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Sarcopenia is defined as the loss of skeletal muscle mass and muscle function. It is common in patients with malignancies and often associated with adverse clinical outcomes. The presence of sarcopenia in patients with cancer is determined by body composition, and recently, radiologic technology for the accurate estimation of body composition is under development. Artificial intelligence- (AI-) assisted image measurement facilitates the detection of sarcopenia in clinical practice. Sarcopenia is a prognostic factor for patients with cancer, and confirming its presence helps to recognize those patients at the greatest risk, which provides a guide for designing individualized cancer treatments. In this review, we examine the recent literature (2017-2021) on AI-assisted image assessment of body composition and sarcopenia, seeking to synthesize current information on the mechanism and the importance of sarcopenia, its diagnostic image markers, and the interventions for sarcopenia in the medical care of patients with cancer. We concluded that AI-assisted image analysis is a reliable automatic technique for segmentation of abdominal adipose tissue. It has the potential to improve diagnosis of sarcopenia and facilitates identification of oncology patients at the greatest risk, supporting individualized prevention planning and treatment evaluation. The capability of AI approaches in analyzing series of big data and extracting features beyond manual skills would no doubt progressively provide impactful information and greatly refine the standard for assessing sarcopenia risk in patients with cancer. [ABSTRACT FROM AUTHOR]

Background. Radiation using conventional X-ray is associated with exposure of radiosensitive organs and typically requires the use of protection. This study is aimed at evaluating the use of bismuth shielding for radiation protection in pediatric pelvic radiography. The effects of the anteroposterior and lateral bismuth shielding were verified by direct measurements at the anatomical position of the gonads. Methods. Radiation doses were measured using optically stimulated luminescence dosimeters (OSLD) and CIRS ATOM Dosimetry Verification Phantoms. Gonad radiographs were acquired using different shields of varying material (lead, bismuth) and thickness and were compared with radiographs obtained without shielding to examine the effects on image quality and optimal reduction of radiation dose. All images were evaluated separately by three pediatric orthopedic practitioners. Results. Results showed that conventional lead gonadal shielding reduces radiation doses by 67.45%, whereas dose reduction using one layer of bismuth shielding is 76.38%. The use of two layers of bismuth shielding reduces the dose by 84.01%. Using three and four layers of bismuth shielding reduces dose by 97.33% and 99.34%, respectively. Progressively lower radiation doses can be achieved by increasing the number of bismuth layers. Images obtained using both one and two layers of bismuth shielding provided adequate diagnostic information, but those obtained using three or four layers of bismuth shielding were inadequate for diagnosis. Conclusions. Bismuth shielding reduces radiation dose exposure providing appropriate protection for children undergoing pelvic radiography. The bismuth shielding material is lighter than lead, making pediatric patients more comfortable and less apt to move, thereby avoiding repeat radiography. [ABSTRACT FROM AUTHOR]