Diagnostic Accuracy of Magnetic Resonance Imaging in diagnosing Urinary Bladder Cancer, Taking Histopathology as Gold Standard
DOI:
https://doi.org/10.51253/pafmj.v74iSUPPL-2.10849Keywords:
Urinary bladder cancer, Magnetic resonance imaging, SensitivityAbstract
Objective: To determine the diagnostic accuracy of Magnetic resonance imaging in diagnosing and staging urinary bladder cancer, taking histopathology as gold standard.
Study Design: Descriptive, Cross-sectional study.
Place and Duration of Study: The study was done in Department of Diagnostic Radiology, Combined Military Hospital, Multan, Pakistan from Jan to Dec 2020.
Methodology: A total of 117 patients with irregular soft tissue structures of low echogenicity projecting into the bladder lumen from a fixed mural site on ultrasonography aged 20-60 years of either gender were included in the study. While patients already taking radiotherapy or immunotherapy or having any other contraindication to Magnetic resonance imaging were excluded. Magnetic resonance imaging was performed in every patient using 1.5 Tesla MR system. Magnetic Resonance Imaging findings were interpreted by consultant radiologist for presence or absence of urinary bladder carcinoma and further local staging of carcinoma if present. Magnetic resonance imaging findings were compared with histopathology results taken via cystoscopy.
Results: All the patients were subjected to Magnetic resonance imaging abdomen pelvis and found that 60 were True Positive and 05 were False Positive. Among 52, MRI negative patients, 05 (False Negative) had urinary bladder carcinoma on histopathology whereas 47 (True Negative) had no carcinoma on histopathology (p=0.0001). Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of Magnetic resonance imaging in diagnosing and staging urinary bladder cancer, taking histopathology as gold standard was 92.31%, 90.38%, 92.31%, 90.38% and 91.45% respectively.
Conclusion: MRI is a highly sensitive and accurate noninvasive
Downloads
References
Zhang N, Wang X, Wang C. Diagnostic Accuracy of Multi-Parametric Magnetic Resonance Imaging for Tumor Staging of Bladder Cancer: Meta-Analysis. Front. Oncol 2019; 9:981.
https://doi: 10.3389/fonc.2019.00981
Teama AH, Darweesh AN, Abol-Enin HA, Abouelkheir RT. Role of multidetector computed tomography virtual cystoscopy in evaluation of urinary bladder carcinoma. Egyptian J Radiol Nuclear Med 2014; 45: 543-54.
http://doi.org/10.1016/j.ejrnm.2014.02.015
Degeorge KC, Holt HR, Hodges SC. Bladder cancer: diagnosis and treatment. Am Fam Phys (2017) 96: 507–14.
Maurer T, Horn T, Heck M, Gschwend JE, Eiber M, Beer AJ, et al. Current staging procedures in urinary bladder cancer. Diagnostics 2013; 3: 315-324.
https://doi.org/10.3390/diagnostics3030315
De Haas RJ, Steyvers MJ, Fütterer JJ, Multiparametric M. MRI of the bladder: ready for clinical routine. AJR Am J Roentgenol 2014; 202: 1187–1195.https://doi.org/10.2214/ajr.13.12294
Gandrup KL, Nordling J, Henrik S. MRI of the bladder in patients suspected of bladder tumors. Open J Radiol 2014; 4: 207–214.http://doi.org/10.4236/ojrad.2014.42028
Abdel-Rahman HM, Fiki ME, Desoky AE, Elsayed ER, Abd Samad KM. The role of diffusion-weighted magnetic resonance imaging in T staging and grading of urinary bladder cancer. Egyptian J Radiol Nuclear Med 2015; 46(3): 741-747.
Zytoon AA, Azab SM, Abo Samak WA. Role of magnetic resonance in evaluation of urinary bladder cancer. Menoufia Med J 2017; 30: 104-109.
Tekes A, Kamel I, Imam K, et al. Dynamic MRI of bladder cancer: evaluation of staging accuracy. AJR Am J Roentgenol. 2005;184(1):121-127
Wang HJ, Pui MH, Guo Y. Multiparametric 3-T MRI for differentiating low versus high-grade and category T1 versus T2 bladder urothelial carcinoma. AJR Am J Roentgenol 2015; 204(2): 330-334.https://doi.org/10.2214/ajr.14.13147
El-Assmy A, Abou-El-Ghar ME, Mosbah A. Bladder tumour staging: comparison of diffusion- and T2- weighted MR imaging. Eur Radiol 2009; 19(7): 1575-1581.https://doi.org/10.1007/s00330-009-1340-7
Takeuchi M, Sasaki S, Ito M. Urinary bladder cancer: diffusion weighted MR imaging--accuracy for diagnosing T stage and estimating histologic grade. Radiology 2009; 251(1): 112-121.https://doi.org/10.1148/radiol.2511080873
Abou-El-Ghar ME, El-Assmy A, Refaie HF, El-Diasty T. Bladder cancer: diagnosis with diffusion-weighted MR imaging in patients with gross hematuria. Radiol 2009; 251: 415-421.
https://doi.org/10.1148/radiol.2503080723
Brierley J, Gospodarowicz MK,Wittekind C. TNM Classification of Malignant Tumors. 8th ed. Chichester: Chichester Wiley (2017)
Narumi Y, Kadota T, Inoue E. Bladder tumors: staging with gadolinium enhanced oblique MR imaging. Radiology 1993; 187: 145–150.
https://doi.org/10.1148/radiology.187.1.8451401
Daneshmand S, Ahmadi H, Huynh LN, Dobos N. Preoperative staging of invasive bladder cancer with dynamic gadolinium-enhanced magnetic resonance imaging: results from a prospective study. J. Urology 2012; 80(6): 1313-1318.https://doi.org/10.1016/j.urology.2012.07.056
Rajesh A, Sokhi HK, Fung R, Mulcahy KA, Bankart MJ. Bladder cancer evaluation of staging accuracy using dynamic MRI. Clin Radiol. 2011; 66(12): 1140-1145.
https://doi.org/10.1016/j.crad.2011.05.019
Gupta N, Sureka B, Kumar MM, Malik A, Bhushan TB, Mohanty NK. Comparison of dynamic contrast enhanced and diffusion weighted magnetic resonance image in staging and grading of carcinoma bladder with histopathological correlation. Urol Ann. 2015;7(2):199-204
Nguyen HT, Pohar KS, Jia G. Improving bladder cancer imaging using 3-T functional dynamic contrast enhanced magnetic resonance imaging. Invest Radiol 2014; 49(6): 390-395108.https://doi.org/10.1097/rli.0000000000000022
Klein L, Pollack HM. Computed tomography and magnetic resonance imaging of the female lower urinary tract. Radiol Clin North Am 1992; 30(4): 843-860
Beyersdorff D, Zhang J, Schoder H, Bochner B, Hricak H. Bladder cancer: can imaging change patient management? Curr Opin Urol 2008; 18(1): 98-104
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Mubashrah Aziz, Sadaf Aziz, Ammara Tariq, Yasser khan, Atif Latif, Munazzah Aziz

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.