{"id":378502,"date":"2024-05-14T00:01:00","date_gmt":"2024-05-13T22:01:00","guid":{"rendered":"https:\/\/medizinonline.com\/?p=378502"},"modified":"2024-05-09T18:08:38","modified_gmt":"2024-05-09T16:08:38","slug":"ai-supported-risk-classification-based-on-lc-oct-images","status":"publish","type":"post","link":"https:\/\/medizinonline.com\/en\/ai-supported-risk-classification-based-on-lc-oct-images\/","title":{"rendered":"AI-supported risk classification based on LC-OCT images"},"content":{"rendered":"\n

Certain morphological features of actinic keratoses (AK) are considered predictive for the development of invasive squamous cell carcinoma. The classification into PRO scores I-III is based on this, which represents three risk levelsfor the risk of progression of AK lesions. A study published in 2023 shows that an AI-supported automated PRO score classification based on LC-OCT image data has the potential to facilitate the diagnosis and follow-up of AK in the future. <\/strong><\/p>\n\n\n\n

One aim of the study by Thamm et al. was to train convolutional neural networks so that they can be used for automated epidermal segmentation in confocal line-field optical coherence tomography (LC-OCT) image datasets to perform real-time assessment of the epidermal and dermal pathology of AK lesions [1]. AK are considered to be squamous cell carcinomas in situ, which can develop into invasive cutaneous squamous cell carcinomas (SCC). Estimating the risk of progression of AK lesions using LC-OCT imaging offers advantages over conventional histology, as it is a non-invasive, high-tech procedure. Macroscopically, AK lesions appear as pink to brown patches in sun-exposed areas of skin and are usually accompanied by hyperkeratosis [2]. While in AK keratinocyte atypia is restricted to the epidermis, in contrast, loss of the dermoepidermal junction (DEJ) can be observed in SCC, which defines its invasive proliferation [3]. Although the DEJ remains intact in AK lesions, its basal growth patterns change in the course of the malignant transformation process [4]. Assessing which AKs have a high risk of malignant transformation is becoming increasingly important. Therefore, a histological classification was developed with the PRO score, which classifies AK based on changes in the area of basal proliferation [4,5]. PRO III AK lesions are associated with a higher risk of developing invasive SCC than PRO II or PRO I. <\/p>\n\n

Evaluation of image material using a deep learning approach<\/h3>\n\n

Image material from line-field confocal optical coherence tomography (LC-OCT) [1,5] serves as the basis for the PRO score I-III (Fig. 1)<\/strong>. LC-OCT makes it possible to examine a skin change suspected of being a tumor without having to take an invasive tissue sample. The following characteristics are decisive for the classification of transformation risk: <\/p>\n\n