Independent component analysis for the examination of dynamic contrast-enhanced breast magnetic resonance imaging data: Preliminary study

Investigative Radiology

Volumn 37, Issue 12, 2002, Pages 647-654

  Yoo, Seung Schik ^a,b   Choi, Byung Gil ^b   Han, Ji Youn ^c   Kim, Hak Hee ^b  

^a HARVARD MEDICAL SCHOOL   (United States)

^b The Catholic University of Korea College of Medicine   (South Korea)

^c National Cancer Center   (South Korea)

Author keywords

Blind source separation; Breast MRI; Contrast enhancement; Dynamic MRI; Independent component analysis

Indexed keywords

ADULT; ALGORITHM; ARTICLE; BENIGN TUMOR; BREAST LESION; CLINICAL ARTICLE; CONTRAST ENHANCEMENT; CONTROLLED STUDY; CORRELATION ANALYSIS; DIAGNOSTIC PROCEDURE; DIAGNOSTIC VALUE; FEASIBILITY STUDY; FEMALE; HUMAN; MALIGNANT NEOPLASTIC DISEASE; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; RADIODIAGNOSIS;

EID: 0036895597     PISSN: 00209996     EISSN: None     Source Type: Journal    
DOI: 10.1097/00004424-200212000-00002     Document Type: Article

References (36)

1. Liu PF, Debatin JF, Caduff RF, et al. Improved diagnostic accuracy in dynamic contrast enhanced MRI of the breast by combined quantitative and qualitative analysis. Br J Radiol 1998;71:501-509.
2. Kuhl CK, Schild HH. Dynamic image interpretation of MRI of the breast. J Magn Reson Imaging 2000;12:965-974.
3. Tofts PS, Berkowitz B, Schnall MD. Quantitative analysis of dynamic Gd-DTPA enhancement in breast tumors using a permeability model. Magn Reson Med 1995;33:564-568.
4. Kelcz F, Santyr GE, Cron GO, et al. Application of a quantitative model to differentiate benign from malignant breast lesions detected by dynamic, gadolinium-enhanced MRI. J Magn Reson Imaging 1996;6:743-752.
5. Mussurakis S, Buckley DL, Horsman A. Dynamic MR imaging of invasive breast cancer: Correlation with tumor grade and other histological factors. Br J Radiol 1997;70:446-451.
6. Snow RD, Dyess DL, Harpen MD, et al. Dynamic magnetic resonance imaging in evaluating suspicious breast lesions: Correlation with pathologic findings. South Med J 1998;91:527-532.
7. Helbich TH, Roberts TPL, Gossmann A, et al. Quantitative gadopentetate-enhanced MRI of breast tumors: Testing of different analytic methods. Magn Reson Med 2000;44:915-924.
8. den Boer JA, Hoenderop RK, Smink J, et al. Pharmacokinefic analysis of Gd-DTPA enhancement in dynamic three-dimensional MRI of breast lesions. J Magn Reson Imaging 1997;7:702-715.
9. Knopp MV, Weiss E, Sinn HP, et al. Pathophysiologic basis of contrast enhancement in breast tumors. J Magn Reson Imaging 1999;10:260-266.
10. Khatri VP, Stuppino JJ, Espinosa MH, et al. Improved accuracy in differentiating malignant from benign mammographic abnormalities: A simple, improved magnetic resonance imaging method. Cancer 2001;92:471-478.
11. Aref M, Brechbiel M, Wiener EC. Identifying tumor vascular permeability heterogeneity with magnetic resonance imaging contrast agents. Invest Radiol 2002;37:178-192.
12. Heywang-Kobrunner SH, Schreer I, Dershaw DD. Magnetic resonance imaging (MRI). In: Heywang-Kobrunner SH, ed. Diagnostic Breast Imaging: Mammography, Sonography, Magnetic Resonance Imaging, and Interventional Procedures. 1st Ed. New York, NY: Thieme; 1997: 92-100.
13. Mussurakis S, Gibbs P, Horsman A. Peripheral enhancement and spatial contrast uptake heterogeneity of primary breast tumors: Quantitative assessment with dynamic MRI. J Comput Assist Tomogr 1998;22:35-46.
14. Sinha S, Lucas-Quesada FA, DeBruhl ND, et al. Multifeature analysis of Gd-enhanced MR images of breast lesions. J Magn Reson Imaging 1997;7:1016-1026.
15. Liney GP, Gibbs P, Hayes C, et al. Dynamic contrast-enhanced MRI in the differentiation of breast tumors: User-defined versus semiautomated region-of- interest analysis. J Magn Reson Imaging 1999;10:945-949.
16. Gilles R, Meunier M, Lucidarme O, et al. Clustered breast microcalcifications: Evaluation by dynamic contrast-enhanced subtraction MRI. J Comput Assist Tomogr 1996;20:9-14.
17. Kuhl CK, Bieling HB, Gieseke J, et al. Healthy premenopausal breast parenchyma in dynamic contrast-enhanced MR imaging of the breast: Normal contrast medium enhancement and cyclical-phase dependency. Radiology 1997;203:137-144.
18. Boetes C, Barentsz JO, Mus RD, et al. MR characterization of suspicious breast lesions with a gadolinium-enhanced TurboFLASH subtraction technique. Radiology 1994;193:777-781.
19. Furman-Haran E, Grobgeld D, Kelcz F, et al. Critical role of spatial resolution in dynamic contrast-enhanced breast MRI. J Magn Reson Imaging 2001;13:862-867.
20. Herault J, Juten C. Blind separation of sources, part, an adaptive algorithm based on neuromimetic architecture. Signal Proc 1991; 24:1-10.
21. Burel G. Blind separation of sources: A nonlinear algorithm. Neural Networks 1992;5:937-947.
22. Bell AJ, Sejnowski TJ. An information-maximization approach to blind separation and blind deconvolution. Neural Comput 1995;7:1129-1159.
23. Common P. Independent component analysis - A new concept? Signal Proc 1989;36:287-314.
24. Biswal BB, Ulmer JL. Blind source separation of multiple signal sources of fMRI data sets using independent component analysis. J Comput Assist Tomogr 1999;23:265-271.
25. McKeown MJ, Makeig S, Brown GG, et al. Analysis of fMRI data by blind separation into independent spatial components. Hum Brain Mapp 1998;6:160-188.
26. Makeig S, Westerfield M, Jung T-P, et al. Functionally independent components of the late positive event-related potential during visual spatial attention. J Neurosci 1999;19:2665-2680.
27. Jung TP, Humphries C, Lee TW, et al. Removing electroencephalographic artifacts by blind source separation. Psychophysiology 2000;37:163-178.
28. Lee TW, Girolami M, Sejnowski TJ. Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural Comput 1999;11:417-441.
29. Schnall MD, Ikeda DM. Lesion diagnosis working group report. J Magn Reson Imaging 1999;10:982-990.
30. James D, Clymer BD, Schmalbrock P. Texture detection of simulated microcalcification susceptibility effects in magnetic resonance imaging of breasts. J Magn Reson Imaging 2001;13:876-881.
31. Lucht RE, Knopp MV, Brix G. Classification of signal-time curves from dynamic MR mammography by neural networks. Magn Reson Imaging 2001;19:51-57.
32. Tien RD. Fat-suppression MR. imaging in neuroradiology: Techniques and clinical application. AJR 1992;158:369-379.
33. Kerslake RW, Carleton PJ, Fox JN, et al. Dynamic gradient-echo and fat-suppressed spin-echo contrast-enhanced MRI of the breast. Clin Radiol 1995;50:440-454.
34. Degani H, Gusis V, Weinstein D, et al. Mapping pathophysiological features of breast tumors by MRI at high spatial resolution. Nat Med 1997;3:780-782.
35. Bishop JE, Santyr GE, Kelcz F, et al. Limitations of the keyhole technique for quantitative dynamic contrast-enhanced breast MRI. J Magn Reson Imaging 1997;7:716-723.
36. Pruessmann KP, Weiger M, Scheidegger MB, et al. SENSE: Sensitivity encoding for fast MRI. Magn Reson Med 1999;42:952-962.