Setup in a Clinical Workflow and Results of In Vivo Dosimetry Procedure in an Overload Radiation Therapy Department

Abstract

for the prostate and lung tumors. Niemierko model produced marginally different (< 4%) TCPs than that from the Poisson model for the DVH whose minimal dose are less than 20 Gy than the mean dose; however, for DVHs with differences between minimal dose and mean dose greater than 30 Gy, linearly depending on the dose differences, Niemierko-calculated TCPs were substantially smaller than those from Poisson model. For DVHs with Poisson model-calculated TCPs less than 40%, the "Marsden" model produced TCPs < 1%, but linearly increasing from 0 to100% with Poisson model TCPs for the other DVHs. Conclusion: IMRT for prostate and H&N cancers showed higher TCPs than lung cancer treatment calculated using the three TCP models. Poisson and Niemierko model-calculated TCPs were significantly different when the minimal dose was >30 Gy less than the median dose in a DVH. "Marsden" Model showed much sharper dose response than the Poisson and Niemierko models. The radiobiological models should be assessed when applying in IMRT treatment plan and evaluation of prescription models (D100 or D95).

In vivo dosimetry in external beam photon radiotherapy: Requirements and future directions for research, development, and clinical practice

“…Detailed software and hardware requirements regarding the overall system performance, as well as EPID imager, MV image acquisition software and IVD software are presented as Supplementary Material, see Tables S1-S4. Furthermore, for a successful large-scale implementation, EIVD systems must ensure a manageable and configurable workload to guarantee an optimal balance between resources and performance [7,8,48,68]. Automation is essential for large-scale clinical implementation of EIVD systems because it reduces the number of laborintensive, time-consuming, and error-prone tasks [69,70].…”

“…Furthermore, for a successful large-scale implementation, EIVD systems must ensure a manageable and configurable workload to guarantee an optimal balance between resources and performance [7] , [8] , [48] , [68] . Automation is essential for large-scale clinical implementation of EIVD systems because it reduces the number of labor-intensive, time-consuming, and error-prone tasks [69] , [70] .…”