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Comparative analysis of three-dimensional and two-dimensional models for predicting the malignancy probability of subsolid nodules.
Hui, Y-M; Guo, Y; Li, B; Meng, Y-Q; Feng, H-M; Su, Z-P; Lin, M-Z; Chen, Y-Z; Zheng, Z-Z; Li, H-T.
Afiliação
  • Hui YM; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: huiyimingp@outlook.com.
  • Guo Y; Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: guoooyu@163.com.
  • Li B; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: leebin@lzu.edu.cn.
  • Meng YQ; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: 178721101@qq.com.
  • Feng HM; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: 13649312381@163.com.
  • Su ZP; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: 2502048631@qq.com.
  • Lin MZ; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: 420389065@qq.com.
  • Chen YZ; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: 393220317@qq.com.
  • Zheng ZZ; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: 756314042@qq.com.
  • Li HT; Department of Thoracic Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, LanZhou, Gansu Province, China. Electronic address: lihaitian1999@163.com.
Clin Radiol ; 79(10): 781-790, 2024 Oct.
Article em En | MEDLINE | ID: mdl-39068114
ABSTRACT

AIM:

To construct three-dimensional (3D) and two-dimensional (2D) models to predict the malignancy probability of subsolid nodules (SSNs) and compare their effectiveness. MATERIALS AND

METHODS:

A total of 371 SSNs from 332 patients, collected between January 2020 and January 2024, were included in the study. The SSNs were divided into a training set for constructing the models and a test set for validating the models. Models were developed using binary logistic backward regression, based on factors that showed significant differences in univariate analyses. The performance of the models was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). The AUCs of different models were compared using the DeLong test.

RESULTS:

The AUCs for the two 3D models, one 2D model, and the Brock model were 0.785 (0.733-0.836), 0.776 (0.723-0.829), 0.764 (0.710-0.818), and 0.738 (0.679-0.798) in the training set. In the test set, these AUCs were 0.817 (0.706-0.928), 0.796 (0.679-0.913), 0.771 (0.647-0.895), and 0.790 (0.678-0.903). The two 3D models demonstrated statistically significant differences from the Brock model in the training set (P=0.024 and P=0.046). None of the four models showed significant differences in the test set (all P>0.05).

CONCLUSION:

The 3D models outperform both the 2D model and the Brock model in predicting the malignancy probability of SSNs, and the 3D model incorporating volume, mean CT attenuation value, and lobulation as factors performed the best.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tomografia Computadorizada por Raios X / Imageamento Tridimensional Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tomografia Computadorizada por Raios X / Imageamento Tridimensional Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2024 Tipo de documento: Article