Associations of radiomic data extracted from static and respiratory-gated CT scans with disease recurrence in lung cancer patients treated with SBRT

PLoS ONE

Volumn 12, Issue 1, 2017, Pages

  Huynh, Elizabeth ^a   Coroller, Thibaud P ^a   Narayan, Vivek ^a   Agrawal, Vishesh ^a   Romano, John ^a   Franco, Idalid ^a   Parmar, Chintan ^a   Hou, Ying ^a   Mak, Raymond H ^a   Aerts, Hugo J W L ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; AVERAGE INTENSITY PROJECTION; CANCER PROGNOSIS; CANCER RECURRENCE; CANCER STAGING; CLINICAL EFFECTIVENESS; COHORT ANALYSIS; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; DISTANT METASTASIS; FEMALE; HUMAN; IMAGE ANALYSIS; LUNG CANCER; MAJOR CLINICAL STUDY; MALE; NON SMALL CELL LUNG CANCER; OUTCOME ASSESSMENT; PREDICTIVE VALUE; RADIATION DOSE; RADIOLOGICAL PARAMETERS; RESPIRATORY GATED COMPUTED TOMOGRAPHY; STATIC FREE BREATHING; STEREOTACTIC BODY RADIATION THERAPY; BREATHING; CARCINOMA, NON-SMALL-CELL LUNG; DIAGNOSTIC IMAGING; FALSE POSITIVE RESULT; LUNG NEOPLASMS; METASTASIS; MIDDLE AGED; MULTIVARIATE ANALYSIS; PATHOLOGY; PERSONALIZED MEDICINE; PROCEDURES; PROGNOSIS; RADIOMETRY; RADIOSURGERY; REPRODUCIBILITY; TREATMENT OUTCOME; TUMOR RECURRENCE; VERY ELDERLY; X-RAY COMPUTED TOMOGRAPHY;

TUMOR MARKER;

AGED; AGED, 80 AND OVER; BIOMARKERS, TUMOR; CARCINOMA, NON-SMALL-CELL LUNG; FALSE POSITIVE REACTIONS; FEMALE; HUMANS; LUNG NEOPLASMS; MALE; MIDDLE AGED; MULTIVARIATE ANALYSIS; NEOPLASM METASTASIS; NEOPLASM RECURRENCE, LOCAL; PRECISION MEDICINE; PROGNOSIS; RADIOMETRY; RADIOSURGERY; REPRODUCIBILITY OF RESULTS; RESPIRATION; TOMOGRAPHY, X-RAY COMPUTED; TREATMENT OUTCOME;

EID: 85008178682     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0169172     Document Type: Article

References (47)

1. Jameson JL, Longo DL (2015) Precision medicine - personalized, problematic, and promising. N Engl J Med 372: 2229-2234. doi: 10.1056/NEJMsb1503104 PMID: 26014593
2. Lambin P, van Stiphout RG, Starmans MH, Rios-Velazquez E, Nalbantov G, et al. (2013) Predicting outcomes in radiation oncology-multifactorial decision support systems. Nat Rev Clin Oncol 10: 27-40. doi: 10.1038/nrclinonc.2012.196 PMID: 23165123
3. Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, et al. (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48: 441-446. doi: 10.1016/j.ejca.2011.11.036 PMID: 22257792
4. Kumar V, Gu Y, Basu S, Berglund A, Eschrich SA, et al. (2012) Radiomics: the process and the challenges. Magn Reson Imaging 30: 1234-1248. doi: 10.1016/j.mri.2012.06.010 PMID: 22898692
5. Coroller TP, Grossmann P, Hou Y, Rios Velazquez E, Leijenaar RT, et al. (2015) CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma. Radiother Oncol 114: 345-350. doi: 10.1016/j.radonc.2015.02.015 PMID: 25746350
6. Yip SS, Coroller TP, Sanford NN, Huynh E, Mamon H, et al. (2016) Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction. Phys Med Biol 61: 906-922. doi: 10.1088/0031-9155/61/2/906 PMID: 26738433
7. Wu J, Aguilera T, Shultz D, Gudur M, Rubin DL, et al. (2016) Early-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis. Radiology: 151829.
8. Li H, Zhu Y, Burnside ES, Drukker K, Hoadley KA, et al. (2016) MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays. Radiology: 152110.
9. Huynh E, Coroller TP, Narayan V, Agrawal V, Hou Y, et al. (2016) CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer. Radiother Oncol.
10. Nie K, Shi L, Chen Q, Hu X, Jabbour S, et al. (2016) Rectal Cancer: Assessment of Neoadjuvant Chemo-Radiation Outcome Based on Radiomics of Multi-Parametric MRI. Clin Cancer Res.
11. Huang YQ, Liang CH, He L, Tian J, Liang CS, et al. (2016) Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer. J Clin Oncol 34: 2157-2164. doi: 10.1200/JCO.2015.65.9128 PMID: 27138577
12. Coroller TP, Agrawal V, Narayan V, Hou Y, Grossmann P, et al. (2016) Radiomic phenotype features predict pathological response in non-small cell lung cancer. Radiother Oncol.
13. Parmar CG P.; Rietveld D.; Rietbergen M. M.; Lambin P.; Aerts H. J. (2015) Radiomic Machine Learning Classifiers for Prognostic Biomarkers of Head & Neck Cancer. Front Oncol 5.
14. Cunliffe A, Armato SG 3rd, Castillo R, Pham N, Guerrero T, et al. (2015) Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development. Int J Radiat Oncol Biol Phys 91: 1048-1056. doi: 10.1016/j.ijrobp.2014.11.030 PMID: 25670540
15. Parmar C, Leijenaar RT, Grossmann P, Rios Velazquez E, Bussink J, et al. (2015) Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer. Sci Rep 5: 11044. doi: 10.1038/srep11044 PMID: 26251068
16. Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, et al. (2014) Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5: 4006. doi: 10.1038/ncomms5006 PMID: 24892406
17. Segal E, Sirlin CB, Ooi C, Adler AS, Gollub J, et al. (2007) Decoding global gene expression programs in liver cancer by noninvasive imaging. Nat Biotechnol 25: 675-680. doi: 10.1038/nbt1306 PMID: 17515910
18. Zinn PO, Mahajan B, Sathyan P, Singh SK, Majumder S, et al. (2011) Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme. PLoS One 6: e25451. doi: 10.1371/journal.pone.0025451 PMID: 21998659
19. Baumann P, Nyman J, Hoyer M, Wennberg B, Gagliardi G, et al. (2009) Outcome in a prospective phase II trial of medically inoperable stage I non-small-cell lung cancer patients treated with stereotactic body radiotherapy. J Clin Oncol 27: 3290-3296. doi: 10.1200/JCO.2008.21.5681 PMID: 19414667
20. Chi A, Liao Z, Nguyen NP, Xu J, Stea B, et al. (2010) Systemic review of the patterns of failure following stereotactic body radiation therapy in early-stage non-small-cell lung cancer: clinical implications. Radiother Oncol 94: 1-11. doi: 10.1016/j.radonc.2009.12.008 PMID: 20074823
21. Mak RH, Hermann G, Lewis JH, Aerts HJ, Baldini EH, et al. (2015) Outcomes by tumor histology and KRAS mutation status after lung stereotactic body radiation therapy for early-stage non-small-cell lung cancer. Clin Lung Cancer 16: 24-32. doi: 10.1016/j.cllc.2014.09.005 PMID: 25450872
22. Fakiris AJ, McGarry RC, Yiannoutsos CT, Papiez L, Williams M, et al. (2009) Stereotactic body radiation therapy for early-stage non-small-cell lung carcinoma: four-year results of a prospective phase II study. Int J Radiat Oncol Biol Phys 75: 677-682. doi: 10.1016/j.ijrobp.2008.11.042 PMID: 19251380
23. Timmerman R, Paulus R, Galvin J, Michalski J, Straube W, et al. (2010) Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA 303: 1070-1076. doi: 10.1001/jama.2010.261 PMID: 20233825
24. Onishi H, Araki T, Shirato H, Nagata Y, Hiraoka M, et al. (2004) Stereotactic hypofractionated high-dose irradiation for stage I nonsmall cell lung carcinoma: clinical outcomes in 245 subjects in a Japanese multiinstitutional study. Cancer 101: 1623-1631. doi: 10.1002/cncr.20539 PMID: 15378503
25. Grills IS, Mangona VS, Welsh R, Chmielewski G, McInerney E, et al. (2010) Outcomes after stereotactic lung radiotherapy or wedge resection for stage I non-small-cell lung cancer. J Clin Oncol 28: 928-935. doi: 10.1200/JCO.2009.25.0928 PMID: 20065181
26. Fave X, Cook M, Frederick A, Zhang L, Yang J, et al. (2015) Preliminary investigation into sources of uncertainty in quantitative imaging features. Comput Med Imaging Graph 44: 54-61. doi: 10.1016/j.compmedimag.2015.04.006 PMID: 26004695
27. Zhao B, Tan Y, Tsai WY, Qi J, Xie C, et al. (2016) Reproducibility of radiomics for deciphering tumor phenotype with imaging. Sci Rep 6: 23428. doi: 10.1038/srep23428 PMID: 27009765
28. Mackin D, Fave X, Zhang L, Fried D, Yang J, et al. (2015) Measuring Computed Tomography Scanner Variability of Radiomics Features. Invest Radiol 50: 757-765. doi: 10.1097/RLI.0000000000000180 PMID: 26115366
29. van Velden FH, Kramer GM, Frings V, Nissen IA, Mulder ER, et al. (2016) Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation. Mol Imaging Biol.
30. Cheng NM, Fang YH, Tsan DL, Hsu CH, Yen TC (2016) Respiration-Averaged CT for Attenuation Correction of PET Images - Impact on PET Texture Features in Non-Small Cell Lung Cancer Patients. PLoS One 11: e0150509. doi: 10.1371/journal.pone.0150509 PMID: 26930211
31. Chen Y, Guo W, Lu Y, Zou B (2008) Dose-individualized stereotactic body radiotherapy for T1-3N0 non-small cell lung cancer: long-term results and efficacy of adjuvant chemotherapy. Radiother Oncol 88: 351-358. doi: 10.1016/j.radonc.2008.07.013 PMID: 18722684
32. Pieper S. HM, Kikinis R. (2004) 3D SLICER. Proceedings of the 1st IEEE International Symposium on Biomedical Imaging: From Nano to Macro 1: 632-635.
33. Team RC (2015) R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria.
34. Zhao B, James LP, Moskowitz CS, Guo P, Ginsberg MS, et al. (2009) Evaluating variability in tumor measurements from same-day repeat CT scans of patients with non-small cell lung cancer. Radiology 252: 263-272. doi: 10.1148/radiol.2522081593 PMID: 19561260
35. Gamer ML J.; Singh I.F.P. (2012) irr: Various Coefficients of Interrater Reliability and Agreement. R package version 0.84.
36. Husson FJ J.; Le S.; Mazet J. (2015) FactoMineR: Multivariate Exploratory Data Analysis and Data Mining. R package version 1.31.3.
37. Steck H, Krishnapuram B, Dehing-oberije C, Lambin P, Raykar VC. On ranking in survival analysis: Bounds on the concordance index; 2008. pp. 1209-1216.
38. Harrell FE, Lee KL, Mark DB (1996) Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statistics in medicine 15: 361-387.
39. Schroder MS, Culhane AC, Quackenbush J, Haibe-Kains B (2011) survcomp: an R/Bioconductor package for performance assessment and comparison of survival models. Bioinformatics 27: 3206-3208. doi: 10.1093/bioinformatics/btr511 PMID: 21903630
40. Benjamini YH Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B 57: 289-300.
41. Lo A, Chernoff H, Zheng T, Lo SH (2015) Why significant variables aren't automatically good predictors. Proc Natl Acad Sci U S A 112: 13892-13897. doi: 10.1073/pnas.1518285112 PMID: 26504198
42. Rietzel E, Pan T, Chen GT (2005) Four-dimensional computed tomography: image formation and clinical protocol. Med Phys 32: 874-889. doi: 10.1118/1.1869852 PMID: 15895570
43. Pan H, Simpson DR, Mell LK, Mundt AJ, Lawson JD (2011) A survey of stereotactic body radiotherapy use in the United States. Cancer 117: 4566-4572. doi: 10.1002/cncr.26067 PMID: 21412761
44. Crino L, Weder W, van Meerbeeck J, Felip E, Group EGW (2010) Early stage and locally advanced (non-metastatic) non-small-cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 21 Suppl 5: v103-115.
45. Solda F, Lodge M, Ashley S, Whitington A, Goldstraw P, et al. (2013) Stereotactic radiotherapy (SABR) for the treatment of primary non-small cell lung cancer; systematic review and comparison with a surgical cohort. Radiother Oncol 109: 1-7. doi: 10.1016/j.radonc.2013.09.006 PMID: 24128806
46. Christensen JD, Chiles C (2015) Low-dose computed tomographic screening for lung cancer. Clin Chest Med 36: 147-160, vii. doi: 10.1016/j.ccm.2015.02.002 PMID: 26024597
47. National Lung Screening Trial Research T, Church TR, Black WC, Aberle DR, Berg CD, et al. (2013) Results of initial low-dose computed tomographic screening for lung cancer. N Engl J Med 368: 1980-1991. doi: 10.1056/NEJMoa1209120 PMID: 23697514