A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary Adenocarcinoma

Xiaonan Cui, Marjolein A Heuvelmans, Shuxuan Fan, Daiwei Han, Sunyi Zheng, Yihui Du, Yingru Zhao, Grigory Sidorenkov, Harry J M Groen, Monique D Dorrius, Matthijs Oudkerk, Geertruida H de Bock, Rozemarijn Vliegenthart, Zhaoxiang Ye*

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

8 Citaten (Scopus)
108 Downloads (Pure)


It is essential to identify the subsolid nodules subtype preoperatively to select the optimal treatment algorithm. We developed and validated an imaging reporting system using a classification and regression tree model that based on computed tomography imaging characteristics (291 cases in training group, 146 cases in testing group). The model showed high sensitivity and accuracy of classification. Our model can help clinicians to make follow-up recommendations or decisions for surgery for clinical patients with a subsolid nodule.

Originele taal-2English
Pagina's (van-tot)314-+
Aantal pagina's16
TijdschriftClinical lung cancer
Nummer van het tijdschrift4
Vroegere onlinedatum6-feb.-2020
StatusPublished - jul.-2020

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