Possibilities for improved early breast cancer detection by Padé-optimized magnetic resonance spectroscopy

Israel Medical Association Journal

Volumn 13, Issue 4, 2011, Pages 236-243

  Belkić, Karen ^a,b,c   Belkić, Dževad ^a  

^a KAROLINSKA INSTITUTE   (Sweden)

^b CLAREMONT GRADUATE UNIVERSITY   (United States)

^c UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Breast cancer; Early detection; High risk; Magnetic resonance spectroscopy; Signal processing

Indexed keywords

GLYCEROPHOSPHORYLCHOLINE; LACTIC ACID; PHOSPHOETHANOLAMINE; PHOSPHORYLCHOLINE;

BREAST CANCER; BREAST FIBROADENOMA; CANCER DIAGNOSIS; CANCER SCREENING; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIFFERENTIAL DIAGNOSIS; DISEASE MARKER; EARLY CANCER; EARLY DIAGNOSIS; FALSE POSITIVE RESULT; HUMAN; IMAGE RECONSTRUCTION; IONIZING RADIATION; MOLECULAR IMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PADE OPTIMIZED NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; RADIATION EXPOSURE; REVIEW; RISK ASSESSMENT; SIGNAL NOISE RATIO;

BREAST NEOPLASMS; EARLY DIAGNOSIS; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MAGNETIC RESONANCE SPECTROSCOPY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 79957585121     PISSN: 15651088     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (40)

1. Boyle P, Leon ME, Maisonneuve P, Autier P. Cancer control in women. Update 2003. Int J Gynecol Obstet 2003; 83 (Suppl 1): 179-202.
2. Hampel H, Sweet K, Westman JA, Offit K, Eng C. Referral for cancer genetics consultation: a review and compilation of risk assessment criteria. J Med Genet 2004; 4: 81-91.
3. www.nbcc.org.au 2006.
4. Saslow D, Boetes C, Burke W, et al. American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography. CA Cancer J Clin 2007; 57: 75-89.
5. Fackenthal JD, Olopade OI. Breast cancer risk associated with BRCA1 and BRCA2 in diverse populations. Nature Rev Cancer 2007; 7: 937-48.
6. Calderon-Margalit R, Friedlander Y, Yanetz R, et al. Cancer risk after exposure to treatments for ovulation induction. Am J Epidemiol 2009; 169: 365-75.
7. Kloog I, Haim A, Stevens RG, Barchana M, Portnov BA. Light at night codistributes with incident breast but not lung cancer in the female population of Israel. Chronobiol Int 2009; 26: 108-25.
8. Shaham J, Gurvich R, Goral A, Czerniak A. The risk of breast cancer in relation to health habits and occupational exposures. Am J Ind Med 2006; 49: 1021-30.
9. Shema L, Ore L, Ben-Shachar M, Haj M, Linn S. The association between breastfeeding and breast cancer occurrence among Israeli Jewish women: a case control study. J Cancer Res Clin Oncol 2007; 133: 539-46.
10. Keinan-Boker L, Vin-Raviv N, Liphshitz I, Linn S, Barchana M. Cancer incidence in Israeli Jewish survivors of World War II. J Natl Cancer Inst 2009; 101: 1489-500.
11. Allweis TM, Nissan A, Spira RM, Sklair-Levy M, Freund HR, Peretz T. Screening mammography for early diagnosis of breast cancer: facts, controversies, and the implementation in Israel. Harefuah 2003; 142: 281-6, 317 (Hebrew).
12. Cohen M, Azaiza F. Developing and testing an instrument for identifying culturespecific barriers to breast cancer screening in Israeli Arab women. Acta Oncologica 2008; 47: 1570-7.
13. Belkić K. Current dilemmas and future perspectives for breast cancer screening with a focus upon optimization of magnetic resonance spectroscopic imaging by advances in signal processing. IMAJ Isr Med Assoc J 2004; 6: 610-18.
14. Armstrong K, Moye E, Williams S, Berlin J, Reynolds E. Screening mammography in women 40 to 49 years of age: a systematic review for the American College of Physicians. Ann Intern Med 2007; 146: 516-26.
15. Kuni H, Schmitz-Feuerhake I, Dieckmann H. Mammography screening-neglected aspects of radiation risks. Gesundheitswesen 2003; 65: 443-6.
16. Schrading S, Kuhl CK. Mammographic, US, and MR imaging phenotypes of familial breast cancer. Radiology 2008; 246: 58-70.
17. Houssami N, Wilson R. Should women at high risk of breast cancer have screening magnetic resonance imaging (MRI)? J Breast 2007; 16: 2-4.
18. Iglesias A, Arias M, Santiago P, Rodríguez M, Mañas J, Saborido C. Benign breast lesions that simulate malignancy: magnetic resonance imaging with radiologic-pathologic correlation. Curr Probl Diagn Radiol 2007; 36: 66-82.
19. Essink-Bot ML, Rijnsburger AJ, van Dooren S, de Koning HJ, Seynaeve C. Women's acceptance of MRI in breast cancer surveillance because of a familial or genetic predisposition. Breast 2006; 15: 673-6.
20. Robson M. Breast cancer surveillance in women with hereditary risk due to BRCA1 or BRCA2 mutations. Clin Breast Cancer 2004; 5: 260-8.
21. Katz-Brull R, Lavin PT, Lenkinski RE. Clinical utility of proton magnetic resonance spectroscopy in characterizing breast lesions. J Natl Cancer Inst 2002; 94: 1197-203.
22. Tse GM, Yeung DK, King AD, Cheung HS, Yang WT. In vivo proton magnetic resonance spectroscopy of breast lesions: an update. Breast Cancer Res Treat 2007; 104: 249-55.
23. Belkić DŽ, Belkić K. Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications. Boca Raton, FL: CRC Press Taylor & Francis Group, 2010.
24. Belkić Dž, Belkić K. Exact quantification of time signals from magnetic resonance spectroscopy by the fast Padé transform with applications to breast cancer diagnostics. J Math Chem 2009; 45: 790-818.
25. Gribbestad IS, Sitter B, Lundgren S, Krane J, Axelson D. Metabolite composition in breast tumors examined by proton nuclear magnetic resonance spectroscopy. Anticancer Res 1999; 19: 1737-46.
26. Belkić Dž. Exact analytical expressions for any Lorentzian spectrum in the fast Padé transform (FPT). J Comp Meth Sci Engin 2003; 3: 109-86.
27. Belkić DŽ. Quantum Mechanical Signal Processing and Spectral Analysis. Bristol: Institute of Physics Publishing, 2005.
28. Belkić Dž. Exact quantification of time signals in Padé-based magnetic resonance spectroscopy. Phys Med Biol 2006; 51: 2633-70.
29. Belkić DŽ. Machine accurate quantification in magnetic resonance spectroscopy. Nucl Instrum Methods Phys Res A 2007; 580: 1034-40.
30. Belkić Dž, Belkić K. Unequivocal resolution of multiplets in MR Spectra for prostate cancer diagnostics achieved by the fast Padé transform. J Math Chem 2009; 45: 819-58.
31. van der Veen JW, de Beer R, Luyten PR, et al. Accurate quantification of in vivo 31P NMR signals using the variable projection method and prior knowledge. Magn Reson Med 1988; 6: 92-8.
32. Vanhamme L, van den Boogaart A, van Haffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 1997; 29: 35-43.
33. Provencher SW. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med 1993; 30: 672-9.
34. Belkić Dž, Belkić K. Unequivocal disentangling genuine from spurious information in time signals: clinical relevance in cancer diagnostics through magnetic resonance spectroscopy. J Math Chem 2008; 44: 887-912.
35. Belkić Dž, Belkić K. Mathematical optimization of in vivo NMR chemistry through the fast Padé transform: Potential relevance for early breast cancer detection by magnetic resonance spectroscopy. J Math Chem 2006; 40: 85-103.
36. Aboagye EO, Bhujwalla ZM. Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Res 1999; 59: 80-4.
37. Katz-Brull R, Seger D, Rivenson-Segal D, et al. Metabolic markers of breast cancer. Enhanced choline metabolism and reduced choline-etherphospholipid synthesis. Cancer Res 2002; 62: 1966-70.
38. Glunde K, Jie C, Bhujwalla ZM. Molecular causes of the aberrant choline phospholipid metabolism in breast cancer. Cancer Res 2004; 64: 4270-6.
39. Sharma U, Mehta A, Seenu V, et al. Biochemical characterization of metastatic lymph nodes of breast cancer patients by in vitro 1H magnetic resonance spectroscopy: a pilot study. Magn Reson Imaging 2004; 22: 697-706.
40. Rivenzon-Segal D, Margalit R, Degani H. Glycolysis as a metabolic marker in orthotopic breast cancer, monitored by in vivo 13C MRS. Am J Physiol Endocrinol Metab 2002; 283: E623-30.