Morphological characteristics of hepatocellular carcinoma tumor margin: a crucial factor in clinical treatment decision-making and prognostic assessment
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摘要:
肝细胞癌(HCC)的肿瘤边缘形态是影响患者预后和治疗方案选择的关键因素。本文回顾了HCC肿瘤边缘的分类方法, 涉及从传统的宏观分类到基于多组学分析的改良分类系统，并分析这些分类方法在指导个性化治疗方案制订中的作用。此外，本文强调三维影像学技术在评估肿瘤边缘形态中的关键作用，并展望了未来研究的方向，包括验证多组学分类系统的有效性和开发新的影像学及分子生物标志物，以提供更精确的治疗方案，延长患者生存时间。
Abstract:The morphological characteristics of hepatocellular carcinoma (HCC) tumor margins are pivotal in influencing patient's prognosis and the selection of therapeutic strategies. This paper reviewed the classification methods of HCC tumor margins, ranging from traditional macroscopic classifications to refined classification systems based on multi-omics analysis, and analyzed the role of these classification methods in guiding the formulation of personalized treatment plans. Additionally, this paper emphasized the crucial role of three-dimensional imaging techniques in assessing tumor margin morphology and outlined future research directions, including validating the effectiveness of multi-omics classification systems and developing new imaging and molecular biomarkers to achieve more precise treatment plans and prolong patient survival.
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频繁短暂性脑缺血发作(TIA)被认为是缺血性脑卒中的前兆和危险因素, 15%~35%的患者6个月内可继发脑卒中，导致神经功能缺损和生活质量下降[1]。早期筛选高危TIA患者，并予以干预能有效降低缺血性脑卒中的发生率，因此探寻灵敏度和准确度均较好的量化指标意义重大[2]。相关研究[3-4]证实，经颅多普勒超声(TCD)能准确提供动脉血流动力学指标结果，对早期诊断并评估急性脑血流异常程度具有较好的临床价值。研究[5]显示，早期TIA的TCD异常血流信号发生率为80%以上，其中尤以脑血管储备(CVR)功能异常率最高。CVR对TIA患者脑小血管实际缺血缺氧损害程度和代偿能力的评估结果准确可靠[6-7], 但CVR是否可预测TIA继发脑卒中的风险尚无定论[8]。本研究探讨了CVR对频繁TIA患者继发脑卒中风险的评估价值，现报告如下。
1. 资料与方法
1.1 一般资料
选择2017年6月—2018年6月在枣庄市中医院确诊频繁TIA的患者86例为研究对象。纳入标准: ①经TCD、计算机断层扫描(CT)或磁共振成像(MRI)检查排除明确脑卒中和出血，符合TIA诊断意见者; ②每月发作次数 > 2次，每次发作时间最长不超过24 h者; ③无明显脑血管畸形、脑外伤者; ④顺利完成CVR评估试验和随访者; ⑤临床资料完整者。排除标准: ①心源性脑栓塞、脑肿瘤者; ②严重肝、肾功能障碍，凝血功能异常者; ③未能按医嘱规律用药，自行更改药物方案或终止治疗者。本研究经医院伦理委员会审查批准，且研究对象均签署书面知情同意书。86例患者中，男50例，女36例; 年龄48~75岁，平均(56.8±7.7)岁; 发病时间2~10个月，平均(6.1±1.3)个月; 每月发作次数2~5次，平均(2.8±0.6)次; 合并高血压36例，合并糖尿病15例，有吸烟史者22例。
1.2 方法
1.2.1 综合治疗:
根据TIA治疗指南[9]中推荐的治疗方案对患者实施治疗，肠溶性阿司匹林片100 mg(1次/d), 阿托伐他汀片20 mg(每晚1次)，氨氯地平缓释片或硝苯地平控释片控制血压，同时控制血糖，并予以营养脑神经、调整饮食、适量运动、戒烟限酒等综合治疗措施。
1.2.2 超声检查:
采用德国DWL公司的Multi-DOP X2型经颅多普勒超声诊断仪进行检查，探头频率2~4 MHz。嘱患者取仰卧位，首先将2个多深度监测探头固定在专用支架上，对准患者双颞窗。以颅脑CT定位可疑靶血管，通常取双侧，准备5%CO2和95%O2混合气体钢瓶、麻醉呼吸气囊(含2个单向呼吸活瓣)、呼吸面罩和气体导管各1个。待患者双侧被测脑血管的血流速度曲线平稳，指导患者经气囊面罩均匀吸入混合气体1 min, 诱发高碳酸血症，同时测量吸气前后的血流速度, CVR=(吸气后血流速度-吸气前血流速度)/吸气前血流速度×100%[10]。血流灌注指数(PI)和脑动脉平均血流量(MCV)则由TCD自带软件检测后计算得出。
1.2.3 预后分析:
对所有患者进行随访(门诊或电话方式)1年，记录患者脑卒中发生情况，并根据随访期间有无发生脑卒中将患者分为卒中组和无卒中组。
1.3 观察指标
采用TCD检查结合CO2吸入试验评估2组患者治疗前和治疗后14 d的CVR、PI和MCV变化，并记录随访1年患者继发脑卒中情况。
1.4 统计学分析
应用SPSS 20.0统计学软件分析数据，符合正态分布的计量资料以(x±s)表示，组间比较采用t检验，计数资料以[n(%)]表示，组间比较采用χ2检验。应用多元Logistic回归分析法分析随访1年患者继发脑卒中的相关危险因素。绘制受试者工作特征(ROC)曲线评估有统计学差异的危险因素，评估CVR对患者继发脑卒中的预测价值。以α=0.05作为检验水准, P < 0.05为差异有统计学意义。
2. 结果
2.1 基线资料比较
根据随访1年的结果，卒中组纳入24例(27.9%), 无卒中组纳入62例(72.1%)。2组患者的基线资料比较，差异无统计学意义(P > 0.05), 见表 1。
表 1 2组患者基线资料比较(x±s) [n(%)]指标 卒中组(n=24) 无卒中组(n=62) t/χ2 P 性别 男 16(66.7) 34(54.8) 2.772 0.096 女 8(33.3) 28(45.2) 年龄 57.3±7.9 56.4±7.3 0.356 0.642 危险因素 高血压 13(54.2) 23(37.1) 2.072 0.150 糖尿病 5(20.8) 10(16.1) 0.040 0.842 吸烟史 7(29.2) 15(24.2) 0.225 0.635 发病情况 每月发作次数/次 2.9±0.7 2.7±0.5 0.452 0.528 发病时间/月 6.8±3.9 6.0±3.1 1.096 0.226 血脂指标 总胆固醇/(mmol/L) 6.5±1.1 6.4±1.2 0.563 0.502 低密度脂蛋白/(mmol/L) 4.6±0.7 4.4±0.5 0.487 0.598 靶血管位置 大脑中动脉 13(54.2) 33(53.2) 0.599 0.897 大脑前动脉 4(16.7) 7(11.3) 大脑后动脉 3(12.4) 10(16.1) 椎基底动脉 4(16.7) 12(19.4) 2.2 CVR、PI和MCV比较
治疗前, 2组CVR、PI和MCV比较，差异无统计学意义(P>0.05);治疗后, 2组CVR、MCV均高于治疗前, PI均低于治疗前，差异有统计学意义(P < 0.05);治疗后，卒中组CVR低于无卒中组，差异有统计学意义(P < 0.05)，但2组PI、MCV差异无统计学意义(P > 0.05)。见表 2。
表 2 2组CVR、PI和MCV比较(x±s))组别 CVR/% PI MCV/(cm/s) 治疗前 治疗后 治疗前 治疗后 治疗前 治疗后 卒中组(n=24) 22.3±4.5 39.8±6.8* 0.88±0.23 0.49±0.14* 15.5±3.2 26.8±5.7* 无卒中组(n=62) 22.5±4.7 45.7±7.3*# 0.86±0.21 0.47±0.12* 15.6±3.4 27.7±6.3* CVR:脑血管储备; PI:血流灌注指数; MCV:脑动脉平均血流量。与治疗前比较, *P < 0.05;与卒中组比较, #P < 0.05。 2.3 预后相关因素的多元Logistic回归分析
以随访1年患者继发脑卒中情况为应变量，以年龄、高血压、糖尿病、吸烟、发作次数、发病时间、总胆固醇、低密度脂蛋白、靶血管位置、CVR、PI、MCV为自变量，应用全模型多元Logistic回归分析方法进行分析，结果显示CVR为患者继发脑卒中的影响因素(OR=3.219, P=0.011), 见表 3。
表 3 预后相关因素的多元Logistic回归分析因素 β SE Wald OR P 95%CI 年龄 0.230 0.376 0.373 1.258 0.171 0.862~1.634 高血压 0.509 0.416 1.498 1.664 0.077 9.824~2.272 糖尿病 0.197 0.203 0.944 1.218 0.085 0.736~1.753 吸烟 0.407 0.315 1.668 1.502 0.072 0.938~2.203 发作次数 0.466 0.334 0.958 1.754 0.087 0.812~1.927 发病时间 0.781 0.437 3.195 2.184 0.058 1.721~2.656 总胆固醇 0.311 0.283 1.209 1.365 0.080 0.884~1.820 低密度脂蛋白 0.245 0.195 1.574 1.283 0.075 0.839~1.606 靶血管位置 0.121 0.236 0.768 1.054 0.102 0.755~1.321 CVR 1.170 0.421 7.711 3.219 0.011 2.851~3.689 PI 0.804 0.318 2.871 2.235 0.063 1.812~2.512 MCV 0.813 0.289 2.903 2.266 0.066 1.432~2.661 CVR:脑血管储备; PI:血流灌注指数; MCV:脑动脉平均血流量。 2.4 CVR对继发脑卒中风险的预测价值
以CVR作为频繁TIA患者继发脑卒中风险的预测指标进行ROC分析，结果显示, CVR预测继发脑卒中风险的准确度为84.6%, 灵敏度为87.6%, 特异度为75.3%。
3. 讨论
相关研究[11-12]指出，频发TIA患者1年内继发脑卒中的风险较高，因此临床应早期识别频发TIA患者并积极干预，以改善患者预后。目前, 临床评估TIA风险的方法较多，包括颅脑MRI检查、颈动脉彩超测定斑块数量和性质、血脂以及高同型半胱氨酸等多种血清生化指标检测等，但多数方法灵敏度、准确性较差[5-6]。近年来研究[10]表明, CVR可较好地评价脑小动脉和毛细血管的血液灌注储备能力，主要体现血管在神经或体内其他因素诱导下扩张或收缩来适应脑组织即时的血氧需求。TIA和脑卒中发生的重要病理基础为各种原因导致的颈动脉血管结构和功能发生重塑，致使CVR明显下降[4, 6], 因此CVR对频发TIA患者脑卒中发生风险有较好的评估价值。目前，临床用于评价CVR的方法较多，例如TCD结合CO2试验法、屏气和过度换气试验法、静脉注射乙酰唑胺法等，其中TCD结合CO2试验法操作简便、损伤小、重复性好、准确性高[10], 可较好地评估CVR对频繁TIA患者继发脑卒中风险的预测价值。
本研究中, 2组患者基线资料比较，差异无统计学意义(P > 0.05), 表明本研究受其他临床因素影响较小，结果可靠。规范治疗后, 2组患者TCD检查相关指标中仅CVR差异有统计学意义(P < 0.05), 而PI、MCV差异无统计学意义(P > 0.05), 提示CVR具有较好的敏感性，可作为频发TIA患者继发脑卒中风险的评估指标。全模型多元Logistic回归分析结果显示, CVR为随访1年频发TIA患者继发脑卒中风险的影响因素，提示检测CVR指标可对频发TIA患者短期预后尤其是脑卒中发生风险进行有效预测。ROC分析显示, CVR预测脑卒中发生风险的敏感性和特异性均较优，表明检测CVR能有效准确预测频发TIA患者的脑卒中发生风险。但本研究样本量较小，随访时间较短，也未分析CVR影响TIA患者继发脑卒中的内在机制，故有待进一步深入研究。
综上所述, CVR与频繁TIA患者继发脑卒中风险密切相关，其可作为预测脑卒中发生风险的重要定量指标。
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[1] VILLANUEVA A. Hepatocellular carcinoma[J]. N Engl J Med, 2019, 380(15): 1450-1462. doi: 10.1056/NEJMra1713263
[2] 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
[3] LLOVET J M, KELLEY R K, VILLANUEVA A, et al. Hepatocellular carcinoma[J]. Nat Rev Dis Primers, 2021, 7(1): 6. doi: 10.1038/s41572-020-00240-3
[4] BENSON A B, D'ANGELICA M I, ABBOTT D E, et al. Hepatobiliary cancers, version 2.2021, NCCN clinical practice guidelines in oncology[J]. J Natl Compr Canc Netw, 2021, 19(5): 541-565. doi: 10.6004/jnccn.2021.0022
[5] LLOVET J M, CASTET F, HEIKENWALDER M, et al. Immunotherapies for hepatocellular carcinoma[J]. Nat Rev Clin Oncol, 2022, 19(3): 151-172. doi: 10.1038/s41571-021-00573-2
[6] VOGEL A, CERVANTES A, CHAU I, et al. Hepatocellular carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up[J]. Ann Oncol, 2018, 29(Suppl 4): iv238-iv255.
[7] VOGEL A, MARTINELLI E, ESMO G Committee, et al. Updated treatment recommendations for hepatocellular carcinoma (HCC) from the ESMO Clinical Practice Guidelines[J]. Ann Oncol, 2021, 32(6): 801-805. doi: 10.1016/j.annonc.2021.02.014
[8] SALEM R, TSELIKAS L, DE BAERE T. Interventional treatment of hepatocellular carcinoma[J]. J Hepatol, 2022, 77(4): 1205-1206. doi: 10.1016/j.jhep.2022.03.037
[9] FAN Z Q, JIN M S, ZHANG L, et al. From clinical variables to multiomics analysis: a margin morphology-based gross classification system for hepatocellular carcinoma stratification[J]. Gut, 2023, 72(11): 2149-2163. doi: 10.1136/gutjnl-2023-330461
[10] KANAI T, HIROHASHI S, UPTON M P, et al. Pathology of small hepatocellular carcinoma. A proposal for a new gross classification[J]. Cancer, 1987, 60(4): 810-819. doi: 10.1002/1097-0142(19870815)60:4<810::AID-CNCR2820600417>3.0.CO;2-1
[11] OKUDA K, PETERS R L, SIMSON I W. Gross anatomic features of hepatocellular carcinoma from three disparate geographic areas. Proposal of new classification[J]. Cancer, 1984, 54(10): 2165-2173.
[12] KUDO M, KITANO M, SAKURAI T, et al. General rules for the clinical and pathological study of primary liver cancer, nationwide follow-up survey and clinical practice guidelines: the outstanding achievements of the liver cancer study group of Japan[J]. Dig Dis, 2015, 33(6): 765-770. doi: 10.1159/000439101
[13] JANG J Y, LEE J S, KIM H J, et al. The general rules for the study of primary liver cancer[J]. J Liver Cancer, 2017, 17(1): 19-44. doi: 10.17998/jlc.17.1.19
[14] GONVERS S, MARTINS-FILHO S N, HIRAYAMA A, et al. Macroscopic characterization of hepatocellular carcinoma: an underexploited source of prognostic factors[J]. J Hepatocell Carcinoma, 2024, 11: 707-719. doi: 10.2147/JHC.S447848
[15] BENSON A B, D'ANGELICA M I, ABRAMS T, et al. NCCN guidelines insights: biliary tract cancers, version 2.2023[J]. J Natl Compr Canc Netw, 2023, 21(7): 694-704. doi: 10.6004/jnccn.2023.0035
[16] LI Y M, LI P P, MA J J, et al. Preoperative three-dimensional morphological tumor features predict microvascular invasion in hepatocellular carcinoma[J]. Acad Radiol, 2024, 31(5): 1862-1869. doi: 10.1016/j.acra.2023.10.060
[17] LLOVET J M, DE BAERE T, KULIK L, et al. Locoregional therapies in the era of molecular and immune treatments for hepatocellular carcinoma[J]. Nat Rev Gastroenterol Hepatol, 2021, 18(5): 293-313. doi: 10.1038/s41575-020-00395-0
[18] ZHANG W, ZHANG B X, CHEN X P. Adjuvant treatment strategy after curative resection for hepatocellular carcinoma[J]. Front Med, 2021, 15(2): 155-169. doi: 10.1007/s11684-021-0848-3
[19] LIN W D, YE L N, SONG Z S, et al. Wide surgical margins improve prognosis for HCC with microvascular invasion[J]. Eur Rev Med Pharmacol Sci, 2023, 27(5): 2052-2059.
[20] TSILIMIGRAS D I, SAHARA K, MORIS D, et al. Effect of surgical margin width on patterns of recurrence among patients undergoing R0 hepatectomy for T1 hepatocellular carcinoma: an international multi-institutional analysis[J]. J Gastrointest Surg, 2020, 24(7): 1552-1560. doi: 10.1007/s11605-019-04275-0
[21] GONG S C, CHO M Y, LEE S W, et al. The meaning of gross tumor type in the aspects of cytokeratin 19 expression and resection margin in patients with hepatocellular carcinoma[J]. J Gastroenterol Hepatol, 2016, 31(1): 206-212. doi: 10.1111/jgh.13063
[22] PARK J H, KIM D H, KIM S H, et al. The clinical implications of liver resection margin size in patients with hepatocellular carcinoma in terms of positron emission tomography positivity[J]. World J Surg, 2018, 42(5): 1514-1522. doi: 10.1007/s00268-017-4275-1
[23] ADHOUTE X, PÉNARANDA G, RAOUL J L, et al. Hepatocellular carcinoma macroscopic gross appearance on imaging: predictor of outcome after transarterial chemoembolization in a real-life multicenter French cohort[J]. Eur J Gastroenterol Hepatol, 2019, 31(11): 1414-1423. doi: 10.1097/MEG.0000000000001420
[24] SHERMAN M. Recurrence of hepatocellular carcinoma[J]. N Engl J Med, 2008, 359(19): 2045-2047. doi: 10.1056/NEJMe0807581
[25] SAKON M, KOBAYASHI S, WADA H, et al. "Logic-based medicine" is more feasible than "evidence-based medicine" in the local treatment for hepatocellular carcinoma[J]. Oncology, 2020, 98(5): 259-266. doi: 10.1159/000505554
[26] XU X F, WU H, LI J D, et al. Association of tumor morphology with long-term prognosis after liver resection for patients with a solitary huge hepatocellular carcinoma-a multicenter propensity score matching analysis[J]. Hepatobiliary Surg Nutr, 2023, 12(3): 314-327. doi: 10.21037/hbsn-21-423
[27] ERSTAD D J, TANABE K K. Prognostic and therapeutic implications of microvascular invasion in hepatocellular carcinoma[J]. Ann Surg Oncol, 2019, 26(5): 1474-1493. doi: 10.1245/s10434-019-07227-9
[28] HE J, SHI J, FU X, et al. The clinicopathologic and prognostic significance of gross classification on solitary hepatocellular carcinoma after hepatectomy[J]. Medicine, 2015, 94(32): e1331. doi: 10.1097/MD.0000000000001331
[29] NAKASHIMA Y, NAKASHIMA O, TANAKA M, et al. Portal vein invasion and intrahepatic micrometastasis in small hepatocellular carcinoma by gross type[J]. Hepatol Res, 2003, 26(2): 142-147. doi: 10.1016/S1386-6346(03)00007-X
[30] LAUWERS G Y, TERRIS B, BALIS U J, et al. Prognostic histologic indicators of curatively resected hepatocellular carcinomas: a multi-institutional analysis of 425 patients with definition of a histologic prognostic index[J]. Am J Surg Pathol, 2002, 26(1): 25-34. doi: 10.1097/00000478-200201000-00003
[31] CUCCHETTI A, PISCAGLIA F, CATURELLI E, et al. Comparison of recurrence of hepatocellular carcinoma after resection in patients with cirrhosis to its occurrence in a surveilled cirrhotic population[J]. Ann Surg Oncol, 2009, 16(2): 413-422. doi: 10.1245/s10434-008-0232-4
[32] BRUIX J, REIG M, RIMOLA J, et al. Clinical decision making and research in hepatocellular carcinoma: pivotal role of imaging techniques[J]. Hepatology, 2011, 54(6): 2238-2244.
[33] HATANAKA K, MINAMI Y, KUDO M, et al. The gross classification of hepatocellular carcinoma: usefulness of contrast-enhanced US[J]. J Clin Ultrasound, 2014, 42(1): 1-8. doi: 10.1002/jcu.22080
[34] ZWANENBURG A, VALLI?RES M, ABDALAH M A, et al. The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping[J]. Radiology, 2020, 295(2): 328-338. doi: 10.1148/radiol.2020191145
[35] MUTHUKRISHNAN R, RADHA M. Edge detection techniques for image segmentation[J]. Int J Comput Sci Inf Technol, 2011, 3(6): 259-267.
[36] Li L H, Wang J W, Liu B, et al. Clinical application of threedimensional reconstruction in preoperative evaluation of hepatectomy[J]. J Clin Hepatol, 2016, 32(5): 938-942.
[37] JR F R B. Transplantation for hepatocellular carcinoma: the Milan criteria and beyond[J]. Liver Transpl, 2006, 12(11 Suppl 2): S8-S13.
[38] XIE D Y, SHI J Y, ZHOU J, et al. Clinical practice guidelines and real-life practice in hepatocellular carcinoma: A Chinese perspective[J]. Clin Mol Hepatol, 2023, 29(2): 206-216. doi: 10.3350/cmh.2022.0402
[39] ZHOU J, SUN H C, WANG Z, et al. Guidelines for the diagnosis and treatment of hepatocellular carcinoma (2019 edition)[J]. Liver Cancer, 2020, 9(6): 682-720. doi: 10.1159/000509424
[40] ZHANG Y F, YANG C, SHENG R F, et al. Preoperatively identify the microvascular invasion of hepatocellular carcinoma with the restricted spectrum imaging[J]. Acad Radiol, 2023, 30(Suppl 1): S30-S39.
[41] CHA S W, SOHN J H, KIM S H, et al. Interaction between the tumor microenvironment and resection margin in different gross types of hepatocellular carcinoma[J]. J Gastroenterol Hepatol, 2020, 35(4): 648-653. doi: 10.1111/jgh.14848
[42] Martins-Filho S N, Alves V A F. The strengths and weaknesses of gross and histopathological evaluation in hepatocellular-carcinoma: A brief review[J]. Surg Exp Pathol, 2019, 2(1): 23. doi: 10.1186/s42047-019-0047-6
[43] VOGEL A, MEYER T, SAPISOCHIN G, et al. Hepatocellular carcinoma[J]. Lancet, 2022, 400(10360): 1345-1362. doi: 10.1016/S0140-6736(22)01200-4
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