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肥厚型脉络膜谱系疾病的广角眼底影像研究进展

Advances in wide-field fundus imaging for pachychoroid disease

来源期刊: 眼科学报 | 2025年2月 第40卷 第2期 179-188 发布时间:2025-2-28 收稿时间:2025/2/13 15:07:38 阅读量:324
作者:
关键词:
肥厚型脉络膜谱系疾病中心性浆液性脉络膜视网膜病变广角眼底影像多模式影像人工智能
pachychoroid disease central serous chorioretinopathy wide-field fundus imaging multimodal imaging artificial intelligence
DOI:
10.12419/24103101
收稿时间:
2024-10-30 
修订日期:
2024-11-27 
接收日期:
2024-12-05 
肥厚型脉络膜谱系疾病(pachychoroid disease, PCD)是一组以病理性脉络膜增厚为共同特征的疾病谱系。其特征性改变包括Haller层脉络膜血管扩张,脉络膜毛细血管层和Sattler层变薄,以及肥厚血管(pachyvessels)上视网膜色素上皮(retinal pigment epithelium, RPE)的异常。PCD主要包括单纯肥厚型脉络膜病变(uncomplicated pachychoroid, UCP)、肥厚型脉络膜色素上皮病变(pachychoroid pigment epitheliopathy, PPE)、中心性浆液性脉络膜视网膜病变(central serous chorioretinopathy, CSC)、肥厚型脉络膜新生血管病变(pachychoroid neovasculopathy, PNV)和息肉状脉络膜血管病变(polypoidal choroidal vasculopathy, PCV)。传统眼底检查因单张成像局限于后极部,难以全面评估病变范围。广角影像技术突破了这一局限,其成像范围覆盖后极部至赤道部涡静脉壶腹部(约60°~100°),而超广角成像更可达后极部至锯齿缘(约 110°~220°)。这一技术的进步不仅扩大了PCD眼底病灶的观察范围,更提升了对脉络膜结构和功能的评估能力,为深化研究PCD的发病机制提供了新的视角。近年来,基于深度学习的人工智能技术在PCD辅助诊断方面取得重要突破,展现出优异的PCD相关疾病识别和分类能力,有助于显著提升基层医疗机构诊断效率,并推动医疗资源优化配置。文章综述了广角眼底影像技术在PCD评估与诊断中的研究进展,旨在为眼科临床工作者和研究者提供最新的技术应用视角,并为进一步探索PCD的病理机制和诊疗方法奠定科学基础。
Pachychoroid disease (PCD) represents a group of disorders characterized by pathological choroidal thickening. The characteristic changes include dilated choroidal vessels in Haller's layer, thinning of the choriocapillaris and Sattler's layer, and retinal pigment epithelium (RPE) abnormalities overlying the pachyvessels. The PCD primarily encompasses uncomplicated pachychoroid (UCP), pachychoroid pigment epitheliopathy (PPE), central serous chorioretinopathy (CSC), pachychoroid neovasculopathy (PNV), and polypoidal choroidal vasculopathy (PCV). Traditional fundus examination is limited to the posterior pole in single-frame imaging, making it challenging to comprehensively evaluate the extent of lesions. Wide-field imaging technology has overcome this limitation, with its imaging range covering from the posterior pole to the ampulla of vortex veins at the equator (approximately 60-100°), while ultra-wide-field imaging can extend from the posterior pole to the pars plana (approximately 110-220°). This technological advancement has not only expanded the observation range of PCD fundus lesions but also enhanced the assessment capabilities of choroidal structure and function, providing new perspectives for investigating PCD pathogenesis. In recent years, deep learning-based artificial intelligence technology has achieved significant breakthroughs in PCD-assisted diagnosis, demonstrating excellent capability in identifying and classifying PCD-related diseases. This has contributed to significantly improving diagnostic efficiency in primary healthcare institutions and optimizing medical resource allocation. This review summarizes the advances in wide-field fundus imaging technologies for the assessment and diagnosis of PCD.

文章亮点

1. 关键发现

 • 肥厚型脉络膜谱系疾病 (pachychoroid disease, PCD) 患眼常存在优势脉络膜静脉 (choroidal vein, ChV),且视网膜色素上皮(retinal pigment epithelium, RPE) 渗漏主要发生在优势 ChV 所在象限。
 • 广角眼底成像范围覆盖后极部至赤道部涡静脉壶腹部 ( 约 60°~100°),超广角成像可达后极部至锯齿缘 ( 约110°~220°)。
 • 基于深度学习的人工智能模型对 PCD 疾病的识别和分类准确率超过 90%。

2. 已知与发现

 • PCD 是以病理性脉络膜增厚为共同特征的疾病谱系。表现为 Haller 层脉络膜血管扩张,脉络膜毛细血管层和 Sattler 层变薄,以及肥厚血管 (pachyvessels) 上的 RPE 异常。
 • 传统眼底检查单张成像局限于后极部,难以全面评估病变范围。广角成像技术显著扩大 PCD 的观察范围,可实现对周边病变的较全面评估。

3. 意义与改变

 • 广角眼底影像扩大了 PCD 眼底病灶的观察范围,提升了对脉络膜结构和功能的评估能力,为 PCD 发病机制的研究提供了新的研究方法和视角。
 • 人工智能辅助诊断 PCD 有助于显著提升基层医疗机构诊断效率,可推动医疗资源优化配置。

       自2012年光学相干断层扫描(optical coherence tomography, OCT)技术实现脉络膜成像以来,研究者们逐渐认识到了一类以脉络膜增厚为共同特征的脉络膜疾病——肥厚型脉络膜谱系疾病(pachychoroid disease, PCD/ pachychoroid spectrum disease)。这一谱系疾病的特点包括Haller层脉络膜血管扩张,脉络膜毛细血管层和Sattler层变薄,以及肥厚血管(pachyvessels)上视网膜色素上皮(retinal pigment epithelium, RPE)的异常[1–4]。Warrow等[1]学者将具有上述特征的疾病定义为PCD。
       近年来,随着广角眼底影像技术的发展,我们能够较精准观察脉络膜的结构和功能状态。本综述旨在总结多种广角眼底影像技术在PCD研究中的最新进展,包括广角OCT(wide-field optical coherence tomography, WF-OCT)、广角荧光素眼底血管造影(widefield fundus fluorescein angiography, WF-FFA)、广角吲哚菁绿血管造影(wide-field indocyanine green angiography, WF-ICGA)、广角光学相干断层扫描血管成像(wide-field optical coherence tomography angiography, WF-OCTA)、广角眼底彩照(wide-field color fundus photograph, WF-CFP)和广角眼底自发荧光(wide-field fundus autofluorescence, WF-FAF)。

1 肥厚型脉络膜谱系疾病概述

        PCD包括中心性浆液性脉络膜视网膜病变(central serous chorioretinopathy, CSC)、肥厚型脉络膜色素上皮病变(pachychoroid pigment epitheliopathy, PPE)[1]、肥厚型脉络膜新生血管病变(pachychoroid neovasculopathy, PNV)[2]、息肉状脉络膜血管病变(polypoidal choroidal vasculopathy, PCV)[3]和视盘周围肥厚型脉络膜综合征(peripapillary pachychoroid syndrome, PPS)[4]。Cheung等[5]在2019年进一步描述了这类疾病的共性,包括脉络膜的病理性增厚、RPE损害、脉络膜毛细血管萎缩、Haller层血管扩张、脉络膜血管高通透性(choroidal vascular hyperpermeability, CVH)。值得注意的是,他们也将具有类似肥厚型脉络膜血管改变的局灶脉络膜凹陷(focal choroidal excavation, FCE)纳入PCD之中。然而,Siedlecki等[6]认为,将FCE及PPS归入肥厚脉络膜谱系疾病的证据尚不充分,并将单纯肥厚型脉络膜病变(uncomplicated pachychoroid, UCP)作为PCD一员。因此,目前PCD主要包括UCP、PPE、CSC、PNV和PCV。

2 广角眼底影像概述

       眼底疾病的识别和研究进展与眼底影像技术的发展紧密相连。技术从最初的窄角和传统角度成像发展到广角(wide angle)/宽视场(wide field, WF)和超广角(ultrawide angle)/超宽视场(ultra-wide field, UWF)成像。传统的眼底彩照技术主要关注后极部(包括视盘、黄斑区和血管弓),对于中周部及远周部的眼底成像能力有限[7]。例如,直接检眼镜成像角度约10°~15°,20 D间接检眼镜成像角度约37°。传统眼底彩照和血管造影成像角度为30°~55°,标准的7视野眼底彩照约75°。随着影像技术的不断进展,成像角度也不断扩大,目前眼底检查已实现WF及UWF成像。2019年国际广角成像研究组(International Widefield Imaging Study Group)对广角影像进行分类和指南制定,明确指出WF成像范围为后极部至赤道部涡静脉壶腹部(约60°~100°),而UWF成像覆盖后极部至锯齿缘的整个眼底范围(约110°~220°)[8]

3 广角眼底影像在肥厚型脉络膜谱系疾病的应用

3.1 WF-OCT

        OCT凭借其无创、快速、可重复和高分辨率等优势,已成为PCD患者诊断与随访的可靠影像学检查方法,在临床实践中发挥着重要作用。随着眼科影像技术的不断进步,从频域OCT(swept-domain optical coherence tomography, SD-OCT)到增强深度成像(enhanced depth imaging, EDI)技术,再到扫频OCT(swept-source optical coherence tomography, SS-OCT)和WF-OCT的出现,使我们能够以更高分辨率、更深穿透力观察包括脉络膜-巩膜界面在内的深层组织结构[9–11]
       CSC是最早被发现且最具代表性的PCD[12-13]。其典型表现为黄斑区的浆液性视网膜神经上皮层脱离(serous retinal detachment, SRD),伴有局灶或多灶性RPE异常,伴或不伴浆液性视网膜色素上皮脱离(pigment epithelial detachment, PED)。通过OCT扫描急性CSC的视网膜下液(subretinal fluid, SRF)区域,可发现与荧光素眼底血管造影(fundus fluorescein angiography, FFA)的渗漏点高度对应的RPE微撕裂。在伴有纤维蛋白渗出的病例中,RPE微撕裂上方可见特征性的“空泡征”(vacuole sign)[14-15],表现为RPE微撕裂上方低反射率,提示液体持续渗出。这一征象是判断疾病活动性的重要标志,尤其在无法进行FFA时有重要指导意义。CSC中PED的发病率为9%~100%[16-17]。急性CSC中的PED多表现为内含浆液成分的RPE圆顶状隆起,可自行消退;而慢性CSC中的PED多呈扁平不规则PED(flat irregular pigment epithelial detachment, FIPED)[18]。本团队研究发现与非血管性FIPED相比,血管性FIPED宽度显著更宽,FIPED区域具有显著更多的RPE聚集、最大RPE厚度显著增加[19]。其中,RPE聚集与慢性CSC中的血管性FIPED密切相关。
       PPE被认为是CSC的一种前体状态[1]。其典型表现为RPE色素异常,伴随脉络膜病理性增厚、脉络膜中大血管扩张、脉络膜毛细血管变薄,但不伴SRD即无SRF。UCP的典型表现包括脉络膜病理性增厚、脉络膜血管扩张、脉络膜毛细血管变薄,无RPE色素脱失及SRF[20]。PNV典型表现为肥厚型脉络膜血管上方的RPE与Bruch膜扁平不规则脱离并内含1型脉络膜新生血管(choroidal neovascularization, CNV)成分[2]。PNV被认为可能是PPE和慢性CSC的长期并发症,可以发展成脉络膜动脉瘤样扩张,即PCV[21]
       PCD最显著的特征是脉络膜的病理性增厚。临床上通常以中心凹下脉络膜厚度(subfoveal choroidal thickness, SFCT)≥300 μm或中心凹外脉络膜厚度较SFCT增厚超过50 μm作为诊断标准[5, 20]。近期研究表明,CSC 患眼在WF-OCT范围内的各象限脉络膜厚度均大于对侧眼和健康眼的脉络膜厚度[11, 22-23]。然而,由于正常人脉络膜厚度受年龄、解剖位置、昼夜节律及生活习惯等多种因素影响[24],且PCD患眼脉络膜增厚主要源于Haller层血管扩张,因此不应将脉络膜厚度作为诊断的唯一依据。值得注意的是,近期多项采用前节OCT的研究发现CSC患眼存在巩膜增厚现象[25–27],这一发现提示眼部解剖因素可能参与CSC的发病机制。有关巩膜在PCD发病过程中的作用,仍需更多广角多模式影像研究予以阐明。
       脉络膜空洞(choroidal caverns)在慢性CSC的发病率明显高于其他脉络膜视网膜疾病[28],可见于52%的PCD患眼[29]。在OCT图像上,其特征性表现为脉络膜内的低反射腔,无高反射边界,腔内伴点状或线状高反射后伴高穿透尾影[30]。研究表明,脉络膜空洞的形成可能与血管退行性改变[29]或脂质代谢异常有关[31],其存在往往提示脉络膜高灌注和RPE萎缩[28]。WF-OCT有助于观察PCD患眼周边部的脉络膜空洞,为深入研究其发病机制提供了新的途径。
       PPS患眼的典型特征包括视盘周围区域的脉络膜增厚,常伴随脉络膜皱褶、较短的眼轴长度(<23 mm)和远视[4]。这些患眼可出现视盘水肿和充血、视网膜内或视网膜下积液,以及RPE、椭圆体带和外界膜的萎缩性改变。尽管PPS患眼表现出PCD的典型特征之一——病理性脉络膜增厚,但其与PCD疾病谱系的确切关系仍需深入研究[6]。WF-OCT能同时显示视盘和黄斑区域的特点为探索两者关系提供了重要帮助。
       WF-OCT凭借其快速、广角成像的优势,能在单次扫描中获取大范围的视网膜和脉络膜信息,避免了传统多张图像拼接的繁琐过程。这项技术不仅显著提升了检查效率,还能全面评估PCD患者的病变特征,包括广泛区域的脉络膜厚度变化和视网膜层次结构改变。特别是其同时显示视盘和黄斑的能力,有助于全面评估病灶范围和演变过程。在疾病随访中,这种广角成像技术具有独特优势,可以更好地揭示UCP、PPE、CSC、PNV、PCV等PCD谱系疾病之间的演变关系。此外,WF-OCT作为重要的检查手段,将有助于深入研究PPS的疾病特征及其在PCD谱系中的定位。

3.2 WF-FFA

       急性CSC的FFA特征是炊烟状或墨迹状RPE渗漏。慢性CSC的典型表现为多灶性RPE损害,FFA呈多灶性RPE渗漏及色素脱失,并可继发CNV。在迁延不愈、新旧病灶同时出现的患者中呈现不典型表现[32],包括多灶性RPE渗漏,有时渗漏点并不明显,可伴有色素增生引起的遮蔽荧光。PCD患眼长期存在的SRD可因重力作用形成特征性的重力引流通道(descending tracts),在WF-FFA上表现为明显的RPE带状萎缩伴色素增殖。
       尽管WF-FFA在全局观察PCD方面具有优势,微小病灶的精细观察仍需结合常规小视角成像。这种组合策略虽增加了工作量,但能提供更准确的诊断依据,有助于制定更合理的治疗方案。将广角成像与传统成像方式相结合,可充分发挥各自优势,为PCD的诊断和治疗提供更全面的影像学信息。

3.3 WF-ICGA

       ICGA作为PCD诊断的金标准,在疾病的诊疗中至关重要。与传统55°视野的ICGA相比,WF-ICGA单张图像的拍摄范围可达102°。通过9个方位的图像采集,几乎可以完整覆盖整个眼底脉络膜,为疾病诊断提供更全面的信息。超广角ICGA(ultra-widefield indocyanine green angiography, UWF-ICGA)能够清晰显示CSC患眼的整个脉络膜涡静脉系统[33]
       随着多模式影像的发展,特别是WF-ICGA的应用,越来越多基于影像的证据表明PCD患眼中脉络膜血管存在异常[34-35]。Spaide等[36]观察到CSC患眼中ChV呈现出肠样和球样的管径变化,表明PCD患眼存在脉络膜血管形态改变。近期的研究进一步揭示了PCD患眼中不对称ChV扩张和ChV吻合现象,为脉络膜静脉重塑提供了有力的证据[37–40]。在其受累区域,涡静脉表现为血管扩张和通透性增加,这些改变延伸至扩张的壶腹部[35, 41]。后极部脉络膜静脉的扩张实际反映了涡静脉眼内段的扩张,而壶腹部扩张则提示涡静脉瘀滞,可能与巩膜通道处的阻力增加有关。
       本团队借助WF-ICGA对CVH区域的脉络膜静脉变化模式进行了系统评估[42],包括形态变化(梭样、球样和肠样ChV)、结构变化(ChV汇合和吻合)以及不对称ChV(优势和非优势ChV,图1)。在所观察的CVH区域中,形态变化的梭样ChV占35.8%,球样ChV占35.1%,肠样ChV占29.1%;结构变化的ChV汇合和吻合分别占所有ChV变化的21.2%和11.9%。随着疾病从PPE进展至CSC再到PNV,梭状ChV的比例逐渐降低,而肠状ChV、ChV汇合和吻合的比例则呈上升趋势。值得注意的是,该研究中观察到的ChV吻合发生率(11.9%)低于既往研究报道,这种差异主要源于两个方面:首先,通过ICGA早期动态图像的细致观察,可避免将重叠的ChV末梢误判为ChV吻合;其次,既往研究多采用小范围(如6 mm×6 mm)OCTA进行观察,易将跨越水平分水带的优势ChV误认为ChV吻合。此外,本团队研究首次提出了优势ChV的概念,发现83.8%的PCD患眼存在优势ChV,且69.1%的RPE渗漏发生在优势ChV所在象限。这种现象可能与优势ChV的特殊生理特征有关:优势ChV承担了更多的血液引流任务,在静脉瘀滞和负荷过重时更易发生血管异常;当优势ChV穿过黄斑区时,更容易诱发RPE渗漏,继而导致CSC等病变的发生。这些发现不仅强调了准确识别优势ChV的临床重要性,也提示在评估ChV特征时应尽量避免使用小范围眼底影像技术。同时,临床医生需要特别关注存在优势ChV人群的PCD相关诱发因素,以期实现早期干预和预防。

图 1 正常眼和伴有优势ChV的PCD患眼中脉络膜血管系统示意图
Figure 1 Illustrations of choroidal vasculature in a normal eye and eyes with dominant ChVs in PCD eyes

20250310095137_0860.png
(A、E)正常眼对称ChV:上方和下方ChVs以水平分水带为界对称分布。(B、F)PCD患眼颞侧优势ChV:颞侧ChV的引流路径(黄色箭头)穿过黄斑中心凹。(C、G)PCD患眼鼻侧优势ChV:鼻侧ChV的引流路径(橙色箭头)穿过视盘中央。(D、H)PCD患眼颞侧和鼻侧均有即单眼2条优势ChV:颞侧ChV引流路径(黄色箭头)穿过黄斑中心凹,鼻侧ChV引流路径(橙色箭头)穿过视盘中心。该图来自作者本人已发表的论文[42]
(A, E) Symmetric ChVs in the normal eye: superior and inferior ChVs are symmetrical at the horizontal watershed zone. (B, F) Dominant ChV in the temporal side of the PCD eye: the terminal of the lateral temporal ChV (yellow arrowheads) crosses the macular fovea. (C, G) Dominant ChV in the nasal side of the PCD eye: the terminal of the lateral nasal ChV (orange arrowheads) crosses the disc center. (D, H) Two dominant ChVs in the temporal and nasal sides of the PCD eye: the terminal of the lateral temporal ChV (yellow arrowheads) crosses the macular fovea and the terminal of the lateral nasal ChV (orange arrowheads) crosses the disc center. The figure is from the author's own published paper.[42]
       本团队基于WF-ICGA的PCD涡静脉分布特征的前期研究揭示了一系列重要发现[43]。PCD患眼中后极部涡静脉(posterior vortex vein, PVV)较为罕见,仅占8.9%。在涡静脉的形态学分析中,不完整型涡静脉是最为常见(61.9%),其次依次为完整型(19.5%)、缺失型(11.1%)和完整型伴壶腹(7.5%)。另外,在优势ChV所属的涡静脉中,不完整型涡静脉的比例高达79.9%。此外,这些涡静脉在PCD患眼的各象限的分布有所不同,以颞下象限最多见(26.9%),其次为鼻上象限(26.1%)、颞上象限(24.3%)和鼻下象限(22.7%)。每只PCD患眼的涡静脉中位数为8.0条(范围:5~15条)。
       这些发现不仅为深入理解PCD的发病机制提供了新的视角,同时也彰显了广角ICGA成像技术在评估脉络膜血管异常中的独特优势。然而,鉴于ICGA的有创性质,其临床应用需要严格遵循适应证原则,主要集中在两个关键时间点:首诊时的确诊评估和随访过程中的活动性判断。这种建立在精准医学理念基础上的检查策略,既确保了获取必要的诊断信息,又最大程度地减轻了患者的检查负担,充分体现了现代医学实践中“以最小代价获取最大健康收益”的核心价值理念。

3.4 WF-OCTA

       OCTA作为OCT的技术延伸,通过捕捉血流引起的光信号变化并经专用软件处理,实现了无创血管造影[44]。近年来,OCTA的性能获得显著提升:扫描速度从每秒2万次提升至40万次;轴向分辨率高达2 μm,几乎接近细胞级别[44]。扫描深度从3 mm增加到6 mm甚至12 mm。扫描范围从最初的3 mm×3 mm、6 mm×6 mm扩大到9 mm×9 mm、12 mm×12 mm,最新的WFOCTA甚至可以在单次扫描中覆盖长达26 mm的线(眼底3 mm大约对应10°视野范围)[44]。这些进展使WFOCTA能在单次无散瞳成像中覆盖眼底后极部和中周部,显著提升了其临床应用价值。
       WF-OCTA的另一优势在于能够通过横断面像清晰展现脉络膜大血管的形态。其三维数据集可在任意方位显示二维横断面图像:垂直于视网膜表面的横断面图像即通常所指的OCT图像(B扫描),而平行于视网膜表面的横断面则为en face图像[45]。OCTA的en face图像分为结构型(即通常所指的en face OCTA图像)和血流型(即常规OCTA图像)两类[46-47],分别适用于不同的临床观察需求。
       在PCD研究中,en face OCTA清晰显示了pachyvessels导致的脉络膜血管直径增加[20, 46]。Savastano等[48]研究发现,Haller血管排列在健康眼中多呈颞侧人字形(49.2%),而在CSC患眼中则以网状模式为主(48.8%)。Lee等[49]研究表明,急性和慢性CSC患眼中分别有91.7%和88.2%可观察到脉络膜血管扩张,且呈现出不同的扩张模式:急性期以局灶性为主(81.8%),慢性期则以弥漫性为主(66.6%)。
       Zeng等[50]研究显示,UWF-OCTA的粗颗粒状高反射区与 ICGA中的高通透区具有良好的对应性,有助于实现CSC患者脉络膜血管系统的无创可视化和定量分析。多项研究证实,UWF-OCTA扫描定量显示,CSC患眼的平均CVI显著大于对侧眼和对照眼[10, 51]。且CSC 患眼的脉络膜毛细血管密度在颞上、颞下和鼻下区域均大于对照眼[23]。Luo等[51]应用UWF-OCTA研究发现,CSC患眼所有区域的CVV和CVI均高于健康眼,其中颞上引流系统具有最大的 CVV 和最厚的脉络膜。这些研究展示了更广范围内CSC的脉络膜特征,也突出了脉络膜引流系统的不对称性表现。
       WF-OCTA在脉络膜层次的en face成像能力与ICGA相近,为ICG染料过敏或无明显眼底症状的人群提供了快捷的无创眼底筛查手段,对深入了解脉络膜血管病变具有重要临床价值。

3.5 WF-CFP

       眼底彩照是眼科医生眼底所见的客观记录[52]。急性CSC的典型表现为盘状的视网膜隆起;慢性CSC常表现多样,包括伴有黄白色的纤维蛋白渗出或无纤维蛋白深层的大泡性浆液性脱离[12]或黄斑下方中周部沙漏样的视网膜脱离,甚至这些沙漏样的视网膜脱离区域演变为萎缩灶,可伴有色素脱失及色素增殖。相较于传统30°~55°范围的眼底彩照,WF-CFP可以直观观察到后极部至赤道部涡静脉壶腹部,UWF-CFP一览无遗的观察到覆盖后极部至锯齿缘的整个眼底范围[8]。这种技术进步为临床医生提供了更全面的病变观察视角,大幅提升了诊断效率和准确性。
       在正常眼的UWF-CFP研究中,Funatsu等[53]的研究发现每只眼平均存在8.0条涡静脉壶腹,其分布规律表现为鼻上象限平均2.2条,颞下象限2.1条,鼻下象限2.0条,颞上象限1.8条。这些基础数据为PCD患者涡静脉分布特征的研究奠定了重要基础。近期,本团队基于广角影像技术WF-ICGA进一步探讨了多种PCD疾病中涡静脉的分布特征(详见3.4 WF-ICGA),为PCD的病理机制研究提供了新的视角。

3.6 WF-FAF

       眼底自发荧光(fudus autofluorescence, FAF)是一种无创成像方式,在RPE功能障碍性疾病的诊断中具有重要价值。Pang等[33]应用超广角FAF(ultra-widefield fudus autofluorescence, UWF-FAF)观察发现,超过半数的CSC患眼可见超出传统55°视野范围的重力引流通道。
       UWF-FAF成像不仅能够显示更广泛的周边部视网膜病变,还可以观察到延伸至远周边部的SRF重力引流通道。这些特征性的FAF信号有助于CSC的诊断,而周边异常的强FAF信号可能提示疾病的活动性,需要通过OCT或ICGA进一步评估。
       总的来说,CSC患眼的强FAF区域通常提示SRF积聚和(或)光感受器丢失,而更严重的弱FAF区域则往往与RPE丢失相关。然而,FAF检查不应视为PCD独立的诊断依据,而需要结合临床表现和其他多模式影像检查进行综合分析,以提高诊断的准确性和可靠性。

4 人工智能技术在PCD中的应用

       随着2022年《“十四五”全国眼健康规划》的发布,眼底病防治已上升至国家战略高度。该规划特别强调了AI技术在眼病预防、诊断和随访等方面的重要应用价值。作为人工智能(artificial intelligence, AI)的核心分支,深度学习技术在眼科疾病诊断领域展现出卓越性能。由于眼科诊断高度依赖图像识别,这一特点使其成为深度学习技术应用的理想领域。自2018年8月美国食品药品监督管理局(Food and Drug Administration)批准首个AI辅助糖尿病视网膜病变筛查系统IDx-DR[54]以来,AI在眼科领域的应用呈现蓬勃发展态势。
       在PCD疾病的辅助筛查和诊断方面,深度学习技术已取得多项重要进展。多个研究团队从不同角度开发了针对性的AI解决方案:Zhen等[55]基于传统眼底彩照的影像学特征构建深度学习模型,成功实现了CSC与非CSC疾病的区分。Han等[56]基于OCT的影像学特征构建深度学习模型,在nAMD和CSC的分类中取得99.7%的高准确率,在视网膜病变类型分类方面也达到了91.1%的优异表现。Chen等[57]开发出能够评估FFA图像中CSC渗漏点的深度学习模型。最近,Chen等[58]实现了基于AI的FFA图像自动解析和交互式问答功能。
       Kim等[59]的研究表明,基于自动机器学习平台开发的深度学习模型,已能够应用UWF-ICGA准确识别PCD与非PCD疾病,为相关疾病的早期筛查和精准诊断开辟了新途径。
       尽管AI在眼科领域展现出广阔前景,但仍面临着若干重要挑战。首先,许多与眼底影像结合的AI模型尚未在大规模外部实际数据集中得到充分验证,其诊断准确性有待系统评估。其次,相关的伦理问题、法律法规以及医疗收费标准等配套政策仍需进一步完善[52, 60]

5 总结与展望

       随着医学影像技术的飞速发展,多模式影像的成像角度从传统后极部眼底检查扩展到广角乃至超广角成像,极大地提升了对PCD眼底病灶的观察范围,提升了对脉络膜结构和功能的评估能力。AI技术的引入为PCD诊疗带来革新,通过深度学习快速识别病变特征,不仅提高了诊断效率和准确性,也为基层医疗机构提供了有力支持。
       展望未来,先进的影像学手段将揭示PCD更多未知的疾病特征。广角眼底影像与AI的深度融合将进一步提升PCD的诊断水平,加强基层筛查能力,推动疾病早期发现和精准诊疗的实现。随着多中心研究数据的持续积累和分析技术的不断提升,我们将更深入地探讨PCD的发病机制,为患者提供更加个体化的诊疗方案,最终提高患者的预后及生活质量。

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