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2.
Radiologe ; 56(9): 803-9, 2016 Sep.
Article in German | MEDLINE | ID: mdl-27495787

ABSTRACT

Pulmonary nodules are the most frequent pathological finding in low-dose computed tomography (CT) scanning for early detection of lung cancer. Early stages of lung cancer are often manifested as pulmonary nodules; however, the very commonly occurring small nodules are predominantly benign. These benign nodules are responsible for the high percentage of false positive test results in screening studies. Appropriate diagnostic algorithms are necessary to reduce false positive screening results and to improve the specificity of lung cancer screening. Such algorithms are based on some of the basic principles comprehensively described in this article. Firstly, the diameter of nodules allows a differentiation between large (>8 mm) probably malignant and small (<8 mm) probably benign nodules. Secondly, some morphological features of pulmonary nodules in CT can prove their benign nature. Thirdly, growth of small nodules is the best non-invasive predictor of malignancy and is utilized as a trigger for further diagnostic work-up. Non-invasive testing using positron emission tomography (PET) and contrast enhancement as well as invasive diagnostic tests (e.g. various procedures for cytological and histological diagnostics) are briefly described in this article. Different nodule morphology using CT (e.g. solid and semisolid nodules) is associated with different biological behavior and different algorithms for follow-up are required. Currently, no obligatory algorithm is available in German-speaking countries for the management of pulmonary nodules, which reflects the current state of knowledge. The main features of some international and American recommendations are briefly presented in this article from which conclusions for the daily clinical use are derived.


Subject(s)
Early Detection of Cancer/methods , Lung Neoplasms/diagnostic imaging , Radiation Exposure/prevention & control , Radiation Protection/methods , Solitary Pulmonary Nodule/diagnostic imaging , Tomography, X-Ray Computed/methods , Evidence-Based Medicine , Humans , Lung Neoplasms/prevention & control , Patient Safety , Radiation Dosage , Radiation Exposure/analysis , Solitary Pulmonary Nodule/prevention & control
3.
Pediatr Radiol ; 45(5): 634-9, 2015 Apr.
Article in English | MEDLINE | ID: mdl-25655370

ABSTRACT

The incidental detection of small lung nodules in children is a vexing consequence of an increased reliance on CT. We present an algorithm for the management of lung nodules detected on CT in children, based on the presence or absence of symptoms, the presence or absence of elements in the clinical history that might explain these nodules, and the imaging characteristics of the nodules (such as attenuation measurements within the nodule). We provide suggestions on how to perform a thoughtfully directed and focused search for clinically occult extrathoracic disease processes (including malignant disease) that may present as an incidentally detected lung nodule on CT. This algorithm emphasizes that because of the lack of definitive information on the natural history of small solid nodules that are truly detected incidentally, their clinical management is highly dependent on the caregivers' individual risk tolerance. In addition, we present strategies to reduce the prevalence of these incidental findings, by preventing unnecessary chest CT scans or inadvertent inclusion of portions of the lungs in scans of adjacent body parts. Application of these guidelines provides pediatric radiologists with an important opportunity to practice patient-centered and evidence-based medicine.


Subject(s)
Health Communication , Incidental Findings , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/prevention & control , Solitary Pulmonary Nodule/diagnostic imaging , Solitary Pulmonary Nodule/prevention & control , Child, Preschool , Humans , Lung/diagnostic imaging , Lung Neoplasms/therapy , Risk , Solitary Pulmonary Nodule/therapy , Tomography, X-Ray Computed
4.
Article in Portuguese | LILACS | ID: lil-512267

ABSTRACT

JUSTIFICATIVA E OBJETIVOS: O nódulo pulmonar solitário (NPS) é definido radiologicamente como uma le­são pulmonar intraparenquimatosa com menor que 3 cm de diâme­tro e que não está associada com atelectasia ou adenopatia. Destes nódulos, 90% são achados radiológicos incidentais. O objetivo deste estudo foi discutir as causas e característi­cas dos NPS e como proceder com a investigação. CONTEÚDO: A abordagem do paciente com um NPS deve basear-se na estimativa da probabilidade de câncer, de acordo com o tamanho do nódulo, a presença de tabagis­mo, a idade do paciente e as características das margens do nódulo na tomografia computadorizada (TC). Exames de imagem modernos, como a TC dinâmica, a tomografia com emissão de pósitrons (PET) e a biópsia com agulha guiada por TC são altamente sensíveis na identificação do NPS, mas a especificidade dos exames de imagem é variável e geralmente baixa. CONCLUSÃO: O objetivo da avaliação do NPS é a pronta identificação de todos os pacientes com nódulos malignos, bem como evitar toracotomias em pacientes com nódulos benignos.


Subject(s)
Humans , Solitary Pulmonary Nodule/diagnosis , Solitary Pulmonary Nodule/epidemiology , Solitary Pulmonary Nodule/prevention & control , Solitary Pulmonary Nodule/therapy
5.
Clin Imaging ; 18(1): 16-20, 1994.
Article in English | MEDLINE | ID: mdl-8180854

ABSTRACT

Computed tomography (CT) imaging as an excellent approach to the detection and characterization of small solitary pulmonary nodules (SSPN) raises three questions: (1) How often does CT imaging lead to detection of SSPN? (2) How often is such an SSPN malignant? (3) If malignant, how curable is it? The first question pertains to decisions about screening use of CT (clinical or mass screening), the second to decisions about screening for SSPN and diagnosis of malignancy given SSPN, and the third--in the context of known curability at ordinary clinical diagnosis--to decisions about screening for SSPN, diagnosis given SSPN and intervention given malignant SSPN. We present a three component study design that addresses these questions. The first is directed primarily to the first question. Some 1000 persons at high risk for lung cancer will be screened for SSPN using screening-type CT. The primary aim is to determine the prevalence of CT-detectable SSPN as a joint function of risk-relevant aspects of the person. The second component addresses the prevalence of malignancy among the detected cases of SSPN. To develop the prevalence function, a larger series of CT-detected SSPN will be obtained by developing a multi-center SSPN "registry." A subsequent, third component will focus on the registered cases of malignant SSPN screening incidentally detected and address their curability on the basis of long-term follow-up. This design, in lieu of a randomized trial, may represent a new paradigm for applied research on radiologic technologies in cancer screening, given its advantages in terms of research efficiency and implications to decisions about diagnostic workup and therapeutic intervention.


Subject(s)
Lung Neoplasms/diagnostic imaging , Lung Neoplasms/prevention & control , Mass Screening , Solitary Pulmonary Nodule/diagnostic imaging , Solitary Pulmonary Nodule/prevention & control , Tomography, X-Ray Computed , Decision Making , Humans , Lung Neoplasms/pathology , Lung Neoplasms/surgery , Prevalence , Probability , Research Design , Risk Factors , Sensitivity and Specificity , Solitary Pulmonary Nodule/pathology , Solitary Pulmonary Nodule/surgery , Treatment Outcome
6.
Invest Radiol ; 27(6): 471-5, 1992 Jun.
Article in English | MEDLINE | ID: mdl-1607261

ABSTRACT

RATIONALE AND OBJECTIVE: To alert radiologists to possible nodule locations and subsequently to reduce the number of false-negative diagnoses, the authors are developing a computer-aided diagnostic (CAD) scheme for the detection of lung nodules in digital chest images. METHODS: A computer-vision scheme was applied to photofluorographic films obtained in a mass survey for detection of asymptomatic lung cancer in Japan. Ninety-five patients with abnormal test results who had primary and metastatic lung cancers and 103 patients with normal test results were included. RESULTS: The sensitivity of the computer output was comparable with that of physicians in this mass survey (62%). The computer detected approximately 40% of all nodules missed in the mass survey, but missed 17 true-positive results identified in the mass survey. The CAD scheme produced an average of 15 false-positive findings per image. CONCLUSION: If the number of false-positive results can be significantly reduced, computer-vision schemes such as this may have a role in lung cancer screening programs.


Subject(s)
Mass Chest X-Ray , Radiographic Image Interpretation, Computer-Assisted , Solitary Pulmonary Nodule/prevention & control , False Positive Reactions , Humans , Japan/epidemiology , Lung Neoplasms/epidemiology , Lung Neoplasms/prevention & control , Radiographic Image Enhancement , Sensitivity and Specificity , Solitary Pulmonary Nodule/epidemiology
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