Dermatologists' attitude towards psoriasis treatment during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic introduced new challenges in several dimensions in healthcare services. Herein, we describe the real-life strategies and therapeutic options adopted by dermatologists regarding their patients with psoriasis being treated with or with an indication for systemic therapy during the first COVID-19 lockdown period in Portugal. METHODS: The study involves a web-based survey on the clinical management of systemic therapy for psoriasis during the COVID-19 pandemic administered to Portuguese dermatologists. The survey consisted of 55 questions (4 open-ended questions; 51 closed-ended questions), grouped into 6 sections. RESULTS: A total of 60 dermatologists voluntarily participated in this survey. Nearly 63% of the participants opted for suspending biologics during the COVID-19 lockdown period and 23.3% increased the time between drug administrations. Eighty percent of the participants agreed that biologics did not change the probability of acquiring COVID-19 and 58.4% believed that these drugs decreased or did not change the severity of the disease. Approximately one-third of the participants opted not to prescribe a biological agent in patients despite clinical indication over the duration of the pandemic. Nearly 25% of the participants opted for suspending traditional immunosuppressant administration. Virtual appointments were an option for 93.3% of the participants. CONCLUSION: The COVID-19 pandemic has significantly affected the management of patients with psoriasis being treated with or with an indication for systemic therapy. Some of the decisions made during the first lockdown period were contrary to what we know today. These decisions might have had a significant impact on patients' quality of life and on future therapeutic success. An adequate interpretation and analysis of the available data will be extremely important to an insightful adaptation of the clinical practice in future confinement or restrictive scenarios.

PH² - a dermoscopic image database for research and benchmarking.

The increasing incidence of melanoma has recently promoted the development of computer-aided diagnosis systems for the classification of dermoscopic images. Unfortunately, the performance of such systems cannot be compared since they are evaluated in different sets of images by their authors and there are no public databases available to perform a fair evaluation of multiple systems. In this paper, a dermoscopic image database, called PH², is presented. The PH² database includes the manual segmentation, the clinical diagnosis, and the identification of several dermoscopic structures, performed by expert dermatologists, in a set of 200 dermoscopic images. The PH² database will be made freely available for research and benchmarking purposes.

A system for the detection of pigment network in dermoscopy images using directional filters.

A pigment network is one of the most important dermoscopic structures. This paper describes an automatic system that performs its detection in dermoscopy images. The proposed system involves a set of sequential steps. First, a preprocessing algorithm is applied to the dermoscopy image. Then, a bank of directional filters and a connected component analysis are used in order to detect the "lines" of the pigment network. Finally, features are extracted from the detected network and used to train an AdaBoost algorithm to classify each lesion regarding the presence of the pigment network. The algorithm was tested on a dataset of 200 medically annotated images from the database of Hospital Pedro Hispano (Matosinhos), achieving a sensitivity = 91.1% and a specificity = 82.1%.

Detecting the pigment network in dermoscopy images: a directional approach.

Several algorithms have been recently proposed for the analysis of dermoscopy images and the detection of melanomas. However, the pigment network is not considered in most of these works, although this cue plays a major role in clinical diagnosis routines. This paper proposes an algorithm for the detection of the pigment network. The algorithm is based on a bank of directional filters (difference of Gaussians) and explores color, directionality and topological properties of the network.

Comparison of segmentation methods for automatic diagnosis of dermoscopy images.

Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the prospects of automatic image analysis methods for dermoscopy, both to provide quantitative information about a lesion, which can be of relevance for the clinician, and as a stand alone early warning tool. The effective implementation of such a tool could lead to a reduction in the number of cases selected for exeresis, with obvious benefits both to the patients and to the health care system. The standard approach in automatic dermoscopic image analysis has usually three stages: (i) image segmentation, (ii) feature extraction and feature selection, (iii) lesion classification. This paper presents a comparison of segmentation methods applied to 50 dermoscopic image analysis, along with a clinical evaluation of each segmentation result performed by an experienced dermatologist.