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Importance: Clinical estimation of hair density has an important role in assessing and tracking the severity and progression of alopecia, yet to the authors' knowledge, no automation currently exists for this process. While some algorithms have been developed to assess alopecia presence on a binary level, their scope has been limited by focusing on a re-creation of the Severity of Alopecia Tool (SALT) score for alopecia areata (AA). Yet hair density loss is common to all alopecia forms, and an evaluation of that loss is used in established scoring systems for androgenetic alopecia (AGA), central centrifugal cicatricial alopecia (CCCA), and many more., Objective: To develop and validate a new model, HairComb, to automatically compute the percentage hair loss from images regardless of alopecia subtype., Design, Setting, and Participants: In this research study to create a new algorithmic quantification system for all hair loss, computational imaging analysis and algorithm design using retrospective image data collection were performed. This was a multicenter study, where images were collected at the Children's Hospital of Philadelphia, University of Pennsylvania (Penn), and via a Penn Dermatology web interface. Images were collected from 2015 to 2021, and they were analyzed from 2019 to 2021., Main Outcomes and Measures: Scoring systems correlation analysis was measured by linear and logarithmic regressions. Algorithm performance was evaluated using image segmentation accuracy, density probability regression error, and average percentage hair loss error for labeled images, and Pearson correlation for manual scores., Results: There were 404 participants aged 2 years and older that were used for designing and validating HairComb. Scoring systems correlation analysis was performed for 250 participants (70.4% female; mean age, 35.3 years): 75 AGA, 66 AA, 50 CCCA, 27 other alopecia diagnoses (frontal fibrosing alopecia, lichen planopilaris, telogen effluvium, etc), and 32 unaffected scalps without alopecia. Scoring systems showed strong correlations with underlying percentage hair loss, with coefficient of determination R2 values of 0.793 and 0.804 with respect to log of percentage hair loss. Using HairComb, 92% accuracy, 5% regression error, 7% hair loss difference, and predicted scores with errors comparable to annotators were achieved., Conclusions and Relevance: In this research study,it is shown that an algorithm quantitating percentage hair loss may be applied to all forms of alopecia. A generalizable automated assessment of hair loss would provide a way to standardize measurements of hair loss across a range of conditions.

Purpose of Review: The current review will address the different causes of localized hair loss in infancy. The data presented here will provide clinicians with the latest understanding of different disorders leading to localized hair loss and will provide recommendations for further management of infants who present with alopecia., Recent Findings: Localized hair loss in infancy is common, but its underlying causes vary greatly. Alopecia in infants can be categorized into congenital, genetic, inflammatory, mechanical, and physiologic causes. Decisions regarding further management are complex, as they often involve not only cosmetic concerns, but also work-up of possible systemic medical issues related to hair loss., Summary: Clinicians must be able to distinguish between the different causes of infantile hair loss so that appropriate work-up and further management can be pursued. Factors such as physical appearance, timing of presentation, dermoscopic exam, histopathology, and associated systemic features can help lead clinicians to the correct diagnosis in the case of an infant with localized alopecia., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Determining the minimum image resolution needed for clinical assessment is crucial for computational efficiency, image standardization, and storage needs alleviation. In this paper, we explore the image resolution requirements for the assessment of alopecia by analyzing how clinicians detect the presence of characteristics needed to quantify the disorder in the clinic. By setting the image resolution as a function of width of the patient's head, we mimicked experiments conducted in the computer vision field to understand human perception in the context of scene recognition and object detection and asked 6 clinicians to identify the regions of interest on a set of retrospectively collected de-identified images at different resolutions. The experts were able to detect the presence of alopecia at very low resolutions, while significantly higher resolution was required to identify the presence of vellus-like hair. Furthermore, the accuracy with which alopecia was detected as a function of resolution followed the same trend as the one obtained when we classified normal versus abnormal hair density using a standard neural network architecture, hinting that the resolution needed by an expert human observer may also provide an upper bound for future image processing algorithms.

Background: Caregiver-oriented quality of life (QoL) research in alopecia areata is limited. No study has used a parent-tailored survey to examine the relationship between QoL and severity of alopecia as measured by Severity of Alopecia Tool (SALT) scores., Objectives: This is a prospective study that describes QoL in parents of pediatric patients with all subtypes of alopecia areata and investigates the relationship between QoL and severity of disease, duration of disease, and age of patients., Methods: Pediatric patients and their parents were invited to participate during clinic visits. Participating parents completed the Quality of Life in a Child's Chronic Disease Questionnaire (QLCCDQ) and the Family Dermatology Life Quality Index (FDLQI). A subset of children completed the Children's Dermatologic Life Quality Index (CDLQI). SALT scores at time of survey completion were recorded., Results: In total, 153 patients were included. Significant mild-to-moderate negative correlations were found between SALT scores and FDLQI scores, QLCCDQ scores, and QLCCDQ emotional domain scores. Age of child correlated negatively with QLCCDQ scores but not FDLQI scores. No significant correlation was found between duration of disease and FDLQI scores, QLCCDQ scores, or QLCCDQ emotional domain scores., Limitations: This study is limited by its small sample size and cross-sectional design., Conclusions: Impaired parent QoL might be associated with increasing severity of disease and age of affected child but not duration of disease. Providers should tailor counseling accordingly and help parents set realistic expectations for long-term experience with the disease., (Copyright © 2019 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Alopecia is a disorder that affects all patients, young and old. Many diagnoses, particularly the scarring alopecias, are more common in adults; however, others, such as tinea capitis, are more common in children, and some, such as alopecia areata, often affect both age groups. The approach to, and evaluation of, an alopecia patient is thus highly dependent on his or her age. In adults with diffuse, non-scarring hair loss, a part-width examination can help detect pattern hair loss, the most common cause of diffuse loss in this age group. In children this is much less likely, and a careful evaluation for tinea capitis is in order. The same holds true for patchy alopecia in children, as well as scarring alopecia-tinea needs to always be considered. In adults, patchy alopecia is often due to alopecia areata and sometimes to one of the primary scarring alopecias. A laboratory evaluation, and especially a biopsy, would be a more appropriate undertaking for an adult than a child, and an adult would be more likely to tolerate certain therapeutic regimens such as intralesional injections. In a conversational manner, the authors discuss their individual approaches to the alopecia patient, highlighting the differences in diagnosis, workup, and management that depend on whether the affected individual is an adult or a child., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Alopecia in childhood is a source of high concern, frustration, and anxiety. Delineating types of alopecia and those that are chronic or potentially related to underlying medical problems is important. There are 5 common types of hair loss in children: alopecia related to tinea capitis, alopecia areata spectrum/autoimmune alopecia, traction alopecia, telogen effluvium, and trichotillomania/trichotillosis. Hair-cycle anomalies including loose anagen syndrome can lead to sparse-appearing hair. Rarer reasons for alopecia in children include pressure-induced alopecia, alopecia related to nutritional deficiency or toxic ingestion, and androgenetic alopecia. Congenital lesions should be considered for areas of localized alopecia occurring at birth., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Autoimmune polyendocrinopathy‐candidiasis‐ectodermal dystrophy (APECED) is an inherited disorder of immunity which leads to increased risk for mucocutaneous candidiasis and multiorgan autoimmune disease. While alopecia areata (AA) has been described in some patients with APECED, the extent and timing of AA is not well established and extent and timing of concomitant vitiligo and hypothyroidism has not been described. We evaluated an APECED cohort followed at the National Institutes of Health for the timing of development of associated diseases. We found AA occurred earlier in those with APECED than in the general population, was rarely the first sign of APECED, and the timing of AA onset did correlate with the timing of onset of vitiligo or hypothyroidism which also occurred at high rates and early age. [ABSTRACT FROM AUTHOR]

Abstract: The relationship between alopecia areata and celiac disease has been suspected for more than 20 years. For a particular individual with alopecia areata, the risk of coexisting celiac disease and the potential benefit of a gluten‐free diet on hair loss or regrowth is known. Despite this limited information, patients often aske dermatologists whether they should undergo celiac disease testing or begin a gluten‐free diet. We reviewed all available studies of the relationship between alopecia areata and celiac disease to provide guidance to practicing clinicians. [ABSTRACT FROM AUTHOR]