Research - Clinical Schizophrenia & Related Psychoses ( 2021) Volume 0, Issue 0
2Department of Diagnostic and Interventional Radiology, Baghdad Medical City, Baghdad, Iran
3Department of Radiologists, Ministry of Health, Babylon, Iraq
Ahmed Jasim Abbas, Department of Radiology and Radiotherapy, Tehran University of Medical Sciences, Tehran, Iran, Email: ahmedalmansoory5540@gmail.com
Received: 26-Jul-2021 Accepted Date: Aug 09, 2021 ; Published: 16-Aug-2021
Abstract
Introduction: Conflicting results have been reported between the use of conventional protocol MRI and advanced protocol MRI to avoid unnecessary histopathology when Magnetic Resonance Imaging (MRI) is used for the diagnosis of Hepatocellular Carcinoma (HCC). Therefore, we aimed to compare the diagnostic performance of conventional MRI and advanced technique MRI to avoid unnecessary histopathology.
Methods: Original studies reporting the diagnostic performance of MRI for the diagnosis of HCC published between January 2010 and February 2021 were identified in Literature search. A systematic literature search using PubMed(https://pubmed.ncbi.nlm.nih.gov), Embase (https://www.embase.com), Web of Science (https://apps.webofknowledge. com), PROQUEST, SEMANTIC SCHOLAR Google Scholar and Cochrane Library databases (https://wwwcochranelibrary. com) were performed independently by two radiologists to identify articles published prior to June 2021.
Results: A total of 3,757 HCCs and 3,682 benign liver lesions from 35 studies were included. The overall sensitivity and specificity of the diagnostic performance of conventional MRI was 0.81 (0.77-0.94) 0.78 (0.84-0.92) and Advance MRI 0.93 (0.83-0.89), 0.86 (0.79-0.96) respectively
Conclusion: The present meta‑analysis suggests that Advance MRI may increase the sensitivity, and specificity for the diagnosis of HCCs.
Keywords
Diffusion weighted image • Apparent Diffusion Coefficient • Perfusion weighted image • Meta-analysis
Introduction
Hepatocellular Carcinoma (HCC) is the most common primary malignancy of the liver [1]. HCC is the fifth most common type of cancer and the second leading cause of cancer-related death worldwide [2]. Approximately 70%-90% of HCCs are developed on the background of established liver cirrhosis or advanced fibrosis. Hepatitis B Virus (HBV) and/ or Hepatitis C Virus (HCV) infection, alcohol, and Nonalcoholic Aatty Liver Disease (NAFLD) are the most predominant risk factors for HCC worldwide [3]. A tremendous development of new imaging techniques has taken place during these last year’s [4]. Maximizing accuracy of imaging in the context of HCC is paramount in avoiding unnecessary histopathology, which may result in post-procedural complications up to 6.4%, and mortality up to 0.1% [5]. Noninvasive imaging modalities, including Ultrasound (US), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI), have played pivotal roles in assessing HCC in recent decades [6]. Several clinical practice guidelines, the application of US is limited in obese patients and patients with very cirrhotic heterogeneous livers. In addition, the performance of US is usually deteriorated for deep, sub diaphragmatic, multiple, and treated lesions. In general, US is less accurate for diagnosing HCC than MRI [7]. Therefore, US is not yet recommended as the first-line diagnostic tool for HCC, according to current guidelines [6]. Multiphasic dynamic Computed Tomography (CT) is useful in the evaluation of nodular lesions in the cirrhotic liver [8]. Arterial phase imaging is most useful for the detection of HCC as its predominant blood supply is from the hepatic artery [9]. However, it is less sensitive for the detection of small HCC and for dysplastic nodules which appear isodense to the liver parenchyma due to their predominant blood supply from the portal vein [10]. CT arterio-portography and CT hepatic arteriography are more sensitive for the detection of HCC but the false positive rate is high due to benign hyper vascular lesions like arterioportal shunts [11]. Nowadays, magnetic resonance plays a key role in management of liver lesions, using a radiation-free technique and a safe contrast agent profile [12]. Magnetic Resonance Imaging (MRI) provides valuable imaging information for the preoperative and postoperative evaluation of HCC [13]. DWI is a functional MRI technique that allows quantitative measurements of proton diffusion in tissues [14]. HCC and other malignancies are usually characterized by increased cellularity and, thus, have restricted water proton diffusion [6]. Therefore, most HCCs are observed as a hyper intense lesion on high b value DWI with low Apparent Diffusion Coefficient (ADC) value on quantitative maps compared with background liver [15]. HCC and other malignancies are usually characterized by increased cellularity and, thus have restricted [16]. Perfusion weighted image Dynamic Contrast- Enhanced (DCEMRI) enables quantification of the vascular characteristics of tissue and tumor [17]. DCE-MRI requires IV injection of a gadoliniumbased contrast agent and uses high-temporal images that capture changes in MR Signal Intensity (SI) as a function of time. Tracer kinetic modeling based on DCE-MRI has been used to detect liver fibrosis and cirrhosis and to assess tumor angiogenesis [18].
Materials and Methods
This systematic review and meta-analysis was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA) guidelines [19].
Literature search
A systematic literature search using PubMed( https://pubmed.ncbi. nlm.nih.gov), Embase (https://www.embase.com), Web of Science (https://apps.webofknowledge com), SEMANTIC SCHOLAR, Google Scholar, PROQUEST, and Cochrane Library databases (https://www cochranelibrary.com) were performed independently by tow radiologists to identify articles published prior to June 2021, using the key words ‘hepatocellular carcinoma’, ‘liver cancer’, ‘liver cell carcinoma’, ‘magnetic resonance imaging’ ‘diffusion magnetic resonance imaging’, Meta-analysis • Systematic review susceptibility weighted image SWI. Related citations in eligible articles were also assessed for inclusion. The search was limited to English-language studies on human subjects. The time period for the studies was limited from January 1, 2010 to February 6, 2021. The detailed search strategy is described in supplementary Figure 1.
The ethical approval for this study was obtained from Tehran University of medical sciences ethical committee in our institution IR.TUMS.SPH. REC.1399.324 during 14 Mars 2021. The study included (35) articles studied consecutive with HCC. In our study, Embase, MEDLINE, PubMed, the Cochrane library, Elsevier, Springer and free journals were searched using the search queries: HCC , conventional MRI, Locally Advance MRI, diffusion weighted imaging DWI, perfusion MRI , IVIM and SWI. Only original articles that performed during the years 2010 to 2020 presented in English language that relevant to our objectives were considered for inclusion. We searched more in databases using function of Related Articles in PubMed and browsed the scholar.google.com using same terns. Also we searched the references of all retrieved articles manually for relevant related articles. Then we compared the retrieved articles and accepted recent publication for the overlapping patients ‘series. Furthermore, we assessed for potential eligibility by screening for relevance on title and reading the abstracts first and then full text article and then start to apply agreed upon inclusion and exclusion criteria.
Inclusion and exclusion criteria
Studies meeting the following criteria were included: (a) population: Patients at high risk for HCC [1,2,5]; (b) index test: liver MRI with conventional protocol or advanced protocol; (c) reference standard: HCC histopathology and clinical diagnosis such as imaging follow-up or laboratory markers; Studies meeting any of the following criteria were excluded: (a) studies not reporting sufficient data to clearly establish outcomes; (b) studies for which it was not possible to obtain separate outcomes using with conventional protocol or advanced protocol; (c) studies with hepatic lesions previously treated with systemic therapy; (d) studies with case–control designs; (e) studies with partially overlapping cohorts; (f) case reports or series including fewer than ten patients; and (g) protocols, conference abstracts, reviews, guidelines, books, letters, editorials, and errata.
Data extraction and quality assessment
The following data were extracted from each eligible study: (a) Study characteristics: Authors, year of publication, institution, country, duration, and study design (prospective vs. retrospective); (b) patient characteristics: number of patients, sex, age, underlying liver disease, (c) lesion characteristics: lesion number, lesion size,; (d) MRI techniques: magnetic field, MRI protocol, (e) reference standard; The methodological quality of the selected studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool [11]. The risk of bias and applicability of each eligible study were assessed according to the four different domains of patient selection, index test, reference standard, and flow and timing. Studies without a high risk of bias in any domain were considered to have a low-to-moderate overall risk of bias. Likewise, studies without a high concern for applicability in any domain were considered to have a low-tomoderate overall concern for applicability. The data extraction and quality assessment were independently conducted by the two reviewers, with any disagreements being resolved by discussion with the third reviewer.
The two radiologists reviewed all 2380 abstracts after duplication removal and subsequently the full text of the 120 articles was obtained if the following inclusion criteria was fulfilled: 1) Included the diagnostic accuracy of conventional MRI only or with advance protocol for HCC; 2) constituted original research rather than a meta‑analysis, a review article, case report or case series; 3) published in English; and 4) results are from humans and not animals 5) included both MRI with conventional protocol and advanced protocol 6) included sufficient data, with>20 patients to calculate True Positive (TP), False Positive (FP), False Negative (FN) and True Negative (TN) for constructing a 2 × 2 contingency table; and 7) patients at high risk for HCC using pathological analysis (surgical resection, explant and/or biopsy) or imaging from follow‑up according to the guidelines for standardization of liver imaging, diagnosis, classification and reporting of hepatocellular carcinoma. In addition, articles from the same institution, which included an overlap period of patient recruitment, were considered to have an overlapping population. In these cases, the study, which had the larger number of HCCs cases, was included.
If there were disagreements between the two investigators, the consensus amongst the two radiologists was used to resolve the disagreement. Disagreements were resolved following discussions between the two investigators, until at least own of the investigators reached the same conclusion. A total of 85 studies were excluded according to the following exclusion criteria:1) They were not relevant to the present meta‑analysis if they fit one of the followings conditions: Cancer type includes malignant cancer other than HCC, such as cholangiocarcinoma, hepatoepidermoid carcinoma and metastatic cancer; diagnosis of HCC using a combination of multiple imaging modalities;2) they evaluated previously treated HCCs; 3) the sensitivity and specificity was not evaluated; 4) there was a lack of sufficient data to construct a 2 × 2 contingency table; and vi) there was study population overlap. A total of 35 studies were included for analysis. In addition, the reference list of these 35 studies was reviewed.
Results
Study selection. A flow chart following the Preferred Reporting Items for Systematic Reviews and Meta-analysis principles was used to demonstrate the selection procedure (Figure 1).
A total of 2,380 articles were initially identified. There was a total of 2,260 articles remaining following the removal of duplicates and a further 120 articles were excluded, following screening of the abstract. Amongst the remaining 85 studies, a total of 35 studies were included in the Meta analysis using the inclusion criteria.
Summary of included studies
The summarized characteristics and the diagnostic performance of conventional MRI and Advance MRI for the included 35 studies are shown in Tables 1 and 2, respectively. A total of 3,757 HCCs with a diameter 2 cm and 3,682 benign liver lesions, with a diameter 2 cm was included in the meta analysis. The DWI, HCC, MRI and were all calculated on a per lesion basis. Of the included studies, 27 originated from Asia, 7 from Europe and one from USA. In addition, 23 of the studies were retrospective, and 12 were prospective. The reference standard for the diagnosis of HCC included pathological analysis (surgical resection, explant and/or biopsy) and imaging from follow-up. MR imaging field strength was 3 T and 1.5 T.
S.no | Author | Year | Country | No of Patients | No. lesions of HCC | Reference Standard | MRI field, T | MRI sequence with HBPI and without 0 |
---|---|---|---|---|---|---|---|---|
1. | Shankarin Shiva | 2016 | India | 20 | 22 | Fine needle aspiration | 3.0 | 0 |
2. | Zixing Huang, Yi Wei | 2019 | China | 115 | 135 | Histopathology | 3.0 | 0 |
3. | Heon-Ju kwon | 2015 | Korea | 230 | 222 | Histopathology | 1.5 | 1 |
4. | Sungmin Woo | 2013 | South Korea | 40 | 42 | Histopathology | 3.0 | 0 |
5. | Vincenza Granata | 2016 | Italy | 34 | 62 | Biopsy | 1.5 | 0 |
6. | Yong-Sheng Xu | 2019 | China | 51 | 51 | Histopathology | 3.0 | 0 |
7. | Guang-Zhi Wang | 2020 | China | 128 | 128 | Histopathology | 3.0 | 0 |
8. | Shao-Cheng Zhu | 2018 | China | 62 | 62 | Histopathology | 3.0 | 0 |
9. | Likun Cao | 2019 | China | 74 | 74 | Histopathology | 3.0 | 0 |
10. | Tomohisa Moriya | 2017 | Japan | 53 | 56 | Surgery | 3.0 | 1 |
11. | Jinkun Zhao | 2017 | China | 318 | 211 | Hepatic resection surgery | 1.5 | 0 |
12. | Jiyoung Hwang | 2014 | Korea | 63 | 113 | Explant | 3.0 | 0 |
13. | Yanyan Zhang | 2020 | China | 91 | 91 | WD-HCCs | 3.0 | 0 |
14. | Jie Chen | 2019 | China | 115 | 121 | Surgery | 3.0 | 1 |
15. | Seunghee Han | 2018 | Korea | 175 | 175 | HCC (KLCSG-NCC) |
3.0 | 0 |
16. | Yi Kyung Kim | 2013 | Korea | 135 | 136 | Histopathological and biopsy | 3.0 | 0 |
17. | Matteo Renzulli | 2018 | Italy | 228 | 420 | Histology | 1.5 | 1 |
18. | Yingmei Jia Yingmei Jia | 2019 | China | 151 | 114 | Surgery or biopsy | 3.0 | 0 |
19. | Juan Peng | 2020 | China | 65 | 55 | Surgery | 3.0 | 0 |
20. | Hina Gu | 2018 | Pakistan | 85 | 48 | Histopathology | 1.5 | 0 |
21. | Cecilia Besa | 2016 | USA | 174 | 80 | Histopathology | 1.5 | 1 |
22. | Rita Golfieri | 2011 | Italy | 127 | 62 | Histopathology | 1.5 | 1 |
23. | Bedriye Koyuncu Sokmena | 2019 | Turkey | 29 | 42 | Histopathologically | 1.5 | 0 |
24. | Dong Ik Cha | 2020 | Korea | 122 | 122 | Histopathology | 3.0 | 0 |
25. | Ah Yeong Kim | 2012 | Korea | 189 | 240 | Histopathology | 3.0 | 0 |
26. | A Koa | 2019 | Korea | 117 | 89 | Histopathology | 3.0 | 0 |
27. | Michele Di Martino | 2019 | Italy | 40 | 93 | Histopathology | 1.5 | 1 |
28. | Michele Di Martino | 2016 | Italy | 52 | 71 | Histopathology | 3.0 | 1 |
29. | Suwannee Surattanasophon | 2014 | Thailand | 45 | 101 | Histopathology | 3.0 | 1 |
30. | Zhi-bo Hou | 2021 | China | 40 | 44 | Histopathology | 3.0 | 0 |
31. | Heno-Ju Know | 2014 | Korea | 230 | 210 | Histopathology | 1.5 | 0 |
32. | Ruo-kun Li | 2012 | China | 58 | 65 | Histopathology | 3.0 | 0 |
33. | Ruo-kun Li | 2015 | China | 68 | 89 | Histopathology | 3.0 | 1 |
34 | Meng zhou | 2021 | China | 60 | 62 | Histopathology | 3.0 | 1 |
35. | Ijin Joo | 2018 | Korea | 288 | 292 | Histopathology | 3.0,1.5 | 1 |
S.no | Author ,Year | Study Period | MRI Interpretation | Study Type | Primary HCC Eatology | Size of HCCs, cm | Less than 2 cm=0 more than 2 cm=1 |
---|---|---|---|---|---|---|---|
1. | Shiva Shankarin, 2016 | Period of 18 months | A prospective study | Conventional MRI | HCV (NASH) | 3 cm to 17 cm | 1 |
2. | Zixing, YiWei and Huang, 2019 | January 2016 and April 2017 | Prospective | Advance MRI | Hepatitis B virus 26 | 7.04 ± 3.67 cm, 5.80 ± 3.95 cm | 1 |
3. | Heon â?? Ju kwon, 2015 | November 2009 and June 2011 | Retrospective Study | Conventional MRI | Hepatitis B | 0.5 cm to 2 cm | 1 |
4. | Sungmin Woo, 2013 | August 2010 to May 2012 | Retrospective Study | Advance MRI | NA | 4.7 cm ± 3.4, 1.2-16.3 cm | 1 |
5. | Vincenza Granata, 2016 | From August 2014 to February 2016 | A retrospective Study | Advance MRI | Hepatitis C Virus 14 patients hepatitis B virus |
12 mm to 20 mm | 0 |
6. | Yong â?? Sheng Xu, 2019 | Between December 2015 to June 2018 | A retrospective Study | Conventional MRI | Hepatitis B | 6 mm to 118 mm | 1 |
7. | Guang â?? Zhi Wang, 2020 | From December 2015 to January 2017 | Prospective study | Advance MRI | Hepatitis B HBV (+) hepatitis |
3.0 cm to 18.0 cm | 1 |
8. | Shao- Cheng Zhu, 2018 | Between March 2016 to May 2017 | A retrospective Study | Advance MRI | Hepatitis B | - | 1 |
9. | Likun Cao, 2019 | From September 2015 to January 2017 | Prospective study | Advance MRI | Hepatitis B | 5.80 ± 2.68 | 1 |
10. | Tomohisa Moriya, 2017 | 3 months before surgery | Retrospective Study | Conventional MRI | Hepatitis B Hepatitis C | NA | - |
11. | Jinkun Zhao, 2017 | January 2011 and January 2015 | Retrospective Study | Conventional MRI | Hepatitis | 1.5 cm to 21.0 cm | 1 |
12. | Jiyoung Hwang, 2014 | From April 2008 to October 2013 | Retrospective Study | Conventional MRI | Hepatitis B and C | Mean 2.0 cm+1.3 cm | 0 |
13. | Yanyan Zhang, 2020 | From January 2012 to April 2018 | Retrospective Study | Conventional MRI | NA | 30 mm | 1 |
14. | Jie Chen, 2019 | August 2015 to September 2018 | Retrospective Study | Conventional MRI | Hepatitis B, virus B and hepatitis C | 6.36(1.5, 12.73) | 1 |
15. | Seunghee Han, 2018 | From January 2012 to August 2015 | Study retrospective | Conventional MRI | Hepatitis B Hepatitis C | Bigger than | 0 |
16. | Yi Kyung Kim, 2013 | December 10 and May 2012 | Retrospective Study | Conventional MRI | HBV/HCV | 0.6 cm to 2.0 cm | 1 |
17. | Matteo Renzulli, 2018 | From 18 June 2013 to 1 December 2015 | A Prospective Study |
Conventional MRI |
HCV |
11 mm to 150 mm |
1 |
18. | Yingmei Jia Ying mei Jia, 2019 | March 2013 and November 2016 | Study retrospectively | Advance MRI | NA | NA | - |
19. | Juan Peng, 2020 | - | Prospective Study | Advance MRI | NA | NA | - |
20. | Hina Gul, 2018 | From July 2015 to June 2017 | This cross-sectional Validation study | Conventional MRI | NA | (â?¤ 2 cm) | 0 |
21. | Cecilia Besa, 2016 | 1/1/2011 to 31/12/2011 | Retrospective | Conventional MRI | HCV/NASH | 11 mm to 20 mm | 0 |
22. | Rita Golfieri, 2011 | May 2008 and October 2009 | Prospective study | Conventional MRI | HBV/HCV | (<1 cm and 1 cm to 2 cm>) | 0 |
23. | Bedriye Koyuncu Sokmena, 2019 | Between January 2015 and October 2016 | Study retrospective | Advance MRI | Hepatitis B Hepatitis C | NA | - |
24. | Dong Ik Cha, 2020 | Between November 2016 and September 2018 | Prospective | Conventional MRI | HBV/HCV | 2.1 (0.6-5.0) | 1 |
25. | Ah Yeong Kim, 2012 | Between October 2009 and February 2011 | Retrospective study | Conventional MRI | Hepatitis B | (3.0 cm) | 1 |
26. | A. Koa, 2019 | Between October 2009 and January 2016 | Retrospective study | Conventional MRI | Hepatitis B | Mean size 14 ± 3.4 | 1 |
27. | Michele Di Martino, 2019 | Between December 2011 and April 2012 | Retrospective study | Conventional MRI | HCV/HBV Cryptogenic HCV+HBV |
5 mm to 20 mm | 0 |
28. | Michele Di Martino, 2016 | Between January 2014 and July 2015 | Prospectively | Conventional MRI | Dynamic | (5 mm to 20 mm; median 15 mm) | 0 |
29. | Suwannee Surattanasophon, 2014 | Between January 2012 and November 2013 | Retrospective study | Conventional MRI | C Hepatitis C | 2.06 cm | 1 |
30. | Zhi-bo Hou, 2021 | NA | Retrospective study | Advance MRI | NA | 0.7 cm to 2.8 cm | 1 |
31. | Heon-Ju Kwon, 2014 | Between November 2009 and June 2011 | Retrospective Study | Conventional MRI | NA | (0.5 cm to 2 cm) | 0 |
32. | Ruo-kun Li, 2012 | Between March and August 2010 | Â Preoperative | Advance MRI | Hepatitis B | (4.1 cm to 63.4 cm) | 1 |
33. | Ruo-kun Li, 2015 | From March 2010 to August 2012 | Â Preoperative | Advance MRI | Hepatitis B Hepatitis C | NA | - |
34. | Meng Zhou, 2021 | Hospital from October 2018 to October 2019 | Retrospective Study | Conventional MRI | HBV 29 | <3 cm | 1 |
35. | Ijin Joo, 2018 | Between September 2012 and May 13 | Retrospective Study | Conventional MRI | Chronic hepatitis image analyses | NA | - |
Quality assessment and publication bias: Figure 2 demonstrates the overall evaluation for the quality of the included studies using QUADAS.2. The quality of the index test was high (90%, 9/35 studies); however, patient selection had a low score (70%, 7/35 studies), which could be due to a lack of avoidance of a case control design or the inappropriate exclusions during patient selection.
Figure 2.Quality assessment of the included studies using the Quality Assessment of Diagnostic Accuracy Studies. The red bar indicates high risk of bias; the yellow bar indicates unclear risk of bias; and the green bar indicates low risk of bias. In the lower part, details of quality assessment were shown. Green circle with â??+â?? indicates low risk of bias or low concern for applicability; yellow circle with â???â?? indicates unclear risk of bias or unclear concern for applicability; red circle with â??â??â?? indicates high risk of bias or low concern for applicability. Funnel plot of comparison.
This also increased concerns regarding the applicability of patient selection. For all the 35 included studies, some of them used pathological finding as the only reference standard to diagnose HCC. For the others, Histopathology was used as a reference standard for patients when pathology analysis was not available. Liver transplantation (n¼10), surgical resection (n¼26), or fine needle aspiration biopsy (n¼55). Of the 91 nodules, 60 nodules were pathologically confirmed as WD-HCCs and 31 nodules were confirmed as HGDNs.
Therefore, the concerns of bias for applicability of reference standards was low for studies using imaging follow up as one of the reference standards for patients when pathology was not used. The risk of bias for flow and timing was high for 1 study since the interval between MRI scan and the pathological analysis exceeded 117 days for some of the patients, and was unclear for 2 studies for the lack of information regarding the time interval between MRI scan and the references standard (Figure 3 and Table 3).
Characteristic | No. of studies | Pooled sensitivity (CI) |
Pâ??value | Pooled specificity (CI) |
Pâ??value |
---|---|---|---|---|---|
MRI field strength, T | 0.87 | 0.51 | |||
3.0 | 25 |
0.83 (0.79-0.91) | 0.92 (0.77-0.95) | ||
1.5 | 10 |
0.91 (0.88-0.97) | 0.80 (0.79-0.89) | ||
Country of origin |
|
0.36 | 0.79 | ||
Asia | 27 |
0.79 (0.81-0.95) | 0.83 (0.88-0.92) | ||
Europe | 7 |
0.88 (0.86-0.90) | 0.81 (0.82-0.94) | ||
USA | 1 |
0.91 (0.90-0.97) | 0.87 (0.89-0.97) | ||
Study design |
|
0.64 | 0.91 | ||
Prospective | 11 |
0.90 (0.72-0.89) | 0.79 (0.84-0.91) | ||
Retrospective | 24 |
0.84 (0.77-0.99) | 0.85 (0.80-0.93) | ||
Hepatobiliary phase imaging | 0.21 | 0.84 | |||
Yes | 21 |
0.77 (0.85-0.92) | 0.84 (0.78-0.89) | ||
No | 14 |
0.86 (0.80-0.94) | 0.81 (0.88-0.98) |
Heterogeneity between studies the 35 included studies demonstrated significant heterogeneity with P<0.00001 using X2 test. The heterogeneity for the sensitivity (I2 of 93) was higher compared with that for specificity (I2 of 93). In addition, there was no threshold effect found (correlation,.0.46; proportion of heterogeneity due to threshold effect, (0.46), (P=0.65).
Synthesis of general diagnostic
Figure 4 demonstrates the forest plots of sensitivity and specificity, Tables 4-6 comparison of the diagnostic performance of conventional MRI, The pooled sensitivity and specificity were 0.81 (95% CI, 0.77-0.94) and 0.78 (95% CI, 0.84-0.92), respectively, +Advance MRI. The pooled sensitivity and specificity were 0.93 (95% CI, 0.83-0.89) and 0.86 (95% CI, 0.79-0.96), respectively. The positive and negative likelihood ratio was 0.02 (95% CI, 0.06-0.09), respectively.
Diagnostic methods | Pooled sensitivity (CI) | Pâ??value | Pooled specificity (CI) | Pâ??value |
---|---|---|---|---|
Conventional MRI | 0.81 (0.77-0.94) | 0.72 | 0.78 (0.84-0.92) | 0.89 |
Advance MRI | 0.93 (0.83-0.89) | 0.86 (0.79-0.96) |
Sequence | Valid N (list wise) |
---|---|
Positive Negative Missing |
23 12 1 |
Positive if greater than or equal to | Sensitivity | 1-Specificity |
---|---|---|
-1.00- | 1.000 | 1.000 |
.50 | .348 | .250 |
2.00 | .000 | .000 |
SROC, The confidence region (smaller circle with dash line) represents the ellipsoid 95% confidence region in SROC space for the summary point estimate of diagnostic performance. SROC, summary receiver operating characteristics curve; AUC, area under the curve; SPEC, Specificity; SENS, Sensitivity (Figure 5).
Figure 5. Sensitivity was significantly higher for studies not using hepatobiliary phase compared with those using hepatobiliary phase (P<0.001). Specificity was significantly higher for studies using a 3 T magnetic field compared with those using 1.5 T magnetic field (P=0.03). There were no significant differences in either the sensitivity or in specificity for the remaining study characteristics (all P>0.05).
Sensitivity was significantly higher for studies not using hepatobiliary phase compared with those using hepatobiliary phase (P<0.001). Specificity was significantly higher for studies using a 3 T magnetic field compared with those using 1.5 T magnetic field (P=0.03). There were no significant differences in either the sensitivity or in specificity for the remaining study characteristics (all P>0.05) (Figure 6).
Larger values of the test result variable(s) indicate stronger evidence for a positive actual state. The positive actual state is 0.
The test result variable(s): Interpretation has at least one tie between the positive actual state group and the negative actual state group. The smallest cutoff value is the minimum observed test value minus 1, and the largest cutoff value is the maximum observed test value plus 1. All the other cutoff values are the averages of two consecutive ordered observed test values. Diagonal segments are produced by ties.
Discussion
The aim of the present meta‑analysis was to assess the diagnostic performance of advance MRI combined with conventional MRI for the diagnosis of HCC lesions. The results suggested that advance MRI with conventional MRI had a high sensitivity of 0.93 (0.83-0.89), and specificity of 0.86 (0.79-0.96). The meta‑regression analysis revealed that the heterogeneity of Sensitivity was significantly higher for studies not using hepatobiliary phase compared with those using hepatobiliary phase (P<0.001). Specificity was significantly higher for studies using a 3T magnetic field compared with those using 1.5 T magnetic field (P=0.03). There were no significant differences in either the sensitivity or in specificity for the remaining study characteristics (all P>0.05). However, a threshold effect was not identified. Non‑contrast enhanced Ultrasonography (US) is a common choice for HCC screening in patients who with chronic liver disease, as it is cost‑effective [20]. However, there is low sensitivity when compared with that in contrast‑ enhanced Computer Tomography (CT) and MRI [21]. Contrast‑enhanced US has emerged as a promising method to diagnose small HCCs however, additional studies are required to confirm its clinical value [20,22]. Multiple meta‑analyses have found that contrast‑enhanced MRI out performs contrast enhanced CT in the diagnosis of HCCs with higher sensitivity and overall accuracy [23]. Previous meta‑analysis indicated that contrast‑enhanced MRI had moderately high sensitivity and high specificity in the diagnosis of small HCC [24]. However, gadolinium contrast cannot be used in patients with chronic renal failure due to risk of nephrogenic systemic fibrosis and in those with history allergy to gadolinium [25]. This creates a need for imaging sequences without the use of gadolinium which can be used for diagnosing HCC in patients with contraindication for gadolinium [26]. In DCEMR, hepatic lesions, which show arterial phase enhancement without venous washout such as dysplastic nodules, and arterio- portal shunts are often encountered which hoften posea diagnostic difficulty indiscriminating HCC from these pseudo-enhancing lesions [27].
The present meta‑analysis suggested that Advance MRI combined with conventional MRI increased the sensitivity and specificity in the diagnosis of HCC. However, the prognosis is poor when HCC is diag- nosed at an advanced stage. Hence, diagnosing HCC at an early stage is very important. ADC has been used to diagnose benign and malignant hepatic lesions [28].
An increasing number of studies have suggested that ADC is more accurate in grading smaller HCCs [29], and for monitoring early treatment responses of HCC to radiofrequency ablation (39).
In the 35 studies included in the present meta‑analysis, one of them study Zhi-bo Hou et al. used a predetermined threshold SWI with DWI value to diagnose small HCC was found Conventional MRI, sen, spes, accuracy 81.24 83.71 80.34 and he found SWI+ DWI increase sens, spes accuracy 91.26 93.55 91.47 respectively.
Conclusion
The present meta‑analysis suggests that Advance MRI may increase the sensitivity, and specificity for the diagnosis of HCCs. The aim of the present meta‑analysis was to assess the diagnostic performance of advance MRI combined with conventional MRI for the diagnosis of HCC lesions. The results suggested that advance MRI with conventional MRI had a high sensitivity of 0.93 (0.83-0.89), and specificity of 0.86 (0.79-0.96).
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Citation: Vahid Changizi, Ahmed Jasim Abbas, Hayder Jasim Taher and Hayder Suhail Najim, et al. “Advanced Imaging Techniques of the Magnetic Resonance in Characterization of Hepatocellular Carcinoma Type: A Systematic Review and Meta Analysis.” Clin Schizophr Relat Psychoses 15S(2021). Doi: 10.3371/CSRP.CVAA.16.0821.
Copyright: ©2021 Changizi V, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.