|Year : 2016 | Volume
| Issue : 1 | Page : 77-83
Diagnostic value of lymph node metastasis by diffusion-weighted magnetic resonance imaging in cervical cancer
Xiang-Qin He1, Li-Na Wei2
1 Department of Ultrasound, The First People's Hospital of Jining City, Jining, Shandong, China
2 Department of Reproductive Medicine, The First People's Hospital of Jining City, Jining, Shandong, China
|Date of Web Publication||13-Apr-2016|
Department of Reproductive Medicine, The First People's Hospital of Jining City, No. 6 Jiankang Road, Jining - 272 011, Shandong
Source of Support: None, Conflict of Interest: None
Introduction: Diffusion.weighted imaging. (DWI) combined with its apparent diffusion coefficient. (ADC) value shows great significance in the differential diagnosis of human tumors. This meta.analysis is to determine whether ADC valued in DWI could contribute to the differential diagnosis of positive and negative lymph node. (LN) metastasis in cervical cancer. (CC) or not.
Materials and Methods: A series of types of computerized databases were used searching for eligible studies relied on a strict inclusion and exclusion criteria. Two investigators were involved in the process of selecting articles and extracting dataset. Standardized mean differences (SMD) for the assessment of ADC values in positive and negative LN metastasis in CC patients were calculated.
Results: Fifteen cohort studies composed of 687 cases diagnosed with cervical tumor were incorporated into the current meta-analysis. Statistical analysis showed that the ADC value in positive LN metastasis was significantly lower than that with negative LN metastasis [SMD = 1.02, 95% confidence interval (CI) =0.54~1.50, P < 0.001]. Stratified by country, a lower ADC value in tumor tissues with LN metastasis was detected in comparison to that of tumor tissues without LN metastasis among China (SMD = 1.28, 95# CI = 0.62~1.94, P < 0.001) and Korea subgroups (SMD = 1.09, 95% CI = 0.65~1.52, P < 0.001).
Conclusion: The ADC values in CC tissues with LN metastasis were significantly lower than those without LN metastasis, suggesting that DWI appears to improve diagnostic performance and can be a useful adjunct imaging for identifying LN metastasis in CC patients.
Keywords: Apparent diffusion coefficient, cervical cancer, diffusion weighted magnetic resonance imaging (MRI), meta-analysis
|How to cite this article:|
He XQ, Wei LN. Diagnostic value of lymph node metastasis by diffusion-weighted magnetic resonance imaging in cervical cancer. J Can Res Ther 2016;12:77-83
| > Introduction|| |
Cervical cancer (CC), a malignant neoplasm arising from cells originating in the cervix uteri, remains second most prevalent female malignancy and the third most common cause of cancer related deaths in females worldwide., Of note, CC is more prevailing in developing countries, with an estimated 529,800 women encountering it, equivalent to 9% of the total cases, and approximately 234,000 deaths per year among developing countries in comparison with 40,000 women per year in developed nations., Among 100 women who have suffered CC even treated by radical therapy, approximately 30 women will have a recurrence and die of the disease, and a recent research from the UK showed a 5-year survival rate of only close to half percentage., Previous studies have reported that the etiology of CC is absolutely complex, involved external, genetic, and cellular risk factors. The main cause of CC is that human papillomavirus (HPV) infect the whole cervix, and then the virus substantially metastasizes to bladder, rectum, and other organs consequently conducing to death. Via stimulating the massive growth of HPV, smoking also indicated to be the vital cause resulting in the incidence of CC. Treatment and detection in the early terms of CC might increase its survival rate possibly, so improvement of the diagnostic accuracy indicated to be of great importance. Recently, increasing numbers of scholars have paid more attention to that the apparent diffusion coefficient (ADC), derived from the diffusion-weighted image (DWI), has an important effects on the diagnosis of CC via monitoring lymph node (LN) metastasis.
DWI, a non-invasive imaging method calculating the ADC values, aims to observe the molecular mobility in the region of biological tissues, especially water molecule. The water diffusion process is no free, affected by macromolecules, fibers, and membranes, thus its diffusion imaging can accurately and clearly shows micro-structural performances such as cell density, tissue architecture, and cellular membrane obstacles, either normal or in a diseased state. Characterized by diffusion gradients, homogeneous or converse imaging, high amplitude, and short acquisition time, DWI is regarded as the standardized imaging technique. In addition, the quality and accuracy of DWI are determined by several factors, including magnet strength, pulse direction, and signal intensity. Based on qualitative and quantitative information from ADC values measured by different diffusion imaging, DWI is useful for detecting tumor size, staging, post-operative follow-up, and treatment response. The DWI history is originated from mid-1980s, mainly clinically applied in neurological disorders, i.e. acute stroke, and then it developed to manage the liver, differentiating liver tumors from angiomas. For instance, numerous studies have shown that DWI has clinical significance in ischemic stroke, lower ADC values related with brain ischemia due to metabolic disturbance and cytotoxic edema. In the past decades, many publications indicated that the role of DWI contributes to breast imaging, which functions as discriminating benign from malignant lesions and choosing surgical planning based on post-operative assessment. Combined DWI with endovaginal receiver coil, DWI with more sensitivity and specificity precisely diagnosed stage Ia or Ib1 of cervical cancers and explored whether its stages is correlated with lymph node status. Furthermore, large amount of reports demonstrated that ADC values are closely implicated with prognostic outcomes, which rely on tumor cell volume and type, LN. Several scholars put up with a possibility that patients with LN metastasis in cervical cancer reveal decreased ADC values, blocking the diffusion of water protons.,, However, lines of studies have the reverse results., In virtue of these conflicting results, we carried out the necessary meta-analysis to investigate the relationship of valuable potentials of DWI with lymph node status.
| > Materials and Methods|| |
Identification of relevant studies
We conducted MEDLINE, Science Citation Index, the Cochrane Library, Embase, CINAHL, and Current Contents Index, and additional Chinese Biomedical, Chinese Journal Full-Text, and Weipu Journal for papers. We utilized the following medical subject headings and free language terms with a highly sensitive search strategy: (”Diffusion Magnetic Resonance Imaging” or “Diffusion MRI” or “Diffusion Weighted MRI” or “DWI” or “diffusion-weighted magnetic resonance imaging” or “MRI-DWI” or “diffusion-weighted imaging” or “diffusion-weighted-MRI”) and (”Uterine Cervical Neoplasms” or “Cervical Neoplasms” or “Cervical cancer” or “cervical carcinoma” or “cervix cancer” or “Cervix Neoplasms” or “Cervix carcinoma”). Human studies published in any language until the data of June 30, 2014 were considered, and articles must be published in the primary literatures with no obvious overlap of contents with other publishes. Studies reported in languages not familiar to the investigators were translated. We also searched the reference lists of relevant studies manually to find other potentially works.
Inclusion and exclusion criteria
Clinical cohort studies reporting ADC values measured with DWI and LN metastasis in CC must followed our predefined inclusion criteria: (1) the search results were conducted within a human population and published in a peer-reviewed journal; (2) the diagnostic criteria of CC usually based on histological data, symptoms, gynecological or colposcopy examination, and combined with cervical biopsy; (3) diagnostic evaluations of imaging detection such as computed tomography scanning or magnetic resonance imaging (MRI) were applied for the diagnosis of CC in clinical, and combined with histopathologically confirmation; (4) original data and sufficient information on the ADC value should be presented in the positive and negative LN metastasis of CC patients. Additionally, when the same data subset was found in over one publishes, we chose the most detailed or most recently published articles. We selected articles by two steps:First, relied on the selection criteria we predefined, un-eligible articles were eliminated reviewing all the titles and abstracts, and subsequently confirmed the final articles implicated from those remaining studies after applying the similar selection criteria. Articles that did not satisfy our predefined inclusion criteria with unpublished sources of data, duplications or certain publication types (letters, abstracts, reviews, and meta-analysis) were all not accepted in the current meta-analysis.
Study quality and data extraction
By using a standardized form, two investigators selected reasonable articles and eligible data regarding the characteristics of this study. A third observer assessed all involved contents for the purpose of resolve disagreement between those two investigators. Our application of methodological quality assessment of the included trials was mainly based on the quality assessment of diagnostic studies (this quality assessment tool judges included studies' diagnostic accuracy in systematic reviews). This tool consisted of 14 questions scored as “yes,” “no,” or “unclear.” The three broad perspectives were judged: (1) bias: 0~9; (2) viability: 0~2; and (3) reporting: 0~3. Quality assessment of diagnostic accuracy assessment (QUADAS) ranged from 0 to 14; and a score ≥10 revealed a good methodological quality.
The surname and initials of the first author, the year of publication or submission, source country and ethnicity, language of publication, total sample size of patients, mean age and age-spanning scope, demographic variables of the subjects, MRI machine type, MRI machine type code, b value (s/mm 2), and ADC (×10-3 mm2/s) in positive and negative LN metastasis were all extracted from every single study for the following statistical analysis.
Standardized mean differences (SMD) for the assessment of ACD values in positive and negative LN metastasis in CC patients were calculated. A 95% confidence interval (95% CI) was calculated for the summary SMD by utilizing Z test. Statistical analyses were conducted with the statistical data (STATA) statistical software (Version 12.0, STATA Corporation, and College Station, TX, USA). Also, Chi-square value test Q statistic and inconsistency index (I-squared, I2) was applied to estimate the possible existence of heterogeneity of individual study and between-studies heterogeneity resulting from the pooled estimate.,Q-test showed a P < 0.05 or I2 test exhibited <50%, indicating maximal heterogeneity and we did a random-effects model-relied exploration of heterogeneity source, and otherwise SMDs were pooled in accordance with the fixed-effects model., Further subgroups of different explanatory variables (country and MRI machine type) when a substantial heterogeneity was found. Additionally, in order to evaluate the impact of single studies on the overall estimate, a one-way sensitivity analysis was conducted. Further, Egger's linear regression test with visual inspection of the funnel plot was applied to detect the potential publication bias.,
| > Results|| |
Description of included studies
[Table 1] showed the baseline characteristics and ADC in the tumor and normal tissues of the individual studies. Flow diagram of study selection progress and the main reason for exclusion were displayed in [Figure 1]. The combined electronic and manual search initially resulted in 196 potentially eligible articles. After the exception of 1 duplicated studies, these retrieved studies (n = 194) were screened by title and abstract for relevance; subsequently, 84 irrelevant articles were excluded (39 articles were letters, reviews and meta-analysis, 20 not human studies, and 25 not correlated with the current research topic). Then, we systematically reviewed the remaining 110 articles qualified for full-text reading. After full-text reading, 94 articles were deemed unsuitable and were therefore excluded, and 16 articles were identified to be included in qualitative analysis. In addition, another one study was excluded due to lack of data integrity after a more careful assessment of the remaining articles. Finally, 15 cohort studies composed of 687 cases diagnosed with CC were incorporated into the current meta-analysis, the sample size of the 15 studies ranged from 18 to 143 participants.,,,,,,,,,,,,,, All the enrolled papers showed moderate-high quality. Of the 15 included studies, 14 were performed in Asian, Japan, and the remaining one was from Caucasians failed to obtain age information. MRI machine types were included with GE 1.5 T MRI scanners, Philips 1.5 scanners, Siemens 1.5T scanners. ADC (×10-3 mm 2/s) values were expressed as mean ± standard deviation (SD), and the ADC in the tumor and normal tissues were recorded.
|Table 1: The characteristics and methodological quality of the included studies in this meta-analysis|
Click here to view
|Figure 1: Flow chart shows study selection procedure. Thirteen studies were included in this meta-analysis|
Click here to view
Quantitative data synthesis
The following analyses were performed with a random-effects model for the evidence of Q-test and I2 test (I2= 94.2%, P = 0.000). In the meta-analysis, statistical analysis showed that the ADC value in CC tissues with LN metastasis was detected to be apparently lower than that of CC tumor tissues without LN metastasis, according to the random effects pooled SMD in the 15 studies (SMD = 1.02, 95% CI = 0.54~1.50, P < 0.001) [Figure 2]. Additionally, studies were stratified by country and MRI machine type to explore potential sources of heterogeneity. Country stratified analysis demonstrated a lower ADC values in breast tumor tissues with LN metastasis in comparison to that of tumor tissues without LN metastasis among China (SMD = 1.28, 95% CI = 0.62~1.94, P < 0.001) and Korea subgroups (SMD = 1.09, 95% CI = 0.65~1.52, P < 0.001), but not among Japan (SMD = 0.09, 95%CI = -0.86~1.04, P = 0.858) and UK (SMD = 0.06, 95% CI = -0.59~0.71, P = 0.859). When concerned about the MRI machine type-stratified analysis, evidence revealed that significant difference in ADC value were found between CC tissues with and without LN metastasis among GE 1.5T, GE 3.0T, and Philips 1.5T scanner types subgroups (all P < 0.05); while similar results were not detected among Siemens 3.0T (SMD = 0.36, 95% CI = -0.21~0.93, P = 0.213) and Siemens 1.5T (SMD = 2.11, 95% CI = -0.93~5.14, P = 0.173) scanners subgroups [Figure 3].
|Figure 2: Forest plots on the difference in the frequency of apparent diffusion coefficient (ADC) value between lymph node (LN) metastasis and non-LN metastasis in cervical cancer patients|
Click here to view
|Figure 3: Subgroup analyses by magnetic resonance imaging (MRI) machine type and country on the difference of apparent diffusion coefficient (ADC) value between lymph node (LN) metastasis and non-LN metastasis in cervical cancer patients|
Click here to view
Sensitivity analyses suggested no significant difference of every study in the influence of the whole results [Figure 4]. Finally, no asymmetrical distribution was detected from the Egger's regression test in the funnel-plot in ADC values in positive and negative LN metastasis, suggesting no publication bias in systematic reviews (Egger's test: t = -1.44, P = 0.173) [Figure 5].
|Figure 4: Sensitivity analysis of the summary odds ratio coefficients on the difference in the frequency of apparent diffusion coefficient (ADC) value between lymph node (LN) metastasis and non-LN metastasis in cervical cancer patients|
Click here to view
|Figure 5: Funnel plot of publication biases on the difference in the frequency of apparent diffusion coefficient (ADC) value between lymph node (LN) metastasis and non-LN metastasis in cervical cancer patients|
Click here to view
| > Discussion|| |
In the current meta-analysis, the combination of the detect-ability of pelvic LN metastasis on ADC value measured with DWI provided useful information and diagnostic significance for distinguishing metastatic LN from the non-metastatic ones, with a lower ADC values in the LN metastasis subgroups. And these results were significantly comparable to the previous evidence., With regard to the specific mechanisms by which the metastatic nodes showed a low ADC value and a high signal intensity on DWI, it might be largely attributed to the features of metastatic nodes and properties of DWI and ADC, and especially the metastatic foci have a relatively different cellularity of the cancer microstructure.,
Generally speaking, DWI is a type of non-invasive MRI technique, enabling the characterization of tissue at a microscopic level, that could show clearly considering the micro-structural characteristics of normal or tumor tissues on the basis of the water molecular diffusion around the cells., With respect to the common mechanisms of DWI in the diagnosis and differential diagnosis of human tumors, it can be interpreted that the density, structures, and metabolism of normal cells would change accompanied with the occurrence of serious organs lesions, and eventually the diffusion distance of water molecules will also changes per unit time. In clinical application, DWI has been widely used for differentiating malignant tumors from benign tumors, and in particular contributing to the identification of histopathological features for various kinds of human tumors., To our knowledge, difference in ADC value and signal intensity on DWI map of LN reflects the difference in cellularity and histopathological features of benign and malignant nodes. And malignant nodes have increased cellularity compared with benign nodes with subsequent reduction of the ADC value. ADC values derived from DWI detection reflected the protons random thermal motion indicated a quantitative measure of water diffusivity. To be specific, if water molecules would be able to diffuse more freely in the sensitive direction of the gradient field alignment, this may result in a larger diffusion distance and magnetic field changes, and thereby with a lower signal intensity on DWI and an elevated ADC value; whereas the signal from fast-moving water molecules attenuated by slow diffusion water molecules, a higher signal intensity and a lower ADC value would be observed., Taken into consideration about the previous principles, we could further hypothesize that ADC values could be referenced as one of the most critical elements in the diagnosis of LN metastasis in CC development. According to our results, we considered that since those metastatic pelvic LN might be invaded with those malignant cervical carcinomas, and normal lymphoid tissues within the original LNs could be substituted by those malignant tumor tissues, and consequently, the diffusion of water molecules from extracellular space were limited. In addition, accepted evidence showed that the increased nuclear-cytoplasmic ratio of tumor cells may lead to a integrated and compact CC cell which might apparently restricted the random motion of water molecules, including extra-, intra- and trans-cellular motion, and hence promoted a stronger signal intensity on DWI and a lower ADC values (http://www.cqvip.com/qk/91143a/201318/47495922.html). And finally, considering that the ADC value of metastatic pelvic LN was much lower than those without LN metastasis, we postulated that the detection of mean ADC values measurement with DWI could have referential effects on the pelvic LN metastasis among CC patients, and supporting that the ADC value is a robust indicator of metastatic nodes.
A subgroup analysis was conducted to evaluate the influence of country and MRI machine type on the significant relationship of lower ADC value and pelvic LN metastasis in CC patients. From the country-stratified analysis, we could know that the relationship of ADC and pelvic LN metastasis was unaffected in Japan and UK, which could be explained by the possible environment differences in different countries. As for the MRI machine type subgroup analysis, the relationship of ADC and pelvic LN metastasis could not be affected by GE 1.5T, GE 3.0T, and Philips 1.5T, but could be affected by Siemens 3.0T and Siemens 1.5T, possibly due to the difference and deviation of detection methods.
Although there was significant difference with regard to the mean ADC values between CC patients with pelvic LN metastasis and without LN metastasis, several limitations of this study should be taken into noted. First and mostly, the mean ADC value of malignant nodes was apparently lower in our study, but overlap was encountered in some cases, which was potentially correlated with the different tumor invasion degree of LN metastasis, and the degree of inflammatory lymph node hyperplasia, yet we failed to continue this topic. Additionally, our inclusions of CC patients were relatively small, and resident included were too single (only one trial conducted among Caucasians), this could have influenced our results by revealing no strongly statistic reliability. Finally, we could not ensure a node-by-node correspondence between DWI and histopathology, and hence there might be a possibility that it would be not so identical regarding the analyzed LNs and the actual LNs metastasis. Ignoring these limitations, nevertheless, our study eventually concluded a usefulness of DWI in differentiating metastatic pelvic LN in CC patients.
Collectively, mean ADC value measured from DWI maps of metastatic pelvic LN showed an apparently decreased level as compared to that of tissues without LN metastasis. The combination of the detect-ability of high signal intensity on DWI and the threshold ADC value may therefore holds a higher diagnostic accuracy for the differential diagnosis of metastatic LN in CC from the non-metastatic ones. Recent advance with future refinement of DWI techniques will improve the image quality and accuracy of this technique to a larger clinical application.
| > Acknowledgments|| |
We would like to acknowledge the reviewers for their helpful comments on this paper.
| > References|| |
Nakamura K, Kajitani S, Joja I, Haruma T, Fukushima C, Kusumoto T, et al.
The post treatment mean apparent diffusion coefficient of primary tumor is superior to pretreatment ADC mean of primary tumor as a predictor of prognosis with cervical cancer. Cancer Med 2013;2:519-25.
Bygbjerg IC. Double burden of noncommunicable and infectious diseases in developing countries. Science 2012;337:1499-501.
Makino H, Kato H, Furui T, Morishige K, Kanematsu M. Predictive value of diffusion-weighted magnetic resonance imaging during chemoradiotherapy for uterine cervical cancer. J Obstet Gynaecol Res 2014;40:1098-104.
Sima N, Cheng X, Ye F, Ma D, Xie X, Lu W. The over expression of scaffolding protein NEDD9 promotes migration and invasion in cervical cancer via tyrosine phosphorylated FAK and SRC. PLoS One 2013;8:e74594.
Liu T, Liu Y, Bao X, Tian J, Liu Y, Yang X. Over expression of TROP2 predicts poor prognosis of patients with cervical cancer and promotes the proliferation and invasion of cervical cancer cells by regulating ERK signaling pathway. PLoS One 2013;8:e75864.
Somoye G, Harry V, Semple S, Plataniotis G, Scott N, Gilbert FJ, et al.
Early diffusion weighted magnetic resonance imaging can predict survival in women with locally advanced cancer of the cervix treated with combined chemo-radiation. Eur Radiol 2012;22:2319-27.
Chang B, Kim J, Jeong D, Jeong Y, Jeon S, Jung SI, et al.
Klotho inhibits the capacity of cell migration and invasion in cervical cancer. Oncol Rep 2012;28:1022-8.
Cheng YM, Chou CY, Hsu YC, Chen MJ, Wing LY. The role of human papillomavirus type 16 E6/E7 oncoproteins in cervical epithelial-mesenchymal transition and carcinogenesis. Oncol Lett 2012;3:667-71.
Luhn P, Walker J, Schiffman M, Zuna RE, Dunn ST, Gold MA, et al.
The role of co-factors in the progression from human papillomavirus infection to cervical cancer. Gynecol Oncol 2013;128:265-70.
Nogueira L, Brandao S, Matos E, Nunes RG, Ferreira HA, Loureiro J, et al.
Diffusion-weighted breast imaging at 3 T: Preliminary experience. Clin Radiol 2014;69:378-84.
Lin G, Ho KC, Wang JJ, Ng KK, Wai YY, Chen YT, et al.
Detection of lymph node metastasis in cervical and uterine cancers by diffusion-weighted magnetic resonance imaging at 3T. J Magn Reson Imaging 2008;28:128-35.
Park JJ, Kim CK, Park SY, Park BK, Lee HM, Cho SW. Prostate cancer: Role of pretreatment multiparametric 3-T MRI in predicting biochemical recurrence after radical prostatectomy. AJR Am J Roentgenol 2014;202:459-65.
Baba S, Isoda T, Maruoka Y, Kitamura Y, Sasaki M, Yoshida T, et al.
Diagnostic and prognostic value of pretreatment SUV in 18F-FDG/PET in breast cancer: Comparison with apparent diffusion coefficient from diffusion-weighted MR imaging. J Nucl Med 2014;55:736-42.
Chong Y, Kim CK, Park SY, Park BK, Kwon GY, Park JJ. Value of diffusion-weighted imaging at 3 T for prediction of extracapsular extension in patients with prostate cancer: A preliminary study. AJR Am J Roentgenol 2014;202:772-7.
Pierce TT, Provenzale JM. Evaluation of apparent diffusion coefficient thresholds for diagnosis of medulloblastoma using diffusion-weighted imaging. Neuroradiol J 2014;27:63-74.
Schmid-Tannwald C, Dahi F, Jiang Y, Ivancevic MK, Rist C, Sethi I, et al.
DW-MRI of liver lesions: Can a single ADC-value represent the entire lesion? Clin Radiol 2014;69:492-8.
Kim BJ, Kim HJ, Lee DH, Kwon SU, Kim SJ, Kim JS, et al.
Diffusion-weighted image and fluid-attenuated inversion recovery image mismatch: Unclear-onset versus clear-onset stroke. Stroke 2014;45:450-5.
Inoue M, Mlynash M, Christensen S, Wheeler HM, Straka M, Tipirneni A, et al.
Early diffusion-weighted imaging reversal after endovascular reperfusion is typically transient in patients imaged 3 to 6 hours after onset. Stroke 2014;45:1024-8.
McDonald ES, Schopp JG, Peacock S, DeMartini WB, Rahbar H, Lehman CD, et al.
Diffusion-weighted MRI: Association between patient characteristics and apparent diffusion coefficients of normal breast fibroglandular tissue at 3 T. AJR Am J Roentgenol 2014;202:496-502.
Lautz J, Kessler H, van Gunsteren WF, Weber HP, Wenger RM. On the dependence of molecular conformation on the type of solvent environment: A molecular dynamics study of cyclosporin A. Biopolymers 1990;29:1669-87.
Downey K, Riches SF, Morgan VA, Giles SL, Attygalle AD, Ind TE, et al.
Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: Quantitative histogram analysis of diffusion-weighted MR images. AJR Am J Roentgenol 2013;200:314-20.
Wang BX, Cheng JL. Value of 3t MR ADC in pelvic lymph nodes of cervical cancer. J Med Forum 2013;34:48-9.
Nakai G, Matsuki M, Inada Y, Tatsugami F, Tanikake M, Narabayashi I, et al.
Detection and evaluation of pelvic lymph nodes in patients with gynecologic malignancies using body diffusion-weighted magnetic resonance imaging. J Comput Assist Tomogr 2008;32:764-8.
Liu L, Pan Y, Ning G. Diagnosis of metastasis from non-metastatic lymph nodes in cervical cancers using diffusion weighted imaging with background suppression at 3T magnetic resonance. J Sichuan Univ (Med Sci Edit) 2014;45:159-63.
Kuang F, Ren J, Zhong Q, Liyuan F, Huan Y, Chen Z. The value of apparent diffusion coefficient in the assessment of cervical cancer. Eur Radiol 2013;23:1050-8.
Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of QUADAS: A tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 2003;3:25.
Jackson D, White IR, Riley RD. Quantifying the impact of between-study heterogeneity in multivariate meta-analyses. Stat Med 2012;31:3805-20.
Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Comparison of two methods to detect publication bias in meta-analysis. JAMA 2006;295:676-80.
Zintzaras E, Ioannidis JP. Heterogeneity testing in meta-analysis of genome searches. Genet Epidemiol 2005;28:123-37.
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21:1539-58.
Song F, Gilbody S. Bias in meta-analysis detected by a simple, graphical test. Increase in studies of publication bias coincided with increasing use of meta-analysis. BMJ 1998;316:471.
Park SO, Kim JK, Kim KA, Park BW, Kim N, Cho G, et al.
Relative apparent diffusion coefficient: Determination of reference site and validation of benefit for detecting metastatic lymph nodes in uterine cervical cancer. J Magn Reson Imaging 2009;29:383-90.
Kim JK, Kim KA, Park BW, Kim N, Cho KS. Feasibility of diffusion-weighted imaging in the differentiation of metastatic from nonmetastatic lymph nodes: Early experience. J Magn Reson Imaging 2008;28:714-9.
Chen YB, Liao J, Xie R, Chen GL, Chen G. Discrimination of metastatic from hyperplastic pelvic lymph nodes in patients with cervical cancer by diffusion-weighted magnetic resonance imaging. Abdom Imaging 2011;36:102-9.
Zheng YS, Song XQ, Xu HW, Yang RW. The clinical applications of DWI in the diagnosis of pelvic lymph nodes of cervical cancer. Mod Med Health 2013;29:2801-2.
Kim MH, Kim JK, Lee Y, Park BW, Lee CK, Kim N, et al.
Diagnosis of lymph node metastasis in uterine cervical cancer: Usefulness of computer-aided diagnosis with comprehensive evaluation of MR images and clinical findings. Acta Radiol 2011;52:1175-83.
Nakamura K, Joja I, Nagasaka T, Haruma T, Hiramatsu Y. Maximum standardized lymph node uptake value could be an important predictor of recurrence and survival in patients with cervical cancer. Eur J Obstet Gynecol Reprod Biol 2014;173:77-82.
Liu Y, Liu H, Bai X, Ye Z, Sun H, Bai R, et al.
Differentiation of metastatic from non-metastatic lymph nodes in patients with uterine cervical cancer using diffusion-weighted imaging. Gynecol Oncol 2011;122:19-24.
Payne GS, Schmidt M, Morgan VA, Giles S, Bridges J, Ind T, et al.
Evaluation of magnetic resonance diffusion and spectroscopy measurements as predictive biomarkers in stage 1 cervical cancer. Gynecol Oncol 2010;116:246-52.
Yu SP, He L, Liu B, Zhuang XZ, Liu MJ, Hu XS. Differential diagnosis of metastasis from non-metastatic lymph nodes in cervical cancers: Pilot study of diffusion weighted imaging with background suppression at 3T magnetic resonance. Chin Med J (Engl) 2010;123:2820-4.
Zhang J, Ren C, Xue HD, Zhou HL, Sun ZY, Jin ZY. Value of diffusion-weighted imaging in diagnosis of lymph node metastasis in Patients with Cervical Cancer. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 2014;36:73-8.
Abdel Razek AA, Soliman NY, Elkhamary S, Alsharaway MK, Tawfik A. Role of diffusion-weighted MR imaging in cervical lymphadenopathy. Eur Radiol 2006;16:1468-77.
Liu Y, Bai R, Sun H, Liu H, Wang D. Diffusion-weighted magnetic resonance imaging of uterine cervical cancer. J Comput Assist Tomogr 2009;33:858-62.
Holzapfel K, Duetsch S, Fauser C, Eiber M, Rummeny EJ, Gaa J. Value of diffusion-weighted MR imaging in the differentiation between benign and malignant cervical lymph nodes. Eur J Radiol 2009;72:381-7.
Junping W, Tongguo S, Yunting Z, Chunshui Y, Renju B. Discrimination of axillary metastatic from nonmetastatic lymph nodes with PROPELLER diffusion-weighted MR imaging in a metastatic breast cancer model and its correlation with cellularity. J Magn Reson Imaging 2012;36:624-31.
Heusner TA, Kuemmel S, Koeninger A, Hamami ME, Hahn S, Quinsten A, et al.
Diagnostic value of diffusion-weighted magnetic resonance imaging (DWI) compared to FDG PET/CT for whole-body breast cancer staging. Eur J Nucl Med Mol Imaging 2010;37:1077-86.
Choi BB, Kim SH, Kang BJ, Lee JH, Song BJ, Jeong SH, et al.
Diffusion-weighted imaging and FDG PET/CT: Predicting the prognoses with apparent diffusion coefficient values and maximum standardized uptake values in patients with invasive ductal carcinoma. World J Surg Oncol 2012;10:126.
Martincich L, Deantoni V, Bertotto I, Redana S, Kubatzki F, Sarotto I, et al.
Correlations between diffusion-weighted imaging and breast cancer biomarkers. Eur Radiol 2012;22:1519-28.
Kosucu P, Tekinbas C, Erol M, Sari A, Kavgaci H, Oztuna F, et al.
Mediastinal lymph nodes: Assessment with diffusion-weighted MR imaging. J Magn Reson Imaging 2009;30:292-7.
Park SH, Moon WK, Cho N, Chang JM, Im SA, Park IA, et al.
Comparison of diffusion-weighted MR imaging and FDG PET/CT to predict pathological complete response to neoadjuvant chemotherapy in patients with breast cancer. Eur Radiol 2012;22:18-25.
Koh DM, Collins DJ. Diffusion-weighted MRI in the body: Applications and challenges in oncology. AJR Am J Roentgenol 2007;188:1622-35.
Assaf Y, Mayk A, Cohen Y. Displacement imaging of spinal cord using q-space diffusion-weighted MRI. Magn Reson Med 2000;44:713-22.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]