Endometrioid adenocarcinoma of the ovary: MRI findings with emphasis on diffusion-weighted imaging for the differentiation of ovarian tumors

Kovač, Jelena Djokić; Terzić, Milan; Mirkovic, Milan; Banko, Bojan; Đikić-Rom, Aleksandra; Maksimović, Ružica

doi:10.1177/0284185115599805

Cited by 15 publications

(10 citation statements)

References 26 publications

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“…After full-text examinations of the remaining 153 articles, 137 were further excluded. Finally, 16 articles (11–13,16–28) were eligible for inclusion in the systematic review. For discrimination between malignant and benign lesions, ten articles (11,12,16–23) including 722 malignant tumors and 298 benign tumors in total were found in the literature.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, 16 articles (11–13,16–28) were eligible for inclusion in the systematic review. For discrimination between malignant and benign lesions, ten articles (11,12,16–23) including 722 malignant tumors and 298 benign tumors in total were found in the literature. For differentiating borderline tumors and malignant tumors, six studies (13,24–28) were eligible for meta-analysis, including 144 borderline tumors and 229 malignant tumors.…”

Section: Resultsmentioning

confidence: 99%

“…Among the ten studies that discriminated between benign and malignancies, the ADC cut-off value in one study was unclear (11). The magnetic fields in eight studies were 1.5-T (12,16–18,20–23); one study used 3-T (11), and the remaining study included both 1.5-T and 3-T (19). The b values in six articles were 0 and 1000 s/mm 2 (11,12,16–18,22), and the b values in the remaining studies were 0 and 800 s/mm 2 (19–21,23).…”

Section: Resultsmentioning

confidence: 99%

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Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance

Cao

Qiang

et al. 2018

Acta Radiol

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Background Diffusion-weighted imaging (DWI) and quantitative apparent diffusion coefficient (ADC) values are widely used in the differential diagnosis of ovarian tumors. Purpose To assess the diagnostic performance of quantitative ADC values in ovarian tumors. Material and Methods PubMed, Embase, the Cochrane Library, and local databases were searched for studies assessing ovarian tumors using quantitative ADC values. We quantitatively analyzed the diagnostic performances for two clinical problems: benign vs. malignant tumors and borderline vs. malignant tumors. We evaluated diagnostic performances by the pooled sensitivity and specificity values and by summary receiver operating characteristic (SROC) curves. Subgroup analyses were used to analyze study heterogeneity. Results From the 742 studies identified in the search results, 16 studies met our inclusion criteria. A total of ten studies evaluated malignant vs. benign ovarian tumors and six studies assessed malignant vs. borderline ovarian tumors. Regarding the diagnostic accuracy of quantitative ADC values for distinguishing between malignant and benign ovarian tumors, the pooled sensitivity and specificity values were 0.91 and 0.91, respectively. The area under the SROC curve (AUC) was 0.96. For differentiating borderline from malignant tumors, the pooled sensitivity and specificity values were 0.89 and 0.79, and the AUC was 0.91. The methodological quality of the included studies was moderate. Conclusion Quantitative ADC values could serve as useful preoperative markers for predicting the nature of ovarian tumors. Nevertheless, prospective trials focused on standardized imaging parameters are needed to evaluate the clinical value of quantitative ADC values in ovarian tumors.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance

Cao

Qiang

et al. 2018

Acta Radiol

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“…Since the majority of ovarian cancers have a similar morphological appearance on conventional magnetic resonance imaging (MRI), more advanced diagnostic technology is necessary to improve the differential diagnosis . Depending on the microscopic motion of water molecules, diffusion‐weighted imaging (DWI) can provide additional information.…”

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confidence: 99%

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched‐exponential diffusion models

Wang

Zhou

et al. 2017

Magnetic Resonance Imaging

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“…Spearman’s correlation was used to analyze the correlation between the change rates of DWI and DKI parameters and change rates of the tumor size, necrosis, apoptosis, Ki-67 and Bcl-2. The results were interpreted according to the degree of association as strong (1 ≥ r ≥ 0.75), moderate (0.75 > r ≥ 0.50), low (0.50 > r ≥ 0.25), or not relevant (r < 0.25) after taking significant correlation ( p < 0.01 or p < 0.05) values into consideration [ 19 – 21 ]. A p < 0.05 was considered statistically significant.…”

Section: Methodsmentioning

confidence: 99%

Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer

2018

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BackgroundTo investigate diffusion-weighted magnetic imaging (DWI) and diffusion kurtosis magnetic imaging (DKI) for the early detection of the response to docetaxel (DTX) chemotherapy in rat epithelial ovarian cancer (EOC).Methods7,12-Dimethylbenz[A]anthracene was applied to induce orthotopic EOC in Sprague–Dawley rats. Rats with EOC were treated with DTX on day 0 (treatment group) or were left untreated (control group). DWI and DKI were performed on days 0, 3, 7, 14 and 21 after treatment. On day 21, the tumors were categorized into the sensitive and insensitive groups according to the size change. The cutoff values of the DWI and DKI parameters for the early response were determined. The experiment was repeated, and the treatment group was divided into the sensitive and insensitive groups according to the initially obtained cutoff values. The DWI and DKI parameters were correlated with tumor size, proliferation, apoptosis and tumor necrosis.ResultsIn the sensitive vs. insensitive or control group, significant differences were found in the Δ% of the DWI and DKI parameters (ADC, D and K) from day 3 and in tumor size from day 14. Early on day 7, the Δ% of K had an AUC of 1 and sensitivity and specificity values of 100% and 100%, respectively, to detect the response to DTX using a cutoff value of 19.03% reduction in K. From day 7, significant differences were found in the Δ% of Ki-67 and CA125 in the sensitive vs. control group and from day 14 in the sensitive vs. insensitive group. From day 14, there were significant differences in the Δ% of Bcl-2, apoptosis and tumor necrosis in the sensitive vs. control or insensitive group. The Δ% values of ADC and D were negatively correlated with the Δ% values of tumor size, Ki-67, CA125 and Bcl-2 and were positively correlated with the Δ% values of apoptosis and tumor necrosis. The Δ% of K was positively correlated with the Δ% values of tumor size, Ki-67, CA125 and Bcl-2 and was negatively correlated with the Δ% values of apoptosis and tumor necrosis.ConclusionsDWI and DKI parameters, especially K, are superior for imaging tumor size for the early detection of the response to DTX chemotherapy in induced rat EOC.

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Endometrioid adenocarcinoma of the ovary: MRI findings with emphasis on diffusion-weighted imaging for the differentiation of ovarian tumors

Cited by 15 publications

References 26 publications

Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance

Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched‐exponential diffusion models

Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer

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