Pulmonary nodules: Sensitivity of maximum intensity projection versus that of volume rendering of 3D mul tidetector CT data

Radiology

Volumn 243, Issue 2, 2007, Pages 561-569

  Peloschek, Philipp ^a   Sailer, Johannes ^a   Weber, Michael ^a   Herold, Christian J ^a   Prokop, Mathias ^b   Schaefer Prokop, Cornelia ^c  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

^b Utrecht Medical Centet ^*  (Netherlands)

^c UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

IOPROMIDE;

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; CLINICAL TRIAL; COMPUTED TOMOGRAPHY SCANNER; COMPUTER PROGRAM; CONTRAST ENHANCEMENT; FEMALE; HUMAN; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; LUNG NODULE; MALE; MULTIDETECTOR COMPUTED TOMOGRAPHY; PRIORITY JOURNAL; STATISTICAL ANALYSIS; THREE DIMENSIONAL IMAGING;

ALGORITHMS; COIN LESION, PULMONARY; FEMALE; HUMANS; IMAGING, THREE-DIMENSIONAL; LUNG NEOPLASMS; MALE; MIDDLE AGED; OBSERVER VARIATION; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 34247468808     PISSN: 00338419     EISSN: None     Source Type: Journal    
DOI: 10.1148/radiol.2432052052     Document Type: Article

References (27)

1. Naidich DP. Volumetric scans change perceptions in thoracic CT. Diagn Imaging (San Franc) 1993;15:70-74.
2. Seltzer SE, Judy PF, Adams DF, et al. Spiral CT of the chest: comparison of cine and film-based viewing. Radiology 1995;197:73-78.
3. Napel S, Rubin GD, Jeffrey RB Jr. STS-MIP: a new reconstruction technique for CT of the chest. J Comput Assist Tomogr 1993;17:832-838.
4. Diederich S, Lentschig MG, Winter F, Roos N, Bongartz G. Detection of pulmonary nodules with overlapping vs non-overlapping image reconstruction at spiral CT. Eur Radiol 1999;9:281-286.
5. Rubin GD, Lyo JK, Paik DS, et al. Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection. Radiology 2005;234:274-283.
6. Ravenel JG, McAdams HP, Remy-Jardin M, Remy J. Multidimensional imaging of the thorax: practical applications. J Thorac Imaging 2001;16:269-281.
7. Remy-Jardin M, Remy J, Giraud F, Marquette CH. Pulmonary nodules: detection with thick-section spiral CT versus conventional CT. Radiology 1993;187:513-520.
8. Schaefer-Prokop C, Prokop M. New imaging techniques in the treatment guidelines for lung cancer. Eur Respir J Suppl 2002;35:71s-83s.
9. Wormanns D, Ludwig K, Beyer F, Heindel W, Diederich S. Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT. Eur Radiol 2005;15:14-22.
10. Abe H, Ishida T, Shiraishi J, et al. Effect of temporal subtraction images on radiologists' detection of lung cancer on CT: results of the observer performance study with use of film computed tomography images. Acad Radiol 2004;11:1337-1343.
11. Armato SG 3rd, Roy AS, MacMahon H, et al. Evaluation of automated lung nodule detection on low-dose computed tomography scans from a lung cancer screening program. Acad Radiol 2005;12:337-346.
12. Kozuka T, Johkoh T, Hamada S, et al. Detection of pulmonary metastases with multi-detector row CT scans of 5-mm nominal section thickness: autopsy lung study. Radiology 2003;226:231-234.
13. Gruden JF, Ouanounou S, Tigges S, Norris SD, Klausner TS. Incremental benefit of maximum-intensity-projection images on observer detection of small pulmonary nodules revealed by multideteetor CT. AJR Am J Roentgenol 2002;179:149-157.
14. Lawler LP, Wood SA, Pannu HK, Fishman EK. Computer-assisted detection of pulmonary nodules: preliminary observations using a prototype system with multidetector-row CT data sets. J Digit Imaging 2003;16:251-261.
15. Marten K, Grillhosl A, Seyfarth T, Obenauer S, Rummeny EJ, Engelke C. Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings. Eur Radiol 2005;15:203-212.
16. Kim JS, Kim JH, Cho G, Bae KT. Automated detection of pulmonary nodules on CT images: effect of section thickness and reconstruction interval - initial results. Radiology 2005;236:295-299.
17. Bae KT, Kim JS, Na YH, Kim KG, Kim JH. Pulmonary nodules: automated detection on CT images with morphologic matching algorithm - preliminary results. Radiology 2005;236:286-293.
18. Coakley FV, Cohen MD, Johnson MS, Gonin R, Hanna MP. Maximum intensity projection images in the detection of simulated pulmonary nodules by spiral CT. Br J Radiol 1998;71:135-140.
19. Diederich S, Lentschig MG, Overbeck TR, Wormanns D, Heindel W. Detection of pulmonary nodules at spiral CT: comparison of maximum intensity projection sliding slabs and single-image reporting. Eur Radiol 2001;11:1345-1350.
20. Eibel R, Turk TR, Kulinna C, Herrmann K, Reiser MF. Multidetector-row CT of the lungs: multiplanar reconstructions and maximum intensity projections for the detection of pulmonary nodules [in German]. Rofo 2001;173:815-821.
21. Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Earlbaum Associates, 1988.
22. Mori K, Sasagawa M, Moriyama N. Detection of nodular lesions in the lung using helical computed tomography: comparison of fast couch speed technique with conventional computed tomography. Jpn J Clin Oncol 1994;24:252-257.
23. Croisille P, Souto M, Cova M, et al. Pulmonary nodules: improved detection with vascular segmentation and extraction with spiral CT - work in progress. Radiology 1995;197:397-401.
24. Fischbach F, Knollmann F, Griesshaber V, Freund T, Akkol E, Felix R. Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness. Eur Radiol 2003;13:2378-2383.
25. Kuszyk BS, Heath DG, Johnson PT, Eng J, Fishman EK. CT angiography with volume rendering for quantifying vascular stenoses: in vitro validation of accuracy. AJR Am J Roentgenol 1999;173:449-455.
26. Brown MS, Goldin JG, Rogers S, et al. Computer-aided lung nodule detection in CT: results of large-scale observer test. Acad Radiol 2005;12:681-686.
27. Armato SG 3rd, Li F, Giger ML, MacMahon H, Sone S, Doi K. Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program. Radiology 2002;225:685-692.