| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| J Yang, L Cao, H D Mao, W Q Xiong, J Y Che. Convolution Neural Network-Based Automatic Scoring of Coronary Artery Calcification and Its Value to Identify the Risk of Radiation-Induced Cardiac Toxicity on Radiotherapy Planning CT Scans in Breast Cancer Patients. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37784884. |
to develop an automatic scoring of coronary artery calcification (cac) on breast cancer radiotherapy (rt) planning computed tomography (ct) scans, and to explore its predictive value of cac for radiation-induced cardiac toxicity. |
2023-10-03 |
2023-10-07 |
Not clear |
| H A Gomaa, M Mahfouz, N Al-Dhaibani, M A Alidrisi, M Y Almaghrabi, A Habshi, D Mohorjy, K Alsalma. Evaluation of Peer Review Practice in Radiation Oncology Treatment Planning: Single Institution Experience. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785302. |
pretreatment peer review meeting at our radiation oncology department is a weekly meeting, where the initial radiation treatment (rt) planning process for every patient is discussed including: computed tomography (ct) simulation and treatment planning. |
2023-10-03 |
2023-10-07 |
Not clear |
| R Ratnakumaran, J Mohajer, E Lee, S Withey, D H Brand, D A Loblaw, S Tolan, N van As, A Tre. Validating a Simple Urethra Surrogate Model to Facilitate Dosimetric Analysis to Predict Genitourinary Toxicity. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785406. |
identifying the urethra requires an mri planning scan or foley catheter insertion at ct planning. |
2023-10-03 |
2023-10-07 |
Not clear |
| A Elangovan, K Wachowicz, T Riauka, S Ghosh, J Yun, A Abraham, A Waheed, H Daly, H K Warkentin, D M Severin, K J Josep. Significance of Radiomics in Predicting Local Control for Patients with Malignant Liver Tumors Treated Using Stereotactic Body Radiotherapy. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785484. |
we routinely deliver stereotactic body radiotherapy (sbrt) in malignant liver tumors using planning computed tomography (ct) and magnetic resonance images (mri) to aid target definition. |
2023-10-03 |
2023-10-07 |
Not clear |
| J A Perez-Sanchez, R J Brisson, K E Hitchcock, R A Zlotecki, Y Badyal, C Liu, G Ya. Clinical Evaluation of Deep Learning-Based Auto-Segmentation toward MRI-Only Prostate Radiotherapy. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785525. |
a recent advanced mr scanner allows for an mri-only workflow owing to its ability to generate synthetic ct (mrcat) that enables accurate dose calculation and treatment planning. |
2023-10-03 |
2023-10-07 |
Not clear |
| J Y Wang, Y Chen, D Pham, J Lewis, B M Beadle, M F Gensheimer, Q T Le, X Gu, L Xin. Prospective Clinical Adoption of Artificial Intelligence for Organ Contouring in Head and Neck Radiation Treatment Planning. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785549. |
patients that undergo head and neck (h&n) radiation therapy (rt) require laborious delineation of organs-at-risk (oars) on computed tomography (ct) scans in a treatment planning system (tps) to minimize radiation to normal tissue. |
2023-10-03 |
2023-10-07 |
Not clear |
| J Yang, W Q Xiong, S M Wang, J Y Chen, L Ca. A Cascaded Deep Learning-Based Cardiac Substructures Segmentation Frame and on Non-Gated Non-Enhanced Planning CT Scans in Breast Cancer Patients. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785557. |
a cascaded deep learning-based cardiac substructures segmentation frame and on non-gated non-enhanced planning ct scans in breast cancer patients. |
2023-10-03 |
2023-10-07 |
Not clear |
| J Yang, W Q Xiong, S M Wang, J Y Chen, L Ca. A Cascaded Deep Learning-Based Cardiac Substructures Segmentation Frame and on Non-Gated Non-Enhanced Planning CT Scans in Breast Cancer Patients. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785557. |
to develop a deep learning-based segmentation frame for cardiac substructures especially coronary arteries (cas) on non-gated non-enhanced planning computed tomography (ct) scans in breast cancer (bc) patients. |
2023-10-03 |
2023-10-07 |
Not clear |
| J Du, P Shen, S Huang, X Yan. Is a Deep Learning Based Segmentation Model Trained on planning CTs Transferable for Segmentation of Organs at Risk in Replanning CTs? International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785560. |
to evaluate the differences in the segmentation of organs at risk (oars) in planning and replanning radiotherapy ct images, and to assess the feasibility of using deep learning segmentation models trained on planning radiotherapy cts for the contouring of oars in replanning radiotherapy cts. |
2023-10-03 |
2023-10-07 |
Not clear |
| Y Zhang, X Ye, J Ge, D Guo, D Zheng, H Yu, Y Chen, G Yao, Z Lu, A Yuille, L Lu, D Jin, S Ya. Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785566. |
in clinical practice, radiation oncologists manually delineate the gtv in planning ct with the help of diagnostic mri. |
2023-10-03 |
2023-10-07 |
Not clear |
| L Lin, Z Wei, L C Jia, C Guo, G Q Zhou, Y X Yang, S M He, W Zhang, Y Su. Automated Contouring of Cervical Lymph Nodes and Clinical Target Volumes for Nasopharyngeal Carcinoma Based on Deep Learning and Experience Constraints. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785805. |
in this work, we proposed an ai automated contouring tool for gtvn and ctvs for radiotherapy of npc on the plain scans of planning compute tomography (ct). |
2023-10-03 |
2023-10-07 |
Not clear |
| Y Peng, S Chen, Y Liu, L Zhao, P Liu, Q An, C Zhao, X Deng, R L Deraniyagala, C W Stevens, X Din. Mitigation of Dosimetric Uncertainty in MRI-Based Proton Planning Using Spot-Scanning Proton Arc (SPArc) Technique. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785844. |
mri-based synthetic ct (sct) images created using generative adversarial network (gan) have been demonstrated to be feasible for intensity-modulated proton therapy (impt) planning. |
2023-10-03 |
2023-10-07 |
Not clear |
| M Benayu. Dosimetry Validation of MR-Only Treatment Planning Based upon the Synthetic MRCAT Pelvis with Continuous Hounsfield Units in Prostate Cancer. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785916. |
mr-based radiotherapy delivery systems are increasingly encouraging treatment planning based upon an ai generated synthetic ct created from an mr image. |
2023-10-03 |
2023-10-07 |
Not clear |
| C R Buckey, M Armstrong, S Chitsazzadeh, D Hobbis, E L Clouser, S H Patel, J Smetanick, J Pettit, Y Ron. A Free, Open-Source Toolkit to Produce 3D Bolus in the Clinic. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785922. |
these materials can be applied at the time of simulation and included in a planning ct scan, or can be added during the planning process and first physically applied at the time of treatment. |
2023-10-03 |
2023-10-07 |
Not clear |
| S Chen, S Shen, E A Simiele, Z Iqbal, D N Stanley, X Wu, J Peacock, M B Yusuf, S Marcrom, C Cardena. Artificial Intelligence-Assisted Automated Applicator Digitization for Fully-Automated Gynecological High-Dose Rate Brachytherapy Treatment Planning. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785937. |
to automate the digitization of plastic and titanium applicators used in interstitial and hybrid gynecological (gyn) computed tomography (ct)-based high-dose-rate (hdr) brachytherapy procedures to accelerate the planning and reduce the potential for planning errors. |
2023-10-03 |
2023-10-07 |
Not clear |
| Z Hu, R Yin, C Sun, Q Li, Y Che. A Comparison of Two Plan Optimization Methods in Three-Dimensional Brachytherapy for Cervical Cancer. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785940. |
to compare dose distributions created by using two inverse planning simulated annealing (ipsa) and hybrid inverse planning optimization (hipo) in three-dimensional (with ct image guidance) brachytherapy planning for cervical cancer. |
2023-10-03 |
2023-10-07 |
Not clear |
| C Choi, N P Mankuzhy, J Jiang, S Elguindi, M Thor, A Rimner, H Veeraraghava. Clinical Feasibility of Deep Learning-Based CT during Treatment CBCT Tumor Registration-Segmentation in Thoracic Radiotherapy (RT). International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785946. |
in thoracic rt, low image contrast, imaging artifact, and geometry and image modality differences from the planning ct (pct) typically limits accurate tumor segmentation and registration. |
2023-10-03 |
2023-10-07 |
Not clear |
| C Choi, M Thor, J Jiang, A Rimner, H Veeraraghava. Determining the Dosimetric Accuracy of Deep Learning-Based Fully Automated Registration-Segmentation Approach for Thoracic Cancer Organs-at-Risk Contouring. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785947. |
for adaptive radiation therapy (art), the contours on the planning ct (pct) are frequently propagated to cone-beam ct (cbct) via deformable image registration and manually edited, which is observer-dependent and time-consuming. |
2023-10-03 |
2023-10-07 |
Not clear |
| C Han, C Wong, O M Oderinde, W T Watkins, K Qing, B Liu, T M Williams, A Li. Comparison of AI-Based Auto-Segmentation Quality with Different Daily IGRT Imaging Modalities for Adaptive Radiotherapy Treatment Planning. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785979. |
modern ai-based auto-segmentation tools may be applied on daily computed tomography (ct) images in an image-guided radiotherapy course to facilitate evaluation of anatomical variations and adaptive treatment planning. |
2023-10-03 |
2023-10-07 |
Not clear |
| C Han, C Wong, O M Oderinde, W T Watkins, K Qing, B Liu, T M Williams, A Li. Comparison of AI-Based Auto-Segmentation Quality with Different Daily IGRT Imaging Modalities for Adaptive Radiotherapy Treatment Planning. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37785979. |
however, most ai auto-segmentation models are trained with high-quality diagnostic or planning ct image data. |
2023-10-03 |
2023-10-07 |
Not clear |