Dataset Information

Prolonged Mpox Disease in People With Advanced HIV: Characterization of Mpox Skin Lesions.

ABSTRACT: We report 3 complicated and prolonged cases of mpox in people with advanced human immunodeficiency virus (HIV) not on antiretroviral therapy (ART) at mpox diagnosis. Multiple medical countermeasures were used, including prolonged tecovirimat treatment and immune optimization with ART initiation. Immunofluorescence of skin biopsies demonstrated a dense immune infiltrate of predominantly myeloid and CD8+ T cells, with a strong type I interferon local response. RNAscope detected abundant replication of monkeypox virus (MPXV) in epithelial cells and dendritic cells. These data suggest that prolonged mpox in people with advanced HIV may be due to ongoing MPXV replication, warranting aggressive medical countermeasures and immune optimization.

SUBMITTER: O'Shea J

PROVIDER: S-EPMC10965209 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Prolonged Mpox Disease in People With Advanced HIV: Characterization of Mpox Skin Lesions.

O'Shea Jesse J Zucker Jason J Stampfer Samuel S Cash-Goldwasser Shama S Minhaj Faisal S FS Dretler Alexandra A Cheeley Justin J Chaudhuri Shaoli S Gallitano Stephanie M SM Gunaratne Shauna S Parkinson Melissa M Epling Brian B Morcock David R DR Sereti Irini I Deleage Claire C

The Journal of infectious diseases 20240301 Supplement_2

We report 3 complicated and prolonged cases of mpox in people with advanced human immunodeficiency virus (HIV) not on antiretroviral therapy (ART) at mpox diagnosis. Multiple medical countermeasures were used, including prolonged tecovirimat treatment and immune optimization with ART initiation. Immunofluorescence of skin biopsies demonstrated a dense immune infiltrate of predominantly myeloid and CD8+ T cells, with a strong type I interferon local response. RNAscope detected abundant replicatio ...[more]

PMID: 38019806

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Project description:BackgroundThe 2022 global outbreak of mpox has significantly impacted health facilities, and necessitated additional infection prevention and control measures and alterations to clinic processes. Early identification of suspected mpox cases will assist in mitigating these impacts.ObjectiveWe aimed to develop and evaluate an artificial intelligence (AI)-based tool to differentiate mpox lesion images from other skin lesions seen in a sexual health clinic.MethodsWe used a data set with 2200 images, that included mpox and non-mpox lesions images, collected from Melbourne Sexual Health Centre and web resources. We adopted deep learning approaches which involved 6 different deep learning architectures to train our AI models. We subsequently evaluated the performance of each model using a hold-out data set and an external validation data set to determine the optimal model for differentiating between mpox and non-mpox lesions.ResultsThe DenseNet-121 model outperformed other models with an overall area under the receiver operating characteristic curve (AUC) of 0.928, an accuracy of 0.848, a precision of 0.942, a recall of 0.742, and an F1-score of 0.834. Implementation of a region of interest approach significantly improved the performance of all models, with the AUC for the DenseNet-121 model increasing to 0.982. This approach resulted in an increase in the correct classification of mpox images from 79% (55/70) to 94% (66/70). The effectiveness of this approach was further validated by a visual analysis with gradient-weighted class activation mapping, demonstrating a reduction in false detection within the background of lesion images. On the external validation data set, ResNet-18 and DenseNet-121 achieved the highest performance. ResNet-18 achieved an AUC of 0.990 and an accuracy of 0.947, and DenseNet-121 achieved an AUC of 0.982 and an accuracy of 0.926.ConclusionsOur study demonstrated it was possible to use an AI-based image recognition algorithm to accurately differentiate between mpox and common skin lesions. Our findings provide a foundation for future investigations aimed at refining the algorithm and establishing the place of such technology in a sexual health clinic.

Dataset Information

Prolonged Mpox Disease in People With Advanced HIV: Characterization of Mpox Skin Lesions.

Publications

Prolonged Mpox Disease in People With Advanced HIV: Characterization of Mpox Skin Lesions.

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