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Radiation Injuries

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Application of a machine learning method to whole brain white matter injury after radiotherapy for nasopharyngeal carcinoma.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The purpose/aim of this study was to 1) use magnetic resonance diffusion tensor imaging (DTI), fibre bundle/tract-based spatial statistics (TBSS) and machine learning methods to study changes in the white matter (WM) structure and whole b...

Future of Radiotherapy in Nasopharyngeal Carcinoma.

The British journal of radiology
Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as associated Epstein-Barr virus infection and high radiosensitivity. Radiotherapy has long been recognized as the mainstay for the treatment of NPC. However...

Cath Lab Robotics: Paradigm Change in Interventional Cardiology?

Current cardiology reports
PURPOSE OF REVIEW: To review the contemporary evidence for robotic-assisted percutaneous coronary and vascular interventions, discussing its current capabilities, limitations, and potential future applications.

Detection and Monitoring of Thermal Lesions Induced by Microwave Ablation Using Ultrasound Imaging and Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Microwave ablation (MWA) for cancer treatment is frequently monitored by ultrasound (US) B-mode imaging in the clinic, which often fails due to the low intrinsic contrast between the thermal lesion and normal tissue. Deep learning, especially convolu...

Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them.

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)
In radiation oncology, Machine Learning classification publications are typically related to two outcome classes, e.g. the presence or absence of distant metastasis. However, multi-class classification problems also have great clinical relevance, e.g...

A novel deep learning model using dosimetric and clinical information for grade 4 radiotherapy-induced lymphopenia prediction.

Physics in medicine and biology
Radiotherapy-induced lymphopenia has increasingly been shown to reduce cancer survivorship. We developed a novel hybrid deep learning model to efficiently integrate an entire set of dosimetric parameters of a radiation treatment plan with a patient's...

A case report on intensive, robot-assisted rehabilitation program for brainstem radionecrosis.

Medicine
INTRODUCTION: Radiotherapy is a valid treatment option for nasopharyngeal carcinoma. However, complications can occur following irradiation of the closest anatomical structures, including brainstem radionecrosis (BRN). The rehabilitation is poorly de...

Radiomics and deep learning in lung cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Lung malignancies have been extensively characterized through radiomics and deep learning. By providing a three-dimensional characterization of the lesion, models based on radiomic features from computed tomography (CT) and positron-emission tomograp...