In vivo magnetic resonance spectroscopy for ovarian cancer diagnostics: quantification by the fast Padé transform

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• 作者：Dževad Belkić ; Karen Belkić
• 关键词：Magnetic resonance spectroscopy ; Ovarian cancer diagnostics ; Mathematical optimization ; Fast Padé transform
• 刊名：Journal of Mathematical Chemistry
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：55
• 期：1
• 页码：349-405
• 全文大小：1232KB
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Physical Chemistry; Theoretical and Computational Chemistry; Math. Applications in Chemistry;
• 出版者：Springer International Publishing
• ISSN：1572-8897
• 卷排序：55

文摘

Early-stage ovarian cancer has an excellent prognosis, but due mainly to late detection, ovarian cancer remains a major cause of cancer deaths among women. In vivo magnetic resonance spectroscopy (MRS) would be an excellent candidate for early ovarian cancer detection, being non-invasive, surpassing anatomic imaging to identify metabolic features of cancer, and free of ionizing radiation. However, the present meta-analysis of 13 studies indicates that with conventional Fourier-based processing, in vivo MRS insufficiently distinguished 134 cancerous from 114 benign ovarian lesions. The fast Padé transform (FPT), an advanced signal processor with high-resolution and parametric (quantification-equipped) capabilities is best qualified for MRS time signals from the ovary, as demonstrated in our earlier proof-of-concept studies. We now apply the FPT to MRS time signals encoded in vivo on a 3 T scanner, echo time of 30 ms, from a borderline serous cystic ovarian tumor. The FPT-produced total shape spectrum was better resolved than with Fourier processing. Spectra averaging through the FPT generated a denoised total shape spectrum. Subsequent parametric analysis reconstructed dense component spectra in the “usual” mode: absorption and dispersion components mixed and “ersatz” mode: reconstructed phases set to zero, thus eliminating interference effects. Numerous metabolites, including potential cancer biomarkers, were identified and quantified by the FPT, including isoleucine, valine, lipids, lactate, alanine, lysine, N-acetyl aspartate, N-acetylneuraminic acid, glutamine, choline, phosphocholine, myoinositol. Many of these are difficult or impossible to detect with Fourier plus fitting techniques for in vivo MRS of the ovary. These Padé-generated results are promising, overcoming major barriers hindering MRS from becoming a key method for non-invasively assessing ovarian lesions.