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Congress: ECR25
Poster Number: C-18188
Type: Poster: EPOS Radiologist (scientific)
Authorblock: D. H. Kim1, M. H. Choi1, L. Youngjoon1, S. E. Rha1, D. Nickel2, H-S. Lee1, D. Han1; 1Seoul/KR, 2Erlangen/DE
Disclosures:
Dong Hwan Kim: Nothing to disclose
Moon Hyung Choi: Grant Recipient: Siemens Healthineers
Lee Youngjoon: Nothing to disclose
Sung Eun Rha: Nothing to disclose
Dominik Nickel: Employee: Siemens Healthineers
Hyun-Soo Lee: Employee: Siemens Healthineers Ltd.
Dongyeob Han: Employee: Siemens Healthineers Ltd.
Keywords: Genital / Reproductive system male, Pelvis, MR, Biopsy, Cancer
References
  1. Fernandes MC, Yildirim O, Woo S, Vargas HA, Hricak H, The role of MRI in prostate cancer: current and future directions, MAGMA. 35, 503-521 (2022).
  2. Park JJ, Kim CK, Paradigm Shift in Prostate Cancer Diagnosis: Pre-Biopsy Prostate Magnetic Resonance Imaging and Targeted Biopsy, Korean J Radiol. 23, 625-637 (2022).
  3. Gaur S, Turkbey B, Prostate MR Imaging for Posttreatment Evaluation and Recurrence, Radiol Clin North Am. 56, 263-275 (2018).
  4. Lee CH, Tan TW, Tan CH, Multiparametric MRI in Active Surveillance of Prostate Cancer: An Overview and a Practical Approach, Korean J Radiol. 22, 1087-1099 (2021).
  5. Rajwa P, Pradere B, Quhal F, Mori K, Laukhtina E, Huebner NA, et al., Reliability of Serial Prostate Magnetic Resonance Imaging to Detect Prostate Cancer Progression During Active Surveillance: A Systematic Review and Meta-analysis, Eur Urol. 80, 549-563 (2021).
  6. Oberlin DT, Casalino DD, Miller FH, Meeks JJ, Dramatic increase in the utilization of multiparametric magnetic resonance imaging for detection and management of prostate cancer, Abdom Radiol (NY). 42, 1255-1258 (2017).
  7. Kuhl CK, Bruhn R, Kramer N, Nebelung S, Heidenreich A, Schrading S, Abbreviated Biparametric Prostate MR Imaging in Men with Elevated Prostate-specific Antigen, Radiology. 285, 493-505 (2017).
  8. Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, et al., Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2, Eur Urol. 76, 340-351 (2019).
  9. Gupta RT, Spilseth B, Patel N, Brown AF, Yu J, Multiparametric prostate MRI: focus on T2-weighted imaging and role in staging of prostate cancer, Abdom Radiol (NY). 41, 831-843 (2016).
  10. Onay A, Ertas G, Vural M, Colak E, Esen T, Bakir B, The role of T2-weighted images in assessing the grade of extraprostatic extension of the prostate carcinoma, Abdom Radiol (NY). 45, 3293-3300 (2020).
  11. Bass EJ, Pantovic A, Connor M, Gabe R, Padhani AR, Rockall A, et al., A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk, Prostate Cancer Prostatic Dis. 24, 596-611 (2021).
  12. Cuocolo R, Verde F, Ponsiglione A, Romeo V, Petretta M, Imbriaco M, et al., Clinically Significant Prostate Cancer Detection With Biparametric MRI: A Systematic Review and Meta-Analysis, AJR Am J Roentgenol. 216, 608-621 (2021).
  13. Alabousi M, Salameh JP, Gusenbauer K, Samoilov L, Jafri A, Yu H, et al., Biparametric vs multiparametric prostate magnetic resonance imaging for the detection of prostate cancer in treatment-naive patients: a diagnostic test accuracy systematic review and meta-analysis, BJU Int. 124, 209-220 (2019).
  14. Schoots IG, Barentsz JO, Bittencourt LK, Haider MA, Macura KJ, Margolis DJA, et al., PI-RADS Committee Position on MRI Without Contrast Medium in Biopsy-Naive Men With Suspected Prostate Cancer: Narrative Review, AJR Am J Roentgenol. 216, 3-19 (2021).
  15. Tavakoli AA, Hielscher T, Badura P, Gortz M, Kuder TA, Gnirs R, et al., Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer, Radiology. 306, 186-199 (2023).
  16. Christophe C, Montagne S, Bourrelier S, Roupret M, Barret E, Rozet F, et al., Prostate cancer local staging using biparametric MRI: assessment and comparison with multiparametric MRI, Eur J Radiol. 132, 109350 (2020).
  17. Abreu-Gomez J, Lim C, Cron GO, Krishna S, Sadoughi N, Schieda N, Pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI in PI-RADS category 3 peripheral zone lesions: preliminary study evaluating DCE-MRI as an imaging biomarker for detection of clinically significant prostate cancers, Abdom Radiol (NY). 46, 4370-4380 (2021).
  18. Winkel DJ, Heye TJ, Benz MR, Glessgen CG, Wetterauer C, Bubendorf L, et al., Compressed Sensing Radial Sampling MRI of Prostate Perfusion: Utility for Detection of Prostate Cancer, Radiology. 290, 702-708 (2019).
  19. Caglic I, Sushentsev N, Shah N, Warren AY, Lamb BW, Barrett T, Comparison of biparametric versus multiparametric prostate MRI for the detection of extracapsular extension and seminal vesicle invasion in biopsy naive patients, Eur J Radiol. 141, 109804 (2021).
  20. Zawaideh JP, Sala E, Shaida N, Koo B, Warren AY, Carmisciano L, et al., Diagnostic accuracy of biparametric versus multiparametric prostate MRI: assessment of contrast benefit in clinical practice, Eur Radiol. 30, 4039-4049 (2020).
  21. Kiryu S, Akai H, Yasaka K, Tajima T, Kunimatsu A, Yoshioka N, et al., Clinical Impact of Deep Learning Reconstruction in MRI, Radiographics : a review publication of the Radiological Society of North America, Inc. 43, e220133 (2023).
  22. Gassenmaier S, Kustner T, Nickel D, Herrmann J, Hoffmann R, Almansour H, et al., Deep Learning Applications in Magnetic Resonance Imaging: Has the Future Become Present?, Diagnostics (Basel). 11, 2181 (2021).
  23. Lin DJ, Johnson PM, Knoll F, Lui YW, Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians, J Magn Reson Imaging. 53, 1015-1028 (2021).
  24. Bischoff LM, Peeters JM, Weinhold L, Krausewitz P, Ellinger J, Katemann C, et al., Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI, Radiology. 308, e230427 (2023).
  25. Gassenmaier S, Afat S, Nickel D, Mostapha M, Herrmann J, Othman AE, Deep learning-accelerated T2-weighted imaging of the prostate: Reduction of acquisition time and improvement of image quality, Eur J Radiol. 137, 109600 (2021).
  26. Gassenmaier S, Afat S, Nickel MD, Mostapha M, Herrmann J, Almansour H, et al., Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging, Cancers. 13, (2021).
  27. Harder FN, Weiss K, Amiel T, Peeters JM, Tauber R, Ziegelmayer S, et al., Prospectively Accelerated T2-Weighted Imaging of the Prostate by Combining Compressed SENSE and Deep Learning in Patients with Histologically Proven Prostate Cancer, Cancers. 14, (2022).
  28. Johnson PM, Tong A, Donthireddy A, Melamud K, Petrocelli R, Smereka P, et al., Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate, J Magn Reson Imaging. 56, 184-195 (2022).
  29. Jung W, Kim EH, Ko J, Jeong G, Choi MH, Convolutional neural network-based reconstruction for acceleration of prostate T(2) weighted MR imaging: a retro- and prospective study, Br J Radiol. 95, 20211378 (2022).
  30. Tong A, Bagga B, Petrocelli R, Smereka P, Vij A, Qian K, et al., Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate, J Magn Reson Imaging. 58, 1055-1064 (2023).
  31. Park JC, Park KJ, Park MY, Kim MH, Kim JK, Fast T2-Weighted Imaging With Deep Learning-Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy, J Magn Reson Imaging. 55, 1735-1744 (2022).
  32. Gassenmaier S, Warm V, Nickel D, Weiland E, Herrmann J, Almansour H, et al., Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction, Cancers. 15, 578 (2023).
  33. Kim EH, Choi MH, Lee YJ, Han D, Mostapha M, Nickel D, Deep learning-accelerated T2-weighted imaging of the prostate: Impact of further acceleration with lower spatial resolution on image quality, Eur J Radiol. 145, 110012 (2021).
  34. Park KJ, Choi SH, Kim MH, Kim JK, Jeong IG, Performance of Prostate Imaging Reporting and Data System Version 2.1 for Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis, J Magn Reson Imaging. 54, 103-112 (2021).
  35. Mehralivand S, Shih JH, Harmon S, Smith C, Bloom J, Czarniecki M, et al., A Grading System for the Assessment of Risk of Extraprostatic Extension of Prostate Cancer at Multiparametric MRI, Radiology. 290, 709-719 (2019).
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