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. 2019 Mar 5;9:102. doi: 10.3389/fonc.2019.00102

Comparative Diagnostic Accuracy of Contrast-Enhanced Ultrasound and Shear Wave Elastography in Differentiating Benign and Malignant Lesions: A Network Meta-Analysis

Rongzhong Huang 1, Lihong Jiang 1, Yu Xu 2, Yuping Gong 3, Haitao Ran 3, Zhigang Wang 3, Yang Sun 3,*
PMCID: PMC6412152  PMID: 30891425

Abstract

Background: We performed a network meta-analysis to compare the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) in differentiating benign and malignant lesions in different body sites.

Methods: A computerized literature search of Medline, Embase, SCOPUS, and Web of Science was performed using relevant keywords. Following data extraction, we calculated sensitivity, specificity, positive likelihood ratio (LR), negative LR, and diagnostic odds ratio (DOR) for CEUS, and SWE compared to histopathology as a reference standard. Statistical analyses were conducted by MetaDiSc (version 1.4) and R software (version 3.4.3).

Results: One hundred and fourteen studies (15,926 patients) were pooled in the final analyses. Network meta-analysis showed that CEUS had significantly higher DOR than SWE (DOR = 27.14, 95%CI [2.30, 51.97]) in breast cancer detection. However, there were no significant differences between CEUS and SWE in hepatic (DOR = −6.67, 95%CI [−15.08, 1.74]) and thyroid cancer detection (DOR = 3.79, 95%CI [−3.10, 10.68]). Interestingly, ranking analysis showed that CEUS achieved higher DOR in detecting breast and thyroid cancer, while SWE achieved higher DOR in detecting hepatic cancer. The overall DOR for CEUS in detecting renal cancer was 53.44, 95%CI [29.89, 95.56] with an AUROC of 0.95, while the overall DOR for SWE in detecting prostate cancer was 25.35, 95%CI [7.15, 89.89] with an AUROC of 0.89.

Conclusion: Both diagnostic tests showed relatively high sensitivity and specificity in detecting malignant tumors in different organs. Network meta-analysis showed that CEUS had higher diagnostic accuracy than SWE in detecting breast and thyroid cancer, while SWE had higher accuracy in detecting hepatic cancer. However, the results were not statistically significant in hepatic and thyroid malignancies. Further head-to-head comparisons are needed to confirm the optimal imaging technique to differentiate each cancer type.

Keywords: contract enhanced ultrasonography, malignant lesions benign lesions, network meta analysis, shear wave elastography, lesions

Introduction

Ultrasound (US) has been used for decades in differentiating benign and malignant lesions because of its low cost, ease of access, and non-invasiveness. For example, it belongs to the triad (physical examination, mammography and US), commonly used to assess the risk of breast cancer (1). Moreover, it can detect thyroid nodules as small as 2 mm in size and predicts malignancy based on features like irregular border, hypo-echogenicity, and calcification (2, 3). However, none of these features can individually predict malignancy and conventional US alone has shown moderate accuracy in detecting malignant lesions (4). Therefore, improvements to US technique have been sought.

The introduction of contrast agents (contrast-enhanced US/CEUS) allows for visibility of blood flow within the lesion, which improves its characterization (5). The current in-use contrast media are second-generation agents as SonoVue. These agents remain within the intravascular space, which increases their safety and allows for continuous imaging over the enhancement period (6). Several studies have reported high sensitivity and specificity for CEUS in differentiating malignant lesions with the breast, thyroid, liver and kidneys (5, 7–9). A recent meta-analysis showed no significant difference between CEUS and contrast-enhanced computed tomography (CECT) and magnetic resonance imaging (CEMRI) in terms of the diagnostic accuracy in characterizing focal liver lesions (FLLs) (8).

Shear wave elastography (SWE) relies on the degree of lesion stiffness when subjected to external pressure. Malignant nodules have harder consistency (less elasticity) than benign ones due to the uncontrolled proliferation of cancer cells (10). Therefore, SWE has been investigated for differentiating benign and malignant nodules. Compared to conventional US, SWE is more quantitative and is less operator-dependent, allowing more effective detection of malignant tumors (11). Recent diagnostic test accuracy (DTA) studies and meta-analyses showed high sensitivity and specificity for SWE in detecting malignant lesions within the breast and hepatic tissues (11–13).

According to our knowledge, data are lacking on the direct comparison between CEUS and SWE; therefore, we performed a meta-analysis to evaluate the diagnostic accuracy of CEUS and SWE in differentiating malignant tumors in the breast, liver, thyroid, kidneys, and prostate tissues in comparison to histopathology as a reference test. Moreover, we used network meta-analysis (NMA) to compare the diagnostic accuracy of both tests in malignant tumor differentiation.

Materials and Methods

This meta-analysis has been conducted and reported in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (The PRISMA-DTA Statement) (14); Supplementary File I.

Literature Search

We searched Medline (via PubMed), Embase, SCOPUS and Web of Science for diagnostic accuracy studies that evaluated the use of CEUS and SWE in the differentiation of malignant tumors in different body organs. The following search terms were used with different combinations in different databases: Contrast-enhanced Ultrasound OR CEUS OR Ultrasound OR SonoVue OR Shear Wave Elastography OR SWE OR Sonoelastography OR Elastosonography AND Malignant OR Cancer OR Tumor OR Benign OR Adenoma OR Adenocarcinoma OR Carcinoma OR Nodule. No search filters of any sort were used during the search. All retrieved search results from database search (including bibliographic data and abstracts) were imported into EndNote (X7) for duplicate removal and then were transferred to a Microsoft Excel Sheet for screening.

Study Screening

For a study to be eligible for inclusion, it must have matched all the following criteria: (1) Population: Patients, suspected or diagnosed with malignancy in any body organ, (2) Intervention: CEUS or SWE [no specifications by US system or probe type], (3) Comparator: Histopathology, (4) Outcomes: Sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV], and (5) Study type: Diagnostic accuracy study. Two independent authors reviewed the title and abstract of retrieved records against our eligibility criteria and classified them into: eligible, non-eligible, or requires further screening (seems to fit the inclusion criteria, but further confirmation is required). The full-text articles of the latter type were retrieved and underwent a second wave of screening. Any discrepancy between the two reviewers' decisions was solved by a senior reviewer (with a 15-year experience in secondary analysis and evidence synthesis methods) after reviewing the debated studies in reference to the pre-specified PICO criteria.

Data Extraction and Quality Assessment

An extraction sheet (in Microsoft Excel) was formatted and pilot-tested before final extraction. The sheet was customized to extract the baseline data of the imaging device, enrolled patients, as well as the raw diagnostic data of each included study. For pilot testing, two reviewers extracted these data from 5 included studies and the datasets were matched and compared with the original studies by a third reviewer. Each set of data was extracted by two reviewers and discordant decisions were resolved by discussion. These discussions included re-examining the studies, inspecting their available additional data sources and re-evaluating the former decisions. When the discrepancies remained, a senior reviewer examined the studies and settled the differences. The extracted data included (I) baseline characteristics of enrolled participants, (II) study design, (III) diagnostic test parameters: Parameters, cutoff value and US system for SWE and contrast agent, US technique, probe and mechanical index for CEUS, and (IV) Outcome data: true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values. When these values were not directly given, they were calculated from the processed data as sensitivity, specificity, PPV, and NPV, using the statistical calculator on RevMan software (Version 5.3 for Windows). We used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) score to assess the quality of included studies. It consists of 14 (yes/no/unclear) questions to assess different forms of bias within DTA studies (15).

Data Analysis

Pairwise meta-analyses were done under the random-effects model when two or more studies investigated the same predefined research question with the same laboratory test. We extracted the sensitivity, specificity, positive likelihood ratio (LR), negative LR, and diagnostic odds ratio (DOR) values for CEUS and SWE compared to histopathology as a reference standard. The DOR is calculated as (TP X TN)/ (FP X FN) and defined as the odds of having a positive test result in a patient with disease compared with the odds of a positive test result in a patient without disease. Moreover, summary receiver operating characteristic (SROC) curves were constructed to examine diagnostic accuracy. All statistics were reported as absolute values with their 95% confidence interval (95% CI). A p-value < 0.05 was considered statistically significant. The Chi-square and I-square statistics were calculated in order to assess heterogeneity. Significant heterogeneity was considered to be present if the chi-square p-value was < 0.1 (as per the Cochrane Handbook for Systematic Reviews of Intervention). Data were presented into five subgroups according to cancer site: breast, liver, thyroid, kidneys, and prostate. Network meta-analyses were conducted to compare the diagnostic accuracy of CEUS vs. SWE in malignancy detection. Heterogeneity and inconsistency were checked by the I2 and the corresponding p-value. All statistical analyses were conducted on MetaDiSc (version 1.4) and R software (version 3.4.3).

Results

Literature Search and Study Characteristics

Database search retrieved 5896 unique citations. Following title and abstract screening, 422 full-text articles were retrieved for further scrutiny. Finally, 114 diagnostic accuracy studies (65 on SWE and 50 on CEUS; one study by 4 assessed both modalities), reporting data from 15926 patients (5680 for CEUS and 10392 for SWE) were included in our network meta-analysis (Figure 1, Bibliographic details in Supplementary File II). According to the QUADAS score, 25 (21.5%), 30 (25.8%), 22 (18.9%), 23 (19.8%), and 16 (13.8%) studies scored 10, 11, 12, 13, and 14, respectively. The baseline data of enrolled participants, as well as the characteristics of the used US systems for SWE and CEUS tests are illustrated in Tables 1, 2, respectively.

Figure 1.

Figure 1

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PRISMA flow diagram of literature search and study selection.

Table 1.

Baseline characteristics of enrolled patients and criteria of the used SWE system.

References Country Study design Patients/Lesions (N) Age (Years) Male: Female Organ Condition Reference test/Gold standard SWE parameters Cutoff value (Kpa) US system
Li et al. (16) China Prospective cohort 276 (296 lesions) 45.4 ± 14.7 100% F Breast Benign vs. malignant breast masses Histopathology SWS 4.39 m/sec S3000 US scanner (Siemens)
Yang et al. (17, 18) China Retrospective cohort 218 (225 lesions) 45.3 ± 14.6 100% F Breast Benign vs. malignant breast masses Histopathology Emean 36.1 Kpa Aplio500 US machine (Toshiba)
Elmoneam et al. (13) Egypt Prospective cohort 63 (63 lesions) 34.7 ± 5.9 100% F Breast Benign vs. malignant breast masses Histopathology Emax 106.55 Kpa N/A
Kim et al. (19) Korea Retrospective cohort 171 (177 lesions) 45.17 ± 9.37 100% F Breast Small breast lesions < 2 cm Histopathology Emax 87.5 Kpa Aixplorer system (Supersonic Imagine
Youk et al. (20) Korea Prospective cohort 123 (130 lesions) 46.7 ± 11.2 100% F Breast Breast cancer Histopathology Emean 82.2 Kpa Aixplorer ultrasound system
Tang et al. (21) China Prospective cohort 98 (133 lesion) N/A 100% F Breast Benign vs. malignant breast lesion Histopathology Mean SWV 3.68 m/s Siemens S3000 US scanner
Choi et al. (22) Korea Retrospective cohort 54 (56 lesions) 40.76 + 68.07 100% F Breast Benign vs. malignant breast lesion Histopathology Emean 44.3 Kpa Aixplorer US system (SuperSonic Imagine
Liu et al. (12) China Prospective cohort 130 (139 lesions) 44.74 ± 14.77 100% F Breast Benign vs. malignant breast lesion Histopathology Max SWV 5.37 m/s Siemens Acuson S3000 ultra-sound machine
Golatta et al. (23) Germany Prospective cohort 103 (104 lesions) 51 ± 18.56 100% F Breast Benign vs. malignant breast lesion Histopathology Mean SWV 5.18 m/s Siemens Medical Solutions
Youk et al. (24) Korea Retrospective cohort 324 (389 lesions) 46.0 ± 11.4 100% F Breast Benign vs. malignant breast lesion Histopathology Eratio 5.14 Aixplorer US system (SuperSonic Imagine
Ko et al. (25) Korea Retrospective cohort 33 (34 lesions) 46.4 ± 7.5 100% F Breast Breast Non-mass lesions Histopathology Emean 41.6 Kpa Aixplorer US system (SuperSonic Imagine
Lee et al. (26) Korea Prospective cohort 134 (144 lesions) 49.1 ± 12.8 100% F Breast Benign vs. malignant breast lesion Histopathology Emax 147.2 Kpa Aixplorer US system (SuperSonic Imagine
Ng et al. (27) Malaysia Prospective cohort 152 (159 lesions) 52 + 20.5 100% F Breast Benign vs. malignant breast lesion Histopathology Emax 56.0 Kpa Aixplorer ultrasound system (SuperSonic Imagine
Tian et al. (28) China Retrospective cohort 210 (210 lesions) 43.12 ± 13.34 100% F Breast Benign vs. malignant breast lesion Histopathology Emax 80.8 Kpa Aixplorer ultrasound system (SuperSonic Imagine
Olgun et al. (29) Turkey Prospective cohort 109 (115 lesions) 51 + 17.5 0.02:1 Breast Benign vs. malignant breast lesion Histopathology Eratio 4.7 Aixplorer ultrasound system (SuperSonic Imagine
Chang et al. (30) Korea Prospective cohort 115 (133 lesions) 51.4 + 11.75 100% F Breast Benign vs. malignant breast lesion Histopathology Emean 60.7 Kpa IU-22 (Phillips) OR HDI 5000 sonography unit
Yao et al. (31) China Prospective cohort 206 (206 lesions) 44.6 + 13.3 100% F Breast Benign vs. malignant breast lesion Histopathology Mean SWV 4.22 m/s Acuson S2000 ultrasound system (Siemens
Lee et al. (26) Korea Retrospective cohort 139 (156 lesions) 43.54 ± 9.94 100% F Breast Solid breast masses Histopathology Emax 82.3 Kpa Aixplorer ultrasound system (SuperSonic Imagine
Seo et al. (32) Korea Prospective cohort 37 (45 lesions) 47.4 +14.75 100% F Breast Benign vs. malignant breast lesion Histopathology Emean 67.8 Kpa Aplio 500; Toshiba
Au et al. (33) Canada Prospective cohort 112 (123 lesions) 49.2+10.7 100% F Breast Solid breast masses Histopathology Eratio 3.56 Aixplorer Multiwave V3, Supersonic Imagine
Chang et al. (34) Korea Prospective cohort 129 (150 lesions) 47.8+8.83 100% F Breast Benign vs. malignant solid breast lesions Histopathology Emean 80 Kpa Aixplorer, SuperSonic Imagine
Choi et al. (35) Korea Retrospective cohort 113 (116 lesions) 48.4+10 100% F Breast Breast non-mass lesions Histopathology Emean 85.1 Kpa Aixplorer, SuperSonic Imagine
Chung et al. (36) Korea Retrospective cohort 71 (79 lesions) 48+10.67 100% F Breast Breast papillary lesions Histopathology Emax 62.1 Kpa Aixplorer, SuperSonic Imagine
Choi et al. (22) Korea Retrospective cohort 199 (205 lesions) 51.7 ± 13.3 100% F Breast Benign vs. malignant solid breast lesions Histopathology Emean 85.8 Kpa Aixplorer, SuperSonic Imagine
Dobruch-Sobczak et al. (37) Poland Retrospective cohort 76 (84 lesions) 59.9+13 100% F Breast Focal breast lesions Histopathology Eav.adj. 68.5 Kpa Aixplorer, SuperSonic Imagine
Guo et al. (38) China Prospective cohort 379 (404 lesions) N/A 100% F Breast Focal breast lesions Histopathology SWS 3.015 m/s Siemens ACUSON S2000
Hong et al. (39) Korea Prospective cohort 218 (264 lesions) 46.4+10.5 100% F Breast Solid breast masses Histopathology Emax 44.1 Kpa N/A
Kim et al. (40) China Retrospective cohort 67 (67 lesions) 41.5+2.29 100% F Breast Fibroadenoma vs. phylloids tumor Histopathology Emean 43.9 Kpa Aixplorer, SuperSonic Imagine
Klotz et al. (41) France Retrospective cohort 142 (167 lesions) 57.7 +11 100% F Breast Benign vs. malignant solid breast lesions Histopathology Emax 106 Kpa Aixplorer, SuperSonic Imagine
Lee et al. (42) Korea Retrospective cohort 139 (140 lesions) 45.5 + 10.33 100% F Breast Complex cystic and solid breast lesions Histopathology Emax 108.5 Kpa Aixplorer, SuperSonic Imagine
Li et al. (16) China Retrospective cohort 116 (116 lesions) 48.56+ 14.4 100% F Breast Breast lesions BIRADS IV Histopathology SWS 3.49 m/s Siemens S3000 US machine
Shi et al. (43) China Prospective cohort 251 (279 lesions) 45.3 6 11.8 100% F Breast Benign vs. malignant solid breast lesions Histopathology SD 8.05 Kpa Aixplorer, SuperSonic Imagine
Sim et al. (44) UK Retrospective cohort 52 (52 lesions) 67 100% F Breast IDC Histopathology Emean 50 Kpa Aixplorer, SuperSonic Imagine
Sim et al. (44) UK Retrospective cohort 52 (52 lesions) 67 100% F Breast ILC Histopathology Emean 50 Kpa Aixplorer, SuperSonic Imagine
Wu et al. (45) China Retrospective cohort 192 (209 lesions) N/A 100% F Breast Benign vs. malignant solid breast lesions Histopathology N/A N/A Siemens ACUSON S2000
Youk et al. (20) Korea Retrospective 78 (79 lesions) 45.5 + 11.6 100% F Breast Benign vs. malignant solid breast lesions Histopathology Eratio 3.7 Aixplorer, SuperSonic Imagine
Zhang et al. (46) China Prospective cohort 97 (98 lesions) 44.74 ± 14.77 100% F Breast Small breast lesions < 10 cm Histopathology SWV 3.27 m/s Siemens ACUSON S2000
Cong et al. (47) China Prospective cohort 315 (326 lesions) 44.51 + 11.81 100% F Breast Breast masses Histopathology SD 13.75 Aixplorer, SuperSonic Imagine
Park et al. (48, 49) Korea Retrospective cohort 133 (156 lesions) 47.8 ± 12.7 100% F Breast Palpable breast masses Histopathology or periodic imaging surveillance Emax 45.1 Kpa Aixplorer, SuperSonic Imagine
Wang et al. (50) China Retrospective cohort 63 (67 lesions) 40.1 + 21.2 100% F Breast Non-mass breast lesions Histopathology Emax 81.07 Kpa iU22 Philips
Kasai et al. (51) Japan Prospective cohort 273 patients with chronic liver disease 59.64 ± 14.40 70.98 ± 9.33 1:01 Liver HCC Histopathology Young's Modulus N/A Aixplorer US system (SuperSonic Imagine S.A.)
Gerber et al. (52) Germany Prospective cohort 106 (106 lesions) 55.5+16.74 3.8:1 Liver Characterization of solid HFLs Histopathology and CE imaging for benign lesions Emedian 37.6 Kpa Aixplorer ultrasound system (SuperSonic Imagine)
Özmen et al. (53) Turkey Prospective cohort 20 (20 lesions) 4.74+4 2.3:1 Liver Heamangioma vs. malignant liver lesions Histopathology Emean 23.62 Kpa Aixplorer ultrasound system (SuperSonic Imagine)
Tian et al. (54) China Prospective cohort 221 (229 lesions) 48.9 + 13.2 2.4:1 Liver Benign vs. malignant HFLs Histopathology Emax 39.6 Kpa Aixplorer, SuperSonic Imagine
Ahmad et al. (55) UK Prospective cohort 50 (11 with PSA> 20) 69 100% M Prostate Prostate cancer Histopathology Shear wave velocity and Young's modulus N/A SuperSonic Imagine
Boehm et al. (56) Germany Prospective cohort 60 patients with suspected prostate cancer N/A 100% M Prostate Prostate cancer histopathology Young's Modulus 50 Kpa TRUS Aixplorer
Porsch et al. (57) Germany Prospective cohort 69 (794 samples) 65+8 100% M Prostate Prostate cancer Histopathology Young's Modulus 48 Kpa SuperSonic Imagine Ultrasound System AIXPLORER
Woo et al. (58) Korea Prospective cohort 87 (87 lesions) 66 ± 9.0 100% M Prostate Prostate cancer Histopathology Young's Modulus 43.9 Kpa SuperSonic Imagine
Correas et al. (59) France Prospective cohort 184 (1040 samples) 65.1 6 7.6 100% M Prostate Prostate cancer Histopathology Young's Modulus 35 Kpa SuperSonic Imagine
Glybochko et al. (60) Russia Prospective cohort 302 (134 with suspected PC, 120 with confirmed PC and 48 healthy men) N/A 100% M Prostate Prostate cancer Histopathology Young's Modulus 50 Kpa Super Sonic Imagine
Zhang et al. (61, 62) China Prospective cohort 59 (71 lesions) 50.5 ± 9.1 0.4:1 Thyroid Benign vs. malignant thyroid nodules < 10 mm Histopathology Shear wave velocity 2.910 m/s Acuson S2000 Seimens VTTQ
Azizi et al. (63) USA Prospective cohort 676 (707 lesions) 51.2+15 0.2:1 Thyroid Thyroid cancer Histopathology Shear wave velocity 3.54 m/s Virtual Touch IQ Software on the Siemens ACU-SON S3000 US
Liu et al. (12) China Prospective cohort 271 (331 lesions) 45.9 ± 13.4 0.3:2 Thyroid Malignant thyroid nodule Histopathology SWE mean 39.3 Kpa SuperSonic Imagine
Wang et al. (64) China Prospective cohort 322 (322 nodules) 50.5 ± 12.6 0.3:1 Thyroid Malignant thyroid nodule Histopathology Elastic modulous and SWS 3.52 m/s Aplio500, Toshiba Medical Systems
Duan et al. (65) China Prospective cohort 118 (137 lesions) 45.9 ± 13.4 0.6:1 Thyroid Malignant thyroid nodule Histopathology SWE mean 34.5 Aixplorer; Supersonic Imagine
Liu et al. (66) China Prospective cohort 238 (254 lesions) 50.9 ± 11.9 0.3:1 Thyroid Malignant thyroid nodule Histopathology SWS 2.78 m/s N/A
Liu et al. (67) China Retrospective cohort 227 (313 lesions) 46.14 ± 9.70 0.2:1 Thyroid Malignant thyroid nodule Histopathology Emax 51.95 Kpa N/A
Kim et al. (68) Korea Retrospective cohort 99 (99 lesions) 45.7+13 N/A Thyroid Malignant thyroid nodule Histopathology Emean 62 Kpa Aixplorer US system (SuperSonic Imagine)
Deng et al. (69) China Prospective cohort 146 (175 nodules) 46.36 ± 12.5 0.4:1 Thyroid Malignant thyroid nodule Histopathology SWS 2.59 m/s. Siemens Acuson S2000 US machine
Baig et al. (70) China Prospective cohort 122 (163 nodules) 53 ± 13.7 0.2:1 Thyroid Malignant thyroid nodule Histopathology Emax 67.3 Kpa Aixplorer, Supersonic Imagine
Dobruch-Sobczak et al. (71) Poland Prospective cohort 119 (169 lesions) 49.2+14 0.3:1 Thyroid Characterization of thyroid nodules Histopathology Emean 30.5 Kpa Aixplorer, SuperSonic Imagine
Liu et al. (72) China Prospective cohort 49 (64 lesions) 45.3 ± 13.1 0.4:1 Thyroid benign vs. malignant solid Thyroid lesions Histopathology Emean 38.3 Kpa Q-box TM; Super Sonic Imagine
Park et al. (73) Korea Retrospective cohort 453 (476 nodules) 45.7+10.33 0.2:1 Thyroid Benign vs. malignant solid Thyroid lesions Histopathology Emean 85.2 Kpa Aixplorer, SuperSonic Imagine
Samir et al. (74) USA Prospective cohort 35 (35 lesions) 55 + 16.1 0.5:1 Thyroid Benign vs. malignant thyroid follicular lesions Histopathology Young's Modulus 22.3 Kpa Aixplorer, SuperSonic Imagine
Yang et al. (75) China Prospective cohort 107 (107 lesions) 54.0 ± 9.4 0.26:1 Thyroid Benign vs. malignant solid Thyroid lesions Histopathology Mean SWS 3.01 m/s Acuson S3000 (Siemens)
Zhou et al. (76) China Prospective cohort 290 (302 lesions) 49.80+12.34 0.4:1 Thyroid Benign vs. malignant solid Thyroid lesions Histopathology Mean SWS 2.6 m/s Acuson S3000 (Siemens)
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Table 2.

Baseline characteristics of enrolled patients and criteria of the used CEUS system.

References Country Study design Organ Condition Patients/ Lesions (N) Age (Years) Male: Female Contrast agent Reference test US technique Mechanical index Probe
Bertolotto et al. (5) Italy Retrospective Kidney Indeterminate renal masses with equivocal enhancement on CT 47 (30 HP) 65 ± 13 4.75:1 2.4 mL SonoVue Histopathology Pulse inversion harmonic imaging Cadence contrast pulse sequencing 0.05–0.21 Convex array (C5–1) & (4C1) &(C5–2 HDI) & (CA430E)
Cai et al. (77) China Prospective cohort Kidney Benign vs. malignant renal masses 73 (73 lesions) 56.36 ± 12.2 1.6:1 1.0–1.8 mL SonoVue Histopathology and follow up data Acuson Sequoia 512, Siemens, 0.21–0.23 4C1-S convex probe 1–4 MHz
Chang et al. (30) USA Prospective cohort Kidney Renal solid and cystic lesions 44 (23 HP lesions) 56 ± 14 0.7:1 Sonazoid Histopathology and follow up data Siemens Acuson Sequoia 512 0.19 4C1 abdominal transducer
Chen et al. (78, 79) China Prospective cohort Kidney RCC vs. AML 99 (102 lesions) 56.6 ± 16.5 2:01 1.2 ml of SonoVue Histopathology Acuson S2000 (contrast pulse sequencing) N/A N/A
Chen et al. (80) China Prospective cohort Kidney Complex cystic renal masses 59 (71 lesions) 49.6 + 14.25 2.9:1 2.4 mL of SonoVue Histopathology and follow up data Coded phase inversion harmonic imaging (Logiq 9 scanner GE Healthcare) 0.07–0.10 3.5C (2.5–5.0 MHz) and 4C (1.0–4.0 MHz) convex transducers
Defortescu et al. (81) France Prospective cohort Kidney Complex renal cysts 47 (47 lesions) 46 + 9.75 1.8:1 1.2 mL SonoVue Histopathology and follow up data ACUSON S2000-Siemens−10 0.06–0.1 Convex probe 3–4.5 mHz
Li et al. (16) China Retrospective Kidney RCC vs. AML 411 (429 lesions) 54.12 ± 12.57 1.9:1 1.2 mL SonoVue Histopathology E9 system (GE Healthcare 0.11 C1-5, 1–5 MHz
Li et al. (82) China Retrospective Kidney Solid Renal Masses 91 (100 lesions) 62.0 ± 15.6 2.6:1 1.0–1.2 ml SonoVue Histopathology Acuson Sequoia 512 scanner < 0.2 4V1 vector transducer, 1–4 MHz
Lu et al. (83) China Retrospective Kidney RCC vs. AML 189 (189 lesions) 47.3 ± 20.7 1.6:1 1.2 ml SonoVue Histopathology LOGIC E9 < 0.1 C1–5, 1.5 MHz
Nicolau et al. (84) Spain Prospective cohort Kidney Indeterminate renal masses by CT 72 (83 nodules) 64.9 + 14.5 1.9:1 2.4 mL of SonoVue Histopathology and follow up data Cadence contrast pulse sequencing technology (CPS) < 0.2 at Sequoia 512, < 0.009 at S2000) 4C1 convex array probe
Oh et al. (85) Korea Retrospective Kidney RCC vs. AML (small masses) 49 lesions 61+11.5 2.5:1 SonoVue Histopathology N/A N/A N/A
Sanz et al. (86) Spain Prospective cohort Kidney Complex cystic renal masses 66 (67 lesions) 67.8+ 1.83 2.7:1 2.4 mL SonoVue Histopathology Hitachi Preirus N/A EUP-C715 probe (5–1 MHz
Tamas-Szora et al. (87) Romania Prospective cohort Kidney RCC 32 (33 lesions) 60.9 ± 10.43 1:01 1.6 mL of SonoVue Histopathology General Electric Logiq 7 system 0.09–0.11 Convex wide-band transducer (2–5.5 MHz)
Tian et al. (28) China Prospective cohort Kidney Renal SOL 367 (378 lesions) N/A N/A 1.2 mL SonoVue Histopathology ACUSON S2000 Ultrasound System Probe 4C1, 2.5–5 MHz
Wei et al. (88) China Retrospective Kidney Benign vs. malignant solid renal masses 118 (118 lesions) 53.5 ± 12.6 1.6:1 1.6–2.4 mL SonoVue Histopathology Contrast pulse sequence, Sequoia 512 ultrasound system (Siemens 0.18−0.20 4C1, 3–4 MHz
Yong et al. (89) Singapore Retrospective Kidney Undetermined renal masses 63 (74 nodules) 62.4 ± 14.5 1.6:1 1.5 ml of SonoVue Histopathology Aplio 500, Toshiba Medical Systems AND iU22, Philips Healthcare N/A N/A
Zhang et al. (90) China Prospective cohort Kidney Benign vs. malignant thyroid nodules 148 (157 lesions) 45.4 ± 10.5 N/A 2.4 ml SonoVue Histopathology Contrast pulse sequence (CPS) imaging. Acuson, Sequoia 512 Encompass 0.20–0.23 15L8w probe (8–14 MHz)
Miyamoto et al. (91) Japan Prospective cohort Breast Focal breast lesions 127 (127 lesions) 48.5 ± 12.3 :1 0.015 mL/kg Sonazoid Histopathology AplioXG, Toshiba AND, Hitachi-Aloka AND Logiq E9, GE 0.1–0.4 Broadband linear phased-array transducer
Xia et al. (92) China Retrospective Breast Papillary breast lesions 50 (52 lesions) 51 +13.57 :1 2.4 mL SonoVue Histopathology Pulse-inverse harmonic imaging technique [Philips iU22] 0.05–0.08 3–9-MHz linear transducer
Xiao et al. (93) China Prospective cohort Breast Subcentimetric breast lesions 203 (209 lesions) 47+15.25 :1 4.8 mL of SonoVue Histopathology Pulse inversion harmonic technique w iU22 (Philips) 0.06 9–3-MHz linear transducer
Yuan et al. (94) China Prospective cohort Breast Breast tumors 216 (216 lesions) 46 ± 12 :1 2.5 mL SonoVue Histopathology Sequoia; Siemens Medical Solutions N/A 10 MHz transducer
Aubé et al. (95) France Prospective cohort Liver Diagnosis of HCC (< 3 cm) 381 (544 lesions) 62 ± 9.69 4.6:1 SonoVue Histopathology, CT and MRI according to EASL-AASLD N/A N/A N/A
Beyer et al. (96) Germany Retrospective Liver Benign vs. malignant liver nodules 83 (83 lesions) 59.8 +10 2.6:1 1–2.4 ml SonoVue Histopathology LOGIQ E9, GE N/A 1–6 MHz curved probe
Corvino et al. (97) Italy Prospective cohort Liver Cystic and cyst like liver lesions 48 (50 lesions) 65+15 0.9:1 2.4 or 4.8 mL SonoVue Histopathology MyLab 70 Twice scanner (Esaote) N/A D multifrequency (2.5–5 MHz) convex probes
Feng et al. (98) China Retrospective Liver HCC differentiation 271 (374 lesions) 49.25 + 17 3.9:1.0 2.4 mL SonoVue Histopathology iU22 system (Philips) < 0.1 (5–2 MHz) convex transducer (C5-2).
Iwamoto et al. (99) Japan Retrospective Liver Macroscopic HCC 77 (79 lesions) 70 ± 9 2.7:1 0.015 ml/kg Sonazoid Histopathology (tissue harmonic grayscale imaging) LOGIQ 7 or E9 US 0.2–0.3 Convex or linear probes with a frequency of 2–5 or 4–9 MHz
Kobayashi et al. (100) Japan Retrospective Liver NS-HCC 85 (85 lesions) 66 + 13.75 2.9:1 0.015 ml/kg Sonazoid Histopathology Wide-band pulse-inversion harmonic imaging (HI VISION Ascendus (Hitachi)) 0.16–0.2 Microconvex probe (EUP- C715, 3.5 MHz
Kobayashi et al. (101) Japan Retrospective Liver Liver metastasis 98 (148 lesions) 66.46 ± 11.2 1.7:1 0.0075 mL/kg Sonazoid Histopathology SSA 770 A or 790 A US system (Toshiba) 0.17–0.27 3.75-MHz convex probe
Liu et al. (12) China Prospective cohort Liver Hyperechoic HFL 102 (135 lesions) 51.4 ± 12.5 2.8:1 1.5 mL of SonoVue Histopathology GE Logiq9 color Doppler ultrasonography 0.11 convex array probe (frequency: 3.5–5 MHz)
Quaia et al. (102) Italy Retrospective Liver Benign vs. malignant liver lesions in cirrhotic patients 46 (55 lesions) 55 ± 10 0.8:1 2.4 mL SonoVue Histopathology Sequoia, Acuson-Siemens AND iU22 (iU22; Philip) 0.09–0.14 Convex array 2–4 MHz 4C1 transducer AND 2–5-MHz broadband curvilinear probe
Sandrose et al. (103) USA Retrospective Liver CT undetermined HFL 78 (163 lesions) 61.8 + 15.25 1.1:1 1.2 ml bolus of SonoVue Histopathology and PET/CT follow up Pulse inversion harmonic imaging (GE LOGIQ 9E) N/A N/A
Schellhaas et al. (104) Germany Prospective cohort Liver HCC by CEUS and ESCULAP 100 (100 lesions) 66.1 + 7.17 5.7:1 1.5 ml SonoVue Histology and imaging GE Logiq E9 AND Siemens Acuson S2000 AND Toshiba Aplio 500 N/A N/A
Tada et al. (105) Japan Prospective cohort Liver Macroscopic HCC 99 (99 lesions) 67.8 ± 10.4 2.7:1 0.015 ml/kg of Sonazoid Histopathology Wideband harmonic imaging (Aplio XG system, Toshiba) (0.18–0.28) 5-MHz convex transducer 1.4 and 5.3 MHz
Thakur et al. (106) India Prospective cohort Liver HCC 50 (50 lesions) 52 + 14.25 1.4:1 2.4 ml SonoVue Histopathology, CT and MRI Xario XG (Toshiba) < 0.2
Wang et al. (64) Germany Prospective cohort Liver Superficial HFL 27 (27 lesions) N/A 2.4:1 2.4 ml SonoVue Histopathology, one patient by MRI Philips iU22, LOGIQ E9, Aplio 500 N/A High frequency transducer (7.5–12 MHz)
Wu et al. (107) China Prospective cohort Liver Focal hepatic lesions 46 (55 lesions) 46.5 + 15.2 1.2:1 2.4-mL dose of SonoVue Histopathology, CECT and MRI Philips iU22 US system 0.06 5C2 multi- frequency convex probe
Yin et al. (108) China Prospective cohort Liver Cholangiocarcinoma vs. inflammatory lesions 40 (40 lesions) 58.7 + 9.701 1.4:1 1.5 mL of SonoVue Histopathology LOGIQ E9 (GE Healthcare) < 0.1 C5-1, 2.0–4.0 MHz
Zhang et al. (109) China Prospective cohort Liver Benign vs. malignant liver lesions 156 (176 lesions) 50.7 + 16.25 1.9:1 2.4 mL of SonoVue Histopathology Acuson S2000 ultrasound system Seimens N/A 4C1 convex array probe; frequency 2.0–4.0 MHz
Takahashi et al. (110) Japan Prospective cohort Liver HFL < 30 mm 56 (67 lesions) 65.8 ± 10.1 2.5:1 0.0075 mL/kg Sonazoid Histopathology SSA-790A ultrasound system (Aplio (0.20–0.25) 3.75 MHz convex probe
Taimr et al. (111) Canada Prospective cohort Liver Liver metastasis 89 (89 lesions) 31–87 1.6:1 1.5–2.4 mL SonoVue Histopathology Contrast-tuned imaging Hitachi 900 and Hitachi Preirus N/A 2.5–5.0 MHz probe
Cantisani et al. (9) Italy Prospective cohort Thyroid Thyroid nodules 48 (53 lesions) 49.4 + 8.75 2.7:1 4.8 mL SonoVue Histopathology MyLab 70XvG, Esaote N/A Linear probe (7–12 MHz) (N:36)
Deng et al. (69) China Prospective cohort Thyroid Malignant thyroid nodule 146 (175 nodules) 46.36 ± 12.5 0.4:1 2.4 mL of the SonoVue Histopathology Siemens Acuson S2000 US machine 0.1 9L4, 5.0 MHz to 14.0 MHz
Diao et al. (112) China Prospective cohort Thyroid Benign vs. malignant thyroid nodules 77 (87 lesions) 52.4 ± 17.2 N/A 1.5 mL SonoVue Histopathology Siemens Acuson S2000 US 0.06–0.1 5- to 14-MHz linear array transducer (9L4)
Giusti et al. (113) Italy Prospective cohort Thyroid Benign vs. malignant thyroid nodules 63 (HP in 38 lesions) 55.9 ± 14.7 0.2:1 4.8 ml of SonoVue Histopathology MyLab 70 US scanner N/A 7.5-MHz linear probe
Jiang et al. (114) China Prospective cohort Thyroid Benign vs. malignant calcified thyroid nodules 122 (122 nodules) 46 + 12 0.4:1 2.4 mL of the SonoVue Histopathology Contrast pulse sequencing (CPS) (ACUSON Sequoia 512 (Siemens Healthcare) 0.32 15L8w high- frequency linear transducer
Wu et al. (107) China Retrospective Thyroid Benign vs. malignant thyroid nodules 133 lesions 46.3 + 10 0.5:1 1.2 mL SonoVue Histopathology ESAOTE MyLab 90 X-vision 0.05–0.07) L522 (3–9 MHz) linear-array probe
Zhang et al. (46) China Prospective cohort Thyroid Benign vs. malignant thyroid nodules 70 (200 lesions) 49.6 + 12.8 0.3:1 2.0 mL SonoVue Histopathology Acuson S2000 < 0.10 9-MHztransducer
Zhang et al. (90) China Prospective cohort Thyroid Benign vs. malignant thyroid nodules 246 (319 patients) 46.1 ± 15.2 0.5:1 2.4 ml SonoVue Histopathology Contrast pulsed sequencing (CPS) Siemens Acuson S2000 N/A 9 L4 transducer
Zhang et al. (90) China Prospective cohort Thyroid Benign vs. malignant thyroid nodules 111 (145 nodules) 48 + 13.45 0.2:1 1.6 mL SonoVue Histopathology Contrast tuned imaging Mylab Twice Esaote N/A LA522 transducer (3–9 MHz)
Zhou et al. (115) China Prospective cohort Thyroid Benign vs. malignant thyroid nodules 161 (167 lesions) 44.14 + 12.01 0.4:1 2.4 ml SonoVue Histopathology DC-8EXP; Mindray 0.15 L12-3E transducer
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Outcomes of Pair-Wise Meta-Analysis

Breast Cancer

Detailed figures for pairwise meta-analysis in all five organs are illustrated in Supplementary File III. The pooled sensitivity, specificity, positive LR, and negative LR for CEUS in detection of breast malignant lesions were 0.89 (95% CI, 0.85, 0.92), 0.85 (95% CI, 0.81, 0.89), 6.13 (95% CI, 4.70, 8.01), and 0.12 (95% CI, 0.07, 0.21), respectively. The pooled DOR was 49.66 (95% CI, 29.42, 83.82) and the area under the receiving-operating characteristic (AUROC) curve was 0.92, Figure 2A. No heterogeneity was observed for sensitivity (p = 0.15) or specificity (p = 0.95).

Figure 2.

Figure 2

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Summary receiver operating characteristic curve of (A) Contrast Enhanced Ultrasound, and (B) Shear Weight Elastography in breast cancer diagnosis.

For SWE, the pooled sensitivity, specificity, positive LR, and negative LR were 0.84 (95% CI, 0.83, 0.86), 0.86 (95% CI, 0.85, 0.87), 7.12 (95% CI, 5.54, 9.15), and 0.18 (95% CI, 0.15, 0.22), respectively. The pooled DOR was 46.22 (95% CI, 31.33, 68.18) with an AUROC of 0.93, Figure 2B. Significant heterogeneity was observed for sensitivity (p < 0.0001) and specificity (p < 0.0001).

Hepatic Cancer

The pooled sensitivity, specificity, positive LR, and negative LR for CEUS in differentiating malignant hepatic lesions were 0.78 (95% CI, 0.76, 0.81), 0.89 (95% CI, 0.87, 0.91), 6.51 (95% CI, 3.90, 10.85), and 0.13 (95% CI, 0.06, 0.25), respectively. The overall DOR was 57.94 (95% CI, 24.78, 135.45) with an AUROC of 0.95, Figure 3A. The included studies were heterogeneous in the estimates of sensitivity (p < 0.0001) and specificity (p < 0.0001).

Figure 3.

Figure 3

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receiver operating characteristic curve of (A) Contrast Enhanced Ultrasound, and (B) Shear Weight Elastography in hepatic cancer diagnosis.

For SWE, the pooled sensitivity, specificity, positive LR, and negative LR were 0.82 (95% CI, 0.77, 0.87), 0.83 (95% CI, 0.76, 0.89), 4.30 (95% CI, 2.85, 6.48), and 0.29 (95% CI, 0.12, 0.71), respectively. The overall DOR was 14.46 (95% CI, 4.09, 51.04) with an AUROC of 0.90, Figure 3B. The included studies were heterogeneous in the estimates of sensitivity (p < 0.0009) and specificity (p < 0.0001).

Thyroid Cancer

The pooled sensitivity, specificity, positive LR, and negative LR for CEUS in detecting malignant thyroid nodules were 0.81 (95% CI, 0.78, 0.84), 0.88 (95% CI, 0.86, 0.90), 6.01 (95% CI, 3.88, 9.31), and 0.23 (95% CI, 0.17, 0.31), respectively. The overall DOR was 28.54 (95% CI, 16.79, 48.51) with an AUROC of 0.91, Figure 4A. Significant heterogeneity was observed for sensitivity (p = 0.001) and for specificity (p < 0.0001).

Figure 4.

Figure 4

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Summary receiver operating characteristic curve of (A) Contrast Enhanced Ultrasound, and (B) Shear Weight Elastography in thyroid cancer diagnosis.

For SWE, the pooled sensitivity, specificity, positive LR, and negative LR were 0.67 (95% CI, 0.64, 0.69), 0.77 (95% CI, 0.76, 0.79), 3.50 (95% CI, 2.93, 4.18), and 0.33 (95% CI, 0.25, 0.45), respectively. The overall DOR was 11.17 (95% CI, 8.04, 15.51) with an AUROC of 0.84, Figure 4B. Significant heterogeneity was observed for sensitivity (p < 0.0001) and specificity (p < 0.0001).

Renal Cancer

The sensitivity of CEUS ranged from 0.71 to 0.98 with a pooled sensitivity of 0.87 (95% CI, 0.85, 0.88). Specificity ranged from 0.50 to 0.97 with a pooled specificity of 0.84 (95% CI, 0.82, 0.87). The pooled positive and negative LRs were 5.55 (95% CI, 3.74, 8.22) and 0.12 (95% CI, 0.07, 0.19), respectively. The overall DOR was 53.44 (95% CI, 29.89, 95.56) with an AUROC of 0.95, Figure 5A. Significant heterogeneity was observed for sensitivity (p < 0.0001) and specificity (p < 0.0001).

Figure 5.

Figure 5

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Summary receiver operating characteristic curve of (A) Contrast Enhanced Ultrasound in renal cancer diagnosis, and (B) Shear Weight Elastography in prostate cancer diagnosis.

Prostate Cancer

The sensitivity of SWE ranged from 0.42 to 0.96 with a pooled sensitivity of 84% (95% CI, 0.80, 0.87). Specificity ranged from 0.70 to 0.95 with a pooled specificity of 0.84 (95% CI, 0.82, 0.86). The pooled positive and negative LRs were 4.59 (95% CI, 2.68, 7.87) and 0.18 (95% CI, 0.07, 0.44), respectively. The overall DOR was 25.35 (95% CI, 7.15, 89.89) with an AUROC of 0.89 (Figure 5A). Significant heterogeneity was observed for sensitivity (p < 0.0001) and specificity (p < 0.0001) (Figure 5B). Table 3 summarizes the diagnostic results for both tests in different cancer sites.

Table 3.

Summary of the results of pooled sensitivity, specificity, positive, and negative likelihood ratios for SWE and CEUS in different cancers.

Cancer Test Sensitivity Specificity + ve LR -ve LR DOR AUROC
Breast cancer SWE 0.84 (95% CI, 0.83, 0.86) 0.86 (95% CI, 0.85, 0.87) 7.12 (95% CI, 5.54, 9.15) 0.18 (95% CI, 0.15, 0.22) 46.22 (95% CI, 31.33, 68.18) 0.93
CEUS 0.89 (95% CI, 0.85, 0.92) 0.85 (95% CI, 0.81, 0.89) 6.13 (95% CI, 4.70, 8.01) 0.12 (95% CI, 0.07, 0.21) 49.66 (95% CI, 29.42, 83.82) 0.92
Hepatic cancer SWE 0.82 (95% CI, 0.77, 0.87) 0.83 (95% CI, 0.76, 0.89) 4.30 (95% CI, 2.85, 6.48) 0.29 (95% CI, 0.12, 0.71) 14.46 (95% CI, 4.09, 51.04) 0.90
CEUS 0.78 (95% CI, 0.76, 0.81) 0.89 (95% CI, 0.87, 0.91) 6.51 (95% CI, 3.90, 10.85) 0.13 (95% CI, 0.06, 0.25) 57.94 (95% CI, 24.78, 135.45) 0.95
Thyroid cancer SWE 0.67 (95% CI, 0.64, 0.69) 0.77 (95% CI, 0.76, 0.79) 3.50 (95% CI, 2.93, 4.18) 0.33 (95% CI, 0.25, 0.45) 11.17 (95% CI, 8.04, 15.51) 0.84
CEUS 0.81 (95% CI, 0.78, 0.84) 0.88 (95% CI, 0.86, 0.90) 6.01 (95% CI, 3.88, 9.31) 0.23 (95% CI, 0.17, 0.31) 28.54 (95% CI, 16.79, 48.51) 0.91
Renal carcinoma CEUS 0.87 (95% CI, 0.85, 0.88) 0.84 (95% CI, 0.82, 0.87) 5.55 (95% CI, 3.74, 8.22) 0.12 (95% CI, 0.07, 0.19) 53.44 (95% CI, 29.89, 95.56) 0.95
Prostate cancer SWE 84% (95% CI, 0.80, 0.87) 0.84 (95% CI, 0.82, 0.86) 4.59 (95% CI, 2.68, 7.87) 0.18 (95% CI, 0.07, 0.44) 25.35 (95% CI, 7.15, 89.89) 0.89
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AUROC, Area under the receiving-operating curve; CEUS, contrast-enhanced ultrasound; DOR, Diagnostic odds ratio; LR, Likelihood ratio; SWE, Shear wave elastography.

Outcomes of Network Meta-Analysis

Corresponding network plots and forest plots of network meta-analysis between CEUS and SWE are shown in Figure 6. In breast cancer, NMA showed that CEUS was associated with significantly higher DOR than SWE (DOR = 27.14, 95% CI [2.30, 51.97], p = 0.011). While NMA showed no significant difference between CEUS and SWE in detecting hepatic (DOR = −6.67, 95% CI [-15.08, 1.74, p = 0.61]) and thyroid malignant lesions (DOR = 3.79, 95% CI [−3.10, 10.68], p = 0.58). No significant heterogeneity or inconsistency were observed between the pooled studies for breast (I2 = 10%, p = 0.30) and hepatic cancer (I2 = 20%, p = 0.21). While a p-value of 0.05 indicated significant heterogeneity among the studies of thyroid cancer; therefore, the random-effects model was employed.

Figure 6.

Figure 6

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Network plots showing direct evidence between Contrast Enhanced Ultrasound and Shear Weight Elastography in (A) breast cancer, (B) hepatic caner, and (C) thyroid cancer. Also, forest plots of network meta-analysis between Contrast Enhanced Ultrasound and Shear Weight Elastography vs. histopathology in (A) breast cancer, (B) hepatic caner, and (C) thyroid cancer. (D) Forest plot CEUS vs. SWE of breast cancer. (E) Forest plot CEUS vs. SWE of hepatic cancer. (F) Forest plot CEUS vs. SWE of thyroid cancer.

Ranking Diagnostic Tests

According to Glas et al. (116), the DOR is considered as an indicator of ranking of competing diagnostic tests. According to our results, CEUS achieved the highest DOR in detecting breast and thyroid malignant lesions, while SWE achieved the highest DOR in detecting hepatic malignant lesions.

Discussion

This meta-analysis of DTA studies provides a comprehensive assessment and comparison of the diagnostic accuracy of two US modalities in differentiating malignant tumors in different body organs. It showed relatively high sensitivity (between 78 and 89%) and specificity (between 84 and 89%) for CEUS in identifying malignant lesions in the breast, liver, thyroid and kidneys. Moreover, it demonstrated relatively high sensitivity (between 82 and 84%) and specificity (between 83 and 86%) for SWE in differentiating malignant tumors within the breast, liver and prostate. However, it had relatively lower sensitivity (67%) and specificity (77%) in identifying malignant nodules within the thyroid gland.

Our results support some recent practice guidelines that endorse the use of CEUS and SWE in differentiating malignant lesions within the liver and the breast (117, 118). Moreover, it provides new data on a comparison that can impact the clinical practice. Through NMA, we compared the diagnostic accuracy of CEUS and SWE in three organs (where data on both tests were available in the literature). Our network and ranking analysis showed that CEUS was more accurate than SWE in differentiating breast and thyroid lesions (although the difference was not significant in thyroid malignancy according to NMA). On the other hand, SWE ranked higher in terms of diagnostic accuracy in differentiating hepatic malignant lesions (although the difference was not significant according to NMA).

Our results are in agreement with a former meta-analysis by Sadigh et al. that showed high sensitivity and specificity for SWE in differentiating breast malignant lesions [88 and 83% in comparison to 84 and 86% in our analysis; (11)]. However, our sensitivity and specificity results are quite lower than those obtained by Liu et al. in a meta-analysis on SWE accuracy in differentiating thyroid malignancy [sensitivity 81% and specificity 84%; (12)]. Likewise, another meta-analysis reported high sensitivity and specificity (93 and 90%, respectively) for CEUS in identifying hepatic malignant lesions (119). The observed discrepancy between our findings and those of the aforementioned meta-analyses may be attributed to the different sample size (being larger in our analysis) or the lesional characteristics of enrolled patients (being easier to identify in the studies included in the other meta-analysis i.e., less depth and clear contrast from the surrounding tissue).

Interestingly, a meta-analysis by Guang et al. showed comparable diagnostic accuracy for SonoVue-enhanced US with contrast-enhanced computed tomography and magnetic resonance imaging (8). Moreover, CEUS has other advantages over these modalities as ease of access, lack of radiation exposure or nephrotoxic materials; limitations that affect the use of CT and MRI in several diagnostic applications (120, 121). It is also fair to recognize that both tests have limitations as well. For example, SWE suffers from operator-dependency and manual compression, while the adverse effects of the contrast agent is a concern with CEUS use. Further technical improvements with both modalities would further enhance their clinical potential.

Strength Points

This NMA directly compares the diagnostic accuracies of CEUS and SWE in different cancer sites and using different analytic approaches as pairwise, network and ranking pooled analyses. Therefore, it provides a holistic evaluation of the comparison of both techniques in different body organs. We performed a thorough literature search and retrieved a large number of studies (relatively large sample size), which adds to the validity and generalizability of our findings. Unlike former reviews that retrieved a small number of studies and focused on one test in one organ, we aimed to provide a comprehensive assessment of both tests in different organs and a high quality comparison whenever suitable data were provided.

Limitations and Future Research Implications

Our meta-analysis has some limitations. First, the observed heterogeneity in the majority of our outcomes may be due to differences in study design and patient characteristics. Second, we could not examine the effects of lesion characteristics, such as size and depth on the diagnostic accuracy of both tests due to lack of data. Third, many of the included studies did not mention whether the results of CEUS or SWE were interpreted with blinding to the findings of histopathology or not. Future studies should report diagnostic accuracy data based on the size and depth of the lesions to allow more detailed analysis. Moreover, they should adhere to the Standards for Reporting of Diagnostic Accuracy “STRAD” checklist in reporting their methods and findings to allow a more thorough critical appraisal.

Conclusion

Both diagnostic tests (CEUS and SWE) showed relatively high sensitivity and specificity in detecting malignant tumors in different organs; CEUS had higher diagnostic accuracy than SWE in detecting breast and thyroid cancer, while SWE had higher accuracy in detecting hepatic cancer (the differences in the latter two cancer types were not statistically significant). These results endorse the use of both tests for malignancy detection and rank their accuracy in different organs. Future studies should provide more data to allow characterization of both tests in lesions of different size or depth.

Author Contributions

YS developed the concept, designed the study, and prepared the manuscript. RH acquired the data, controlled quality of the work, analyzed the data, and prepared the manuscript. LJ acquired the data. YX analyzed the data. YG acquired the data. HR acquired the data and conducted the analysis. ZW analyzed the data and prepared the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We are extremely thankful to authors of all the included papers for proving suitable data for analysis.

Footnotes

Funding. This work was supported by funding from National Natural Science Foundation of China. Award Number 31300137 received by RH.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2019.00102/full#supplementary-material

Supplementary File I

PRISMA checklist for systematic reviews/meta-analysis.

Click here for additional data file. (64KB, DOC)
Supplementary File II

Bibliographic Information of Included Studies.

Click here for additional data file. (94.7KB, DOCX)
Supplementary File III

Additional Pairwise Meta-analysis Figures.

Click here for additional data file. (104.1KB, DOCX)

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Associated Data

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Supplementary Materials

Supplementary File I

PRISMA checklist for systematic reviews/meta-analysis.

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Supplementary File II

Bibliographic Information of Included Studies.

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Supplementary File III

Additional Pairwise Meta-analysis Figures.

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