Global ovarian cancer health disparities

Chornokur, Ganna; Amankwah, Ernest K.; Schildkraut, Joellen M.; Phelan, Catherine M.

doi:10.1016/j.ygyno.2012.12.016

Cited by 162 publications

(134 citation statements)

References 73 publications

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“…The high mortality rate is mainly due to late detection, at Stage III or IV with tumor spread outside the true pelvis [7]. When detected early, ovarian cancer has an excellent prognosis, especially when confined to a single ovary (Stage Ia) with five-year survival rates over 90% [8]. The difficulty is that early stage ovarian cancer is very frequently silent, i.e.…”

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

confidence: 99%

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

Belkić

2017

J Math Chem

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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.

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

confidence: 99%

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

Belkić

2017

J Math Chem

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“…When detected early, ovarian cancer has an excellent prognosis, especially at Stage Ia (confined to a single ovary) for which five-year survival rates are well above 90 % [19]. The challenge, however, is that early stage ovarian cancer is most often asymptomatic and, as noted, the ovary may still be of normal size [1].…”

Section: Late Detection Of Ovarian Cancermentioning

confidence: 99%

“…The difference between the lhs of (14) and (19) for the kth usual component (P + K /Q + K ) U k and the usual envelope (P + K /Q + K ) U , respectively, is the omitted subscript k in the latter and, by the same token, for the ersatz modes in (13) and (18).…”

Section: By the Fpt (+) Likewise In The Fpt (−)mentioning

confidence: 99%

“…By evaluating P + K (z)/Q + K (z) for z = exp(2πiντ ) at any chosen set of real-valued sweep frequencies ν, the non-parametric spectrum is obtained. For the parametric case, the total cross sections via the Heaviside partial fraction decompositions (18) and (19) are employed in terms of the ersatz and usual components, respectively.…”

Section: The Derivation Of the Envelopes In The Representation Of Thementioning

confidence: 99%

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

Belkić

2016

J Math Chem

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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.

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“…The lack of specific symptoms, effective screening and early diagnostic techniques makes ovarian cancer as a highly dreadful malignancy (Chornokur et al, 2013). Survival is directly related to stage with a 5 year survival of 93% for those diagnosed with localized disease and only 31% for those with distant disease.…”

Section: Introductionmentioning

confidence: 99%

Risk Factors for Epithelial Ovarian Carcinoma in India: A Case Control Study in Low-Incidence Population

Shanmughapriya¹,

Senthilkumar²,

Seshachalam³

et al. 2015

International J. of Cancer Research

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A case-control study to identify the risk factors for ovarian carcinoma in Tiruchirapalli district, Tamilnadu, India a low incidence population was conducted. The invasive epithelial ovarian cancer case patients were 37. The control group consisted of 74 healthy women, matched according to age categories. Subjects were interviewed in person regarding socio demographic and reproductive characteristics. The unconditional logistic regression was performed and tests of statistical significance were based on difference in the log likelihoods and all p values were 2-sided. In logistic regression analysis, the risk of ovarian cancer was strongly related to the increased physical activity (OR: 3.227, 95% CI: 1.143, 9.108), intake of high fat (OR: 6.286, 95% CI: 0.779, 50.701) early age at menarche (OR: 6.389, 95% CI: 2.143, 19.047), post menopausal status (OR: 3.22, 95% CI: 1.417, 7.316). The use of contraceptive methods, tubal ligation, one birth, late menarche was found to be inversely associated with ovarian cancer risk. The risk of ovarian cancer decreased 80% by one birth event, 40% by use of contraceptives and tubal ligation and six times reduced risk for menarche at later age. The present study thus clearly typified this neoplasm as hormone dependent and it is possible to establish that "ovulation" mechanism determine the level of risk for ovarian cancer in this study population. In addition, the difference in the distribution of histologic subtypes in this population compared with high-incidence populations may point to further differences in risk factors.

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Global ovarian cancer health disparities

Cited by 162 publications

References 73 publications

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

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

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

Risk Factors for Epithelial Ovarian Carcinoma in India: A Case Control Study in Low-Incidence Population

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