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PO-0839: Personalized VMAT optimization for pancreatic SBRT
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versa. The figure outlines the normalized (with respect to the Treatment plans) tallied quantities on patient-bypatient basis. In 8 out of the 40 maximum doses the Treatment plans demonstrated lower absolute doses. For none of the 30 tallied average (or mean) doses the Treatment plans were better than the Auto plans. The average differences over the patient cohort range from 7% to +36%.
Conclusion This study demonstrates the ability of creating highquality MRL treatment plans for rectum cancer. Given the differences in machine characteristics, some plan quality differences were found between MRL treatment plans and current clinical practice. These results support a wellprepared clinical introduction of the MRL. PO-0839 Personalized VMAT optimization for pancreatic SBRT I. Mihaylov1, L. Portelance1 1 University of Miami, Radiation Oncology, Miami, USA Purpose or Objective Inverse IMRT planning is a very labor intensive, trial-anderror process, aiming to find a middle ground between the conflicting objectives of adequate tumor coverage and sparing nearby healthy tissues. Even if a plan is clinically acceptable, that plan is unlikely to be the best solution, where the healthy tissue is spared as much as possible. To a large extent the optimization process is user and treatment planning system specific, where more experienced users generate better quality radiotherapy plans. This work introduces a fully automated inverse optimization approach and its application to pancreatic SBRT. Material and Methods Ten cases, treated breath-hold, were retrospectively studied. The outlined anatomical structures consisted of a PTV, and OARs including duodenum, stomach, bowel, spinal cord, liver, and kidneys. In each case the prescription was set to 35 Gy (to 95% of the PTV) in 5 fractions. The treatment plans were created by experienced dosimetrists, following national and international clinical protocols. Those treatment plans were generated for VMAT delivery. For each case an additional plan was generated with the newly proposed automated inverse optimization. This optimization is based on unattended step-wise reduction of DVHs, where several DVH objectives were specified for each OAR. The automated plans utilized the same number of arcs, with the same parameters as the treatment plans. The treatment and the automated plans (Treatment and Auto hereafter) were compared on commonly used clinical dosimetric parameters. Those parameters included DPTV95% (dose to 95% of the PTV), DDuodenum1%, DBowel1%, DStomach1%, DCord1%, DLivermean, Drt_kidneymean, and Dlt_kidneymean. The doses to 1% of the volumes of duodenum, bowel, stomach, and spinal cord were used as surrogates for maximum doses. The prescriptions for the Auto plans matched the prescriptions of the Treatment plans. Results The first row in the table below summarizes the average values of the tallied quantities (over the ten patients) as derived from the treatment plans. The second row outlines the average differences (in per-cent) between the dosimetric endpoints as well as the range of the differences between the Treatment and the Autooptimized plans. The negative differences indicate that the Auto plans result in lower absolute doses and vice-
Conclusion Unattended inverse optimization holds great potential for further personalization and tailoring of radiotherapy to particular patient anatomies. It utilizes minimum user time and it can be used at the very minimum as a good starting point for personalized precision radiotherapy. PO-0840 Hypofractionated intensity modulated radiotherapy in patients with immediate breast reconstruction D.P. Rojas1, R. Ricotti2, M.C. Leonardi2, A. Viola1, S. Dicuonzo1, D. Ciardo2, R. Cambria3, R. Luraschi3, F. Cattani3, C. Fodor2, A. Morra2, V. Dell'Acqua2, V. Galimberti4, R. Orecchia5, B.A. Jereczek-Fossa1 1 European Institute of Oncology - University of Milan, Department of Radiation Oncology - Department of Oncology and Hemato-oncology, MIlan, Italy 2 European Institute of Oncology, Department of Radiation Oncology, MIlan, Italy 3 European Institute of Oncology, Department of Medical Physics, MIlan, Italy 4 European Institute of Oncology, Department of Surgery, MIlan, Italy 5 European Institute of Oncology - University of Milan, Department of Medical Imaging and Radiation Sciences -
versa. The figure outlines the normalized (with respect to the Treatment plans) tallied quantities on patient-bypatient basis. In 8 out of the 40 maximum doses the Treatment plans demonstrated lower absolute doses. For none of the 30 tallied average (or mean) doses the Treatment plans were better than the Auto plans. The average differences over the patient cohort range from 7% to +36%.
Conclusion This study demonstrates the ability of creating highquality MRL treatment plans for rectum cancer. Given the differences in machine characteristics, some plan quality differences were found between MRL treatment plans and current clinical practice. These results support a wellprepared clinical introduction of the MRL. PO-0839 Personalized VMAT optimization for pancreatic SBRT I. Mihaylov1, L. Portelance1 1 University of Miami, Radiation Oncology, Miami, USA Purpose or Objective Inverse IMRT planning is a very labor intensive, trial-anderror process, aiming to find a middle ground between the conflicting objectives of adequate tumor coverage and sparing nearby healthy tissues. Even if a plan is clinically acceptable, that plan is unlikely to be the best solution, where the healthy tissue is spared as much as possible. To a large extent the optimization process is user and treatment planning system specific, where more experienced users generate better quality radiotherapy plans. This work introduces a fully automated inverse optimization approach and its application to pancreatic SBRT. Material and Methods Ten cases, treated breath-hold, were retrospectively studied. The outlined anatomical structures consisted of a PTV, and OARs including duodenum, stomach, bowel, spinal cord, liver, and kidneys. In each case the prescription was set to 35 Gy (to 95% of the PTV) in 5 fractions. The treatment plans were created by experienced dosimetrists, following national and international clinical protocols. Those treatment plans were generated for VMAT delivery. For each case an additional plan was generated with the newly proposed automated inverse optimization. This optimization is based on unattended step-wise reduction of DVHs, where several DVH objectives were specified for each OAR. The automated plans utilized the same number of arcs, with the same parameters as the treatment plans. The treatment and the automated plans (Treatment and Auto hereafter) were compared on commonly used clinical dosimetric parameters. Those parameters included DPTV95% (dose to 95% of the PTV), DDuodenum1%, DBowel1%, DStomach1%, DCord1%, DLivermean, Drt_kidneymean, and Dlt_kidneymean. The doses to 1% of the volumes of duodenum, bowel, stomach, and spinal cord were used as surrogates for maximum doses. The prescriptions for the Auto plans matched the prescriptions of the Treatment plans. Results The first row in the table below summarizes the average values of the tallied quantities (over the ten patients) as derived from the treatment plans. The second row outlines the average differences (in per-cent) between the dosimetric endpoints as well as the range of the differences between the Treatment and the Autooptimized plans. The negative differences indicate that the Auto plans result in lower absolute doses and vice-
Conclusion Unattended inverse optimization holds great potential for further personalization and tailoring of radiotherapy to particular patient anatomies. It utilizes minimum user time and it can be used at the very minimum as a good starting point for personalized precision radiotherapy. PO-0840 Hypofractionated intensity modulated radiotherapy in patients with immediate breast reconstruction D.P. Rojas1, R. Ricotti2, M.C. Leonardi2, A. Viola1, S. Dicuonzo1, D. Ciardo2, R. Cambria3, R. Luraschi3, F. Cattani3, C. Fodor2, A. Morra2, V. Dell'Acqua2, V. Galimberti4, R. Orecchia5, B.A. Jereczek-Fossa1 1 European Institute of Oncology - University of Milan, Department of Radiation Oncology - Department of Oncology and Hemato-oncology, MIlan, Italy 2 European Institute of Oncology, Department of Radiation Oncology, MIlan, Italy 3 European Institute of Oncology, Department of Medical Physics, MIlan, Italy 4 European Institute of Oncology, Department of Surgery, MIlan, Italy 5 European Institute of Oncology - University of Milan, Department of Medical Imaging and Radiation Sciences -