Ovarian Cancer in Iranian Women, a Trend Analysis of Mortality and Incidence

Sharifian, Abdolhamid; Pourhoseingholi, Mohamad Amin; Norouzinia, Mohsen; Vahedi, Mohsen

doi:10.7314/apjcp.2014.15.24.10787

Cited by 29 publications

(24 citation statements)

References 18 publications

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“…Moreover, there appears to be a trend towards increasing incidence of this malignancy in many parts of the world [1][2][3][4]. The case fatality rate for ovarian cancer is very high; more than 14 000 women die each year from this disease in the USA alone [5,6].…”

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

confidence: 99%

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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%

“…without any symptoms. Further obstacles arise due to the small size of the ovary (6.1 to 1.8 cm 3 , normally diminishing with age) and that it is not necessarily enlarged with early-stage cancer [9].…”

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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“…or "Does she/he get chemotherapy?" Ovarian/cervical cancers which are the forth common cancers among women was also estimated (Sharifian et al, 2014). The incidence of these cancers, wholly, was 14.42 per 100000 which was approximately far from national …”

Section: Discussionmentioning

confidence: 99%

Application of a Network Scale-up Method to Estimate the Size of Population of Breast, Ovarian/Cervical, Prostate and Bladder Cancers

Haghdoost¹,

Baneshi²,

Haji-Maghsoodi³

et al. 2015

Asian Pacific Journal of Cancer Prevention

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Network scale up (NSU) is a novel approach to estimate parameters in hard to reach populations through asking people the number of individuals they know in their active social network. Although the method have been used in hidden populations, advantages of NSU indicate that exploration of applicability to disease like cancer might be feasible. The aim of this study was to assess the application of NSU to estimate the size of the population of breast, ovarian/cervical, prostate, and bladder cancers in the South-east of Iran. A total of 3,052 (99% response rate) Kermanian people were interviewed in 2012-2013. Based on NSU, participants were asked about if they know any people on their social network who suffered from breast, ovarian/cervical, prostate, and bladder cancers, if yes, they should enumerate them. A total of 1,650 persons living with four types of cancers (breast, ovary/cervix, prostate, and bladder) were identified by the respondents. Totally, the prevalence of people living with the four types of cancers was 228.4 per 100,000 Kermanian inhabitants. The most prevalent cancer was breast cancer, at 168.9 per 100,000, followed by prostate cancer with 116.9, ovarian/cervical cancer with 99.8, and bladder cancer with 36.3 per 100000 Kerman city population. NSU values provide a usable but not very precise way of estimating the size of subpopulations in the context of the four major cancers (breast, ovary/ cervix, prostate, and bladder).

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“…In many parts of the world, its incidence appears to be increasing [20][21][22][23][24][25]. If detected early, the prognosis for ovarian cancer is excellent: when confined to a single ovary (Stage Ia), the 5-year survival rates are better than 90% [26].…”

Section: Ovarian Cancer: the Need And Challenge Of Early Detectionmentioning

confidence: 99%

Encoded in vivo time signals from the ovary in magnetic resonance spectroscopy: poles and zeros as the cornerstone for stability of response functions of systems to external perturbations

Belkić

2017

J Math Chem

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In order to handle encoded data from magnetic resonance spectroscopy (MRS), advanced signal processing methods are vital. This is presently carried out using the fast Padé transform (FPT) applied to in vivo MRS time signals encoded from the ovary. We examine the essential features of the response function, namely the spectral poles and zeros, as the key to stability of the system to external excitations. Noise is separated from signal by reliance upon the multi-level signature of Froissart doublets. Our focus is upon eliminating the oversensitivity to alterations in model order K , through systematic examination of poles and zeros, as well as Padé-reconstructed total shape spectra, spectral parameters and component shape spectra. This comprehensive examination of convergence of all variables under study includes investigation of the combined role of spectra averaging and time signal extrapolation. Comparisons are made throughout between the results for six model orders (K = 575, 585, . . . , 625) with an increment of ten and eleven model orders (K = 575, 580, . . . , 625) with an increment of 5. It is demonstrated that for the reconstructed poles and zeros, as well as for magnitudes and phases, spectra averaging and Padé-based extrapolation of time signals are essential for the stability of the system and for the accurate retrieval of resonances. Full convergence is achieved when spectra averaging and extrapolation are applied together. Spectra averaging and extrapolation are also shown to be needed to obtain stabilized results to the level of stochasticity for the component spectra for the six and the eleven model orders. Without spectra averaging and extrapolation, there were noticeable variances for the six and the eleven model orders with regard to all the variables under study. The present analysis and results have important implications for expediting the robust quantification by the FPT. All the analysis herein was applied to in vivo MRS data encoded on a 3 T scanner from a borderline serous cystic ovarian tumor. This clinical problem has been chosen in light of the urgent need to develop effective methods for early detection of ovarian cancer. The overriding motivation is to improve survival for women afflicted with this malignancy. The reported results further hone the Padé-designed methodology for practical applications of in vivo MRS and, therefore, are anticipated to help in achieving the stated goal.

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Ovarian Cancer in Iranian Women, a Trend Analysis of Mortality and Incidence

Cited by 29 publications

References 18 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

Application of a Network Scale-up Method to Estimate the Size of Population of Breast, Ovarian/Cervical, Prostate and Bladder Cancers

Encoded in vivo time signals from the ovary in magnetic resonance spectroscopy: poles and zeros as the cornerstone for stability of response functions of systems to external perturbations

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