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Imaging Biomarkers for Early Differentiation of Candida and Aspergillus Endogenous Fungal Endophthalmitis:
Aniruddha Agarwal1, Nitin Kumar Menia2, Alessandro Invernizzi3
1From the Eye Department, Integrated Surgical Institute (ISI) (A.A), Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates; Cleveland Clinic Lerner College of Medicine (A.A.), Case Western Reserve University, Cleveland, Ohio, USA.
Purpose:
Endogenous fungal endophthalmitis (EFE) is a rare, sight-threatening intraocular infection with heterogeneous clinical presentations. Candida and Aspergillus species are the most common etiologic agents and may manifest with retinochoroiditis lesions that can be challenging to differentiate clinically. Accurate identification of the causative organism is essential for targeted antifungal therapy, anticipating disease progression, and optimizing outcomes. This study aimed to differentiate the etiology of EFE-associated retinochoroiditis using detailed clinical and optical coherence tomography (OCT) analysis.
Design:
International, multicenter, retrospective comparative case series.
Methods:
Demographic information, clinical characteristics, fundus photography, and OCT scans of patients with culture-proven Candida or Aspergillus EFE presenting with retinochoroiditis lesions were collected from eight tertiary-care centers worldwide. Lesion morphology (size, location, multifocality, and associated features) and OCT patterns (vitreal changes, vitreoretinal interface abnormalities, inner/outer retinal infiltration, and choroidal involvement) were compared between groups. Student's t-tests were used for continuous variables and Fisher's exact tests for categorical variables. Multivariable logistic regression and a random forest classifier were applied to identify the features most predictive of fungal species.
Results:
Thirty-eight eyes of 30 patients (mean age: 64.7 ± 15 years) were included: 28 with Candida and 10 with Aspergillus EFE. Foveal involvement occurred only in Candida cases (28.6% eyes). Compared with Aspergillus, Candida EFE showed significantly more multifocal lesions (P = .008), mid-peripheral/peripheral involvement (P = .004), satellite lesions (P = .001), and "string-of-pearls" vitreous exudates (P = .05). Aspergillus eyes had larger lesions (2.4 vs. 1.2 disc-diameters; P = .001), more pre-/subretinal hemorrhage (P = .03), and higher rates of occlusive vasculitis (P = .008). On OCT, Candida eyes demonstrated more vitreous condensations/rain-cloud sign (P = .03), preretinal aggregates (P = .02), and intraretinal fluid (IRF) (P = .04). Aspergillus infections more commonly exhibited full-thickness involvement with dense shadowing (P = .001) and choriocapillaris alteration (P = .008). Multivariable regression and random forest analysis identified lesion size, multifocality, satellite lesions, hemorrhage/vasculitis, IRF, and choriocapillaris alteration as the most discriminative features. These features allowed species differentiation with ∼85% accuracy using machine-learning classification.
Conclusions:
Candida and Aspergillus EFE presenting with retinochoroiditis exhibit distinct features that allow reliable differentiation between these fungal etiologies. These OCT-based biomarkers may inform early organism-specific management while awaiting microbiological confirmation.
Insights
This study differentiates Candida and Aspergillus endogenous fungal endophthalmitis (EFE) retinochoroiditis using clinical and OCT findings. Distinct OCT biomarkers enable accurate species differentiation, guiding early management.
Area of Science:
- Ophthalmology
- Infectious Diseases
- Medical Imaging
Background:
- Endogenous fungal endophthalmitis (EFE) is a severe intraocular infection.
- Candida and Aspergillus are common causes, presenting with similar retinochoroiditis.
- Accurate identification is crucial for targeted antifungal therapy and improved outcomes.
Purpose of the Study:
- To differentiate Candida and Aspergillus EFE retinochoroiditis using clinical and optical coherence tomography (OCT) features.
- To identify key diagnostic biomarkers for distinguishing fungal etiologies.
- To improve early diagnosis and management of EFE.
Main Methods:
- Retrospective comparative case series of patients with culture-proven Candida or Aspergillus EFE.
- Analysis of demographic data, clinical characteristics, fundus photography, and OCT scans.
- Application of multivariable logistic regression and random forest classifiers for feature prediction.
Main Results:
- Candida EFE showed more multifocal lesions and vitreous exudates; Aspergillus EFE had larger lesions and more hemorrhage.
- Distinct OCT patterns observed: Candida EFE with vitreous condensations and intraretinal fluid; Aspergillus EFE with full-thickness involvement and choriocapillaris alteration.
- Machine learning models achieved ~85% accuracy in differentiating fungal species based on identified features.
Conclusions:
- Candida and Aspergillus EFE retinochoroiditis exhibit distinct clinical and OCT features.
- OCT-based biomarkers facilitate reliable differentiation between these fungal etiologies.
- These findings support organism-specific management decisions prior to microbiological confirmation.
