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Lumic Lumic: Ophthalmology Encyclopedia
Retina & Vitreous

Hyperreflective Foci (HRF) on OCT

Key points at a glance

Section titled “Key points at a glance”

1. What Are Hyperreflective Foci (HRF) on OCT?

Section titled “1. What Are Hyperreflective Foci (HRF) on OCT?”

Hyperreflective foci (HRF) are punctate, round hyperreflective lesions <30 μm observed on optical coherence tomography (OCT) scans. Also called hyperreflective dots 1)2). They are attracting attention as new biomarkers of retinal inflammation and vascular damage 1).

HRF are found in various ocular diseases including age-related macular degeneration, diabetic retinopathy, glaucoma, retinal vein occlusion (RVO), uveitis, and retinal dystrophies 1)2). Among the top five causes of blindness defined by WHO, three—AMD, diabetic retinopathy, and glaucoma—lack reliable biomarkers. HRF are positioned as a promising candidate 1).

HRF were first reported in 2009 in exudative AMD, and in the same year in untreated diabetic macular edema patients. Subsequent analysis of 42 reports confirmed 26 cases in AMD, 12 in diabetic retinopathy, and 4 in glaucoma 1).

HRF are considered useful for identifying early signs of disease, monitoring progression, and assessing treatment response 1).

Definition

Size: ≤30 μm. Punctate, round hyperreflective lesions detected on OCT.

Visibility: Not detectable by fundus examination. An OCT-specific finding.

Reflectivity: Shows high reflectivity equal to or greater than the RPE.

Value as a Biomarker

Early Detection: Captures early changes in disease.

Progression Prediction: Prognostic thresholds have been reported for different diseases.

Treatment Monitoring: Can be used as an indicator of treatment response.

Q Can hyperreflective foci (HRF) be seen on fundus examination?
A

HRF is an OCT-specific finding and cannot be detected by routine fundus examination. Because they are smaller than 30 μm, they are not detectable by fundus photography or slit-lamp microscopy.

2. Imaging Characteristics and Association with Various Diseases

Section titled “2. Imaging Characteristics and Association with Various Diseases”

Defining Imaging Characteristics

Section titled “Defining Imaging Characteristics”

The defining characteristics of HRF are shown below.

  • Size: ≤30 μm1)2)
  • Reflectivity: Equal to or greater than the RNFL (retinal nerve fiber layer)2)
  • Posterior shadowing: None2)
  • Fundus findings: Invisible2)
  • Clarity: Distinct punctate lesions with reflectivity equal to or greater than the RPE1)

HRF and hard exudates are easily confused, but their characteristics differ.

FeatureHRFHard exudate
Size≤30 μmVariable
Posterior shadowNonePresent
Fundus findingsInvisibleYellow lesions
Q How are hyperreflective foci and hard exudates different?
A

Hard exudates appear on OCT with posterior shadowing and can be seen as yellow lesions on fundus examination. In contrast, HRF are less than 30 μm, have no shadowing, and are invisible on fundus examination. HRF are also suggested to be precursors of hard exudates1)2).

Characteristics of HRF in various diseases

Section titled “Characteristics of HRF in various diseases”
Section titled “Age-related macular degeneration”
  • Distribution: Predominantly in the outer retina (ONL and subretinal space)1)
  • Relationship with drusen: Directly correlated with drusen1)
  • Dry age-related macular degeneration: Derived from RPE and photoreceptors. Accumulate along Henle fibers toward the fovea1)2)
  • Wet age-related macular degeneration: Mainly derived from activated microglia2)
  • Progression prediction (GA): >20 HRF/mm² predicts progression to geographic atrophy (GA) (2–5 years)1)
  • Fibrosis prediction: >10 HRF/lesion predicts subretinal fibrosis (1–3 years)1)
  • Intermediate age-related macular degeneration: HRF is an independent risk factor for progression to wet age-related macular degeneration within 24 months2)3)

Kikushima et al. (2022) analyzed 155 patients with intermediate age-related macular degeneration and reported an HRF positivity rate of 34.2%3). The hazard ratio for progression to macular neovascularization (MNV) was significantly higher in the HRF-positive group at 3.67 (95% CI 1.68–8.00, p=0.001). The 60-month MNV progression rate was 37.7% in HRF-positive vs. 9.8% in HRF-negative (p=7.0×10⁻⁵). Characteristics of the HRF-positive group included pseudodrusen 60.4%, drusenoid PED 54.7%, and choroidal thickness 189 μm. Racial differences were suggested, with atrophy-related progression in Western populations and MNV-related progression in Japanese populations3).

Furthermore, the frequency of the ARMS2 A69S risk allele is significantly higher in the HRF-positive group, suggesting an association with genetic background3).

Diabetic Retinopathy

Section titled “Diabetic Retinopathy”
  • Distribution: Predominantly in the inner retinal layers (INL)1)
  • Origin: Reflects microglial activation1)
  • Edema/Visual Prognosis: In diabetic macular edema, >15 HRF correlates with persistent edema and visual deterioration (1–2 years)1)
  • PDR Progression: Increased HRF count predicts progression to proliferative diabetic retinopathy (PDR)1)
  • Inflammatory Marker: Baseline HRF increase correlates with elevated CD14 (monocyte/macrophage activation marker)2)

Glaucoma

Section titled “Glaucoma”
  • Size/Distribution: <30 μm. Distributed across all layers except ONL and RPE1)
  • Origin: Derived from activated microglia1)
  • Structural/Functional Prediction: >10 HRF/scan predicts retinal layer thinning and visual field defects (2–4 years)1)

Retinal Vein Occlusion (RVO)

Section titled “Retinal Vein Occlusion (RVO)”
  • Two Types: Fine and confluent types exist2)
  • Distribution Significance: Fine type indicates extravasation sites; confluent type is associated with absorption in unaffected areas2)
  • Treatment Response: Increased baseline HRF is associated with poor response to anti-VEGF therapy2)

Retinal Dystrophy

Section titled “Retinal Dystrophy”

Uveitic Macular Edema

Section titled “Uveitic Macular Edema”
  • Distribution: HRF is distributed across all layers2)
  • Treatment response: Responds to treatment. Persists in inner layers after edema resolution2)
  • Correlation: Shows positive correlation with central macular thickness (CMT)2)

Purtscher-like Retinopathy

Section titled “Purtscher-like Retinopathy”

Prabhu et al. (2024) reported that in a case of Purtscher-like retinopathy, hyperreflective dots in the posterior vitreous and ILM (internal limiting membrane) detachment serve as inflammatory markers4). These findings disappeared 10 days after steroid administration.

The distribution of HRF by disease and prognostic thresholds are summarized.

DiseaseMain DistributionPrognostic Threshold
Age-related macular degenerationOuter layer (ONL)>20/mm² → GA progression
Diabetic retinopathyInner layer (INL)>15 → persistent edema
GlaucomaFull thickness>10/scan → thinning

3. Origin and formation mechanism of HRF

Section titled “3. Origin and formation mechanism of HRF”

HRF has multiple histological origins, which vary depending on the disease and stage 1).

Activated microglia

Role: Migrate from INL to outer layers. Reflect inflammatory and ischemic responses.

Diseases: Predominant in diabetic retinopathy (INL), exudative age-related macular degeneration, and glaucoma.

Significance: Direct marker of neuroinflammation1)2).

Degenerated photoreceptors

Role: Formed following damage to photoreceptor structures.

Disease: Late stages of various degenerative diseases.

Significance: May suggest irreversible photoreceptor loss2).

Common mechanisms underlying HRF formation include inflammation, vascular changes, and oxidative stress1). Among 42 analyzed reports, 20 showed a correlation between HRF and inflammation1).

Age-related hyperreflective dots also exist, but they can be distinguished from HRF associated with age-related macular degeneration by quantity and appearance1). Choroidal HRF is distributed near Bruch’s membrane and is not found within blood vessels. It arises as a result of pathology and is considered to have a limited role as a progression biomarker1).

In Purtscher-like retinopathy, reperfusion injury due to inflammation is thought to cause HRF formation, which resolves with steroids4).

In animal models, administration of Peptide5, a connexin hemichannel blocker, has been shown to reduce HRF1).

4. Detection and Evaluation Methods and Prognosis Prediction

Section titled “4. Detection and Evaluation Methods and Prognosis Prediction”

HRF is detected using SD-OCT or SS-OCT. A major advantage is that it can be detected noninvasively1)2).

Positive criteria: At least one clear or two or more ambiguous punctate lesions showing reflectivity equal to or greater than the RPE are considered positive1).

Main limitations: Manual counting is currently the standard method, and there are challenges in the reproducibility of quantitative assessment2).

Prognostic thresholds by disease are as follows1):

A systematic review of OCT biomarkers by Nanji et al. (2026) showed that baseline EZ (ellipsoid zone) disruption and HRF were associated with visual decline at 6 months, but the certainty of evidence was rated as “Low certainty”6).

Associations between HRF and functional impairment have also been reported. Correlations with reduced electroretinogram amplitude, delayed dark adaptation, and decreased retinal sensitivity have been shown1).

Visible-light OCT (vis-OCT) achieves a resolution of 1.3 μm (more than 5 times that of NIR-OCT), and fibergram en face imaging enables visualization of HRF that is difficult to confirm with conventional OCT5).

Q Can the number of HRF predict disease progression?
A

Prognostic thresholds have been reported by disease: in age-related macular degeneration, >20 HRF/mm² predicts GA progression; in diabetic retinopathy, >15 HRF correlates with persistent edema and visual deterioration1). However, manual counting is currently the standard, and standardization of quantitative assessment remains a future challenge.

5. Significance of HRF in Monitoring Treatment Response

Section titled “5. Significance of HRF in Monitoring Treatment Response”

HRF are not themselves targets for treatment, but they are useful as monitoring indicators to evaluate treatment response of the underlying disease.

  • Diabetic macular edema: Decrease in HRF after treatment is a well-established finding. Its usefulness as a predictive factor remains unconfirmed2)
  • RVO: Increased baseline HRF is associated with poor anti-VEGF treatment response. Dexamethasone implants may be beneficial2)
  • Purtscher-like retinopathy: HRF disappears after steroid administration 4)
  • Animal model of diabetic retinopathy: HRF decreases with administration of connexin hemichannel blocker Peptide5 1)
  • Association with visual acuity: Improvement in biomarkers may correlate with visual acuity improvement 6)

6. Pathophysiology and detailed mechanisms

Section titled “6. Pathophysiology and detailed mechanisms”

The formation mechanism of HRF is multifactorial, and the reflectivity varies depending on the specific retinal pathology 1). Common mechanisms across diseases include inflammation, vascular changes, and oxidative stress 1).

Layer-specific distribution patterns: In age-related macular degeneration, HRF is distributed in the outer layer (ONL); in diabetic retinopathy, in the inner layer (INL); and in glaucoma, across all layers 1). This layer-specific pattern reflects disease-specific pathology.

Genetic background related to age-related macular degeneration: The ARMS2 A69S risk allele is significantly more frequent in HRF-positive age-related macular degeneration, showing a stronger association than CFH I62V 3). In Western countries, HRF is associated with geographic atrophy, while in Japan, it is strongly associated with MNV (choroidal neovascularization). This racial difference may reflect differences in genetic background and disease subtypes 3).

Distinction from age-related changes: Hyperreflective dots increase with age after age 50, but they can be distinguished from HRF associated with age-related macular degeneration by quantity, distribution, and appearance 5).

Choroidal HRF: Distributed near Bruch’s membrane and not found within blood vessels. Choroidal HRF occurs as a result of pathology, and its role as an independent progression biomarker is considered limited 1).

Association with uveitis: If HRF persists in the inner layer after resolution of edema, it may suggest residual chronic inflammation 2).

7. Latest research and future perspectives

Section titled “7. Latest research and future perspectives”

Stratification by origin of HRF: Development of methods to distinguish microglia-derived and lipoprotein-derived HRF on OCT images is progressing. Application to disease-specific treatment strategies is expected1).

Visible-light OCT (vis-OCT): Using visible light with wavelengths of 400–700 nm, it achieves a resolution of 1.3 μm (more than 5 times that of NIR-OCT).

Krause et al. (2024) reported a case in which high-reflective dots in the fovea were visualized in detail using visible-light OCT and fibergram en face imaging5). This resolution enables the detection of fine HRF that could not be confirmed with conventional NIR-OCT.

Quantification by AI (artificial intelligence): Although manual counting is currently the standard, AI-based detection and quantification of HRF is expected to enable highly reproducible large-scale longitudinal studies1).

Novel therapeutic targets: Connexin hemichannel blockers (such as Peptide5) have been shown to suppress HRF formation in animal models, and future clinical application is expected1).

Promotion of standardization: International standardization of imaging and evaluation criteria, along with accumulation of longitudinal studies, is expected to further improve the accuracy of HRF prognosis prediction1).

Elucidation of racial differences: Research is needed to clarify the genetic and environmental background of racial differences, such as atrophy-related HRF in Western countries and MNV-related HRF in Japan3).

Q Has visible-light OCT made it possible to detect HRF that were previously invisible?
A

Visible-light OCT achieves a resolution of 1.3 μm, which is more than five times the resolution of conventional NIR-OCT (near-infrared OCT)5). This enables visualization of fine HRF that were difficult to confirm with conventional OCT. However, at present, this technology is still at the research stage, and widespread clinical adoption is yet to come.

8. References

Section titled “8. References”
  1. Mat Nor MN, Green CR, Squirrell D, Acosta ML. Retinal hyperreflective foci are biomarkers of ocular disease: a scoping review with evidence from humans and insights from animal models. J Ophthalmol. 2025;2025:9573587.
  2. Fragiotta S, Abdolrahimzadeh S, Dolz-Marco R, Sakurada Y, Gal-Or O, Scuderi G. Significance of hyperreflective foci as an optical coherence tomography biomarker in retinal diseases: characterization and clinical implications. J Ophthalmol. 2021;2021:6096017.
  3. Kikushima W, Sakurada Y, Sugiyama A, et al. Characteristics of intermediate age-related macular degeneration with hyperreflective foci. Sci Rep. 2022;12:18420.
  4. Prabhu V, Joshi A, Chitturi SP, Yadav NK, Chhablani J, Venkatesh R. Internal limiting membrane separation and posterior vitreous hyperreflective dots: novel OCT findings in Purtscher-like retinopathy. BMC Ophthalmol. 2024;24:137.
  5. Krause MA, Grannonico M, Tyler BP, et al. Hyperreflective dots in central fovea visualized by a novel application of visible-light optical coherence tomography. Case Rep Ophthalmol Med. 2024;2024:5823455.
  6. Nanji K, Hatamnejad A, Grad J, et al. Visual outcomes associated with optical coherence tomography biomarkers in diabetic macular edema: A systematic review. Surv Ophthalmol. 2026;71(2):289-308. doi:10.1016/j.survophthal.2025.09.009. PMID:40967513.

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