Anterior segment optical coherence tomography in uveitis: A comprehensive review of clinical applications, diagnostic insights, and future directions

Abstract

Anterior segment optical coherence tomography (AS-OCT) is emerging as an essential tool in the diagnosis and monitoring of uveitis. Offering noninvasive, high-resolution imaging, AS-OCT allows clinicians to visualize and quantify subtle changes in the anterior chamber (AC), iris, cornea, sclera, and lens that may be difficult to capture with slit-lamp examination alone.

We highlight how AS-OCT improves the detection of AC cells and flare, supports disease monitoring through automated, reproducible metrics, and facilitates care in challenging settings, such as pediatric uveitis or clinical trials. In the cornea, AS-OCT allows detailed evaluation of keratic precipitates and subclinical endothelial dysfunction. It also provides disease-specific metrics of iris thickness and surface smoothness in conditions such as Fuchs uveitis syndrome. In the sclera, AS-OCT can distinguish episcleritis from scleritis, differentiate their subtypes, and monitor inflammation resolution.

Emerging applications, including anterior vitreous imaging and artificial intelligence-driven analysis, suggest a growing role for AS-OCT in personalized care. As evidence expands, AS-OCT is poised to become a cornerstone of multimodal imaging in uveitis, enhancing precision, reducing subjectivity, and improving outcomes for patients across a wide spectrum of inflammatory eye disease.

1. Introduction

Anterior segment optical coherence tomography (AS-OCT) is emerging as a simple, noninvasive yet powerful and objective, imaging modality in the clinical assessment and multimodal imaging of uveitis.^{1,13,16,21,40,50,59,70,91} This technology enables detailed visualization and quantification of anterior chamber (AC) inflammation, including AC cells and aqueous flare,^{6,36,70,79,88,99} while also distinguishing these findings from pigment dispersion, assessing AC depth, and evaluating inflammatory anterior vitreous involvement.^37,78 Furthermore, AS-OCT provides valuable information on iris thickness and smoothness,^7,109–111 and uveitis-related changes such as iris nodules and synechiae, and corneal,^76,89,90 scleral,^5,32,52,80 and lens^44,69 abnormalities.

In our comprehensive review, we discuss and summarize the key clinical applications of AS-OCT in the context of a wide spectrum of uveitic disorders and highlight its role in enhancing diagnostic accuracy and disease monitoring. We also discuss emerging advancements, including the integration of artificial intelligence(AI)-driven and automated quantification systems, which may further streamline and standardize AS-OCT-based evaluation in clinical practice. By consolidating current evidence, this article emphasizes the growing importance of AS-OCT as a cornerstone in the multimodal imaging and clinical approach to uveitis.

2. Clinical applications

2.1. Anterior chamber

AC inflammation is a hallmark of inflammation involving the anterior segment of the eye.⁷⁰ Its evaluation plays a central role in the diagnosis, monitoring, and management of uveitis,^70,100 and is traditionally performed by slit-lamp biomicroscopy and graded according to the Standardization of Uveitis Nomenclature (SUN) criteria,³⁹ based on the number of cells visualized within a 1 × 1 mm slit beam. Although widely used in clinical practice, this method is limited by its subjective and examiner-dependent nature and may fail to detect subtle but clinically meaningful changes in AC inflammation, especially in patients with photophobia or limited cooperation, such as children.⁴⁸

AS-OCT is increasingly recognized as a non-invasive, objective imaging modality capable of detecting inflammatory AC cells in the aqueous humor as hyperreflective foci (HRF).⁶⁴ AS-OCT-based quantification shows strong correlation with SUN grading, while offering continuous, reproducible measurements which are less susceptible to user bias. These advantages make AS-OCT particularly valuable for clinical trials, where standardized and sensitive outcome measures are essential, and for longitudinal monitoring of uveitis in everyday clinical practice.^{1,6,10,34,36,61,64,79,88,99}

2.1.1. From time-domain to spectral-domain and swept-source AS-OCT

One of the first applications of AS-OCT in uveitis was reported and described in 2009 by Agarwal and colleagues,¹ who utilized time-domain (TD) AS-OCT (Carl Zeiss Meditec, Dublin, CA) to image AC inflammatory reactions, including AC cells, aqueous flare, keratic precipitates (KP), and fibrinous membranes in 62 eyes from 45 patients with uveitis. TD-OCT systems operate at a wavelength of 1310 nm, with a scan speed of approximately 2,000 axial scans per second, and offer axial and transverse resolutions of 17 μm and 45 μm, respectively.³³ These technical features enabled the detection of AC cells and KP as hyperreflective dots within the AC and along the corneal endothelium, respectively, even in the presence of corneal edema or infiltrates.¹

In addition, they demonstrated a strong correlation of the AC cells captured with AS-OCT with the clinical grading of AC cells based on the SUN criteria³⁹ and that the custom-made automated method was more sensitive than the manual method in more severe uveitic cases, especially when complicated by significant corneal edema.¹ Similar results were obtained by Li and coworkers (both in vivo and in vitro),⁵⁷ and Igbre and colleagues,³⁴ who showed a good correlation of AS-OCT cell counts with the clinical slit-lamp-based grading system of AC inflammation.

TD-OCT systems, however, are limited by relatively slow scanning speeds, low axial and transverse resolution, and the static, two-dimensional nature of the images produced. These limitations were largely overcome by Fourier-domain (FD) systems, which include spectral-domain (SD) and swept-source (SS) OCT devices.^{54,74,105,106} SD-OCT offers significantly higher scan speeds and improved axial and transverse resolution, enabling the visualization of even individual white blood cells, which may measure as little as 7–9 μm in diameter. Moreover, the integration of automated software with SD-OCT technology facilitates 3-dimensional (3D) reconstruction and quantitative analysis of AC inflammation, representing a major advance in the objective assessment of anterior uveitis.

In 2015, Sharma and colleagues⁸⁸ were the first to assess the feasibility of using AS-OCT to objectively image and quantify AC inflammation with a SD-OCT device (RTVue-100, Optovue, Inc., Fremont, CA). This system featured a scanning speed of 26,000 axial scans per second and an axial resolution of 5 μm. The authors manually graded single-line 6-mm scans as well as 6 mm × 6 mm 3D volume scans for the presence of hyperreflective AC cells and found a strong correlation between the number of detected cells and clinical grading scores based on the SUN criteria. Notably, they also developed an automated algorithm for quantifying AC cell counts, which demonstrated a high correlation with manual grading in 3D volume scans. This work laid the foundation for the use of AS-OCT as an objective and reproducible tool to grade intraocular inflammation and monitor treatment response.^42,88

SS-OCT, characterized by high axial resolution (< 10 μm), ultrafast scanning speeds (> 100 kHz), and rapid acquisition of 3D models, has demonstrated strong agreement between automated and manual AC cell quantification and robust correlations with clinical grading systems across multiple studies.^6,36,60,99

In a pivotal 2017 prospective study, Invernizzi and colleagues³⁶ evaluated 237 eyes from 122 subjects (167 eyes with uveitis and 70 healthy controls) using the CASIA SS-1000 OCT system (Tomey Corporation, Nagoya, Japan). They found that AC cell counts derived from SS-OCT strongly correlated with SUN clinical grading, with a clear, stepwise increase in OCT-detected cell counts corresponding to each SUN grade. Additionally, their study introduced the aqueous-to-air relative intensity (ARI) index, a novel flare quantification metric calculated by comparing the optical density of the AC to a reference air intensity value. The ARI index demonstrated high reproducibility and showed performance comparable to laser flare photometry (LFP) in distinguishing active uveitis from inactive and control eyes; however, while ARI values correlated with LFP in active inflammation, no significant correlation was found in inactive or control eyes, suggesting reduced sensitivity at lower levels of flare.

Building on these foundations, Solebo’s group, specifically Etherton¹⁹ and Solebo and colleagues⁹³, contributed important pediatric data on AS-OCT imaging and normative HRF thresholds in children, which will be further discussed in Section 2.1.3.

In a 2022 prospective validity and reliability analysis, Tsui and colleagues⁹⁹ evaluated the feasibility of AS-OCT for quantifying AC cells in 59 eyes of 30 children with uveitis using the SD Optovue Avanti RTVue XR system (Optovue, Inc., Fremont, CA). Two acquisition modes, i.e. a single cross-sectional line scan and an 8-line radial scan, were compared, with cell counts manually graded by 2 independent, masked observers. Tsui and coworkers’ study demonstrated excellent intergrader agreement and high concordance between acquisition modes, particularly at lower SUN clinical grades (< 1+), which represent the most frequently observed levels of inflammation in pediatric uveitis. Notably, AS-OCT imaging was feasible even in young children (as early as 3 years of age). These findings, while based on manual grading, align with adult studies using SS-OCT and automated quantification, such as those by Invernizzi³⁶ and Lu,⁶¹ and confirm the reliability of AS-OCT for detecting and monitoring AC inflammation in children, a high-risk population in whom slit-lamp examination may be limited by patient cooperation or photosensitivity.³

More recently, Pillar and coauthors⁷⁹ advanced the field by validating a fully automated algorithm for AC cell quantification using high-resolution line-scan images from the ANTERION SS-OCT (Heidelberg Engineering, Heidelberg, Germany). Their algorithm showed strong agreement with manual counts and significant correlation with SUN grades, while offering a continuous, objective metric. Unlike earlier manual or semiautomated approaches, this method automatically segmented the AS, selected the region of interest (ROI), and quantified HRF without user input, reducing bias and improving reproducibility. Notably, subclinical inflammation was identified in eyes graded as inactive on clinical examination, suggesting improved sensitivity over slit-lamp biomicroscopy. Therefore, Pillar and coauthors’ findings marked a significant step toward standardized, precise, and scalable inflammation quantification in clinical trials and routine care.⁷⁹

A representative case of the utility of AS-OCT in the context of AC inflammation is shown in Fig. 1.

Fig. 1.

Anterior segment optical coherence tomography (AS-OCT) of the anterior chamber (AC) in the left eye (OS) of an 84-year-old male with severe anterior and intermediate uveitis secondary to fungal infection. Culture OS confirmed the presence of Coccidioides immits. A. Horizontal AS-OCT B-scan illustrates keratic precipitates visible as hyperreflective dots along the corneal endothelium (highlighted by yellow arrows in B), grade 3 aqueous flare (marked by red asterisks in C) and grade 2 AC cells (seen as hyperreflective foci outlined by red circles in D).

2.1.2. Cell differentiation

Although AS-OCT reliably detects inflammatory AC cells as HRF and correlates well with SUN grading, it remains limited in its ability to distinguish leukocytes from red blood cells (RBC) and pigmented cells, potentially leading to overestimation of inflammation, particularly in eyes with pigment dispersion or hyphema.

To address this limitation, Rose-Nussbaumer and colleagues⁸⁴ used SD-OCT with a custom algorithm to differentiate cell types based on reflectance, showing significant differences among leukocyte subtypes and RBC. A spectroscopic SS-OCT study similarly identified distinct backscatter profiles for inflammatory and non-inflammatory cells.⁸¹

In 2025, Bellchambers and colleagues⁸ used the CASIA2 SS-OCT device to analyze hyperreflective particle size in 62 eyes from 31 adults with uveitis. Particles > 4 pixels (24 μm) strongly correlated with higher SUN grades, especially in eyes without clinically visible pigment, while particles ≤ 2 pixels were more often associated with pigment. ROC curve analyses showed optimal diagnostic performance when using a size threshold > 2 pixels to detect active inflammation. Importantly, particle size varied by uveitis etiology, with smaller particles observed in viral uveitis and larger ones in juvenile idiopathic arthritis (JIA) cases.

Although further validation with aqueous sampling and larger cohorts is clearly needed, these findings highlight the potential of AS-OCT not only for objective quantification of intraocular inflammation, but also for distinguishing pigment from inflammatory cells, and even characterizing distinct uveitis subtypes.^47,56

2.1.3. Future directions: automated imaging for pediatric uveitis screening

Recent advances in AI and computer vision have paved the way for fully automated AC cell quantification, addressing key limitations of manual and semi-automated grading approaches.^44,47,79,96 As discussed above, Pillar and colleagues⁷⁹ demonstrated the feasibility of using a fully automated SS-OCT-based algorithm to quantify AC inflammation with high reproducibility and strong correlation with SUN grading.

These developments are particularly relevant in pediatric uveitis, where traditional slit-lamp exams are often limited by poor cooperation and low sensitivity.^3,10 In this context, Etherton and colleagues¹⁹ conducted a prospective study including 180 eyes from 90 children (median age of 11.5 years), evaluating repeatability, clinical responsiveness, and acceptability of the SS CASIA2 and Heidelberg Spectralis HS1 AS-OCT devices. They reported that OCT-derived metrics are dependent on OCT platform and confirmed that cell counts correlate with clinical grades of uveitis activity and are responsive to changes in clinical activity. Additionally, families and patients welcomed the scanning process and rated it as well-tolerated, supporting its feasibility in routine pediatric care.¹⁹

Complementing these findings, Uthayananthan and colleagues¹⁰¹ evaluated the effect of operator-dependent acquisition parameters on AS-OCT performance in pediatric anterior uveitis using the Optovue RTVue80. In their prospective study of 77 eyes from 40 children, both low-volume (horizontal and vertical cross-sections) and high-volume (68 horizontal sections) scans achieved excellent repeatability. Low-volume, 2-line imaging showed a high negative predictive value (82.9%) and moderate positive predictive value, whereas the high-volume protocol achieved perfect rule-out performance (negative predictive value = 100%) but limited specificity, therefore offering minimal additional diagnostic yield despite greater storage and analysis burden. They concluded that streamlined low-volume acquisition provides robust, reproducible inflammation quantification suitable for pediatric screening, while high-volume imaging may serve as a confirmatory or research tool.¹⁰¹

In parallel, Solebo and colleagues⁹³ imaged 434 eyes from 217 healthy, uveitis-free children (aged 5–15 years) using the Heidelberg ANTERION SS-OCT. They established normative data on HRF in the absence of clinical inflammation and found that small hyperreflective particles were common, appearing in 76 % of eyes and 87 % of children. These findings suggest that background signal may be physiologic in some children and reinforce the need for disease-specific thresholds when interpreting AS-OCT in pediatric populations. This study also emphasizes the importance of particle size thresholding, with most physiologic signals measuring ≤ 2 pixels in diameter.

Building on these foundations, the UVESCREEN1 trial¹⁴ is currently evaluating the role of AS-OCT as a primary screening tool for children with JIA at risk for anterior uveitis. This multicenter randomized controlled trial aims to assess diagnostic accuracy, feasibility, and integration of decentralized AS-OCT imaging into real-world surveillance models. If validated, AI-enhanced AS-OCT could shift pediatric uveitis screening from specialized centres to more accessible community-based care, enabling earlier detection, timelier intervention, and improved visual outcomes.

Together, these studies demonstrate the transformative potential of AI-powered AS-OCT to deliver longitudinal, sensitive, standardized, and scalable assessments of AC inflammation, particularly in pediatric patients where conventional examination methods are limited.

2.2. Anterior vitreous

Unlike AC inflammation, for which the SUN Working Group³⁹ has established a standardized grading system based on slit-lamp cell counts, no widely accepted criteria currently exist for quantifying inflammatory cells in the anterior vitreous. Although the Multicenter Uveitis Steroid Treatment (MUST) trial⁶⁸ proposed a clinical grading scale for anterior vitreous cells, consensus was not reached among SUN experts regarding its adoption. Consequently, the MUST scale has seen limited uptake and is not routinely used in clinical practice or, importantly, incorporated into randomized clinical trials. In this context, AS-OCT offers a promising avenue for objective, reproducible imaging of anterior vitreous cells and inflammation,^15,37,78,115 potentially paving the way toward more standardized assessment methods.

A recent multicentric, cross-sectional study by Invernizzi and colleagues³⁷ involving 140 eyes from 96 patients used the Heidelberg ANTERION SS AS-OCT to evaluate objectively inflammatory activity in the anterior vitreous, through the assessment of anterior vitreous cells and anterior vitreous reflectivity.

Eyes with active uveitis showed a significantly higher number of HRF in the anterior vitreous, compared to those with inactive disease or healthy controls. Notably, these cell counts significantly correlated with conventional clinical parameters such as AC cells grading, National Eye Institute (NEI) vitreous haze score (specifically grades 2 and 3), and uveitis subtype, especially in the context of intermediate uveitis as compared to anterior, posterior or panuveitis. In addition, anterior vitreous cell counts were consistent between vertical and horizontal scans and demonstrated excellent interobserver agreement, underscoring their reliability.

Regarding anterior vitreous reflectivity, this was indirectly assessed by calculating the vitreous-to-iris pigment epithelium (VIT/IPE) relative intensity index, obtained by comparing the mean pixel intensity of the vitreous region to that of the iris pigment epithelium. This method is based on the rationale that increased vitreous reflectivity corresponds to a greater concentration of inflammatory proteins suspended in the vitreous body.^45,46,67,112 The VIT/IPE index trended higher in inflamed eyes, likely reflecting increased light scatter from inflammatory proteins or particulate material within the vitreous matrix; however, differences between active, inactive, and control eyes did not reach statistical significance. Moreover, this index demonstrated weaker and less consistent correlations with clinical inflammation grading compared to cell counts (consistent with previous findings by the same authors¹¹³) and was more prone to confounding variables such as lens status.

Interestingly, AS-OCT-detectable vitreous cells were also seen in inactive uveitis and control eyes. These may represent residual inflammatory cells “trapped” in the vitreous matrix, physiologic hyalocytes, or collagen network fibres seen perpendicularly by the B-scans.^{37,45,46,67,75,112}

Finally, beyond inflammation, AS-OCT radiomic analysis has also been explored to differentiate vitreous involvement due to vitreoretinal lymphoma from uveitic vitritis, showing promising diagnostic performance and suggesting potential utility in distinguishing neoplastic from inflammatory processes.²⁸

In conclusion, the use of AS-OCT to evaluate the anterior vitreous could fill a long-standing gap in uveitis assessment by enabling objective, reproducible, and quantifiable inflammation grading in a compartment for which no standard currently exists. Future studies should focus on characterizing the morphological and optical features of anterior vitreous cells (e.g., size, shape, reflectivity), validating automated detection algorithms, establishing normative reference data, and exploring the clinical utility of anterior vitreous imaging in disease classification, monitoring, and treatment response.

A representative case of the utility of AS-OCT in the context of anterior vitreous inflammation is shown in Fig. 2.

Fig. 2. Anterior segment optical coherence tomography (AS-OCT) of the anterior vitreous in the left eye (OS) of a 55-year-old male with anterior and intermediate uveitis.

Systemic work-up revealed elevated erythrocyte sedimentation rate, positive antinuclear antibodies, and positive rheumatoid factor, with negative results for HLA-B27, syphilis serologies (TPPA/RPR), QuantiFERON-TB Gold, angiotensin-converting enzyme, and chest X-ray. Viral etiologies were excluded through aqueous humor PCR analysis. A. Horizontal AS-OCT B-scan demonstrates marked anterior vitreous inflammation, characterized by hyperreflective foci and haze. B. These inflammatory aggregates are further highlighted by red circles.

2.3. Iris and iridocorneal angle

AS-OCT enables high-resolution visualization of the iris and iridocorneal angle, allowing clinicians to assess iris contour, thickness, nodularity, and angle configuration in a reproducible fashion in a wide range of anterior uveitic disorders.

2.3.1. Iris thickness in Fuchs uveitis syndrome

In 2013, Basarir and colleagues⁷ first proposed the use of AS-OCT to analyze the iris structure and biometric parameters of the iridocorneal angle in 66 eyes (38 patients) with Fuchs uveitis syndrome (FUS) by using a TD-OCT. The authors demonstrated that iris thickness in the thickest part, iris bowing and iris shape were all statistically significantly different between the affected eye and the healthy eye in individual patients with FUS, reporting a thinning of the iris in its thickest part as compared with the unaffected fellow eyes. Additionally, all iridocorneal angle parameters (i.e. angle opening distance, scleral spur angle, trabecular-iris space) and AC depth were significantly larger in eyes with FUS than in healthy eyes.⁷

Subsequently, Invernizzi and colleagues³⁵ were the first to measure iris thickness in vivo in the 4 main iris sectors (inferior, nasal, superior, temporal), using SD AS-OCT cross-sectional full-thickness scans in both healthy and FUS eyes. In healthy eyes, they reported iris thickness values ranging from 327.92 ± 37.29 μm temporally to 405.25 ± 48.49 μm superiorly, consistent with the first in vivo iris thickness measurements obtained using ultrasound biomicroscopy by Wang and coworkers¹⁰⁴ in 1997. In FUS eyes, their findings confirmed earlier observations by Basarir and colleagues,⁷ showing a significant thinning of the iris in affected eyes compared to both the fellow unaffected eyes and healthy controls, supporting the notion of pathological, unilateral iris thinning and atrophy as a hallmark of FUS.

These results were not confirmed in a subsequent prospective study using SD AS-OCT in 21 FUS patients by Ozer and colleagues,⁷³ who did not observe statistically significant differences between affected and fellow eyes; however, they attributed this discrepancy to the smaller sample size of their cohort, although a trend toward nasal and temporal iris thinning in FUS eyes was still observed.

2.3.2. Iris surface smoothness

Zarei and coworkers^109–111 recently introduced a novel index for quantitative analysis of iris surface, termed “iris surface smoothness”, using SS AS-OCT (CASIA1 or 2). Their work stemmed from the clinical observation that FUS eyes often exhibit a relatively featureless or cryptless anterior iris surface. On slit-lamp examination, this diffuse smoothness stands in stark contrast to the more irregular and crypt-rich surface of the healthy fellow eye in unilateral cases. They defined the iris surface smoothness index¹⁰⁹ as the ratio of the length of the straight line connecting the most peripheral and the most central points of anterior iris surface, i.e. the basal length of anterior iris border, to actual length of this boundary in nasal and temporal sides. To calculate the overall smoothness index, the sum length of nasal and temporal “straight lines” was divided by the sum of nasal and temporal actual lengths of anterior iris boundary.

Zarei and coauthors¹¹⁰ demonstrated that in unilateral FUS eyes, the overall, temporal, and nasal smoothness index was significantly higher compared to the unaffected fellow eyes, with a greater inter-eye difference than in healthy controls, although the differences in temporal and nasal smoothness index versus controls did not reach statistical significance, likely due to the relatively small sample size (40 eyes with unilateral FUS and 40 eyes from 20 healthy subjects).

Subsequently, the same authors developed an automated method to calculate the smoothness index using the same SS AS-OCT (CASIA1 or 2).¹¹¹ This automated approach demonstrated high inter- and intra-rater reliability, strong agreement with the manual measurements, and a substantially shorter processing time (5–10 seconds vs. approximately 3 minutes by an experienced grader).

Building upon these foundational observations, López and Guijarro^17,18 expanded the application of SS AS-OCT to a broader spectrum of anterior uveitic entities, including FUS, rubella uveitis syndrome (RVU), cytomegalovirus (CMV) anterior uveitis, and Posner-Schlossman syndrome (PSS), enabling comparative analyses across multiple disease subtypes.

In 2022, the authors quantitatively compared iridian AS-OCT-derived parameters in RVU and CMV anterior uveitis.¹⁷ RVU eyes exhibited significantly reduced mean stromal thickness compared to CMV eyes, with more pronounced thinning in the superior and temporal quadrants. In contrast, CMV eyes showed relatively preserved stromal thickness in these regions. Additionally, RVU eyes demonstrated significantly higher smoothness index values overall, as well as in the temporal and nasal quadrants, suggesting more marked stromal flattening. When compared to healthy controls, both RVU and CMV eyes showed reduced mean stromal thickness and increased smoothness index.

In 2025, the same authors differentiated FUS from PSS using SS AS-OCT.¹⁸ In FUS eyes, iris stromal thickness was significantly reduced in the superior and temporal quadrants compared to PSS, with a trend toward lower overall stromal thickness. Additionally, FUS eyes showed significantly higher smooth index, particularly temporally, suggesting greater stromal flattening. Compared to healthy controls, FUS eyes exhibited lower stromal thickness in all quadrants and increased smooth index, reinforcing the pattern of diffuse iris atrophy. In contrast, PSS eyes showed selective thinning of the superior, nasal, and inferior quadrants but preserved temporal stromal thickness, along with increased smooth index and decreased optical density, especially nasally.

These findings highlight quadrant-specific differences in iridian involvement between RVU, CMV, FUS and PSS and support SS AS-OCT as a valuable tool for objective iris evaluation and disease differentiation, though image processing remains time-intensive.

2.3.3. Iris: other miscellaneous applications

AS-OCT of the iris and iridocorneal angle has also proven useful in many other heterogeneous uveitic diseases and conditions, including presumed intraocular tuberculosis,³¹ epi-iridic membrane in the context of recurrent hyphema and presumed juvenile xanthogranuloma,⁶³ iris ischemia in CMV panuveitis,¹¹⁴ unilateral herpetic uveitis,⁷² inflammatory glaucoma⁸² and assessment of iris bombé before and after laser iridotomy in the context of uveitic secondary glaucoma,⁶⁶ membrane pupillary-block glaucoma in a phakic eye with uveitis,³⁸ bilateral iris retraction as a complication of nivolumab treatment,⁴¹ Posner-Schlossman syndrome,¹⁰⁷ Berlin nodules due to sarcoidosis in the context of granulomatous anterior uveitis,⁵³ neurosarcoidosis and chronic uveitis with Koeppe nodules,⁴⁹ iris granulomas in Hansen disease,⁶² pearl-like lesions in the AC in patients with pupil distortion,⁹⁵ vascular iris lesions in ocular syphilis,^12,83,86 and potential applications of OCT angiography for the evaluation of the dilation of iris vessels in anterior uveitis.⁷⁷

Fig. 3 shows the utility of AS-OCT in the context of a syphilitic iris nodule associated with AC inflammation.

Fig. 3. Anterior segment optical coherence tomography (AS-OCT) of the anterior chamber (AC) in the left eye (OS) of a 74-year-old male with syphilitic uveitis.

A. Horizontal AS-OCT B-scan reveals a hyperreflective iris nodule nasally, consistent with syphilitic etiology (magnified in B), along with numerous mutton-fat keratic precipitates, seen as hyperreflective dots along the corneal endothelium, more prominent temporally (highlighted by yellow arrows in C). C. Also evident are grade 4 anterior chamber cells, visualized as hyperreflective foci (outlined by red circles).

2.4. Cornea

The cornea is another anatomical structure frequently affected in anterior uveitis, manifesting with KP, stromal edema, endothelial dysfunction, and band keratopathy among others. AS-OCT can visualize subtle corneal pathology in cases where slit-lamp evaluation may be limited by haze, edema, or poor patient cooperation.

As described in Section 2.1.1., Agarwal and colleagues¹ were the first to describe the use of TD AS-OCT to detect KP, which represent corneal endothelial deposits composed of various inflammatory cells, including lymphocytes, macrophages, or epithelioid cells.

In 2014, Agra and colleagues² demonstrated that AS-OCT could detect subclinical yet significant reductions in central corneal thickness as early as two weeks after initiating therapy in patients with acute anterior uveitis, despite the absence of clinically apparent corneal edema or changes in intraocular pressure, reflecting inflammation-induced corneal endothelial dysfunction.

Subsequently, Hashida and coworkers³⁰ employed SD AS-OCT (RTVue-100; Optovue, Fremont, CA) to study different corneal findings and the morphologic appearance of KP in a wide spectrum of treatment-naïve uveitic disorders at the time of active intraocular inflammation, including 63 eyes with herpetic iridocyclitis/endotheliitis, 58 eyes with ocular sarcoidosis, 27 eyes with primary intraocular lymphoma, and 5 eyes with FUS. The authors detected KP in 100% of herpetic iridocyclitis/endotheliitis cases, 52% of ocular sarcoidosis eyes and 56% of the lymphoma group.

Notably, the tomographic appearance of herpetic KP varied according to viral etiology. In varicella zoster virus-associated uveitis, KP appeared relatively larger, quadrilateral or elliptical, more pigmented, and hyperreflective. In contrast, herpes simplex virus-related KPs were smaller and less reflective. CMV-associated KP presented as small, coin-shaped, coalescent hyperreflective lesions. In ocular sarcoidosis, KP appeared as large, dome-shaped, hemispheric, and isoreflective. Finally, lymphoma-associated KP were dense and hyperreflective, whereas in FUS, KP appeared as stellate, small, and iso- or hyporeflective dots. In all cases, AS-OCT enabled objective documentation of KP resolution following treatment, underscoring its potential not only for etiologic differentiation of corneal inflammatory disease but also as a valuable tool for treatment monitoring and response assessment, as confirmed by other studies.^{4,51,61,89,94}

In 2020, Lu and colleagues⁶¹ used the CASIA2 SS-OCT device to expand objective evaluation by incorporating quantification of KP through posterior corneal surface smoothness (PCSS). In this prospective study, hyperreflective dot count (AC cells), ARI index (flare), and PCSS (KP) were all significantly elevated in active uveitis compared to inactive and control eyes. These metrics correlated well with SUN grading, and ROC analysis revealed PCSS as the best discriminator of uveitis presence, while AC cell count was the most effective marker for distinguishing active from inactive inflammation.

To objectively and automatically quantify KP volume and monitor its changes over time with treatment, Pichi and colleagues⁷⁶ developed an algorithm able to reconstruct en face OCT images from standard SD AS-OCT volume scans. This approach allowed for precise measurement of baseline KP volume and its progressive reduction following therapy. In a cohort of 20 patients with uveitis of various etiologies, the authors observed a significant decrease in AC cell count on slit-lamp examination after the first month of treatment. Although KP volume showed a downward trend at this early stage, the reduction reached statistical significance only after two months of continued therapy. To account for variability in scan area, the authors also introduced a volume-to-area ratio reflecting KP elevation, which showed a meaningful decrease over time. Importantly, the study found a strong correlation between the subjective grading of AC inflammation and the KP volume measured with their OCT-based method, underscoring its value in objective disease monitoring.⁷⁶

More recently, Foti and colleagues²⁶ proposed an advanced AS-OCT-based imaging approach to differentiate granulomatous from non-granulomatous corneal endothelial exudates in patients with anterior uveitis associated with autoimmune rheumatic diseases, using the Optovue Solix device. In their longitudinal observational study involving 30 patients with rheumatic disease, AS-OCT revealed distinct morphological patterns: granulomatous exudates appeared as well-defined and discrete, hyperreflective nodules with prominent posterior shadowing along the endothelium, while non-granulomatous exudates manifested as homogeneous reflective bands with less-defined margins and minimal shadowing. Granulomatous exudates were detected in approximately one-third of cases, with a variable number (5 20) and size distribution (50–150 μm). High-resolution 3D imaging further characterized the shape and localization of these lesions. Serial AS-OCT scans following steroid and immunosuppressive therapy demonstrated progressive resolution of the exudates, supporting the utility of this technique for both diagnostic differentiation and treatment monitoring.

Altogether, AS-OCT is emerging as a powerful tool for the detailed assessment of corneal inflammatory changes associated with anterior uveitis, enabling early detection of subclinical endothelial dysfunction, precise characterization of KP, and objective monitoring of treatment response.^{26,30,31,76,85,89,108} The integration of AS-OCT-based corneal evaluation into routine clinical practice and clinical trials holds the potential to facilitate standardized outcome measures, improve disease phenotyping, and enhance the assessment of therapeutic efficacy in ocular inflammatory disorders.

2.5. Sclera

Scleral inflammation is another important, though sometimes subtle, feature of anterior and posterior uveitis and systemic autoimmune conditions. AS-OCT has emerged as a promising imaging modality in this setting, providing non-invasive, high-resolution, cross-sectional visualization of the anterior scleral structures, including the conjunctiva, episclera, and sclera in several heterogenous ocular disorders.^{13,22,24,25,29,65,71,80,98}

For instance, distinguishing episcleritis – a superficial, typically self-limited condition – from scleritis, which involves deeper tissue and may be vision-threatening, is essential for appropriate management. Anatomically, episcleritis affects the superficial vascularized episclera, while scleritis involves inflammatory infiltration of the deeper scleral stroma via episcleral and choroidal vessels.

Early studies using SD-OCT demonstrated the ability to differentiate scleritis from episcleritis based on scleral thickness.^5,55,90

In 2015, Shoughy and colleagues⁹⁰ reported increased scleral thickness in active anterior scleritis compared to both episcleritis and normal eyes using SD AS-OCT. These findings were later confirmed by Axmann and coworkers,⁵ who found that ocular wall thickness (sclera + episclera) was significantly higher in affected eyes than in contralateral healthy eyes (982 ± 56 μm vs. 790 ± 23 μm), suggesting that the thickening was primarily localized to the episcleral layer in both conditions, although it was more pronounced in scleritis.

Due to its higher scan speed and deeper tissue penetration, SS AS-OCT has further refined the assessment of scleral inflammation. In 2020, Kuroda and coauthors⁵² used SS-OCT with multiple B-scan averaging to differentiate the conjunctival epithelium, conjunctival stroma/episclera, and scleral stroma in eyes with diffuse anterior scleral inflammation. They showed that the conjunctival stroma/episclera complex was significantly thickened in eyes with scleritis compared to normal controls (403.0 μm vs. 288.0 μm), whereas scleral stroma thickness did not differ significantly (464.7 μm vs. 434.2 μm). Further subgroup analysis confirmed greater thickening of both conjunctival epithelium and conjunctival stroma/episclera in scleritis compared to episcleritis, supporting the role of AS-OCT in anatomical layer-specific analysis of inflammation.

AS-OCT has also been applied to vascular imaging of the sclera using angiography-based approaches. In 2021, Hau and colleagues³² employed AS-OCT and AS-OCT angiography (AS-OCTA) to evaluate vessel density index (VDI) and scleral thickness across different tissue layers in patients with episcleritis, scleritis, and healthy controls. They found that VDI was significantly higher in patients with episcleritis or scleritis at all anatomical planes than in controls. Notably, scleritis showed even higher VDI in the episclera/sclera complex compared to episcleritis, suggesting deeper vascular involvement. This study demonstrated the feasibility of AS-OCTA to non-invasively quantify vascular congestion and distinguish between the two entities based on the degree of vascularity.³²

In addition to differentiating between episcleritis and scleritis, AS-OCT has also been employed to characterize their subtypes based on specific morphologic features.⁸⁰

Diffuse episcleritis is characterized by normal conjunctival reflectivity with mild episcleral thickening and prominent optically clear oval structures representing dilated vessels, without changes in scleral reflectance or contour. In contrast, nodular episcleritis shows localized hyporeflective spaces within the episclera consistent with nodules and posterior shadowing.

On AS-OCT, diffuse anterior scleritis presents with generalized thickening of the conjunctival, episcleral, and scleral layers, along with irregular reflectivity and abundant hyporeflective spaces, likely corresponding to dilated vascular channels and edema. Nodular scleritis features confluent hyporeflective regions with convex scleral contour, while necrotizing scleritis demonstrates high hyperreflectivity suggestive of collagen breakdown, with deeper hyporeflective bands indicating liquefactive necrosis. In more severe cases, AS-OCT may even reveal increased visibility of the underlying choroid, aiding in the identification of early tissue loss and impending scleral perforation.^5,52,80,97

AS-OCT has also proven useful for longitudinal monitoring.^80,102 Serial imaging can document resolution of inflammation through decreased scleral thickness, restoration of normal reflectivity, and disappearance of hyporeflective spaces. In necrotizing scleritis, residual thinning may persist, but normalization of reflectivity and re-epithelialization, seen as a hyporeflective band overlying thinned sclera, can help distinguish healed tissue loss from active perforation, guiding decisions on surgical intervention.⁸⁰

Finally, a recent study by Sutra and colleagues⁹⁷ investigated the structural basis of the violaceous hue often observed in inactive anterior scleritis. Using AS-OCT, the authors found no statistically significant difference in scleral thickness between violaceous areas and the contralateral eye, although there was a trend toward thinning. Interestingly, they reported significantly increased hyperreflectivity in the violaceous regions, suggesting underlying collagen remodelling rather than frank thinning. These findings offer a novel explanation for persistent discoloration in resolved scleritis and underscore the utility of OCT in detecting subtle structural changes not evident on slit-lamp examination.

2.6. Lens

Finally, AS-OCT – particularly SS platforms – can support perisurgical decision-making in uveitic cataract by objectively quantifying AS inflammation and distinguishing cellular from fibrinous components, thereby informing timing and postoperative use of intracameral rtPA in fibrinoid syndrome.⁶⁹ It can also precisely localize dexamethasone implants inadvertently lodged within the crystalline lens,^9,87 delineating the entry tract and aiding surgical planning and timing.

Beyond cataract, AS-OCT can reveal lenticular lamellar disintegration to confirm atypical phacolytic glaucoma in CMV anterior uveitis,⁴³ refining surgical strategy when the clinical picture is ambiguous. In pseudophakia, AS-OCT can depict IOL-iris/ciliary contact, correlate with iris atrophy, and serve as a first-line, non-contact alternative to ultrasound biomicroscopy for diagnosing uveitis-glaucoma-hyphema syndrome and monitoring IOL chafing.^58,92

Overall, while these applications are promising, larger prospective studies with standardized acquisition and analysis are needed to validate diagnostic performance and impact on outcomes.^11,20,23,103

3. Conclusions and future directions

AS-OCT is emerging as a powerful, non-invasive imaging modality for the evaluation and monitoring of uveitis. It offers objective, high-resolution imaging of key anterior segment structures, including the anterior chamber, iris, iridocorneal angle, cornea, and sclera, providing quantitative biomarkers that can complement or surpass traditional slit-lamp biomicroscopy in both sensitivity and reproducibility. Its utility has been demonstrated across a range of uveitic entities, from detecting hyperreflective foci corresponding to inflammatory cells and keratic precipitates,^1,79,88 to quantifying iris atrophy in Fuchs’ uveitis syndrome,^7,35 and characterizing scleral thickness and vascularity in episcleritis and scleritis.^32,52,90

Recent advances include fully automated algorithms for AC cell quantification,⁷⁹ en face OCT-based volume analyses of KP,⁷⁶ and the integration of AS-OCTA for vascular mapping in episcleritis and scleritis.³² Pediatric studies have also confirmed the feasibility of AS-OCT in children^19,99 as young as 3 years old, with early trials underway to validate decentralized, AI-assisted screening in JIA.^14,93

Despite these advances, several challenges remain. These include standardizing segmentation protocols across devices, establishing normative databases (particularly in children⁹³), and validating size- and reflectivity-based thresholds for differentiating inflammatory from non-inflammatory cells.⁸ Furthermore, while anterior vitreous imaging shows promise,^37,78 additional work is needed to optimize reflectivity-based flare surrogates and confirm their utility across uveitis subtypes.

In this context, a milestone step toward the harmonization of AS imaging terminology was recently achieved with the publication of the Advised Protocol for OCT Study Terminology and Elements Extension for Anterior Segment (APOSTEL)-AS consensus.²⁷ This consensus report establishes a unified nomenclature for AS-OCT anatomical landmarks, providing a critical framework to standardize reporting, improve cross-study comparability, and accelerate clinical and research integration of AS-OCT imaging.²⁷

Standardization gaps, however, remain – particularly the absence of a consensus grading system for anterior vitreous cells^37,78 and device-agnostic normative datasets, especially in pediatric populations. Quantitative indices such as VIT/IPE,^45,46,67,112 iris surface smoothness,^109–111 KP volume,^76,89 and PCSS⁶¹ also require greater automation and harmonization, with attention to confounders including lens status and platform-specific variability. The differentiation between leukocytes, pigment, and erythrocytes on routine AS-OCT remains limited,^81,84 and further refinement through spectroscopic and AI-assisted techniques will be critical. Similarly, scleral imaging⁵ continues to pose interpretive challenges due to its layered structure, underscoring the need for consensus segmentation and standardized reporting. Prospective, multicenter studies will therefore be essential to validate automated algorithms, establish normative databases, and confirm clinical utility across uveitis subtypes, ultimately supporting the integration of AS-OCT into real-world, decentralized care models.

Looking forward, the integration of AS-OCT into multimodal imaging workflows, coupled with artificial intelligence applications, has the potential to transform how anterior uveitis is screened, classified, and monitored across diverse clinical settings. Use of these quantitative biomarkers may eventually allow ophthalmologists to better treat inflammation, eventually enabling a paradigm shift from using subjective clinical grading criteria to a more objective approach. In particular, its expanding role in pediatric populations and clinical trials, along with the ability to detect subclinical inflammation and assess therapeutic response, positions AS-OCT as a cornerstone in the future of precision uveitis care.

3.1. Methods of literature search

We performed a review of literature up to October 2025, on PubMed and Embase databases using the following terms: anterior segment optical coherence tomography; AS-OCT; OCT; time domain; spectral domain; swept source; uveitis; anterior uveitis; anterior chamber; anterior chamber inflammation; AC inflammation; AC cell; flare; iris; iris thickness; iris smoothness; cornea; keratic precipitate; lens; cataract; sclera; scleral thickness; vitreous; anterior vitreous; clinical trials; screening; and the combination of them. The search was restricted to relevant publications and case reports in English. Articles in other languages with an English abstract were considered if adequate information could be retrieved from the abstract. Articles without an English abstract were excluded. All selected works were analysed, and their bibliographies were evaluated to identify other pertinent articles.