Reliability of PET/CT Shape and Heterogeneity Features in Functional and Morphologic Components of Non-Small Cell Lung Cancer Tumors: A Repeatability Analysis in a Prospective Multicenter Cohort

被引:132
|
作者
Desseroit, Marie-Charlotte [1 ,2 ]
Tixier, Florent [2 ,3 ]
Weber, Wolfgang A. [4 ]
Siegel, Barry A. [5 ,6 ]
Le Rest, Catherine Cheze [2 ,3 ]
Visvikis, Dimitris [1 ]
Hatt, Mathieu [1 ]
机构
[1] Univ Brest, Lab Med Informat Proc, INSERM UMR 1101, IBSAM, Brest, France
[2] Univ Poitiers, Sch Med, Poitiers, France
[3] CHU Miletrie, Nucl Med, Poitiers, France
[4] Mem Sloan Kettering Canc Ctr, 1275 York Ave, New York, NY 10021 USA
[5] Washington Univ, Sch Med, Mallinckrodt Inst Radiol, St Louis, MO USA
[6] Washington Univ, Sch Med, Siteman Canc Ctr, St Louis, MO USA
关键词
PET/CT; texture analysis; radiomics; repeatability; F-18-FDG PET; FDG-PET; TEXTURE FEATURES; RESPONSE PREDICTION; RADIOMICS FEATURES; ESOPHAGEAL CANCER; TEST-RETEST; REPRODUCIBILITY; IMAGES; CT;
D O I
10.2967/jnumed.116.180919
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
The main purpose of this study was to assess the reliability of shape and heterogeneity features in both the PET and the low-dose CT components of PET/CT. A secondary objective was to investigate the impact of image quantization. Methods: A Health Insurance Portability and Accountability Act-compliant secondary analysis of deidentified prospectively acquired PET/CT test-retest datasets of 74 patients from multicenter Merck and American College of Radiology Imaging Network trials was performed. Metabolically active volumes were automatically delineated on PET with a fuzzy locally adaptive bayesian algorithm. Software was used to semiautomatically delineate the anatomic volumes on the low-dose CT component. Two quantizationmethods were considered: a quantization into a set number of bins (quantization B) and an alternative quantization with bins of fixed width (quantization W). Four shape descriptors, 10 first-order metrics, and 26 textural features were evaluated. Bland-Altman analysis was used to quantify repeatability. Features were subsequently categorized as very reliable, reliable, moderately reliable, or poorly reliable with respect to the corresponding volume variability. Results: Repeatability was highly variable among features. Numerous metrics were identified as poorly or moderately reliable. Others were reliable or very reliable in both modalities and in all categories (shape and first-, second-, and third-order metrics). Image quantization played a major role in feature repeatability. Features were more reliable in PET with quantization B, whereas quantization W showed better results in CT. Conclusion: The test-retest repeatability of shape and heterogeneity features in PET and low-dose CT varied greatly among metrics. The level of repeatability also depended strongly on the quantization step, with different optimal choices for each modality. The repeatability of PET and low-dose CT features should be carefully considered when selecting metrics to build multiparametric models.
引用
收藏
页码:406 / 411
页数:6
相关论文
共 50 条
  • [1] Repeatability of 18F-FDG PET/CT in Advanced Non-Small Cell Lung Cancer: Prospective Assessment in 2 Multicenter Trials
    Weber, Wolfgang A.
    Gatsonis, Constantine A.
    Mozley, P. David
    Hanna, Lucy G.
    Shields, Anthony F.
    Aberle, Denise R.
    Govindan, Ramaswamy
    Torigian, Drew A.
    Karp, Joel S.
    Yu, Jian Q.
    Subramaniam, Rathan M.
    Halvorsen, Robert A.
    Siegel, Barry A.
    JOURNAL OF NUCLEAR MEDICINE, 2015, 56 (08) : 1137 - 1143
  • [2] Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation
    van Velden, Floris H. P.
    Kramer, Gerbrand M.
    Frings, Virginie
    Nissen, Ida A.
    Mulder, Emma R.
    de Langen, Adrianus J.
    Hoekstra, Otto S.
    Smit, Egbert F.
    Boellaard, Ronald
    MOLECULAR IMAGING AND BIOLOGY, 2016, 18 (05) : 788 - 795
  • [3] Preoperative staging of non-small cell lung cancer: prospective comparison of PET/MR and PET/CT
    Lee, Sang Min
    Goo, Jin Mo
    Park, Chang Min
    Yoon, Soon Ho
    Paeng, Jin Chul
    Cheon, Gi Jeong
    Kim, Young Tae
    Park, Young Sik
    EUROPEAN RADIOLOGY, 2016, 26 (11) : 3850 - 3857
  • [4] Repeatability of texture features derived from magnetic resonance and computed tomography imaging and use in predictive models for non-small cell lung cancer outcome
    Mahon, R. N.
    Hugo, G. D.
    Weiss, E.
    PHYSICS IN MEDICINE AND BIOLOGY, 2019, 64 (14)
  • [5] FDG PET/CT as theranostic imaging in diagnosis of non-small cell lung cancer
    Kirienko, Margarita
    Gallivanone, Francesca
    Sollini, Martina
    Veronesi, Giulia
    Voulaz, Emanuele
    Antunovic, Lidjia
    Leonardi, Lorenzo
    Testanera, Giorgio
    Castiglioni, Isabella
    Chiti, Arturo
    FRONTIERS IN BIOSCIENCE-LANDMARK, 2017, 22 : 1713 - 1723
  • [6] Evaluation of Shape and Textural Features from CT as Prognostic Biomarkers in Non-small Cell Lung Cancer
    Bianconi, Francesco
    Fravolini, Mario Luca
    Bello-Cerezo, Raquel
    Minestrini, Matteo
    Scialpi, Michele
    Palumbo, Barbara
    ANTICANCER RESEARCH, 2018, 38 (04) : 2155 - 2160
  • [7] Preoperative staging of non-small cell lung cancer: prospective comparison of PET/MR and PET/CT
    Sang Min Lee
    Jin Mo Goo
    Chang Min Park
    Soon Ho Yoon
    Jin Chul Paeng
    Gi Jeong Cheon
    Young Tae Kim
    Young Sik Park
    European Radiology, 2016, 26 : 3850 - 3857
  • [8] Staging of Non-Small Cell Lung Cancer Using Integrated PET/CT
    Kligerman, Seth
    Digumarthy, Subba
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2009, 193 (05) : 1203 - 1211
  • [9] Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery
    Kirienko, Margarita
    Cozzi, Luca
    Antunovic, Lidija
    Lozza, Lisa
    Fogliata, Antonella
    Voulaz, Emanuele
    Rossi, Alexia
    Chiti, Arturo
    Sollini, Martina
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2018, 45 (02) : 207 - 217
  • [10] Texture Analysis on [18F]FDG PET/CT in Non-Small-Cell Lung Cancer: Correlations Between PET Features, CT Features, and Histological Types
    Bianconi, Francesco
    Palumbo, Isabella
    Fravolini, Mario Luca
    Chiari, Rita
    Minestrini, Matteo
    Brunese, Luca
    Palumbo, Barbara
    MOLECULAR IMAGING AND BIOLOGY, 2019, 21 (06) : 1200 - 1209