劉　慧　林　江△　陸秀良　顧君英　姚家美

(1復(fù)旦大學(xué)附屬中山醫(yī)院放射科,2病理科　上?！?00032)

320排容積CT雙血供灌注評估肺占位性病變的良惡性及與微血管密度的相關(guān)性

劉慧1林江1△陸秀良1顧君英1姚家美2

(1復(fù)旦大學(xué)附屬中山醫(yī)院放射科,2病理科上海200032)

【摘要】目的評價(jià)肺占位性病變雙重血供CT灌注(dual-input CT perfusion,DI-CTP)的可重復(fù)性、鑒別良惡性病變的能力及與病變微血管密度(microvessel density,MVD)的相關(guān)性。方法116例經(jīng)病理證實(shí)的肺占位性病變患者接受320排容積CT的DI-CTP檢查,由兩名觀察者單獨(dú)進(jìn)行DI-CTP參數(shù)測量,獲得病變的肺動(dòng)脈血流量(pulmonary flow,PF)、支氣管動(dòng)脈血流量(bronchial flow,BF)及血流灌注指數(shù)(perfusion index,PI),并計(jì)算灌注總量(total perfusion,TPF)。評價(jià)觀察者內(nèi)及觀察者間的可重復(fù)性;分析良惡性病變DI-CTP參數(shù)的差異;并對其中94例外科手術(shù)切除病灶進(jìn)行CD34免疫組化染色分析DI-CTP參數(shù)與MVD間的相關(guān)性。結(jié)果觀察者間和觀察者內(nèi)的可重復(fù)性達(dá)到良好以上(ICC>0.90)。良惡性肺占位的BF、PF、PI差異有統(tǒng)計(jì)學(xué)意義(P<0.05),其中PI的ROC曲線下面積為0.936。良惡性肺占位間的MVD差異具有統(tǒng)計(jì)學(xué)意義(P<0.05);BF、PF及TPF與MVD呈正相關(guān)。結(jié)論320排容積DI-CIP可重復(fù)性良好,其參數(shù)可反映肺占位性病變的血管生成情況,并為鑒別肺占位的良惡性提供依據(jù)。

【關(guān)鍵詞】肺部病變;CT灌注成像;雙重血供;可重復(fù)性;微血管密度

CT 灌注成像(CT perfusion,CTP)作為一種無創(chuàng)性評價(jià)組織血流灌注的功能成像方式,已經(jīng)成為評價(jià)腫瘤血管生成及抗血管生成治療藥物效果的主要檢查方法[1]。以往肺癌CTP由于受掃描技術(shù)限制,一般只能采用主動(dòng)脈作為輸入動(dòng)脈,即采用單血供灌注(single-input CT perfusion,SI-CTP)模型,該模型只能反映肺腫瘤的支氣管動(dòng)脈供血情況[2-3]。然而大量研究均證實(shí)肺癌的供血來自支氣管動(dòng)脈和肺動(dòng)脈[4-6]。

320排容積CT成像由于探測器寬度達(dá)到16 cm,在無需移床的情況下,一次曝光掃描范圍即可覆蓋成人肺臟的大部,單次容積掃描一般可同時(shí)包含肺內(nèi)病灶、肺動(dòng)脈和主動(dòng)脈,該掃描技術(shù)能夠同時(shí)捕捉到肺動(dòng)脈、主動(dòng)脈以及病灶的動(dòng)態(tài)強(qiáng)化特征,在此基礎(chǔ)上建立的雙血供灌注(dual-input CT perfusion,DI-CTP)模型可以獲得反映肺部病變兩套血供的參數(shù),對于肺內(nèi)病灶的診治有重要意義。

目前使用320排容積CT進(jìn)行肺占位DI-CTP的研究才剛剛起步,國內(nèi)外文獻(xiàn)報(bào)道不多[7-9],且主要用于良惡性病變的鑒別診斷,尚未見系統(tǒng)性地評估肺占位性病變DI-CTP觀察者可重復(fù)性的研究,尚未見將DI-CTP參數(shù)與病變的微血管密度(micro-vessel density,MVD)這一評價(jià)病變血管生成“金標(biāo)準(zhǔn)”進(jìn)行對照的報(bào)道。本研究目的是評價(jià)肺占位性病變DI-CTP觀察者的可重復(fù)性和對肺占位性病變的鑒別診斷價(jià)值,并研究其與MVD之間的相關(guān)性。

資 料 和 方 法

一般資料本研究為前瞻性,經(jīng)復(fù)旦大學(xué)附屬中山醫(yī)院醫(yī)學(xué)倫理委員會(huì)批準(zhǔn)。共116例肺占位性病變患者接受灌注成像檢查,其中男93例,女23例,平均年齡60歲(42～80歲)。納入標(biāo)準(zhǔn):(1)病灶最大徑≥1cm,為實(shí)性病灶;(2)檢查前未接受任何治療;(3) 肝、腎功能良好,無對比劑過敏史;(4)有能力配合檢查。所有病例在CT檢查后均經(jīng)病理證實(shí)(外科手術(shù)切除94例,經(jīng)支氣管鏡活檢16例,CT引導(dǎo)下穿刺活檢6例),其中惡性病變95例,包括腺癌39例、鱗癌34例、腺鱗癌3例、小細(xì)胞肺癌14例、類癌3例、肉瘤樣癌l例、不能分型肺癌l例;良性病變21例,包括錯(cuò)構(gòu)瘤4例、炎性病變14例、肺結(jié)核2例和肺硬化性血管瘤l例。

檢查方法采用Toshiba Aquilion One 320排螺旋CT掃描儀,先進(jìn)行常規(guī)平掃定位,確定灌注掃描范圍,采用高壓注射器從單側(cè)上肢靜脈注射60 mL碘普羅胺(370 mg/mL),注射流率8 mL/s,開始注藥時(shí)即屏氣,2 s后啟動(dòng)17個(gè)回合動(dòng)態(tài)容積掃描(圖1)。掃描參數(shù):管電壓80 kV,管電流80 mA,探測器寬度16 cm,轉(zhuǎn)速0.5 s/r,層厚0.5 mm。一次灌注掃描的平均輻射量是5.07 mSv。

圖像后處理及分析采用Toshiba雙血供灌注軟件,在肺門水平的肺動(dòng)脈主干、降主動(dòng)脈、左心房及肺內(nèi)病灶內(nèi)繪制感興趣區(qū)(regions of interest,ROI)生成4條時(shí)間-密度曲線(time-density curve,TDC)(圖2)。設(shè)置灌注窗寬范圍為0～150 HU,以排除骨質(zhì)及肺組織的干擾,確保病灶灌注測量圖得到良好顯示。運(yùn)行灌注軟件,自動(dòng)生成512×512矩陣編碼的偽彩圖像,分別顯示肺動(dòng)脈血流量(pulmonary flow,PF)、支氣管動(dòng)脈血流量(bronchial flow,BF)及灌注指數(shù)[perfusion index,PI=PF/(PF+BF)](圖3),并計(jì)算灌注總量(total perfusion flow,TPF)。為了解觀察者間一致性(inter-observer agreement),患者的圖像分析由兩名高年資放射科醫(yī)師采用盲法獨(dú)立完成上述所有后處理程序,在病灶的3個(gè)代表層面各測量1次,最終采用3次測量值的平均值;為了解觀察者內(nèi)一致性(intra-observer agreement),并最大程度降低回憶偏倚,其中1位醫(yī)師在1個(gè)月后再次對所有圖像進(jìn)行測量和分析。

Seventeen intermittent low-dose volume acquisitions were made 2 s after the bolus injection (1.5 s per acquisition for the first 8 acquisitions and 2s per acquisition for the subsequent 9 acquisitions).

圖1動(dòng)態(tài)容積掃描流程式圖

Fig 1Dynamic volumetric scanning process diagram

The peak enhancement time point of the left atrium (indicated by the max line) was located between the two peaks of PA and aorta, distinguishing between pulmonary and bronchial circulation. The lesion had two ascending slopes representing pulmonary and bronchial circulation respectively. The latter was much steeper than the former, which suggests that bronchial circulation was dominant in this case.

圖2輸入動(dòng)脈(肺動(dòng)脈,主動(dòng)脈)、左心房及病灶的時(shí)間密度曲線

Fig 2Time-density curves of input arteries

(PA and aorta),left atrium and lung lesion

BF was 40.9 mL·min-1·100 mL-1, PF was 27.4 mL·min-1·100 mL-1and PI was 42.2%. Microvessel density with CD34 immunostaining was 73 (Original magnification, ×200).

圖363歲男性鱗癌病例

Fig 3Squamous cell carcinoma of a 63-year-old man

病理標(biāo)本免疫組化處理及觀察94例外科手術(shù)切除病灶進(jìn)行CD34染色,其中惡性病變80例(腺癌34例、鱗癌31例、小細(xì)胞肺癌7例、腺鱗癌3例、類癌3例、肉瘤樣癌l例、不能分型肺癌l例),良性病變14例(肺結(jié)核1例、炎性病變9例、錯(cuò)構(gòu)瘤4例)。以PBS液代替一抗作為陰性空白對照,MVD計(jì)數(shù)采用Weidner方法,結(jié)果判定在盲法下進(jìn)行。

統(tǒng)計(jì)學(xué)分析使用SPSS 21.0及MedCale 14.8.1軟件完成。采用Bland-Altman法及組內(nèi)相關(guān)系數(shù)(intraclass correlation coefficient,ICC)分析DI-CTP檢查的觀察者一致性;采用非參數(shù)秩和檢驗(yàn)(Wilcoxon法)比較惡性與良性肺占位性病變DI-CTP參數(shù),并繪制有鑒別診斷價(jià)值參數(shù)的受試者工作特性曲線(receiver operating characteristic curve,ROC曲線);運(yùn)用Youden指數(shù)決定ROC曲線的最佳工作點(diǎn)(optimal operating point,OOP),并計(jì)算OOP、相應(yīng)敏感性、特異性、似然比(1ikelihood ratio,LR)、陽性預(yù)測值(positive predictive value,+PR)和陰性預(yù)測值(negative predictive value,-PR);采用Spearman相關(guān)系數(shù)分析各DI-CTP參數(shù)與MVD的相關(guān)性。

結(jié)果

DI-CTP結(jié)果觀察者間和觀察者內(nèi)的可重復(fù)性均達(dá)到良好以上(ICC>0.90),觀察者間測定病灶的PF、BF、PI值的ICC分別為0.96、0.98和0.95;觀察者內(nèi)ICC則分別為0.97、0.99和0.97。病變最大徑(40.96±17.74) mm,范圍14～120 mm。良、惡性肺占位的支氣管動(dòng)脈血流量BF、肺動(dòng)脈血流量PF、灌注指數(shù)PI均數(shù)間差異具有統(tǒng)計(jì)學(xué)意義(P<0.05);灌注總量TPF均數(shù)間的差異無統(tǒng)計(jì)學(xué)意義,具體統(tǒng)計(jì)結(jié)果見圖4、表1。BF、PF、PI值鑒別良惡性肺占位的ROC曲線下面積(area under curve,AUC)分別為0.644、0.711、0.936,其中PI數(shù)值最大,具有最高的診斷準(zhǔn)確性(圖5)。PI=51.15%時(shí),鑒別良、惡性肺占位的敏感度是0.95,特異度是0.84,+LR是17.54,-LR是0.17,+PR是17.54,-PR是0.17。

PF:Pulmonary flow;BF: Bronchial flow;PI:Perfusion index;TPF:Total pulmonary flow.

圖4　良惡性病變CTP參數(shù)箱線圖(n=116)

BF,PF,TPF:mL·min-1·100 mL-1;PI:100 %.

Parameters for identifying lung lesions.

圖 5CT灌注成像四個(gè)參數(shù)診斷肺占位性病變的ROC曲線

Fig 5ROC curves of the four perfusion parameters

for identifying lung lesions

MVD計(jì)數(shù)結(jié)果良惡性肺占位的MVD分別為(139.49±107.85)條/視野和(62.04±35.43)條/視野,差異具有統(tǒng)計(jì)學(xué)意義(P=0.011)。

DI-CTP參數(shù)與MVD相關(guān)性分析 94例免疫組化染色的肺占位性病變BF、PF、TPF與MVD呈正相關(guān)(P值均<0.05),PI與MVD無相關(guān)性(P>0.05,表2)。

表2　CT灌注參數(shù)與MVD相關(guān)性分析

討論

應(yīng)用CTP對肺占位性病變進(jìn)行鑒別診斷的病理生理基礎(chǔ)是良惡性病變的血管生成和血管反應(yīng)的性質(zhì)不同造成其血液動(dòng)力學(xué)差異。既往研究已證實(shí)肺部CTP檢查可以用來鑒別診斷良惡性病變[10-12],并認(rèn)為CTP參數(shù)與MVD具有較好的相關(guān)性[2,13]。

肺占位性病變320排容積CT雙血供灌注成像研究的技術(shù)優(yōu)勢肺占位血流灌注不均勻[2],如CTP掃描只覆蓋其中心區(qū)域,則可重復(fù)性有限,故需要擴(kuò)大掃描覆蓋范圍,實(shí)現(xiàn)病灶容積CTP[13-14]。320排CT的覆蓋范圍達(dá)16 cm,可實(shí)現(xiàn)真正意義的容積灌注,另外,320排容積CT的球管轉(zhuǎn)速為0.5 s/r,掃描時(shí)間間隔大大縮短,時(shí)間分辨率進(jìn)一步提高,故能更真實(shí)準(zhǔn)確地反映病變的血供情況,其可重復(fù)性明顯提高。灌注研究一直受輻射劑量的限制,本研究采用低劑量掃描,平均輻射量是5.07 mSv,為歐共體標(biāo)準(zhǔn)的55.7%,極大地降低了受檢者的輻射劑量。

目前,國內(nèi)外灌注研究[2,11,15]多應(yīng)用SI-CTP模型計(jì)算灌注參數(shù),然而SI-CTP模型通常只能反映肺癌的優(yōu)勢供血來源,而供血相對少的那一部分血流灌注則被忽略。Yuan等[7]認(rèn)為DI-CTP模型可以很好地應(yīng)用于肺癌的灌注研究,Ohno等[16]對肺孤立結(jié)節(jié)的灌注研究發(fā)現(xiàn)DI-CTP模型比SI-CTP模型具有更好的定性診斷價(jià)值。本研究也發(fā)現(xiàn),使用DI-CTP模型可以將肺占位性病變內(nèi)肺動(dòng)脈和支氣管動(dòng)脈供血分開觀察,測量的灌注值能夠更全面、準(zhǔn)確地反映肺占位的血供特點(diǎn),且使用DI-CTP模型進(jìn)行灌注研究的可重復(fù)性很好,可能更有利于病灶血供的觀察與比較。

CTP參數(shù)在肺占位病變鑒別診斷中的價(jià)值肺部病變具有肺動(dòng)脈及支氣管動(dòng)脈雙重血供,并且惡性病變多以支氣管動(dòng)脈供血為主,良性病變多以肺動(dòng)脈供血為主[6,8]。本研究中BF反映了支氣管動(dòng)脈供血豐富程度,PF反映了肺氣管動(dòng)脈供血豐富程度,PI反映了肺動(dòng)脈血流量在總灌注量中所占比例。本研究顯示惡性病變組的BF值高于良性病變組,而PF及PI值低于良性病變組,該結(jié)果與不同性質(zhì)肺占位的病理生理基礎(chǔ)相一致,其中PI的ROC AUC最大,具有最高的診斷準(zhǔn)確性,并且可用PI<51.15%作為良惡性病變的診斷閾值。本研究中惡性病變的PF及PI值均高于Yuan 等[8]的研究,LR和PR值也有所差異,這可能與對比劑注射方法和掃描技術(shù)不同有關(guān),也可能與病變大小、位置和個(gè)體生理差異等因素有關(guān)。

肺占位性病變CTP參數(shù)與MVD相關(guān)性分析腫瘤內(nèi)MVD可定量反映腫瘤血管生成狀態(tài),是目前評價(jià)腫瘤血管生成的“金標(biāo)準(zhǔn)”[14,17-18]。MVD可以通過一些特異性抗體進(jìn)行標(biāo)記,且多采用Weidner的計(jì)數(shù)標(biāo)準(zhǔn)[19]。CTP成像則是可以定量反映病變微循環(huán)特征的功能成像方法。既往CTP成像運(yùn)用的是單血供模型,對肺占位病變CTP參數(shù)與MVD相關(guān)性分析顯示,血流量和血容量與MVD有較好的相關(guān)性[12,20-21]。本文首次應(yīng)用DI-CTP模型對其參數(shù)與MVD做相關(guān)性研究,結(jié)果發(fā)現(xiàn)肺占位病變BF、PF、TPF與MVD呈正相關(guān);且良惡性肺占位的MVD差異具有統(tǒng)計(jì)學(xué)意義;另外TPF與MVD相關(guān)系數(shù)最高,故BF、PF及TPF可以無創(chuàng)性間接反映肺占位性病變的MVD這一病理特征,并具備幫助鑒別病變的良惡性、指導(dǎo)腫瘤治療和評判療效的潛能。本研究中良性病例多為炎性病變,可能導(dǎo)致良性病變的血流總量及MVD高于惡性病例。

綜上所述,320排容積DI-CTP可重復(fù)性好,其參數(shù)可反映肺占位性病變的血管生成情況,并對肺占位的良惡性鑒別提供幫助。

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Dual-input perfusion of lung lesions with 320-detector-row CT:its value in differentiating malignant from benign lesions and correlation with lesion micro-vessel density

LIU Hui1, LIN Jiang2△, LU Xiu-liang3, GU Jun-ying4, YAO Jia-mei5

(1DepartmentofRadiology,2DepartmentofPathology,ZhongshanHospital,FudanUniversity,Shanghai200032,China)

【Abstract】ObjectiveTo investigate the reproducibility of dual-input CT perfusion (DI-CTP) of lung lesions with 320-detector-row CT,its value in differentiation of malignant and benign lesions and the correlation between CTP parameters and microvessel density (MVD).MethodsOne hundred and sixteen patients with various lung lesions confirmed later by pathology underwent DI-CTP with 320-detector-row CT.The pulmonary trunk and the descending aorta were selected as input arteries for measuring contributions from pulmonary and bronchial circulation to the lesions.Pulmonary flow (PF),bronchial flow (BF),and perfusion index (PI) were recorded by two independent radiologists,and then total perfusion (TPF) was calculated.Intraclass correlation coefficient (ICC) and Bland-Altman statistics were used to evaluate intra-and inter-observer agreement.DI-CTP parameters were compared between malignant and benign lesions.The correlation between DI-CTP and MVD was analysed in 94 cases of lesions with immunohistochemical staining of CD34.ResultsBoth intra- and inter-observer agreements were good to excellent (ICC>0.90).PF and PI of benign lesions were higher than those of malignant lesions.BF of malignant lesions was higher than that of benign lesions.Statistically significant differences of BF,PF and PI were found between malignant and benign lesions (P<0.05) with the area under the ROC curve of PI being 0.936,the largest of the three perfusion parameters.There was statistically significant difference in MVD between benign and malignant lesions (P<0.05).BF,PF and TPF values were positively correlated with MVD .ConclusionsDI-CTP is reproducible and reflects the angiogenesis of lung lesions.It can provide additional information for differential diagnosis of malignant from benign lung lesions.

【Key words】lung lesions;CT perfusion;dual-input;reproducibility;micro-vessel density

【中圖分類號(hào)】R812

【文獻(xiàn)標(biāo)識(shí)碼】A

doi:10.3969/j.issn.1672-8467.2016.03.012

(收稿日期:2015-11-03;編輯:王蔚)

△Corresponding authorE-mail:lin.jiang@zs-hospital.sh.cn