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Volume 47 Issue 3
Mar.  2024
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Article Navigation >  Journal of Molecular Imaging  > 2024  >  47(3): 249-255
XU Zhenyu, YANG Yunjun, DUAN Rui, GUO Li, XU Zhifeng. Value of high-resolution CT radiomics model in differentiating glandular precursor lesions and minimally invasive adenocarcinoma presenting as subcentimeter pure ground glass nodules[J]. Journal of Molecular Imaging, 2024, 47(3): 249-255. doi: 10.12122/j.issn.1674-4500.2024.03.05
Citation: XU Zhenyu, YANG Yunjun, DUAN Rui, GUO Li, XU Zhifeng. Value of high-resolution CT radiomics model in differentiating glandular precursor lesions and minimally invasive adenocarcinoma presenting as subcentimeter pure ground glass nodules[J]. Journal of Molecular Imaging, 2024, 47(3): 249-255. doi: 10.12122/j.issn.1674-4500.2024.03.05
shu

Value of high-resolution CT radiomics model in differentiating glandular precursor lesions and minimally invasive adenocarcinoma presenting as subcentimeter pure ground glass nodules

doi: 10.12122/j.issn.1674-4500.2024.03.05

  • Department of Medical Radiology, Foshan First People's Hospital, Foshan 528000, China

  • Received Date: 2023-07-16
    Available Online: 2024-04-17
  • Publish Date: 2024-03-20
    Abstract
  •   Objective  To assess the efficacy of a radiomics model rooted in high-resolution CT imaging for the differentiation of precursor glandular lesions and minimally invasive adenocarcinoma (MIA) manifesting as subcentimeter pure ground-glass nodules (pGGN).  Methods  A total of 68 patients (75 pulmonary nodules) with subcentimeter pGGN confirmed by surgical pathology from July 2020 to April 2022 were retrospectively analyzed, including 6 atypical adenomatous hyperplasia (AAH), 26 adenocarcinoma in situ (AIS) and 43 MIA. According to the pathological type, the patients were divided into precursor glandular lesions group (AAH+AIS) and minimally invasive group (MIA), including 54 cases in the training group (60 pGGN) and 14 cases in the validation group (15 pGGN). Clinical data (age, gender), CT qualitative parameters (margin, spiculation, lobulation, air bronchogram, internal vseesl sign, bubblen, pleural attachment) and quantitative parameters (longest diameter, shortest diameter, average CT value, maximum CT value, minimum CT value) were collected. Manual segmentation of each pGGN was performed using ITK-SNAP software, and image features were extracted using AK software. Statistical analyses included univariate and multivariate methods to identify significant differences between the two subgroups in the training group. We used these analyses to create imaging radiomics models, clinical models, and combined models through multivariate Logistic regression. The prediction efficiency of each model was compared by ROC curve and the area under the curve (AUC), and Delong's test was used to compare whether there were significant differences among the models. The calibration curve and the decision curve analysis were used to evaluate the calibration and clinical application of the combined model, and Hosmer-Lemeshow test was used to analyze the fitting degree between the predicted value and the observed value of the combined model.  Results  The combined model had highest diagnostic efficiency in both the training group and the text group (AUC=0.857, 95% CI: 0.764-0.951, P < 0.0001 in the training group; AUC=0.84, 95% CI: 0.592-1.000, P=0.0071 in the text group), which was higher than the radiomics model (AUC=0.835, 95% CI: 0.735-0.935, P < 0.0001 in the training group; AUC=0.82, 95% CI: 0.563-1.000, P=0.0145 in the text group) and clinical model (AUC=0.764, 95% CI: 0.636-0.864, P < 0.0001 in the training group; AUC=0.63, 95% CI: 0.347~0.913, P=0.3677 in the text group). Furthermore, the combined model demonstrated a commendable degree of consistency between its predicted values and actual observations in both the training and text group.  Conclusion  The combined model based on CT radiomics and clinical features is helpful to distinguish precursor glandular lesions and MIA which presenting as subcentimeter pure ground glass nodules before operation, and improve the level of diagnosis, treatment and management of pulmonary nodules.

     

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    • References(22)
  • [1]
    Chen WQ, Zheng RS, Zhang SW, et al. Cancer incidence and mortality in China in 2013: an analysis based on urbanization level[J]. Chin J Cancer Res, 2017, 29(1): 1-10. doi: 10.21147/j.issn.1000-9604.2017.01.01
    [2]
    World Health Organization (2021). WHO Classification of tumours of the lung[EB/OL]. [2021-06-10]. https://tumourclassification.iarc.who.int.
    [3]
    She YL, Zhang L, Zhu HY, et al. The predictive value of CT-based radiomics in differentiating indolent from invasive lung adenocarcinoma in patients with pulmonary nodules[J]. Eur Radiol, 2018, 28(12): 5121-8. doi: 10.1007/s00330-018-5509-9
    [4]
    Ishida H, Shimizu Y, Sakaguchi H, et al. Distinctive clinicopathological features of adenocarcinoma in situ and minimally invasive adenocarcinoma of the lung: a retrospective study[J]. Lung Cancer, 2019, 129: 16-21. doi: 10.1016/j.lungcan.2018.12.020
    [5]
    National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening[J]. N Engl J Med, 2011, 365(5): 395-409. doi: 10.1056/NEJMoa1102873
    [6]
    Liu SL, Wang R, Zhang Y, et al. Precise diagnosis of intraoperative frozen section is an effective method to guide resection strategy for peripheral small- sized lung adenocarcinoma[J]. J Clin Oncol, 2016, 34(4): 307-13. doi: 10.1200/JCO.2015.63.4907
    [7]
    Yeh YC, Nitadori JI, Kadota K, et al. Using frozen section to identify histological patterns in stage Ⅰ lung adenocarcinoma of≤3 Cm: accuracy and interobserver agreement[J]. Histopathology, 2015, 66(7): 922-38. doi: 10.1111/his.12468
    [8]
    Wu F, Tian SP, Jin X, et al. CT and histopathologic characteristics of lung adenocarcinoma with pure ground-glass nodules 10 mm or less in diameter[J]. Eur Radiol, 2017, 27(10): 4037-43. doi: 10.1007/s00330-017-4829-5
    [9]
    Lee SM, Park CM, Goo JM, et al. Invasive pulmonary adenocarcinomas versus preinvasive lesions appearing as ground-glass nodules: differentiation by using CT features[J]. Radiology, 2013, 268(1): 265-73. doi: 10.1148/radiol.13120949
    [10]
    Mao HX, Labh K, Han FS, et al. Diagnosis of the invasiveness of lung adenocarcinoma manifesting as ground glass opacities on high-resolution computed tomography[J]. Thorac Cancer, 2016, 7 (1): 129-35. doi: 10.1111/1759-7714.12269
    [11]
    Jiang YN, Che SY, Ma SC, et al. Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact[J]. Cancer Imaging, 2021, 21(1): 1. doi: 10.1186/s40644-020-00376-1
    [12]
    Meng Y, Liu CL, Cai Q, et al. Contrast analysis of the relationship between the HRCT sign and new pathologic classification in small ground glass nodule-like lung adenocarcinoma[J]. La Radiol Med, 2019, 124(1): 8-13. doi: 10.1007/s11547-018-0936-x
    [13]
    Song L, Xing TT, Zhu ZC, et al. Hybrid clinical-radiomics model for precisely predicting the invasiveness of lung adenocarcinoma manifesting as pure ground-glass nodule[J]. Acad Radiol, 2021, 28 (9): e267-77. doi: 10.1016/j.acra.2020.05.004
    [14]
    高琳, 张晶, 顾慧, 等. CT特征预测基于2021年肺肿瘤新分类肺纯磨玻璃结节浸润性及浸润程度的价值[J]. 中华放射学杂志, 2022, 56 (6): 616-22. doi: 10.3760/cma.j.cn112149-20210707-00641
    [15]
    Zhu YQ, Liu CH, Mo Y, et al. Radiomics for differentiating minimally invasive adenocarcinoma from precursor lesions in pure ground- glass opacities on chest computed tomography[J]. Br J Radiol, 2022, 95(1134): 20210768. doi: 10.1259/bjr.20210768
    [16]
    Liu CL, Zhang F, Cai Q, et al. Establishment of a predictive model for surgical resection of ground- glass nodules[J]. J Am Coll Radiol, 2019, 16(4): 435-45. doi: 10.1016/j.jacr.2018.09.043
    [17]
    Xiang WJ, Xing YF, Jiang S, et al. Morphological factors differentiating between early lung adenocarcinomas appearing as pure ground- glass nodules measuring ≤10 mm on thin- section computed tomography[J]. Cancer Imaging, 2014, 14(1): 33. doi: 10.1186/s40644-014-0033-x
    [18]
    Fan L, Fang MJ, Li ZB, et al. Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule[J]. Eur Radiol, 2019, 29(2): 889-97. doi: 10.1007/s00330-018-5530-z
    [19]
    Sun YL, Li C, Jin L, et al. Radiomics for lung adenocarcinoma manifesting as pure ground- glass nodules: invasive prediction[J]. Eur Radiol, 2020, 30(7): 3650-9. doi: 10.1007/s00330-020-06776-y
    [20]
    Wu T, Dai Y. Tumor microenvironment and therapeutic response [J]. Cancer Lett, 2017, 387: 61-8. doi: 10.1016/j.canlet.2016.01.043
    [21]
    Beig N, Khorrami M, Alilou M, et al. Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas[J]. Radiology, 2019, 290(3): 783-92. doi: 10.1148/radiol.2018180910
    [22]
    Nishino M. Perinodular radiomic features to assess nodule microenvironment: does it help to distinguish malignant versus benign lung nodules?[J]. Radiology, 2019, 290(3): 793-5. doi: 10.1148/radiol.2018182619
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