Pulmonary Nodule
Evaluation is guided by nodule size & assessment of probability of malignancy. In addition is based on the yield of available diagnostic testing, patient comorbidities, & patient preferences. Focal pulmonary lesions that are > 3 cm in diameter are called lung masses & should be considered malignant until proven otherwise.
Pulmonary nodules are categorized as small solid (<8 mm), larger solid (β₯8 mm), and subsolid.
Subsolid nodules are divided into ground-glass nodules (no solid component) and part-solid (both ground-glass and solid components).
The probability of malignancy is < 1% for all nodules < 6 mm and 1% to 2% for nodules 6 mm to 8 mm.
Nodules that are 6 mm to 8 mm can be followed with a repeat chest CT in 6 to 12 months, depending on the presence of patient risk factors and imaging characteristics associated with lung malignancy, clinical judgment about the probability of malignancy, and patient preferences.
The treatment of an individual with a solid pulmonary nodule 8 mm or larger is based on the estimated probability of malignancy; the presence of patient comorbidities, such as chronic obstructive pulmonary disease and coronary artery disease; and patient preferences. Management options include surveillance imaging, defined as monitoring for nodule growth with chest CT imaging, positron emission tomography-CT imaging, nonsurgical biopsy with bronchoscopy or transthoracic needle biopsy, and surgical resection.
Part-solid pulmonary nodules are managed according to the size of the solid component.
Larger solid components are associated with a higher risk of malignancy.
Ground-glass pulmonary nodules have a probability of malignancy of 10% to 50% when they persist beyond 3 months and are larger than 10 mm in diameter.
A malignant nodule that is entirely ground glass in appearance is typically slow growing. Current bronchoscopy and transthoracic needle biopsy methods yield a sensitivity of 70% to 90% for a diagnosis of lung cancer.
source : https://pubmed.ncbi.nlm.nih.gov/350
Satyendra Dhar MD @DharSaty
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