Interstitial Lung Abnormality: Narrative Review of the Approach to Diagnosis and Management.

Abstract

Topic importance: As interstitial lung abnormalities (ILAs) are increasingly recognized on imaging and in clinical practice, identification and appropriate management are critical. We propose an algorithmic approach to the identification and management of patients with ILAs.

Review findings: The radiologist initially identifies chest CT scan findings suggestive of an ILA pattern and excludes findings that are not consistent with ILAs. The next step is to confirm that these findings occupy > 5% of a nondependent lung zone. At this point, the radiologic pattern of ILA is identified. These findings are classified as non-subpleural, subpleural nonfibrotic, and subpleural fibrotic. It is then incumbent on the clinician to ascertain if the patient has symptoms and/or abnormal pulmonary physiology that may be attributable to these radiologic changes. Based on the patient's symptoms, physiological assessment, and risk factors for interstitial lung disease (ILD), we recommend classifying patients as having ILA, at high risk for developing ILD, probable ILD, or ILD. In patients identified as having ILA, a multidisciplinary discussion should evaluate features that indicate an increased risk of progression. If these features are present, serial monitoring is recommended to be proactive. If the patient does not have imaging or clinical features that indicate an increased risk of progression, then monitoring is recommended to be reactive. If ILD is subsequently diagnosed, the management is disease specific.

Summary: We anticipate this algorithmic approach will aid clinicians in interpreting the radiologic pattern described as ILA within the clinical context of their patients.