Share:
Share this content in WeChat
X
Experience Exchange
VI-RADS based on multi-parametric MRI for the prediction of muscle-invasion in bladder cancer and MRI findings of muscle-invasion in bladder cancer located in ureteral orifice
DENG Lei  ZOU Yujian  YANG Shuiqing  ZHANG Kunlin  HUANG Xiang  LI Jianpeng 

Cite this article as: Deng L, Zou YJ, Yang SQ, et al. VI-RADS based on multi-parametric MRI for the prediction of muscle-invasion in bladder cancer and MRI findings of muscle-invasion in bladder cancer located in ureteral orifice[J]. Chin J Magn Reson Imaging, 2022, 13(7): 121-125. DOI:10.12015/issn.1674-8034.2022.07.022.


[Abstract] Objective To explore the performance of Vesical Imaging-Reporting and Data System (VI-RADS) score based on multi-parametric magnetic resonance imaging (mp-MRI) in predicting muscle invasion in bladder cancer, and to analyze MRI findings of muscle invasion in bladder cancer occurring at ureteral orifice.Materials and Methods A total of 87 patients with 122 lesions diagnosed as bladder cancer by pathology were enrolled, and all the patients who had undergone mp-MRI were analyzed retrospectively. The two groups of radiologists, who were blinded to pathology and clinical data, reviewed and scored each lesion separately according to VI-RADS. The interobserver agreement of VI-RADS score was assessed by Kappa statistics. The predictive efficiency of detection of muscle invasion in bladder cancer was evaluated by receiver operator characteristic (ROC) curve. The relationship between bladder cancer located around ureterovesical orifice and ureter was also analyzed.Results Interobserver agreement of VI-RADS score between the two groups of radiologists was good [Kappa value=0.727, P<0.001, the area under the ROC curve were 0.880 (95% confidence interval: 0.808-0.932) and 0.905 (95% confidence interval: 0.838-0.950)].With regard to ROC analysis, the best cutoff-point was 3 for the detection of muscle invasion. The Youden index was 67.8%, with a sensitivity of 76.7%, specificity of 91.1%, positive predictive value of 82.5% and negative predictive value of 87.8%. Twenty-nine lesions were located in the ureterovesical orifice. The 7 lesions of 29 lesions appeared as pedicle embedding the ureteral orifice, and 85.7% (6/7) were non-muscle invasive bladder cancer. The other 22 lesions showed blurred boundary with ureterall orifice, and 95.5% (21/22) were muscle invasive bladder cancer.Conclusions Multi-parametric MRI-based VI-RADS exhibited a high agreement between different radiologists, and can effectively predict the muscle invasion of bladder cancer. In the case of the bladder cancer located in the bilateral ureteral orifice, further review on the association between pedicle of tumour or tumour tissue and ureteral orifice is required.
[Keywords] Vesical Imaging-Reporting and Data System;bladder neoplasms;muscular invasiveness;ureteral orifice;magnetic resonance imaging

DENG Lei   ZOU Yujian   YANG Shuiqing   ZHANG Kunlin   HUANG Xiang   LI Jianpeng*  

Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University (Dongguan People's hospital), Dongguan 523000, China

Li JP, E-mail: ljp0885@qq.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Dongguan Science and Technology of Social Development Program (No. 20211800905212).
Received  2022-03-07
Accepted  2022-06-24
DOI: 10.12015/issn.1674-8034.2022.07.022
Cite this article as: Deng L, Zou YJ, Yang SQ, et al. VI-RADS based on multi-parametric MRI for the prediction of muscle-invasion in bladder cancer and MRI findings of muscle-invasion in bladder cancer located in ureteral orifice[J]. Chin J Magn Reson Imaging, 2022, 13(7): 121-125. DOI:10.12015/issn.1674-8034.2022.07.022.

[1]
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
[2]
Babjuk M, Burger M, Capoun O, et al. European association of urology guidelines on non-muscle-invasive bladder cancer (Ta, T1, and carcinoma in situ)[J]. Eur Urol, 2022, 81(1): 75-94. DOI: 10.1016/j.eururo.2021.08.010.
[3]
Witjes JA, Bruins HM, Cathomas R, et al. European association of urology guidelines on muscle-invasive and metastatic bladder cancer: summary of the 2020 guidelines[J]. Eur Urol, 2021, 79(1): 82-104. DOI: 10.1016/j.eururo.2020.03.055.
[4]
Huang L, Kong QC, Liu ZZ, et al. The diagnostic value of MR imaging in differentiating T staging of bladder cancer: a meta-analysis[J]. Radiology, 2018, 286(2): 502-511. DOI: 10.1148/radiol.2017171028.
[5]
van der Pol CB, Chung A, Lim C, et al. Update on multiparametric MRI of urinary bladder cancer[J]. J Magn Reson Imaging, 2018, 48(4): 882-896. DOI: 10.1002/jmri.26294.
[6]
Hayashi N, Tochigi H, Shiraishi T, et al. A new staging criterion for bladder carcinoma using gadolinium-enhanced magnetic resonance imaging with an endorectal surface coil: a comparison with ultrasonography[J]. BJU Int, 2000, 85(1): 32-36. DOI: 10.1046/j.1464-410x.2000.00358.x.
[7]
Panebianco V, de Berardinis E, Barchetti G, et al. An evaluation of morphological and functional multi-parametric MRI sequences in classifying non-muscle and muscle invasive bladder cancer[J]. Eur Radiol, 2017, 27(9): 3759-3766. DOI: 10.1007/s00330-017-4758-3.
[8]
Takeuchi M, Sasaki S, Ito M, et al. Urinary bladder cancer: diffusion-weighted MR imaging: accuracy for diagnosing T stage and estimating histologic grade[J]. Radiology, 2009, 251(1): 112-121. DOI: 10.1148/radiol.2511080873.
[9]
Caglic I, Panebianco V, Vargas HA, et al. MRI of bladder cancer: local and nodal staging[J]. J Magn Reson Imaging, 2020, 52(3): 649-667. DOI: 10.1002/jmri.27090.
[10]
Panebianco V, Narumi Y, Altun E, et al. Multiparametric magnetic resonance imaging for bladder cancer: development of VI-RADS (vesical imaging-reporting and data system)[J]. Eur Urol, 2018, 74(3): 294-306. DOI: 10.1016/j.eururo.2018.04.029.
[11]
Zhang TH, Gu ZC, Yao C, et al. Diagnostic value of multiparametric MRI using vesical imaging reporting and data system in detecting muscle-invasiveness of bladder cancer[J]. J Chin Clin Med Imaging, 2019, 30(8): 569-573. DOI: 10.12117/jccmi.2019.08.010.
[12]
Wang HJ, Luo C, Zhang F, et al. Multiparametric MRI for bladder cancer: validation of VI-RADS for the detection of detrusor muscle invasion[J]. Radiology, 2019, 291(3): 668-674. DOI: 10.1148/radiol.2019182506.
[13]
Ueno Y, Takeuchi M, Tamada T, et al. Diagnostic accuracy and interobserver agreement for the vesical imaging-reporting and data system for muscle-invasive bladder cancer: a multireader validation study[J]. Eur Urol, 2019, 76(1): 54-56. DOI: 10.1016/j.eururo.2019.03.012.
[14]
Kim SH. Validation of vesical imaging reporting and data system for assessing muscle invasion in bladder tumor[J]. Abdom Radiol (NY), 2020, 45(2): 491-498. DOI: 10.1007/s00261-019-02190-1.
[15]
Arita Y, Shigeta K, Akita H, et al. 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[J]. Eur Radiol, 2021, 31(2): 875-883. DOI: 10.1007/s00330-020-07153-5.
[16]
Paner GP, Montironi R, Amin MB. Challenges in pathologic staging of bladder cancer: proposals for fresh approaches of assessing pathologic stage in light of recent studies and observations pertaining to bladder histoanatomic variances[J]. Adv Anat Pathol, 2017, 24(3): 113-127. DOI: 10.1097/PAP.0000000000000152.
[17]
Ueno Y, Tamada T, Takeuchi M, et al. VI-RADS: multiinstitutional multireader diagnostic accuracy and interobserver agreement study[J]. AJR Am J Roentgenol, 2021, 216(5): 1257-1266. DOI: 10.2214/AJR.20.23604.
[18]
del Giudice F, Pecoraro M, Vargas HA, et al. 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[J]. Cancers (Basel), 2020, 12(10): E2994. DOI: 10.3390/cancers12102994.
[19]
Metwally MI, Zeed NA, Hamed EM, et al. The validity, reliability, and reviewer acceptance of VI-RADS in assessing muscle invasion by bladder cancer: a multicenter prospective study[J]. Eur Radiol, 2021, 31(9): 6949-6961. DOI: 10.1007/s00330-021-07765-5.
[20]
Yang YH, Zou XH, Wang YX, et al. Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT[J]. Eur J Radiol, 2021, 139: 109666. DOI: 10.1016/j.ejrad.2021.109666.
[21]
Zheng JJ, Kong JQ, Wu SX, et al. Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach[J]. Cancer, 2019, 125(24): 4388-4398. DOI: 10.1002/cncr.32490.
[22]
Li SC, Liang P, Wang YC, et al. Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer[J]. Abdom Radiol (NY), 2021, 46(9): 4301-4310. DOI: 10.1007/s00261-021-03091-y.
[23]
Feng C, Wang YC, Dan GY, et al. Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma[J]. Eur Radiol, 2022, 32(2): 890-900. DOI: 10.1007/s00330-021-08203-2.

PREV Value of multi-parameter MRI combined with immune inflammatory markers in predicting axillary lymph node metastasis of breast cancer
NEXT Primary central nervous system Burkitt lymphoma: One case report and literature review
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn