Diffusion-weighted MR imaging for differentiating borderline from malignant epithelial tumours of the ovary: pathological correlation

Zhao, Siwen; Qiang, Jin Wei; Zhang, Guo Fu; Feng, Hua; Cai, Song Qi; Li, Hai Ming; Wang, Li

doi:10.1007/s00330-014-3236-4

Cited by 72 publications

(64 citation statements)

References 28 publications

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“…In ovarian masses, the lowest ADC values are observed in malignant lesions (1.39 ± 0.62 mm 2 /s) [22]. This quantifiable difference in ADC between benign and malignant ovarian tumours has been confirmed in a number of other studies [23]. More detailed ADC histogram analysis of the entire tumour volume provides information on the heterogeneity of diffusivity within the tumour and thus on the range of tumour microenvironments present, which is of particular interest in ovarian cancer where tumour is often present at the outset within a variety of tissue types (ovary, peritoneum, omentum, lymph nodes).…”

Section: Ovarian Cancermentioning

confidence: 62%

A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer

Bollineni

Krämer

Liu

et al. 2015

Cancer Treatment Reviews

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Section: Ovarian Cancermentioning

confidence: 62%

A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer

Bollineni

Krämer

Liu

et al. 2015

Cancer Treatment Reviews

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“…In general, MRI is very sensitive, such that ovarian cancer will usually be detected, but many benign lesions will also be misdiagnosed as malignant. Diffusion-weighted imaging (DWI) can provide some additional help in assessing adnexal lesions, but many false positives also occur with DWI [26,27].…”

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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“…В работе S. Zhao было показано, что ДВИ могут исполь-зоваться для дифференциальной диагностики погранич-ных и злокачественных эпителиальных образований яич-ников [53].…”

Section: возможности применения диффузионно-взвешенных изображений маunclassified

Current Possibilities of Magnetic – Resonance Imaging in Detection of Ovarian Cancer

Рубцова¹,

Новикова²,

Sychenkova³

2017

Issled. prakt. med. (Print)

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Diffusion-weighted MR imaging for differentiating borderline from malignant epithelial tumours of the ovary: pathological correlation

Abstract: DW MR imaging is useful for differentiating BEOTs from MEOTs. Patients with BEOTs are treated differently from patients with MEOTs. Conservative fertility-sparing laparoscopic surgery can be performed in patients with BEOTs. BEOTs often affect young women of childbearing age.

Cited by 72 publications

References 28 publications

A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer

A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer

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

Current Possibilities of Magnetic – Resonance Imaging in Detection of Ovarian Cancer

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