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- Belkic, D, et al.
(author)
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Proof-of-the-Concept Study on Mathematically Optimized Magnetic Resonance Spectroscopy for Breast Cancer Diagnostics
- 2015
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In: Technology in cancer research & treatment. - : SAGE Publications. - 1533-0338 .- 1533-0346. ; 14:3, s. 277-297
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Journal article (peer-reviewed)abstract
- Magnetic resonance (MR)-based modalities aid breast cancer detection without exposure to ionizing radiation. Magnetic resonance imaging is very sensitive but costly and insufficiently specific. Molecular imaging through magnetic resonance spectroscopy (MRS) can provide information about key metabolites. Here, the measured/encoded time signals cannot be interpreted directly, necessitating mathematics for mapping to the more manageable frequency domain. Conventional applications of MRS are hampered by data analysis via the fast Fourier transform (FFT) and postprocessing by fitting techniques. Most in vivo MRS studies on breast cancer rely upon estimations of total choline (tCHO). These have yielded only incremental improvements in diagnostic accuracy. In vitro studies reveal richer metabolic information for identifying breast cancer, particularly in closely overlapping components of tCHO. Among these are phosphocholine (PC), a marker of malignant transformation of the breast. The FFT cannot assess these congested spectral components. This can be done by the fast Padé transform (FPT), a high-resolution, quantification-equipped method, which we presently apply to noisy MRS time signals consistent with those encoded in breast cancer. The FPT unequivocally and robustly extracted the concentrations of all physical metabolites, including PC. In sharp contrast, the FFT produced a rough envelope spectrum with a few distorted peaks and key metabolites absent altogether. As such, the FFT has poor resolution for these typical MRS time signals from breast cancer. Hence, based on Fourier-estimated envelope spectra, tCHO estimates are unreliable. Using even truncated time signals, the FPT clearly distinguishes noise from true metabolites whose concentrations are accurately extracted. The high resolution of the FPT translates directly into shortened examination time of the patient. These capabilities strongly suggest that by applying the FPT to time signals encoded in vivo from the breast, MRS will, at last, fulfill its potential to become a clinically reliable, cost-effective method for breast cancer detection, including screening/surveillance.
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- Belkic, D, et al.
(author)
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Strategic steps for advanced molecular imaging with magnetic resonance-based diagnostic modalities
- 2015
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In: Technology in cancer research & treatment. - : SAGE Publications. - 1533-0338 .- 1533-0346. ; 14:1, s. 119-142
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Journal article (peer-reviewed)abstract
- With the rapidly-expanding sophistication in our understanding of cancer cell biology, molecular imaging offers a critical bridge to oncology. Molecular imaging through magnetic resonance spectroscopy (MRS) can provide information about many metabolites at the same time. Since MRS entails no ionizing radiation, repeated monitoring, including screening can be performed. However, MRS via the fast Fourier transform (FFT) has poor resolution and signal-to-noise ratio (SNR). Moreover, subjective and non-unique (ambiguous) fittings of FFT spectra cannot provide reliable quantification of clinical usefulness. In sharp contrast, objective and unique (unambiguous) signal processing by the fast Padé transform (FPT) can increase resolution and retrieve the true quantitative metabolic information. To illustrate, we apply the FPT to in vitro MRS data as encoded from malignant ovarian cyst fluid and perform detailed analysis. This problem area is particularly in need of timely diagnostics by more advanced modalities, such as high-resolution MRS, since conventional methods usually detect ovarian cancers at late stages with poor prognosis, whereas at an early stage the prognosis is excellent. The reliability and robustness of the FPT is assessed for time signals contaminated with varying noise levels. In the presence of higher background noise, all physical metabolites were unequivocally identified and their concentrations precisely extracted, using small fractions of the total signal length. Via the “signal-noise separation” concept alongside the “stability test”, all non-physical information was binned, such that fully denoised spectra were generated. These results imply that a reformulation of data acquisition is needed, as guided by the FPT in MRS, since a small number of short transient time signals can provide high resolution and good SNR. This would enhance the diagnostic accuracy of MRS and shorten examination times, thereby improving efficiency and cost-effectiveness of this high throughput cancer diagnostic modality. Such advantages could be particularly important for more effective ovarian cancer detection, as well as more broadly for improved diagnostics and treatment within oncology.
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