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Results for "predict changes": 16 found

A Combination of Radiomics and Dosiomics for Gross Tumor Volume Regression in Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR)

Authors: Hao Peng, Yajun Yu

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) is a novel ablative radiation dosing scheme developed by our institution. This study aims to establish a regression...

A Two-Layer, Two-Task Prediction Model Based on 3D Imaging and Residual Networks for Mid-Chemoradiation Tumor Response Prediction on FDG PET for La-NSCLC

Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jing Sun, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Xiaojing Zhu

Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Shanghai University of Electric Power, Fred Hutchinson Cancer Center, University of Texas at Arlington

Abstract Preview: Purpose: Accurate prediction of patient response to radiotherapy plays a crucial role in monitoring disease progression and assessing treatment efficacy, enabling clinicians to develop personalized th...

Biologically Guided Deep Learning for MRI-Based Brain Metastasis Outcome Prediction after Stereotactic Radiosurgery

Authors: Evan Calabrese, Hangjie Ji, Kyle J. Lafata, Casey Y. Lee, Eugene Vaios, Chunhao Wang, Lana Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University, North Carolina State University

Abstract Preview: Purpose: To develop a biologically guided deep learning (DL) model for predicting brain metastasis(BM) local control outcomes following stereotactic radiosurgery (SRS). By integrating pre-SRS MR image...

Effect of Dose and Depth Dependence of Rbe on Hypofractionated Proton Therapy for Ocular Melanoma

Authors: Alexei V. Chvetsov, Pavitra Ramesh, Alexei V. Trofimov

Affiliation: Massachusetts General Hospital, University of Washington

Abstract Preview: Purpose: To investigate the effect of dose and depth dependence of relative biological effectiveness (RBE) on hypofractionated proton therapy for ocular melanoma using equivalent uniform RBE-weighted ...

Enhanced Predictive Model for Toxicity and 3-Year Survival in HCC Patients Using Learning Health System Infrastructure and AI-Driven Statistical Profiling

Authors: Ameer Elaimy, Theodore Lawrence, Charles S. Mayo, Seyyedeh Azar Oliaei Motlagh, Benjamin S. Rosen

Affiliation: University of Michigan

Abstract Preview: Purpose: To analyze the impact of clinical features on short-term survival, toxicity, and poor outcomes in HCC patients treated with SBRT,using automated data aggregation and enhanced algorithms with ...

Improve the Risk Prediction of Radiation-Induced Esophagitis in Lung IMRT By an Anisotropic Dose Convolution Neural Network

Authors: Ibtisam Almajnooni, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: We developed a deep learning neural network (DLNN) to predict the risk of radiation-induced esophagitis (RE) during lung cancer radiation therapy based on the spatial dose distribution, for t...

In-Silico Clinical Trials Enabled By Digital Twin Approach Can Accurately and Prospectively Predict Outcomes of Clinical Trials Combining Radiation and Systemic Therapy

Authors: Clemens Grassberger, David (Bo) McClatchy, Harald Paganetti

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Massachusetts General Hospital

Abstract Preview: Purpose: While randomized controlled trials (RCTs) are the gold standard for demonstrating efficacy, nearly 50% of late-stage clinical trials fail to meet their endpoint. Tools to study the design of ...

MR-Based Functional Liver Imaging and Dosimetry to Predict Albi Change Post-SBRT

Authors: Madhava Aryal, James M. Balter, Yue Cao, Daniel T Chang, Kyle Cuneo, Joseph R. Evans, Theodore Lawrence, John Rice, Randall K. Ten Haken, Lise Wei

Affiliation: University of Michigan, Department of Radiation Oncology University of Michigan

Abstract Preview: Purpose: This study aims to identify predictors of global liver function change measured by albumin-bilirubin (ALBI) score following stereotactic body radiation therapy (SBRT) in hepatocellular carcin...

MRI Radiomics-Based Machine Learning Model for Predicting BNCT Treatment Response in Glioblastoma

Authors: Huang Chi-Shiuan, Wu Chih-Chun, Hui-Yu Cathy Tsai, Chen Yan-Han, Chen Yi-Wei, Pan Yi-Ying

Affiliation: Institute of Nuclear Engineering and Science, National Tsing Hua University, Taipei Veterans General Hospital, Tri-Service General Hospital

Abstract Preview: Purpose:
This study aims to develop and validate a machine learning (ML) model based on MRI-derived radiomic features to predict progressive disease (PD) in glioblastoma (GBM) patients four months ...

Multi-Path Deep Learning Model for Predicting Post-Radiotherapy Functional Liver Imaging in Patients with Hepatocellular Carcinoma

Authors: Smith Apisarnthanarax, Stephen R. Bowen, Sunan Cui, Jie Fu, Clemens Grassberger, Yulun He, Yejin Kim, Matthew J. Nyflot, Sharon Pai

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Washington, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Physics, University of Washington, University of Washington and Fred Hutchinson Cancer Center

Abstract Preview: Purpose: 99mTc-sulfur colloid SPECT imaging enables quantitative assessment of voxel-wise liver function in patients with hepatocellular carcinoma (HCC). Accurately predicting post-radiotherapy (RT) l...

Recovery Factor Comparisons for Reirradiation Overlapping the Spinal Cord

Authors: Xinxin Deng, Issam M. El Naqa, Jimm Grimm, Lijun Ma, Vitali Moiseenko, Timothy E. Schultheiss, Gopal Subedi, Wolfgang A. Tomé, Ellen D. Yorke, Albert van der Kogel

Affiliation: Montefiore Medical Center, Wellstar Kennestone Hospital Cancer Center, H. Lee Moffitt Cancer Center, Department of Human Oncology, University of Wisconsin–Madison, Department of Radiation Oncology, Wellstar Health System, Radiation Oncology, Keck School of Medicine of USC, Georgia Institute of Technology, University of California San Diego, City Of Hope National Medical Centre, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Reirradiation is increasingly utilized in clinical practice but dose-time recovery factors for human subjects remain uncertain. We constructed a reirradiation recovery model for spinal cord e...

The Biological TCP/NTCP Modelling on Oropharyngeal Head-and-Neck Cancer for Patients Treated with Proton Beam Therapy

Authors: Wen C. Hsi, Tae Kyu Lee, Biniam Yo Tesfamicael

Affiliation: Allina Health, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Oklahoma Proton Center

Abstract Preview: Purpose: When minimal dose-variations induced by inter-fractional anatomical-changes and positioning-deviation were found for having limited impact on clinic-outcomes of oropharyngeal head-and-neck (H...

Uprightvision: A Deep-Learning Toolkit for Transforming Supine Anatomy to Upright

Authors: Ming Dong, Carri K. Glide-Hurst, Behzad Hejrati, Joshua Pan, Yuhao Yan

Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Upright patient positioners and vertical CT reduce tumor motion and stabilize internal anatomy during treatment delivery. Yet, to fully exploit the advantages of upright, translation of stand...

Utilizing Multiple Modalities to Improve Models to Predict Changes in International Prostate Score for Prostate Cancer

Authors: Matthew C Abramowitz, Alan Dal Pra, Rodrigo Delgadillo, Nesrin Dogan, John C. Ford, Kyle R. Padgett, Levent Sensoy, Benjamin Spieler, Matthew T. Studenski, Jace Allen Walker

Affiliation: University of Miami, Department of Radiation Oncology, University of Miami, University of Miami Sylvester Comprehensive Cancer Center, University of Miami School of Medicine

Abstract Preview: Purpose:
Toxicities that affect a patient’s quality-of-life due to prostate cancer (pCa) radiation therapy (RT) are receiving more attention as RT has become increasingly successful in treating pCA...

Validation of Synthetic CT-Based Online Monitoring for Adaptive Proton Therapy

Authors: Ozgur Ates, Chin-Cheng Chen, Chia-Ho Hua, Matthew J. Krasin, Thomas E. Merchant

Affiliation: St. Jude Children's Research Hospital

Abstract Preview: Purpose: To validate the use of synthetic CTs generated from CBCT images for online monitoring, ensuring accurate and reliable daily plan quality assessments in adaptive proton therapy (APT).
Metho...

Weekly Changes in Ventilation Response for Photon and Proton Patients during Radiotherapy

Authors: Kristy K. Brock, Austin Castelo, Yulun He, Zhongxing Liao, Rebecca Lim, Radhe Mohan, Caleb O'Connor, Tien T Tang, Uwe Titt

Affiliation: University of Washington, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Conformal dose distributions in proton radiotherapy promise to reduce normal tissue toxicity such as radiation-induced pneumonitis, but this has not been fully realized in clinical trials. To...