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Radiation Injuries

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Evaluation of a delineation software for cardiac atlas-based autosegmentation: An example of the use of artificial intelligence in modern radiotherapy.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
PURPOSE: The primary objective of this work was to implement and evaluate a cardiac atlas-based autosegmentation technique based on the "Workflow Box" software (Mirada Medical, Oxford UK), in order to delineate cardiac substructures according to Euro...

Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.

PloS one
OBJECTIVE: In this work, we explore and develop a method that uses Raman spectroscopy to measure and differentiate radiation induced toxicity in murine lungs with the goal of setting the foundation for a predictive disease model.

An Intelligent Robot Detection System of Uncontrolled Radioactive Sources.

Computational intelligence and neuroscience
In recent years, radioactive sources have been widely used in various fields (e.g., nuclear industry, agriculture, medical industry, environmental protection, and scientific research) and successfully applied to develop scientific projects, such as n...

Novel Imaging Biomarkers to Assess Oncologic Treatment-Related Changes.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Cancer therapeutics cause various treatment-related changes that may impact patient follow-up and disease monitoring. Although atypical responses such as pseudoprogression may be misinterpreted as treatment nonresponse, other changes, such as hyperpr...

A deep learning-based radiomics approach to predict head and neck tumor regression for adaptive radiotherapy.

Scientific reports
Early regression-the regression in tumor volume during the initial phase of radiotherapy (approximately 2 weeks after treatment initiation)-is a common occurrence during radiotherapy. This rapid radiation-induced tumor regression may alter target coo...

3D Segmentation Guided Style-Based Generative Adversarial Networks for PET Synthesis.

IEEE transactions on medical imaging
Potential radioactive hazards in full-dose positron emission tomography (PET) imaging remain a concern, whereas the quality of low-dose images is never desirable for clinical use. So it is of great interest to translate low-dose PET images into full-...

[To promote the clinical application of PET/MRI in oncology].

Zhonghua yi xue za zhi
PET/MRI integrates anatomical, functional and metabolic information, and is increasingly used in the field of clinical oncology, including early diagnosis of disease, local staging, detection of systemic metastases, evaluation of treatment efficacy a...

Deciphering the fibrotic process: mechanism of chronic radiation skin injury fibrosis.

Frontiers in immunology
This review explores the mechanisms of chronic radiation-induced skin injury fibrosis, focusing on the transition from acute radiation damage to a chronic fibrotic state. It reviewed the cellular and molecular responses of the skin to radiation, high...

A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).

Advanced Technologies in Radiation Research.

Radiation research
The U.S. Government is committed to maintaining a robust research program that supports a portfolio of scientific experts who are investigating the biological effects of radiation exposure. On August 17 and 18, 2023, the Radiation and Nuclear Counter...