Screening of high-risk groups for breast and ovarian cancer in Europe: a focus on the Jewish population

2017

The fast Padé transform (FPT) is further optimized for encoded in vivo MRS time signals. This is achieved by a judicious combination of spectra averaging and time signal extrapolation. The motivation is in strengthening suppression of the over-sensitivity of signal processing to changes in model order K . Implementation is carried out in the FPT variant FPT (+) which, by numerically performed analytical continuation, converts divergent into convergent series. Convergence of reconstructions is monitored for a sequence of successive values of K . Comparison is made with the corresponding retrieval without spectra averaging and time signal extrapolation. Variances are dramatically reduced for the reconstructed parameters (complex frequencies and complex amplitudes) when spectra averaging and extrapolation are performed. Negligible variances imply convergence, which is accomplished herein using a single averaging procedure (no iterations). This has important implications in practice with encoded MRS data, providing remarkable efficiency, robustness and accuracy of Padé-based quantification. Algorithmically, spectra averaging and time signal extrapolation consist of four steps. First, the encoded time signal is used to compute total shape spectra (envelopes) for a sequence of model orders K , which is the number of resonances. Second, these envelopes are averaged (spectra averaging). All the spectra are computed at the same sweep frequencies whose number considerably exceeds the number of data points in the encoded time signal. Third, the complex average envelope is inverted to yield a new time signal which is longer than the encoded data (time signal extrapolation). Fourth, the Padé extrapolated time signal is quantified for a sequence of K to monitor convergence of the reconstructed parameters. All four steps are applied to in vivo MRS data encoded on a 3 T scanner from a borderline serous cystic ovarian tumor. We focus on this clinical problem to help develop effective methods for early detection of ovarian cancer, in order to improve survival for women afflicted with this malignancy. It is anticipated that the presently refined, multi-purpose Padé-based methodology with its practical advantages for in vivo MRS can contribute to this goal.

Section: The Clinical Problem: the Need For Accurate And Timely Detecmentioning

confidence: 99%

Section: Spectra Averagingmentioning

confidence: 99%

Synergism of spectra averaging and extrapolation for quantification of in vivo MRS time signals encoded from the ovary

2017

“…Taking this wider view motivates efforts to garner maximal diagnostic information from MRS. One priority area is early ovarian cancer diagnostics, where the need for an effective in vivo MRS-based screening method has been underscored for many years [19][20][21]. While technological progress is obviously important, mathematical advances in signal processing are the most critical for MRS, as we will demonstrate.…”

Section: Implications For Cancer Diagnosticsmentioning

confidence: 99%

Iterative averaging of spectra as a powerful way of suppressing spurious resonances in signal processing

2016

The fast Padé transform (FPT) was applied to magnetic resonance spectroscopic (MRS) time signals encoded in vivo on a 1.5 T scanner from the parietal-temporal brain region of a pediatric patient who had suffered cerebral asphyxia. An iterative averaging procedure was implemented to the 9th iteration, whereby spurious structures on the total shape spectra were effectively suppressed. The parametric and non-parametric FPT (±) were verified to reconstruct equivalent total shape spectra. Via the parametric FPT, the spectral region of interest was chosen to bypass the giant water resonance, automatically generating spectral envelopes without the need for windowing. The dense component spectra were reliably reconstructed by the FPT (+) , in the "usual" mode (mixture of absorption and dispersion components) and "ersatz" mode (reconstructed phases set to zero). Via the latter, interference effects were well-visualized for closely-overlapping and hidden resonances. The most stringent test was performed for the complex frequencies and associated complex amplitudes reconstructed by the FPT (+) . Exceedingly small variances were obtained for all four Padé-reconstructed parameters per genuine resonance, once convergence was achieved at the 7th to 9th iterated averages. This now fully-validated methodology can generate denoised spectra and accurate spectral parameters for in vivo MRS data encoded within neurodiagnostics. Such a multi-faceted Padé-based strategy for processing the dense spectra of the brain could vitally improve pediatric neurodiagnostics. A wider range of clinical applications becomes within reach, including areas of cancer diagnostics where the added value of in vivo MRS is urgently needed. The broad theoretical underpinnings of incorporating quantum mechanics into signal processing provide the basis for these innovative advances.

“…Among these are areas of cancer diagnostics where in vivo MRS could potentially have the greatest added value. We have singled out early ovarian cancer diagnostics, where the need for an effective in vivo MRS-based screening method has been highlighted for nearly two decades [58,76,96]. …”

Section: Iterative Averaging: a Stabilization Procedures Through The Fptmentioning

confidence: 99%

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

2016

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, gluta- mine, 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.