Three-dimensional image analysis for staging chronic rhinosinusitis.

Three-dimensional image analysis for staging chronic rhinosinusitis.

Int Forum Allergy Rhinol. 2017 Sep 22;:

Authors: Lim S, Ramirez MV, Garneau JC, Ford MK, McKeough K, Ginat DT, Baroody FM, Armato SG, Pinto JM

Abstract
BACKGROUND: Traditional methods of staging chronic rhinosinusitis (CRS) through imaging do not differentiate between degrees of partial mucosal sinus inflammation, thus limiting their utility as imaging biomarkers. We hypothesized that software-aided, quantitative measurement of sinus inflammation would generate a metric of disease burden that would correlate with clinical parameters in patients with suspected sinus disease.
METHODS: Adults with rhinologic complaints undergoing computed tomography imaging were recruited at an urban, academic, tertiary care center (n = 45 with Lund-Mackay [LM] scores ≥4). Three-dimensional (3D) volumetric image analysis was performed using a semiautomated method to obtain a "Chicago-modified Lund-Mackay" (Chicago MLM) score, which provides a continuous scale to quantify extent of opacification. Linear regression was used to test the association of the Chicago MLM score with concurrent symptoms (Total Nasal Symptom Score [TNSS]) and disease-specific quality of life, based on the Sinonasal Outcome Test-22 (SNOT-22).
RESULTS: Chicago MLM scores were significantly associated with both symptoms (p = 0.037) and disease-specific quality of life (p = 0.007). Inflammation in the ethmoid and sphenoid sinuses appeared to influence these associations. These findings were even more robust when analysis was limited to patients with more severe disease (LM >6).
CONCLUSION: The quantitative measurement of sinus inflammation by computer-aided 3D analysis correlates modestly with both symptoms and disease-specific quality of life. Posterior sinuses appear to have the greatest impact on these findings, potentially providing an anatomic target for clinicians to base therapy. The Chicago MLM score is a promising imaging biomarker for clinical and research use.

PMID: 28941169 [PubMed - as supplied by publisher]

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