AIMC Topic: Radiosurgery

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Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study.

Journal of applied clinical medical physics Mar 4, 2024
PURPOSE: Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lung cancer provides important information for the feasibility of the individualized radiotherapy and allows to select the appropriate treatment strateg...
Radiomics Male Middle Aged Image Processing, Computer-Assisted Female Aged Aged, 80 and over Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Radiotherapy, Intensity-Modulated Radiosurgery Machine Learning Lung Neoplasms Algorithms Carcinoma, Non-Small-Cell Lung Prognosis Positron Emission Tomography Computed Tomography Retrospective Studies Neoplasm Recurrence, Local
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Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Feb 24, 2024
BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain adequate tumor dose in lung stereotactic body radiation therapy (SBRT). Lung SBRT using an articulated robotic arm allows dynamic tracking during rad...
Algorithms Deep Learning Lung Neoplasms Respiration Humans Fiducial Markers Radiosurgery Movement Radiotherapy, Image-Guided
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Two is better than one: longitudinal detection and volumetric evaluation of brain metastases after Stereotactic Radiosurgery with a deep learning pipeline.

Journal of neuro-oncology Feb 1, 2024
PURPOSE: Close MRI surveillance of patients with brain metastases following Stereotactic Radiosurgery (SRS) treatment is essential for assessing treatment response and the current disease status in the brain. This follow-up necessitates the compariso...
Brain Neoplasms Humans Deep Learning Brain Radiosurgery Retrospective Studies
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Efficacy of stereotactic body radiotherapy and response prediction using artificial intelligence in oligometastatic gynaecologic cancer.

Gynecologic oncology Jan 24, 2024
PURPOSE: We present a large real-world multicentric dataset of ovarian, uterine and cervical oligometastatic lesions treated with SBRT exploring efficacy and clinical outcomes. In addition, an exploratory machine learning analysis was performed.
Genital Neoplasms, Female Radiosurgery Treatment Outcome Ovarian Neoplasms Uterine Neoplasms Female Aged Aged, 80 and over Young Adult Adult Uterine Cervical Neoplasms Middle Aged Humans Artificial Intelligence Machine Learning Retrospective Studies
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Determination of output factor for CyberKnife using scintillation dosimetry and deep learning.

Physics in medicine and biology Jan 22, 2024
. Small-field dosimetry is an ongoing challenge in radiotherapy quality assurance (QA) especially for radiosurgery systems such as CyberKnife. The objective of this work is to demonstrate the use of a plastic scintillator imaged with a commercial cam...
Neural Networks, Computer Algorithms Deep Learning Radiosurgery Radiometry
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Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.

International journal of radiation oncology, biology, physics Dec 5, 2023
PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractions is sometimes considered controversial, as the nominal biologically effective dose (BED) of 100 Gy is felt by some to be insufficient for long-term ...
Radiosurgery Treatment Failure Radiometry Aged, 80 and over Humans Lung Neoplasms Male Tomography, X-Ray Computed Carcinoma, Non-Small-Cell Lung Middle Aged Female Radiotherapy Planning, Computer-Assisted Deep Learning Aged Radiotherapy Dosage
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Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.

European radiology Sep 2, 2023
OBJECTIVES: We aimed to evaluate whether deep learning-based detection and quantification of brain metastasis (BM) may suggest treatment options for patients with BMs.
Humans Retrospective Studies Brain Neoplasms Male Middle Aged Deep Learning Cohort Studies Magnetic Resonance Imaging Diagnostic Imaging Radiosurgery
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Federated Learning: A Cross-Institutional Feasibility Study of Deep Learning Based Intracranial Tumor Delineation Framework for Stereotactic Radiosurgery.

Journal of magnetic resonance imaging : JMRI Aug 12, 2023
BACKGROUND: Deep learning-based segmentation algorithms usually required large or multi-institute data sets to improve the performance and ability of generalization. However, protecting patient privacy is a key concern in the multi-institutional stud...
Meningioma Magnetic Resonance Imaging Feasibility Studies Radiosurgery Neuroma, Acoustic Humans Adolescent Brain Neoplasms Algorithms Child Aged Male Retrospective Studies Image Processing, Computer-Assisted Aged, 80 and over Female Middle Aged Young Adult Deep Learning Adult
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Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networks.

Medical physics May 23, 2023
BACKGROUND: Radiotherapy (RT) is involved in about 50% of all cancer patients, making it a very important treatment modality. The most common type of RT is external beam RT, which consists of delivering the radiation to the tumor from outside the bod...
Respiration Radiotherapy, Intensity-Modulated Radiosurgery Humans Deep Learning Cone-Beam Computed Tomography Lung Neoplasms Radiotherapy Planning, Computer-Assisted
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Implementation and evaluation of an intelligent automatic treatment planning robot for prostate cancer stereotactic body radiation therapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Apr 28, 2023
PURPOSE: We previously developed a virtual treatment planner (VTP), an artificial intelligence robot, operating a treatment planning system (TPS). Using deep reinforcement learning guided by human knowledge, we trained the VTP to autonomously adjust ...
Humans Radiotherapy, Intensity-Modulated Robotics Artificial Intelligence Radiosurgery Prostatic Neoplasms Male Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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