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Research progress of synthetic magnetic resonance imaging in prostate cancer
BEI Mingjie  ZHU Xin 

Cite this article as: BEI M J, ZHU X. Research progress of synthetic magnetic resonance imaging in prostate cancer[J]. Chin J Magn Reson Imaging, 2025, 16(2): 210-214. DOI:10.12015/issn.1674-8034.2025.02.034.


[Abstract] Synthetic MRI (SyMRI) is a new type of rapid quantitative MRI technique, which can obtain multiple quantitative maps and contrast-weighted images in a short scanning time, and can non-invasively obtain objective quantitative parameters of tissues and provide more information about tissue composition from a microscopic perspective. The longitudinal relaxation time T1, transverse relaxation time T2 and proton density (PD) obtained by Synthetic MRI (SyMRI) play an important role in the differential diagnosis, prediction of aggressiveness and prognosis of prostate cancer. This paper describes the basic principles of SyMRI technology and reviews the existing literature on the application of integrated MRI technology in prostate cancer, aiming to improve the early diagnosis of prostate cancer and provide more additional information for prostate cancer treatment. In addition, this paper discusses the future development direction of this technology based on the current application of prostate cancer, hoping to provide a reference for subsequent research.
[Keywords] prostate cancer;bone metastasis;synthetic magnetic resonance imaging;differential diagnosis;aggressiveness;Gleason grading;prognosis

BEI Mingjie   ZHU Xin*  

Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China

Corresponding author: ZHU X, E-mail: 66zhuxin@163.com

Conflicts of interest   None.

Received  2024-08-29
Accepted  2025-01-10
DOI: 10.12015/issn.1674-8034.2025.02.034
Cite this article as: BEI M J, ZHU X. Research progress of synthetic magnetic resonance imaging in prostate cancer[J]. Chin J Magn Reson Imaging, 2025, 16(2): 210-214. DOI:10.12015/issn.1674-8034.2025.02.034.

[1]
NIKITA SANDEEP WAGLE MBBS M, et al. Cancer statistics, 2023[J]. CA A Cancer J Clin, 2023, 73(1): 17-48. DOI: 10.3322/caac.21763.
[2]
BRAY F, LAVERSANNE M, SUNG H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263. DOI: 10.3322/caac.21834.
[3]
AHMED H U, BOSAILY A E, BROWN L C, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study[J]. Lancet, 2017, 389(10071): 815-822. DOI: 10.1016/S0140-6736(16)32401-1.
[4]
PARKIN C J, GILBOURD D, GRILLS R, et al. Transrectal ultrasound-guided prostate needle biopsy remains a safe method in confirming a prostate cancer diagnosis: a multicentre Australian analysis of infection rates[J]. World J Urol, 2022, 40(2): 453-458. DOI: 10.1007/s00345-021-03862-8.
[5]
MASONE M C. Feasibility and potential of an MRI-based prostate cancer screening[J/OL]. Nat Rev Urol, 2023, 20: 578 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/37696943/. DOI: 10.1038/s41585-023-00821-3.
[6]
FAZEKAS T, SHIM S R, BASILE G, et al. Magnetic resonance imaging in prostate cancer screening: a systematic review and meta-analysis[J]. JAMA Oncol, 2024, 10(6): 745-754. DOI: 10.1001/jamaoncol.2024.0734.
[7]
PADHANI A R, GODTMAN R A, SCHOOTS I G. Key learning on the promise and limitations of MRI in prostate cancer screening[J]. Eur Radiol, 2024, 34(9): 6168-6174. DOI: 10.1007/s00330-024-10626-6.
[8]
WEINREB J C, BARENTSZ J O, CHOYKE P L, et al. PI-RADS prostate imaging-reporting and data system: 2015, version 2[J]. Eur Urol, 2016, 69(1): 16-40. DOI: 10.1016/j.eururo.2015.08.052.
[9]
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.
[10]
WANG Y H, LIANG C, ZHU F P, et al. Improving the understanding of PI-RADS in practice: characters of PI-RADS 4 and 5 lesions with negative biopsy[J]. Asian J Androl, 2023, 25(2): 217-222. DOI: 10.4103/aja2022112.
[11]
WILLIAMS C, AHDOOT M, DANESHVAR M A, et al. Why does magnetic resonance imaging-targeted biopsy miss clinically significant cancer?[J]. J Urol, 2022, 207(1): 95-107. DOI: 10.1097/JU.0000000000002182.
[12]
CALLAGHAN M F, MOHAMMADI S, WEISKOPF N. Synthetic quantitative MRI through relaxometry modelling[J]. NMR Biomed, 2016, 29(12): 1729-1738. DOI: 10.1002/nbm.3658.
[13]
COBAN G, GUMELER E, PARLAK S, et al. Synthetic MRI in children with tuberous sclerosis complex[J/OL]. Insights Imag, 2022, 13(1): 115 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/27753154/. DOI: 10.1186/s13244-022-01219-2.
[14]
XU S F, MA Z H, ZHANG J L, et al. Quantitative assessment of preoperative brain development in pediatric congenital heart disease patients by synthetic MRI[J/OL]. Insights Imaging, 2024, 15(1): 166 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/38954290/. DOI: 10.1186/s13244-024-01746-0.
[15]
HWANG K P, ELSHAFEEY N A, KOTROTSOU A, et al. A radiomics model based on synthetic MRI acquisition for predicting neoadjuvant systemic treatment response in triple-negative breast cancer[J/OL]. Radiol Imaging Cancer, 2023, 5(4): e230009 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/37505106/. DOI: 10.1148/rycan.230009.
[16]
CUI Y D, HAN S Y, LIU M, et al. Diagnosis and grading of prostate cancer by relaxation maps from synthetic MRI[J]. J Magn Reson Imaging, 2020, 52(2): 552-564. DOI: 10.1002/jmri.27075.
[17]
JI S, YANG D J, LEE J, et al. Synthetic MRI: technologies and applications in neuroradiology[J]. J Magn Reson Imaging, 2022, 55(4): 1013-1025. DOI: 10.1002/jmri.27440.
[18]
CUI F, WANG C, WANG Y, et al. Basic principle and clinical research progress of MAGiC technology[J]. J Clin Radiol, 2021, 40(12): 2434-2437. DOI: 10.13437/j.cnki.jcr.2021.12.039.
[19]
MAURER G D, TICHY J, HARTER P N, et al. Matching quantitative MRI parameters with histological features of treatment-Naïve IDH wild-type glioma[J/OL]. Cancers, 2021, 13(16): 4060 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/34439213/. DOI: 10.3390/cancers13164060.
[20]
ZHANG H, ZHAO J, DAI J K, et al. Synthetic MRI quantitative parameters in discriminating stage T1 nasopharyngeal carcinoma and benign hyperplasia: Combination with morphological features[J/OL]. Eur J Radiol, 2024, 170: 111264 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/38103492/. DOI: 10.1016/j.ejrad.2023.111264.
[21]
LIU Y W, NIU H J, YIN H X, et al. A comparative study on phantom verification of T1 and T2 relaxation values determined by synthetic MRI and conventional mapping methods[J]. Chin J Magn Reson Imag, 2022, 13(4): 89-93. DOI: 10.12015/issn.1674-8034.2022.04.016.
[22]
XU L Z, XU L, HE M Y, et al. Reproducibility of quantitative relaxation study of synthetic MRI[J]. Radiol Pract, 2019, 34(11): 1178-1181. DOI: 10.13609/j.cnki.1000-0313.2019.11.001.
[23]
HAGIWARA A, HORI M, COHEN-ADAD J, et al. Linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative multidynamic multiecho sequence for rapid simultaneous relaxometry at 3 T: a validation study with a standardized phantom and healthy controls[J]. Invest Radiol, 2019, 54(1): 39-47. DOI: 10.1097/RLI.0000000000000510.
[24]
MAI J, ABUBRIG M, LEHMANN T, et al. T2 mapping in prostate cancer[J]. Invest Radiol, 2019, 54(3): 146-152. DOI: 10.1097/rli.0000000000000520.
[25]
CHATTERJEE A, DEVARAJ A, MATHEW M, et al. Performance of T2 maps in the detection of prostate cancer[J]. Acad Radiol, 2019, 26(1): 15-21. DOI: 10.1016/j.acra.2018.04.005.
[26]
MENG T B, LIU H M, ZHANG W J, et al. Quantification of relaxation time by synthetic MRI in diagnosis of prostate cancer[J]. J Clin Radiol, 2020, 39(3): 605-608. DOI: 10.13437/j.cnki.jcr.2020.03.040.
[27]
CAO H Y, XU W J, XU Y, et al. Value of synthetic MRI quantitative parameters in preprocedural evaluation for TRUS/MRI fusion-guided biopsy of the prostate[J]. Prostate, 2023, 83(11): 1089-1098. DOI: 10.1002/pros.24550.
[28]
SONG N, WANG T, ZHANG D, et al. The value of relaxation time quantitative technique from synthetic magnetic resonance imaging in the diagnosis and invasion assessment of prostate cancer[J]. Natl Med J China, 2022, 102(15): 1093-1099. DOI: 10.3760/cma.j.cn112137-20211018-02304.
[29]
DEVLIN C M, SIMMS M S, MAITLAND N J. Benign prostatic hyperplasia-what do we know?[J]. BJU Int, 2021, 127(4): 389-399. DOI: 10.1111/bju.15229.
[30]
CAO Y, ZHANG H, TU G L, et al. The symptoms of benign prostatic hyperplasia patients with stromal-dominated hyperplasia nodules may be associated with prostate fibrosis[J]. Int J Gen Med, 2023, 16: 1181-1191. DOI: 10.2147/IJGM.S395705.
[31]
DAI J C, MORGAN T N, GOUELI R, et al. MRI features associated with histology of benign prostatic hyperplasia nodules: generation of a predictive model[J]. J Endourol, 2022, 36(3): 381-386. DOI: 10.1089/end.2021.0397.
[32]
PARK S Y, JUNG D C, OH Y T, et al. Prostate cancer: PI-RADS version 2 helps preoperatively predict clinically significant cancers[J]. Radiology, 2016, 280(1): 108-116. DOI: 10.1148/radiol.16151133.
[33]
ASBACH P, PADHANI A R. Are upgraded DCE-positive PI-RADS 3 lesions truly suspicious for clinically significant prostate cancer?[J]. Eur Radiol, 2023, 33(8): 5825-5827. DOI: 10.1007/s00330-023-09711-z.
[34]
XU W J, DU F, XUE S, et al. Clinical value of MAGnetic resonance image compilation (MAGiC) for differentiating benign and malignant lesions of PI-RADS 3 in transitional zone of prostate[J]. Radiol Pract, 2024, 39(6): 772-778. DOI: 10.13609/j.cnki.1000-0313.2024.06.010.
[35]
LI X W, CHEN L H, WANG N, et al. Evaluation of the value of DWI combined with T2 mapping sequences to identify prostate cancer and benign prostatic hyperplasia[J]. Chin J Magn Reson Imag, 2024, 15(2): 97-102. DOI: 10.12015/issn.1674-8034.2024.02.014.
[36]
CHEN X, WU Y F, YANG J H, et al. A comparative study of quantification of relaxation time by synthetic MRI in transitional zone prostate cancer and hyperplasia[J]. Inn Mong Med J, 2023, 55(11): 1289-1293, 1297. DOI: 10.16096/J.cnki.nmgyxzz.2023.55.11.003.
[37]
CUI Y D, LI C M, HAN S Y, et al. The diagnostic value of synthetic MRI quantitative parameters for prostate cancer[J]. Chin J Radiol, 2021, 55(9): 975-980. DOI: 10.3760/cma.j.cn112149-20200721-00935.
[38]
KISHAN A U, ROMERO T, ALSHALALFA M, et al. Transcriptomic heterogeneity of gleason grade group 5 prostate cancer[J]. Eur Urol, 2020, 78(3): 327-332. DOI: 10.1016/j.eururo.2020.05.009.
[39]
SWANSON G P, TREVATHAN S, HAMMONDS K A P, et al. Gleason score evolution and the effect on prostate cancer outcomes[J]. Am J Clin Pathol, 2021, 155(5): 711-717. DOI: 10.1093/ajcp/aqaa130.
[40]
SURINTRSPANONT J, ZHOU M. Prostate pathology: what is new in the 2022 WHO classification of urinary and male genital tumors?[J]. Pathologica, 2022, 115(1): 41-56. DOI: 10.32074/1591-951X-822.
[41]
BENGTSSON J, THIMANSSON E, BAUBETA E, et al. Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners[J/OL]. Front Oncol, 2023, 13: 1079040 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/36890837/. DOI: 10.3389/fonc.2023.1079040.
[42]
SUROV A, MEYER H J, WIENKE A. Correlations between apparent diffusion coefficient and gleason score in prostate cancer: A systematic review[J]. Eur Urol Oncol, 2020, 3(4): 489-497. DOI: 10.1016/j.euo.2018.12.006.
[43]
GÜNDOĞDU E, EMEKLI E, KEBAPÇı M. Evaluation of relationships between the final Gleason score, PI-RADS v2 score, ADC value, PSA level, and tumor diameter in patients that underwent radical prostatectomy due to prostate cancer[J]. Radiol Med, 2020, 125(9): 827-837. DOI: 10.1007/s11547-020-01183-1.
[44]
JAMBOR I, PESOLA M, MERISAARI H, et al. Relaxation along fictitious field, diffusion-weighted imaging, and T2 mapping of prostate cancer: Prediction of cancer aggressiveness[J]. Magn Reson Med, 2016, 75(5): 2130-2140. DOI: 10.1002/mrm.25808.
[45]
LUCARELLI N M, VILLANOVA I, MAGGIALETTI N, et al. Quantitative ADC: an additional tool in the evaluation of prostate cancer?[J/OL]. J Pers Med, 2023, 13(9): 1378 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/37763146/. DOI: 10.3390/jpm13091378.
[46]
BERLIN A, BRIERLEY J, CORNFORD P, et al. TNM staging of prostate cancer: challenges in securing a globally applicable classification[J/OL]. Eur Urol, 2022, 82(2): e52-e53 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/35562268/. DOI: 10.1016/j.eururo.2022.04.019.
[47]
LV Z W, WANG X, ZHU C M, et al. The global status of research in prostate cancer bone metastasis: a bibliometric and visualized analysis[J/OL]. Front Med, 2022, 9: 931422 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/35991630/. DOI: 10.3389/fmed.2022.931422.
[48]
FOSTER B M, SHI L H, HARRIS K S, et al. Bone marrow-derived stem cell factor regulates prostate cancer-induced shifts in pre-metastatic niche composition[J]. Front Oncol, 2022, 12: 855188. DOI: 10.3389/fonc.2022.855188.
[49]
ZARRER J, TAIPALEENMÄKI H. The osteoblast in regulation of tumor cell dormancy and bone metastasis[J/OL]. J Bone Oncol, 2024, 45: 100597 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/38550395/. DOI: 10.1016/j.jbo.2024.100597.
[50]
ALI A, HOYLE A, HARAN Á M, et al. Association of bone metastatic burden with survival benefit from prostate radiotherapy in patients with newly diagnosed metastatic prostate cancer: a secondary analysis of a randomized clinical trial[J]. JAMA Oncol, 2021, 7(4): 555-563. DOI: 10.1001/jamaoncol.2020.7857.
[51]
KANG J N, LA MANNA F, BONOLLO F, et al. Tumor microenvironment mechanisms and bone metastatic disease progression of prostate cancer[J]. Cancer Lett, 2022, 530: 156-169. DOI: 10.1016/j.canlet.2022.01.015.
[52]
ARITA Y, TAKAHARA T, YOSHIDA S, et al. Quantitative assessment of bone metastasis in prostate cancer using synthetic magnetic resonance imaging[J]. Invest Radiol, 2019, 54(10): 638-644. DOI: 10.1097/RLI.0000000000000579.
[53]
LIU Z N, HONG P, HE J D, et al. Favorable prostate-specific antigen levels correlate with a worse prognosis in high-grade prostate cancer: a population-based analysis[J/OL]. Int J Surg, 2024 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/38935086/. DOI: 10.1097/JS9.0000000000001884.
[54]
ADAMAKI M, ZOUMPOURLIS V. Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics[J/OL]. Pharmacol Ther, 2021, 228: 107932 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/34174272/. DOI: 10.1016/j.pharmthera.2021.107932.
[55]
HANZLIKOVA P, VILIMEK D, KAHANKOVA R V, et al. Longitudinal analysis of T2 relaxation time variations following radiotherapy for prostate cancer[J/OL]. Heliyon, 2024, 10(2): e24557 [2024-12-08]. https://pubmed.ncbi.nlm.nih.gov/38298676/. DOI: 10.1016/j.heliyon.2024.e24557.

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