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综述
集成磁共振成像技术在前列腺癌中的研究进展
贝明洁 祝新

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.本文引用格式:贝明洁, 祝新. 集成磁共振成像技术在前列腺癌中的研究进展[J]. 磁共振成像, 2025, 16(2): 210-214. DOI:10.12015/issn.1674-8034.2025.02.034.


[摘要] 集成磁共振成像(synthetic magnetic resonance imaging, SyMRI)是一种新型快速定量MRI技术,能通过短时间扫描获得多种定量图谱和对比加权图像,无创性地获得组织客观定量参数,从微观角度提供更多组织成分信息。该技术获得的纵向弛豫时间T1、横向弛豫时间T2和质子密度(proton density, PD)在前列腺癌的鉴别诊断、侵袭性预测和预后评价等方面发挥了重要作用。本文通过阐述SyMRI技术基本原理,就现有文献对SyMRI在前列腺癌中的相关应用进行综述,旨在提高对前列腺癌的早期诊断,并为前列腺癌治疗提供额外信息。此外,本文就该技术在前列腺癌的应用现状,探讨其未来发展方向,以期为后续的研究提供参考。
[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.
[关键词] 前列腺癌;骨转移;集成磁共振成像;鉴别诊断;侵袭性;Gleason分级;预后
[Keywords] prostate cancer;bone metastasis;synthetic magnetic resonance imaging;differential diagnosis;aggressiveness;Gleason grading;prognosis

贝明洁    祝新 *  

南京中医药大学附属江苏省中医院放射科,南京 210029

通信作者:祝新,E-mail: 66zhuxin@163.com

作者贡献声明:祝新设计本研究的方案,对稿件重要内容进行了修改,获得了江苏省中医院院内基金项目的资助;贝明洁起草和撰写稿件,获取、分析并解释本研究的文献;全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。


基金项目: 江苏省中医院院内基金项目 Y2021ZR30
收稿日期:2024-08-29
接受日期:2025-01-10
中图分类号:R445.2  R737.25 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2025.02.034
本文引用格式:贝明洁, 祝新. 集成磁共振成像技术在前列腺癌中的研究进展[J]. 磁共振成像, 2025, 16(2): 210-214. DOI:10.12015/issn.1674-8034.2025.02.034.

0 引言

       前列腺癌(prostate cancer, PCa)是全球男性第二常见恶性肿瘤,是男性癌症死亡的重要原因之一[1]。根据2022年美国的全球癌症统计数据显示PCa占全球男性癌症新发病例的7.3%[2]。经直肠超声引导下穿刺活检是PCa诊断及病理分级的金标准,但临床中穿刺活检检测PCa的敏感度较低[3],并且穿刺活检为有创检查,可能导致感染、尿潴留等不良事件[4]。MRI是诊断PCa的最佳影像学方法,不但能提高临床显著性PCa的检出率,还有助于减少非必要的活检[5, 6, 7]。前列腺影像报告和数据系统(prostate imaging-reporting and data system, PI-RADS)的提出促进了前列腺MRI采集标准化和图像解释规范化[8, 9]。然而,不同观察者经验水平的异质性会导致PI-RADS评分的差异,造成病灶检出存在一定漏诊和误诊[10, 11]。集成磁共振成像(synthetic magnetic resonance imaging, SyMRI)是一种MRI定量成像技术,能无创性获取客观的定量指标[12],从微观角度提供更多病灶信息,以便于实现对疾病的精准化评估[13]。多项研究报道SyMRI在颅脑、乳腺和前列腺疾病中的潜在价值[14, 15, 16]。目前,SyMRI对前列腺的研究集中在PCa的鉴别诊断和侵袭性评估等方面,对PCa预后评估的研究相对较少,限制了该技术在临床上的广泛运用。本文通过阐述SyMRI技术基本原理,就现有文献对SyMRI技术在PCa鉴别诊断、侵袭性预测及预后评估等方面的应用进行综述,探讨其未来发展方向,旨在为SyMRI技术在前列腺的后续研究提供参考。

1 SyMRI技术概述

       SyMRI技术是一种快速同步定量MRI技术[17],一次图像扫描时间仅需4~6 min便可生成T1 mapping、T2 mapping等定量图谱和多种对比度图像,获得组织的横向弛豫时间(T2)、纵向弛豫时间(T1)及质子密度(proton density, PD)等组织固有物理参数[17, 18]。SyMRI为组织的定量研究提供客观稳定的指标,定量参数T1、T2及PD值的改变能反映组织成分及病理学的变化[19],有助于提高病灶的检出率[20],满足放射科医师对病灶进行定量分析和精准诊断的要求。多项研究证实SyMRI中的定量T1值和T2值具有良好的可重复性和稳定性。刘雅文等[21]研究对SyMRI和传统定量MRI进行比较,结果两种方法测量的T1值及T2值差异无统计学意义,SyMRI检查时间更短、操作简单、定量测量准确,更具临床应用价值。徐良洲等[22]研究中使用同种1.5 T MRI扫描仪在不同的时间点测量T1值和T2值,结果显示组内和组间之间一致性良好,进一步验证了SyMRI定量测定的准确性。HAGIWARA等[23]用不同3 T MRI同样证实了SyMRI定量测定T1值和T2值的可行性,不同MRI设备之间变异度<5%。以上均表明SyMRI中T1值和T2值的准确性和可靠性,可用于临床定量研究。

2 SyMRI在前列腺癌中的应用

2.1 SyMRI对前列腺良恶性病变的鉴别诊断

       通过无创性手段对前列腺疾病做出精准诊断,对临床决策至关重要。MRI软组织分辨率高,能准确区分前列腺各解剖结构和病变部位,已成为PCa检测的常规方案。MRI扫描参数对信号强度影响较大,且MRI信号的解读具有个体主观性,无法实现量化比较。SyMRI通过测量组织定量参数值,提供了一种可靠的方法来反映组织结构特征,从而实现信号强度的定量化分析,定量参数有助于将PCa与正常组织和非PCa病变如前列腺炎和良性前列腺增生(benign prostatic hyperplasia, BPH)区分开,从而达到提高PCa的诊断效能的目的。

2.1.1 外周带PCa与正常组织或前列腺炎的鉴别

       多项研究证实了SyMRI中定量参数T1值和T2值对前列腺良恶性病变鉴别的潜在价值,已有研究[16, 24, 25]报道了外周带PCa和非PCa组织的T2值差异存在统计学意义。孟铁豹等[26]研究对20名外周带PCa患者和20名健康受试者的SyMRI定量参数进行分析,结果发现外周带PCa的T1值和T2值均低于正常组织(P<0.001),表明定量T1值和T2值有鉴别外周带PCa和正常组织的潜力。有报道[24, 27]称定量T2值是诊断外周带PCa的独立预测因子。CAO等[27]认为T2值诊断外周带PCa的最佳阈值为81 ms,而MAI等[24]研究表明选择T2值为134 ms作为诊断阈值时,诊断PCa效能最佳,曲线下面积(area under the curve, AUC)为0.871,敏感度为85%,特异度为65%。导致T2诊断阈值存在差异的原因可能包括:样本量大小不同、MRI扫描参数的差异、ROI选择及处理方式不同、PCa组织特性的差异和PCa周围微环境改变等。同时,MAI等[24]研究还发现T2值也是区别外周带PCa和前列腺炎的可靠指标,外周带PCa的T2值显著低于前列腺炎,T2值对两者鉴别效能的AUC为0.846。宋娜等[28]研究结果显示T2值在区分在外周带PCa和非PCa组(包含前列腺炎)时,T2值与表观扩散系数(apparent diffusion coefficient, ADC)的AUC相近(0.963 vs. 0.991,P=0.105)。也有学者提出不同观点,CUI等[16]得出T1值和T2值区分外周带PCa与非PCa组织的有用参数,但两者的诊断效能低于ADC值。总之,在外周带PCa与正常组织以及外周带PCa与和前列腺炎的鉴别方面,T1值和T2值均显示出一定的潜能,T2值的表现比T1值更加稳定,T2值可作为诊断外周带PCa的有效定量指标。

2.1.2 移行带PCa与BPH的鉴别

       移行带PCa的诊断相对于外周带PCa而言更具挑战性。老年男性常发生移行带BPH[29],由于BPH的增生结节含腺体、基质和纤维肌成分的不同[30],在T2WI上表现的T2信号强度不同,例如:T2高信号的腺体增生(glandular hyperplasia, GH)结节、T2低信号的基质增生(stromal hyperplasia, SH)结节或高低混杂信号结节[30, 31]。基质增生结节和移行带PCa均表现为T2低信号,两者诊断存在一定难度。SyMRI中T1值和T2值与组织的纤维化、脂肪、水分等性质的变化相关,能提供额外的组织成分信息,成为近年移行带PCa定量研究的热点方向。PI-RADS评分已被证明与具有临床意义的PCa相关[32],评分越高,PCa的可能性越大,但是对于PI-RADS 3分良恶性不明的病灶,是否需要穿刺是临床医师关注的重点[33]。徐文娟等[34]研究显示T2值能预测移行带PI-RADS 3分病灶的性质,有助于减少非必要的穿刺活检,得出T2值的诊断阈值为77 ms。李茜玮等[35]发现移行区PCa的T2值和ADC值显著低于BPH,T2值和ADC值是区分移行区良恶性病变的独立预测因子,两者联合模型诊断效能优于单一参数,与临床指标结合的综合模型效益最大,为无创诊断移行带PCa提供了可靠的指标。宋娜等[28]研究表明T1值、T2值和ADC值均能准确有效区分移行带PCa和BPH,三者诊断效能相当(AUC值分别为0.930、0.867、0.938)。CAO等[27]认为T2值对移行区PCa诊断效能更高,其次为T1值。陈曦等[36]根据病理组织类型的不同,探索了移行带PCa与GH结节和SH结节之间定量参数的差异性,GH结节的T1、T2和PD值均高于PCa和SH结节(P<0.001),但三者在移行带PCa和SH结节间差异无统计学意义,此结论尚存在一定争议[24, 37]。崔亚东等[37]报道了不同观点,报道中肯定了T1值和T2值对移行带PCa诊断的积极作用,但在不同病理组成的BPH中有所差异,研究以ADC值作对照,T1值和T2值在移行带PCa与SH结节鉴别价值低于AUC值,但是在移行带PCa与GH结节的鉴别中T1值和T2值的效能与ADC值相当。CUI等[16]研究同样证实了此观点。推测出现不同研究结果的原因可能如下:(1)不同学者对病灶的分类不同;(2)SH结节的成分主要为增生的纤维基质及平滑肌,腺体成分较少,而PCa灶中癌细胞浸润破坏正常腺泡结构,液体含量减少,且癌细胞生长迅速,细胞排列密集,自由水含量减少,这些原因均可导致移行带PCa和SH结节的T1值及T2值存在一定重叠;(3)研究样本量过少,也可能引起结果偏差,还需扩大样本量进一步验证。

       综上所述,SyMRI能无创性对前列腺疾病组织成分进行定量测定,在PCa的诊断方面展现出良好的应用价值。T2值对前列腺不同解剖区良恶性病变的鉴别均有一定的潜力,总体效能优于T1值,但定量T2的最佳诊断阈值需仍在多中心大样本的研究中进一步确立并验证。

2.2 SyMRI对PCa侵袭性的预测

2.2.1 预测Gleason分级

       Gleason(GS)评分系统是使用最广泛的PCa病理组织学分级方法,PCa的侵袭性通过GS评分来表征,GS评分越高肿瘤恶性程度越高[38, 39, 40]。有报道[25]称T2值不但具有鉴别PCa的潜力,还能表征PCa侵袭性,与GS评分具有显著相关性。ADC值能反映水分子自由扩散受限程度,是评估PCa侵袭性的生物标志物之一[41]。ADC值与GS评分呈负相关性,已在既往研究中得以证实[42, 43]。关于PCa侵袭性的定量研究多以ADC值作为参照。MAI等[24]研究分析了177个不同GS评分的PCa的定量值差异,结果显示T2值会随GS评分的升高而降低,与ADC值呈显著相关性。T2值能提供PCa侵袭性的有效证据,对外周带PCa的GS分级效能优于移行带PCa(GS=6分 vs. GS≥7分)。然而,之前的一项研究认为GS评分和T2值之间没有相关性[44]。宋娜等[28]对58例PCa患者(9例GS≤6,49例GS≥7)的ADC和SyMRI图像分析,结果显示GS≥7分的PCa的ADC值和T2值均低于GS≤6分的PCa(Z=-4.22、-2.74,P均<0.01),且T2值和ADC值的诊断效能相当,亦证实T2值与GS分级的相关性。CUI等[16]得出相同的结果,研究还表示PD值在区分GS=6分及GS≥7分的PCa时表现出与T2值和ADC值相似的AUC,PD值对PCa的GS分级可能也有一定作用,PCa具有更高的细胞密度和较低的水分含量,这可能导致了PD值的变化。T2值和ADC值作为反映含水量、细胞密度和组织组成的生物标志物,两者存在一定的关联。PCa细胞增殖迅速,细胞密度增加,水分子的弥散受限,导致ADC值降低[45],高GS评分的PCa具有更高侵袭性,癌细胞破坏正常腺体结构,液体含量减少,会导致T2值降低,两者可以相互补充。T2值是评估PCa侵袭性的潜在指标,低T2值可能预示着较高的GS评分,T2值与ADC值联合可能会提高对GS分级的预测效能,还有待后续研究进一步验证。

2.2.2 评估PCa的TNM分期

       TNM分期与PCa患者的侵袭性和预后密切相关,同时也是临床医师制订个体化治疗方案的重要依据[46]。但目前关于SyMRI在评估PCa的TNM分期方面的文章鲜有报道。PCa具有高度的成骨性转移倾向,据统计70%~80%的PCa患者会生骨转移[47, 48],进展为PCa晚期阶段(M1期)[49]。若是能早期检测骨转移灶的存在,将有利于PCa治疗策略的制订,改善患者预后及生存质量[50, 51]。SyMRI中的PD值是组织的固有物理参数之一,反映的是组织中水分子的浓度。既往研究认为PD值在PCa诊断中的价值有待商榷[28, 37]。近期的一项研究发现PD值在PCa骨转移的评估方面显示出良好的应用价值。ARITA等[52]探索定量PD值用于评估PCa骨转移的可行性,发现PCa骨转移灶和非活动性病灶的差异能通过PD值来区分,PD值的诊断效能显著高于T1和T2值,这表明PD值有助于提高早期隐匿性PCa骨转移灶的检出,并具有评估骨转移治疗变化的潜能,未来将有可能使用PD值作为检测PCa是否存在骨转移的生物学指标之一。

       以上研究表明,SyMRI可以作为PCa侵袭性评估的有力工具之一,在GS分级和TNM分期(M1期)中骨转移灶的识别等方面表现出一定的应用价值,对PCa的准确分期有一定的帮助,但是SyMRI对PCa的包膜外侵犯和淋巴结转移(N分期)等方面的研究尚未有文章报道,此技术未来的研究和发展仍有巨大空间。

2.3 SyMRI对PCa的预后评估

       PCa的预后评估是临床医生长久以来关注的重点内容,准确评估PCa的预后状况能帮助临床医生判断当前治疗方案是否有效,直接影响到PCa患者的治疗方案和生存质量[53, 54]。近期一项关于PCa放疗后T2弛豫时间变化的纵向分析,提示T2值可能有益于PCa患者疗效的判断,HANZLIKOVA等[55]对24例低中级别PCa(GS3+3或3+4,分期T1、N0或T2aN0)患者在1.5T MRI行7次T2 mapping检查,分别为放疗前1次,放疗后6次(放疗后1周及5个月内每月各1次)共7次,结果表明T2值能反映PCa中肿瘤瘢痕形成的量化过程,放疗过程中对T2值变化的监测能了解整个前列腺即时和延迟变化。T2值可能是监测低中等风险PCa患者放疗效果的潜在指标,有助于指导患者治疗方案的选择—继续主动监测或是手术治疗。目前,关于SyMRI在PCa预后评估的相关文章鲜有发表,还有待进一步验证。HANZLIKOVA等[55]研究给未来SyMRI(T2 mapping)在PCa患者的临床管理开拓了新的思路。

3 总结与展望

       SyMRI一次扫描可以获得多个定量参数值及不同mapping图像,在不降低图像质量的同时还能克服传统单定量MRI技术扫描时间的限制,其定量参数值有助于较客观且稳定对病变组织特性进行定量分析。目前,SyMRI在PCa鉴别诊断、侵袭性预测和预后评估等方面已有一定研究进展。但还存在一定的问题和挑战:(1)针对PCa的SyMRI研究多为单个中心且样本量有限,缺乏多样化数据支持;(2)SyMRI扫描参数和后处理的标准需进一步规范化,提高图像对比的一致性;(3)SyMRI在PCa中的应用尚存在一定空白,对TNM分期的评估目前仅局限于PCa骨转移(M1期)的监测,暂未涉及包膜外侵犯和淋巴结转移(N分期)等方面。此外,SyMRI在PCa预后评估的研究仍处于初步探索阶段,有待深入研究。随着SyMRI技术的不断发展和完善,未来有可能作为常规前列腺MRI检查的重要补充,提供更多定量评估的信息,为实现精准医疗添砖加瓦。

[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]
崔峰, 王聪, 王娅, 等. MAGiC技术的基本原理及临床研究进展[J]. 临床放射学杂志, 2021, 40(12): 2434-2437. DOI: 10.13437/j.cnki.jcr.2021.12.039.
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]
刘雅文, 牛海军, 尹红霞, 等. 合成MRI与传统定量方法对T1、T2弛豫值测定的模体验证对比研究[J]. 磁共振成像, 2022, 13(4): 89-93. DOI: 10.12015/issn.1674-8034.2022.04.016.
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]
徐良洲, 徐霖, 贺梦吟, 等. 集成MR序列T1、T2弛豫定量的可重复性研究[J]. 放射学实践, 2019, 34(11): 1178-1181. DOI: 10.13609/j.cnki.1000-0313.2019.11.001.
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]
孟铁豹, 刘辉明, 张蔚菁, 等. 集成磁共振成像弛豫时间定量在前列腺癌诊断中的应用[J]. 临床放射学杂志, 2020, 39(3): 605-608. DOI: 10.13437/j.cnki.jcr.2020.03.040.
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]
宋娜, 王涛, 张丹, 等. 集成MRI弛豫时间定量技术在前列腺癌诊断及侵袭性评估中的价值[J]. 中华医学杂志, 2022, 102(15): 1093-1099. DOI: 10.3760/cma.j.cn112137-20211018-02304.
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]
徐文娟, 杜芳, 薛松, 等. 一站式驰豫定量(MAGiC)技术预测前列腺移行带PI-RADS 3分病灶良恶性能力的临床价值[J]. 放射学实践, 2024, 39(6): 772-778. DOI: 10.13609/j.cnki.1000-0313.2024.06.010.
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]
李茜玮, 陈丽华, 王楠, 等. DWI联合T2 mapping序列鉴别前列腺癌与前列腺增生价值评估[J]. 磁共振成像, 2024, 15(2): 97-102. DOI: 10.12015/issn.1674-8034.2024.02.014.
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]
陈曦, 武轶非, 杨金花, 等. 集成磁共振成像弛豫时间定量对移行带前列腺癌和前列腺增生的对比研究[J]. 内蒙古医学杂志, 2023, 55(11): 1289-1293, 1297. DOI: 10.16096/J.cnki.nmgyxzz.2023.55.11.003.
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]
崔亚东, 李春媚, 韩思圆, 等. 合成MRI定量参数对前列腺癌的诊断价值[J]. 中华放射学杂志, 2021, 55(9): 975-980. DOI: 10.3760/cma.j.cn112149-20200721-00935.
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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