ESTRO 2023 - Abstract Book

S1435

Digital Posters

ESTRO 2023

Table 1: DoseCHECK (DC) and PerFRACTION (PF) results: ✗ represents a fail and ✓ represents a pass. For all six plans DoseCHECK produced a failure when the central five leaves were changed by 1.0mm. PerFRACTION analysis of EPID measurements produced a failure for all six patients when a single leaf was displaced by 2mm, and when 5 leaves were changed by 1.0mm. Four out of six patient plans failed with a leaf error of only 0.5mm. 31/36 of all generated error plans failed DoseCHECK, PerFRACTION or both, demonstrating that used together they have a high degree of sensitivity for detecting errors. Conclusion DoseCHECK and PerFRACTION modules of SunCHECK Patient are highly sensitive at detecting MLC positional errors introduced into SRS plans, demonstrating that errors in TPS calculations and machine delivery can be detected at the pre treatment stage. PerFRACTION can be safely implemented for SRS patient specific QC, replacing time consuming phantom measurements and thus reducing staff and machine clinical workload.

PO-1720 PSQA with IQM detector for high modulated fields: impact of a better small segments modelling

M. Zani 1 , S. Calusi 2 , T. Zoppi 3 , L. Marrazzo 2,1 , C. Arilli 1 , M. Casati 1 , A. Compagnucci 1 , C. Talamonti 1,2 , S. Pallotta 2,1

1 Azienda Ospedaliero Universitaria Careggi, Medical Physics Unit, Florence, Italy; 2 University of Florence, Experimental and Clinical Biomedical Sciences “Mario Serio”, Florence, Italy; 3 University of Florence, Mathematics and Computer Science “Ulisse Dini”, Florence, Italy Purpose or Objective This work aims to test the Integral Quality Monitor (IQM) detector as a tool for patient-specific QA (PSQA) after an upgrade of the Signal Calculation Model (SCM). This upgrade aimed to increase the system reliability for plans with segments characterized by a small aperture (average x/y dimension of 1cm or lower). The performances of the new IQM SCM were assessed by comparing the QA results of a set of VMAT plans acquired before and after the model upgrade. Correlation between QA results and plan complexity was also investigated. Materials and Methods The IQM system consists of a large transmission IC, mounted on the LINAC collimator face and of a software designed and commissioned to predict the detector output [1]. PSQA is carried out by comparing measured and predicted IQM signal output.

The new IQM SCM, generated after additional small fields measurement, was tested with a three-step process:

1. 84 VMAT plans planned with Monaco® TPS and delivered with an Elekta VersaHD™ LINAC were tested with the original IQM SCM. Plans with a cumulative signal deviation (CSD) ≤ 2.5% (G1) were separated from those showing a CSD>2.5% (G2). The threshold value of 2.5% was suggested by the vendor after the acceptance test.

2. G2 plans QA was performed for a second time using the new SCM.

3. For each plan, the total MUs, the index of modulation (M), the modulation complexity score (MCSv), the mean-field area index (MFC) [2], and the number of segments per plan with an average aperture ≤ 1 cm along both x and y directions, were calculated by using the open-source framework MACARON[3]. [1] M. Pasler et al 2017 Phys. Med. Biol. 62 7440

[2] M. Antoine et al 2019 EJMP 64:98-108

[3] NextGenerationEU programme, Italian DM737 – CUP B15F21005410003, MACARON project https://github.com/tommyippoz/MACARON

Results Step1: Of the 84 VMAT plans, 75 (G1) had a CSV<2.5% (CSD= 0.1%±1.0%), while 9 plans (G2) had a CSD above the threshold (CSD =3.8%±0.7%). Step2: With the new SCM, G2 QA results registered a significant improvement, as shown in Fig.1. Step3: Fig.2 (a,b) shows the distribution of segments with a small average aperture, along x. The two groups' results were statistically different (t-test, p<0.01). On the MLC travel direction (x), the percentage of segments with an average aperture ≤ 1 cm was 2.9% (G1) vs 6.2% (G2), while on jaws direction (y), the percentages for G1 and G2 were 0.6% and 2.9% respectively. In fig.2(c) the plan complexity analysis is shown. The two groups’ results were statistically different in terms of total MUs, M and MFC, indices that are both higher for plans composed by a high number of segments with a small area.