Improved diagnosis by automated macro‐ and micro‐anatomical region mapping of skin photographs

Background: The exact location of skin lesions is key in clinical dermatology. On one hand, it supports differential diagnosis (DD) since most skin conditions have specific predilection sites. On the other hand, location matters for dermatosurgical interventions. In practice, lesion evaluation is not well standardized and anatomical descriptions vary or lack altogether. Automated determination of anatomical location could benefit both situations. Objective: Establish an automated method to determine anatomical regions in clinical patient pictures and evaluate the gain in DD performance of a deep learning model (DLM) when trained with lesion locations and images. Methods: Retrospective study based on three datasets: macro-anatomy for the main body regions with 6000 patient pictures partially labelled by a student, micro-anatomy for the ear region with 182 pictures labelled by a student and DD with 3347 pictures of 16 diseases determined by dermatologists in clinical settings. For each dataset, a DLM was trained and evaluated on an independent test set. The primary outcome measures were the precision and sensitivity with 95% CI. For DD, we compared the performance of a DLM trained with lesion pictures only with a DLM trained with both pictures and locations. Results: The average precision and sensitivity were 85% (CI 84-86), 84% (CI 83-85) for macro-anatomy, 81% (CI 80-83), 80% (CI 77-83) for micro-anatomy and 82% (CI 78-85), 81% (CI 77-84) for DD. We observed an improvement in DD performance of 6% (McNemar test P-value 0.0009) for both average precision and sensitivity when training with both lesion pictures and locations. Conclusion: Including location can be beneficial for DD DLM performance. The proposed method can generate body region maps from patient pictures and even reach surgery relevant anatomical precision, e.g. the ear region. Our method enables automated search of large clinical databases and make targeted anatomical image retrieval possible

The impact of gender and sex in psoriasis: What to be aware of when treating women with psoriasis

Background:. Psoriasis is a common chronic inflammatory skin disease with an exceptionally high burden for women. Objective:. Sex-dependent differences in disease manifestation, severity, treatment choices, subjective disease perception, and the impact on quality of life and risk factors are described and comprehensively discussed. Methods:. A literature search was conducted using MEDLINE (PubMed) and the Cochrane Library for systematic reviews to investigate the challenges in treating women with psoriasis. Results and conclusions:. The incidence, prevalence, and manifestation of psoriasis of the skin are similar between different sexes. Genetic and environmental factors such as obesity and metabolic syndrome are risk factors and are not equally relevant or pronounced in women and men. Overall, women have a lower disease severity measured by the Psoriasis Area Severity Index, which is associated with a higher impairment of their life quality measured by the Dermatology Life Quality Index compared with men. In addition, women with psoriasis are more likely to have depression than men. Hormonal factors affect psoriasis, with a correlation of high estrogen levels and improvement of psoriasis. Data regarding differences in prescribing patterns of systemic treatments and the severity of psoriasis are not entirely consistent. Registry studies show that men tend to have more severe psoriasis and, in some cases, are prescribed systemic therapies more frequently. Women tend to respond better to systemic treatments and to experience more adverse events. Treatment options are the same for both sexes, except during pregnancy and lactation. Various treatment options are contraindicated due to fear of fetal or neonate harm and lack of data. Topical steroids can be prescribed with a high degree of safety during pregnancy. For other topical therapies (calcineurin inhibitors and vitamin D analogs), no studies of adverse effects in pregnancy are available, and safety data mainly stem from studies examining effects after systemic administration. Antitumor necrosis factor monoclonal antibodies (except for certolizumab pegol) have been associated with a possible increased risk of preterm birth, low gestational age, and cesarean deliveries. Prospective data on the safety of biologics other than antitumor necrosis factor-alpha antibodies to accurately assess whether novel biologics (eg, anti-interleukin 17, 12/23, 23) can be used for systemic therapy in pregnancy are lacking or currently being conducted