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Diagnostic accuracy of vesical imaging-reporting and data system (VI-RADS) for the detection of muscle-invasive bladder cancer: a meta-analysis

  • Kidneys, Ureters, Bladder, Retroperitoneum
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Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

Vesical Imaging-Reporting and Data System (VI-RADS) was proposed and considered as a standardized reporting criterion for bladder magnetic resonance imaging (MRI). VI-RADS could suggest the likelihood of muscle invasion based on the multiparametric MRI (mp-MRI) findings which contain five-point scores. The current study is designed to comprehensively and systematically evaluate the diagnostic performance of VI-RADS (score 3 and 4) for predicting muscle invasion.

Methods

The Cochrane Library, Embase, and PubMed were searched comprehensively from inception to October 2021.

Results

Finally, 19 studies incorporating 2900 patients were enrolled. The pooled sensitivity and specificity of VI-RADS 3 for predicting muscle invasion were 0.92 (95%CI 0.89–0.94) and 0.82 (95%CI 0.76–0.87), respectively. The pooled sensitivity and specificity of VI-RADS 4 were 0.78 (95%CI 0.72–0.83) and 0.96 (95%CI 0.93–0.97), respectively. And the area under the curve (AUCs) of VI-RADS 3 and 4 were all 0.94 (95%CI 0.92–0.96). No significant publication biases were not observed for VI-RADS 3 (P = 0.74) and 4 (P = 0.57).

Conclusion

The VI-RADS reveals a good diagnostic performance for predicting muscle invasive in bladder cancer, which also has good clinical utilities and applicability. And VI-RADS 3 and 4 as cutoff values provide similar overall diagnostic and could be selectively applied individually. Prospective studies with a large scale are further required to validate the accuracy of the VI-RADS score.

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References

  1. [1] H. Sung, J. Ferlay, R.L. Siegel, M. Laversanne, I. Soerjomataram, A. Jemal, F. Bray, Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries, CA Cancer J Clin. 71 (2021) 209–249. https://doi.org/https://doi.org/10.3322/caac.21660.

    Article  Google Scholar 

  2. [2] M. Babjuk, M. Burger, E.M. Compérat, P. Gontero, A.H. Mostafid, J. Palou, B.W.G. van Rhijn, M. Rouprêt, S.F. Shariat, R. Sylvester, R. Zigeuner, O. Capoun, D. Cohen, J.L.D. Escrig, V. Hernández, B. Peyronnet, T. Seisen, V. Soukup, European Association of Urology Guidelines on Non-muscle-invasive Bladder Cancer (TaT1 and Carcinoma In Situ) - 2019 Update, Eur Urol. 76 (2019) 639–657. https://doi.org/https://doi.org/10.1016/j.eururo.2019.08.016.

    Article  CAS  PubMed  Google Scholar 

  3. [3] P. Mariappan, A. Zachou, K.M. Grigor, Detrusor muscle in the first, apparently complete transurethral resection of bladder tumour specimen is a surrogate marker of resection quality, predicts risk of early recurrence, and is dependent on operator experience, Eur Urol. 57 (2010) 843–849. https://doi.org/https://doi.org/10.1016/j.eururo.2009.05.047.

    Article  PubMed  Google Scholar 

  4. [4] Y. Ueno, M. Takeuchi, T. Tamada, K. Sofue, S. Takahashi, Y. Kamishima, N. Hinata, K. Harada, M. Fujisawa, T. Murakami, Diagnostic Accuracy and Interobserver Agreement for the Vesical Imaging-Reporting and Data System for Muscle-invasive Bladder Cancer: A Multireader Validation Study, Eur Urol. 76 (2019) 54–56. https://doi.org/https://doi.org/10.1016/j.eururo.2019.03.012.

    Article  PubMed  Google Scholar 

  5. [5] M. Takeuchi, S. Sasaki, M. Ito, S. Okada, S. Takahashi, T. Kawai, K. Suzuki, H. Oshima, M. Hara, Y. Shibamoto, Urinary bladder cancer: diffusion-weighted MR imaging--accuracy for diagnosing T stage and estimating histologic grade, Radiology. 251 (2009) 112–121. https://doi.org/https://doi.org/10.1148/radiol.2511080873.

    Article  PubMed  Google Scholar 

  6. [6] A. El-Assmy, M.E. Abou-El-Ghar, H.F. Refaie, A. Mosbah, T. El-Diasty, Diffusion-weighted magnetic resonance imaging in follow-up of superficial urinary bladder carcinoma after transurethral resection: initial experience, BJU Int. 110 (2012) E622-7. https://doi.org/https://doi.org/10.1111/j.1464-410X.2012.11345.x.

    Article  PubMed  Google Scholar 

  7. [7] V. Panebianco, Y. Narumi, E. Altun, B.H. Bochner, J.A. Efstathiou, S. Hafeez, R. Huddart, S. Kennish, S. Lerner, R. Montironi, V.F. Muglia, G. Salomon, S. Thomas, H.A. Vargas, J.A. Witjes, M. Takeuchi, J. Barentsz, J.W.F. Catto, Multiparametric Magnetic Resonance Imaging for Bladder Cancer: Development of VI-RADS (Vesical Imaging-Reporting And Data System), Eur Urol. 74 (2018) 294–306. https://doi.org/https://doi.org/10.1016/j.eururo.2018.04.029.

    Article  PubMed  PubMed Central  Google Scholar 

  8. [8] D. Moher, A. Liberati, J. Tetzlaff, D.G. Altman, Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement, PLoS Med. 6 (2009) e1000097. https://doi.org/https://doi.org/10.1371/journal.pmed.1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  9. [9] P.F. Whiting, A.W. Rutjes, M.E. Westwood, S. Mallett, J.J. Deeks, J.B. Reitsma, M.M. Leeflang, J.A. Sterne, P.M. Bossuyt, QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies, Ann Intern Med. 155 (2011) 529–536. https://doi.org/https://doi.org/10.7326/0003-4819-155-8-201110180-00009.

    Article  PubMed  Google Scholar 

  10. [10] J.B. Reitsma, A.S. Glas, A.W. Rutjes, R.J. Scholten, P.M. Bossuyt, A.H. Zwinderman, Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews, J Clin Epidemiol. 58 (2005) 982–990. https://doi.org/https://doi.org/10.1016/j.jclinepi.2005.02.022.

    Article  PubMed  Google Scholar 

  11. [11] S. Woo, V. Panebianco, Y. Narumi, F. Del Giudice, V.F. Muglia, M. Takeuchi, S. Ghafoor, B.H. Bochner, A.C. Goh, H. Hricak, J.W.F. Catto, H.A. Vargas, Diagnostic Performance of Vesical Imaging Reporting and Data System for the Prediction of Muscle-invasive Bladder Cancer: A Systematic Review and Meta-analysis, Eur Urol Oncol. 3 (2020) 306–315. https://doi.org/https://doi.org/10.1016/j.euo.2020.02.007.

    Article  PubMed  PubMed Central  Google Scholar 

  12. [12] J.P. Higgins, S.G. Thompson, J.J. Deeks, D.G. Altman, Measuring inconsistency in meta-analyses, Bmj. 327 (2003) 557–560. https://doi.org/https://doi.org/10.1136/bmj.327.7414.557.

    Article  PubMed  PubMed Central  Google Scholar 

  13. [13] J.J. Deeks, P. Macaskill, L. Irwig, The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed, J Clin Epidemiol. 58 (2005) 882–893. https://doi.org/https://doi.org/10.1016/j.jclinepi.2005.01.016.

    Article  PubMed  Google Scholar 

  14. [14] C. Luo, B. Huang, Y. Wu, J. Chen, L. Chen, Use of Vesical Imaging-Reporting and Data System (VI-RADS) for detecting the muscle invasion of bladder cancer: a diagnostic meta-analysis, Eur Radiol. 30 (2020) 4606–4614. https://doi.org/https://doi.org/10.1007/s00330-020-06802-z.

    Article  PubMed  Google Scholar 

  15. [15] S. Taguchi, M. Tambo, M. Watanabe, H. Machida, T. Kariyasu, K. Fukushima, Y. Shimizu, T. Okegawa, K. Yokoyama, H. Fukuhara, Prospective Validation of Vesical Imaging-Reporting and Data System Using a Next-Generation Magnetic Resonance Imaging Scanner-Is Denoising Deep Learning Reconstruction Useful?, J Urol. 205 (2021) 686–692. https://doi.org/https://doi.org/10.1097/ju.0000000000001373.

    Article  PubMed  Google Scholar 

  16. [16] M.I. Metwally, N.A. Zeed, E.M. Hamed, A.S.F. Elshetry, R.M. Elfwakhry, A.M. Alaa Eldin, A. Sakr, S.A. Aly, W. Mosallam, Y.M.A. Ziada, R. Balata, O.A. Harb, M.A.A. Basha, The validity, reliability, and reviewer acceptance of VI-RADS in assessing muscle invasion by bladder cancer: a multicenter prospective study, Eur Radiol. 31 (2021) 6949–6961. https://doi.org/https://doi.org/10.1007/s00330-021-07765-5.

    Article  PubMed  Google Scholar 

  17. [17] S. Li, P. Liang, Y. Wang, C. Feng, Y. Shen, X. Hu, D. Hu, X. Meng, Z. Li, Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer, Abdom Radiol (NY). 46 (2021) 4301–4310. https://doi.org/https://doi.org/10.1007/s00261-021-03091-y.

    Article  PubMed  Google Scholar 

  18. [18] M. Erkoc, A. Otunctemur, M. Bozkurt, O. Can, H.A. Atalay, H. Besiroglu, E. Danis, R.B. Degirmentepe, The efficacy and reliability of VI-RADS in determining candidates for repeated transurethral resection in patients with high-risk non-muscle invasive bladder cancer, Int J Clin Pr. 75 (2021) e14584. https://doi.org/https://doi.org/10.1111/ijcp.14584.

    Article  Google Scholar 

  19. [19] X. Wang, N. Tu, F. Sun, Z. Wen, X. Lan, Y. Lei, E. Cui, F. Lin, Detecting Muscle Invasion of Bladder Cancer Using a Proposed Magnetic Resonance Imaging Strategy, J Magn Reson Imaging. 54 (2021) 1212–1221. https://doi.org/https://doi.org/10.1002/jmri.27676.

    Article  PubMed  Google Scholar 

  20. [20] Y. Ueno, T. Tamada, M. Takeuchi, K. Sofue, S. Takahashi, Y. Kamishima, Y. Urase, A. Kido, N. Hinata, K. Harada, M. Fujisawa, Y. Miyaji, T. Murakami, VI-RADS: Multiinstitutional Multireader Diagnostic Accuracy and Interobserver Agreement Study, AJR Am J Roentgenol. 216 (2021) 1257–1266. https://doi.org/https://doi.org/10.2214/ajr.20.23604.

    Article  PubMed  Google Scholar 

  21. [21] B. Cao, Q. Li, P. Xu, W. Chen, X. Hu, C. Dai, Y. Shan, Y. Ding, W. Mao, K. Liu, P.Y. Wu, W. Sun, S. Rao, M. Zeng, S. Jiang, J. Zhou, Preliminary Exploration of the Application of Vesical Imaging-Reporting and Data System (VI-RADS) in Post-treatment Patients With Bladder Cancer: A Prospective Single-Center Study, J Magn Reson Imaging. (2021). https://doi.org/https://doi.org/10.1002/jmri.27807.

    Article  PubMed  PubMed Central  Google Scholar 

  22. [22] Y. Arita, K. Shigeta, H. Akita, T. Suzuki, R. Kufukihara, T.C. Kwee, R. Ishii, S. Mikami, S. Okuda, E. Kikuchi, M. Oya, M. **zaki, Clinical utility of the Vesical Imaging-Reporting and Data System for muscle-invasive bladder cancer between radiologists and urologists based on multiparametric MRI including 3D FSE T2-weighted acquisitions, Eur Radiol. 31 (2021) 875–883. https://doi.org/https://doi.org/10.1007/s00330-020-07153-5.

    Article  PubMed  Google Scholar 

  23. [23] A. Akcay, A.B. Yagci, S. Celen, Y. Ozlulerden, N.S. Turk, F. Ufuk, VI-RADS score and tumor contact length in MRI: A potential method for the detection of muscle invasion in bladder cancer, Clin Imaging. 77 (2021) 25–36. https://doi.org/https://doi.org/10.1016/j.clinimag.2021.02.026.

    Article  PubMed  Google Scholar 

  24. [24] Z. Wang, Y. Shang, T. Luan, Y. Duan, J. Wang, H. Wang, J. Hao, Evaluation of the value of the VI-RADS scoring system in assessing muscle infiltration by bladder cancer, Cancer Imaging. 20 (2020) 26. https://doi.org/https://doi.org/10.1186/s40644-020-00304-3.

    Article  PubMed  PubMed Central  Google Scholar 

  25. K. Sakamoto, M. Ito, S. Ikuta, Y. Nakanishi, M. Kataoka, K. Takemura, H. Suzuki, K.I. Tobisu, T. Kamai, F. Koga, Detection of Muscle-Invasive Bladder Cancer on Biparametric MRI Using Vesical Imaging-Reporting and Data System and Apparent Diffusion Coefficient Values (VI-RADS/ADC), Bl. Cancer. 6(2) (2020) 161–169. https://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=emed21&AN=632155410.

  26. [26] M. Marchioni, G. Primiceri, A. Delli Pizzi, R. Basilico, F. Berardinelli, E. Mincuzzi, R. Castellucci, B. Sessa, M. Di Nicola, L. Schips, Could Bladder Multiparametric MRI Be Introduced in Routine Clinical Practice? Role of the New VI-RADS Score: Results From a Prospective Study, Clin Genitourin Cancer. 18 (2020) 409–415.e1. https://doi.org/https://doi.org/10.1016/j.clgc.2020.03.002.

    Article  PubMed  Google Scholar 

  27. [27] S. Liu, F. Xu, T. Xu, Y. Yan, X. Yao, G. Tang, Evaluation of Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in predicting muscle invasion of bladder cancer, Transl Androl Urol. 9 (2020) 445–451. https://doi.org/https://doi.org/10.21037/tau.2020.02.16.

    Article  PubMed  PubMed Central  Google Scholar 

  28. [28] S.H. Kim, Validation of vesical imaging reporting and data system for assessing muscle invasion in bladder tumor, Abdom Radiol (NY). 45 (2020) 491–498. https://doi.org/https://doi.org/10.1007/s00261-019-02190-1.

    Article  PubMed  Google Scholar 

  29. [29] S.B. Hong, N.K. Lee, S. Kim, I.W. Son, H.K. Ha, J.Y. Ku, K.H. Kim, W.Y. Park, Vesical Imaging-Reporting and Data System for Multiparametric MRI to Predict the Presence of Muscle Invasion for Bladder Cancer, J Magn Reson Imaging. 52 (2020) 1249–1256. https://doi.org/https://doi.org/10.1002/jmri.27141.

    Article  PubMed  Google Scholar 

  30. [30] F. Del Giudice, G. Barchetti, E. De Berardinis, M. Pecoraro, V. Salvo, G. Simone, A. Sciarra, C. Leonardo, M. Gallucci, C. Catalano, J.W.F. Catto, V. Panebianco, Prospective Assessment of Vesical Imaging Reporting and Data System (VI-RADS) and Its Clinical Impact on the Management of High-risk Non-muscle-invasive Bladder Cancer Patients Candidate for Repeated Transurethral Resection, Eur Urol. 77 (2020) 101–109. https://doi.org/https://doi.org/10.1016/j.eururo.2019.09.029.

    Article  PubMed  Google Scholar 

  31. [31] H. Wang, C. Luo, F. Zhang, J. Guan, S. Li, H. Yao, J. Chen, J. Luo, L. Chen, Y. Guo, Multiparametric MRI for Bladder Cancer: Validation of VI-RADS for the Detection of Detrusor Muscle Invasion, Radiology. 291 (2019) 668–674. https://doi.org/https://doi.org/10.1148/radiol.2019182506.

    Article  PubMed  Google Scholar 

  32. [32] G. Barchetti, G. Simone, I. Ceravolo, V. Salvo, R. Campa, F. Del Giudice, E. De Berardinis, D. Buccilli, C. Catalano, M. Gallucci, J.W.F. Catto, V. Panebianco, Multiparametric MRI of the bladder: inter-observer agreement and accuracy with the Vesical Imaging-Reporting and Data System (VI-RADS) at a single reference center, Eur Radiol. 29 (2019) 5498–5506. https://doi.org/https://doi.org/10.1007/s00330-019-06117-8.

    Article  PubMed  Google Scholar 

  33. [33] J. Crozier, N. Papa, M. Perera, B. Ngo, D. Bolton, S. Sengupta, N. Lawrentschuk, Comparative sensitivity and specificity of imaging modalities in staging bladder cancer prior to radical cystectomy: a systematic review and meta-analysis, World J Urol. 37 (2019) 667–690. https://doi.org/https://doi.org/10.1007/s00345-018-2439-8.

    Article  PubMed  Google Scholar 

  34. [34] S. Woo, C.H. Suh, S.Y. Kim, J.Y. Cho, S.H. Kim, Diagnostic performance of MRI for prediction of muscle-invasiveness of bladder cancer: A systematic review and meta-analysis, Eur J Radiol. 95 (2017) 46–55. https://doi.org/https://doi.org/10.1016/j.ejrad.2017.07.021.

    Article  PubMed  Google Scholar 

  35. [35] N. Zhang, X. Wang, C. Wang, S. Chen, J. Wu, G. Zhang, W. Zhu, J. Liu, B. Xu, M. Du, M. Chen, Diagnostic Accuracy of Multi-Parametric Magnetic Resonance Imaging for Tumor Staging of Bladder Cancer: Meta-Analysis, Front Oncol. 9 (2019) 981. https://doi.org/https://doi.org/10.3389/fonc.2019.00981.

    Article  PubMed  PubMed Central  Google Scholar 

  36. [36] J.O. Barentsz, G.J. Jager, P.B. van Vierzen, J.A. Witjes, S.P. Strijk, H. Peters, N. Karssemeijer, S.H. Ruijs, Staging urinary bladder cancer after transurethral biopsy: value of fast dynamic contrast-enhanced MR imaging, Radiology. 201 (1996) 185–193. https://doi.org/https://doi.org/10.1148/radiology.201.1.8816542.

    Article  CAS  PubMed  Google Scholar 

  37. [37] H.J. Wang, M.H. Pui, Y. Guo, D. Yang, B.T. Pan, X.H. Zhou, Diffusion-weighted MRI in bladder carcinoma: the differentiation between tumor recurrence and benign changes after resection, Abdom Imaging. 39 (2014) 135–141. https://doi.org/https://doi.org/10.1007/s00261-013-0038-0.

    Article  PubMed  Google Scholar 

  38. [38] F. Del Giudice, M. Pecoraro, H.A. Vargas, S. Cipollari, E. De Berardinis, M. Bicchetti, B.I. Chung, C. Catalano, Y. Narumi, J.W.F. Catto, V. Panebianco, Systematic Review and Meta-Analysis of Vesical Imaging-Reporting and Data System (VI-RADS) Inter-Observer Reliability: An Added Value for Muscle Invasive Bladder Cancer Detection, Cancers (Basel). 12 (2020). https://doi.org/https://doi.org/10.3390/cancers12102994.

    Article  PubMed  PubMed Central  Google Scholar 

  39. [39] S.B. Donaldson, S.C. Bonington, L.E. Kershaw, R. Cowan, J. Lyons, T. Elliott, B.M. Carrington, Dynamic contrast-enhanced MRI in patients with muscle-invasive transitional cell carcinoma of the bladder can distinguish between residual tumour and post-chemotherapy effect, Eur J Radiol. 82 (2013) 2161–2168. https://doi.org/https://doi.org/10.1016/j.ejrad.2013.08.008.

    Article  PubMed  Google Scholar 

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Feng, Y., Zhong, K., Chen, R. et al. Diagnostic accuracy of vesical imaging-reporting and data system (VI-RADS) for the detection of muscle-invasive bladder cancer: a meta-analysis. Abdom Radiol 47, 1396–1405 (2022). https://doi.org/10.1007/s00261-022-03449-w

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