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.

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.

Forgotten Joint Score in THA: Comparing the Direct Anterior Approach to Posterior Approach.

BACKGROUND: The direct anterior approach (DAA) in total hip arthroplasty (THA) has gained popularity because of potential decreased postoperative pain and quicker recovery after surgery in comparison to the posterior approach (PA). With a growing focus on patient-reported outcome (PRO) measurements after surgery, we sought to determine if one approach led to better PRO scores as determined by the Forgotten Joint Score-12 (FJS-12) questionnaire. METHODS: A retrospective chart review of primary THAs between September 2016 and September 2019 at a single academic hospital was conducted. Demographic and clinical data in addition to FJS-12 scores were collected. Two groups were created based on THA approach. Frequency rates, means, and standard deviations were used to describe baseline patient characteristics. Differences in demographic data were accounted for using linear regression models. RESULTS: A total of 1469 cases were identified, with 830 using the DAA and 639 the PA. Significant demographic differences were observed between the 2 groups. However, when controlling for this, there were no differences in FJS-12 scores between approaches at 1 and 1.75 years (P = .232 and P = .486, respectively). At 12 weeks, DAA patients had higher satisfaction (59.21 vs 46.8; P = .006). When controlling for surgeon case volume, no differences in FJS-12 were observed at any of the time points (P = .536, P = .452, and P = .967, respectively) CONCLUSION: DAA THA patients trended toward better PRO scores than their PA counterparts. However, when controlling for surgeon case volume, no differences were observed, which suggests that surgeon case volume and experience have an important effect on patient satisfaction and FJS-12 scores.

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.