1er BEST OF ASTRO - COLOMBIA 2021 - 26 DE MARZO 2021
Módulo: Artificial intelligence I
Físico. Jaider Vásquez
Físico. Alberto Adrada
  • Quality Assurance of Contouring for NRG Oncology/RTOG 1308 Clinical Trial Based onAutomated Segmentation with Deep Active Learning. 

  • Comparing deep learning-based auto-segmentation of organs at risk and clinical target volumes to expert inter-observer variability in radiotherapy planning. 

  • External validation and radiologist comparison of a deep learning model (dlm) to identify extranodal extension (ene) in head and neck squamous cell carcinoma (hnscc) with pretreatment computed tomography (ct) imaging. 

  • A Deep-Learning Based 3D Tumor Motion Prediction Algorithm for Non-Invasive Intra-Fractional Tumor-Tracked Radiotherapy (nifteRT) on Linac-MR. 

Módulo: Applied radiation biology 
Físico. Alejandro Marín
Físico. Juliana Sandoval
  • Imaging-driven Biophysical Model for the Differentiation of Tumor Progression from Radiation Necrosis 

  • Effective Volume of Parotid Glands for Assessing Radiation Injury during Radiation Therapy for Head and Neck Cancer 

  • Habitat Evolution Imaging Biomarkers to Assess Early Response and Predict Treatment Outcomes in Oropharyngeal Cancer 

  • Dose-distribution-driven pet image-based outcome prediction (ddd-piop): a framework design for oropharyngeal cancer imrt application 

  • Predicting late radiation-induced xerostomia with parotid pet biomarkers and dose metrics. 

Módulo: Patient Safety
Físico. Luz Adriana Maya
  • Optimizing Efficiency and Safety in External Beam Radiotherapy Using Automated Plan Check (APC) Tool and Six Sigma Methodology 

  • Reducing Treatment Delays with a Modified No-Fly Policy 

  • Targeted needs assessment of dosimetry and treatment planning education for united states radiation oncology residents. 

  • Patient safety and process improvements in radiation therapy through 10 years of incident reporting and learning.

Módulo: Artificial Intelligence II
Físico. Juan Carlos Paz
Físico. Luis Carlos Medina
  • Applying a machine learning approach to predict acute radiation toxicities for head and neck cancer patients. 

  • Deep-learning based automatic delineation improves ctv contouring quality and efficiency for pathological n2 (pn2) non-small cell lung cancer (nsclc) receiving post-operation radiation therapy. 

  • Elevated coronary artery calcium quantified by a deep learning model from radiotherapy planning scans predicts mortality in lung cancer. 

  • Implementation of machine learning-based treatment planning tool for whole breast radiotherapy using irregular surface compensator technique. 

Módulo: Tracking and MR-LINAC
Físico. Johnny Burbano
Físico. Isaias Mendoza
  • Markerless Tumor Tracking using Fast-kV Switching Dual Energy Imaging with the On-Board Imager of a Commercial Linac. 

  • Real-Time Scatter Imaging during Lung Stereotactic Body Radiation Therapy (SBRT) Treatment: An Initial Report. 

  • Real-time kv target tracking in pancreatic sbrt: characterizing the clinical and dosimetric impact. 

  • First clinical use of 4d-mri for online adaptive mr-grt on a high field mr-linac. 5. Clinical imrt irradiation with an mr-linac system: a methodology and preliminary results for a real-time verification of spatial accuracy of dose delivery.