Diagnose und Therapie aktinischer Keratosen: Diagnosis and therapy of actinic keratosis.

Actinic keratosis (AK) is considered a chronic and recurring in situ skin neoplasia, with a possible transformation into invasive squamous cell carcinoma (SCC). Among others, predominant risk factors for development of AK are UV-light exposure and immunosuppression. Basal epidermal keratinocyte atypia (AK I) and proliferation (PRO Score) seem to drive malignant turnover, rather than clinical appearance of AK (Olsen I-III). Due to the invasiveness of punch biopsy, those histological criteria are not regularly assessed. Non-invasive imaging techniques, such as optical coherence tomography (OCT), reflectance confocal microscopy (RCM) and line-field confocal OCT (LC-OCT) are helpful to distinguish complex cases of AK, Bowen's disease and SCC. Moreover, LC-OCT can visualize the epidermis and the papillary dermis at cellular resolution, allowing real-time PRO Score assessment. The decision-making for implementation of therapy is still based on clinical risk factors, ranging from lesion- to field-targeted and ablative to non-ablative regimes, but in approximately 85% of the cases a recurrence of AK can be observed after a 1-year follow-up. The possible beneficial use of imaging techniques for a non-invasive follow-up of AK to detect recurrence or invasive progression early on should be subject to critical evaluation in further studies.

Diagnosis and therapy of actinic keratosis.

Actinic keratosis (AK) is considered a chronic and recurring in situ skin neoplasia, with a possible transformation into invasive squamous cell carcinoma (SCC). Among others, predominant risk factors for development of AK are UV-light exposure and immunosuppression. Basal epidermal keratinocyte atypia (AK I) and proliferation (PRO score) seem to drive malignant transformation, rather than clinical appearance of AK (Olsen I-III). Due to the invasiveness of punch biopsy, those histological criteria are not regularly assessed. Non-invasive imaging techniques, such as optical coherence tomography (OCT), reflectance confocal microscopy (RCM) and line-field confocal OCT (LC-OCT) are helpful to distinguish complex cases of AK, Bowen's disease, and SCC. Moreover, LC-OCT can visualize the epidermis and the papillary dermis at cellular resolution, allowing real-time PRO score assessment. The decision-making for implementation of therapy is still based on clinical risk factors, ranging from lesion- to field-targeted and ablative to non-ablative regimens, but in approximately 85% of the cases a recurrence of AK can be observed after a 1-year follow-up. The possible beneficial use of imaging techniques for a non-invasive follow-up of AK to detect recurrence or invasive progression early on should be subject to critical evaluation in further studies.

Differences in the annotation between facial images and videos for training an artificial intelligence for skin type determination.

BACKGROUND: The Grand-AID research project, consisting of GRANDEL-The Beautyness Company, the dermatology department of Augsburg University Hospital and the Chair of IT Infrastructure for Translational Medical Research at Augsburg University, is currently researching the development of a digital skin consultation tool that uses artificial intelligence (AI) to analyze the user's skin and ultimately perform a personalized skin analysis and a customized skin care routine. Training the AI requires annotation of various skin features on facial images. The central question is whether videos are better suited than static images for assessing dynamic parameters such as wrinkles and elasticity. For this purpose, a pilot study was carried out in which the annotations on images and videos were compared. MATERIALS AND METHODS: Standardized image sequences as well as a video with facial expressions were taken from 25 healthy volunteers. Four raters with dermatological expertise annotated eight features (wrinkles, redness, shine, pores, pigmentation spots, dark circles, skin sagging, and blemished skin) with a semi-quantitative and a linear scale in a cross-over design to evaluate differences between the image modalities and between the raters. RESULTS: In the videos, most parameters tended to be assessed with higher scores than in the images, and in some cases significantly. Furthermore, there were significant differences between the raters. CONCLUSION: The present study shows significant differences between the two evaluation methods using image or video analysis. In addition, the evaluation of the skin analysis depends on subjective criteria. Therefore, when training the AI, we recommend regular training of the annotating individuals and cross-validation of the annotation.

Effects of an immunosuppressive therapy on the efficacy of immune checkpoint inhibition in metastatic melanoma - An analysis of the prospective skin cancer registry ADOREG.

BACKGROUND: The impact of immunosuppressive therapy (IST) on immune-checkpoint inhibition (ICI) is unclear. METHODS: Patients with unresectable advanced melanoma (MM) treated with ICI in the years 2011-2020 were identified from the prospective multicenter German skin cancer registry ADOREG. Patients with IST within 60 days before, or within 30 days after start of ICI were compared to patients without IST. End points were disease control rate (DCR), overall survival (OS) and progression-free survival (PFS) determined by Kaplan-Meier method. Prognostic factors were evaluated in a Cox regression model. RESULTS: Of 814 patients treated with ICI, 73 (9%) received concomitant IST, mainly steroids. Patients with brain metastases (BM) received IST more frequently (n = 34/130 patients; 26%), than patients without BM (39/684 patients; 6%). In patients without BM, IST initiated before, but not IST initiated after start of ICI was significantly associated with worse PFS (univariate hazard ratio (HR) 2.59, 95% confidence interval (95%-CI) 1.07-6.28, p = 0.035; multivariate HR 3.48, 95%-CI 1.26-9.6, p = 0.016). There was no association between IST and OS or DCR. In patients with BM, IST initiated before, but not after start of ICI was significantly associated with worse OS (univariate HR 2.06, 95%-CI 1.07-3.95, p = 0.031; multivariate HR 5.91, 95%-CI 1.74-20.14, p = 0.004). There was no association between IST and PFS or DCR. CONCLUSION: Patients receiving IST 60 days before start of ICI showed a tendency to an impaired therapy outcome. IST initiated within 30 days after start of ICI, mainly due to early side effects, did not affect the efficacy of ICI therapy.

Line-field confocal optical coherence tomography, a novel non-invasive tool for the diagnosis of onychomycosis.

BACKGROUND AND OBJECTIVES: Onychomycosis is common and important to distinguish from other nail diseases. Rapid and accurate diagnosis is necessary for optimal patient treatment and outcome. Non-invasive diagnostic tools have increasing potential for nail diseases including onychomycosis. This study evaluated line-field confocal optical coherence tomography (LC-OCT) as a rapid non-invasive tool for diagnosing onychomycosis as compared to confocal laser scanning microscopy (CLSM), optical coherence tomography (OCT), and conventional methods. PATIENTS AND METHODS: In this prospective study 86 patients with clinically suspected onychomycosis and 14 controls were examined using LC-OCT, OCT, and CLSM. KOH-preparation, fungal culture, PCR, and histopathology were used as comparative conventional methods. RESULTS: LC-OCT had the highest sensitivity and negative predictive value of all methods used, closely followed by PCR and OCT. Specificity and positive predictive value of LC-OCT were as high as with CLSM, while OCT scored much lower. The gold standard technique, fungal culture, showed the lowest sensitivity and negative predictive value. Only PCR and culture allowed species differentiation. CONCLUSIONS: LC-OCT enables quick and non-invasive detection of onychomycosis, with advantages over CLSM and OCT, and similar diagnostic accuracy to PCR but lacking species differentiation. For accurate nail examination, LC-OCT requires well-trained and experienced operators.

Dynamic optical coherence tomography of chronic venous ulcers.

BACKGROUND: Chronic ulcers, especially venous leg ulcers, are a major burden on the healthcare system. To date there are only few non-invasive established procedures for evaluation of blood perfusion in wounds. Dynamic optical coherence tomography (D-OCT) provides images of the skin's superficial vascularisation. OBJECTIVES: This study aims to investigate if and how the D-OCT measurement of chronic wounds can provide new information about the vascularisation during the healing process. METHODS: We examined 16 venous ulcers over 16 weeks and evaluated the vessel morphology and density using D-OCT at the wound bed, borders, two centimetres adjacent to the wound und at non-ulcerated skin on the contralateral leg. RESULTS: In D-OCT scans clumps were unique and the most common vessel type in the wound area of venous ulcers, whereas lines and serpiginous vessels were the most common in non-ulcerated skin. At the wound border mottle and cluster patterns occurred more frequently. Healthy skin showed a significant increase of mesh pattern. Vessel density significantly increased at the wound area compared to non-ulcerated skin. During the healing process the wound border showed the most vascular changes while only an increase in curves was observed in the wound centre. Non-healing wounds had fewer dots and blobs at the borders, fewer dots, coils, clumps, lines and serpiginous vessels at the centre and fewer dots in adjacent skin. Temperature analysis showed higher temperatures in non-ulcerated skin, followed by the wound margin and centre. Non-healing wounds showed the lowest temperatures in the wound centre. CONCLUSIONS: These results highlight the non-invasive use of D-OCT for the examination and monitoring of wound healing in chronic venous ulcers. D-OCT imaging of blood vessels may offer the potential to detect disorders of wound healing at an early stage, differentiate ulcers of different genesis and to tailor more individualized, patient-oriented therapy.

S3 guideline "actinic keratosis and cutaneous squamous cell carcinoma" - update 2023, part 2: epidemiology and etiology, diagnostics, surgical and systemic treatment of cutaneous squamous cell carcinoma (cSCC), surveillance and prevention.

Actinic keratosis (AK) are common lesions in light-skinned individuals that can potentially progress to cutaneous squamous cell carcinoma (cSCC). Both conditions may be associated with significant morbidity and constitute a major disease burden, especially among the elderly. To establish an evidence-based framework for clinical decision making, the guideline "actinic keratosis and cutaneous squamous cell carcinoma" was updated and expanded by the topics cutaneous squamous cell carcinoma in situ (Bowen's disease) and actinic cheilitis. The guideline is aimed at dermatologists, general practitioners, ear nose and throat specialists, surgeons, oncologists, radiologists and radiation oncologists in hospitals and office-based settings, as well as other medical specialties, policy makers and insurance funds involved in the diagnosis and treatment of patients with AK and cSCC. A separate guideline exists for patients and their relatives. In this part, we will address aspects relating to epidemiology and etiology, diagnostics, surgical and systemic treatment of cutaneous squamous cell carcinoma (cSCC), surveillance and prevention.

Correlation of tumor PD-L1 expression in different tissue types and outcome of PD-1-based immunotherapy in metastatic melanoma - analysis of the DeCOG prospective multicenter cohort study ADOREG/TRIM.

BACKGROUND: PD-1-based immune checkpoint inhibition (ICI) is the major backbone of current melanoma therapy. Tumor PD-L1 expression represents one of few biomarkers predicting ICI therapy outcome. The objective of the present study was to systematically investigate whether the type of tumor tissue examined for PD-L1 expression has an impact on the correlation with ICI therapy outcome. METHODS: Pre-treatment tumor tissue was collected within the prospective DeCOG cohort study ADOREG/TRIM (CA209-578; NCT05750511) between February 2014 and May 2020 from 448 consecutive patients who received PD-1-based ICI for non-resectable metastatic melanoma. The primary study endpoint was best overall response (BOR), secondary endpoints were progression-free (PFS) and overall survival (OS). All endpoints were correlated with tumor PD-L1 expression (quantified with clone 28-8; cutoff ≥5%) and stratified by tissue type. FINDINGS: Tumor PD-L1 was determined in 95 primary tumors (PT; 36.8% positivity), 153 skin/subcutaneous (34.0% positivity), 115 lymph node (LN; 50.4% positivity), and 85 organ (40.8% positivity) metastases. Tumor PD-L1 correlated with BOR if determined in LN (OR = 0.319; 95% CI = 0.138-0.762; P = 0.010), but not in skin/subcutaneous metastases (OR = 0.656; 95% CI = 0.311-1.341; P = 0.26). PD-L1 positivity determined on LN metastases was associated with favorable survival (PFS, HR = 0.490; 95% CI = 0.310-0.775; P = 0.002; OS, HR = 0.519; 95% CI = 0.307-0.880; P = 0.014). PD-L1 positivity determined in PT (PFS, HR = 0.757; 95% CI = 0.467-1.226; P = 0.27; OS; HR = 0.528; 95% CI = 0.305-0.913; P = 0.032) was correlated with survival to a lesser extent. No relevant survival differences were detected by PD-L1 determined in skin/subcutaneous metastases (PFS, HR = 0.825; 95% CI = 0.555-1.226; P = 0.35; OS, HR = 1.083; 95% CI = 0.698-1.681; P = 0.72). INTERPRETATION: For PD-1-based immunotherapy in melanoma, tumor PD-L1 determined in LN metastases was stronger correlated with therapy outcome than that assessed in PT or organ metastases. PD-L1 determined in skin/subcutaneous metastases showed no outcome correlation and therefore should be used with caution for clinical decision making. FUNDING: Bristol-Myers Squibb (ADOREG/TRIM, NCT05750511); German Research Foundation (DFG; Clinician Scientist Program UMEA); Else Kröner-Fresenius-Stiftung (EKFS; Medical Scientist Academy UMESciA).

Dynamic Optical Coherence Tomography of Blood Vessels in Cutaneous Melanoma-Correlation with Histology, Immunohistochemistry and Dermoscopy.

Dermoscopy adds important information to the assessment of cutaneous melanoma, but the risk of progression is predicted by histologic parameters and therefore requires surgery and histopathologic preparation. Neo-vascularization is crucial for tumor progression and worsens prognosis. The aim of this study was the in vivo evaluation of blood vessel patterns in melanoma with dynamic optical coherence tomography (D-OCT) and the correlation with dermoscopic and histologic malignancy parameters for the risk assessment of melanoma. In D-OCT vessel patterns, shape, distribution and presence/type of branching of 49 melanomas were evaluated in vivo at three depths and correlated with the same patterns in dermoscopy and with histologic parameters after excision. In D-OCT, blood vessel density and atypical shapes (coils and serpiginous vessels) increased with higher tumor stage. The histologic parameters ulceration and Hmb45- and Ki67-positivity increased, whereas regression, inflammation and PD-L1-positivity decreased with risk. CD31, VEGF and Podoplanin correlated with D-OCT vasculature findings. B-RAF mutation status had no influence. Due to pigment overlay and the summation effect, the vessel evaluation in dermoscopy and D-OCT did not correlate well. In summary, atypical vessel patterns in melanoma correlate with histologic parameters for risk for metastases. Tumor vasculature can be noninvasively assessed using D-OCT before surgery.

Artificial intelligence-based PRO score assessment in actinic keratoses from LC-OCT imaging using Convolutional Neural Networks.

BACKGROUND AND OBJECTIVES: The histological PRO score (I-III) helps to assess the malignant potential of actinic keratoses (AK) by grading the dermal-epidermal junction (DEJ) undulation. Line-field confocal optical coherence tomography (LC-OCT) provides non-invasive real-time PRO score quantification. From LC-OCT imaging data, training of an artificial intelligence (AI), using Convolutional Neural Networks (CNNs) for automated PRO score quantification of AK in vivo may be achieved. PATIENTS AND METHODS: CNNs were trained to segment LC-OCT images of healthy skin and AK. PRO score models were developed in accordance with the histopathological gold standard and trained on a subset of 237 LC-OCT AK images and tested on 76 images, comparing AI-computed PRO score to the imaging experts' visual consensus. RESULTS: Significant agreement was found in 57/76 (75%) cases. AI-automated grading correlated best with the visual score for PRO II (84.8%) vs. PRO III (69.2%) vs. PRO I (66.6%). Misinterpretation occurred in 25% of the cases mostly due to shadowing of the DEJ and disruptive features such as hair follicles. CONCLUSIONS: The findings suggest that CNNs are helpful for automated PRO score quantification in LC-OCT images. This may provide the clinician with a feasible tool for PRO score assessment in the follow-up of AK.

Innovation in Actinic Keratosis Assessment: Artificial Intelligence-Based Approach to LC-OCT PRO Score Evaluation.

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.