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      The Value of Diffusion-Weighted Imaging in the Differential Diagnosis of Ovarian Lesions: A Meta-Analysis

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          Abstract

          Objectives

          The ability of contrast-enhanced MRI to distinguish between malignant and benign ovarian masses is limited. The aim of this meta-analysis is to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) in differentiating malignant from benign ovarian masses.

          Methods

          A comprehensive literature search was performed in several authoritative databases to identify relevant articles. The weighted mean difference (WMD) and corresponding 95% confidence interval (95% CI) were calculated. We also used subgroup analysis to analyze study heterogeneity, and evaluated publication bias.

          Results

          The meta-analysis is based on 21 studies, which reported the findings for 731 malignant and 918 benign ovarian masses. There was no significant difference in apparent diffusion coefficient (ADC) values for DWI between benign and malignant lesions (WMD = 0.22, 95% CI = -0.02–0.47, p = 0.08). Subgroup analysis by benign tumor type revealed higher ADC values (or a trend toward higher values) for cysts, cystadenomas and other benign tumors compared to malignant masses (cyst: WMD = 0.54, 95% CI = -0.05–1.12, p = 0.07; cystadenoma: WMD = 0.73, 95% CI = 0.38–1.07, p < 0.0001; other benign tumor: WMD = 0.16, 95% CI = -0.13–0.46, p = 0.28). On the other hand, lower ADC values (or a trend toward lower values) were observed for endometrioma and teratoma compared to malignant masses (endometrioma: WMD = -0.09, 95% CI = -0.47–0.29, p = 0.64; teratoma: WMD = -0.49, 95% CI = -0.85–0.12, p = 0.009). Subgroup analysis by mass property revealed higher ADC values in cystic tumor types than in solid types for both benign and malignant tumors. Significant study heterogeneity was observed. There was no notable publication bias.

          Conclusions

          Quantitative DWI is not a reliable diagnostic method for differentiation between benign and malignant ovarian masses. This knowledge is essential in avoiding misdiagnosis of ovarian masses.

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          Most cited references31

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          Bias in meta-analysis detected by a simple, graphical test. Increase in studies of publication bias coincided with increasing use of meta-analysis.

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            Characterization of and correction for eddy current artifacts in echo planar diffusion imaging.

            Magnetic resonance diffusion imaging is potentially an important tool for the noninvasive characterization of normal and pathological tissue. The technique, however, is prone to a number of artifacts that can severely affect its ability to provide clinically useful information. In this study, the problem of eddy current-induced geometric distortions that occur in diffusion images acquired with echo planar sequences was addressed. These geometric distortions produce artifacts in computed maps of diffusion parameters and are caused by misalignments in the individual diffusion-weighted images that comprise the diffusion data set. A new approach is presented to characterize and calibrate the eddy current effects, enabling the eddy current distortions to be corrected in sets of interleaved (or snapshot) echo planar diffusion images. Correction is achieved by acquiring one-dimensional field maps in the read and phase encode direction for each slice and each diffusion step. The method is then demonstrated through the correction of distortions in diffusion images of the human brain. It is shown that by using the eddy current correction scheme outlined, the eddy current-induced artifacts in the diffusion-weighted images are almost completely eliminated. In addition, there is a significant improvement in the quality of the resulting diffusion tensor maps.
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              The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas.

              The usefulness of diffusion-weighted (DW) magnetic resonance (MR) imaging for the diagnosis of uterine sarcomas was investigated, as well as whether DW images and quantitative measurement of apparent diffusion coefficient (ADC) values can facilitate differentiating uterine sarcomas from benign leiomyomas. MR images including DW images were obtained in 43 surgically treated patients with 58 myometrial tumors, including seven uterine sarcomas (five leiomyosarcomas and two endometrial stromal sarcomas) and 51 benign leiomyomas (43 ordinary leiomyomas, two cellular leiomyomas and six degenerated leiomyomas). Qualitative analysis of non-enhanced and postcontrast MR images and DW images and quantitative measurement of ADC values were performed for each myometrial tumor. Both uterine sarcomas and cellular leiomyomas exhibited high signal intensity on DW images, whereas ordinary leiomyomas and most degenerated leiomyomas showed low signal intensity. The mean ADC value (10(-3) mm(2)/s) of sarcomas was 1.17 +/- 0.15, which was lower than those of the normal myometrium (1.62 +/- 0.11) and degenerated leiomyomas (1.70 +/- 0.11) without any overlap; however, they were overlapped with those of ordinary leiomyomas and cellular leiomyomas. In addition to morphological features on nonenhanced and postcontrast MR sequences, DW imaging and ADC measurement may have a potential ability to differentiate uterine sarcomas from benign leiomyomas.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                23 February 2016
                2016
                : 11
                : 2
                : e0149465
                Affiliations
                [1 ]Department of Preventive Medicine, College of Medicine, Korea University, Seoul, Korea
                [2 ]Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
                [3 ]Department of Radiology, College of Medicine, Incheon St. Mary's Hospital, The Catholic University of Korea, Incheon, Republic of Korea
                Suzhou University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: YRS. Performed the experiments: YRS SYL HJK. Analyzed the data: YRS HJK. Contributed reagents/materials/analysis tools: YRS SYL HJK CSP KK. Wrote the paper: YRS.

                Article
                PONE-D-15-36300
                10.1371/journal.pone.0149465
                4764370
                26907919
                6577d59a-34ff-4429-a3d1-e252830b3370
                © 2016 Kim et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 August 2015
                : 31 January 2016
                Page count
                Figures: 4, Tables: 1, Pages: 13
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Carcinomas
                Adenocarcinomas
                Biology and Life Sciences
                Neuroscience
                Brain Mapping
                Brain Morphometry
                Diffusion Weighted Imaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Anatomical Pathology
                Histopathology
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Malignant Tumors
                Medicine and Health Sciences
                Oncology
                Cancer Detection and Diagnosis
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Benign Tumors
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