Optical Coherence Tomography Findings in Choroidal Melanoma-Associated Subretinal Fluid

Guner, Melis Kabaalioglu; Ferenchak, Kevin; Olsen, Timothy W.; Dalvin, Lauren A

doi:10.1097/iae.0000000000003578

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…1 C). In the recent report but Guner et al [ 23 ] 58% of the eyes with BALAD were associated with heterogenous hyperreflective material. The size and number of BALAD varied among our cases, some were subtle and small (Figs.…”

Section: Discussionmentioning

confidence: 91%

“…Here, we provide preliminary incidence data on BALAD occurrence with the two most common types of choroidal malignancy and demonstrate an incidence of 54.5% and 14.3% with choroidal metastasis and melanoma, respectively. Recently, Guner et al [ 23 ] reported on the SRF characteristics of a large sample of choroidal melanomas (236 patients). They found the incidence of BALAD to be 28.4%, and that it was more common in medium-sized tumors with larger SRF, which is consistent with our described case of medium-sized malignant melanoma and BALAD.…”

Section: Discussionmentioning

confidence: 99%

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Bacillary layer detachment with malignant choroidal tumors: a case series

et al. 2023

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Purpose To study the incidence and characteristics of bacillary layer detachment (BALAD) occurring with the two most common choroidal malignancies, choroidal metastasis and choroidal melanoma. Methods A retrospective multicentric record analysis. Eyes with a diagnosis of choroidal melanoma or choroidal metastasis that had good-quality fundus photography and spectral domain optical coherence tomography (OCT) scans of the macular and tumor regions allowing for delineation of the retinal layers were included for analysis. Qualitative image evaluation was done by two independent graders for the presence, location, and OCT features of BALAD, as well as any associated intraretinal or subretinal fluid. Demographic and clinical data were also retrieved. Results Of the 11 eyes with choroidal metastasis and 7 eyes with choroidal melanoma that were included in the final analysis, 6 (54.5%) and 1 (14.3%) had BALAD, respectively. The BALAD co-localized with the subretinal fluid in all cases and with the intraretinal fluid in 1/3 cases (33.3%), was foveal in location in 3 eyes (42.9%), was overlying the tumor in 6 eyes (85.7%), and varied in number and size. Reflectivity within the BALAD was consistently higher than the vitreous and adjacent subretinal fluid, and discernable suspended hyperreflective particles were noted in 5 eyes (71.4%). Conclusion BALAD is relatively common with choroidal metastasis. The OCT features described supplement our recognition of this new entity.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Bacillary layer detachment with malignant choroidal tumors: a case series

et al. 2023

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“… 14 TFSOM-DIM incorporates multimodal imaging techniques in the identification of risk factors, including subretinal fluid on OCT, orange pigment on autofluorescence, and a basal diameter of at least 0.5 mm on fundus photography. 14 These additional imaging techniques provided a more nuanced approach to identifying UM, 36 which have been evaluated in subsequent studies. Geiger et al used the TFSOM-DIM criteria to grade multimodal imaging by retrospective chart review, revealing significant differences in the range of risk scores between UM and choroidal nevi.…”

Section: Discussionmentioning

confidence: 99%

Predicting Malignant Transformation of Choroidal Nevi Using Machine Learning

Iddir,

Love,

et al. 2023

Preprint

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Objective This study aims to assess a machine learning (ML) algorithm using multimodal imaging to accurately identify risk factors for uveal melanoma (UM) and aid in the diagnosis of melanocytic choroidal tumors. Subjects and Methods This study included 223 eyes from 221 patients with melanocytic choroidal lesions seen at the eye clinic of the University of Illinois at Chicago between 01/2010 and 07/2022. An ML algorithm was developed and trained on ultra-widefield fundus imaging and B-scan ultrasonography to detect risk factors of malignant transformation of choroidal lesions into UM. The risk factors were verified using all multimodal imaging available from the time of diagnosis. We also explore classification of lesions into UM and choroidal nevi using the ML algorithm. Results The ML algorithm assessed features of ultra-widefield fundus imaging and B-scan ultrasonography to determine the presence of the following risk factors for malignant transformation: lesion thickness, subretinal fluid, orange pigment, proximity to optic nerve, ultrasound hollowness, and drusen. The algorithm also provided classification of lesions into UM and choroidal nevi. A total of 115 patients with choroidal nevi and 108 patients with UM were included. The mean lesion thickness for choroidal nevi was 1.6 mm and for UM was 5.9 mm. Eleven ML models were implemented and achieved high accuracy, with an area under the curve of 0.982 for thickness prediction and 0.964 for subretinal fluid prediction. Sensitivity/specificity values ranged from 0.900/0.818 to 1.000/0.727 for different features. The ML algorithm demonstrated high accuracy in identifying risk factors and differentiating lesions based on the analyzed imaging data. Conclusions This study provides proof of concept that ML can accurately identify risk factors for malignant transformation in melanocytic choroidal tumors based on a single ultra-widefield fundus image or B-scan ultrasound at the time of initial presentation. By leveraging the efficiency and availability of ML, this study has the potential to provide a non-invasive tool that helps to prevent unnecessary treatment, improve our ability to predict malignant transformation, reduce the risk of metastasis, and potentially save patient lives.

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