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   复旦学报(医学版)  2021, Vol. 48 Issue (2): 217-223      DOI: 10.3969/j.issn.1672-8467.2021.02.011
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3D-胸部CT估算肺纤维化程度在特发性肺纤维化预后分析中的应用
杜开锋1,3 , 张来2 , 贺红梅4 , 陈智鸿1     
1. 复旦大学附属中山医院呼吸科 上海 200032;
2. 复旦大学附属中山医院放射科 上海 200032;
3. 复旦大学附属闵行医院呼吸科 上海 201199;
4. 四川省眉山市人民医院呼吸科 眉山 620010
摘要目的 探讨3D-CT(three-dimensional CT)估算的肺纤维化体积(fibrotic lung volume,FLV)占肺总体积(total lung volume,TLV)的百分比(简称CTFLV/TLV%)是否可预测特发性肺纤维化(idiopathic pulmonary fibrosis,IPF)患者的预后。方法 纳入复旦大学附属中山医院2012年3月1日—7月31明确诊断为IPF的患者。记录患者一般情况、肺功能参数、圣乔治评分、GAP评分、氧饱和度和CTFLV/TLV%等,分析各指标对患者生存期的影响。患者随访至2020年7月31日。结果 共纳入10例IPF患者,最长随访时间96个月,最短5个月,平均37.3个月。CTFLV/TLV%与患者预后密切相关,CTFLV/TLV%≤15的患者较CT FLV/TLV%>15的患者具有明显的生存优势,两组差异有统计学意义(t=-2.93,P < 0.05)。基线一氧化碳弥散量占预计值百分比(percentage of carbon monoxide diffusing capacity in the predicted value,DLCO% pred)与患者预后呈正相关(r=0.690,P=0.026)。基线GAP评分与生存有负相关趋势,但差异无统计学意义。用力肺活量(forced vital capacity,FVC)和用力肺活量占预计值百分比(percentage of FVC in the predicted value,FVC% pred)与患者预后无明显相关性。结论 采用3D-CT估算CTFLV/TLV%可初步预测IPF患者预后;CT FLV/TLV%或可预测IPF患者的生存期。
关键词特发性肺纤维化(IPF)    3D重建    CT    预后    
Fibrotic lung volume evaluated by 3D quantitative chest CT in predicting the survival of patients with idiopathic pulmonary fibrosis
DU Kai-feng1,3 , ZHANG Lai2 , HE Hong-mei4 , CHEN Zhi-hong1     
1. Department of Respiratory Medcine, Zhongshan Hospital, Fudan University, Shanghai 200032, China;
2. Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China;
3. Department of Respiratory Medicine, Minhang Hospital, Fudan University, Shanghai 201199, China;
4. Department of Respiratory Medicine, People's Hospital of Meishan, Meishan 620010, Sichuan Province, China
Abstract: Objective To investigate whether the percentage of fibrotic lung volume (FLV) in total lung volume (TLV), i.e., CTFLV/TLV% assessed by three-dimensional (3D) chest CT can predict the prognosis of patients with idiopathic pulmonary fibrosis (IPF). Methods Patients diagnosed with IPF in Zhongshan Hospital, Fudan University from Mar 1 to Jul 31, 2012 were recruited. Clinical characteristics, lung function, St.George's score (SGRQ), GAP score, oxygen saturation and FLV/TLV% estimated by 3D-chest CT were recorded.All the patients were followed up until Jul 31, 2020. Results A total of 10 IPF patients were enrolled.The follow-up period was 96 months at most and 5 months at least, with the mean of 37.3 months.FLV/TLV% was closely correlated with the prognosis of patients with IPF.Patients with CTFLV/TLV% ≤ 15 had a clear survival advantage compared with those with CTFLV/TLV%>15, and there was a significant difference between the two groups (t=-2.93, P < 0.05).The baseline DLCO%pred (percentage of carbon monoxide diffusing capacity in the predicted value) had a positive correlation with the survival (r=0.690, P=0.026).The baseline GAP score had a trend of negative correlation with the survival, however, no statistical difference was found.There was no significant correlation between forced vital capacity (FVC), percentage of FVC in the predicted value (FVC%pred) and the patient's prognosis. Conclusion CTFLV/TLV% estimated by 3D chest CT could preliminarily predict the prognosis of patients with IPF.CT FLV/TLV% may predict the survival of IPF patients.
Key words: idiopathic pulmonary fibrosis (IPF)    3D reconstruction    CT    prognosis    

特发性肺纤维化(idiopathic pulmonary fibrosis,IPF)是一种慢性进行性加重的肺部纤维化疾病。其病因未明,起病隐匿且不可逆,早期症状不明显,病程中主要表现为渐进性呼吸困难,常伴有干咳、消瘦等,肺组织学及胸部高分辨CT表现为寻常型间质性肺炎的病理及影像特点[1]。IPF好发于长期吸烟的中老年男性,此类患者中位生存期为3~5年,5年生存率仅为20%~40%[2-3]。有关IPF预后因素的研究发现,用力肺活量(forced vital capacity,FVC)、FVC%pred(percentage of FVC in the predicted value)、血氧饱和度(blood oxygen saturation,SpO2)、一氧化碳弥散量占预计值百分比(percentage of carbon monoxide diffusing capacity in the predicted value,DLCO%pred)、GAP(gender,age,and physiologic variables)评分等与IPF生存期相关,但这些指标是否可预测疾病的发生发展及最终结局,目前尚无定论[4-5]。研究发现高分辨率计算机断层扫描(high resolution computed tomography,HRCT)可以显示肺纤维化程度,较肺功能重复性好,且有标准的扫描间隔,可做定量分析。

本研究拟通过3D-CT软件量化肺纤维化程度,初步探索采用3D-CT估算肺纤维化体积(fibrotic lung volume,FLV)占肺总体积(total lung volume,TLV)的百分比(简称CTFLV/TLV%)是否可预测IPF患者的生存期。

资料和方法

研究对象和纳入及排除标准  采用回顾性队列研究方法,于2012年3月1日—7月31日于复旦大学附属中山医院招募确诊为IPF稳定期的患者。依据2011年ATS/ERS/JRS/ALAT有关IPF的诊断标准。纳入标准:(1)患者肺功能满足FVC%pred≥50%,同时DLCO%pred为30%~79%;(2)未行外科肺活检,胸部HRCT表现确定为普通型间质性肺炎(usual interstitial pueumonia,UIP);(3)行外科肺活检的患者,结合HRCT和肺活检病理符合特定的类型。排除标准:(1)除外已知病因所致的间质性肺疾病,如职业接触、室内外环境暴露、结缔组织病和药物性肺损害等;(2)有明显肺部感染需抗感染治疗;(3)有严重其他系统疾病和脏器功能不全;(4)患有恶性肿瘤;(5)有明显肝、肾功能损害,丙氨酸转氨酶(ALT)/天冬氨酸转氨酶(AST)>1.5倍正常值上限。

伦理和随访  本研究经复旦大学附属中山医院伦理委员会审核通过(伦理编号为ZS2013-31),所有入组患者均签署知情同意书。随访方式为患者每隔6个月或1年来院随访,或者研究者采取电话随访。随访截至2020年7月31日。

观察指标  记录入组患者的一般资料,包括性别、年龄、吸烟史、确诊日期、主要症状及合并症。所有入组患者均进行肺功能和胸部HRCT检查,均采用64层螺旋CT(Lightspeed VCT,美国GE Healthcare公司)。扫描参数:管电压120~140 kV,管电流140 mAs,扫描准直64×0.625 mm,螺距0.987 5;重建层厚1.25 mm。采用3D软件估算CTFLV/TLV%,导入患者胸部HRCT原始DICOM格式图像至Synapse3D软件(版本V4.4,日本FujiFilm公司),逐层人工辅助描记CT所示总肺组织和纤维化肺组织。纤维化肺组织在CT上定义为蜂窝肺和网格影改变肺组织,其判断由1位呼吸科医师和1位放射科医师共同阅片;若存在争议则请示放射科高年资医师协助阅片。软件自动计算出每层面总肺组织面积及纤维化肺组织面积,根据近似圆台体积计算方法估算每两层之间总肺组织体积及纤维化肺组织体积(图 1),最终得出FLV、TLV及CTFLV/TLV%,分析CTFLV/TLV%、FVC及FVC%pred、DLCO%pred、GAP评分与患者预后的相关性。

A and D: Two adjacent HRCT images of transverse axial scan of one IPF patient.B and E: The total lung area and the total area of fibrosis were automatically captured and drawn by Synapse 3D software. The volume of FLV and TLV were calculated by cone volume formula approximately.C and F: Green color shows the area of fibrosis after drawing by Synapse 3D software. 图 1 通过Synapse 3D软件估算CTFLV/TLV% Fig 1 The evaluation of CTFLV/TLV% by Synapse 3D software

统计方法  数值变量以x±s或中位数(四分位数)表示,分类变量以频数和百分比表示。两独立样本间比较采用独立样本t检验或Mann Whitney U检验;分类变量采用χ2检验或Fisher精确检验(n < 5)。采用Kaplan-Meier法绘制生存分布图,用Log-rank检验评价两组生存差异。临床参数与生存期采用直线相关分析法和多因素直线回归,相关性用Pearson相关系数表示。所有假设检验均为双尾检验,P < 0.05为差异有统计学意义,采用SAS 9.4软件进行统计分析。

结果

一般资料  共纳入IPF患者14例,其中2例因合并急性感染或恶性肿瘤排除,2例失访,最终完成研究并进入数据分析的稳定期IPF患者10例。其中女性2例、男性8例,平均年龄(66.4±3.75)岁。中位生存时间为26.5个月。10例患者均有呼吸困难,干咳7例,体重减轻6例;8例存在合并症,其中高血压5例、糖尿病3例、冠心病1例、慢性胃炎2例、高脂血症1例、银屑病1例、骨质疏松症1例、神经性耳聋1例、慢性肾炎1例、椎间盘突出1例。有吸烟史者4例。FVC平均值(2.41±0.60)L;FVC%pred平均值71.30%±15.44%;DLCO%pred平均值43.97%±12.42%;(不吸氧)SpO2平均值96.50%±1.78%;圣乔治呼吸问卷(St.George's Respiratory Questionnaire score,SGRQ)评分平均值33.16±15.65,GAP评分平均值3.90±1.97。患者基本情况见表 1

表 1 10例IPF患者的基线临床特征 Tab 1 Baseline clinical features of the 10 patients with IPF
Case No. Gender Age(y) Smoking Course of disease at enrollment (year) Symptom Complication Baseline FVC (L) FVC %pred DLCO% pred SPO2 (%) SGRQ GAP Score
1 Female 65 No 5 Dyspnea, dry cough Hyperlipidemia, hypertension, neurological deafness, osteoporosis, chronic gastritis 1.42 64 54.4 96 29.3 3
2 Male 72 No 4 Dyspnea, dry cough, weight loss Hypertension, psoriasis, coronary heart disease 2.32 65 33.7 92 58.7 6
3 Female 59 No 4 Dyspnea Hypertension, chronic nephritis 1.97 79 67.2 97 12.1 0
4 Male 67 No 1 Dyspnea, dry cough, weight loss Disc herniation 3.33 97 39.8 98 30.6 4
5 Male 67 Yes 1 Dyspnea, weight loss Diabetes 2.00 53 31.7 98 52.0 5
6 Male 65 Yes 4 Dyspnea, dry cough, weight loss Diabetes 2.26 56 31.3 98 49.3 6
7 Male 64 Yes 1 Dyspnea, weight loss None 2.83 78 43.6 97 32.2 3
8 Male 72 No 5 Dyspnea, dry cough, weight loss Hypertension, diabetes, chronic gastritis 2.59 85 46.0 97 26.0 4
9 Male 65 No 0.5 Dyspnea, dry cough Hypertension 3.25 84 58.1 96 13.3 2
10 Male 67 Yes 3.5 Dyspnea, dry cough None 2.10 52 33.9 96 28.1 6
FVC: Fibrotic lung volume; FVC%pred: Percentage of FVC in the predicted value;DLCO%pred: Percentage of carbon monoxide diffusing capacity in the predicted value; SPO2: Blood oxygen saturation; SGRQ: St.George's Respiratory Questionnaire score; GAP: Gender, age, and physiologic variables.

肺纤维化程度(CTFLV/TLV%)与患者生存期的分析  采用3D-CT估算CTFLV/TLV%(表 2)。Kaplan-Meier法绘制的CTFLV/TLV%与生存期(月数)分布图见图 2。CTFLV/TLV%的cutoff值≤15时,IPF患者具有明显的生存优势(P < 0.05)。

表 2 IFP患者基线时的3D-CT纤维化肺体积比及肺总体积和生存期 Tab 2 3D CTFLV/TLV% at baselinle and the survival time of the 10 IPF patients
Case No. CT fibrosis volume (mL) CT total lung volume (mL) Fibrosis volume/lung volume (%) Death Survival month (mo)
1 197.22 2 014.72 9.79 No 96
2 1 141.50 3 425.66 33.32 Yes 19
3 142.88 2 866.14 4.99 No 96
4 627.39 4 256.69 14.74 Yes 34
5 973.25 3 220.58 30.22 Yes 39
6 872.94 2 989.54 29.29 Yes 16
7 1 054.16 3 763.49 28.01 Yes 5
8 1 377.14 3 702.01 37.25 Yes 14
9 961.68 4 366.02 22.03 Yes 42
10 1 322.17 3 424.90 40.77 Yes 12
CT fibrosis volume: The volume of reticulation, honeycombing and architectural distortions in CT images; Survival month: Duration from enrollment to death or duration from enrollment till July 31, 2020.
图 2 Kaplan-Meier法分析基线CTFLV/TLV%与IPF患者生存期 Fig 2 Kaplan-Meier ananlysis of the relationship between baseline CTFLV/TLV% and survival in patients with IPF

CT值、肺功能和临床生理评分与IPF患者预后的相关性  线性相关分析显示:生存期与基线CTFLV/TLV%成明显负相关(r=-0.869,P=0.001);与基线DLCO%pred成明显正相关(r=0.690,P=0.026);与GAP评分相关系数为-0.602,具有一定的负相关,但无统计学意义(P=0.066);与FVC年下降率和基线FVC%pred无明显相关性(r=0.116,P=0.750;r=-0.332,P=0.357)(图 3)。

图 3 CT FLV/TLV%值、GAP评分和肺功能参数与IPF患者生存期的相关性 Fig 3 Correlation analysis between CT FLV/TLV%, GAP score and lung function parameters and the survival time of patients with IPF

CT FLV/TLV%值及临床生理参数与IPF预后的多元回归  将单因素分析显示与患者生存相关的因素进一步进行多元回归分析。结果显示CT FLV/TLV%值每增加1个单位,生存期减少1.949个月,差异有统计学意义(P=0.026);而GAP评分和基线DLCO%pred与生存期则无统计学意义。提示CTFLV/TLV%值或可预测IPF患者生存期(表 3)。

表 3 CT值及临床生理参数与IPF患者预后的多元回归分析 Tab 3 Multiple regression analysis of CT value, clinical physiological parameters and prognosis of patients with IPF
Variables Degree of freedom Estimation of parameters Standard error t P 95%CI
CTFLV/TLV% 1 -1.949 0.666 -2.93 0.026 -3.578 -0.320
GAP score 1 2.476 10.223 0.24 0.817 -22.538 27.491
DLCO%pred 1 1.093 1.748 0.63 0.555 -3.184 5.370
GAP: Gender, age, and physiologic variables; DLCO%pred: Percentage of carbon monoxide diffusing capacity in the predicted value.
讨论

特发性肺纤维化(IPF)是一种慢性进行性纤维化间质性肺疾病,既往研究表明该病的预后较差,中位生存期仅2~3年,约25%的患者在确诊后存活时间可超过5年,约15%~20%患者病程中会发生严重和致命的急性加重。IPF临床病程变异度大,可分为缓慢进展、中速进展和快速进展3种亚型。目前尚缺乏统一的分期系统来区分这些亚型,给何时起始治疗、姑息治疗、肺移植等临床决策带来困难。因此,挖掘可靠的生存预测指标将有助于指导临床诊疗。

已有研究报道了多种可预测IPF预后的指标,但其预测价值不一。多数研究提示基础FVC%pred预计值对IPF患者的预后有影响,FVC%pred年下降率10%~15%的患者死亡风险是年下降率 < 5%患者的2倍多[6]。单因素分析发现,6个月FVC%pred下降、12个月FVC%pred下降、12个月DLCO%pred下降与患者生存显著相关。在预测死亡结局方面,DLCO%pred似乎比FVC%pred更好[7-8]。Kärkkäinen等[9]对芬兰东部库奥皮奥大学医院的132例IPF患者进行回顾性队列研究,发现GAP评分和综合生理指标(composite physiologic index,CPI)均与生存率显著相关,GAP分期预测2年内死亡率的准确性(0.67)略高于CPI(0.64)。多变量分析显示最佳的预测模型为包含年龄、性别和CPI的模型。在本研究中,我们发现生存期与DLCO%pred基线值呈明显正相关,与GAP评分有一定的负相关趋势(但无统计学意义);FVC年下降率和FVC%pred基线值无明显相关性,可能与样本量较少有关。

IPF的HRCT特征主要为广泛性分布在双肺基底部、外带的网状阴影或蜂窝样阴影。HRCT可清楚地观察IPF患者肺组织的细微组织结构,是诊断IPF的关键。同时HRCT扫描有既定操作规范、可重复性强,且可捕获整个肺部的纤维化累及范围并分析影像特征的异质性,在临床工作中通常根据HRCT所示纤维化范围大致判断患者病情轻重,未能做到纤维化程度的量化指标,作者查阅既往文献发现,定量CT是预后的最佳预测因子。Nakagawa等[10]通过计算机辅助量化HRCT图像上的蜂窝肺,分析蜂窝肺与IPF预后的相关性,其中蜂窝肺的面积被称为“HA%”,研究发现HA%与FVC%pred、CPI、GAP均显著相关,HA%是IPF患者3年内死亡率的重要独立预测因子。该研究共纳入了52例患者,将HA%的阈值设定为4.8%,HA% < 4.8%与HA%≥4.8%的患者相比,中位生存期分别为5.0年和1.3年(P < 0.001),因此认为CT影像在预测IPF生存方面具有优势。目前3D-CT定量系统已被用于量化IPF或COPD等疾病中的纤维化或肺气肿程度[11-13]。但还未见使用3D-CT定量系统计算CTFLV/TLV%在IPF进行预后判断,本研究中我们提出用3D-CT量化系统测量CT影像中符合肺纤维化的肺体积(包括蜂窝肺和网状肺),计算纤维化肺体积占总肺体积的百分比,并定义为CT FLV/TLV%。在进行生存分析时,根据ROC曲线下最大面积选择15%的阈值,显示两组生存曲线的差异有统计学意义。

虽然目前文献报道的各种方案均对IPF预后有一定的预测价值,但是均未得到大规模临床验证,应进一步探索更多预测IPF预后的指标。而使用CT FLV/TLV%对IPF患者预后判断的优势在于HRCT扫描规范、可重复性强,且在患者初诊时即可做出预后判断,在IPF预后预测中具有重要价值。本研究发现采用3D-CT估算CTFLV/TLV%可初步预测特发性肺纤维化患者预后,CT FLV/TLV%可能是肺纤维化全因死亡率的危险因素。CT影像客观性强,相对稳定,能捕获细微的变化,且能反映纤维化程度对肺的整体影响。随着三维影像技术的开发和算法的进步,3D-CT估算CTFLV/TLV%将有助于判断IPF的预后。

本研究存在以下局限性:(1)纳入的病例数较少;(2)目前FLV及TLV计算采用计算机系统和人工协助相结合的操作,需进一步研发自动分析软件;(3)因临床资料的局限性,本研究未能进一步随访CTFLV/TLV%动态变化,以及CTFLV/TLV%动态变化与生存期的相关性。

本研究提示采用Synapse3D软件对HRCT肺纤维化进行量化可直接、有效地评估IPF患者预后及生存期。

将来,使用多种方法联合对疾病进行监测和管理,将有助于评估疾病进展,判断何时进行药物干预,康复治疗和肺移植等,为IPF患者制定个体化的诊疗方案。

致谢 复旦大学循证医学中心金雪娟老师在分析方法和数据统计方面给予了大力指导。

作者贡献声明  杜开锋  病例资料收集和数据整理,CT影像分析,统计分析,论文撰写。张来  CT影像分析,论文撰写。贺红梅  病例资料收集和数据整理,统计分析。陈智鸿  论文构思,组织实施,论文撰写和修订。

利益冲突声明  所有作者均声明不存在利益冲突。

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文章信息

杜开锋, 张来, 贺红梅, 陈智鸿
DU Kai-feng, ZHANG Lai, HE Hong-mei, CHEN Zhi-hong
3D-胸部CT估算肺纤维化程度在特发性肺纤维化预后分析中的应用
Fibrotic lung volume evaluated by 3D quantitative chest CT in predicting the survival of patients with idiopathic pulmonary fibrosis
复旦学报医学版, 2021, 48(2): 217-223.
Fudan University Journal of Medical Sciences, 2021, 48(2): 217-223.
Corresponding author
CHEN Zhi-hong, E-mail: chen.zhihong@zs-hospital.sh.cn.
基金项目
国家自然科学基金(81970023);上海市卫计委重中之重临床重点学科建设项目(2017ZZ02013)
Foundation item
This work was supported by the National Natural Science Foundation of China (81970023) and the Top-Priority Clinical Key Disciplines Construction Project of Shanghai Health and Family Planning Commission (2017ZZ02013)

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