Modern possibilities of radiological diagnosis of bladder cancer

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Bladder cancer is one of the most severe and common diseases of genitourinary organs. According to WHO statistics, bladder cancer is the tenth in cancer morbidity structure and the 13th in cancer mortality structure in the world. In Russia, bladder cancer is 11th in cancer morbidity structure and 16th in cancer mortality structure. In most cases, bladder cancer is diagnosed at 65–74 years of age. The 5-year survival rate for stage IV bladder cancer is about 15%. Early detection, correct staging, and management of the patient influence the prognosis and further quality of life. This review shows detection and staging methods of bladder cancer, staging categories based on multiparametric magnetic-resonance imaging with the use of Vesical Imaging-Reporting and Data System (VI-RADS). Illustrations and a brief overview of alternative visualization methods of bladder lesions, and new approaches in assessment of digital medical images, radiomics and radiogenomics, are presented. In the future, these methods should help to determine the biological characteristics of the tumor without taking a biopsy.

作者简介

Maria Suchilova

Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies

编辑信件的主要联系方式.
Email: maria.suchilova@gmail.com
ORCID iD: 0000-0003-1117-0294
SPIN 代码: 4922-1894

Research Assistant

俄罗斯联邦, Moscow

Aleksandr Nikolaev

Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: a.e.nikolaev@yandex.ru
ORCID iD: 0000-0001-5151-4579
SPIN 代码: 1320-1651

Research Assistant

俄罗斯联邦, Moscow

Arsen Shapiev

Morozov Children's Clinical Hospital; Russian Children's Clinical Hospital of Russian National Research Medical University

Email: shapiev_an@mail.ru
ORCID iD: 0000-0002-1890-6711
SPIN 代码: 1662-0349

науч. сотр., отдел ДПО

俄罗斯联邦, Moscow

Guzel Mukhutdinova

Pirogov Russian National Research Medical University

Email: dr.guzelzuferovna@gmail.com
ORCID iD: 0000-0002-0623-7194
SPIN 代码: 5568-0859

Student

俄罗斯联邦, Moscow

Polina Tkacheva

Pirogov Russian National Research Medical University

Email: polya_tkacheva@mail.ru
ORCID iD: 0000-0001-8349-6598
SPIN 代码: 7190-7661

Student

俄罗斯联邦, Moscow

Marina Nikiforova

Pirogov Russian National Research Medical University

Email: nikif.802@mail.ru
ORCID iD: 0000-0001-8933-6544
SPIN 代码: 1086-5509

Resident

俄罗斯联邦, Moscow

Viktor Gombolevskiy

Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: gombolevskiy@npcmr.ru
ORCID iD: 0000-0003-1816-1315
SPIN 代码: 6810-3279

Cand. Sci. (Med.)

俄罗斯联邦, Moscow

Sergey Morozov

Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: npcmr@zdrav.mos.ru
ORCID iD: 0000-0001-6545-6170
SPIN 代码: 8542-1720

D. Sci. (Med.), Prof.

俄罗斯联邦, Moscow

参考

  1. Статистические данные Национального института онкологии (National Cancer Institute). https://seer.cancer.gov/statfacts/html/urinb.html[Statisticheskie dannye Natsional’nogo instituta onkologii (National Cancer Institute). https://seer.cancer.gov/statfacts/html/urinb.html (in Russian).]
  2. Статистические данные ВОЗ. https://gco.iarc.fr/today/data/factsheets/cancers/30-Bladder-fact-sheet.pdf [Statisticheskie dannye VOZ. https://gco.iarc.fr/today/data/factsheets/cancers/30-Bladder-fact-sheet.pdf (in Russian).]
  3. Статистические данные ВОЗ. https://gco.iarc.fr/today/data/factsheets/populations/643-russian-federation-fact-sheets.pdf [Statisticheskie dannye VOZ. https://gco.iarc.fr/today/data/factsheets/populations/643-russian-federation-fact-sheets.pdf (in Russian).]
  4. Malayeri AA, Pattanayak P, Apolo AB. Imaging muscle-invasive and metastatic urothelial carcinoma. Curr Opin Urol 2015; 25 (5): 441–8.
  5. D’Andrea D, Black PC, Zargar H et al. Impact of sex on response to neoadjuvant chemotherapy in patients with bladder cancer. Urologic Oncology: Seminars and Original Investigations. Elsevier 2020.
  6. Saginala K, Barsouk A, Aluru JS et al. Epidemiology of Bladder Cancer. J Med Sci 2020; 8 (1): 15.
  7. Статистические данные Национального института онкологии (National Cancer Institute). https://seer.cancer.gov/statfacts/html/urinb.html [Statisticheskie dannye Natsional’nogo instituta onkologii (National Cancer Institute). https://seer.cancer.gov/statfacts/html/urinb.html (in Russian).]
  8. Статистические данные ВОЗ. https://www.who.int/ageing/publications/ global_health.pdf?ua=1 [Statisticheskie dannye VOZ. https://www.who.int/ageing/publications/ global_health.pdf?ua=1 (in Russian).]
  9. Naka M, Shuto S, Konishi C, Maekawa K. High prevalence of airway obstruction and pulmonary emphysema in urothelial (renal pelvis, ureter, and bladder) cancer patients. Respir Investig 2020.
  10. Antoni S, Ferlay J, Soerjomataram I et al. Bladder cancer incidence and mortality: a global overview and recent trends. Eur Urol 2017; 71 (1): 96–108.
  11. Oh H, Lee DH, Giovannucci EL, Keum N. Gastric and duodenal ulcers, periodontal disease, and risk of bladder cancer in the Health Professionals Follow-up Study. Cancer Causes Control 2020; 31 (4): 383–91.
  12. Mahdavifar N, Ghoncheh M, Pakzad R et al. Epidemiology, incidence and mortality of bladder cancer and their relationship with the development index in the world. Asian Pac J Cancer Prev 2016; 17 (1): 381–6.
  13. Guideline, N. I. C. E, and National Institute for Clinical Excellence. Bladder Cancer: Diagnosis and Management. BJU Int 2017; 120 (6): 755–65.
  14. Kamat AM, Karam JA, Grossman HB et al. Prospective trial to identify optimal bladder cancer surveillance protocol: reducing costs while maximizing sensitivity. BJU Int 2011; 108 (7): 1119–23.
  15. Hafeez, S, Huddart, R. Advances in bladder cancer imaging. BMC Med 2013; 11 (1): 104.
  16. Avcu S, Koseoglu MN, Ceylan K et al. The value of diffusion-weighted MRI in the diagnosis of malignant and benign urinary bladder lesions. Br J Radiol 2011; 84 (1006): 875–82.
  17. El-Assmy A, Abou-El-Ghar ME, Mosbah A et al. Bladder tumour staging: comparison of diffusion- and T2-weighted MR imaging. Eur Radiol 2009; 19 (7): 1575–81.
  18. Zhou G, Chen X, Zhang J et al. Contrast-enhanced dynamic and diffusion-weighted MR imaging at 3.0T to assess aggressiveness of bladder cancer. Eur J Radiol 2014; 83 (11): 2013–8.
  19. Isfoss BL. The sensitivity of fluorescent-light cystoscopy for the detection of carcinoma in situ (CIS) of the bladder: a meta-analysis with comments on gold standard. BJU Int 2011: 108 (11): 1703–7.
  20. Liu JJ, Droller MJ, Liao JC. New optical imaging technologies for bladder cancer: considerations and perspectives. J Urol 2012; 188 (2): 361–8.
  21. Hafeez S, Huddart R. Advances in bladder cancer imaging. BMC Med 2013; 11 (1): 104.
  22. Kamat AM, Karam JA, Grossman HB et al. Prospective trial to identify optimal bladder cancer surveillance protocol: reducing costs while maximizing sensitivity. BJU Int 2011; 108 (7): 1119–23.
  23. Park HJ, Hong SS, Kim JH et al. Tumor detection and serosal invasion of bladder cancer: role of three-dimensional volumetric reconstructed US. Abdom Imaging 2010; 35 (3): 265–70.
  24. Itzchak Y, Singer D, Fischelovitch Y. Ultrasonographic assessment of bladder tumors. 1. Tumor detection. J Urol 1981; 126 (1): 31–3.
  25. Wong-You-Cheong JJ, Woodward PJ, Manning MA, Sesterhenn IA. Neoplasms of the urinary bladder: radiologic-pathologic correlation. Radiographics 2006; 26 (2): 553–80.
  26. Huang L, Kong Q, Liu Z et al. The diagnostic value of MR imaging in differentiating T staging of bladder cancer: a meta-analysis. Radiology 2018; 286 (2): 502–11.
  27. Purysko AS, Leão Filho HM, Herts BR. Radiologic imaging of patients with bladder cancer. Semin Oncol 2012; 39 (5): 543–58.
  28. Hodson NJ, Husband JE, MacDonald JS. The role of computed tomography in the staging of bladder cancer. Clin Radiol 1979; 30 (4): 389–95.
  29. Sammet S. Magnetic resonance safety. Abdom radiol (NY) 2016; 41 (3): 444–51.
  30. Harkirat S, Anand SS, Jacob MJ. Forced diuresis and dual-phase 18F-fluorodeoxyglucose-PET/CT scan for restaging of urinary bladder cancers. Indian J Radiol Imaging 2010; 20 (1): 13–9.
  31. Anjos DA, Etchebehere EC, Ramos CD et al. 18F-FDG PET/CT delayed images after diuretic for restaging invasive bladder cancer. J Nucl Med 2007; 48 (5): 764–70.
  32. Goodfellow H, Viney Z, Hughes P et al. Role of fluorodeoxyglucose positron emission tomography (FDG PET)–computed tomography (CT) in the staging of bladder cancer. BJU Int 2014; 114 (3): 389–95.
  33. Cipollari S, Carnicelli G, Bicchetti M et al. Utilization of imaging for staging in bladder cancer: is there a role for MRI or PET-computed tomography? Curr Opin Urol 2020; 30 (3): 377–86.
  34. Kibel AS, Dehdashti F, Katz MD et al. Prospective study of [18F] fluorodeoxyglucose positron emission tomography/computed tomography for staging of muscle-invasive bladder carcinoma. J Clin Oncol 2009; 27 (26): 4314–20.
  35. Drieskens O, Oyen R, Van Poppel H et al. FDG-PET for preoperative staging of bladder cancer. Eur J Nucl Med Mol Imaging 2005; 32 (12): 1412–7.
  36. Lu YY, Chen JH, Liang JA et al. Clinical value of FDG PET or PET/CT in urinary bladder cancer: a systemic review and meta-analysis. Eur J Radiol 2012; 81 (9): 2411–6.
  37. Lodde M, Lacombe L, Friede J et al. Evaluation of fluorodeoxyglucose positron-emission tomography with computed tomography for staging of urothelial carcinoma. BJU Int 2010; 106 (5): 658–63.
  38. Öztürk H, Karapolat I. Efficacy of 18F-fluorodeoxyglucose-positron emission tomography/computed tomography in restaging muscle-invasive bladder cancer following radical cystectomy. Exp Ther Med 2015; 9 (3): 717–24.
  39. Civelek AC, Apolo A, Agarwal P et al. 18F-FDG PET-MRI in the management of muscle invasive bladder cancer: Challenges in imaging and solutions. J Nucl Med 2016; 57 (Suppl. 2): 1292.
  40. Civelek A, Lin J, Agarwal P et al. FDG PET-MRI in the management of patients with muscle invasive bladder cancer. J Nucl Med 2017; 58 (Suppl. 1): 753.
  41. Helenius M, Brekkan E, Dahlman P et al. Bladder Cancer Detection in Patients With Gross Haematuria: Computed Tomography Urography With Enhancement-Triggered Scan Versus Flexible Cystoscopy. Scand J Urol 2015; 49 (5): 377–81.
  42. Gharibvand MM, Kazemi M, Motamedfar A et al. The role of ultrasound in diagnosis and evaluation of bladder tumors. J Family Med Prim Care 2017; 6 (4): 840–3.
  43. Capalbo E, Kluzer A, Peli M et al. Bladder cancer diagnosis: the role of CT urography. Tumori 2015; 101 (4): 412–7.
  44. 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. Radiology 2009; 251: 415–21.
  45. Eulitt P, Altun E, Sheikh A et al. Pilot study of [18F] fluorodexoyglucose positron emission tomography-magnetic resonance imaging (FDG-PET-MRI) for staging of muscle-invasive bladder cancer. J Clin Oncol 2019: e16002.
  46. Wallmeroth A, Wagner U, Moch H et al. Patterns of metastasis in muscle-invasive bladder cancer (pT2–4): an autopsy study on 367 patients. Urol Int 1999; 62 (2): 69–75.
  47. Horn T, Zahel T, Adt N et al. Evaluation of computed tomography for lymph node staging in bladder cancer prior to radical cystectomy. Urol Int 2016; 96 (1): 51–6.
  48. Girard A, Rouanne M, Taconet S et al. Integrated analysis of 18 F-FDG PET/CT improves preoperative lymph node staging for patients with invasive bladder cancer. Eur Radiol 2019; 29 (8): 4286–93.
  49. 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). Eur Urol 2018; 74 (3): 294–306.
  50. Malayeri AA, Pattanayak P, Apolo A. B. Imaging muscle-invasive and metastatic urothelial carcinoma. Curr Opin Urol 2015; 25 (5): 441–8.
  51. Del Giudice F, Barchetti G, De Berardinis E et al. 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 2020; 77 (1): 101–9.
  52. Cipollari S, Carnicelli G, Bicchetti M et al. Utilization of imaging for staging in bladder cancer: is there a role for MRI or PET-computed tomography? Curr Opin Urol 2020; 30 (3): 377–86.
  53. Johnson W, Taylor MB, Carrington BM et al. The value of hyoscine butylbromide in pelvic MRI. Clin Radiol 2020; 62 (11): 1087–93.
  54. Donaldson SB, Bonington SC, Kershaw LE et al. 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 2013; 82 (12): 2161–8.
  55. Takeuchi M, Sasaki S, Naiki T et al. MR imaging of urinary bladder cancer for T-staging: a review and a pictorial essay of diffusion-weighted imaging. J Magn Reson Imaging. 2013; 38 (6): 1299–309.
  56. Takeuchi M, Sasaki S, Ito M et al. Urinary bladder cancer: diffusion-weighted MR imaging–accuracy for diagnosing T stage and estimating histologic grade. Radiology 2009; 251 (1): 112.
  57. Liu S, Xu F, Xu T et al. Evaluation of Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in predicting muscle invasion of bladder cancer Transl Androl Urol 2020; 9 (2): 445–51.
  58. Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 2016; 278 (2): 563–77.
  59. Yip SS, Aerts HJ. Applications and limitations of radiomics. Phys Med Biol 2016; 61 (13): R150.
  60. Zhang X, Xu X, Tian Q et al. Radiomics assessment of bladder cancer grade using texture features from diffusion‐weighted imaging. J Magn Reson Imaging 2017; 46 (5): 1281–8.
  61. Zheng J, Kong J, Wu S et al. Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach. Cancer 2019; 125 (24): 4388–98.
  62. Xu X, Wang H, Du P et al. A predictive nomogram for individualized recurrence stratification of bladder cancer using multiparametric MRI and clinical risk factors. J Magn Reson Imaging 2019; 50 (6): 1893–904.
  63. Wu S, Zheng J, Li Y et al. A radiomics nomogram for the preoperative prediction of lymph node metastasis in bladder cancer. Clin Cancer Res 2017; 23 (22); 6904–11.
  64. Cha KH, Hadjiiski L, Chan HP et al. Bladder cancer treatment response assessment in CT using radiomics with deep-learning. Sci Rep 2017; 7 (1): 1–12.
  65. Lin P, Wen DY, Chen L, Li X et al. A radiogenomics signature for predicting the clinical outcome of bladder urothelial carcinoma. Eur Radiol 2020; 30 (1): 547–57.

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