دورية أكاديمية
Quantitative radiomics analysis of imaging features in adults and children Mycoplasma pneumonia.
| العنوان: | Quantitative radiomics analysis of imaging features in adults and children Mycoplasma pneumonia. |
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| المؤلفون: | Meng H; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China., Wang TD; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China., Zhuo LY; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China., Hao JW; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China., Sui LY; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China., Yang W; Department of Radiology, Baoding First Central Hospital, Baoding, China., Zang LL; Department of Radiology, Baoding Children's Hospital, Baoding, China., Cui JJ; Department of Research and Development, United Imaging Intelligence (Beijing) Co., Beijing, China., Wang JN; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China., Yin XP; Clinical Medicine School of Hebei University, Baoding, China.; Department of Radiology, Affiliated Hospital of Hebei University, Baoding, China.; Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Baoding, China. |
| المصدر: | Frontiers in medicine [Front Med (Lausanne)] 2024 May 20; Vol. 11, pp. 1409477. Date of Electronic Publication: 2024 May 20 (Print Publication: 2024). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: Lausanne, Switzerland : Frontiers Media S.A., [2014]- |
| مستخلص: | Purpose: This study aims to explore the value of clinical features, CT imaging signs, and radiomics features in differentiating between adults and children with Mycoplasma pneumonia and seeking quantitative radiomic representations of CT imaging signs. Materials and Methods: In a retrospective analysis of 981 cases of mycoplasmal pneumonia patients from November 2021 to December 2023, 590 internal data (adults:450, children: 140) randomly divided into a training set and a validation set with an 8:2 ratio and 391 external test data (adults:121; children:270) were included. Using univariate analysis, CT imaging signs and clinical features with significant differences ( p < 0.05) were selected. After segmenting the lesion area on the CT image as the region of interest, 1,904 radiomic features were extracted. Then, Pearson correlation analysis (PCC) and the least absolute shrinkage and selection operator (LASSO) were used to select the radiomic features. Based on the selected features, multivariable logistic regression analysis was used to establish the clinical model, CT image model, radiomic model, and combined model. The predictive performance of each model was evaluated using ROC curves, AUC, sensitivity, specificity, accuracy, and precision. The AUC between each model was compared using the Delong test. Importantly, the radiomics features and quantitative and qualitative CT image features were analyzed using Pearson correlation analysis and analysis of variance, respectively. Results: For the individual model, the radiomics model, which was built using 45 selected features, achieved the highest AUCs in the training set, validation set, and external test set, which were 0.995 (0.992, 0.998), 0.952 (0.921, 0.978), and 0.969 (0.953, 0.982), respectively. In all models, the combined model achieved the highest AUCs, which were 0.996 (0.993, 0.998), 0.972 (0.942, 0.995), and 0.986 (0.976, 0.993) in the training set, validation set, and test set, respectively. In addition, we selected 11 radiomics features and CT image features with a correlation coefficient r greater than 0.35. Conclusion: The combined model has good diagnostic performance for differentiating between adults and children with mycoplasmal pneumonia, and different CT imaging signs are quantitatively represented by radiomics. Competing Interests: J-JC was employed by United Imaging Intelligence (Beijing) Co. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Meng, Wang, Zhuo, Hao, Sui, Shen, Yang, Zang, Cui, Wang and Yin.) |
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| فهرسة مساهمة: | Keywords: adults; children; computed tomography (CT); mycoplasma pneumonia; radiomics |
| تواريخ الأحداث: | Date Created: 20240604 Latest Revision: 20240607 |
| رمز التحديث: | 20240607 |
| مُعرف محوري في PubMed: | PMC11146305 |
| DOI: | 10.3389/fmed.2024.1409477 |
| PMID: | 38831994 |
| قاعدة البيانات: | MEDLINE |
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