Alopecia in Children with Cancer: A Review from Pathophysiology to Management.

Chemotherapy-induced alopecia and radiation-induced alopecia, the thinning or loss of hair due to cytotoxic chemotherapy and radiation therapy, respectively, are distressing adverse effects of cancer treatment. Chemotherapy, targeted therapies, and radiation therapy used in pediatric oncology often lead to alopecia by damaging hair follicles, with varying degrees of severity depending on the specific treatment type, mechanism of action, and damage-response pathway involved. Pediatric chemotherapy-induced alopecia, radiation-induced alopecia, and permanent alopecia, defined as hair regrowth that remains incomplete 6 months or more after treatment, have significant negative impacts on mental health, self-esteem, and social interactions, highlighting the need for further research into supportive care strategies.

Quantitative and Morphology-Based Deep Convolutional Neural Network Approaches for Osteosarcoma Survival Prediction in the Neoadjuvant and Metastatic Settings.

Purpose: Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep-learning strategies on histology samples to predict outcome for osteosarcoma in the neoadjuvant setting.

Experimental Design: Our study relies on a training cohort from New York University (NYU; New York, NY) and an external cohort from Charles University (Prague, Czechia).