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1.
Radiographics ; 42(2): 359-378, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35089819

RESUMO

Chest wall lesions are relatively uncommon and may be challenging once they are encountered on images. Radiologists may detect these lesions incidentally at examinations performed for other indications, or they may be asked specifically to evaluate a suspicious lesion. While many chest wall lesions have characteristic imaging findings that can result in an accurate diagnosis with use of imaging alone, other entities are difficult to distinguish at imaging because there is significant overlap among them. The interpreting radiologist should be familiar with the imaging features of both "do not touch" benign entities (which can be confidently diagnosed with imaging only, with no need for biopsy or resection unless the patient is symptomatic) and lesions that cannot be confidently characterized and thus require further workup. CT and MRI are the main imaging modalities used to assess the chest wall, with each having different benefits and drawbacks. Chest wall lesions can be classified according to their predominant composition: fat, calcification and ossification, soft tissue, or fluid. The identification or predominance of signal intensities or attenuation for these findings, along with the patient age, clinical history, and lesion location, can help establish the appropriate differential diagnosis. In addition, imaging findings in other organs, such as the lungs or upper abdomen, can at times provide clues to the underlying diagnosis. The authors review different chest wall lesions classified on the basis of their composition and highlight the imaging findings that can assist the radiologist in narrowing the differential diagnosis and guiding management. ©RSNA, 2022.


Assuntos
Cavidade Abdominal , Parede Torácica , Diagnóstico Diferencial , Humanos , Imageamento por Ressonância Magnética , Parede Torácica/diagnóstico por imagem , Parede Torácica/patologia
2.
AJR Am J Roentgenol ; 217(5): 1093-1102, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33852360

RESUMO

BACKGROUND. Previous studies compared CT findings of COVID-19 pneumonia with those of other infections; however, to our knowledge, no studies to date have included noninfectious organizing pneumonia (OP) for comparison. OBJECTIVE. The objectives of this study were to compare chest CT features of COVID-19, influenza, and OP using a multireader design and to assess the performance of radiologists in distinguishing between these conditions. METHODS. This retrospective study included 150 chest CT examinations in 150 patients (mean [± SD] age, 58 ± 16 years) with a diagnosis of COVID-19, influenza, or non-infectious OP (50 randomly selected abnormal CT examinations per diagnosis). Six thoracic radiologists independently assessed CT examinations for 14 individual CT findings and for Radiological Society of North America (RSNA) COVID-19 category and recorded a favored diagnosis. The CT characteristics of the three diagnoses were compared using random-effects models; the diagnostic performance of the readers was assessed. RESULTS. COVID-19 pneumonia was significantly different (p < .05) from influenza pneumonia for seven of 14 chest CT findings, although it was different (p < .05) from OP for four of 14 findings (central or diffuse distribution was seen in 10% and 7% of COVID-19 cases, respectively, vs 20% and 21% of OP cases, respectively; unilateral distribution was seen in 1% of COVID-19 cases vs 7% of OP cases; non-tree-in-bud nodules was seen in 32% of COVID-19 cases vs 53% of OP cases; tree-in-bud nodules were seen in 6% of COVID-19 cases vs 14% of OP cases). A total of 70% of cases of COVID-19, 33% of influenza cases, and 47% of OP cases had typical findings according to RSNA COVID-19 category assessment (p < .001). The mean percentage of correct favored diagnoses compared with actual diagnoses was 44% for COVID-19, 29% for influenza, and 39% for OP. The mean diagnostic accuracy of favored diagnoses was 70% for COVID-19 pneumonia and 68% for both influenza and OP. CONCLUSION. CT findings of COVID-19 substantially overlap with those of influenza and, to a greater extent, those of OP. The diagnostic accuracy of the radiologists was low in a study sample that contained equal proportions of these three types of pneumonia. CLINICAL IMPACT. Recognized challenges in diagnosing COVID-19 by CT are furthered by the strong overlap observed between the appearances of COVID-19 and OP on CT. This challenge may be particularly evident in clinical settings in which there are substantial proportions of patients with potential causes of OP such as ongoing cancer therapy or autoimmune conditions.


Assuntos
COVID-19/diagnóstico por imagem , Pneumonia em Organização Criptogênica/diagnóstico por imagem , Influenza Humana/diagnóstico por imagem , Pneumonia Viral/diagnóstico por imagem , Tomografia Computadorizada por Raios X , Diagnóstico Diferencial , Feminino , Humanos , Influenza Humana/virologia , Masculino , Massachusetts , Pessoa de Meia-Idade , Variações Dependentes do Observador , Pneumonia Viral/virologia , Radiografia Torácica , Estudos Retrospectivos , SARS-CoV-2
3.
Radiol Clin North Am ; 59(2): 251-277, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33551086

RESUMO

The high soft tissue contrast and tissue characterization properties of magnetic resonance imaging allow further characterization of indeterminate mediastinal lesions on chest radiography and computed tomography, increasing diagnostic specificity, preventing unnecessary intervention, and guiding intervention or surgery when needed. The combination of its higher soft tissue contrast and ability to image dynamically during free breathing, without ionizing radiation exposure, allows more thorough and readily appreciable assessment of a lesion's invasiveness and assessment of phrenic nerve involvement, with significant implications for prognostic clinical staging and surgical management.


Assuntos
Imageamento por Ressonância Magnética/métodos , Neoplasias do Mediastino/diagnóstico por imagem , Humanos , Mediastino/diagnóstico por imagem , Reprodutibilidade dos Testes
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