scholarly journals Spontaneous Regression of Pulmonary Metastases from Breast Angiosarcoma

Sarcoma ◽  
2008 ◽  
Vol 2008 ◽  
pp. 1-4 ◽  
Author(s):  
S. W. Kim ◽  
J. Wylie
Keyword(s):  
Rare Case ◽  
Spontaneous Regression ◽  
Pulmonary Metastases ◽  
Postoperative Radiotherapy ◽  
Metastatic Breast ◽  
Lung Nodules ◽  
Total Mastectomy ◽  
X Ray ◽  
Chest X Ray ◽  
Scalp Lesions

Spontaneous regression of cancer is a rare phenomenon. We present a rare case of pulmonary metastases in a 72-year-old woman with metastatic breast angiosarcoma. She was diagnosed with a breast angiosarcoma in 2005 and underwent a total mastectomy and postoperative radiotherapy. Unfortunately, a year later she was found to have multiple lung and scalp metastases but in a view of her poor general fitness, she was not a candidate for chemotherapy and was kept on regular followup. Despite the absence of any treatment, the followup chest X-ray showed a significant reduction in the number and size of lung nodules and her scalp lesions regressed completely. Seven months after the diagnosis of metastatic disease, the nodules in her scalp remain controlled.

Focal abnormalities

ESC CardioMed ◽  
2018 ◽  
pp. 411-412
Author(s):  
Nicola Sverzellati ◽  
Gianluca Milanese ◽  
Mario Silva
Keyword(s):  
Computed Tomography ◽  
Clinical Assessment ◽  
Lung Nodules ◽  
Technological Equipment ◽  
X Ray ◽  
Progressive Development ◽  
Software Applications ◽  
Lung Abnormalities ◽  
Challenging Tasks ◽  
Chest X Ray

Both the detection and interpretation of focal abnormalities on chest X-ray (CXR) are challenging tasks. CXR accuracy depends on the view (e.g. the supine view has limited sensitivity) and technological equipment. The detection of small focal abnormalities (e.g. lung nodules) varies between anatomical regions according to the presence of dense anatomic structures, such as the bones and the hila. The interpretation of focal abnormalities on CXR is paramount within the whole clinical assessment, because CXR findings can guide the patient’s management, or warrant further investigations, such as computed tomography. Focal lung abnormalities on CXR are still a cornerstone of diagnostic algorithms; however, the radiological approach has progressively changed in the last decade because of the progressive development of both hardware and software applications that enable sensitive detection and accurate characterization.

scholarly journals Interstitial lung disease: A case report

2013 ◽  
Vol 24 (1) ◽  
pp. 52-54
Author(s):  
SM Kamal ◽  
Md Abu Bakar ◽  
MA Ahad
Keyword(s):  
Case Report ◽  
Interstitial Lung Disease ◽  
Idiopathic Pulmonary Fibrosis ◽  
Lung Disease ◽  
Rare Case ◽  
Productive Cough ◽  
X Ray ◽  
Chest Examination ◽  
Chest X Ray ◽  
Medicine Today

A 65 years old farmer was admitted in Medicine ward with the complaints of progressive exertional breathlessness, non-productive cough and recurrent episodes of fever. The patient had clubbing and chest examination revealed end inspiratory crackles. Chest x-ray, CT scan of chest and spirometry revealed the features of interstitial lung disease (ILD). So we diagnosed the case as idiopathic pulmonary fibrosis variety of ILD. We reported this rare case for developing awareness among the clinicians. DOI: http://dx.doi.org/10.3329/medtoday.v24i1.14118 Medicine TODAY Vol.24(1) 2012 pp.52-54

IgG4-related lung disease on the horizon

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Tin Lok Lai ◽  
Cheuk Wan Yim
Keyword(s):  
Lung Disease ◽  
Lung Biopsy ◽  
Lung Nodules ◽  
Lung Involvement ◽  
Immunoglobulin G4 ◽  
X Ray ◽  
Related Disease ◽  
Igg4 Related Disease ◽  
Chest X Ray ◽  
Diffuse Lung

Abstract Immunoglobulin G4 (IgG4) related lung disease is an emerging entity. We report a case of a 42-year-old man presented with fever and cough with minimal sputum. Chest X-ray revealed diffuse reticulonodular shadows. Extensive investigations were performed, including video-assisted thoracoscopic lung biopsy, which confirmed the diagnosis of IgG4-related disease (IgG4-RD) with lung involvement. This case report aims to illustrate that IgG4-related lung involvement can present as diffuse lung nodules and can affect different pulmonary structures. IgG4-RD should always be considered when a similar scenario is encountered.

scholarly journals Rare case of double aortic arch suspected by preoperative chest X-ray in a healthy woman

2014 ◽  
Vol 112 (6) ◽  
pp. 1117-1118 ◽  
Author(s):  
Y. Suzuki ◽  
Y. Nishikawa ◽  
D. Horiuchi ◽  
K. Semba ◽  
T. Fujii ◽  
...  
Keyword(s):  
Aortic Arch ◽  
Rare Case ◽  
Healthy Woman ◽  
Double Aortic Arch ◽  
X Ray ◽  
Chest X Ray ◽  
Preoperative Chest

scholarly journals Adopting Confident Learning to Eliminate Uncertainty in Chest X-ray Images for Lung Nodules Prediction

2020 ◽  
Vol 108 (3) ◽  
pp. e338
Author(s):  
M. Kholiavchenko ◽  
B. Maksudov ◽  
I. Sirazitdinov ◽  
T. Mustafaev ◽  
R. Kuleev ◽  
...  
Keyword(s):  
Lung Nodules ◽  
X Ray ◽  
Chest X Ray

Clue to the diagnosis on chest X-ray in a child with neck swelling

2018 ◽  
Vol 105 (2) ◽  
pp. 97-98
Author(s):  
Gurinder Kumar ◽  
Vasudev Omprakash Sharma ◽  
Khalid Mohamed Mansour Mohamedfaris ◽  
Rajendran Nair ◽  
Aman Preet Singh Sohal
Keyword(s):  
Thyroid Cancer ◽  
Children And Adolescents ◽  
Rare Disease ◽  
Papillary Thyroid Cancer ◽  
Rare Case ◽  
Differentiated Thyroid Cancer ◽  
Papillary Thyroid ◽  
Neck Swelling ◽  
X Ray ◽  
Chest X Ray

Differentiated thyroid cancer is a rare disease in children and adolescents and manifests exclusively in the form of papillary thyroid cancer (PTC). We present a rare case of PTC who presented initially with lung symptoms and miliary nodules on chest X-ray. This case emphasises the important differential of miliary mottling of the lungs.

A rare case of central venous catheter malpositioning in polytraumatic patient not recognized by chest x-ray

2012 ◽  
Vol 14 (1) ◽  
pp. 97-98 ◽  
Author(s):  
Simonetta Nataloni ◽  
Andrea Carsetti ◽  
Vincenzo Gabbanelli ◽  
Abele Donati ◽  
Erica Adrario ◽  
...  
Keyword(s):  
Central Venous Catheter ◽  
Rare Case ◽  
Venous Catheter ◽  
Central Venous ◽  
X Ray ◽  
Chest X Ray

scholarly journals Deep Mining Generation of Lung Cancer Malignancy Models from Chest X-ray Images

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6655
Author(s):  
Michael Horry ◽  
Subrata Chakraborty ◽  
Biswajeet Pradhan ◽  
Manoranjan Paul ◽  
Douglas Gomes ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Computer Vision ◽  
Deep Learning ◽  
Decision Tree ◽  
Decision Trees ◽  
Lung Nodules ◽  
X Rays ◽  
Learning Models ◽  
X Ray ◽  
Chest X Ray

Lung cancer is the leading cause of cancer death and morbidity worldwide. Many studies have shown machine learning models to be effective in detecting lung nodules from chest X-ray images. However, these techniques have yet to be embraced by the medical community due to several practical, ethical, and regulatory constraints stemming from the “black-box” nature of deep learning models. Additionally, most lung nodules visible on chest X-rays are benign; therefore, the narrow task of computer vision-based lung nodule detection cannot be equated to automated lung cancer detection. Addressing both concerns, this study introduces a novel hybrid deep learning and decision tree-based computer vision model, which presents lung cancer malignancy predictions as interpretable decision trees. The deep learning component of this process is trained using a large publicly available dataset on pathological biomarkers associated with lung cancer. These models are then used to inference biomarker scores for chest X-ray images from two independent data sets, for which malignancy metadata is available. Next, multi-variate predictive models were mined by fitting shallow decision trees to the malignancy stratified datasets and interrogating a range of metrics to determine the best model. The best decision tree model achieved sensitivity and specificity of 86.7% and 80.0%, respectively, with a positive predictive value of 92.9%. Decision trees mined using this method may be considered as a starting point for refinement into clinically useful multi-variate lung cancer malignancy models for implementation as a workflow augmentation tool to improve the efficiency of human radiologists.

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