Research progress of magnetic resonance imaging in predicting biochemical recurrence of prostate cancer after radical prostatectomy

Share this content in WeChat

• Review •

FENG Zhaoyan ZHANG Peipei MIN Xiangde

Cite this article as: FENG Z Y, ZHANG P P, MIN X D. Research progress of magnetic resonance imaging in predicting biochemical recurrence of prostate cancer after radical prostatectomy[J]. Chin J Magn Reson Imaging, 2023, 14(5): 186-190, 202. DOI:10.12015/issn.1674-8034.2023.05.033.

Abstract

[Abstract] Prostate cancer (PCa) is one of the most common malignant tumors in elderly men. Radical prostatectomy (RP) is the main treatment option of localized PCa. Some clinical and pathologic variables are used to predict probability of biochemical recurrence-free progression after RP. MRI, with its superior soft tissue resolution and spatial resolution, and multi-sequence, multi-parameter and analytical techniques (such as artificial intelligence), has been extensively studied in evaluating biochemical recurrence after RP. In this paper, we review the application of MRI in the predicting biochemical recurrence after RP, to analyze the advantages and shortcomings of MRI at this stage and the future development direction, hoping to provide references to clinicians and improve the prognosis of PCa patients.

[Keywords] prostate cancer；radical prostatectomy；biochemical recurrence；magnetic resonance imaging；multi-parameter；prognosis

Contributor Information

FENG Zhaoyan ZHANG Peipei MIN Xiangde^*

Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

Corresponding author: Min XD, E-mail: minxiangde0129@126.com

Conflicts of interest None.

Publication Information

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81801668, 82102028).

Received 2022-08-23

Accepted 2023-03-13

DOI: 10.12015/issn.1674-8034.2023.05.033

Text

References

[1]

SIEGEL R L, MILLER K D, JEMAL A. Cancer statistics, 2015[J]. CA A Cancer J Clin, 2015, 65(1): 5-29. DOI: 10.3322/caac.21254">10.3322/caac.21254">10.3322/caac.21254.

[2]

XIA C F, DONG X S, LI H, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants[J]. Chin Med J (Engl), 2022, 135(5): 584-590. DOI: 10.1097/CM9.0000000000002108">10.1097/CM9.0000000000002108">10.1097/CM9.0000000000002108.

[3]

CHEN W Q, ZHENG R S, BAADE P D, et al. Cancer statistics in China, 2015[J]. CA A Cancer J Clin, 2016, 66(2): 115-132. DOI: 10.3322/caac.21338">10.3322/caac.21338">10.3322/caac.21338.

[4]

SCHAEFFER E, SRINIVAS S, ANTONARAKIS E S, et al. NCCN guidelines insights: prostate cancer, version 1.2021[J]. J Natl Compr Canc Netw, 2021, 19(2): 134-143. DOI: 10.6004/jnccn.2021.0008">10.6004/jnccn.2021.0008">10.6004/jnccn.2021.0008.

[5]

TOURINHO-BARBOSA R, SROUGI V, NUNES-SILVA I, et al. Biochemical recurrence after radical prostatectomy: what does it mean?[J]. Int Braz J Urol, 2018, 44(1): 14-21. DOI: 10.1590/S1677-5538.IBJU.2016.0656">10.1590/S1677-5538.IBJU.2016.0656">10.1590/S1677-5538.IBJU.2016.0656.

[6]

AXÉN E, STRANNE J, MÅNSSON M, et al. Biochemical recurrence after radical prostatectomy - a large, comprehensive, population-based study with long follow-up[J]. Scand J Urol, 2022, 56(4): 287-292. DOI: 10.1080/21681805.2022.2108140">10.1080/21681805.2022.2108140">10.1080/21681805.2022.2108140.

[7]

GARCÍA-BARRERAS S, SANCHEZ-SALAS R, MEJIA-MONASTERIO C, et al. Biochemical recurrence-free conditional probability after radical prostatectomy: a dynamic prognosis[J]. Int J Urol, 2019, 26(7): 725-730. DOI: 10.1111/iju.13982">10.1111/iju.13982">10.1111/iju.13982.

[8]

MURRAY N P, AEDO S, REYES E, et al. Prediction model for early biochemical recurrence after radical prostatectomy based on the Cancer of the Prostate Risk Assessment score and the presence of secondary circulating prostate cells[J]. BJU Int, 2016, 118(4): 556-562. DOI: 10.1111/bju.13367">10.1111/bju.13367">10.1111/bju.13367.

[9]

D'AMICO A V, WHITTINGTON R, MALKOWICZ S B, et al. Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer[J]. JAMA, 1998, 280(11): 969-974. DOI: 10.1001/jama.280.11.969">10.1001/jama.280.11.969">10.1001/jama.280.11.969.

[10]

ZHANG Y D, WU C J, BAO M L, et al. MR-based prognostic nomogram for prostate cancer after radical prostatectomy[J]. J Magn Reson Imaging, 2017, 45(2): 586-596. DOI: 10.1002/jmri.25441">10.1002/jmri.25441">10.1002/jmri.25441.

[11]

YAN Y, SHAO L Z, LIU Z Y, et al. Deep learning with quantitative features of magnetic resonance images to predict biochemical recurrence of radical prostatectomy: a multi-center study[J/OL]. Cancers (Basel), 2021, 13(12): 3098 [2022-08-20]. https://www.mdpi.com/2072-6694/13/12/3098. DOI: 10.3390/cancers13123098">10.3390/cancers13123098">10.3390/cancers13123098.

[12]

MUELLER-LISSE U G, MUELLER-LISSE U L, ZAMECNIK P, et al. Diffusion-weighted MRI of the prostate[J]. Radiologe, 2011, 51(3): 205-214. DOI: 10.1007/s00117-010-2061-2">10.1007/s00117-010-2061-2">10.1007/s00117-010-2061-2.

[13]

CORNELIS F, DE CLERMONT H, BERNHARD J C, et al. Quantitative imaging in uro-oncology[J]. Prog Urol, 2014, 24(7): 399-413. DOI: 10.1016/j.purol.2014.02.008">10.1016/j.purol.2014.02.008">10.1016/j.purol.2014.02.008.

[14]

JIA Y S, QUAN S, REN J L, et al. MRI radiomics predicts progression-free survival in prostate cancer[J/OL]. Front Oncol, 2022, 12: 974257 [2023-01-12]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468743/. DOI: 10.3389/fonc.2022.974257">10.3389/fonc.2022.974257">10.3389/fonc.2022.974257.

[15]

SALAZAR-RUIZ S Y, CHILACA-ROSAS M F, SANCHEZ-RODRIGUEZ I G, et al. Current MRI methods for the assessment of pathologic prostate: a brief review for clinicians[J]. Curr Med Imaging, 2022, 18(8): 808-816. DOI: 10.2174/1573405618666211217101542">10.2174/1573405618666211217101542">10.2174/1573405618666211217101542.

[16]

IRRERA P, CONSOLINO L, ROBERTO M, et al. In vivo MRI-CEST tumor pH imaging detects resistance to proton pump inhibitors in human prostate cancer murine models[J/OL]. Cancers, 2022, 14(19): 4916 [2023-01-12]. https://www.mdpi.com/2072-6694/14/19/4916. DOI: 10.3390/cancers14194916">10.3390/cancers14194916">10.3390/cancers14194916.

[17]

GANDAGLIA G, PLOUSSARD G, VALERIO M, et al. Prognostic implications of multiparametric magnetic resonance imaging and concomitant systematic biopsy in predicting biochemical recurrence after radical prostatectomy in prostate cancer patients diagnosed with magnetic resonance imaging-targeted biopsy[J]. Eur Urol Oncol, 2020, 3(6): 739-747. DOI: 10.1016/j.euo.2020.07.008">10.1016/j.euo.2020.07.008">10.1016/j.euo.2020.07.008.

[18]

HO R, SIDDIQUI M M, GEORGE A K, et al. Preoperative multiparametric magnetic resonance imaging predicts biochemical recurrence in prostate cancer after radical prostatectomy[J/OL]. PLoS One, 2016, 11(6): e0157313 [2023-01-12]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0157313. DOI: 10.1371/journal.pone.0157313">10.1371/journal.pone.0157313">10.1371/journal.pone.0157313.

[19]

HATTORI S, KOSAKA T, MIZUNO R, et al. Prognostic value of preoperative multiparametric magnetic resonance imaging (MRI) for predicting biochemical recurrence after radical prostatectomy[J]. BJU Int, 2014, 113(5): 741-747. DOI: 10.1111/bju.12329">10.1111/bju.12329">10.1111/bju.12329.

[20]

SANDEMAN K, EINELUOTO J T, POHJONEN J, et al. Prostate MRI added to CAPRA, MSKCC and Partin cancer nomograms significantly enhances the prediction of adverse findings and biochemical recurrence after radical prostatectomy[J/OL]. PLoS One, 2020, 15(7): e0235779 [2023-01-16]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347171/. DOI: 10.1371/journal.pone.0235779">10.1371/journal.pone.0235779">10.1371/journal.pone.0235779.

[21]

ASUNCION A, WALKER P M, BERTAUT A, et al. Prediction of prostate cancer recurrence after radiation therapy using multiparametric magnetic resonance imaging and spectroscopy: assessment of prognostic factors on pretreatment imaging[J]. Quant Imaging Med Surg, 2022, 12(12): 5309-5325. DOI: 10.21037/qims-22-184">10.21037/qims-22-184">10.21037/qims-22-184.

[22]

GAO W Z, HE Y H, XIA M C, et al. Establishment of a biochemical recurrence prediction model of prostate cancer based on deep learning algorithm[J]. J Mod Urol, 2022, 27(3): 230-233. DOI: 10.3969/j.issn.1009-8291.2022.03.0011">10.3969/j.issn.1009-8291.2022.03.0011">10.3969/j.issn.1009-8291.2022.03.0011.

[23]

PARK J, RHO M J, MOON H W, et al. Dr. answer AI for prostate cancer: predicting biochemical recurrence following radical prostatectomy[J/OL]. Technol Cancer Res Treat, 2021, 20: 15330338211024660 [2022-08-20]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243093/. DOI: 10.1177/15330338211024660">10.1177/15330338211024660">10.1177/15330338211024660.

[24]

COOKSON M S, AUS G, BURNETT A L, et al. Variation in the definition of biochemical recurrence in patients treated for localized prostate cancer: the American Urological Association Prostate Guidelines for Localized Prostate Cancer Update Panel report and recommendations for a standard in the reporting of surgical outcomes[J]. J Urol, 2007, 177(2): 540-545. DOI: 10.1016/j.juro.2006.10.097">10.1016/j.juro.2006.10.097">10.1016/j.juro.2006.10.097.

[25]

ZHANG M, QI J C. Interpretation of the update points of China urology prostate cancer diagnosis and treatment guidelines in 2019 edition[J]. J Hebei Med Univ, 2021, 42(10): 1117-1122, 1154. DOI: 10.3969/j.issn.1007-3205.2021.10.001">10.3969/j.issn.1007-3205.2021.10.001">10.3969/j.issn.1007-3205.2021.10.001.

[26]

ARTIBANI W, PORCARO A B, DE MARCO V, et al. Management of biochemical recurrence after primary curative treatment for prostate cancer: a review[J]. Urol Int, 2018, 100(3): 251-262. DOI: 10.1159/000481438">10.1159/000481438">10.1159/000481438.

[27]

VAN DEN BROECK T, VAN DEN BERGH R C N, ARFI N, et al. Prognostic value of biochemical recurrence following treatment with curative intent for prostate cancer: a systematic review[J]. Eur Urol, 2019, 75(6): 967-987. DOI: 10.1016/j.eururo.2018.10.011">10.1016/j.eururo.2018.10.011">10.1016/j.eururo.2018.10.011.

[28]

MORRIS M J, MOTA J M, LACUNA K, et al. Phase 3 randomized controlled trial of androgen deprivation therapy with or without docetaxel in high-risk biochemically recurrent prostate cancer after surgery (TAX3503)[J]. Eur Urol Oncol, 2021, 4(4): 543-552. DOI: 10.1016/j.euo.2021.04.008">10.1016/j.euo.2021.04.008">10.1016/j.euo.2021.04.008.

[29]

WANG L, CHEN M, SHEN J K, et al. Interpretation of prostate imaging recurrence reporting guideline for prostate cancer local recurrence[J]. Chin J Radiol, 2022, 56(1): 12-15. DOI: 10.3760/cma.j.cn112149-20210715-00676">10.3760/cma.j.cn112149-20210715-00676">10.3760/cma.j.cn112149-20210715-00676.

[30]

ZHANG-YIN J, MONTRAVERS F, MONTAGNE S, et al. Diagnosis of early biochemical recurrence after radical prostatectomy or radiation therapy in patients with prostate cancer: state of the art[J]. Diagn Interv Imaging, 2022, 103(4): 191-199. DOI: 10.1016/j.diii.2022.02.005">10.1016/j.diii.2022.02.005">10.1016/j.diii.2022.02.005.

[31]

PANEBIANCO V, VILLEIRS G, WEINREB J C, et al. Prostate magnetic resonance imaging for local recurrence reporting (PI-RR): international consensus-based guidelines on multiparametric magnetic resonance imaging for prostate cancer recurrence after radiation therapy and radical prostatectomy[J]. Eur Urol Oncol, 2021, 4(6): 868-876. DOI: 10.1016/j.euo.2021.01.003">10.1016/j.euo.2021.01.003">10.1016/j.euo.2021.01.003.

[32]

LU X, REN S C, SUN Y H. Diagnosis and treatment of biochemical recurrence after radical prostatectomy[J]. Chin J Urol, 2007, 28(12): 861-863. DOI: 10.3760/j.issn:1000-6702.2007.12.018">10.3760/j.issn:1000-6702.2007.12.018">10.3760/j.issn:1000-6702.2007.12.018.

[33]

ONDRACEK R P, KATTAN M W, MUREKEYISONI C, et al. Validation of the kattan nomogram for prostate cancer recurrence after radical prostatectomy[J]. J Natl Compr Canc Netw, 2016, 14(11): 1395-1401. DOI: 10.6004/jnccn.2016.0149">10.6004/jnccn.2016.0149">10.6004/jnccn.2016.0149.

[34]

COOPERBERG M R, PASTA D J, ELKIN E P, et al. The University of California, San Francisco Cancer of the Prostate Risk Assessment score: a straightforward and reliable preoperative predictor of disease recurrence after radical prostatectomy[J]. J Urol, 2005, 173(6): 1938-1942. DOI: 10.1097/01.ju.0000158155.33890.e7">10.1097/01.ju.0000158155.33890.e7">10.1097/01.ju.0000158155.33890.e7.

[35]

WANG H F, GAO X, WANG Y, et al. Validation of Kattan nomogram and Cancer of the Prostate Risk Assessment scores in anticipating the recurrence free survival after radical prostatectomy of Chinese patients[J]. Chin J Urol, 2015, 36(4): 285-289. DOI: 10.3760/cma.j.issn.1000-6702.2015.04.011">10.3760/cma.j.issn.1000-6702.2015.04.011">10.3760/cma.j.issn.1000-6702.2015.04.011.

[36]

MA S J, ZHANG J L, SU X, et al. Risk factor analysis of patients with biochemical recurrence after radical prostatectomy[J]. Chin J Urol, 2022, 43(1): 35-39. DOI: 10.3760/cma.j.cn112330-20210722-00388">10.3760/cma.j.cn112330-20210722-00388">10.3760/cma.j.cn112330-20210722-00388.

[37]

FAN Y, MULATI Y, LIANG L, et al. Analysis of risk factors for clinical cure and biochemical recurrence in patients after radical prostatectomy[J]. Chin J Urol, 2021, 42(9): 644-649. DOI: 10.3760/cma.j.cn112330-20210720-00379">10.3760/cma.j.cn112330-20210720-00379">10.3760/cma.j.cn112330-20210720-00379.

[38]

Turkbey B, Rosenkrantz A B, Haider M A, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2[J]. Eur Urol, 2019, 76(3): 340-351. DOI: 10.1016/j.eururo.2019.02.033.

[39]

TAMADA T, UEDA Y, UENO Y, et al. Diffusion-weighted imaging in prostate cancer[J]. Magn Reson Mater Phy, 2022, 35(4): 533-547. DOI: 10.1007/s10334-021-00957-6.

[40]

UENO Y, TAMADA T, SOFUE K, et al. Diffusion and quantification of diffusion of prostate cancer[J/OL]. Br J Radiol, 2022, 95(1131): 20210653 [2023-01-11]. https://pubmed.ncbi.nlm.nih.gov/34538094/. DOI: 10.1259/bjr.20210653.

[41]

REYNOLDS H M, TADIMALLA S, WANG Y F, et al. Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy[J/OL]. Cancer Imaging, 2022, 22(1): 71 [2022-12-27]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762110/.

[42]

REISÆTER L A R, FÜTTERER J J, LOSNEGÅRD A, et al. Optimising preoperative risk stratification tools for prostate cancer using mpMRI[J]. Eur Radiol, 2018, 28(3): 1016-1026. DOI: 10.1007/s00330-017-5031-5.

[43]

HARMON S A, GESZTES W, YOUNG D, et al. Prognostic features of biochemical recurrence of prostate cancer following radical prostatectomy based on multiparametric MRI and immunohistochemistry analysis of MRI-guided biopsy specimens[J]. Radiology, 2021, 299(3): 613-623. DOI: 10.1148/radiol.2021202425.

[44]

MANCEAU C, BEAUVAL J B, LESOURD M, et al. MRI characteristics accurately predict biochemical recurrence after radical prostatectomy[J/OL]. J Clin Med, 2020, 9(12): 3841 [2022-12-27]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7760513/. DOI: 10.3390/jcm9123841.

[45]

KELLY B S, JUDGE C, BOLLARD S M, et al. Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)[J]. Eur Radiol, 2022, 32(11): 7998-8007. DOI: 10.1007/s00330-022-08784-6.

[46]

KOH D M, PAPANIKOLAOU N, BICK U, et al. Artificial intelligence and machine learning in cancer imaging[J/OL]. Commun Med (Lond), 2022, 2: 133 [2023-01-11]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613681/. DOI: 10.1038/s43856-022-00199-0.

[47]

VENTE C, VOS P, HOSSEINZADEH M, et al. Deep learning regression for prostate cancer detection and grading in Bi-parametric MRI[J]. IEEE Trans Biomed Eng, 2021, 68(2): 374-383. DOI: 10.1109/TBME.2020.2993528.

[48]

MANSUR A, SALEEM Z, ELHAKIM T, et al. Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions[J/OL]. Front Oncol, 2023, 13: 1065402 [2023-01-11]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9905815/. DOI: 10.3389/fonc.2023.1065402.

[49]

ROUVIÈRE O, JAOUEN T, BASEILHAC P, et al. Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: how accurate are they when tested on independent cohorts?-A systematic review[J/OL]. Diagn Interv Imaging, 2022: S2211-S5684(22)00224-8 [2023-01-11]. https://www.sciencedirect.com/science/article/abs/pii/S2211568422002248?via%3Dihub. DOI: 10.1016/j.diii.2022.11.005.

[50]

GNEP K, FARGEAS A, GUTIÉRREZ-CARVAJAL R E, et al. Haralick textural features on T2-weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer[J]. J Magn Reson Imaging, 2017, 45(1): 103-117. DOI: 10.1002/jmri.25335.

[51]

BOURBONNE V, FOURNIER G, VALLIÈRES M, et al. External validation of an MRI-derived radiomics model to predict biochemical recurrence after surgery for high-risk prostate cancer[J/OL]. Cancers (Basel), 2020, 12(4): 814 [2022-08-20]. https://www.mdpi.com/2072-6694/12/4/814. DOI: 10.3390/cancers12040814.

[52]

LOH HW, OOI CP, SEONI S, et al. Application of explainable artificial intelligence for healthcare: a systematic review of the last decade (2011-2022)[J/OL]. Comput Methods Programs Biomed, 2022, 226: 107161 [2023-01-11]. https://www.sciencedirect.com/science/article/abs/pii/S0169260722005429?via%3Dihub. DOI: 10.1016/j.cmpb.2022.107161.

[53]

GHASSEMI M, OAKDEN-RAYNER L, BEAM A L. The false hope of current approaches to explainable artificial intelligence in health care[J/OL]. Lancet Digit Health, 2021, 3(11): e745-e750 [2023-01-11]. https://www.thelancet.com/journals/landig/article/PIIS2589-7500(21)00208-9/fulltext. DOI: 10.1016/S2589-7500(21)00208-9.

[54]

CHADDAD A, PENG J H, XU J, et al. Survey of explainable AI techniques in healthcare[J/OL]. Sensors (Basel), 2023, 23(2): 634 [2023-01-12]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9862413/.

[55]

WANG J, DENG Y, JONDAL D, et al. New and emerging applications of magnetic resonance elastography of other abdominal organs[J]. Top Magn Reson Imaging, 2018, 27(5): 335-352. DOI: 10.1097/RMR.0000000000000182.

[56]

LITWILLER D V, MARIAPPAN Y K, EHMAN R L. Magnetic resonance elastography[J]. Curr Med Imaging Rev, 2012, 8(1): 46-55. DOI: 10.2174/157340512799220562.

[57]

EVANS V S, TORREALDEA F, REGA M, et al. Optimization and repeatability of multipool chemical exchange saturation transfer MRI of the prostate at 3.0 T[J]. J Magn Reson Imaging, 2019, 50(4): 1238-1250. DOI: 10.1002/jmri.26690.

[58]

ZHANG L, WANG J. Research progress in the application of chemical exchange saturation transfer imaging in glioma[J]. Chin J Magn Reson Imaging, 2022, 13(6): 139-142. DOI: 10.12015/issn.1674-8034.2022.06.029.

PREV Research status of hypertrophic cardiomyopathy complicated with atrial fibrillation based on cardiac magnetic resonance imaging technology

NEXT Advances in the assessment of biological behaviors of endometrial carcinoma by IVIM-DWI and texture analysis

LINK

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