Heterogeneity in [18F]fluorodeoxyglucose positron emission tomography/computed tomography of non-small cell lung carcinoma and its relationship to metabolic parameters and pathologic staging

Molecular Imaging

Volumn 13, Issue 9, 2014, Pages

  Van Gómez López, Ober ^a,b,c   García Vicente, Ana María ^a,b,c   Honguero Martínez, Antonio Francisco ^a,b,c   Soriano Castrejón, Ángel María ^a,b,c   Jiménez Londoño, German Andrés ^a,b,c   Udias, José Manuel ^a,b,c   Atance, Pablo León ^a,b,c  

^a HOSPITAL GENERAL UNIVERSITARIO DE CIUDAD REAL   (Spain)

^b HOSPITAL GENERAL UNIVERSITARIO DE ALBACETE   (Spain)

^c UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL ORGANS; ENTROPY; METABOLISM; PATHOLOGY; POSITRONS; TUMORS;

CORRELATION ANALYSIS; FLUORODEOXYGLUCOSE-POSITRON EMISSION TOMOGRAPHIES; METABOLIC PARAMETERS; METABOLIC TUMOR VOLUMES; NON-SMALL CELL LUNG CARCINOMATA; RETROSPECTIVE ANALYSIS; STANDARDIZED UPTAKE VALUES; TEXTURAL PARAMETERS;

POSITRON EMISSION TOMOGRAPHY;

FLUORODEOXYGLUCOSE F 18; RADIOPHARMACEUTICAL AGENT;

AGED; CANCER STAGING; COMPUTER ASSISTED TOMOGRAPHY; DIAGNOSTIC USE; FEMALE; HUMAN; LUNG TUMOR; MALE; MIDDLE AGED; MULTIMODAL IMAGING; NON SMALL CELL LUNG CANCER; PATHOLOGY; POSITRON EMISSION TOMOGRAPHY; PROCEDURES; RETROSPECTIVE STUDY; ADENOCARCINOMA; CARCINOMA, NON-SMALL-CELL LUNG; CARCINOMA, SQUAMOUS CELL; LUNG NEOPLASMS; SCINTISCANNING;

AGED; CARCINOMA, NON-SMALL-CELL LUNG; FEMALE; FLUORODEOXYGLUCOSE F18; HUMANS; LUNG NEOPLASMS; MALE; MIDDLE AGED; MULTIMODAL IMAGING; NEOPLASM STAGING; POSITRON-EMISSION TOMOGRAPHY; RADIOPHARMACEUTICALS; RETROSPECTIVE STUDIES; TOMOGRAPHY, X-RAY COMPUTED; ADENOCARCINOMA; CARCINOMA, SQUAMOUS CELL;

EID: 84911365015     PISSN: 15353508     EISSN: None     Source Type: Journal    
DOI: 10.2310/7290.2014.00032     Document Type: Article

References (47)

1. Molina JR, Yang P, Cassivi SD, et al. Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship. Mayo Clin Proc 2008;83:584-94, doi:10.1016/S0025-6196(11)60735-0.
2. American Cancer Society. Cancer facts and figures 2012. Atlanta: American Cancer Society; 2012.
3. Wao H, Mhaskar R, Kumar A, et al. Survival of patients with non-small cell lung cancer without treatment: a systematic review and meta-analysis. Syst Rev 2013;4:2-10.
4. Garcia Garzon JR, Rodriguez A, Cabrera A. Positron emission tomography/computed tomography with 18F-FDG. Rev Esp Med Nucl 2009;28:85-9, doi:10.1016/S0212-6982(09)70706-2.
5. Soussan M, Chouahnia K, Maisonobe JA, et al. Prognostic implications of volume-based measurements on FDG PET/CT in stage III non-small-cell lung cancer after induction chemotherapy. Eur J Nucl Med Mol Imaging 2013;40:668-76, doi:10.1007/s00259-012-2321-7.
6. Kim K, Kim SJ, Kim IJ, et al. Prognostic value of volumetric parameters measured by F-18 FDG PET/CT in surgically resected non-small-cell lung cancer. Nucl Med Commun 2012;33:613-20, doi:10.1097/MNM.0b013e328351d4f5.
7. van de Wiele C, Kruse V, Smeets P, et al. Predictive and prognostic value of metabolic tumour volume and total lesion glycolysis in solid tumours. Eur J Nucl Med Mol Imaging 2013;40:290-301, doi:10.1007/s00259-012-2280-z.
8. Zaidi H, El Naqa I. PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques. Eur J Nucl Med Mol Imaging 2010;37:2165-87, doi:10.1007/s00259-010-1423-3.
9. Belhassen S, Zaidi H. A novel fuzzy C-means algorithm for unsupervised heterogeneous tumor quantification in PET. Med Phys 2010;37:1309-24, doi:10.1118/1.3301610.
10. Denison TA, Bae YH. Tumor heterogeneity and its implication for drug delivery. J Control Release 2012;164:187-91, doi:10.1016/j.jconrel.2012.04.014.
11. Li JY, Zhang Y, Zhang WH, et al. Effects of differential distribution of microvessel density, possibly regulated by miR-374a, on breast cancer prognosis. Asian Pac J Cancer Prev 2013;14:1715-20, doi:10.7314/APJCP.2013.14.3.1715.
12. Saunders NA, Simpson F, Thompson EW, et al. Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives. EMBO Mol Med 2012;4:675-84, doi:10.1002/emmm.201101131.
13. Wyss MT, Hofer S, Hefti M, et al. Spatial heterogeneity of low-grade gliomas at the capillary level: a PET study on tumor blood flow and amino acid uptake. J Nucl Med 2007;48:1047-52, doi:10.2967/jnumed.106.038489.
14. Jakobsen JN, Santoni-Rugiu E, Ravn J, et al. Intratumour variation of biomarker expression by immunohistochemistry in resectable non-small cell lung cancer. Eur J Cancer 2013;49:2494-503, doi:10.1016/j.ejca.2013.04.003.
15. Chicklore S, Goh V, Siddique M, et al. Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis. Eur J Nucl Med Mol Imaging 2013;40:133-40, doi:10.1007/s00259-012-2247-0.
16. Lambin P, Rios-Velazquez E, LeijenaarR, et al. Radiomics: extracting more information frommedical images using advanced feature. Eur J Cancer 2012;48:441-6, doi:10.1016/j.ejca.2011.11.036.
17. Davnall F, Yip CS, Ljungqvist G, et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging 2012;3:573-89, doi:10.1007/s13244-012-0196-6.
18. Ganeshan B, Miles KA. Quantifying tumour heterogeneity with CT. Cancer Imaging 2013;13:140-9, doi:10.1102/1470-7330.2013.0015.
19. Kassner A, Thornhill RE. Texture analysis: a review of neurologic MR imaging applications. AJNR Am J Neuroradiol 2010;31:809-16, doi:10.3174/ajnr.A2061.
20. Castellano G, Bonilha L, Li LM, et al. Texture analysis of medical images. Clin Radiol 2004;59:1061-9, doi:10.1016/j.crad.2004.07.008.
21. Cook GJ, Yip C, Siddique M, et al. Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy? J Nucl Med 2013;54:19-26, doi:10.2967/jnumed.112.107375.
22. Ganeshan B, Panayiotou E, Burnand K, et al. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol 2012;22:796-802, doi:10.1007/s00330-011-2319-8.
23. Dong X, Xing L, Wu P, et al. Three-dimensional positron emission tomography image texture analysis of esophageal squamous cell carcinoma: relationship between tumor 18F-fluorodeoxyglucose uptake heterogeneity, maximum standardized uptake value, and tumor stage. Nucl Med Commun 2013;34:40-6, doi:10.1097/MNM.0b013e32835ae50c.
24. \Edge SB, Byrd DR, Compton CC, et al. Lung. In: Edge SB, editor. AJCC cancer staging manual. 7th ed. New York: Springer; 2010. p. 253-66.
25. Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 2012;30:1323-41, doi:10.1016/j.mri.2012.05.001.
26. Szczypiński PM, Strzelecki M, Materka A, et al. MaZda - a software package for image texture analysis. Comput Methods Programs Biomed 2009;94:66-76, doi:10.1016/j.cmpb.2008.08.005.
27. Tixier F, Rest CCL, Hatt M, et al. Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med 2011;52:369-78, doi:10.2967/jnumed.110.082404.
28. Dierckx RA, van de Wiele C. FDG uptake, a surrogate of tumour hypoxia? Eur J Nucl Med Mol Imaging 2008;35:1544-9, doi:10.1007/s00259-008-0758-5.
29. Christian N, Deheneffe S, Bol A, et al. Is (18)F-FDG a surrogate tracer to measure tumor hypoxia? Comparison with the hypoxic tracer (14)C-EF3 in animal tumor models. Radiother Oncol 2010;97:183-8, doi:10.1016/j.radonc.2010.02.020.
30. Ganeshan B, Goh V, Mandeville HC, et al. Non-small cell lung cancer: histopathologic correlates for texture parameters at CT. Radiology 2013;266:326-36, doi:10.1148/radiol.12112428.
31. 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma. Eur J Nucl Med Mol Imaging 2013;40:1662-71, doi:10.1007/s00259-013-2486-8.
32. Tixier F, Hatt M, Le Rest CC, et al. Reproducibility of tumor uptake heterogeneity characterization through textural feature analysis in 18F-FDG PET. J Nucl Med 2012;53:693-700, doi:10.2967/jnumed.111.099127.
33. Lucht R, Brix G, Lorenz WJ. Texture analysis of differently reconstructed PET images. Phys Med Biol 1996;41:2207-19, doi:10.1088/0031-9155/41/10/025.
34. Ng F, Kozarski R, Ganeshan B, et al. Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis? Eur J Radiol 2013;82:342-8, doi:10.1016/j.ejrad.2012.10.023.
35. Ganeshan B, Abaleke S, Young RC, et al. Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging 2010;10:137-43, doi:10.1102/1470-7330.2010.0021.
36. Hatt M, Cheze-le Rest C, van Baardwijk A, et al. Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation. J Nucl Med 2011;52:1690-7, doi:10.2967/jnumed.111.092767.
37. Vaidya M, Creach KM, Frye J, et al. Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer. Radiother Oncol 2012;102:239-45, doi:10.1016/j.radonc.2011.10.014.
38. Bagci U, Yao J,Miller-Jaster K, et al. Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images. PLoS One 2013;8:e57105, doi:10.1371/journal.pone.0057105.
39. van Velden FH, Cheebsumon P, Yaqub M, et al. Evaluation of a cumulative SUV-volume histogram method for parameterizing heterogeneous intratumoural FDG uptake in non-small cell lung cancer PET studies. Eur J Nucl Med Mol Imaging 2011;38:1636-47, doi:10.1007/s00259-011-1845-6.
40. Aquino SL, Halpern EF, Kuester LB, et al. FDG-PET and CT features of non-small cell lung cancer based on tumor type. Int J Mol Med 2007;19:495-9.
41. Zhu SH, Zhang Y, Yu YH, et al. FDG PET-CT in non-small cell lung cancer: relationship between primary tumor FDG uptake and extensional or metastatic potential. Asian Pac J Cancer Prev 2013;14:2925-9, doi:10.7314/APJCP.2013.14.5.2925.
42. Galavis PE, Hollensen C, Jallow N, et al. Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters. Acta Oncol 2010;49:1012-6, doi:10.3109/0284186X.2010.498437.
43. Sahiner I, Atasever T, Akdemir UO, et al. Relationship between primary lesion metabolic parameters and clinical stage in lung cancer. Rev Esp Med Nucl 2013;32:357-63.
44. Aydin F, Dertsiz L, Budak ES, et al. Measurements of tumor size using CT and PET compared to histopathological size in non-small cell lung cancer. Diagn Interv Radiol 2013;19:271-8.
45. Garcia Vicente AM, Soriano Castrejon AM, Talavera Rubio MP, et al. (18)F-FDG PET-CT respiratory gating in characterization of pulmonary lesions: approximation towards clinical indications. Ann Nucl Med 2010;24:207-14, doi:10.1007/s12149-010-0345-2.
46. Garcia Vicente AM, Soriano Castrejon A, Talavera Rubio P, et al. (18)F-FDG PET-CT and respiratory synchronization: effect in the detection and catalogation of pulmonary lesions. Rev Esp Med Nucl 2009;28:181-7, doi:10.1016/S0212-6982(09)00009-3.
47. Singh D, Miles K. Multiparametric PET/CT in oncology. Cancer Imaging 2012;12:336-44, doi:10.1102/1470-7330.2012.9007.