baseline frontal and lateral classes.

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Marrie, Thomas J. "Survey of Physicians Concerning the Use of Chest Radiography in the Diagnosis of Pneumonia in Out-Patients." Canadian Journal of Infectious Diseases 8, no. 2 (1997): 95–98. http://dx.doi.org/10.1155/1997/162459.

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OBJECTIVE: To determine how physicians use chest radiography in the diagnosis of pneumonia in ambulatory patients.STUDY POPULATION: A convenience sample of 176 Nova Scotia family physicians and internists selected to represent all geographic areas of the province proportional to population.STUDY INSTRUMENT: A 35-item questionnaire covering demographics, experience with out-patients with pneumonia, use of chest radiographs to make this diagnosis and factors that were considered important in the decision to perform initial and follow-up chest radiographs. Two skill-testing questions were also included.RESULTS: One hundred and fourteen of 176 (64.7%) responded; 88% had treated out-patients with pneumonia in the previous three months. Fifty-seven per cent of physicians requested chest radiographs on 90% to 100% of out-patients in whom they had made a clinical diagnosis of pneumonia. These physicians were more likely to be internists and to have graduated before 1970. Factors that ranked most important in the decision to request the initial chest radiograph were clinical appearance, respiratory distress and physical findings, while age and smoking history contributed most to the decision to perform a follow-up chest radiograph.CONCLUSIONS: There is considerable variability among physicians in requesting chest radiographs on out-patients with a clinical diagnosis of pneumonia. Physician and patient factors contribute to this variability.

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Hillis, James M., Bernardo C. Bizzo, Sarah Mercaldo, John K. Chin, Isabella Newbury-Chaet, Subba R. Digumarthy, Matthew D. Gilman, et al. "Evaluation of an Artificial Intelligence Model for Detection of Pneumothorax and Tension Pneumothorax in Chest Radiographs." JAMA Network Open 5, no. 12 (December 15, 2022): e2247172. http://dx.doi.org/10.1001/jamanetworkopen.2022.47172.

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ImportanceEarly detection of pneumothorax, most often via chest radiography, can help determine need for emergent clinical intervention. The ability to accurately detect and rapidly triage pneumothorax with an artificial intelligence (AI) model could assist with earlier identification and improve care.ObjectiveTo compare the accuracy of an AI model vs consensus thoracic radiologist interpretations in detecting any pneumothorax (incorporating both nontension and tension pneumothorax) and tension pneumothorax.Design, Setting, and ParticipantsThis diagnostic study was a retrospective standalone performance assessment using a data set of 1000 chest radiographs captured between June 1, 2015, and May 31, 2021. The radiographs were obtained from patients aged at least 18 years at 4 hospitals in the Mass General Brigham hospital network in the United States. Included radiographs were selected using 2 strategies from all chest radiography performed at the hospitals, including inpatient and outpatient. The first strategy identified consecutive radiographs with pneumothorax through a manual review of radiology reports, and the second strategy identified consecutive radiographs with tension pneumothorax using natural language processing. For both strategies, negative radiographs were selected by taking the next negative radiograph acquired from the same radiography machine as each positive radiograph. The final data set was an amalgamation of these processes. Each radiograph was interpreted independently by up to 3 radiologists to establish consensus ground-truth interpretations. Each radiograph was then interpreted by the AI model for the presence of pneumothorax and tension pneumothorax. This study was conducted between July and October 2021, with the primary analysis performed between October and November 2021.Main Outcomes and MeasuresThe primary end points were the areas under the receiver operating characteristic curves (AUCs) for the detection of pneumothorax and tension pneumothorax. The secondary end points were the sensitivities and specificities for the detection of pneumothorax and tension pneumothorax.ResultsThe final analysis included radiographs from 985 patients (mean [SD] age, 60.8 [19.0] years; 436 [44.3%] female patients), including 307 patients with nontension pneumothorax, 128 patients with tension pneumothorax, and 550 patients without pneumothorax. The AI model detected any pneumothorax with an AUC of 0.979 (95% CI, 0.970-0.987), sensitivity of 94.3% (95% CI, 92.0%-96.3%), and specificity of 92.0% (95% CI, 89.6%-94.2%) and tension pneumothorax with an AUC of 0.987 (95% CI, 0.980-0.992), sensitivity of 94.5% (95% CI, 90.6%-97.7%), and specificity of 95.3% (95% CI, 93.9%-96.6%).Conclusions and RelevanceThese findings suggest that the assessed AI model accurately detected pneumothorax and tension pneumothorax in this chest radiograph data set. The model’s use in the clinical workflow could lead to earlier identification and improved care for patients with pneumothorax.

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Lewis, David. "My Patient is Short of Breath: Have They Got a Pneumothorax?" Ultrasound 19, no. 4 (October 31, 2011): 230–35. http://dx.doi.org/10.1258/ult.2011.011019.

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Clinical diagnosis of pneumothorax in the emergency department (ED) resuscitation room can be difficult and in certain circumstances chest radiography is either impractical or the delay is unacceptable. The diagnosis must also be considered in other clinical areas such as critical care, theatres, respiratory units and acute medical units. Erect chest radiography is the standard first-line diagnostic test for pneumothorax in the ED, but the sensitivity is low (59–81%). For many patients in ED, critical care and theatre, an erect chest radiograph is not possible as the patient must remain supine. The sensitivity for a supine chest radiograph has been reported as being 45–75%. Ultrasound has been shown to be more sensitive than chest radiography in the diagnosis of pneumothorax in certain settings. This paper outlines the evidence for ultrasound in the diagnosis of pneumothorax in the point of care setting; it describes the technique and discusses the clinical application of this imaging modality.

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Manninen, H., K. Partanen, S. Soimakallio, and H. Rytkönen. "Large-Image Intensifier Photofluorography and Conventional Radiography in Pulmonary Emphysema." Acta Radiologica 29, no. 3 (May 1988): 293–97. http://dx.doi.org/10.1177/028418518802900307.

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Large-screen image intensifier (II) photofluorography was compared with full-size screen-film chest radiography in the diagnosis of pulmonary emphysema in 84 patients. Photospot films and conventional radiographs were interpreted independently by three radiologists. Computed tomography (CT) was used as an independent reference technique, and diagnostic performance of chest radiography in various CT patterns of emphysema was evaluated. The difference in diagnostic sensitivity for emphysema in favor of conventional chest radiography over photofluorography (0.65 versus 0.56) was statistically significant (p<0.05). Specificity of the imaging modalities was equal: 0.78 in full-size films and 0.77 in photospot films. All CT patterns of emphysema had great false negative response rates in chest radiography, which is an inaccurate technique for the diagnosis of emphysema. CT is required for reliable radiologic evaluation of emphysema.

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Rossen, B., N. O. Laursen, and S. Just. "Chest Radiography after Minor Chest Trauma." Acta Radiologica 28, no. 1 (January 1987): 53–54. http://dx.doi.org/10.1177/028418518702800110.

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The results of chest radiography in 581 patients with blunt minor thoracic trauma were reviewed. Frontal and lateral views of the chest indicated pathology in 72 patients (12.4%). Pneumothorax was present in 16 patients; 4 had hemothorax. The physical examination and the results of chest radiography were not in accordance because in 6 (30%) of the 20 patients with hemo/-pneumothorax the physical examination was normal. Consequently there is wide indication for chest radiography after minor blunt chest trauma.

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Hirano, Hiroshi. "Lines on Chest Radiograph-Clues to Radiography Interpretation." Japanese Journal of Radiological Technology 65, no. 8 (2009): 1118–26. http://dx.doi.org/10.6009/jjrt.65.1118.

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Rossen, Benni, N. O. Laursen, and S. Just. "Chest Radiography after Minor Chest Trauma." Acta Radiologica 28, no. 1 (January 1987): 53–54. http://dx.doi.org/10.3109/02841858709177306.

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Annisa Dhea Mutiara, Dewi Nadia Purnama, and Septiana Vina Tri. "Hubungan Luas Lesi Radiografi Toraks Berdasarkan Sistem Skoring RALE dengan Derajat Klinis Pasien Covid-19 di RS Universitas Andalas Padang." Jurnal Ilmiah Manusia Dan Kesehatan 5, no. 3 (September 17, 2022): 323–36. http://dx.doi.org/10.31850/makes.v5i3.1826.

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COVID-19 is a contagious infectious disease caused by a highly contagious coronavirus. The RT-PCR method is still used as the gold standard for diagnosing COVID-19, but this examination has several limitations, including delays in the release of examination results, causing delays in diagnosis. A chest radiograph can be performed while waiting for the RT-PCR results to come out. The RALE scoring system on chest radiographs can be used as an easy-to-apply method to assess and triage patients diagnosed with COVID-19. To determine the correlation between chest radiographic lesion based on RALE scoring system with clinical severity of COVID-19 patients at RS Universitas Andalas Padang. This research is observational analytic with a cross sectional design. The Population in the study were patients diagnosed with COVID-19 who underwent chest radiography examinations at the Andalas University Hospital, Padang with a total of 124 samples using the consecutive sampling technique. The most gender were women, namely 71 people (57.3%), the most age was 46-55 years, namely 29 people (23.4%), the most comorbids were having comorbidities, namely 72 people (58.1%) with the type the most disease was hypertension, namely 31 people (25.0%), the most clinical degree was mild, namely 78 people (62.9%), the most extensive chest radiographic lesions were normal, namely 89 people (71.8%), the correlation between chest radiographic lesions with the clinical severity of COVID-19 patients at RS Universitas Andalas Padang, obtained p value = 0.000 with r value = 0.50. The correlation between chest radiographic lesions based on the RALE scoring system and the clinical degree of COVID-19 patients has sufficient correlation strength.

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Hogg, J. I. C. "Bronchogenic and enteric cysts presenting as asymptomatic mediastinal masses at routine chest radiography." Journal of The Royal Naval Medical Service 72, no. 3 (December 1986): 153–59. http://dx.doi.org/10.1136/jrnms-72-153.

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AbstractRoutine radiographic chest screening—as employed upon entry and release from the Royal Navy—is intended to identify pathology which may be clinically covert. Occasionally, asymptomatic lesions of wholly benign appearance are identified. In these circumstances, clinicians may feel obliged to undertake a series of increasingly complex investigations, even exploratory surgery, in order to confirm the diagnosis. This course of events may also follow chest radiographs taken for unrelated reasons—eg exclusion of skeletal injury following trauma.Mediastinal cysts (eg Bronchogenic and Enteric) may present as asymptomatic mediastinal masses with benign features. Two such cases are reported in which a prominent mediastinal mass was revealed at routine or post trauma chest radiography and a brief review of bronchogenic and enteric cysts is presented.

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Daya, Rupesh Baloo, Maurice A. Kibel, Richard Denys Pitcher, Lesley Workman, Tania S. Douglas, and Virginia Sanders. "A pilot study evaluating erect chest imaging in children, using the Lodox Statscan digital X-ray machine." South African Journal of Radiology 13, no. 4 (November 30, 2009): 80. http://dx.doi.org/10.4102/sajr.v13i4.485.

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ABSTRACT Background: Chest radiography accounts for a significant proportion of ionising radiation in children. The radiation dose of radiographs performed on the Lodox Statscan system has been shown to be lower than that of a computed radiography (CR) system. The role of the Lodox Statscan (hereafter referred to as the Statscan) in routine erect chest radiography in children has not been evaluated. Objective: To evaluate the image quality and diagnostic accuracy of erect paediatric chest radiographs obtained with the Statscan and compare this with conventional erect chest images obtained with a CR system. Materials and Methods: Thirty three children with suspected chest pathology were enrolled randomly over a period of three months. Erect chest radiographs were obtained with the Statscan, and a Shimadzu R-20J X-ray machine coupled with a Fuji FCR 5000 CR system. Image quality and diagnostic accuracy and diagnostic capability were evaluated between the two modalities. Results: The erect Statscan allowed superior visualisation of the three major airways. Statscan images however, demonstrated exposure and movement artifacts with hemidiaphragms and ribs most prone to movement. Bronchovascular clarity was also considered unsatisfactory on the Statscan images. Conclusion: The Statscan has limitations in erect chest radiography in terms of movement artefacts, exposure fluctuations, and poor definition of lung markings. Despite this, the Statscan allows better visualisation of the major airways, equivalent to a ‘high KV’ film at a fraction of the radiation dose. This supports the finding of an earlier study evaluating Statscan images in trauma cases, where the images were taken supine. Statscan has great potential in assisting in the diagnosis of childhood tuberculosis where airway narrowing occurs as a result of nodal compression.

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Manninen, M. P., T. A. Paakkala, J. S. Pukander, and P. H. Karma. "Diagnosis of Tracheal Carcinoma at Chest Radiography." Acta Radiologica 33, no. 6 (November 1992): 546–47. http://dx.doi.org/10.1177/028418519203300609.

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All of the 95 primary tracheal carcinomas registered in Finland during 1967 to 1985 were reviewed. Chest radiographs of 44 patients were available. A tracheal tumor was detected in 8 cases (18%) in the primary examination and according to the review all the detected tumors were larger than 15 mm. However, when the same radiographs were reexamined by a senior radiologist, the tumor was identified in the correct site in 66%. This percentage parallels the results of high kV tracheal radiography (69%) performed on 32 patients. Tumors involving anterior or posterior wall and tumors near the bifurcation were the most difficult to detect.

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Qadir, Sadaf Abdul, Syed Muhammad Yousaf Farooq, Muhammad Yousaf, Syed Amir Gilani, Madiha Mumtaz, and Ahmed Ishfaq. "Chest x-ray Findings in the Diagnosis and Evaluation of Covid-19 Patients – A Systematic Review." Pakistan Journal of Medical and Health Sciences 16, no. 4 (April 29, 2022): 7–9. http://dx.doi.org/10.53350/pjmhs221647.

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Aim: To assess the main radiological feature of chest radiography for diagnosis and evaluation of COVID-19 patients. Methodology: A literature search was performed with the use of search engines. The following search engines provided us articles for this systematic review from until 27 February 2021: PubMed, NCBI, Medline, Medscape, and Google Scholar. We included only those articles in which CXR was performed on infected patients for the detection and evaluation of COVID-19. Results: out of eighty (80) articles, only twelve (12) were included in this review to assess the main radiological feature of chest radiography of COVID-19 patients. Patients who went for chest x-ray have shown following radiographic features with pooled percentages as mentioned GGO 32.38%, consolidation 35.15%, vascular congestion sign 7.92%, nodules 33.57% whereas pleural effusion accounts 19.36%, pneumothorax 18.55%, and lymphadenopathy was noted on 1.96%. Pooled Percentages of radiographic features of COVID-19 patients in right lung, left lung or both affected lungs were 21.32%, 5.77% and 47.78% respectively. This calculation is showing B/L lung involvement is more dominant as compare to right and left lung independently. Conclusion: Chest radiograph can be helpful modality in the diagnosis, evaluation and follow-up of SARS- CoV 2 pneumonia patients. Consolidation, GGO with peripheral distribution of lesion and bilateral pneumonia are most common findings of COVID-19 on chest X-ray. Chest x-ray are the baseline/first line approach for COVID-19 as it is easily available. Moreover, in late stages multiple radiological findings are quite helpful. Keywords: COVID-19, Chest X-Ray, Ground Glass Opacities, Consolidation.

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Engeler, Christopher E. "Errors in Chest Radiography." Radiology 183, no. 2 (May 1992): 368. http://dx.doi.org/10.1148/radiology.183.2.368-b.

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Brown, Larry R. "Errors in Chest Radiography." Mayo Clinic Proceedings 67, no. 4 (April 1992): 405–6. http://dx.doi.org/10.1016/s0025-6196(12)61569-9.

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Hnatiuk, Oleh W. "Chest Radiography Following Thoracentesis." Chest 119, no. 4 (April 2001): 1289. http://dx.doi.org/10.1378/chest.119.4.1289.

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Petersen, W. G. "Chest Radiography Following Thoracentesis." Chest 119, no. 4 (April 2001): 1289. http://dx.doi.org/10.1016/s0012-3692(15)52102-8.

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Hochhegger, Bruno, and Klaus L. Irion. "Chest radiography and CPOD." Radiologia Brasileira 46, no. 6 (December 2013): V—VI. http://dx.doi.org/10.1590/s0100-39842013000600001.

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Connell, J., and N. S. Parekh. "Chest Radiography and Catheterization." Chest 129, no. 2 (February 2006): 499. http://dx.doi.org/10.1378/chest.129.2.499.

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Eisen, Lewis A., Jeffrey S. Berger, Abhijith Hegde, and Roslyn F. Schneider. "Competency in chest radiography." Journal of General Internal Medicine 21, no. 5 (May 2006): 460–65. http://dx.doi.org/10.1111/j.1525-1497.2006.00427.x.

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MacMahon, Heber, and Samuel G. Armato. "Temporal subtraction chest radiography." European Journal of Radiology 72, no. 2 (November 2009): 238–43. http://dx.doi.org/10.1016/j.ejrad.2009.05.059.

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Sano, Atsushi. "Rib Radiography versus Chest Computed Tomography in the Diagnosis of Rib Fractures." Thoracic and Cardiovascular Surgeon 66, no. 08 (May 1, 2018): 693–96. http://dx.doi.org/10.1055/s-0038-1645887.

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Background The accurate diagnosis of rib fractures is important in chest trauma. Diagnostic images following chest trauma are usually obtained via chest X-ray, chest computed tomography, or rib radiography. This study evaluated the diagnostic characteristics of rib radiography and chest computed tomography. Methods Seventy-five rib fracture patients who underwent both chest computed tomography and rib radiography between April 2008 and December 2013 were included. Rib radiographs, centered on the site of pain, were taken from two directions. Chest computed tomography was performed using a 16-row multidetector scanner with 5-mm slice-pitch without overlap, and axial images were visualized in a bone window. Result In total, 217 rib fractures were diagnosed in 75 patients. Rib radiography missed 43 rib fractures in 24 patients. The causes were overlap with organs in 15 cases, trivial fractures in 21 cases, and injury outside the imaging range in 7 cases. Left lower rib fractures were often missed due to overlap with the heart, while middle and lower rib fractures were frequently not diagnosed due to overlap with abdominal organs. Computed tomography missed 21 rib fractures in 17 patients. The causes were horizontal fractures in 10 cases, trivial fractures in 9 cases, and insufficient breath holding in 1 case. Conclusion In rib radiography, overlap with organs and fractures outside the imaging range were characteristic reasons for missed diagnoses. In chest computed tomography, horizontal rib fractures and insufficient breath holding were often responsible. We should take these challenges into account when diagnosing rib fractures.

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Chaya Devi, S. K., and T. Satya Savithri. "Review: On Segmentation of Nodules from Posterior and Anterior Chest Radiographs." International Journal of Biomedical Imaging 2018 (October 18, 2018): 1–11. http://dx.doi.org/10.1155/2018/9752638.

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Lung cancer is one of the major types of cancer in the world. Survival rate can be increased if the disease can be identified early. Posterior and anterior chest radiography and computerized tomography scans are the most used diagnosis techniques for detecting tumor from lungs. Posterior and anterior chest radiography requires less radiation dose and is available in most of the diagnostic centers and it costs less compared to the remaining diagnosis techniques. So PA chest radiography became the most commonly used technique for lung cancer detection. Because of superimposed anatomical structures present in the image, sometimes radiologists cannot find abnormalities from the image. To help radiologists in diagnosing tumor from PA chest radiographic images range of CAD scheme has been developed for the past three decades. These computerized tools may be used by radiologists as a second opinion in detecting tumor. Literature survey on detecting tumors from chest graphs is presented in this paper.

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Asare-Boateng, Kwame, Yaw B. Mensah, Naa Adjeley Mensah, Joseph Oliver-Commey, and Ebenezer Oduro-Mensah. "A review of chest radiographic patterns in mild to moderate novel corona virus disease 2019 at an urban hospital in Ghana." Ghana Medical Journal 54, no. 4s (December 31, 2020): 46–51. http://dx.doi.org/10.4314/gmj.v54i4s.8.

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Introduction: The novel corona virus disease 2019 (COVID-19) was diagnosed in Wuhan, China in December 2019 and, in Ghana, in March 2020. As of 30th July 2020, Ghana had recorded 35,142 cases. COVID-19 which can be transmitted by both symptomatic and asymptomatic individuals usually manifest as pneumonia with symptoms like fever, cough, dyspnoea and fatigue. The current non-availability of a vaccine or drug for COVID-19 management calls for early detection and isolation of affected individuals. Chest imaging has become an integral part of patient management with chest radiography serving as a primary imaging modality in many centres.Methods: The study was a retrospective study conducted at Ga East Municipal Hospital (GEMH). Chest radiographs of patients with mild to moderate disease managed at GEMH were evaluated. The age, gender, symptom status, comorbidities and chest x-ray findings of the patients were documented. Results: 11.4 % of the patients had some form of respiratory abnormality on chest radiography with 88.9% showing COVID-19 pneumonia features. 93.8% showed ground glass opacities (GGO), with 3.1% each showing consolidation (CN) only and CN with GGO. There was a significant association between COVID-19 radiographic features and patient’s age, symptom status and comorbidities but not with gender.Conclusion: Most radiographs were normal with only 11% showing COVID-19-like abnormality. There was a significant association between age, symptom status and comorbidities with the presence of COVID-19 like features but not for gender. There was no association between the extent of the lung changes and patient characteristics.

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