Illuminating characteristic patterns of inflammatory dermatoses: A comprehensive dual-imaging approach using Optical coherence tomography and Line-field confocal optical coherence tomography.

BACKGROUND: Inflammatory skin diseases, such as psoriasis, atopic eczema, and contact dermatitis pose diagnostic challenges due to their diverse clinical presentations and the need for rapid and precise diagnostic assessment. OBJECTIVE: While recent studies described non-invasive imaging devices such as Optical coherence tomography and Line-field confocal OCT (LC-OCT) as possible techniques to enable real-time visualization of pathological features, a standardized analysis and validation has not yet been performed. METHODS: One hundred forty lesions from patients diagnosed with atopic eczema (57), psoriasis (50), and contact dermatitis (33) were imaged using OCT and LC-OCT. Statistical analysis was employed to assess the significance of their characteristic morphologic features. Additionally, a decision tree algorithm based on Gini's coefficient calculations was developed to identify key attributes and criteria for accurately classifying the disease groups. RESULTS: Descriptive statistics revealed distinct morphologic features in eczema, psoriasis, and contact dermatitis lesions. Multivariate logistic regression demonstrated the significance of these features, providing a robust differentiation between the three inflammatory conditions. The decision tree algorithm further enhanced classification accuracy by identifying optimal attributes for disease discrimination, highlighting specific morphologic criteria as crucial for rapid diagnosis in the clinical setting. CONCLUSION: The combined approach of descriptive statistics, multivariate logistic regression, and a decision tree algorithm provides a thorough understanding of the unique aspects associated with each inflammatory skin disease. This research offers a practical framework for lesion classification, enhancing the interpretability of imaging results for clinicians.

Unmet Needs in Darier's Disease from a Patient's Perspective: Lessons Learnt from the German Registry.

The MDHHgermany registry was initiated to characterize the "real-life" situation of affected individuals with Darier's disease (DD; Morbus Darier, MD) and Hailey-Hailey disease (HH), including their treatment and healthcare. To gain deeper insights into medical care of patients with DD, various aspects such as demographics, subjective symptoms, patient satisfaction with medical care, past and current therapies were explored. Patients with diagnosed DD were included. Subjective symptoms such as itch, pain and burning sensation were assessed. Individual therapy goals were recorded and patients assessed previous/current therapies along with satisfaction of medical care and treatment. A total of 55 patients were recruited; 47 patients were eligible for the analysis. Pruritus was rated the most bothersome symptom. Some 42.6% had not received systemic treatment so far or systemic therapies were rated ineffective (32.6%). Most commonly oral retinoids were prescribed, followed by corticosteroids. Patient satisfaction with medical care and treatment proved to be mediocre. This "real-life" data show an alarming unmet need regarding patients' satisfaction with medical care and treatment, evidenced by the reported lack of disease control. Further studies and interventions are needed to improve the spectrum of available therapies. MDHHgermany provides a foundational platform for future clinical trials, epidemiological studies, and pathophysiological analyses.

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.

Risk of pneumothorax in Birt-Hogg-Dubé syndrome during pregnancy and birth.

Birt-Hogg-Dubé syndrome (BHDS) is a genetic disorder characterized by fibrofolliculomas, renal cell cancer and lung cysts. Patients are at risk to develop pneumothorax but the magnitude of this risk during pregnancy is unknown. Information was obtained from 46 women with BHDS that had at least one pregnancy (BHDS-with preg), 18 female BHDS relatives without pregnancies (BHDS-no preg) and 25 non-BHDS female relatives with at least one pregnancy (noBHDS-with preg). In total, 77 pneumothoraces occurred in the BHDS-with preg group (mean 1.7/patient) and 11 in the BHDS-no preg group. Comparison of patient years for the first two groups showed pneumothorax incidence rates of 0.054 and 0.016, respectively. The incidence rate difference was significant [0.038 (CI 0.02-0.057), value of p-value 0.0001]. This difference is not caused by an increased number of patients with pneumothorax but by an increased number of pneumothoraces per patient. Pregnancy in BHDS therefore might be a risk factor for multiple pneumothoraces.

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.

Update of penetrance estimates in Birt-Hogg-Dubé syndrome.

BACKGROUND: Birt-Hogg-Dubé (BHD) syndrome is a rare genetic syndrome caused by pathogenic or likely pathogenic germline variants in the FLCN gene. Patients with BHD syndrome have an increased risk of fibrofolliculomas, pulmonary cysts, pneumothorax and renal cell carcinoma. There is debate regarding whether colonic polyps should be added to the criteria. Previous risk estimates have mostly been based on small clinical case series. METHODS: A comprehensive review was conducted to identify studies that had recruited families carrying pathogenic or likely pathogenic variants in FLCN. Pedigree data were requested from these studies and pooled. Segregation analysis was used to estimate the cumulative risk of each manifestation for carriers of FLCN pathogenic variants. RESULTS: Our final dataset contained 204 families that were informative for at least one manifestation of BHD (67 families informative for skin manifestations, 63 for lung, 88 for renal carcinoma and 29 for polyps). By age 70 years, male carriers of the FLCN variant have an estimated 19% (95% CI 12% to 31%) risk of renal tumours, 87% (95% CI 80% to 92%) of lung involvement and 87% (95% CI 78% to 93%) of skin lesions, while female carriers had an estimated 21% (95% CI 13% to 32%) risk of renal tumours, 82% (95% CI 73% to 88%) of lung involvement and 78% (95% CI 67% to 85%) of skin lesions. The cumulative risk of colonic polyps by age 70 years old was 21% (95% CI 8% to 45%) for male carriers and 32% (95% CI 16% to 53%) for female carriers. CONCLUSIONS: These updated penetrance estimates, based on a large number of families, are important for the genetic counselling and clinical management of BHD syndrome.

Delayed diagnosis of Birt-Hogg-Dubé syndrome might be aggravated by gender bias.

Background: Birt-Hogg-Dubé syndrome is a rare genetic tumor syndrome characterized by renal cell cancer, lung bullae, pneumothorax, and fibrofolliculoma. Patients with such orphan tumor disorders are at risk of not receiving a timely diagnosis. In the present, gender-sensitive study, we analyzed the delay between onset of symptoms and diagnosis of Birt-Hogg-Dubé syndrome. Methods: Clinical data of 158 patients from 91 unrelated families were collected. FLCN mutation testing was performed in index patients and family members. Findings: The occurrence of the first symptom (fibrofolliculoma, pneumothorax or renal cell cancer) was rarely followed by a timely diagnosis of Birt-Hogg-Dubé syndrome and did so significantly less often in female (1.3%) compared to male (11.4%) patients (chi-square 6.83, p-value 0.009). Only 17 out of 39 renal cell cancers (7/17 female, 10/22 male patients) were promptly recognized as a symptom of Birt-Hogg-Dubé syndrome. Patients in which renal cell cancer was initially not recognized as a symptom of Birt-Hogg-Dubé syndrome waited 9.7 years (females SD 9.2, range 1-29) and 8.8 years (males, SD 4.1, range 2-11) for their diagnosis, respectively. Four (three female, one male) patients developed renal cell cancer twice before the genetic tumor syndrome was diagnosed. The delay between fibrofolliculoma or pneumothorax as a first symptom and diagnosis of Birt-Hogg-Dubé syndrome was considerable but not significantly different between females and males (18.1/17.19 versus 16.1/18.92 years). Furthermore, 73 patients were only diagnosed due to family history (delay 15.1 years in females and 17.4 years in males). Interpretation: The delay between onset of symptoms and diagnosis of Birt-Hogg-Dubé syndrome can be substantial and gender-dependent, causing considerable health risks for patients and their families. It is therefore important to create more awareness of Birt-Hogg-Dubé syndrome and resolve gender biases in diagnostic work-up. Funding: None declared.

Ex vivo confocal laser scanning microscopy: A diagnostic technique for easy real-time evaluation of benign and malignant skin tumours.

Ex vivo confocal laser scanning microscopy (ex vivo CLSM) is a novel diagnostic tool for a quick bedside evaluation of freshly excised tissue, comparable to histology. We aimed to assess the sensitivity and specificity of ex vivo CLSM in detecting malignant features, to validate its reliability in identifying various skin tumours based on a combination of confocal features and to evaluate the digital staining mode (DS). One-hundred twenty freshly excised skin samples from 91 patients were evaluated. Each lesion was screened for the presence of 23 predefined confocal criteria with ex vivo CLSM, followed by a histopathological examination. The diagnostic agreement between ex vivo CLSM and histology was 89.2%. The diagnostic accuracy of ex vivo CLSM in detecting malignancy reached a sensitivity of 98% and a specificity of 76%. Ex vivo CLSM enabled a rapid identification of the most common skin tumours, the tumour dignity and cytological features. The DS demonstrated a close resemblance to conventional histopathology.

Line-Field Confocal Optical Coherence Tomography: A New Tool for the Differentiation between Nevi and Melanomas?

Until now, the clinical differentiation between a nevus and a melanoma is still challenging in some cases. Line-field confocal optical coherence tomography (LC-OCT) is a new tool with the aim to change that. The aim of the study was to evaluate LC-OCT for the discrimination between nevi and melanomas. A total of 84 melanocytic lesions were examined with LC-OCT and 36 were also imaged with RCM. The observers recorded the diagnoses, and the presence or absence of the 18 most common imaging parameters for melanocytic lesions, nevi, and melanomas in the LC-OCT images. Their confidence in diagnosis and the image quality of LC-OCT and RCM were evaluated. The most useful criteria, the sensitivity and specificity of LC-OCT vs. RCM vs. histology, to differentiate a (dysplastic) nevus from a melanoma were analyzed. Good image quality correlated with better diagnostic performance (Spearman correlation: 0.4). LC-OCT had a 93% sensitivity and 100% specificity compared to RCM (93% sensitivity, 95% specificity) for diagnosing a melanoma (vs. all types of nevi). No difference in performance between RCM and LC-OCT was observed (McNemar's p value = 1). Both devices falsely diagnosed dysplastic nevi as non-dysplastic (43% sensitivity for dysplastic nevus diagnosis). The most significant criteria for diagnosing a melanoma with LC-OCT were irregular honeycombed patterns (92% occurrence rate; 31.7 odds ratio (OR)), the presence of pagetoid spread (89% occurrence rate; 23.6 OR) and the absence of dermal nests (23% occurrence rate, 0.02 OR). In conclusion LC-OCT is useful for the discrimination between melanomas and nevi.

Line-Field Confocal Optical Coherence Tomography Increases the Diagnostic Accuracy and Confidence for Basal Cell Carcinoma in Equivocal Lesions: A Prospective Study.

Diagnosing clinically unclear basal cell carcinomas (BCCs) can be challenging. Line-field confocal optical coherence tomography (LC-OCT) is able to display morphological features of BCC subtypes with good histological correlation. The aim of this study was to investigate the accuracy of LC-OCT in diagnosing clinically unsure cases of BCC compared to dermoscopy alone and in distinguishing between superficial BCCs and other BCC subtypes. Moreover, we addressed pitfalls in false positive cases. We prospectively enrolled 182 lesions of 154 patients, referred to our department to confirm or to rule out the diagnosis of BCC. Dermoscopy and LC-OCT images were evaluated by two experts independently. Image quality, LC-OCT patterns and criteria, diagnosis, BCC subtype, and diagnostic confidence were assessed. Sensitivity and specificity of additional LC-OCT were compared to dermoscopy alone for identifying BCC in clinically unclear lesions. In addition, key LC-OCT features to distinguish between BCCs and non-BCCs and to differentiate superficial BCCs from other BCC subtypes were determined by linear regressions. Diagnostic confidence was rated as "high" in only 48% of the lesions with dermoscopy alone compared to 70% with LC-OCT. LC-OCT showed a high sensitivity (98%) and specificity (80%) compared to histology, and these were even higher (100% sensitivity and 97% specificity) in the subgroup of lesions with high diagnostic confidence. Interobserver agreement was nearly perfect (95%). The combination of dermoscopy and LC-OCT reached a sensitivity of 100% and specificity of 81.2% in all cases and increased to sensitivity of 100% and specificity of 94.9% in cases with a high diagnostic confidence. The performance of LC-OCT was influenced by the image quality but not by the anatomical location of the lesion. The most specific morphological LC-OCT criteria in BCCs compared to non-BCCs were: less defined dermoepidermal junction (DEJ), hyporeflective tumor lobules, and dark rim. The most relevant features of the subgroup of superficial BCCs (sBCCs) were: string of pearls pattern and absence of epidermal thinning. Our diagnostic confidence, sensitivity, and specificity in detecting BCCs in the context of clinically equivocal lesions significantly improved using LC-OCT in comparison to dermoscopy only. Operator training for image acquisition is fundamental to achieve the best results. Not only the differential diagnosis of BCC, but also BCC subtyping can be performed at bedside with LC-OCT.

In vivo examination of healthy human skin after short-time treatment with moisturizers using confocal Raman spectroscopy and optical coherence tomography: Preliminary observations.

Skin is our barrier against environmental damage. Moisturizers are widely used to increase hydration and barrier integrity of the skin; however, there are contrasting observations on their in vivo effects in real-life settings. In cosmetic studies, corneometers and tewameters are traditionally used to assess skin hydration. In this study, two novel noninvasive diagnostic techniques, optical coherence tomography (OCT) and confocal Raman spectroscopy, were used to analyze stratum corneum and epidermal thickness (ET), water content, blood flow in function of depth, skin roughness, attenuation coefficient, natural moisturizing factor, ceramides and free fatty acids, cholesterol, urea, and lactates in 20 female subjects aged between 30 and 45 before and after 2 weeks application of a commercially available moisturizing lotion on one forearm. The untreated forearm served as control. A third measurement was conducted 1 week after cessation of moisturizing to verify whether the changes in the analyzed parameters persisted. We noticed a reduction in skin roughness, an increase in ceramides and free fatty acids and a not statistically significant increase in ET. As a conclusion, short time moisturizing appears insufficient to provide significant changes in skin morphology and composition, as assessed by OCT and RS. Novel noninvasive imaging methods are suitable for the evaluation of skin response to topical moisturizers. Further studies on larger sample size and longer treatment schedules are needed to analyze changes under treatment with moisturizers and to standardize the use of novel noninvasive diagnostic techniques.

Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy.

Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the forefront of artificial intelligence (AI) revolution, conventional pathology, which commonly relies on examination of tissue samples on a glass slide, is falling behind in leveraging this technology. On the other hand, ex vivo confocal laser scanning microscopy (ex vivo CLSM), owing to its digital workflow features, has a high potential to benefit from integrating AI tools into the assessment and decision-making process. Aim of this work was to explore a preliminary application of CNN in digitally stained ex vivo CLSM images of cutaneous squamous cell carcinoma (cSCC) for automated detection of tumor tissue. Thirty-four freshly excised tissue samples were prospectively collected and examined immediately after resection. After the histologically confirmed ex vivo CLSM diagnosis, the tumor tissue was annotated for segmentation by experts, in order to train the MobileNet CNN. The model was then trained and evaluated using cross validation. The overall sensitivity and specificity of the deep neural network for detecting cSCC and tumor free areas on ex vivo CLSM slides compared to expert evaluation were 0.76 and 0.91, respectively. The area under the ROC curve was equal to 0.90 and the area under the precision-recall curve was 0.85. The results demonstrate a high potential of deep learning models to detect cSCC regions on digitally stained ex vivo CLSM slides and to distinguish them from tumor-free skin.

[Advances in optical coherence tomography]. / Neues von der optischen Kohärenztomographie.

Optical coherence tomography (OCT) has been able to establish itself in recent years not only in academic-scientific, but also in everyday dermatological practice. Its focus lies on epithelial tumors of the skin, which can be diagnosed intuitively and within a few seconds. Thus, basal cell carcinomas, actinic keratoses, and different stages of field cancerization can be diagnosed and monitored for response to therapy or possible recurrence. This often helps to avoid invasive sample extraction. Recently, the field of OCT and its latest advancement, dynamic OCT (D-OCT), has been expanded to include non-oncologic dermatological diseases. This encompasses inflammatory dermatoses and the analysis of physiological skin parameters such as hydration. Thanks to automated vascular imaging and the measurement of objective parameters such as epidermal thickness, blood flow at depth, optical attenuation coefficient, and skin roughness, more and more characteristics of the skin can be studied in a noninvasive and standardized way. New potential areas of application are eczema, contact allergic dermatitis, psoriasis, rosacea, telangiectasia, acute and chronic wounds, melasma and nevus flammeus but also melanocytic lesions.

In-Vivo LC-OCT Evaluation of the Downward Proliferation Pattern of Keratinocytes in Actinic Keratosis in Comparison with Histology: First Impressions from a Pilot Study.

It is known that actinic keratoses (AKs) can progress to invasive squamous cell carcinoma (SCC). The histological PRO grading of AKs is based on the growth pattern of basal keratinocytes and relates to their progression risk. AKs can be non-invasively characterized by line-field confocal optical coherence tomography (LC-OCT). The aim of the study was to define criteria for an LC-OCT grading of AKs based on the PRO classification and to correlate it with its histological counterpart. To evaluate the interobserver agreement for the LC-OCT PRO classification, fifty AKs were imaged by LC-OCT and biopsied for histopathology. PRO histological grading was assessed by an expert consensus, while two evaluator groups separately performed LC-OCT grading on vertical sections. The agreement between LC-OCT and histological PRO grading was 75% for all lesions (weighted kappa 0.66, 95% CI 0.48-0.83, p ≤ 0.001) and 85.4% when comparing the subgroups PRO I vs. PRO II/III (weighted kappa 0.64, 95% CI 0.40-0.88, p ≤ 0.001). The interobserver agreement for LC-OCT was 90% (Cohen's kappa 0.84, 95% CI 0.71-0.91, p ≤ 0.001). In this pilot study, we demonstrated that LC-OCT is potentially able to classify AKs based on the basal growth pattern of keratinocytes, in-vivo reproducing the PRO classification, with strong interobserver agreement and a good correlation with histopathology.