Micronodular lung disease on high-resolution CT: patterns and differential diagnosis
With the advent of high-resolution computed tomography (HRCT), micronodular lung disease is a routinely encountered pathology in thoracic imaging. This article will review how to differentiate the three main micronodular patterns and review the differential diagnosis for each. Differential diagnosis...
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Veröffentlicht in: | Clinical radiology 2021-06, Vol.76 (6), p.399-406 |
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description | With the advent of high-resolution computed tomography (HRCT), micronodular lung disease is a routinely encountered pathology in thoracic imaging. This article will review how to differentiate the three main micronodular patterns and review the differential diagnosis for each. Differential diagnosis of micronodular lung disease may be extensive, but by identifying the pattern and using additional clues, such as distribution, additional imaging findings, and clinical history, a radiologist can make an accurate diagnosis. First, three micronodular patterns — centrilobular, peri-lymphatic, and random — can be identified by using a simple algorithm based on the location of nodules. This algorithm requires understanding of the anatomy and function of the secondary pulmonary lobule. Each micronodular pattern offers a unique differential diagnosis. Centrilobular nodules can be seen with inflammatory, infectious, or vascular aetiologies; peri-lymphatic nodules with sarcoidosis and lymphangitic carcinomatosis; and random nodules with haematogenous metastases or infections. |
doi_str_mv | 10.1016/j.crad.2020.12.025 |
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This article will review how to differentiate the three main micronodular patterns and review the differential diagnosis for each. Differential diagnosis of micronodular lung disease may be extensive, but by identifying the pattern and using additional clues, such as distribution, additional imaging findings, and clinical history, a radiologist can make an accurate diagnosis. First, three micronodular patterns — centrilobular, peri-lymphatic, and random — can be identified by using a simple algorithm based on the location of nodules. This algorithm requires understanding of the anatomy and function of the secondary pulmonary lobule. Each micronodular pattern offers a unique differential diagnosis. Centrilobular nodules can be seen with inflammatory, infectious, or vascular aetiologies; peri-lymphatic nodules with sarcoidosis and lymphangitic carcinomatosis; and random nodules with haematogenous metastases or infections.</description><identifier>ISSN: 0009-9260</identifier><identifier>EISSN: 1365-229X</identifier><identifier>DOI: 10.1016/j.crad.2020.12.025</identifier><identifier>PMID: 33563413</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><ispartof>Clinical radiology, 2021-06, Vol.76 (6), p.399-406</ispartof><rights>2021 The Royal College of Radiologists</rights><rights>Copyright © 2021 The Royal College of Radiologists. Published by Elsevier Ltd. 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This article will review how to differentiate the three main micronodular patterns and review the differential diagnosis for each. Differential diagnosis of micronodular lung disease may be extensive, but by identifying the pattern and using additional clues, such as distribution, additional imaging findings, and clinical history, a radiologist can make an accurate diagnosis. First, three micronodular patterns — centrilobular, peri-lymphatic, and random — can be identified by using a simple algorithm based on the location of nodules. This algorithm requires understanding of the anatomy and function of the secondary pulmonary lobule. Each micronodular pattern offers a unique differential diagnosis. 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This article will review how to differentiate the three main micronodular patterns and review the differential diagnosis for each. Differential diagnosis of micronodular lung disease may be extensive, but by identifying the pattern and using additional clues, such as distribution, additional imaging findings, and clinical history, a radiologist can make an accurate diagnosis. First, three micronodular patterns — centrilobular, peri-lymphatic, and random — can be identified by using a simple algorithm based on the location of nodules. This algorithm requires understanding of the anatomy and function of the secondary pulmonary lobule. Each micronodular pattern offers a unique differential diagnosis. Centrilobular nodules can be seen with inflammatory, infectious, or vascular aetiologies; peri-lymphatic nodules with sarcoidosis and lymphangitic carcinomatosis; and random nodules with haematogenous metastases or infections.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>33563413</pmid><doi>10.1016/j.crad.2020.12.025</doi><tpages>8</tpages></addata></record> |
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title | Micronodular lung disease on high-resolution CT: patterns and differential diagnosis |
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