Background & Objective: Localization error in X-ray radiosurgery for tumors in eyeball was common due to the rotation of eyeball. The accuracy and precision of X-ray radiosurgery was studied by fixing the eyeball with micro-vacuo-certo-contacting ophthalmophanto (MVCCOP) to reduce the error in this article.
Methods: CT localization accuracy of X-ray radiosurgery system was measured using special markers in skull phantom. The eyeballs were fixed using MVCCOP, which was designed by the authors, and then the eyeball fixation accuracy and target localization accuracy were measured by comparing the CT localization coordinates and verification coordinates of corresponding points.
Results: The mean error of CT localization of BRW head-ring was 0.65 mm and maximum error was 1.09 mm. The mean error of fixation of eyeball using MVCCOP was 0.84 mm and maximal error was 1.17 mm. The accuracy of tumor localization in eyeball was 0.87 mm averagely and 1.19 mm maximally. The mean error of SRS200 was 0.22 mm and maximum error was 0.32 mm. The total error was 1.40 mm and 95 percentile confidence error was 2.12 mm.
Conclusion: The accuracy and precision of X-ray radiosurgery using MVCCOP has come up to the standard of quality control of stereotactic radiosurgery. This localization method can reduce the localization errors in radiosurgery caused by the rotation of eyeball.
Download full-text PDF |
Source |
---|
Neuroradiol J
January 2025
Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.
Objective: Predicting treatment response in patients with vestibular schwannomas (VSs) remains challenging. This study aimed to evaluate the use of pre-treatment normalized apparent diffusion coefficient (nADC) values and magnetic resonance (MR) imaging characteristics in predicting treatment outcomes in patients with VSs undergoing radiosurgery.
Methods: The MR images of 44 patients with VSs who underwent radiosurgery at our institution were retrospectively reviewed, and the patients were categorized into tumor control ( = 28) and progression ( = 16) groups based on treatment response after treatment initiation, with a median follow-up duration of 29.
Eur J Radiol
December 2024
Great Ormond Street Hospital for Children NHS Foundation Trust, London WC1N 3JH, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK.
Phys Med
January 2025
Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
Background And Purpose: Free-breathing computed tomography (FBCT) used in treatment planning for lower thoracic (Th8-Th12) spine stereotactic body radiotherapy (SBRT) can cause deviations between planned and irradiated doses due to diaphragm movement (DM). This study analyzed the dosimetric impact of DM on lower thoracic spine SBRT.
Materials And Methods: Data were collected from 19 patients who underwent FBCT and four-dimensional CT (4DCT) during the same session.
PLoS One
December 2024
Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.
Background: This retrospective study explores two radiomics methods combined with other clinical variables for predicting recurrence free survival (RFS) and overall survival (OS) in patients with pulmonary metastases treated with stereotactic body radiotherapy (SBRT).
Methods: 111 patients with 163 metastases treated with SBRT were included with a median follow-up time of 927 days. First-order radiomic features were extracted using two methods: 2D CT texture analysis (CTTA) using TexRAD software, and a data-driven technique: functional principal components analysis (FPCA) using segmented tumoral and peri-tumoural 3D regions.
Radiat Oncol
December 2024
Department of Cognitive Neuropsychology, Tilburg University, Tilburg, The Netherlands.
Background And Purpose: Timely identification of local failure after stereotactic radiotherapy for brain metastases allows for treatment modifications, potentially improving outcomes. While previous studies showed that adding radiomics or Deep Learning (DL) features to clinical features increased Local Control (LC) prediction accuracy, their combined potential to predict LC remains unexplored. We examined whether a model using a combination of radiomics, DL and clinical features achieves better accuracy than models using only a subset of these features.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!