| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Maria Borshchenko, Kseniya Eremeeva, Valery Svistushki. CT and MRI in the Preoperative Planning of Balloon Dilation of the Eustachian Tube: Literature Review. The Indian journal of radiology & imaging. vol 33. issue 4. 2023-10-09. PMID:37811176. |
the objective of this study was to review the role of computed tomography (ct) and magnetic resonance imaging (mri) in the preoperative planning of bet. |
2023-10-09 |
2023-10-15 |
Not clear |
| Yunji Seol, Jin Ho Song, Kyu Hye Choi, Young Kyu Lee, Byung-Ock Choi, Young-Nam Kan. Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT. European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society. 2023-10-09. PMID:37814013. |
predicting vertebral compression fracture prior to spinal sbrt using radiomics from planning ct. |
2023-10-09 |
2023-10-15 |
Not clear |
| Yunji Seol, Jin Ho Song, Kyu Hye Choi, Young Kyu Lee, Byung-Ock Choi, Young-Nam Kan. Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT. European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society. 2023-10-09. PMID:37814013. |
the purpose of the study was to develop a predictive model for vertebral compression fracture (vcf) prior to spinal stereotactic body radiation therapy (sbrt) using radiomics features extracted from pre-treatment planning ct images. |
2023-10-09 |
2023-10-15 |
Not clear |
| Bo Pang, Hang Si, Muyu Liu, Wensheng Fu, Yiling Zeng, Hongyuan Liu, Ting Cao, Yu Chang, Hong Quan, Zhiyong Yan. Comparison and evaluation of different deep learning models of synthetic CT generation from CBCT for nasopharynx cancer adaptive proton therapy. Medical physics. 2023-10-06. PMID:37800874. |
however, its inaccurate ct numbers limit its applicability in dose calculation and treatment planning. |
2023-10-06 |
2023-10-07 |
Not clear |
| Logan G Thomas, Peter N Chalmers, Heath B Henninger, Evan W Davis, Robert Z Tashjia. Preoperative Planning Software Does Not Accurately Predict Range of Motion in Reverse Total Shoulder Arthroplasty. The Journal of the American Academy of Orthopaedic Surgeons. 2023-10-05. PMID:37797249. |
the purpose of this study was to determine whether preoperative planning software (pps) accurately predicts clinical range of motion (rom) in patients with reverse total shoulder arthroplasty 1 year postoperatively with preoperative and postoperative computed tomography (ct) scans. |
2023-10-05 |
2023-10-07 |
Not clear |
| Robert Schindhelm, Gary Razinskas, Jonas Ringholz, Johannes Kraft, Otto A Sauer, Sonja Wegene. Evaluation of a head rest prototype for rotational corrections in three degrees of freedom. Journal of applied clinical medical physics. 2023-10-04. PMID:37793069. |
cranial stereotactic irradiations require accurate reproduction of the planning ct patient position at the time of treatment, including removal of rotational offsets. |
2023-10-04 |
2023-10-07 |
Not clear |
| Liming Zhong, Zeli Chen, Hai Shu, Kaiyi Zheng, Yin Li, Weicui Chen, Yuankui Wu, Jianhua Ma, Qianjin Feng, Wei Yan. Multi-scale Tokens-Aware Transformer Network for Multi-region and Multi-sequence MR-to-CT Synthesis in A Single Model. IEEE transactions on medical imaging. vol PP. 2023-10-03. PMID:37782590. |
the superiority of magnetic resonance (mr)-only radiotherapy treatment planning (rtp) has been well demonstrated, benefiting from the synthesis of computed tomography (ct) images which supplements electron density and eliminates the errors of multi-modal images registration. |
2023-10-03 |
2023-10-07 |
Not clear |
| Y Wang, J Zhu, D Guo, K Yan, L Lu, S Wang, D Jin, X Ye, Q Wan. Deep Learning for Automatic Prediction of Lymph Node Station Metastasis in Esophageal Cancer Patients from Contrast-Enhanced CT. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37784523. |
the diagnosis of lymph node (ln) metastasis in computed tomography (ct) is an essential yet challenging task in esophageal cancer staging and treatment planning. |
2023-10-03 |
2023-10-07 |
Not clear |
| J Hecko, L Knybel, J Cvek, O Jiravsky, R Neuwirth, M Sramko, M Penhaker, M Ryba. Optimized Target Delineation Procedure for the Radiosurgery Treatment of Ventricular Tachycardia: Observer-Independent Accuracy. International journal of radiation oncology, biology, physics. vol 117. issue 2S. 2023-10-03. PMID:37784817. |
the simplest method of target delineation based on manual transfer of ctv from several 3d visualizations (electroanatomic mapping system) to planning ct slices (2d) was subjective and very time consuming. |
2023-10-03 |
2023-10-07 |
Not clear |
| 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. |
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. |
2023-10-03 |
2023-10-07 |
Not clear |
| 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 |