Abstract
Background: Although clinical assessment has historically been the primary method used for diagnosing and staging pediatric localized scleroderma (LS), highfrequency ultrasonography (HFUS) is being investigated as a more accurate method for evaluating lesions.
Objectives: This study aimed to assess, compare dermal and subcutaneous tissue characteristics and enhance lesion staging in pediatric LS patients using HFUS.
Methods: Twenty two LS patients were cross-sectionally evaluated with B-mode ultrasonography. Lesions were clinically staged, and dermal and subcutaneous tissue characteristics were compared with healthy tissue using HFUS.
Results: Among 55 lesions, 27 were active/new (49.1%), and 28 were atrophic/old (50.9%). Active lesions typically had increased dermal thickness in 66.6% of cases, while atrophic lesions often showed decreased dermal thickness (78.5%), with significant differences (p<0.05). Dermal echogenicity decreased in 40.7% of active lesions but remained largely unchanged in atrophic lesions (82.1%) (p<0.05). Subcutaneous tissue thickness significantly decreased in atrophic lesions (78.5%) and increased in 59.2% of active lesions, with a significant difference (p = 0.002). Subcutaneous tissue echogenicity increased in 44.4% of active lesions and remained mostly unchanged in atrophic lesions (67.8%). Importantly, a considerable proportion of lesions diagnosed as active through physical examination were actually inactive on HFUS evaluation (55.6%), while a significant portion of lesions categorized as atrophic on physical examination displayed areas of inactivity upon ultrasonographic assessment (35.7%). These findings highlight HFUS's potential as a valuable diagnostic tool and reveal discordances between clinical and HFUS staging.
Conclusion: Ultrasonography offers an objective LS lesion evaluation, especially in pediatrics.
Keywords: Childhood, Dermis, Lesion staging, Localized scleroderma, Subcutaneous tissue, Ultrasound.
Call for Papers in Thematic Issues
Advancements and Applications of Photon Counting CT: Transforming Imaging Precision and Quantification
Photon Counting Computed Tomography (CT) represents a transformative advancement in medical imaging technology, offering unprecedented levels of precision and diagnostic capability. This special issue will explore the latest innovations and applications of photon counting CT, highlighting its advantages over traditional energy-integrating detectors. The scope includes an in-depth examination of its ...read more
Advancements in Deep Learning based Medical Image and Signal Processing for Healthcare Applications
The accurate predication from medical data (signals and images) analytics will be achieved through the use of cutting-edge AI tools for tailoring medical treatment to each patient. When the agents are done analysing the user's health data, the user can consult with the agents to receive advice and the most ...read more
AI-Driven Diagnostics in Radiology and Medical Imaging
Medical imaging data, such as X-rays, MRIs, ultrasounds, CT scans, and DXAs, can be analysed by AI algorithms to help healthcare professionals identify and diagnose diseases more rapidly and accurately. Among the most cutting-edge applications of artificial intelligence (AI) in healthcare are imaging-related applications like cancer detection. AI could revolutionise ...read more
Applying medical image processing techniques for early cancer detection in mammograms
Breast cancer survival and successful treatment are significantly boosted by early identification. Breast cancer screening is most commonly accomplished with mammography. The radiologist's experience and the image quality, among several other factors, might affect how well a mammogram is interpreted. Enhancing mammography analysis and increasing cancer early detection are made ...read more
16