|Year : 2016 | Volume
| Issue : 2 | Page : 864-870
Apparent diffusion coefficient measurements with diffusion-weighted imaging for differential diagnosis of soft-tissue tumor
Yu Zou1, Qi-Dong Wang2, Min Zong3, Yue-Fen Zou3, Hai-Bin Shi3
1 Department of Radiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, P. R. China
2 Department of Radiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, P. R. China
3 Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, P. R. China
|Date of Web Publication||25-Jul-2016|
Department of Radiology, School of Medicine, The First Affiliated Hospital, Zhejiang University, No. 79, Qingchun Road, Hangzhou 310003
P. R. China
Source of Support: None, Conflict of Interest: None
Objectives: To evaluate the diagnostic potential of apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) in distinguishing malignant and benign soft-tissue tumors.
Materials and Methods: Published studies were retrieved through comprehensive search in various computerized databases. High-quality studies relevant to ADC values of DWI in differential diagnosis of soft-tissue tumors were screened using our stringent inclusion and exclusion criteria for this meta-analysis. The standard mean difference with 95% confidence interval (95% CI) was estimated. Statistical analyses were performed using the STATA statistical software (Stata Co., College Station, TX, USA).
Results: Thirteen cohort studies were finally included, and these studies provided the required information on the diagnostic value of diffusion magnetic resonance imaging in soft-tissue tumors. The 13 studies contained a combined total of 344 malignant soft tumors and 315 benign soft tumors. The results of our meta-analysis revealed that mean ADC value in patients with malignant soft-tissue tumor decreased significantly in comparison with the ADC values obtained in patients with benign soft-tissue tumor (P < 0.001). Country-stratified analysis suggested that ADC value might play a predictive role in the differential diagnosis of soft-tissue tumors in China (P = 0.007), Egypt (P < 0.001), Germany (P = 0.001), Japan (P = 0.049), and The Netherlands (P < 0.001).
Conclusion: Our results provide strong evidence that patients diagnosed with malignant soft-tissue tumors have low ADC values of DWI compared to those with benign soft-tissue tumors. Therefore, ADC measurements with DWI may be reliable in differential diagnosis of soft-tissue tumors.
Keywords: Apparent diffusion coefficient, diffusion-weighted magnetic resonance imaging, meta-analysis, soft-tissue tumor
|How to cite this article:|
Zou Y, Wang QD, Zong M, Zou YF, Shi HB. Apparent diffusion coefficient measurements with diffusion-weighted imaging for differential diagnosis of soft-tissue tumor. J Can Res Ther 2016;12:864-70
|How to cite this URL:|
Zou Y, Wang QD, Zong M, Zou YF, Shi HB. Apparent diffusion coefficient measurements with diffusion-weighted imaging for differential diagnosis of soft-tissue tumor. J Can Res Ther [serial online] 2016 [cited 2020 Jul 12];12:864-70. Available from: http://www.cancerjournal.net/text.asp?2016/12/2/864/164700
| > Introduction|| |
Soft-tissue tumors, arising from ectodermal and mesodermal layers, are comprised of a biologically diverse group of soft-tissue tumors that are infrequent. Soft-tissue tumors can generally be classified into two main categories, that is, soft-tissue sarcomas and benign tumors, and these tumors can occur at any age and present at any site. An estimated 2500 people are affected by soft-tissue tumors in the United Kingdom alone each year. In children under the age of one year, approximately 16 cases from 1000,000 children were reported, indicating that the incidence of soft-tissue tumor is relatively rare in children. However, epidemiological studies have revealed that the average 5-year survival rate in patients with soft-tissue tumors is only 60%, and the mortality rate of patients with soft-tissue tumors is higher than expected. Also, a recent epidemiologic study also found that the recurrence rates in these patients are very high at 70–90%. As a heterogeneous group of tumors, soft-tissue tumors arise as a result of a complex interaction between genetic components and environmental influences such as congenital anomalies, immunosuppression, and malformation syndromes. Several studies have demonstrated that the apparent diffusion coefficient (ADC) value, calculated by diffusion-weighted imaging (DWI), is a useful and valuable diagnostic tool for soft-tissue tumors.,
DWI detects the micro-structural features through measurement of molecular of the water diffusion and is a noninvasive method and one of the most promising imaging techniques, representing a significant technological advancement in medical diagnostic imaging. Compared with conventional magnetic resonance imaging (MRI) techniques, DWI has a variety of advantages such as a higher contrast resolution, a better detectability, and faster image acquisition.,, The principle of DWI in routine clinical practice is related to the unique biologic information available from this method, including cell membrane integrity and tumor cell density, by probing the random movement of water molecules at a submicroscopic scale without using a contrast agent. Therefore, DWI is applicable to a number of diseases such as bone tumor, glioma, and demyelinating diseases., The ADC value, calculated by the DWI, is sensitive to biophysical characteristics including cell density, tumor cellularity, and microstructure. Also, the ADC value might be changed by transformation of the extracellular space, as seen in proliferating cancer cells. Consequently, a recent report showed that the ADC value might differentiate malignant soft-tissue tumor from the benign tumor by detecting the diffusion of water molecules to reflect cell density. Accordingly, the ADC value for benign soft-tissue tumors was found to be higher than the ADC value of malignant soft-tissue tumor. Notably, while some studies observed an association of ADC value in differential diagnosis of soft-tissue tumors,, other studies showed contradictory results., The main purpose of this meta-analysis was to investigate the accurate relationship between the diagnosis of soft-tissue tumors and ADC values of DWI.
| > Materials and Methods|| |
Published studies, which assessed the diagnostic accuracy of DWI for differentiating the benign and malignant soft-tissue tumor by calculating ADC value, were obtained by searching the following computerized databases without restrictions of language or data collection: PubMed, EMBASE, MEDLINE, the Cochrane Library Database, Chinese Biomedical Database, the Chinese Journal Full-Text Database, and the Weipu Journal Database. The database searches used the following as medical subject heading terms and text words: “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 “soft-tissue neoplasms” or “muscle neoplasms” or “vascular neoplasms” or “soft-tissue neoplasm” or “soft-tissue tumor” or “soft-tissue cancer” or “soft-tissue carcinoma” or “soft-tissue tumor” or “muscle neoplasm” or “muscle tumor” or “muscle cancer” or “muscle carcinoma” or “vascular neoplasm” or “vascular tumor” or “vascular cancer”. Manual searches were used to identify studies from cross-references.
Full-text articles were retrieved and assessed for their suitability using the following inclusion criteria: (1) Only those clinical cohort studies conducted within a human population to examine the diagnostic accuracy of DWI for differentiating the benign and malignant soft-tissue tumor by calculating ADC value were incorporated; (2) patients with benign and malignant soft-tissue tumor should be confirmed by the biopsy; (3) the publication should be in a peer-reviewed journal and contain original data; and (4) must supply sufficient information on the ADC value in the benign and malignant soft-tissue tumor tissues. The study were excluded based on the following exclusion criteria: (1) Did not meet the inclusion criteria; (2) abstracts, reviews, case report, letters, meta-analyses, or proceedings; (3) duplicate publications or studies with overlapping data; and (4) subgroup analysis of the included trials.
Study quality and data extraction
Two experienced reviewers independently evaluated the eligibility of the included trials using the quality assessment of diagnostic accuracy studies (QUADAS). The 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. QUADAS ranged from 0 to 14; and a score ≥10 revealed a good methodological quality. A standard reporting form was used to extract data from each included study, and the following detailed information were collected:First author, year, country, ethnicity, study design, number of cases and controls, demographic variables, MRI machine type, MRI machine type code, b value (s/mm 2), ADC (×10−3 mm 2/s), and the confirmation of diagnosis. Disagreement during study selection was resolved by discussion or consultation with a third investigator.
The ADC value was estimated by the standard mean difference (SMD) with 95% confidence interval (95% CI). We used Cochran's Q-statistic (P < 0.05 was considered significant) and I2 tests to quantify heterogeneity among studies. In order to calculate the pool SMDs, fixed/random effects model were used. Random effects model was applied in case of significant heterogeneity (P < 0.05 or I2 test exhibited >50%), otherwise SMDs were pooled based on the fixed-effects model., When there was significant heterogeneity, subgroup analysis was performed to find potential explanatory cause. Also, we employed a sensitivity analyses to evaluate whether one single study had the weight to impact the overall estimate. Further, the effect of publication bias was detected by Egger's linear regression test (P < 0.05 was considered significant) to evaluate the funnel plot asymmetry whose asymmetric plot revealed possible publication bias., Statistical analyses were performed using the STATA statistical software (version 12.0, Stata Co., College Station, TX, USA).
| > Results|| |
[Figure 1] shows the study selection process. A total of 113 articles were retrieved through electronic database search and manual search, and 38 articles were retained after removing duplicates (n = 2), letters, reviews or meta-analyses (n = 16), nonhuman studies (n = 27), and studies unrelated to research topics (n = 30). Further, an additional 23 studies were removed for not being case–control (n = 3), not relevant to diffusion MRI (n = 8), or irrelevant to soft-tissue tumors (n = 12). In the final selection step, 13 of 15 studies were identified as suitable for inclusion into the meta-analysis, with two articles being abandoned for not supplying enough information.,,,,,,,,,,,, The thirteen cohort studies, published between 2002 and 2014, provided the required information on the diagnostic value of diffusion MRI in soft-tissue tumors. Detailed information on the patients with soft-tissue tumors and baseline characteristics of the eligible studies are summarized in [Table 1]. Eleven studies were performed in Asian population (China, Egypt, and Japan), and the remaining two studies were in Caucasians (Germany and The Netherlands). The 13 studies contained 344 malignant tumors and 315 benign tumors. ADC value in soft-tissue tumor patients was detected with GE 1.5T, GE 3.0T, Siemens 1.5T, Siemens 3.0T, and Philips 1.5T. b values in the enrolled studies ranged from 50 to 1000 s/mm 2.
|Figure 1: Flowchart shows the study selection procedure. Thirteen studies were included in this meta-analysis|
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|Table 1: Baseline characteristics and methodological quality of all included studies|
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Apparent diffusion coefficient values in soft-tissue tumor
As shown in [Figure 2], the pooled SMDs for ADC value revealed that the mean ADC value in patients with soft-tissue tumor decreased significantly compared to patients with benign tissue (SMD = 1.26, 95% CI: 0.73–1.79, P < 0.001). Subgroup analysis based on country and detection method implicated that ADC value plays a predictive role in soft-tissue tumor in all subgroups: China (SMD = 1.18, 95% CI: 0.32–2.03, P = 0.007), Egypt (SMD = 2.18, 95% CI: 1.34–3.02, P < 0.001), Germany (SMD = 1.33, 95% CI: 0.57–2.10, P = 0.001), Japan (SMD = 0.95, 95% CI: 0.00–1.89, P = 0.049), The Netherlands (SMD = 2.08, 95% CI: 1.02–3.13, P < 0.001), Siemens 1.5T subgroup (SMD = 1.68, 95% CI: 0.98–2.39, P < 0.001), Siemens 1.5T/3.0T subgroup (SMD = 1.33, 95% CI: 0.57–2.10, P = 0.001), and Philips 1.5T subgroup (SMD = 2.08, 95% CI: 1.02–3.13, P < 0.001) as shown in [Figure 3]a and [Figure 3]b. Another subgroup based on b value demonstrated that the ADC value in benign tissue was evidently elevated compared to soft-tissue tumor when b value >500 s/mm 2 (SMD = 1.37, 95% CI = 0.81–1.94, P < 0.001), whereas no significant difference on ADC value was detected between benign tissue and soft-tissue tumor when b value ≤500 s/mm 2 (SMD = 0.82, 95% CI = −0.84–2.49, P = 0.332) [Figure 3]c.
|Figure 2: Forest plots on the difference of diffusion-weighted imaging with apparent diffusion coefficient in differential diagnosing of soft-tissue tumor|
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|Figure 3: Subgroup analyzes the difference of diffusion-weighted imaging with apparent diffusion coefficient in differential diagnosing of soft-tissue tumor ((a) subgroup results based on country; (b) subgroup results based on detection method; (c) subgroup results based on b value)|
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Sensitivity analysis and publication bias
We further conducted sensitivity analyses to determine whether the results of our analysis were affected by the choice of any single study. Our results suggested no single study had an effect on the pooled SMDs [Figure 4]. The funnel plots presented to be symmetrical, and Egger's test revealed no publication bias (t = 1.16, P = 0.270) [Figure 5].
|Figure 4: Sensitivity analysis of the summary odds ratio coefficients on the difference of diffusion-weighted imaging with apparent diffusion coefficient in differential diagnosing of soft-tissue tumor|
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|Figure 5: Funnel plot of publication biases on the difference of diffusion-weighted imaging with apparent diffusion coefficient in differential diagnosing of soft-tissue tumor|
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| > Discussion|| |
In this meta-analysis, we extracted data from previous studies to investigate the clinical value of ADC values of DWI in the diagnosis of soft-tissue carcinomas. We found that the ADC value is significantly lower in malignant soft-tissue tumor compared to benign tumor, suggesting that the ADC value has a vital significance in discriminating between malignant and benign tumor, and serve as an important tool for early diagnosis of soft-tissue tumors. Evidence from previous studies showed that the accuracy of DWI detection depends on the average ADC values, which relates to tumor size and type and has been successfully employed to diagnose malignancies and to detect relapse in musculoskeletal tumors. When compared with benign cysts, lower ADC values were observed in solid masses, suggesting that malignant tissues have more resistance to water diffusion, thus decreasing ADC values. The variability of DWI is well-known and affects the diagnosis of soft-tissue carcinomas, but lower ADC value is identified in nonmyxoid malignant tumors compared with benign tumors due to dense cellularity. Additionally, in hemangiopericytoma, a rare soft-tissue tumor, follow-up after radiotherapy or chemotherapy, is related to ADC mapping and high ADC value means tumor necrosis and restoration of water molecule diffusion, which indicates the feasibility of DWI and ADC value to functionally evaluate tumors for their aggressiveness or treatment response. Differences in ADC value in soft-tissue sarcomas are attributed to tumor cell status including tumor cellularity, cell division, differentiation speed, and tumor necrosis, all of which were linked to histological grading of sarcomas, consequently, ADC values have the role in assessing in vivo tumor grades of soft tumor sarcomas. Consistent with our results, Razek et al. found that ADC values are helpful in grading malignancy in soft-tissue tumors, and their results revealed that ADC values in high-grade malignancy were lower due to restricted diffusion.
Subgroup analysis was performed to consider other factors such as country and DWI machine type that may affect the relationship between ADC values and soft-tissue carcinoma diagnosis. A country-stratified analysis showed that the same relationship existed in China, Egypt, Germany, Japan, and The Netherlands, implying that country may not be source of heterogeneity to impact results. The other stratified analysis based on machine type showed that the relationship can be influenced by the use of Siemens 1.5T, Siemens 3.0T, and Philips 1.5T but is not associated with the machine types of GE 1.5T and GE 3.0T. Our study results are partly consistent with previous studies and show that ADC value is correlated with tumor grades of soft-tissue carcinomas, and lower ADC value indicates poor prognostic outcome and decreased survival rates. The subgroup analysis based on b value manifested that the ADC value in benign tissue was evidently elevated compared to soft-tissue tumor in b value >500 s/mm 2 but not in b value ≤ 500 s/mm 2, suggesting that b value plays an important role in the ADC value and DWI image.
There were several limitations in our present meta-analysis. First, the numbers of studies were relatively small, and the sample size of benign or malignant soft-tissue tumors was also relatively small. As a result, this might have influenced the statistical analysis in determining the difference between the ADC values of benign and malignant tumor tissues. Second, retrospective-designed meta-analysis might have a negative effect on the optimization of those acquisition parameters such as the b value and the ADC value that contribute to the production of bias affecting the whole results. Third, different versions of magnetic resonance machine type did influence the detection of water diffusion, and hence the specificity and sensitivity of those involved methods were uncertain, which may restrict the diagnostic accuracy. Finally, no false positive results were available on the ADC values, which indicate there is a need of larger sample size study for the clarification of this issue.
In summary, patients with malignant soft-tissue tumor have low ADC values measurements with DWI as compared to patients with benign soft-tissue tumor. Consequently, ADC measurements with DWI may be reliable imaging techniques in differential diagnosis of soft-tissue tumor. Moreover, to have a better and comprehensive understand the role of DWI in soft-tissue tumors; future study should further investigate the association of ADC value with diverse soft-tissue tumors.
We would like to acknowledge the reviewers for their helpful comments on this paper.
Financial support and sponsorship
This project was supported by the Natural Science Foundation of Zhejiang Province (NO. Y2110172).
Conflicts of interest
There are no conflicts of interest.
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