Axilla

BackgroundA third-generation microwave-based device has been developed to treat axillary hyperhidrosis by selectively heating the interface between the skin and underlying fat where the sweat glands reside.Materials and methodsThirty-one (31) adults with primary axillary hyperhidrosis were enrolled. All subjects had one to three procedure sessions over a 6-month period to treat both axillae fully. Efficacy was assessed using the Hyperhidrosis Disease Severity Scale (HDSS), gravimetric weight of sweat, and the Dermatologic Life Quality Index (DLQI), a dermatology-specific quality-of-life scale. Subject safety was assessed at each visit. Subjects were followed for 12 months after all procedure sessions were complete.ResultsAt the 12-month follow-up visit, 90.3% had HDSS scores of 1 or 2, 90.3% had at least a 50% reduction in axillary sweat from baseline, and 85.2% had a reduction of at least 5 points on the DLQI. All subjects experienced transient effects in the treatment area such as swelling, discomfort, and numbness. The most common adverse event (12 subjects) was the presence of altered sensation in the skin of the arm that resolved in all subjects.ConclusionThe device tested provided efficacious and durable treatment for axillary hyperhidrosis.

The skin microbial community is regarded as essential for human health and well-being, but likewise plays an important role in the formation of body odor in, for instance, the axillae. Few molecular-based research was done on the axillary microbiome. This study typified the axillary microbiome of a group of 53 healthy subjects. A profound view was obtained of the interpersonal, intrapersonal and temporal diversity of the human axillary microbiota. Denaturing gradient gel electrophoresis (DGGE) and next generation sequencing on 16S rRNA gene region were combined and used as extent to each other. Two important clusters were characterized, where Staphylococcus and Corynebacterium species were the abundant species. Females predominantly clustered within the Staphylococcus cluster (87%, n = 17), whereas males clustered more in the Corynebacterium cluster (39%, n = 36). The axillary microbiota was unique to each individual. Left-right asymmetry occurred in about half of the human population. For the first time, an elaborate study was performed on the dynamics of the axillary microbiome. A relatively stable axillary microbiome was noticed, although a few subjects evolved towards another stable community. The deodorant usage had a proportional linear influence on the species diversity of the axillary microbiome.

BackgroundLymphoedema develops after axillary clearance (ANC) in 25% of patients. This prospective, multi-centre study compared multi-frequency bioimpedance spectroscopy (BIS) with arm volume measurement to: (1) determine which test has better diagnostic accuracy, (2) identify factors predicting development of lymphoedema, and its effect on quality-of-life.MethodsParticipants (N = 1100) underwent measurements pre and post-ANC surgery for breast cancer. Relative arm volume increase (RAVI) of >10% diagnosed lymphoedema. Predictors of lymphoedema were determined using logistic regression. Optimal diagnostic method was assessed using diagnostic accuracy. Quality-of-life was assessed using the FACT B + 4 questionnaire.ResultsLymphoedema was diagnosed in 22.8% women using RAVI > 10%, 45.6% using BIS criteria, while 24.5% underwent compression sleeve application by 24 months. BMI > 30 was an independent factor for both development (p = 0.005) and progression (p = 0.015) of lymphoedema. RAVI at 1 month, BMI > 30 and number of involved nodes contributed to a novel scoring model to predict lymphoedema by 36 months. Larger decreases in QoL scores post-surgery occurred in lymphoedema patients (p ConclusionsRAVI measurement was the best diagnostic tool for lymphoedema. BIS alone is not appropriate for lymphoedema screening or diagnosis. BMI > 30 predicted lymphoedema diagnosis and progression.

Axillary Lymph Nodes (ALNs) can be affected by breast cancer, and the number of affected ALNs is a determinant factor in breast cancer staging. Microwave imaging (MWI) has emerged as a promising technique for ALN assessment, addressing limitations in conventional imaging modalities. This study investigates, for the first time, the classification of ALNs and axillary regions from microwave signals, without image reconstruction. Classification is performed considering realistic morphological characteristics of ALNs reported in the literature and is based solely on geometric differences, which differ from targets previously explored in microwave-based classification studies. Eighty ALN numerical models were mathematically generated based on state-of-the-art anatomical descriptions. Microwave signals were simulated for three scenarios of different complexity, involving one and two ALNs, representing healthy and metastasised conditions. The methodology evaluated multiple combinations of signal types, feature extraction methods, and classifiers, including scenarios with multiple targets, reflecting clinically relevant axillary conditions and limited angular views inherent to axillary imaging. Classification accuracy reached 95% for single-ALN scenarios using kNN, while more complex two-ALN cases achieved accuracies up to 83.3% using SVM. These results demonstrate the potential of microwave signal-based classification to differentiate healthy and metastasised ALNs and axillary regions, supporting future integration with MWI image interpretation.