Hybrid method for the detection of pulmonary nodules using positron emission tomography/computed tomography: A preliminary study

International Journal of Computer Assisted Radiology and Surgery

Volumn 9, Issue 1, 2014, Pages 59-69

  Teramoto, Atsushi ^a   Fujita, Hiroshi ^b   Takahashi, Katsuaki ^c   Yamamuro, Osamu ^c   Tamaki, Tsuneo ^c   Nishio, Masami ^d   Kobayashi, Toshiki ^d  

^a FUJITA HEALTH UNIVERSITY   (Japan)

^b GIFU UNIVERSITY   (Japan)

^c East Nagoya Imaging Diagnosis Center   (Japan)

^d Nagoya Radiological Diagnosis Center   (Japan)

Author keywords

Computer aided detection (CAD); CT; PET; Pulmonary nodule

Indexed keywords

FLUORODEOXYGLUCOSE F 18;

ALGORITHM; ARTICLE; CANCER SCREENING; CLASSIFIER; COMPUTER ASSISTED EMISSION TOMOGRAPHY; FALSE POSITIVE RESULT; HUMAN; LUNG NODULE; MAJOR CLINICAL STUDY; NODULE DIAMETER; ONCOLOGICAL PARAMETERS; PET-CT SCANNER; PRIORITY JOURNAL; SENSITIVITY ANALYSIS; SUPPORT VECTOR MACHINE;

DIAGNOSIS, DIFFERENTIAL; HUMANS; LUNG NEOPLASMS; MULTIMODAL IMAGING; POSITRON-EMISSION TOMOGRAPHY; REPRODUCIBILITY OF RESULTS; ROC CURVE; SOLITARY PULMONARY NODULE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84895065936     PISSN: 18616410     EISSN: 18616429     Source Type: Journal    
DOI: 10.1007/s11548-013-0910-y     Document Type: Article

References (35)

1. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM (2008) GLOBOCAN 2008 v2.0, cancer incidence and mortality worldwide: IARC cancerBase no 10. http://globocan.iarc.fr
2. Bartjan H, Cornelia S, Hester AG, Pim AJ, Bram G et al (2010) Screening for lung cancer with digital chest radiography: sensitivity and number of secondary work-up CT examinations. Radiology 255(2):629-637
3. Sone S, Takashima S, Li F, Yang Z, Honda T et al (1998) Mass screening for lung cancer with mobile spiral computed tomography scanner. Lancet 351:1242-1245
4. National lung screening trial research team (2011) The national lung screening trial: overview and study design. Radiology 258(1):243-253
5. Ide M, Suzuki Y (2005) Is whole-body FDG-PET valuable for health screening? Eur J Nucl Med Mol Imaging 32(3):339-341
6. Lee JW, Kang KW, Paeng JC, Lee SM, Jang SJ et al (2009) Cancer screening using 18F-FDG PET/CT in Korean asymptomatic volunteers: a preliminary report. Ann Nucl Med 23(7):685-691
7. Wever W, Meylaerts L, Ceuninck L, Stroobants S, Verschakelen JA (2007) Additional value of integrated PET-CT in the detection and characterization of lung metastases: correlation with CT alone and PET alone. Eur Radiol 17:467-473
8. Niki N, Kawata Y, Kubo M (2001) A CAD system for lung cancer based on CT image. Int Congr Ser 1230:631-638
9. Con Lee Y, Hara T, Fujita H, Itoh S, Ishigaki T (2001) Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique. IEEE Trans Med Imaging 20(7):595-604
10. Suzuki K, Armato SG III, Li F, Sone S, Doi K (2003) Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT. Med Phys 30(7):1602-1617
11. Paik DS, Beaulieu CF, Rubin GD, Acar B, Jeffrey RB et al (2004) Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT. IEEE Trans Med Imaging 23(6):661-675
12. McNitt-Gray MF (2004) Lung nodules and beyond: approaches, challenges and opportunities in thoracic CAD. Int Congr Ser 1268:896-901
13. Con Way TW, Hadjiiski LM, Sahiner B, Chan HP, Cascade PN et al (2006) Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours. Med Phys 33(7):2323-2337
14. Li Q (2007) Recent progress in computer-aided diagnosis of lung nodules on thin-section CT. Comput Med Imaging Graph 31(4-5):248-257
15. Li Q, Li F, Doi K (2008) Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier. Acad Radiol 15(2):165-175
16. Messay T, Hardie R, Rogers S (2010) A new computationally efficient CAD system for pulmonary nodule detection in CT imagery. Med Image Anal 14(3):390-406
17. Teramoto A, Fujita H (2013) Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter. Int J CARS 8(2):182-205
18. Guan H, Kubota T, Huang X, Zhou XS, Turk M (2006) Automatic hot spot detection and segmentation in whole body FDG-PET images. In: Proceedings of IEEE international conference on, image processing, pp 85-88
19. Montgomery DW, Amira A, Zaidi H (2007) Fully automated segmentation of oncological PET volumes using a combined multiscale and statistical model. Med Phys 34(2):722-736
20. Hara T, Kobayashi T, Kawai K, Zhou X, Ito S et al (2008) Automated scoring system of standard uptake value for torso FDG-PET. In: Proceedings of SPIE medical imaging 2008: computer-aided diagnosis, vol 6915, pp 691534-1-691534-4
21. Cui Y, Zhao B, Akhurst TJ, Yan J, Schwartz LH et al (2008) CT-guided, automated detection of lung tumors on PET images. In: Proceedings of SPIE medical imaging 2008: computer-aided diagnosis, vol 6915, pp 69152N-1-69152N-6
22. Ballangan C, Wang X, Eberl S, Fulham M, Feng D (2009) Automated detection and delineation of lung tumors in PET-CT volumes using a lung atlas and iterative mean-SUV threshold. In: Proceedings of SPIE medical imaging 2009: computer-aided diagnosis, vol 7259, pp 72593F-1-72593F-8
23. Teramoto A, Fujita H, Tomita Y, Takahashi K, Yamamuro O et al (2011) Hybrid CAD scheme for lung nodule detection in PET/CT images. In: Proceedings of SPIE medical imaging 2011: computer-aided diagnosis, vol 7963, pp 796335-1-796335-6
24. Teramoto A, Fujita H, Tomita Y, Takahashi K, Yamamuro O et al (2012) Pulmonary nodule detection in PET/CT images: improved approach using combined nodule detection and hybrid FP reduction. In: Proceedings of SPIE medical imaging 2012: computer-aided diagnosis, vol 8315, pp 83152V-1-83152V-6
25. Armato SG III, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR et al (2011) The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys 38(2):915-931
26. Kubota K, Matsuzawa T, Fujiwara T, Ito M, Hatazawa J et al (1990) Differential diagnosis of lung tumor with positron emission tomography: a prospective study. J Nucl Med 31(12):1927-1933
27. Duhaylongsod FG, Lowe VJ, Patz EF, Vaughn AL, Coleman RE et al (1995) Detection of primary and recurrent lung cancer by means of F-18 fluorodeoxyglucose positron emission tomography. J Thorac Cardiovasc Surg 110(1):130-139
28. Pauwels EK, Ribeiro MJ, Stoot JH, McCready VR, Bourguignon M et al (1998) FDG accumulation and tumor biology. Nucl Med Biol 25(4):317-322
29. Keyes JW (1995) SUV: standard uptake or silly useless value? J Nucl Med 36(10):1836-1839
30. Lowe VJ, Hoffman JM, DeLong DM, Patz EF, Coleman RE (1994) Semiquantitative and visual analysis of FDG-PET images in pulmonary abnormalities. J Nucl Med 35(11):1771-1776
31. Cohade C, Osman M, Marshall LN, Wahl RN (2003) PET-CT: accuracy of PET and CT spatial registration of lung lesions. Eur J Nucl Med Mol Imaging 30(5):721-726
32. Cristianini N, Shawe-Taylor J (2000) An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge
33. Chang CC, Lin CJ, LIBSVM: A library for support vector machines. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm/
34. Yamada N, Kusumoto M, Maeshima A, Suzuki K, Matsuno Y (2007) Correlation of the solid part on high-resolution computed tomography with pathological scar in small lung adenocarcinomas. Jpn J Clin Oncol 37(12):913-917
35. Nie Y, Li Q, Li F, Pu Y, Appelbaum D et al (2006) Integrating PET and CT information to improve diagnostic accuracy for lung nodules: a semiautomatic computer-aided method. J Nucl Med 47(7):1075-1080