Photo Visualization of Skintone Compatibility of an SPF 35 Sunscreen.

BACKGROUND: Visual casts and discoloration are common barriers to sunscreen use in melanin-rich populations. However, photoprotective measures are essential for individuals with all skin types, including darker skin. METHODS: Single-center, 7-day, open-label study of healthy adult females with Fitzpatrick Skin Types (FST) IV to VI and sensitive skin treated with once-daily daily facial moisturizer sun protection factor 35 (DFM SPF35). Subjects completed a cosmetic acceptability questionnaire at days 1 and 7. Photography using VISIA CR was performed at day 7. Adverse events were monitored throughout the study. RESULTS: Thirty-two (32) subjects participated; 31.3% had FST IV, 53.1% V, and 15.6% VI skin. DFM SPF35 was viewed as cosmetically elegant. At day 1, 96.7% of subjects agreed product was easy to apply; 90.0% reported soft skin after product use; 86.7% said it had a lightweight, non-greasy feel and hydrated the skin. At day 7, 93.7% reported no visible white residue on their skin and said the product applied easily/absorbed well. The majority (90.6%) would continue using and would recommend the product; and 87.5% reported the product blended seamlessly into their skin, which agreed with clinical photography. Responses were consistent among subjects with normal, oily, or combination skin. No adverse events were reported. CONCLUSIONS: DFM SPF35 blended well into the skin and was perceived favorably among subjects with SOC after 1 and 7 days of use. Subjects felt it had good cosmetic acceptability without unacceptable white residues or a greasy feeling. Dermatologists need to be versed in products that can be used on a variety of skin types.J Drugs Dermatol. 2024;23(7):515-518.  doi:10.36849/JDD.8223.

An exploratory study of structural and microvascular changes in the skin following electrical shaving using optical coherence topography.

BACKGROUND: Consumer products such as electrical shavers exert a combination of dynamic loading in the form of pressure and shear on the skin. This mechanical stimulus can lead to discomfort and skin tissue responses characterised as "Skin Sensitivity". To minimise discomfort following shaving, there is a need to establish specific stimulus-response relationships using advanced tools such as optical coherence tomography (OCT). OBJECTIVE: To explore the spatial and temporal changes in skin morphology and microvascular function following an electrical shaving stimulus. METHODS: Ten healthy male volunteers were recruited. The study included a 60-s electrical shaving stimulus on the forearm, cheek and neck. Skin parameters were recorded at baseline, 20 min post stimulus and 24 h post stimulus. Structural and dynamic skin parameters were estimated using OCT, while transepidermal water loss (TEWL) was recorded to provide reference values for skin barrier function. RESULTS: At baseline, six of the eight parameters revealed statistically significant differences between the forearm and the facial sites, while only surface roughness (Rq) and reflectivity were statistically different (p < 0.05) between the cheek and neck. At 20 min post shaving, there was a significant increase in the TEWL values accompanied by increased blood perfusion, with varying magnitude of change dependent on the anatomical site. Recovery characteristics were observed 24 h post stimulus with most parameters returning to basal values, highlighting the transient influence of the stimulus. CONCLUSIONS: OCT parameters revealed spatial and temporal differences in the skin tissue response to electrical shaving. This approach could inform shaver design and prevent skin sensitivity.

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.

Reflectance confocal microscopy for plaque psoriasis therapeutic follow-up during an anti-interleukin-17A monoclonal antibody: an observational study.

Interleukin-17A therapeutic inhibitors are among the most effective treatment methods for moderate-to-severe plaque psoriasis (PP). Reflectance confocal microscopy is a non-invasive imaging technique already documented to be beneficial in evaluating the follow-up of PP under treatment with topical actives and phototherapy. This study aimed to assess the epidermal and dermal changes associated with psoriasis and its treatment with RCM during systemic secukinumab treatment in patients with moderate-to-severe PP. A pilot study was conducted to evaluate RCM as a non-invasive tool for monitoring secukinumab treatment in patients with PP. For patients receiving secukinumab treatment, lesional skin was selected for RCM imaging, which were recorded at all scheduled times. The RCM evaluation criteria were established based on the histopathological diagnostic criteria for psoriasis. The clinical severity of psoriasis was assessed utilizing the psoriasis area severity index. A total of 23 patients with PP were included in the study. Each patient received 300 mg of subcutaneous secukinumab as induction therapy at baseline and weeks 1-4, followed by maintenance therapy every four weeks. Microscopic confocal changes were observed during the treatment. The results identified early microscopic evidence of the anti-inflammatory activity of secukinumab, which was not detected during the clinical examination. RCM findings correlating with the PASI were used to observe the patient's response to treatment and were identified as follows: acanthosis and parakeratosis, presence of epidermal and dermal inflammatory cells, presence of non-edge dermal papillae, and vascularization in the papillary dermis. This study is the first to demonstrate the use of RCM as an effective tool for non-invasive monitoring of secukinumab therapeutic response at a cellular level in a clinical or research setting. Early detection of RCM parameters associated with secukinumab activity may facilitate the identification of an early treatment response. RCM appears to be capable of providing practical and helpful information regarding follow-up in patients with PP undergoing secukinumab treatment. RCM may also provide novel perspectives on the subclinical evaluation of PP's response to biological therapy.

Diagnostic accuracy of high-frequency ultrasound for cutaneous neoplasms: a narrative review of the literature.

High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of evidence about the diagnostic accuracy of high-frequency ultrasound in dermatology. A narrative review of the PubMed database was performed to establish the correlation between ultrasound findings and histopathologic/dermoscopic findings for cutaneous neoplasms. Articles were divided into the following four categories: melanocytic, keratinocytic/epidermal, appendageal, and soft tissue/neural neoplasms. Review of the literature revealed that ultrasound findings and histopathology findings were strongly correlated regarding the depth of a cutaneous neoplasm. Morphological characteristics were correlated primarily in soft tissue/neural neoplasms. Overall, there is a paucity of literature on the correlation between high-frequency ultrasound and histopathology of cutaneous neoplasms. Further studies are needed to investigate this correlation in various dermatologic conditions.

A comparative study of an advanced skin imaging system in diagnosing facial pigmentary and inflammatory conditions.

Visual assessment, while the primary method for pigmentation and erythema evaluation in clinical practice, is subjective, time-consuming, and may lead to variability in observations among clinicians. Objective and quantitative techniques are required for a precise evaluation of the disease's severity and the treatment's efficacy. This research examines the precision and utility of a newly developed skin imaging system in assessing pigmentation and erythema. Sixty participants were recruited, and their facial images were analyzed with the new OBSERV 520 x skin imaging system, compared to DERMACATCH for regional analysis and VISIA for full-face examination. The degree of skin pigmentation was clinically graded using the MASI scores evaluated by dermatologists. The data revealed positive correlations between the novel skin imaging system and the two conventional instruments in quantifying pigmentation and erythema, whether in regional or full-face analysis. Furthermore, the new skin imaging system positively correlated with the clinical MASI scores (r = 0.4314, P < 0.01). In contrast, our study found no significant correlation between the traditional system and clinical assessment, indicating a more substantial capacity for hyperpigmentation assessment in the new system. Our study validates the innovative skin imaging system's accuracy in evaluating pigmentation and erythema, demonstrating its feasibility for quantitative evaluation in both clinical and research purposes.

Vascular feature identification in actinic keratosis grades I-III using dynamic optical coherence tomography with automated, quantitative analysis.

Clinical grading of actinic keratosis (AK) is based on skin surface features, while subclinical alterations are not taken into consideration. Dynamic optical coherence tomography (D-OCT) enables quantification of the skin´s vasculature, potentially helpful to improve the link between clinical and subclinical features. We aimed to compare microvascular characteristics across AK grades using D-OCT with automated vascular analysis. This explorative study examined AK and photodamaged skin (PD) on the face or scalp. AKs were clinically graded according to the Olsen Classification scheme before D-OCT assessment. Using an open-source software tool, the OCT angiographic analyzer (OCTAVA), we quantified vascular network features, including total and mean vessel length, mean vessel diameter, vessel area density (VAD), branchpoint density (BD), and mean tortuosity from enface maximum intensity projection images. Additionally, we performed subregional analyses on selected scans to overcome challenges associated with imaging through hyperkeratosis (each lesion group; n = 18). Our study included 45 patients with a total of 205 AKs; 93 grade I lesions, 65 grade II, 47 grade III and 89 areas with PD skin. We found that all AK grades were more extensively vascularized relative to PD, as shown by greater total vessel length and VAD (p ≤ 0.009). Moreover, AKs displayed a disorganized vascular network, with higher BD in AK I-II (p < 0.001), and mean tortuosity in AK II-III (p ≤ 0.001) than in PD. Vascularization also increased with AK grade, showing significantly greater total vessel length in AK III than AK I (p = 0.029). Microvascular quantification of AK unveiled subclinical, quantitative differences among AK grades I-III and PD skin. D-OCT-based microvascular assessment may serve as a supplement to clinical AK grading, potentially raising perspectives to improve management strategies.

Multispectral Imaging-Based System for Detecting Tissue Oxygen Saturation With Wound Segmentation for Monitoring Wound Healing.

OBJECTIVE: Blood circulation is an important indicator of wound healing. In this study, a tissue oxygen saturation detecting (TOSD) system that is based on multispectral imaging (MSI) is proposed to quantify the degree of tissue oxygen saturation (StO2) in cutaneous tissues. METHODS: A wound segmentation algorithm is used to segment automatically wound and skin areas, eliminating the need for manual labeling and applying adaptive tissue optics. Animal experiments were conducted on six mice in which they were observed seven times, once every two days. The TOSD system illuminated cutaneous tissues with two wavelengths of light - red ([Formula: see text] nm) and near-infrared ([Formula: see text] nm), and StO2 levels were calculated using images that were captured using a monochrome camera. The wound segmentation algorithm using ResNet34-based U-Net was integrated with computer vision techniques to improve its performance. RESULTS: Animal experiments revealed that the wound segmentation algorithm achieved a Dice score of 93.49%. The StO2 levels that were determined using the TOSD system varied significantly among the phases of wound healing. Changes in StO2 levels were detected before laser speckle contrast imaging (LSCI) detected changes in blood flux. Moreover, statistical features that were extracted from the TOSD system and LSCI were utilized in principal component analysis (PCA) to visualize different wound healing phases. The average silhouette coefficients of the TOSD system with segmentation (ResNet34-based U-Net) and LSCI were 0.2890 and 0.0194, respectively. CONCLUSION: By detecting the StO2 levels of cutaneous tissues using the TOSD system with segmentation, the phases of wound healing were accurately distinguished. This method can support medical personnel in conducting precise wound assessments. Clinical and Translational Impact Statement-This study supports efforts in monitoring StO2 levels, wound segmentation, and wound healing phase classification to improve the efficiency and accuracy of preclinical research in the field.

The biodistribution of triamcinolone acetonide injections in severe keloids: an exploratory three-dimensional fluorescent cryomicrotome study.

Intralesional corticosteroid injections are a first-line treatment for keloids; yet clinical treatment results are highly variable and often suboptimal. Variation in triamcinolone acetonide (TAC) biodistribution may be an important reason for the variable effects of TAC treatment in keloids. In this exploratory study we investigated the biodistribution of TAC in keloids and normal skin using different drug delivery techniques. Fluorescent-labeled TAC suspension was administered into keloids and normal skin with a hypodermic needle and an electronic pneumatic jet injector. TAC biodistribution was represented by the fluorescent TAC volume and 3D biodistribution shape of TAC, using a 3D-Fluorescence-Imaging Cryomicrotome System. Twenty-one keloid and nine normal skin samples were analyzed. With needle injections, the mean fluorescent TAC volumes were 990 µl ± 479 in keloids and 872 µl ± 227 in normal skin. With the jet injector, the mean fluorescent TAC volumes were 401 µl ± 252 in keloids and 249 µl ± 67 in normal skin. 3D biodistribution shapes of TAC were highly variable in keloids and normal skin. In conclusion, TAC biodistribution in keloids is highly variable for both needle and jet injection. This may partly explain the variable treatment effects of intralesional TAC in keloids. Future research is needed to confirm this preliminary finding and to optimize drug delivery in keloids.

Quantitative skin surface hydration measurement by visible optical image processing: A pilot study.

BACKGROUND: Skin barrier function is significantly impacted by skin moisture. Most non-invasive evaluation techniques to measure skin surface hydration relying on its electrical properties, which are limited in scope and have unstable operations. Applying image processing for skin hydration assessment is uncommon, with an emphasis on skin-capacitive pictures and near-infrared images in general, which demand a certain spectrum. As a result, there is an increasing need for wide-area skin hydration evaluation and mapping. OBJECTIVE: The study aims to propose a quantitative evaluation algorithm for skin surface hydration from visible-light images. MATERIALS AND METHODS: Three devices were applied to measure skin hydration: skin image capture device and two recognized commercial skin devices. A digital image processing system creates a new index, called GVR, to symbolize skin surface moisture. The CLAHE algorithm was applied to enhance the contrast of skin image, and after calculating it with the monochrome image, the skin reflectance image was segmented. The GVR was estimated using the values of the individual sites and the entire skin. The correlation coefficient between the three methods was examined using statistical analysis to assess the performance of GVR. RESULTS: Skin hydration estimated from visible-light images is influenced by the entire facial structure in addition to specific areas. The electrical and visible image evaluations showed a strong association with a significant difference. CONCLUSION: It was discovered that reflecting measures from visible images provide a quick and efficient way to quantify the moisture of the skin's surface.

Investigation on the influence of the skin tone on hyperspectral imaging for free flap surgery.

Hyperspectral imaging (HSI) is a new emerging modality useful for the noncontact assessment of free flap perfusion. This measurement technique relies on the optical properties within the tissue. Since the optical properties of hemoglobin (Hb) and melanin overlap, the results of the perfusion assessment and other tissue-specific parameters are likely to be distorted by the melanin, especially at higher melanin concentrations. Many spectroscopic devices have been shown to struggle with a melanin related bias, which results in a clinical need to improve non-invasive perfusion assessment, especially for a more pigmented population. This study investigated the influence of skin tones on tissue indices measurements using HSI. In addition, other factors that might affect HSI, such as age, body mass index (BMI), sex or smoking habits, were also considered. Therefore, a prospective feasibility study was conducted, including 101 volunteers from whom tissue indices measurements were performed on 16 different body sites. Skin tone classification was performed using the Fitzpatrick skin type classification questionnaire, and the individual typology angle (ITA) acquired from the RGB images was calculated simultaneously with the measurements. Tissue indices provided by the used HSI-device were correlated to the possible influencing factors. The results show that a dark skin tone and, therefore, higher levels of pigmentation influence the HSI-derived tissue indices. In addition, possible physiological factors influencing the HSI-measurements were found. In conclusion, the HSI-based tissue indices can be used for perfusion assessment for people with lighter skin tone levels but show limitations in people with darker skin tones. Furthermore, it could be used for a more individual perfusion assessment if different physiological influencing factors are respected.

High-frequency ultrasound evaluation of morphea: Retrospective analytical study.

BACKGROUND: To date, there are no accepted outcome measures to monitor morphea, and consensus on specific monitoring criteria for morphea remains elusive. A few studies have assessed the criterion validity of skin ultrasound in morphea. So, in this study, we approach ultrasound findings in morphea lesions. MATERIAL AND METHODS: This was a retrospective-analytical study conducted between December 2021 and May 2023. Patients were clinically evaluated at a dermatology outpatient clinic and then referred for high-frequency ultrasound (HF-US) evaluation and were selected to be included in this study. The lesions were confirmed by histopathology as well. Sonographic evaluations were performed on the lesion site and the symmetrical uninvolved other side. Dermal thickness and dermal echogenicities were recorded. Statistical analysis of group differences was performed by using the 2-tailed Student t-test. A p-value of less than 0.05 was considered statistically significant. RESULTS: Forty-one morphea lesions in the inflammatory phase of 27 patients were included in the study. The mean dermal thickness of morphea lesions was 1107.97 ± 414.3 and the mean dermal thickness of the control side was 1094.65 ± 331.06, The difference between these two variables was not statistically significant. The mean dermal density of lesions was 49.13 ± 18.97 and the mean dermal density of the control side was 52.22 ± 25.33. The difference between these two variables was not statistically significant. CONCLUSION: This study shows that HF-US indicated increasing dermal thickness and reducing the dermal density of the morphea lesions in the inflammatory phase confirmed with the histopathology.

Ultrasound features of high-risk basal cell carcinoma: a systematic review.

Basal Cell Carcinoma (BCC) is the most prevalent skin cancer and continues to witness a surge in incidence rates. The categorization of BCC subtypes into low or high risk, guided by recurrence and invasiveness metrics, underscores the need for precise differentiation. While the punch biopsy remains the gold standard for diagnosis, its invasiveness prompts a need for non-invasive alternatives. Ultrasound (US) has emerged as a noteworthy candidate, gaining momentum in its potential to offer a less intrusive diagnostic approach. We conducted a systematic review regarding features of the high-risk subtypes of BCC on US. A thorough literature search of PubMed Medline, Embase, and CINAHL databases was conducted according to PRISMA guidelines and a total of nine studies meeting our inclusion criteria were included in this review. Evidence is still nascent but US features such as lesional shape, depth, hyperechoic spots, and color doppler may be helpful in differentiating high-risk BCC subtypes. However, further prospective studies with standardized interventions and outcome measures are required.

Automated Prediction of Malignant Melanoma using Two-Stage Convolutional Neural Network.

PURPOSE: A skin lesion refers to an area of the skin that exhibits anomalous growth or distinctive visual characteristics compared to the surrounding skin. Benign skin lesions are noncancerous and generally pose no threat. These irregular skin growths can vary in appearance. On the other hand, malignant skin lesions correspond to skin cancer, which happens to be the most prevalent form of cancer in the United States. Skin cancer involves the unusual proliferation of skin cells anywhere on the body. The conventional method for detecting skin cancer is relatively more painful. METHODS: This work involves the automated prediction of skin cancer and its types using two stage Convolutional Neural Network (CNN). The first stage of CNN extracts low level features and second stage extracts high level features. Feature selection is done using these two CNN and ABCD (Asymmetry, Border irregularity, Colour variation, and Diameter) technique. The features extracted from the two CNNs are fused with ABCD features and fed into classifiers for the final prediction. The classifiers employed in this work include ensemble learning methods such as gradient boosting and XG boost, as well as machine learning classifiers like decision trees and logistic regression. This methodology is evaluated using the International Skin Imaging Collaboration (ISIC) 2018 and 2019 dataset. RESULTS: As a result, the first stage CNN which is used for creation of new dataset achieved an accuracy of 97.92%. Second stage CNN which is used for feature selection achieved an accuracy of 98.86%. Classification results are obtained for both with and without fusion of features. CONCLUSION: Therefore, two stage prediction model achieved better results with feature fusion.

Ventricular Access Utilizing Cutaneous Reference Points: Statistical Analysis and Proposal of a New Ventricular Entry Point.

OBJECTIVES: Perform radiologic measurements and analysis of normal brain computed tomography (CT) scans; delineate a new ventricular entry point from cutaneous landmarks, highlighting the potential surgical implications of these findings. METHODS: Six radiologic distances (AR; BR; AL; BL, C, and D) were measured in normal brain CT scans using Horos software. Statistical analysis of the measurements was performed with minitab18 software based on age, sex, and side. RESULTS: 132 brain CT scans were analyzed, yielding the following mean results: AR distance: 2.1 cm; BR distance: 7 cm; AL distance: 2.1 cm; BL distance: 7.1 cm; C distance: 12.4 cm; D distance: 7 cm; new ventricular entry point: 12.4 cm posterior to the nasion, and 2.1 cm lateral to the midline. CONCLUSIONS: The freehand technique for accessing the lateral ventricles is a common neurosurgical procedure but is often accompanied by complications. To address this, we suggest a novel entry point for ventricular access, determined by cutaneous reference points. This point is situated 12.4 cm posterior to the nasion along the midline and 2.1 cm lateral to the midline. Although our findings may play a role in presurgical planning for ventricular pathologies, future prospective studies are warranted.

Empirical validation of Conformal Prediction for trustworthy skin lesions classification.

BACKGROUND AND OBJECTIVE: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-risk applications. existing studies have explored various methods that often operate under specific assumptions or necessitate substantial modifications to the network architecture to effectively account for uncertainties. The objective of this paper is to study Conformal Prediction, an emerging distribution-free uncertainty quantification technique, and provide a comprehensive understanding of the advantages and limitations inherent in various methods within the medical imaging field. METHODS: In this study, we developed Conformal Prediction, Monte Carlo Dropout, and Evidential Deep Learning approaches to assess uncertainty quantification in deep neural networks. The effectiveness of these methods is evaluated using three public medical imaging datasets focused on detecting pigmented skin lesions and blood cell types. RESULTS: The experimental results demonstrate a significant enhancement in uncertainty quantification with the utilization of the Conformal Prediction method, surpassing the performance of the other two methods. Furthermore, the results present insights into the effectiveness of each uncertainty method in handling Out-of-Distribution samples from domain-shifted datasets. Our code is available at: github.com/jfayyad/ConformalDx. CONCLUSIONS: Our conclusion highlights a robust and consistent performance of conformal prediction across diverse testing conditions. This positions it as the preferred choice for decision-making in safety-critical applications.

Optimizing deep learning-based segmentation of densely packed cells using cell surface markers.

BACKGROUND: Spatial molecular profiling depends on accurate cell segmentation. Identification and quantitation of individual cells in dense tissues, e.g. highly inflamed tissue caused by viral infection or immune reaction, remains a challenge. METHODS: We first assess the performance of 18 deep learning-based cell segmentation models, either pre-trained or trained by us using two public image sets, on a set of immunofluorescence images stained with immune cell surface markers in skin tissue obtained during human herpes simplex virus (HSV) infection. We then further train eight of these models using up to 10,000+ training instances from the current image set. Finally, we seek to improve performance by tuning parameters of the most successful method from the previous step. RESULTS: The best model before fine-tuning achieves a mean Average Precision (mAP) of 0.516. Prediction performance improves substantially after training. The best model is the cyto model from Cellpose. After training, it achieves an mAP of 0.694; with further parameter tuning, the mAP reaches 0.711. CONCLUSION: Selecting the best model among the existing approaches and further training the model with images of interest produce the most gain in prediction performance. The performance of the resulting model compares favorably to human performance. The imperfection of the final model performance can be attributed to the moderate signal-to-noise ratio in the imageset.

Structural neuroimaging of skin-picking disorder.

BACKGROUND: Skin-picking disorder (SPD) is conceptualized as an obsessive-compulsive and related disorder (OCRD). Patients with SPD excessively manipulate their skin, which leads to skin lesions, psychological distress, and functional impairment. The neuroanatomical facets of this disorder are still poorly understood. METHODS: A total of 220 participants (123 patients with a primary diagnosis of SPD and 97 healthy controls; mean age = 30 years, 80% female) were recruited for a voxel-based morphometry (VBM) study. VBM data were compared between patients and controls, and between three SPD subgroups, each characterized by a distinct age of symptom onset (before puberty, during puberty, adulthood). RESULTS: Relative to the healthy comparison group, patients with SPD had significantly less grey matter volume (GMV) in regions of interest (ROIs: insula, orbitofrontal cortex, pallidum, cerebellum, supramarginal gyrus) and in the frontal pole and occipital regions (whole-brain findings). Early onset of symptoms (before puberty) was associated with elevated levels of focused skin-picking, in addition to less GMV in specific ROIs (insula, orbitofrontal cortex) as well as in paracingulate/ superior temporal regions (whole-brain findings). CONCLUSIONS: SPD-related reductions in GMV were identified in brain regions involved in interoception, emotion regulation, and motor control. This partially aligns with findings for OCD. The detection of different age-of-onset groups based on clinical as well as morphometric data points to the heterogeneity of the disorder and warrants further investigation.