Dynamic properties of water in breast pathology depend on the histological compounds: distinguishing tissue malignancy by water diffusion coefficients

BMC Research Notes

Timur A Sibgatullin³  Farhat F Muhamadiev¹  Sufiya Z Safina²  Kamil K Sadikov²  Roman A Gubanov²  Rustem F Baikeev¹ 

[1] Department of Biochemistry, Kazan State Medical University, Butlerova St., 49, Kazan, Tatarstan, Russia;Kazan Oncological Dispensary, Baturina St., 7., Kazan, Tatarstan, Russia;Kazan Institute of Biochemistry and Biophysics of Russian Academy of Science, Kazan, Tatarstan, Russia

关键词: Non-linear regression analysis;    H₂O;    Morphology;    Self–diffusion coefficient;    NMR;    Breast cancer;   

Others  :  1092443
DOI  :  10.1186/1756-0500-7-887

 received in 2013-02-14, accepted in 2014-11-18,  发布年份 2014

【 摘 要 】

Background

The parameters that characterize the intricate water diffusion in tumors may also reveal their distinct pathology. Specifically, characterization of breast cancer could be aided by diffusion magnetic resonance.

The present in vitro study aimed to discover connections between the NMR biexponential diffusion parameters [fast diffusion phase (D_FDP ), slow diffusion phase (D_SDP ), and spin population of fast diffusion phase (P₁)] and the histological constituents of nonmalignant (control) and malignant human breast tissue. It also investigates whether the diffusion coefficients indicate tissue status.

Methods

Post-surgical specimens of control (mastopathy and peritumoral tissues) and malignant human breast tissue were placed in an NMR spectrometer and diffusion sequences were applied. The resulting decay curves were analyzed by a biexponential model, and slow and fast diffusion parameters as well as percentage signal were identified. The same samples were also histologically examined and their percentage composition of several tissue constituents were measured: parenchyma (P), stroma (St), adipose tissue (AT), vessels (V) , pericellular edema (PCE), and perivascular edema (PVE). Correlations between the biexponential model parameters and tissue types were evaluated for different specimens. The effects of tissue composition on the biexponential model parameters, and the effects of histological and model parameters on cancer probability, were determined by non-linear regression.

Results

Meaningful relationships were found among the in vitro data. The dynamic parameters of water in breast tissue are stipulated by the histological constituents of the tissues (P, St, AT, PCE, and V). High coefficients of determination (R²) were obtained in the non-linear regression analysis: D_FDP (R² = 0.92), D_SDP (R² = 0.81), and P₁(R² = 0.93).

In the cancer probability analysis, the informative value (R²) of the obtained equations of cancer probability in distinguishing tissue malignancy depended on the parameters input to the model. In order of increasing value, these equations were: cancer probability (P, St, AT, PCE, V) (R² = 0.66), cancer probability (D_FDP, D_SDP)(R² = 0.69), cancer probability (D_FDP, D_SDP, P₁) (R² = 0.85).

Conclusion

Histological tissue components are related to the diffusion biexponential model parameters. From these parameters, the relative probability of cancer in a given specimen can be determined with some certainty.

【 授权许可】

   
2014 Baikeev et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Mattea C, Qvist J, Halle B: Dynamics at the protein-water interface from 17O spin relaxation in deeply supercooled solutions. Biophys J 2008, 95:2951-2963.
• [2]Meiboom S: Nuclear magnetic resonance study of the proton transfer in water. J Chem Physiol 1961, 34:375-388.
• [3]Sehy JV, Ackerman JJ, Neil JJ: Apparent diffusion of water, ions and small molecules in the Xenopus oocyte is consistent with Brownian displacement. Magn Reson Med 2002, 48:42-51.
• [4]Stejskal EO, Tanner JE: Spin diffusion measurements:spin echoes in the presence of a time-dependent field gradient. J Chem Phys 1965, 42:288-292.
• [5]Callaghan PT: Pulsed field gradient nuclear magnetic resonance as probe of liquid state molecular organization. Aust J Phys 1984, 37:359-387.
• [6]Price WS: Pulsed field gradient NMR as a tool for studying translational diffusion. Part I. Basic theory. Concepts Magn Reson 1997, 9:299-336.
• [7]Kärger J: Zun Massbarkeit von Diffusionkoeffizienten in Zweiphase System mit Hilfe der Methode der Gepulsten Feldgradienten. Ann Phys 1969, 24:1-7. (DDR)
• [8]Lee JH, Springer CS: Effects of equilibrium exchange on diffusion-weighted NMR signals: the diffusigraphic “shutter-speed”. Magn Reson Med 2003, 49:450-458.
• [9]Price WS, Barzykin AV, Hayamizu K, Tachiya M: A model for diffusive transport through a spherical interface probed by pulsed-field gradient NMR. Biophys J 1998, 74:2259-2271.
• [10]Roth Y, Ocherashvilli A, Daniels D, Ruiz-Cabello J, Maier SE, Orenstein A, Mardor Y: Quantification of water compartmentation in cell suspensions by diffusion-weighted and T2 –weighted MRI. Magn Reson Imaging 2008, 26:88-102.
• [11]Novikov EG, van Dusschoten D, Van As H: Modeling of self-diffusion and relaxation time NMR in multi-compartment systems. J Magn Reson 1998, 135:522-528.
• [12]Sukstanskii AL, Yablonskiy DA, Ackerman JJ: Effects of permeable boundaries on the diffusion-attenuated MR signal: insights from a one-dimensional model. J Magn Reson 2004, 170:56-66.
• [13]Yablonskiy DA, Bretthorst GL, Aсkerman JJ: Statistical model for diffusion attenuated MR signal. Magn Reson Med 2003, 50:664-669.
• [14]van Gelderen P, de Vleeschouwer MH, DesPres D, Pekar J, Van Zijl PC, Moonen CT: Water diffusion and acute stroke. Magn Reson Med 1994, 31:154-163.
• [15]Niendorf T, Dijkhuizen RM, Norris DG, van Lookeren CM, Nicolay K: Biexponential diffusion attenuation in various states of brain tissue: implications for diffusion-weighted imaging. Magn Reson Med 1996, 36:847-857.
• [16]Mulkern RV, Gudbjartsson H, Westin CF, Zengingonul HP, Gartner W, Guttmann CR, Robertson RL, Kyriakos W, Schwartz R, Holtzman D, Jolesz FA, Maier SE: Multi-component apparent diffusion coefficients in human brain. NMR Biomed 1999, 12:51-62.
• [17]Clark CA, Le Bihan D: Water diffusion compartmentation and anisotropy at high b values in the human brain. Magn Reson Med 2000, 44:852-859.
• [18]Tamura T, Usui S, Murakami S, Arihiro K, Akiyama Y, Naito K, Akiyama M: Biexponential Signal Attenuation Analysis of Diffusion-weighted Imaging of Breast. Magn Reson Med Sci 2010, 9:195-207.
• [19]Guo Y, Cai YQ, Cai ZL, Gao YG, An NY, Ma L, Mahankali S, Gao JH: Differentiation of clinically benign and malignant breast lesions using diffusion–weighted imaging. J Magn Reson Imaging 2002, 16:172-178.
• [20]Boes JL, Hoff BA, Hylton N, Pickles MD, Turnbull LW, Schott AF, Rehemtulla A, Chamberlain R, Lemasson B, Chenevert TL, Galb NCJ, Meyer CR: Image registration for quantitative parametric response mapping of cancer treatment response. Transl Oncol 2014, 7:101-110.
• [21]Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C: Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol 2007, 17:2646-2655.
• [22]Tan SL, Rahmat K, Rozalli FI, Mohd-Shah MN, Aziz YF, Yip CH, Vijayananthan A, Ng KH: Differentiation between benign and malignant breast lesions using quantitative diffusion-weighted sequence on 3 T MRI. Clin Radiol 2014, 69:63-67.
• [23]Ramadugu SK, Chung YH, Xia J, Margulis CJ: When sugars get wet. A comprehensive study of the behavior of water on the surface of oligosaccharides. J Phys Chem B 2009, 113:11003-11015.
• [24]Partridge SC, Murthy RS, Ziadloo A, White SW, Allison KH, Lehman CD: Diffusion tensor magnetic resonance imaging of the normal breast. J Magn Reson Imaging 2010, 28:320-328.
• [25]Partridge SC, Ziadloo A, Murthy RS, White SW, Peacock S, Eby PR, DeMartini WB, Lehman CD: Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors. J Magn Reson Imaging 2010, 31:339-347.
• [26]Kuroki Y, Nasu K, Kuroki S, Murakami K, Hayashi T, Sekiguchi R, Nawano S: Diffusion – weighted imaging of breast cancer with the sensitivity encoding technique: analysis of the apparent diffusion coefficient value. Magn Reson Med Sci 2004, 3:79-85.
• [27]Boger W, Gruber S, Pinker K, Grabner G, Stadlbauer A, Weber M, Moser E, Helbich TH, Trattnig S: Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiol 2009, 253:341-351.
• [28]Sun Y, Mulkern RV, Schmidt K, Doshi S, Albert MS, Schmidt NO, Ziu M, Black P, Carrol R, Kieran MW: Quantification of water diffusion and relaxation times of human U87 tumors in a mouse model. NMR Biomed 2004, 17:399-404.
• [29]Tsushima Y, Takahashi-Taketomi A, Endo K: Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficients (ADC) on 1.5-T. J Magn Reson Imaging 2009, 30:249-255.
• [30]Peters NH, Vincken KL, van den Bosch MA, Luijten PR, Mali WP, Bartels LW: Quantitative diffusion weighted imaging for differentiation of benign and malignant breast lesions: the influence of the choice of b-values. J Magn Reson Imaging 2010, 31:1100-1105.
• [31]Baron P, Dorrius MD, Kappert P, Oudkerk M, Sijens PE: Diffusion-weighted imaging of normal fibroglandular breast tissue: influence of microperfusion and fat suppression technique on the apparent diffusion coefficient. NMR Biomed 2010, 23:399-405.
• [32]Tanner JE, Stejskal EO: Restricted self-diffusion of protons in colloidal systems by the pulsed-gradient, spin-echo method. J Chem Phys 1968, 49:1768-1777.
• [33]Bell EL, Garsia R: Fitting Multi-Component Exponential Decay Curves by Digital Computer. Brooks AFB, TX: USAF School of Aerospace Medicine AFSC; 1965:45.
• [34]Stephanov SB: Morphometrical scale of random step as a tool of accelerated measurement of elemental morphogenesis. Cytologiya (RU) 1974, 16:785-787.
• [35]Mendenhall W, Sincich TL: A Second Course in Statistics: Regression Analysis. 5th edition. Upper Saddle River, NJ: Prentice Hall; 1996:899.
• [36]Gubanov RA, Safin KR, Safina SZ, Baikeev RF: Informative evaluation of tumor markers in breast cancer. Creative surgery and oncology 2011, 4:59-66.
• [37]Yoshikawa MI, Ohsumi S, Sugata S, Kataoka M, Takashima S, Kikuchi K, Mochizuki T: Comparison of breast cancer detection by diffusion-weighted magnetic resonance imaging and mammography. Radiat Med 2007, 25:218-223.
• [38]Wang L, Wang D, Fei X, Ruan M, Chai W, Xu L, Li X: A rim-enhanced mass with central cystic changes on MR imaging: how to distinguish breast cancer from inflammatory breast diseases? Plos ONE 2014, 5:e90355.
• [39]McLaughlin RL, Newitt DC, Wilmes LJ, Jones EF, Wisner DJ, Kornak J, Proctor E, Joe BN, Hylton NM: High resolution in vivo characterization of apparent diffusion coefficient at the tumor-stromal boundary of breast carcinomas: a pilot study to assess treatment response using proximity-dependent diffusion weighted imaging. J Magn Reson Imaging 2014, 39:1308-1313.
• [40]Mcdonald ES, Schopp JG, Peacock S, DeMartini WD, Raybar H, Lehman CD, Partridge SC: Duffusion-weighted MRI: association between characteristics and apparent diffusion coefficients of normal breast fibroglandular tissue at 3T. Am J Roentgenol 2014, 202:W496-W502.
• [41]Cai H, Peng Y, Ou C, Chen M, Li L: Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach. PLoS One 2014, 9:e87387.
• [42]Basser PJ, Mattiello J, LeBihan D: Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 1994, 103:247-254.
• [43]Iwasa H, Kubota K, Hamada N, Nogami M, Nishioka A: Early prediction of response to neoadjuvant chemotherapy in patients with breast cancer using diffusion weighted imaging and gray-scale ultrasonography. Oncol Rep 2014, 31:1555-1560.
• [44]Moschetta M, Telegrafo M, Rella L, Capolongo A, Stable Ianora AA, Angelelli G: MR evaluation of breast lesions obtained by diffusion-weighted imaging with background body signal suppression (DWIBS) and correlations with histological findings. Magn Reson Imaging 2014, 32:605-609.
• [45]Woodhams R, Kakita S, Hata H, Iwabuchi K, Umeoka S, Mountford CE, Hatabu H: Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings. Am J Roentgenol 2009, 193:260-266.
• [46]Sehy JV, Ackerman JJ, Neil JJ: Evidence that both fast and slow water ADC components arise from intracellular space. Magn Reson Med 2002, 48:765-770.
• [47]Pfeuffer J, Bröer S, Bröer A, Lechte M, Flögel U, Leibfritz D: Expression of aquaporins in Xenopus laevis oocytes and glial cells as detected by diffusion-weighted 1H NMR spectroscopy and photometric swelling assay. Biochim Biophys Acta 1998, 1448:27-36.
• [48]Flögel U, Pfeuffer J, Leibfritz D: Alterations in Glial Cell Metabolism during Oxygen Deprivation studied by Multinuclear NMR Spectroscopy. Vancouver: Proc., SMRM, 5th Scientific Meeting; 1997:1391.
• [49]Eyre DR: Collagen: molecular diversity in the body’s protein scaffold. Science 1980, 207:1315-1322.
• [50]Tanaka S, Avigad G, Eikenberry EF, Brodsky B: Isolation and partial characterization of collagen chains dimerized by sugar-derived cross-links. J Biol Chem 1998, 263:17650-17657.
• [51]Baikeev RF: Tissue Destruction and Blood Coagulation. Kazan: Remark; 1994:216.
• [52]Metzler DE: Biochemistry. The Chemical Reactions of Living Cells. 2nd edition. San Diego, CA: Harcourt/Academic Press; 2001:1973.
• [53]Zhao L, Sukstanskii AL, Kroenke CD, Song J, Piwnica-Worms D, Ackerman JJ, Neil JJ: Intracellular water specific MR of microbead-adherent cells: HeLa cell intracellular water diffusion. Magn Reson Med 2008, 59:79-84.
• [54]Zhao L, Kroenke CD, Song J, Piwnica-Worms D, Ackerman JJ, Neil JJ: Intracellular water-specific MR of microbead-adherent cells: the HeLa cell intracellular water exchange lifetime. NMR Biomed 2008, 21:159-164.
• [55]Nakagawa M, Miyati T, Hayashi T, Kanao S, Taniguchi M, Higashimura K, Toi M, Togashi K: Triexponential diffusion analysis in invasive ductal carcinoma and fibroadenoma. Nihon Hoshasen Gijutsu Gakkai Zasshi 2014, 70:199-205.
• [56]Tanner JE: Transient diffusion in a system partitioned by permeable barriers. Application to NMR measurements with a pulsed field gradient. J Chem Phys 1978, 69:1748-1754.
• [57]Latour LL, Mitra PP, Kleinberg RL, Sotak CH: Time dependent diffusion coefficients of fluids in porous media as a probe of surface to volume ratio. I. Magn Reson Series A 1993, 101:342-346.
• [58]Song YQ, Ryu S, Sen PN: Determining multiple length scales in rocks. Nature 2000, 406:178-181.
• [59]Cheng Y, Cory DG: Multiple scattering by NMR J. Am Chem Soc 1999, 121:7935-7936.
• [60]Mitra PP, Sen PN, Schwartz LM: Short-time behavior of the diffusion coefficient as a geometrical probe of porous media. Phys Rev 1993, 47:8565-8574.
• [61]Trampel R, Schiller J, Naji L, Stallmach F, Kärger J, Arnold K: Self-diffusion of polymers in cartilage as studied by pulsed field gradient NMR. Biophys Chem 2002, 97:251-260.
• [62]Lawrence L, Latour LL: Time dependent diffusion of water in a biological model system. Proc Natl Acad Sci 1994, 91:1229-1233.
• [63]Kärger I, Pfeifer H, Heink W: Principles and Application of Self-Diffusion Measurements by Nuclear Magnetic Resonance. In Advanced in Magnetic and Optical Reconance. Edited by Warren WS. San Diego, CA: Academic; 1988:1-89.
• [64]Le Bihan D, Turner R, Douek P, Patronas N: Diffusion MR imaging: clinical applications. Am J Roentgenol 1992, 159:591-599.
• [65]Sen PN: Diffusion and tissue microstructure. J Phys Condens Matter 2004, 16:5213-5220.
• [66]Ko ES, Han BK, Kim RB, Cho EY, Ahn S, Nam SJ, Ko EY, Shin JH, Hahn SY: Apparent diffusion coefficient in estrogen receptor-positive invasive ductal breast carcinoma: correlations with tumor-stroma ratio. Radiology 2014, 271:30-37.
• [67]Beaulieu C, Allen PS: Determinants of anisotropic water diffusion in nerves. Magn Reson Med 1994, 31:394-400.
• [68]Volke F, Eisenblätter S, Galle J, Klose G: Dynamic properties of water at phosphatidylcholine lipid-bilayer surfaces are seen by deuterium and pulsed field gradient proton NMR. Chem Phys Lipids 1994, 70:121-131.
• [69]Kimmich R, Noack F: Nuclear magnetic relaxation in solutions of proteins and polypeptides. Ber Bunsenges Phys Chem 1971, 75:269-272.
• [70]Kropman MF, Bakker HJ: Dynamics of water molecules in aqueous salvation shells. Science 2001, 291:2118-2120.
• [71]Weibel ER, Stäubli W, Gnägi HR, Hess FA: Correlated morphometric and biochemical studies on the liver cell. I. Morphometric model, stereologic methods, and normal morphometric data for rat liver. J Cell Biol 1969, 42:68-91.
• [72]Sehy JV, Ackerman JJ, Neil JJ: Water and lipid MRI of the Xenopus oocyte. Magn Res Med 2001, 46:900-906.
• [73]Geil B, Feiweier T, Pospiech E-M, Eisenblatter J, Fujara F, Winter R: Relating structure and translational dynamics in aqueous dispersions of monoolein. Chem and Phys Lipids 2000, 106:115-126.
• [74]Filippov A, Oradd G, Lindblom G: Influence of cholesterol and water content on phospholipid lateral diffusion in bilayers. Langmuir 2003, 19:6397-6400.
• [75]Fossel ET, Carr JM, McDonagh J: Detection of malignant tumors. Water-suppressed proton nuclear magnetic resonance spectroscopy of plasma. N Engl J Med 1986, 315:1369-1376.
• [76]Jagannathan NR, Singh M, Govindaraju V, Rangunathan P, Coshic O, Julka PK, Rath GK: Volume localized in vivo proton MR spectroscopy of breast carcinoma: variation of water-fat ratio in patients receiving chemotherapy. NMR Biomed 1998, 11:414-422.
• [77]Eyal E, Degani H: Model-based and model-free parametric analysis of breast dynamic-contrast-enchanced MRI. NMR Biomed 2009, 22:40-53.
• [78]Alexander-Williams J, Keighley MR: Assessing the problem, preparing the patient, and minimizing the risks in rectal cancer surgery. World J Surg 1982, 6:510-516.
• [79]Sinha S, Sinha U, Lucas-Quesada F, Debruhl N, Englander S, Schnall M: Perfusion and diffusion contributions to ADC: application to breast tumors in-vivo. Proc Intl Soc Mag Reson Med 2001, 9:2331-2331.
• [80]Griseri P, Pagès G: Control of pro-angiogenic cytokine mRNA half-life in cancer: the role of AU-rich elements and associated proteins. J Interferon Cytokine Res 2014, 34:242-254.
• [81]Westra C, Dialani V, Mehta TS, Eisenberg RL: Using T2-weighted sequences to more accurately characterize breast masses seen on MRI. Am J Roentgenol 2014, 202:W183-W190.
• [82]Partridge SC, Singer L, Sun R, Wilmes LJ, Klifa CS, Lehman CD, Hylton NM: Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements. Magn Reson Imaging 2011, 29:1215-1221.