Development and evaluation of an open-source software package "cGITA" for quantifying tumor heterogeneity with molecular images

BioMed Research International

Volumn 2014, Issue , 2014, Pages

  Fang, Yu Hua Dean ^a,b   Lin, Chien Yu ^a,b   Shih, Meng Jung ^c   Wang, Hung Ming ^a,b   Ho, Tsung Ying ^a,b   Liao, Chun Ta ^a,b   Yen, Tzu Chen ^a,b  

^a CHANG GUNG UNIVERSITY   (Taiwan)

^b CHANG GUNG MEMORIAL HOSPITAL   (Taiwan)

^c INSTITUTE FOR INFORMATION INDUSTRY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CANCER PROGNOSIS; CANCER RADIOTHERAPY; CHANG GUNG IMAGE TEXTURE ANALYSIS; CLINICAL ARTICLE; COMPUTER INTERFACE; CONTROL SYSTEM; DIGITAL IMAGING AND COMMUNICATIONS IN MEDICINE; EVALUATION STUDY; HUMAN; IMAGE DISPLAY; IMAGE PROCESSING; IMAGING SOFTWARE; KRUSKAL WALLIS TEST; MOUTH CANCER; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; ADULT; ALGORITHM; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; FEMALE; INTERNET; MALE; MIDDLE AGED; MOLECULAR IMAGING; MOUTH NEOPLASMS; POSITRON EMISSION TOMOGRAPHY; PROCEDURES; REPRODUCIBILITY;

ADULT; ALGORITHMS; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INTERNET; MALE; MIDDLE AGED; MOLECULAR IMAGING; MOUTH NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; POSITRON-EMISSION TOMOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE; SOFTWARE DESIGN; USER-COMPUTER INTERFACE;

EID: 84897539994     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2014/248505     Document Type: Article

References (41)

1. Denison T. A., Bae Y. H., Tumor heterogeneity and its implication for drug delivery. Journal of Controlled Release 2012 164 187 191 2-s2.0-84860573413 10.1016/j.jconrel.2012.04.014
2. Longo D. L., Tumor heterogeneity and personalized medicine. The New England Journal of Medicine 2012 366 10 956 957 2-s2.0-84857820489 10.1056/NEJMe1200656
3. Shibata D., Heterogeneity and tumor history. Science 2012 336 6079 304 305 2-s2.0-84859949200 10.1126/science.1222361
4. Cook G. J., Yip C., Siddique M., Goh V., Chicklore S., Roy A., Marsden P., Ahmad S., Landau D., Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy? Journal of Nuclear Medicine 2013 54 19 26
5. Huang B., Chan T., Kwong D. L., Chan W. K., Khong P. L., Nasopharyngeal carcinoma: investigation of intratumoral heterogeneity with FDG PET/CT. American Journal of Roentgenology 2012 199 169 174
6. Kidd E. A., Grigsby P. W., Intratumoral metabolic heterogeneity of cervical cancer. Clinical Cancer Research 2008 14 16 5236 5241 2-s2.0-52649174273 10.1158/1078-0432.CCR-07-5252
7. Kumar V., Gu Y., Basu S., Berglund A., Eschrich S. A., Schabath M. B., Forster K., Aerts H. J., Dekker A., Fenstermacher D., Radiomics: the process and the challenges. Magnetic Resonance Imaging 2012 30 1234 1248
8. Lambin P., Rios-Velazquez E., Leijenaar R., Carvalho S., van Stiphout R. G. P. M., Granton P., Zegers C. M. L., Gillies R., Boellard R., Dekker A., Aerts H. J. W. L., Radiomics: extracting more information from medical images using advanced feature analysis. European Journal of Cancer 2012 48 4 441 446 2-s2.0-84857037061 10.1016/j.ejca.2011.11.036
9. Salamon J., Derlin T., Bannas P., Busch J. D., Herrmann J., Bockhorn M., Hagel C., Friedrich R. E., Adam G., Mautner V. F., Evaluation of intratumoural heterogeneity on (18)F-FDG PET/CT for characterization of peripheral nerve sheath tumours in neurofibromatosis type 1. European Journal of Nuclear Medicine and Molecular Imaging 2013 40 5 685 692
10. Tixier F., Cheze le Rest C., Hatt M., Albarghach N., Pradier O., Metges J.-P., Corcos L., Visvikis D., Intratumor heterogeneity characterized by textural features on baseline18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. Journal of Nuclear Medicine 2011 52 3 369 378 2-s2.0-79952788113 10.2967/jnumed.110.082404
11. Visvikis D., Hatt M., Tixier F., Cheze le Rest C., The age of reason for FDG PET image-derived indices. European Journal of Nuclear Medicine and Molecular Imaging 2012 39 1670 1672
12. Watabe T., Tatsumi M., Watabe H., Isohashi K., Kato H., Yanagawa M., Shimosegawa E., Hatazawa J., Intratumoral heterogeneity of F-18 FDG uptake differentiates between gastrointestinal stromal tumors and abdominal malignant lymphomas on PET/CT. Annals of Nuclear Medicine 2012 26 222 227 2-s2.0-83655182815 10.1007/s12149-011-0562-3
13. Chicklore S., Goh V., Siddique M., Roy A., Marsden P. K., Cook G. J., Quantifying tumour heterogeneity in (18)F-FDG PET/CT imaging by texture analysis. European Journal of Nuclear Medicine and Molecular Imaging 2013 40 133 140
14. Eichelberg M., Riesmeier J., Wilkens T., Hewett A. J., Barth A., Jensch P., Ten years of medical imaging standardization and prototypical implementation: the DICOM standard and the OFFIS DICOM Toolkit (DCMTK). Medical Imaging: PACS and Imaging Informatics February 2004 International Society for Optics and Photonics 57 68 Proceedings of SPIE 2-s2.0-12144283973 10.1117/12.534853
15. He D.-C., Wang L., Texture features based on texture spectrum. Pattern Recognition 1991 24 5 391 399 2-s2.0-0025792757 10.1016/0031-3203(91)90052-7
16. Horng M.-H., Sun Y.-N., Lin X.-Z., Texture feature coding method for classification of liver sonography. Computerized Medical Imaging and Graphics 2002 26 1 33 42 2-s2.0-0037005657 10.1016/S0895-6111(01)00029-5 (Pubitemid 33081099)
17. Haralick R. M., Shanmugam K., Dinstein I., Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics 1973 3 6 610 621 2-s2.0-0015680481
18. Sun Y., Lu J., Yahagi T., Texture classification for liver tissues from ultrasonic B-scan images using testified PNN. IEICE Transactions on Information and Systems 2006 89 8 2420 2428 2-s2.0-33747863794 10.1093/ietisy/e89-d.8.2420 (Pubitemid 44286352)
19. Loh H.-H., Leu J.-G., Luo R. C., The analysis of natural textures using run length features. IEEE Transactions on Industrial Electronics and Control Instrumentation 1988 35 2 323 328 2-s2.0-0024016411
20. Amadasun M., King R., Textural features corresponding to textural properties. IEEE Transactions on Systems, Man and Cybernetics 1989 19 5 1264 1273 2-s2.0-0024738619 10.1109/21.44046 (Pubitemid 20642913)
21. Thibault G., Fertil B., Navarro C., Pereira S., Cau P., Levy N., Sequeira J., Mari J. L., Texture indexes and gray level size zone matrix: application to cell nuclei classification. pp. 140-145, Pattern Recognition and Information Processing (PRIP), Minsk, Belarus, 2009
22. Sun C., Wee W. G., Neighboring gray level dependence matrix for texture classification. Computer Vision, Graphics and Image Processing 1983 23 3 341 352 2-s2.0-0020974699 (Pubitemid 14449742)
23. Wahl R. L., Jacene H., Kasamon Y., Lodge M. A., From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors. Journal of Nuclear Medicine 2009 50 1 122S 150S 2-s2.0-66149139452 10.2967/jnumed.108. 057307
24. Kemp B. J., Kim C., Williams J. J., Ganin A., Lowe V. J., NEMA NU 2-2001 performance measurements of an LYSO-based PET/CT system in 2D and 3D acquisition modes. Journal of Nuclear Medicine 2006 47 12 1960 1967 2-s2.0-34247204476 (Pubitemid 47544983)
25. Chung M. K., Jeong H.-S., Sang G. P., Jeon Y. J., Son Y.-I., Joon Y. C., Seung H. H., Park K., Ahn M.-J., Yong C. A., Kim H.-J., Ko Y.-H., Baek C.-H., Metabolic tumor volume of [18F]-fluorodeoxyglucose positron emission tomography/computed tomography predicts short-term outcome to radiotherapy with or without chemotherapy in pharyngeal cancer. Clinical Cancer Research 2009 15 18 5861 5868 2-s2.0-70349466802 10.1158/1078-0432.CCR-08-3290
26. Kruskal W. H., Wallis W. A., Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association 1952 47 583 621
27. Dong X., Xing L., Wu P., Fu Z., Wan H., Li D., Yin Y., Sun X., Yu J., 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. Nuclear Medicine Communications 2013 34 40 46
28. Blouin S., Moreau M. F., Baslé M. F., Chappard D., Relations between radiograph texture analysis and microcomputed tomography in two rat models of bone metastases. Cells Tissues Organs 2006 182 3-4 182 192 2-s2.0-33747428363 10.1159/000093967 (Pubitemid 44253221)
29. Dominietto M., Lehmann S., Keist R., Rudin M., Pattern analysis accounts for heterogeneity observed in MRI studies of tumor angiogenesis. Magnetic Resonance in Medicine 2013 70 5 1481 1490
30. Risse F., Pesic J., Young S., Olsson L. E., A texture analysis approach to quantify ventilation changes in hyperpolarised3He MRI of the rat lung in an asthma model. NMR in Biomedicine 2012 25 1 131 141 2-s2.0-84855888225 10.1002/nbm.1725
31. Barajas R. F. Jr., Hodgson J. G., Chang J. S., Vandenberg S. R., Yeh R.-F., Parsa A. T., McDermott M. W., Berger M. S., Dillon W. P., Cha S., Glioblastoma multiforme regional genetic and cellular expression patterns: influence on anatomic and physiologic MR imaging. Radiology 2010 254 2 564 576 2-s2.0-77449124033 10.1148/radiol.09090663
32. Muzic R. F. Jr., Cornelius S., COMKAT: compartment model kinetic analysis tool. Journal of Nuclear Medicine 2001 42 4 636 645 2-s2.0-0035047852 (Pubitemid 32298286)
33. Deasy J. O., Blanco A. I., Clark V. H., CERR: a computational environment for radiotherapy research. Medical Physics 2003 30 5 979 985 2-s2.0-0037572347 10.1118/1.1568978 (Pubitemid 36578702)
34. Friston K. J., Ashburner J. T., Kiebel S. J., Nichols T. E., Penny W. D., Statistical Parametric Mapping: The Analysis of Functional Brain Images 2011 New York, NY, USA Academic Press
35. Eary J. F., O'Sullivan F., O'Sullivan J., Conrad E. U., Spatial heterogeneity in sarcoma 18F-FDG uptake as a predictor of patient outcome. Journal of Nuclear Medicine 2008 49 12 1973 1979 2-s2.0-57149101735 10.2967/jnumed.108.053397
36. El Naqa I., Grigsby P. W., Apte A., Kidd E., Donnelly E., Khullar D., Chaudhari S., Yang D., Schmitt M., Laforest R., Thorstad W. L., Deasy J. O., Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recognition 2009 42 6 1162 1171 2-s2.0-59149105325 10.1016/j.patcog.2008.08.011
37. Vaidya M., Creach K. M., Frye J., Dehdashti F., Bradley J. D., El Naqa I., Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer. Radiotherapy and Oncology 2012 102 2 239 245 2-s2.0-84857636637 10.1016/j.radonc.2011.10.014
38. Jakoby B. W., Bercier Y., Conti M., Casey M. E., Bendriem B., Townsend D. W., Physical and clinical performance of the mCT time-of-flight PET/CT scanner. Physics in Medicine and Biology 2011 56 8 2375 2389 2-s2.0-79953683986 10.1088/0031-9155/56/8/004
39. Kruggel F., Paul J. S., Gertz H.-J., Texture-based segmentation of diffuse lesions of the brain's white matter. NeuroImage 2008 39 3 987 996 2-s2.0-37849010264 10.1016/j.neuroimage.2007.09.058
40. Yu H., Caldwell C., Mah K., Poon I., Balogh J., MacKenzie R., Khaouam N., Tirona R., Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images. International Journal of Radiation Oncology Biology Physics 2009 75 2 618 625 2-s2.0-69549111175 10.1016/j.ijrobp.2009.04.043
41. Joseph S., Balakrishnan K., Local binary patterns, haar wavelet features and haralick texture features for mammogram image classification using artificial neural networks. Communications in Computer and Information Science 2011 198 107 114 2-s2.0-79960308160 10.1007/978-3-642-22555-0-12