Quantification of the spatial distribution of primary tumors in the lung to develop new prognostic biomarkers for locally advanced NSCLC.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_B2FF32E1158E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Quantification of the spatial distribution of primary tumors in the lung to develop new prognostic biomarkers for locally advanced NSCLC.
Journal
Scientific reports
Author(s)
Vuong D., Bogowicz M., Wee L., Riesterer O., Vlaskou Badra E., D'Cruz L.A., Balermpas P., van Timmeren J.E., Burgermeister S., Dekker A., De Ruysscher D., Unkelbach J., Thierstein S., Eboulet E.I., Peters S., Pless M., Guckenberger M., Tanadini-Lang S.
ISSN
2045-2322 (Electronic)
ISSN-L
2045-2322
Publication state
Published
Issued date
22/10/2021
Peer-reviewed
Oui
Volume
11
Number
1
Pages
20890
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
The anatomical location and extent of primary lung tumors have shown prognostic value for overall survival (OS). However, its manual assessment is prone to interobserver variability. This study aims to use data driven identification of image characteristics for OS in locally advanced non-small cell lung cancer (NSCLC) patients. Five stage IIIA/IIIB NSCLC patient cohorts were retrospectively collected. Patients were treated either with radiochemotherapy (RCT): RCT1* (n = 107), RCT2 (n = 95), RCT3 (n = 37) or with surgery combined with radiotherapy or chemotherapy: S1* (n = 135), S2 (n = 55). Based on a deformable image registration (MIM Vista, 6.9.2.), an in-house developed software transferred each primary tumor to the CT scan of a reference patient while maintaining the original tumor shape. A frequency-weighted cumulative status map was created for both exploratory cohorts (indicated with an asterisk), where the spatial extent of the tumor was uni-labeled with 2 years OS. For the exploratory cohorts, a permutation test with random assignment of patient status was performed to identify regions with statistically significant worse OS, referred to as decreased survival areas (DSA). The minimal Euclidean distance between primary tumor to DSA was extracted from the independent cohorts (negative distance in case of overlap). To account for the tumor volume, the distance was scaled with the radius of the volume-equivalent sphere. For the S1 cohort, DSA were located at the right main bronchus whereas for the RCT1 cohort they further extended in cranio-caudal direction. In the independent cohorts, the model based on distance to DSA achieved performance: AUC <sub>RCT2</sub> [95% CI] = 0.67 [0.55-0.78] and AUC <sub>RCT3</sub> = 0.59 [0.39-0.79] for RCT patients, but showed bad performance for surgery cohort (AUC <sub>S2</sub> = 0.52 [0.30-0.74]). Shorter distance to DSA was associated with worse outcome (p = 0.0074). In conclusion, this explanatory analysis quantifies the value of primary tumor location for OS prediction based on cumulative status maps. Shorter distance of primary tumor to a high-risk region was associated with worse prognosis in the RCT cohort.
Pubmed
Web of science
Open Access
Yes
Create date
08/11/2021 10:32
Last modification date
12/01/2022 8:12
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