Purpose: We report the use of online adaptive radiotherapy (OART) aiming to improve dosimetric parameters in the prostate cancer patient who had lower urinary tract symptoms that caused him not to adhere to the standard bladder filling protocol.
Methods And Materials: The reference treatment plan for adaptive radiotherapy plan was generated for the pelvis and the solitary bony lesion using the Ethos treatment planning system. For each treatment session, high-quality iterative reconstructed cone beam CT (CBCT) images were acquired, and the system automatically generated an optimal adaptive plan after verification of contours.
To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCNN) and to benchmark both approaches on broader validation sets.Seven public datasets were considered: (1) low-grade glioma or high-grade glioma (369 patients, BraTS'20) (2) well-differentiated liposarcoma or lipoma (115, LIPO); (3) desmoid-type fibromatosis or extremity soft-tissue sarcomas (203, Desmoid); (4) primary solid liver tumors, either malignant or benign (186, LIVER); (5) gastrointestinal stromal tumors (GISTs) or intra-abdominal gastrointestinal tumors radiologically resembling GISTs (246, GIST); (6) colorectal liver metastases (77, CRLM); and (7) lung metastases of metastatic melanoma (103, Melanoma). Radiomic analysis was performed on 464 (2016) radiomic features for the BraTS'20 (others) datasets respectively.
View Article and Find Full Text PDFOne of the main challenges to using magnetic resonance imaging (MRI) in radiotherapy is the existence of system-related geometric inaccuracies caused mainly by the inhomogeneity in the main magnetic field and the nonlinearities of the gradient coils. Several physical phantoms, with fixed configuration, have been developed and commercialized for the assessment of the MRI geometric distortion. In this study, we propose a new design of a customizable phantom that can fit any type of radio frequency (RF) coil.
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