Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?

被引:44
作者
Digumarthy, Subba R. [1 ,3 ]
Padole, Atul M. [1 ]
Rastogi, Shivam [1 ]
Price, Melissa [1 ]
Mooradian, Meghan J. [2 ]
Sequist, Lecia V. [2 ]
Kalra, Mannudeep K. [1 ]
机构
[1] Massachusetts Gen Hosp, Dept Radiol, 55 Fruit St, Boston, MA 02114 USA
[2] Massachusetts Gen Hosp, Dept Med, 55 Fruit St, Boston, MA 02114 USA
[3] Harvard Med Sch, Massachusetts Gen Hosp, Dept Radiol, 75 Blossom Court,Suite 236, Boston, MA 02114 USA
来源
CANCER IMAGING | 2019年 / 19卷 / 1期
关键词
Radiomics; Lung cancer; Subsolid nodules; Benign and malignant lung nodules; Chest CT; Follow up CT; PART-SOLID NODULES; TEXTURE ANALYSIS; LUNG-CANCER; TUMOR HETEROGENEITY; PREINVASIVE-LESIONS; NEEDLE-BIOPSY; DIFFERENTIATION; ADENOCARCINOMA; IMAGES; PURE;
D O I
10.1186/s40644-019-0223-7
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundTo assess if radiomics can differentiate benign and malignant subsolid lung nodules (SSNs) on baseline or follow up chest CT examinations. If radiomics can differentiate between benign and malignant subsolid lung nodules, the clinical implications are shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging.Materials and methodsThe IRB approved retrospective study included 36 patients (mean age 698years; 5 males, 31 females) with 108 SSNs (31benign, 77 malignant) who underwent follow up chest CT for evaluation of indeterminate SSN. All SSNs were identified on both baseline and follow up chest CT. DICOM CT images were deidentified and exported into the open access 3D Slicer software (version 4.7) to obtain radiomic features. Logistic regression analyses and receiver operating characteristic (ROC) curves for various quantitative parameters were generated with SPSS statistical software.ResultsOnly 2/92 radiomic features (cluster shade and surface volume ratio) enabled differentiation between malignant and benign SSN on baseline chest CT (P=0.01 and 0.03) with moderate accuracy [AUC 0.624 (0.505-0.743)]. On follow-up CT, 52/92 radiomic features were significantly different between benign and malignant SSN (P: 0.04 -<0.0001) with improved accuracy [AUC: 0.708 (0.605-0.811), P=0.04 - <0.0001]. Radiomics of benign SSN were stable over time, whereas 63/92 radiomic features of malignant SSNs changed significantly between the baseline and follow up chest CT (P: 0.04 -<0.0001).Conclusions Temporal changes in radiomic features of subsolid lung nodules favor malignant etiology over benign. The change in radiomics features of subsolid lung nodules can allow shorter follow up CT imaging and early recognition of lung adenocarcinoma on imaging. Radiomic features have limited application in differentiating benign and early malignant SSN on baseline chest CT.
引用
收藏
页数:8
相关论文
共 30 条
  • [1] Computerized Texture Analysis of Persistent Part-Solid Ground-Glass Nodules: Differentiation of Preinvasive Lesions from Invasive Pulmonary Adenocarcinomas
    Chae, Hee-Dong
    Park, Chang Min
    Park, Sang Joon
    Lee, Sang Min
    Kim, Kwang Gi
    Goo, Jin Mo
    [J]. RADIOLOGY, 2014, 273 (01) : 285 - 293
  • [2] Choi W, 2018, MED PHYS
  • [3] Evaluation of solitary pulmonary nodule detected during computed tomography examination
    Choromanska, Agnieszka
    Macura, Katarzyna J.
    [J]. POLISH JOURNAL OF RADIOLOGY, 2012, 77 (02) : 22 - 34
  • [4] Fan L, 2018, EUR RADIOL
  • [5] Radiomics: Images Are More than Pictures, They Are Data
    Gillies, Robert J.
    Kinahan, Paul E.
    Hricak, Hedvig
    [J]. RADIOLOGY, 2016, 278 (02) : 563 - 577
  • [6] CT quantitative parameters to predict the invasiveness of lung pure ground-glass nodules (pGGNs)
    Han, L.
    Zhang, P.
    Wang, Y.
    Gao, Z.
    Wang, H.
    Li, X.
    Ye, Z.
    [J]. CLINICAL RADIOLOGY, 2018, 73 (05) : 504.e1 - 504.e7
  • [7] Predicting Malignant Nodules from Screening CT Scans
    Hawkins, Samuel
    Wang, Hua
    Liu, Ying
    Garcia, Alberto
    Stringfield, Olya
    Krewer, Henry
    Li, Qian
    Cherezov, Dmitry
    Gatenby, Robert A.
    Balagurunathan, Yoganand
    Goldgof, Dmitry
    Schabath, Matthew B.
    Hall, Lawrence
    Gillies, Robert J.
    [J]. JOURNAL OF THORACIC ONCOLOGY, 2016, 11 (12) : 2120 - 2128
  • [8] CT screening for lung cancer: Frequency and significance of part-solid and nonsolid nodules
    Henschke, CI
    Yankelevitz, DF
    Mirtcheva, R
    McGuinness, G
    McCauley, D
    Miettinen, OS
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 2002, 178 (05) : 1053 - 1057
  • [9] CT Screening for Lung Cancer: Part-Solid Nodules in Baseline and Annual Repeat Rounds
    Henschke, Claudia I.
    Yip, Rowena
    Smith, James P.
    Wolf, Andrea S.
    Flores, Raja M.
    Liang, Mingzhu
    Salvatore, Mary M.
    Liu, Ying
    Xu, Dong Ming
    Yankelevitz, David F.
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 2016, 207 (06) : 1176 - 1184
  • [10] Persistent Pure Ground-Glass Nodules Larger Than 5 mm Differentiation of Invasive Pulmonary Adenocarcinomas From Preinvasive Lesions or Minimally Invasive Adenocarcinomas Using Texture Analysis
    Hwang, In-pyeong
    Park, Chang Min
    Park, Sang Joon
    Lee, Sang Min
    McAdams, Holman Page
    Jeon, Yoon Kyung
    Goo, Jin Mo
    [J]. INVESTIGATIVE RADIOLOGY, 2015, 50 (11) : 798 - 804