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Stepwise diagnostic algorithm for high-attenuation pulmonary abnormalities on CT.
Fukuda, Taiki; Egashira, Ryoko; Ueno, Midori; Hashisako, Mikiko; Sumikawa, Hiromitsu; Tominaga, Junya; Yamada, Daisuke; Fukuoka, Junya; Misumi, Shigeki; Ojiri, Hiroya; Hatabu, Hiroto; Johkoh, Takeshi.
Afiliación
  • Fukuda T; Department of Radiology, The Jikei University School of Medicine, 3-25-8, Nishi-Shimbashi, Minato-Ku, Tokyo, 105-8461, Japan. taiki.fukuda@gmail.com.
  • Egashira R; Department of Radiology, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, Saga-City, Saga, 849-8501, Japan.
  • Ueno M; Department of Radiology, University of Occupational and Environmental Health, 1-1, Iseigaoka, Yahatanishi-Ku, Kitakyushu, Fukuoka, 807-8556, Japan.
  • Hashisako M; Department of Pathology, Kyushu University, 3-1-1, Maidashi, Higashi-Ku, Fukuoka-City, Fukuoka, 812-8582, Japan.
  • Sumikawa H; Department of Radiology, National Hospital Organization Kinki-Chuo Chest Medical Center, 1180, Nagasone-Cho, Kita-Ku, Sakai-City, Osaka, 591-8555, Japan.
  • Tominaga J; Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, 1-1, Seiryo-Machi, Aoba-Ku, Sendai, 980-8574, Japan.
  • Yamada D; Department of Radiology, St. Luke's International Hospital, 9-1, Akashicho, Chuo-Ku, Tokyo, 104-8560, Japan.
  • Fukuoka J; Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1, Sakamoto, Nagasaki-City, Nagasaki, 852-8523, Japan.
  • Misumi S; Department of Radiology, The Jikei University School of Medicine, 3-25-8, Nishi-Shimbashi, Minato-Ku, Tokyo, 105-8461, Japan.
  • Ojiri H; Department of Radiology, The Jikei University School of Medicine, 3-25-8, Nishi-Shimbashi, Minato-Ku, Tokyo, 105-8461, Japan.
  • Hatabu H; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.
  • Johkoh T; Department of Radiology, Kansai Rosai Hospital, 3-1-69, Inabaso, Amagasaki, Hyogo, 660-8511, Japan.
Insights Imaging ; 14(1): 177, 2023 Oct 20.
Article en En | MEDLINE | ID: mdl-37857741
ABSTRACT
High-attenuation pulmonary abnormalities are commonly seen on CT. These findings are increasingly encountered with the growing number of CT examinations and the wide availability of thin-slice images. The abnormalities include benign lesions, such as infectious granulomatous diseases and metabolic diseases, and malignant tumors, such as lung cancers and metastatic tumors. Due to the wide spectrum of diseases, the proper diagnosis of high-attenuation abnormalities can be challenging. The assessment of these abnormal findings requires scrutiny, and the treatment is imperative. Our proposed stepwise diagnostic algorithm consists of five steps. Step 1 Establish the presence or absence of metallic artifacts. Step 2 Identify associated nodular or mass-like soft tissue components. Step 3 Establish the presence of solitary or multiple lesions if identified in Step 2. Step 4 Ascertain the predominant distribution in the upper or lower lungs if not identified in Step 2. Step 5 Identify the morphological pattern, such as linear, consolidation, nodular, or micronodular if not identified in Step 4. These five steps to diagnosing high-attenuation abnormalities subdivide the lesions into nine categories. This stepwise radiologic diagnostic approach could help to narrow the differential diagnosis for various pulmonary high-attenuation abnormalities and to achieve a precise diagnosis.Critical relevance statement Our proposed stepwise diagnostic algorithm for high-attenuation pulmonary abnormalities may help to recognize a variety of those high-attenuation findings, to determine whether the associated diseases require further investigation, and to guide appropriate patient management. Key points • To provide a stepwise diagnostic approach to high-attenuation pulmonary abnormalities.• To familiarize radiologists with the varying cause of high-attenuation pulmonary abnormalities.• To recognize which high-attenuation abnormalities require scrutiny and prompt treatment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Insights Imaging Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: ALEMANHA / ALEMANIA / DE / DEUSTCHLAND / GERMANY

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Insights Imaging Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: ALEMANHA / ALEMANIA / DE / DEUSTCHLAND / GERMANY