ArticleCancers2023
Innovation in Actinic Keratosis Assessment: Artificial Intelligence-Based Approach to LC-OCT PRO Score Evaluation.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Line-Field Confocal Optical Coherence Tomography Assessment of Dermal-Epidermal Junction in Actinic Keratosis and Skin Cancer.International journal of dermatology · 2026Article
- Digital Dermatology.Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2026Review
- AI-assisted basal cell carcinoma diagnosis with LC-OCT: A multicentric retrospective study.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026Article
- Non-Invasive Assessment of Treatment Response in Actinic Keratosis: A Clinically Oriented Multimodal Review.Cancers · 2026Review
- Clinical Olsen Grading Does Not Reflect Basal Growth in Actinic Keratoses: Two-Center Retrospective Analysis.Cancers · 2025Article
- Systematic Review of Line-Field Confocal Optical Coherence Tomography for Diagnosing Pre-Malignant and Malignant Keratinocytic Lesions: Optimising the Workflow.Diagnostics (Basel, Switzerland) · 2025Review
- OCT in Oncology and Precision Medicine: From Nanoparticles to Advanced Technologies and AI.Bioengineering (Basel, Switzerland) · 2025Review
- Optical super-high magnification dermoscopy of benign and malignant melanocytic lesions in correlation with histopathology.Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2025Observational
- Evaluating facial dermis aging in healthy Caucasian females with LC-OCT and deep learning.Scientific reports · 2024Article
- [Update in the diagnosis and treatment of actinic keratosis].Dermatologie (Heidelberg, Germany) · 2024Review
- Epidemiology and Risk Factors of Actinic Keratosis. What is New for The Management for Sun-Damaged Skin.Dermatology practical & conceptual · 2024Review
- Clinical and Dermoscopic Diagnosis of Actinic Keratosis.Dermatology practical & conceptual · 2024Review
- An Update on Non-Invasive Skin Imaging Techniques in Actinic Keratosis-A Narrative Review.Medicina (Kaunas, Lithuania) · 2024Review
- Review
- Line-Field Confocal Optical Coherence Tomography (LC-OCT) for Skin Imaging in Dermatology.Life (Basel, Switzerland) · 2023Article
- The Promise of Semantic Segmentation in Detecting Actinic Keratosis Using Clinical Photography in the Wild.Cancers · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Actinic keratosis (AK) is a common skin cancer in situ that can progress to invasive SCC. Line-field confocal optical coherence tomography (LC-OCT) has emerged as a non-invasive imaging technique that can aid in diagnosis. Recently, machine-learning algorithms have been developed that can automatically assess the PRO score of AKs based on the dermo-epidermal junction's (DEJ's) protrusion on LC-OCT images. A dataset of 19.898 LC-OCT images from 80 histologically confirmed AK lesions was used to test the performance of a previous validated artificial intelligence (AI)-based LC-OCT assessment algorithm. AI-based PRO score assessment was compared to the imaging experts' visual score. Additionally, undulation of the DEJ, the number of protrusions detected within the image, and the maximum depth of the protrusions were computed. Our results show that AI-automated PRO grading is highly comparable to the visual score, with an agreement of 71.3% for the lesions evaluated. Furthermore, this AI-based assessment was significantly faster than the regular visual PRO score assessment. The results confirm our previous findings of the pilot study in a larger cohort that the AI-based grading of LC-OCT images is a reliable and fast tool to optimize the efficiency of visual PRO score grading. This technology has the potential to improve the accuracy and speed of AK diagnosis and may lead to better clinical outcomes for patients.
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