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Chest Imaging for Clinicians |

Pictorial Essay: Multinodular Disease*: A High-Resolution CT Scan Diagnostic Algorithm

Suhail Raoof, MD, FCCP; Alexey Amchentsev, MD; Ioannis Vlahos, MD; Ajay Goud, MD; David P. Naidich, MD, FCCP
Author and Funding Information

*From the Division of Pulmonary and Critical Care Medicine (Drs. Raoof and Amchentsev), New York Methodist Hospital, Brooklyn, NY; the Department of Radiology (Drs. Vlahos and Naidich), Tisch Hospital, New York University Medical Center, New York, NY; and the Department of Radiology (Dr. Goud), Brigham and Women’s Hospital, Boston, MA.

Correspondence to: Suhail Raoof, MD, FCCP, Chief, Pulmonary and Critical Care Medicine, Medical Director, Respiratory Therapy Department, New York Methodist Hospital, Pulmonary Division, 506 Sixth St, Brooklyn, NY 11215; e-mail: Sur9016@nyp.org



Chest. 2006;129(3):805-815. doi:10.1378/chest.129.3.805
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The evaluation of patients presenting with multinodular pulmonary disease provides an important clinical challenge for physicians. The differential diagnosis includes an extensive list of benign and malignant processes making the management of these cases frequently problematic. With the introduction of high-resolution CT (HRCT) scanning, the ability to assess various patterns of diffuse multinodular disease has evolved into an essential part of the diagnostic process. The purpose of this article is to develop an approach to the diagnosis of multinodular parenchymal disease using HRCT scan pattern recognition as a point of departure.

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