|
0 前言
流行病學(xué)調(diào)查指出，腦卒中是我國(guó)成年人致死和致殘的首位原因，其中，缺血性腦卒中約占發(fā)病總數(shù)的80%，其發(fā)病率呈上升趨勢(shì)[1, 2]。缺血性腦卒中發(fā)病時(shí)血管狹窄或閉塞，血流灌注減低，腦組織出現(xiàn)不可逆轉(zhuǎn)的梗死核心區(qū)域；但在其周圍存在血流灌注水平低于維持正常腦功能但不至于引起腦組織形態(tài)結(jié)構(gòu)改變的區(qū)域，該區(qū)域被稱為缺血半暗帶（ischemic penumbra, IP），這一概念是由ASTRUP等[3]首次提出?！都毙阅X梗死缺血半暗帶臨床評(píng)估及治療中國(guó)專家共識(shí)》[4]指出，及時(shí)恢復(fù)IP區(qū)域的血流，該區(qū)域即可恢復(fù)正常，否則會(huì)惡化成為梗死灶而加重腦損害，因此IP是缺血性腦梗死治療的關(guān)鍵靶點(diǎn)[5]。另外，多項(xiàng)臨床研究發(fā)現(xiàn)部分超過(guò)時(shí)間窗并存在IP的患者仍可從再灌注治療中獲益，成為拓寬血管內(nèi)治療時(shí)間窗的最新證據(jù)。早期、全面和精準(zhǔn)地識(shí)別IP對(duì)臨床治療至關(guān)重要，MRI以其多參數(shù)、多序列成像以及軟組織分辨率高的優(yōu)勢(shì)在中樞神經(jīng)系統(tǒng)疾病的成像中應(yīng)用廣泛，MRI不匹配模型也是IP評(píng)估中主要方法之一，目前對(duì)梗死核心的診斷價(jià)值基本達(dá)成共識(shí)，對(duì)于如何區(qū)分血流異常灌注的區(qū)域，仍是IP研究的熱點(diǎn)，多種不匹配模型的研究以及基于圖像大數(shù)據(jù)的影像組學(xué)及人工智能技術(shù)的應(yīng)用以期更為早期和精準(zhǔn)地評(píng)估IP，為臨床進(jìn)行再灌注治療提供影像證據(jù)，本文就應(yīng)用較多的MRI技術(shù)對(duì)IP的識(shí)別與評(píng)估的研究進(jìn)展進(jìn)行綜述，旨在為今后的研究提供方向。
1 基于傳統(tǒng)MRI影像學(xué)“不匹配”對(duì)IP的識(shí)別和評(píng)估
1.1 液體衰減反轉(zhuǎn)恢復(fù)-擴(kuò)散加權(quán)成像不匹配模型
當(dāng)擴(kuò)散加權(quán)成像（diffusion weighted imaging, DWI）上出現(xiàn)高信號(hào)區(qū)域，而液體衰減反轉(zhuǎn)恢復(fù)（fluid attenuated inversion recovery, FLAIR）像該區(qū)域信號(hào)改變不明顯時(shí)，即FLAIR-DWI不匹配；FLAIR-DWI不匹配的出現(xiàn)表明患者發(fā)病時(shí)間在4.5 h之內(nèi)[6, 7]，該發(fā)現(xiàn)有助于指導(dǎo)醒后卒中及發(fā)病時(shí)間不明的患者進(jìn)行安全有效的靜脈溶栓治療[8, 9]。但FLAIR-DWI不匹配的判斷存在主觀差異[10]。FLAIR血管高信號(hào)征（FLAIR vascular hyperintensity, FVH）是MRI上比較常見(jiàn)的一種征象，主要表現(xiàn)為MRI FLAIR序列上沿腦溝或腦表面分布的點(diǎn)狀、線狀的高信號(hào)影[11]，該征象的出現(xiàn)與血栓引起大血管狹窄或閉塞繼而導(dǎo)致缺血區(qū)內(nèi)血流緩慢有關(guān)[12]，但這一表現(xiàn)大多在有側(cè)支循環(huán)建立時(shí)才可見(jiàn)。LEGREND等[13, 14]研究發(fā)現(xiàn)，DWI所示梗死核心和FVH出現(xiàn)區(qū)域存在不匹配，并且與灌注加權(quán)成像（perfusion weighted imaging, PWI）-DWI不匹配相比，F(xiàn)VH-DWI不匹配可以識(shí)別更大范圍的IP且具有高度敏感性；更進(jìn)一步的研究發(fā)現(xiàn)，F(xiàn)VH-DWI不匹配可以快速識(shí)別最有可能從血管再通及血運(yùn)重建中獲益的患者，提示臨床存在FVH-DWI不匹配的患者可能會(huì)有較好的臨床預(yù)后，這與WANG等[15]研究結(jié)果一致。但FVH-DWI不匹配敏感度雖高，特異度只有中等[14]，認(rèn)為所顯示的不匹配區(qū)域不僅僅是IP，其原因仍值得進(jìn)一步探討。
1.2 MR血管成像-DWI不匹配模型
急性缺血性腦卒中（acute ischemic stroke, AIS）的發(fā)生與病變區(qū)域供血血管的狹窄或閉塞有關(guān)。MR血管成像（MR angiography, MRA）是MRI檢查序列中常用的一種技術(shù)，可無(wú)損傷、多角度旋轉(zhuǎn)顯示腦血管血流情況。目前MRA在AIS的應(yīng)用多集中在診斷責(zé)任血管及評(píng)估側(cè)支循環(huán)，對(duì)于IP評(píng)估中應(yīng)用較少。LANSBERG等[16]發(fā)現(xiàn)前循環(huán)大動(dòng)脈閉塞或狹窄而DWI所示梗死部位體積越小的患者可以從6 h內(nèi)的再灌注中獲益；DEGUCHI等[17]發(fā)現(xiàn)MRA-DWI不匹配可以用來(lái)預(yù)測(cè)IP并指導(dǎo)溶栓治療及預(yù)后評(píng)估。付志勇等[18]研究急性后循環(huán)腦梗死患者發(fā)現(xiàn)存在MRA-DWI不匹配者容易發(fā)生早期神經(jīng)功能惡化，而早期的血管再通治療可以改善這一情況，認(rèn)為這與IP的存在有一定聯(lián)系，但仍需要更多的研究及更大的樣本量進(jìn)一步證明。
1.3 PWI-DWI不匹配模型
動(dòng)態(tài)磁敏感對(duì)比增強(qiáng)PWI（dynamic susceptibility contrasts enhanced PWI, DSC-PWI）在臨床中應(yīng)用較多，主要基于團(tuán)注順磁性對(duì)比劑追蹤技術(shù)來(lái)反映組織血管灌注情況，并可以通過(guò)擬合得到腦血容量（cerebral blood volume, CBV）、腦血流量（cerebral blood flow, CBF）、平均通過(guò)時(shí)間（mean transit time, MTT）、達(dá)峰時(shí)間（time to peak, TTP）及殘余功能達(dá)峰時(shí)間（time to maximum of the residual function, Tmax）等血流動(dòng)力學(xué)參數(shù)。PWI和DWI之間的不匹配是臨床上運(yùn)用MRI技術(shù)評(píng)估IP的最經(jīng)典的模式，一般認(rèn)為以Tmax＞6 s或相對(duì)MTT（relative MTT, rMTT）＞145%區(qū)域代表低灌注區(qū)，DWI高信號(hào)區(qū)域[表觀擴(kuò)散系數(shù)（apparent diffusion coefficient, ADC）＜620×10-6 mm2/s]代表梗死核心[19]，兩者的不匹配的范圍即為IP。雖然PWI-DWI不匹配模式預(yù)測(cè)IP已被廣泛使用，但隨著研究的深入[20]，發(fā)現(xiàn)PWI-DWI不匹配模型評(píng)價(jià)IP有一定不足：一方面是PWI常常包括了可逆性缺血區(qū)域；另一方面，部分DWI擴(kuò)散受限高信號(hào)區(qū)域在早期溶栓后是可逆的。也有學(xué)者[21]對(duì)經(jīng)典的不匹配模型進(jìn)行改進(jìn)，并提高了IP評(píng)估的準(zhǔn)確性。但是，此模型僅適用于前循環(huán)腦卒中的患者，說(shuō)明該模型有一定的局限性。
1.4 動(dòng)脈自旋標(biāo)記成像-DWI不匹配模型
動(dòng)脈自旋標(biāo)記成像（arterial spin labeling, ASL）技術(shù)是近些年發(fā)展起來(lái)的MRI灌注技術(shù)，利用動(dòng)脈血內(nèi)水質(zhì)子作為內(nèi)源性標(biāo)記物，將標(biāo)記前后采集的圖像進(jìn)行減影而獲得CBF圖像，避免了注射釓對(duì)比劑所致認(rèn)知障礙和腎纖維化的潛在風(fēng)險(xiǎn)[22, 23]，研究發(fā)現(xiàn)該技術(shù)與傳統(tǒng)的PWI技術(shù)對(duì)血流動(dòng)力學(xué)異常區(qū)域的檢出有良好的一致性[24, 25]，可以作為替代手段應(yīng)用于不適于注射釓對(duì)比劑的患者。LIU等[26]發(fā)現(xiàn)ASL-DWI和PWI-DWI兩種不匹配模型對(duì)IP的評(píng)估同樣具有良好的一致性；NIIBO等[27]研究發(fā)現(xiàn)當(dāng)ASL＜20 mL/100g·min-1以及MTT＞10 s時(shí)，ASL-DWI不匹配與PWI-DWI不匹配具有100%一致性。但ASL也有一定的不足，KOHNO等[28]發(fā)現(xiàn)ASL僅對(duì)大面積腦梗死血流灌注敏感，對(duì)低血流灌注區(qū)域或小梗死灶的敏感性較差。侯聰?shù)?sup>[29]認(rèn)為由于技術(shù)因素ASL測(cè)量值會(huì)低于真實(shí)灌注值，或許高估了缺血區(qū)域；但值得注意的是，相對(duì)于DSC-PWI，ASL所獲得的參數(shù)僅有CBF，而沒(méi)有CBV、MTT、Tmax等指標(biāo)，故ASL-DWI不匹配模型在評(píng)估IP時(shí)具有一定局限性。
1.5 磁敏感加權(quán)成像-DWI不匹配模型
磁敏感加權(quán)成像（susceptibility weighted imaging, SWI）是一種利用組織磁敏感性的差異而成像的技術(shù)。研究發(fā)現(xiàn)，SWI在缺血區(qū)域內(nèi)出現(xiàn)明顯減低、管徑明顯增粗的低信號(hào)血管影，稱為突出血管征（prominent vessel sign, PVS）[30, 31]，一般認(rèn)為PVS可以反映側(cè)支血管形成情況。和PWI（ASL）-DWI不匹配模型從血流動(dòng)力學(xué)變化的角度反映IP不同，SWI-DWI主要從側(cè)支血管形成程度方面評(píng)估[32, 33]；WANG等[34]發(fā)現(xiàn)SWI-DWI不匹配與傳統(tǒng)的PWI-DWI不匹配在識(shí)別IP方面能力相近。LU等[35]使用SWI相位圖與幅值圖結(jié)合、過(guò)濾后的SWI mapping圖對(duì)IP的體積進(jìn)行了測(cè)量，發(fā)現(xiàn)SWIvolume-DWI不匹配與PWI-DWI具有很好的一致性，這或許為識(shí)別IP提供了新的方法。但JIANG等[36]研究 發(fā)現(xiàn)并非所有缺血性卒中病人都出現(xiàn)PVS，只有前循環(huán)梗死、大血管閉塞及心源性梗死的患者更容易出現(xiàn)PVS征。而且目前SWI尚不能精準(zhǔn)量化，PVS征象的評(píng)價(jià)需要較為豐富的臨床經(jīng)驗(yàn)，所以SWI-DWI不匹配模型僅能作為輔助手段提高對(duì)IP評(píng)估的準(zhǔn)確性。
2 基于組織代謝成像對(duì)IP的識(shí)別和評(píng)估
2.1 基于磁共振波譜成像對(duì)IP識(shí)別與評(píng)估
磁共振波譜（magnetic resonance spectroscopy, MRS）是一種利用MRI化學(xué)位移現(xiàn)象來(lái)測(cè)定組成物質(zhì)的分子成分進(jìn)而無(wú)創(chuàng)性檢測(cè)活體組織代謝產(chǎn)物的MRI技術(shù)。根據(jù)腦卒中的病理生理改變，當(dāng)缺血時(shí)，缺血腦組織由無(wú)氧酵解功能，使得該區(qū)域pH值減低，而組織缺血程度不同，其發(fā)生無(wú)氧酵解的程度也不同，一般認(rèn)為，缺血區(qū)腦組織發(fā)生代謝異常是早于組織梗死出現(xiàn)的，這使得從代謝層面可以更早地識(shí)別和評(píng)估IP。ZOLLNER等[37]應(yīng)用MRI磷譜研究腦卒中發(fā)現(xiàn)，梗死區(qū)存在不同程度酸中毒的區(qū)域，認(rèn)為該技術(shù)可能具有評(píng)價(jià)IP和梗死核心的能力；LI等[38]基于新型磁共振光譜成像（MRS imaging, MRSI）技術(shù)獲得了N-乙酰天門冬氨酸（N-acetyl-aspartate, NAA）和乳酸（lactate, Lac）的3D地圖，發(fā)現(xiàn)3D高分辨率MRSI可以將PWI-DWI失配區(qū)區(qū)分為酸性半暗帶區(qū)（高Lac和NAA正常或減低）和良性低血區(qū)（低Lac和NAA正常）；DEUCHAR等[39]發(fā)現(xiàn)MRS聯(lián)合血氧水平依賴磁共振成像（blood oxygen level-dependent MRI, BOLD MRI）識(shí)別具有代謝活性半暗帶的潛力；另有研究發(fā)現(xiàn)急性腦梗死的恢復(fù)可能與IP區(qū)代謝產(chǎn)物氨基丁酸明顯下降有關(guān)[40]，這可作為識(shí)別IP的一個(gè)診斷指標(biāo)。盡管MRS可以從代謝層面評(píng)估IP，但是具有采集時(shí)間長(zhǎng)、空間分辨率差、覆蓋范圍窄且不能做到可視化等缺點(diǎn)，因此，其臨床上用于評(píng)估IP仍存在挑戰(zhàn)。
2.2 基于酰胺質(zhì)子轉(zhuǎn)移加權(quán)成像技術(shù)對(duì)IP的評(píng)估
基于酰胺質(zhì)子轉(zhuǎn)移加權(quán)（amide proton transfer weighted, APTw）成像是一種基于化學(xué)交換飽和轉(zhuǎn)移（chemical exchange saturation transfer, CEST）原理，能夠反映受檢組織pH值、微摩爾甚至納摩爾的游離蛋白或多肽內(nèi)酰胺質(zhì)子濃度分子影像新技術(shù)[41]，且可以構(gòu)建出基于pH值及酰胺質(zhì)子濃度的可視化圖像。SUN等[42]應(yīng)用包含APTw技術(shù)在內(nèi)的多序列MRI研究腦梗死大鼠模型時(shí)發(fā)現(xiàn)APTw成像可以早于常規(guī)T1WI、T2WI檢出缺血腦組織，且可進(jìn)一步細(xì)分PWI-DWI不匹配區(qū)，并認(rèn)為APTw-DWI不匹配區(qū)可能為IP，APTw-PWI不匹配區(qū)可能為良性缺血區(qū)；WANG等[43]應(yīng)用弛豫校準(zhǔn)后的APTw技術(shù)研究急性腦梗死大鼠模型得到的結(jié)果與SUN等一致。TIETZE等[44]應(yīng)用APTw技術(shù)研究超急性腦梗死病例發(fā)現(xiàn)APTw低信號(hào)范圍與最終梗死范圍一致；HARSTON等[45]對(duì)急性腦梗死患者進(jìn)行APTw成像，發(fā)現(xiàn)梗死核心區(qū)、梗死進(jìn)展區(qū)以及良性低灌注區(qū)的APTw信號(hào)依次增高，提示APTw技術(shù)有區(qū)分不同缺血程度腦區(qū)的潛力。譚月發(fā)[46]通過(guò)研究亞急性期缺血性腦卒中患者發(fā)現(xiàn)，APTw在臨床試驗(yàn)中同樣可以進(jìn)一步細(xì)分PWI-DWI不匹配區(qū)。CBF灌注和APTw信號(hào)均減低而DWI信號(hào)正?？赡転镮P，而CBF低灌注而APTw與DWI均正常的區(qū)域?qū)?yīng)良性缺血區(qū)。但APT成像影響因素較多，第一是核奧氏效應(yīng)[47]，是指兩個(gè)空間位置很近的質(zhì)子相互之間存在弛豫現(xiàn)象，當(dāng)其中一個(gè)質(zhì)子受到激發(fā)而飽和時(shí)，會(huì)將能量傳遞給另一個(gè)靠近的質(zhì)子，導(dǎo)致其共振信號(hào)增加，繼而產(chǎn)生干擾性的磁化傳遞效應(yīng)，影響APTw成像結(jié)果的準(zhǔn)確性；第二，場(chǎng)強(qiáng)的要求較高，目前僅適合用于場(chǎng)強(qiáng)3.0 T的MRI機(jī)器；第三，掃描時(shí)間仍相對(duì)較長(zhǎng)。相信隨著技術(shù)的進(jìn)步，這些問(wèn)題都會(huì)得到有效解決。
3 基于影像組學(xué)與人工智能技術(shù)在IP識(shí)別與評(píng)估中的應(yīng)用
影像組學(xué)是近年來(lái)新興的圖像后處理技術(shù)，借助于計(jì)算機(jī)軟件對(duì)醫(yī)學(xué)影像圖像進(jìn)行處理，然后通過(guò)定量分析得出最有價(jià)值的影像組學(xué)特征，進(jìn)而提高疾病診斷準(zhǔn)確率。一些學(xué)者將該技術(shù)應(yīng)用于IP的評(píng)判中。BOUTS等[48]在自發(fā)或重組組織纖溶酶原激活劑（recombinant tissue plasminogen activator, rt-PA）誘導(dǎo)再灌注的栓塞性卒中大鼠模型發(fā)現(xiàn)廣義線性模型（generalized linear model, GLM）在區(qū)分梗死核心與IP組織中的準(zhǔn)確性最高，Dice相似指數(shù)為0.79。KUO等[49]開(kāi)發(fā)了一種基于擴(kuò)散張量成像（diffusion tensor imaging, DTI）衍生指標(biāo)的2-level分類模型，用來(lái)預(yù)測(cè)AIS階段的可搶救組織。結(jié)合平均擴(kuò)散率（mean diffusivity, MD）和相對(duì)腦血流量參數(shù)圖（relative cerebral blood flow maps）可以區(qū)分卒中半球的梗死核心、IP和正常組織區(qū)域。ZHANG等[50]將影像組學(xué)引入急性腦卒中患者的研究，發(fā)現(xiàn)通過(guò)提取ADC圖的最佳影像組學(xué)特征構(gòu)建的影像組學(xué)評(píng)分模型對(duì)AIS患者的IP識(shí)別具有較高的價(jià)值，并在此基礎(chǔ)上進(jìn)一步構(gòu)建了ADC低信號(hào)區(qū)域及周圍大腦區(qū)域的影像組學(xué)模型，發(fā)現(xiàn)基于ADC圖低信號(hào)區(qū)域的影像組學(xué)模型的診斷效能優(yōu)于基于ADC圖病灶周圍區(qū)域的影像組學(xué)模型。因此，影像組學(xué)可通過(guò)提取影像信息成為提供AIS演變的生物標(biāo)志物，并且未來(lái)或能成為判斷IP的一種有效的工具。
4 小結(jié)與展望
總之，在急性腦梗死患者IP的評(píng)估中，MRI不匹配模型分別從結(jié)構(gòu)、血流動(dòng)力學(xué)變化、側(cè)支循環(huán)建立及代謝等方面有效的識(shí)別IP這一治療靶點(diǎn)，為臨床干預(yù)提供了有效的影像學(xué)證據(jù)支持，特別是基于圖像大數(shù)據(jù)的影像組學(xué)和人工智能算法的引入，提高了IP識(shí)別和評(píng)估的準(zhǔn)確性。相信隨著MRI技術(shù)的革新以及研究的深入，MRI對(duì)IP的評(píng)估將會(huì)越來(lái)越精準(zhǔn)，越來(lái)越多的卒中患者會(huì)因此而受益。
本文引用格式：
王燕停, 于昊. MRI識(shí)別和評(píng)估急性腦梗死缺血半暗帶的研究進(jìn)展[J]. 磁共振成像, 2023, 14(1): 161-165.
Cite this article as:
WANG Y T, YU H. Research progress of magnetic resonance imaging in the identification and evaluation of ischemic penumbra in acute cerebral infarction[J]. Chin J Magn Reson Imaging, 2023, 14(1): 161-165.
ACKNOWLEDGMENTS
National Natural Science Foundation of China (No. 82001805); Doctoral Research Foundation of Affiliated Hospital of Jining Medical Universitiy (No. 2018-BS-010).
利益沖突
作者利益沖突聲明：
全體作者均聲明無(wú)利益沖突。
參考文獻(xiàn)References
[1]
HOLLISTM, MORGANL, CABATBATR, et al.
Acute Stroke Management: Overview and Recent Updates[J].
Aging Dis,
2021,
12(
4):
1000-
1009.
DOI: 10.14336/AD.2021.0311.
[2]
GUH, YANGX, WANGC, et al.
Clinical Characteristics, Management, and In-Hospital Outcomes in Patients With Stroke or Transient Ischemic Attack in China[J/OL].
JAMA Netw Open,
2021,
4(
8):
e2120745 [
2022-05-10].
https://pubmed.ncbi.nlm./34387677/.
DOI: 10.1001/jamanetworkopen.2021.20745.
[3]
ASTRUPJ, SIESJOB K, SYMONL.
Thresholds in cerebral ischemia-the ischemic penumbra[J].
Stroke,
1981,
12(
6):
723-
725.
DOI: 10.1161/01.str.12.6.723.
[4]
黨超, 盧潔, 宋海慶, 等.
急性腦梗死缺血半暗帶臨床評(píng)估和治療中國(guó)專家共識(shí)[J].
中國(guó)神經(jīng)精神疾病雜志,
2021,
47(
6):
324-
335.
DOI: 10.3969/j.issn.1002-0152.2021.06.002.
DANGC, LUJ, SONGH Q, et al. Chinese expert consensus on clinical evaluation and treatment of ischemic penumbra of acute cerebral infarction[J]. Chin J Nerv Ment Dis, 2021, 47(6): 324-335. DOI: 10.3969/j.issn.1002-0152.2021.06.002.
[5]
YANGS, LIUR.
Four Decades of Ischemic Penumbra and Its Implication for Ischemic Stroke[J].
Transl Stroke Res,
2021,
12(
6):
937-
945.
DOI: 10.1007/s12975-021-00916-2.
[6]
BENZAKOUNJ, DESLYSM A, LegrandL, et al.
Synthetic FLAIR as a Substitute for FLAIR Sequence in Acute Ischemic Stroke[J].
Radiology,
2022,
303(
1):
153-
159.
DOI: 10.1148/radiol.211394.
[7]
CHENGB, PINNSCHMIDTH, K?NIGSBERGA, et al.
Estimating nocturnal stroke onset times by magnetic resonance imaging in the WAKE-UP trial[J].
Int J Stroke,
2022,
17(
3):
323-
330.
DOI: 10.1177/17474930211059608.
[8]
CAOS, DONGH.
Predictive value of DWI-FLAIR Mismatch in patients with Ischemic Stroke and receiving Endovascular treatment beyond Time Window[J].
Pak J Med Sci,
2021,
37(
2):
466-
471.
DOI: 10.12669/pjms.37.2.3293.
[9]
BERGEE, WHITELEYW, AUDEBERTH, et al.
European Stroke Organisation (ESO) guidelines on intravenous thrombolysis for acute ischaemic stroke[J/OL].
Eur Stroke J,
2021,
6(
1):
I-
LXII [
2022-05-10].
https:///10.1177/2396987321989865.
DOI: 10.1177/2396987321989865.
[10]
REGENHARDTR W, BRETZNERM, ZANONZ M, et al.
Radiomic signature of DWI-FLAIR mismatch in large vessel occlusion stroke[J].
J Neuroimaging,
2022,
32(
1):
63-
67.
DOI: 10.1111/jon.12928.
[11]
ZENGL, CHENJ, LIAOH, et al.
Fluid-Attenuated Inversion Recovery Vascular Hyperintensity in Cerebrovascular Disease: A Review for Radiologists and Clinicians[J/OL].
Front Aging Neurosci,
2021,
13:
790626 [
2022-05-10].
https:///10.3389/fnagi.2021.790626.
DOI: 10.3389/fnagi.2021.790626.
[12]
LEEK Y, KIMJ W, PARKM, et al.
Interpretation of fluid-attenuated inversion recovery vascular hyperintensity in stroke[J].
J Neuroradiol,
2022,
49(
3):
258-
266.
DOI: 10.1016/j.neurad.2021.01.009.
[13]
LEGRANDL, TISSERANDM, TURCG, et al.
Do FLAIR Vascular Hyperintensities beyond the DWI Lesion Represent the Ischemic Penumbra?[J].
AJNR Am J Neuroradiol,
2015,
36(
2):
269-
274.
DOI: 10.3174/ajnr.A4088.
[14]
LEGRANDL, TURCG, EDJLALIM, et al.
Benefit from revascularization after thrombectomy according to FLAIR vascular hyperintensities-DWI mismatch[J].
Eur Radiol,
2019,
29(
10):
5567-
5576.
DOI: 10.1007/s00330-019-06094-y.
[15]
WANGY, ZHOUZ, DINGS.
FLAIR vascular hyperintensity-DWI mismatch most likely to benefit from recanalization and good outcome after stroke[J/OL].
Medicine,
2020,
99(
2):
e18665 [
2022-05-10].
https:///10.1097/MD.0000000000018665.
DOI: 10.1097/MD.0000000000018665.
[16]
LANSBERGM G, THIJSV N, BAMMERR, et al.
The MRA-DWI mismatch identifies patients with stroke who are likely to benefit from reperfusion[J].
Stroke,
2008,
39(
9):
2491-
2496.
DOI: 10.1161/STROKEAHA.107.508572.
[17]
DEGUCHII, DEMBOT, YOSHIMURAS, et al.
Relationship between magnetic resonance angiography-diffusion-weighted imaging mismatch and clinical outcome in endovascular treatment for acute ischemic stroke: subgroup analysis of the Recovery by Endovascular Salvage for Cerebral Ultra-acute Embolism--Japan Registry[J].
J Stroke Cerebrovasc Dis,
2014,
23(
6):
1471-
1476.
DOI: 10.1016/j.jstrokecerebrovasdis.2013.12.053.
[18]
付志勇, 王正則, 孫曉紅.
磁共振血管成像-擴(kuò)散加權(quán)成像不匹配預(yù)測(cè)基底動(dòng)脈閉塞型急性后循環(huán)腦梗死缺血半暗帶的價(jià)值[J].
中國(guó)腦血管病雜志,
2019,
16(
11):
587-
592.
DOI: 10.3969/j.issn.1672-5921.2019.11.005.
FUZ Y, WANGZ Z, SUNX H. The value of magnetic resonance angiography diffusion weighted imaging mismatch in predicting ischemic penumbra of acute posterior circulation cerebral infarction with basilar artery occlusion[J] Chin J Cerebrovasc Dis, 2019, 16 (11): 587-592. DOI: 10.3969/j.issn.1672-5921.2019.11.005.
[19]
ALBERSG W, MARKSM P, KEMPS, et al.
Thrombectomy for Stroke at 6 to 16 Hours with Selection by Perfusion Imaging[J].
N Engl J Med,
2018,
378(
8):
708-
718.
DOI: 10.1056/NEJMoa1713973.
[20]
CHEUNGJ, DOERRM, HUR, et al.
Refined Ischemic Penumbra Imaging with Tissue pH and Diffusion Kurtosis Magnetic Resonance Imaging[J].
Transl Stroke Res,
2021,
12(
5):
742-
753.
DOI: 10.1007/s12975-020-00868-z.
[21]
KIDWELLC S, WINTERMARKM, DE SILVAD A, et al.
Multiparametric MRI and CT models of infarct core and favorable penumbral imaging patterns in acute ischemic stroke[J].
Stroke,
2013,
44(
1):
73-
79.
DOI: 10.1161/STROKEAHA.112.670034.
[22]
FALK DELGADOA, VAN WESTEND, NILSSONM, et al.
Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging—a comprehensive overview[J/OL].
Insights Imaging,
2019,
10(
1):
84 [
2022-05-10].
https:///10.1186/s13244-019-0771-1.
DOI: 10.1186/s13244-019-0771-1.
[23]
CHAZOTA, BARRATJ, GAHAM, et al.
Brain MRIs make up the bulk of the gadolinium footprint in medical imaging[J].
J Neuroradiol,
2020,
47(
4):
259-
265.
DOI: 10.1016/j.neurad.2020.03.004.
[24]
QUY, KONGD, WENH, et al.
Perfusion measurement in brain gliomas using velocity-selective arterial spin labeling: comparison with pseudo-continuous arterial spin labeling and dynamic susceptibility contrast MRI[J].
Eur Radiol,
2022,
32(
5):
2976-
2987.
DOI: 10.1007/s00330-021-08406-7.
[25]
GOPINATHG, ASLAMM, ANUSHAP.
Role of Magnetic Resonance Perfusion Imaging in Acute Stroke: Arterial Spin Labeling Versus Dynamic Susceptibility Contrast-Enhanced Perfusion[J/OL].
Cureus,
2022,
14(
3) :
e23625 [
2022-05-10].
https:///10.7759/cureus.23625.
DOI: 10.7759/cureus.23625.
[26]
LIUJ, LINC, MINUTIA, et al.
Arterial spin labeling compared to dynamic susceptibility contrast MR perfusion imaging for assessment of ischemic penumbra: A systematic review[J].
J Neuroimaging,
2021,
31(
6):
1067-
1076.
DOI: 10.1111/jon.12913.
[27]
NIIBOT, OHTAH, YONENAGAK, et al.
Arterial spin-labeled perfusion imaging to predict mismatch in acute ischemic stroke[J].
Stroke,
2013,
44(
9):
2601-
2603.
DOI: 10.1161/strokeaha.113.002097.
[28]
KOHNON, OKADAK, YAMAGATAS, et al.
Distinctive Patterns of Three-Dimensional Arterial Spin-Labeled Perfusion Magnetic Resonance Imaging in Subtypes of Acute Ischemic Stroke[J].
J Stroke Cerebrovasc Dis,
2016,
25(
7):
1807-
1812.
DOI: 10.1016/j.jstrokecerebrovasdis.2016.03.035.
[29]
侯聰, 侯?yuàn)檴?/span>, 張俊, 等.
動(dòng)脈自旋標(biāo)記技術(shù)在急性腦梗死中的應(yīng)用進(jìn)展[J].
分子影像學(xué)雜志,
2020,
43(
4):
563-
567.
DOI: 10.12122/j.issn.1674-4500.2020.04.02.
HOUC, HOUS S, ZHANGJ, et al. Application progress of arterial spin labeling technique in acute cerebral infarction[J]. J Molecular Imaging, 2020, 43(4): 563-567. DOI: 10.12122/j.issn.1674-4500.2020.04.02.
[30]
胡現(xiàn)寧, 袁濤, 劉武杰, 等.
急性缺血性卒中突出靜脈征影響因素的研究現(xiàn)狀[J].
國(guó)際醫(yī)學(xué)放射學(xué)雜志,
2021,
44(
2):
152-
156.
DOI: 10.19300/j.2021.Z18105.
HUX N, YUANT, LIUW J, et al. Factors influencing prominent venous sign in acute ischemic stroke: current study status[J]. Int J Med Radiol, 2021, 44(2): 152-156. DOI: 10.19300/j.2021.Z18105.
[31]
LIZ, BAIX, GAOP, et al.
Changes of prominent vessel sign and susceptibility vessel sign in acute ischemic stroke patients with and without successful recanalization: a study based on susceptibility weighted images[J].
Neurol Res,
2022,
44(
7):
583-
590.
DOI: 10.1080/01616412.2021.2024729.
[32]
XUZ, TONGZ, DUANY, et al.
Diffusion- and Susceptibility Weighted Imaging Mismatch Correlates With Collateral Circulation and Prognosis After Middle Cerebral Artery M1-Segment Occlusion[J/OL].
Front Neurol,
2021,
12:
660529 [
2022-05-10].
https:///10.3389/fneur.2021.660529.
DOI: 10.3389/fneur.2021.660529.
[33]
JIANGH F, ZHANGY X, PANGJ X, et al.
Susceptibility-diffusion mismatch correlated with leptomeningeal collateralization in large vessel occlusion stroke[J/OL].
J Int Med Res,
2021,
49(
5):
3000605211013179 [
2022-05-10].
https:///10.1177/03000605211013179.
DOI: 10.1177/03000605211013179.
[34]
WANGY, LIZ, HUANGW, et al.
The Value of Susceptibility-Weighted Imaging (SWI) in Evaluating the Ischemic Penumbra of Patients with Acute Cerebral Ischemic Stroke[J].
Neuropsychiatr Dis Treat,
2021,
17:
1745-
1750.
DOI: 10.2147/NDT.S301870.
[35]
LUX, MENGL, ZHOUY, et al.
Quantitative susceptibility-weighted imaging may be an accurate method for determining stroke hypoperfusion and hypoxia of penumbra[J].
Eur Radiol,
2021,
31(
8):
6323-
6333.
DOI: 10.1007/s00330-020-07485-2.
[36]
JIANGH F, ZHANGY Q, PANGJ X, et al.
Factors associated with prominent vessel sign on susceptibility-weighted imaging in acute ischemic stroke[J/OL].
Sci Rep,
2021,
11(
1):
5641 [
2022-05-10].
https:///10.1038/s41598-021-84269-8.
DOI: 10.1038/s41598-021-84269-8.
[37]
ZOLLNERJ P, HATTINGENE, SINGERO C, et al.
Changes of pH and energy state in subacute human ischemia assessed by multinuclear magnetic resonance spectroscopy[J].
Stroke,
2015,
46(
2):
441-
446.
DOI: 10.1161/STROKEAHA.114.007896.
[38]
LIY, WANGT, ZHANGT, et al.
Fast high-resolution metabolic imaging of acute stroke with 3D magnetic resonance spectroscopy[J].
Brain,
2020,
143(
11):
3225-
3233.
DOI: 10.1093/brain/awaa264.
[39]
DEUCHARG A, BRENNAND, HOLMESW M, et al.
Perfluorocarbon Enhanced Glasgow Oxygen Level Dependent (GOLD) Magnetic Resonance Metabolic Imaging Identifies the Penumbra Following Acute Ischemic Stroke[J].
Theranostics,
2018,
8(
6):
1706-
1722.
DOI: 10.7150/thno.21685.
[40]
HUY, WUJ, ZHANGX, et al.
Effects of Paired Associative Stimulation on Metabolites in Ischemia Stroke Rats Model as Studied by Nuclear Magnetic Resonance Spectrum[J].
Neurochem Res,
2021,
46(
9):
2495-
2504.
DOI: 10.1007/s11064-021-03388-w.
[41]
ZHOUJ, PAYENJ F, WILSOND A, et al.
Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI[J].
Nat Med,
2003,
9(
8):
1085-
1090.
DOI: 10.1038/nm907.
[42]
SUNP Z, ZHOUJ, SUNW, et al.
Detection of the ischemic penumbra using pH-weighted MRI[J].
J Cereb Blood Flow Metab,
2007,
27(
6):
1129-
1136.
DOI: 10.1038/sj.jcbfm.9600424.
[43]
WANGE, WUY, CHEUNGJ S, et al.
Mapping tissue pH in an experimental model of acute stroke-Determination of graded regional tissue pH changes with non-invasive quantitative amide proton transfer MRI[J].
NeuroImage,
2019,
191:
610-
617.
DOI: 10.1016/j.neuroimage.2019.02.022.
[44]
TIETZEA, BLICHERJ, MIKKELSENI K, et al.
Assessment of ischemic penumbra in patients with hyperacute stroke using amide proton transfer (APT) chemical exchange saturation transfer (CEST) MRI[J].
NMR Biomed,
2014,
27(
2):
163-
174.
DOI: 10.1002/nbm.3048.
[45]
HARSTONG W, TEEY K, BLOCKLEYN, et al.
Identifying the ischaemic penumbra using pH-weighted magnetic resonance imaging[J].
Brain,
2015,
138(
1):
36-
42.
DOI: 10.1093/brain/awu374.
[46]
譚月發(fā).
旋轉(zhuǎn)坐標(biāo)系下時(shí)間常數(shù)(T1ρ)和表觀擴(kuò)散系數(shù)(ADC)在評(píng)估缺血性腦卒中演變進(jìn)程中的對(duì)比應(yīng)用&酰胺質(zhì)子轉(zhuǎn)移成像(APT)和動(dòng)脈自旋標(biāo)記(ASL)聯(lián)合評(píng)價(jià)亞急性腦梗中缺血半暗帶的初步研究[D].
廣州:
南方醫(yī)科大學(xué),
2018,
9:
1-
119.
TANY F. Use of rotating frame (Tlp) and apparent diffusion coefficient (ADC) obtained from MRI with T1 relaxation time to estimate cerebralischemia evolution & preliminary research of ischemic penumbra insubacute stroke patients combinatinguse of amide proton transfer (APT) with arterial spin-labeling (ASL)[D]. Guangzhou: South Med Univ, 2018, 9: 1-119.
[47]
JINT, KIMS G.
Role of chemical exchange on the relayed nuclear Overhauser enhancement signal in saturation transfer MRI[J].
Magn Reson Med,
2022,
87(
1):
365-
376.
DOI: 10.1002/mrm.28961.
[48]
BOUTSM J, TIEBOSCHI A, VAN DER TOORNA, et al.
Early identification of potentially salvageable tissue with MRI-based predictive algorithms after experimental ischemic stroke[J].
J Cereb Blood Flow Metab,
2013,
33(
7):
1075-
1082.
DOI: 10.1038/jcbfm.2013.51.
[49]
KUOD P, KUOP C, CHENY C, et al.
Machine learning-based segmentation of ischemic penumbra by using diffusion tensor metrics in a rat model[J/OL].
J Biomed Sci,
2020,
27(
1):
80 [
2022-10-11].
https://pubmed.ncbi.nlm./32664906/.
DOI: 10.1186/s12929-020-00672-9.
[50]
ZHANGR, ZHUL, ZHUZ, et al.
Apparent diffusion coefficient map based radiomics model in identifying the ischemic penumbra in acute ischemic stroke[J].
Ann Palliat Med,
2020,
9(
5):
2684-
2692.
DOI: 10.21037/apm-20-1142.
|
|
|
