2D lag and signal nonlinearity correction in an amorphous silicon EPID and their impact on pretreatment dosimetric verification
Authors: Warkentin B. , Rathee S. , Steciw S. 
Published: October 2012

Purpose:

This investigation provides measurements of signal lag and nonlinearity separately for the Varian aS500 electronic portal imaging device (EPID), and an algorithm to correct for these effects in 2D; their potential impact on intensity modulated radiation therapy (IMRT) verification is also investigated. The authors quantify lag, as a function of both delivered monitor units (MU) and time, by using a range of MUs delivered at a clinically used rate of 400 MU/min. Explicit cumulative lag curves are thus determined for a range of MUs and times between the end of irradiation and the end of image acquisition. Signal nonlinearity is also investigated as a function of total MUs delivered. The family of cumulative lag curves and signal nonlinearity are then used to determine their effects on dynamic multileaf collimator (MLC) (IMRT) deliveries, and to correct for theses effects in 2D.

Methods:

Images acquired with an aS500 EPID and Varis Portal‐Vision software were used to quantify detector lag and signal‐nonlinearity. For the signal lag investigation, Portal‐Visionˈsservice monitor was used to acquire EPID images at a rate of 8 frames/s. The images were acquired during irradiation and 66 s thereafter, by inhibiting the M‐holdoff‐In signal of the Linac for a range of 4.5–198.5 MUs. Relative cumulative lag was calculated by integrating the EPID signal for a time after beam‐off, and normalizing this to the integrated EPID signal accumulated during radiation. Signal nonlinearity was studied by acquiring 10 × 10 cm2 open‐field EPID images in “integrated image” mode for a range of 2–500 MUs, and normalized to the 100 MU case. All data were incorporated into in‐house written software to create a 2D correction map for these effects, using the fieldˈs MLC file and a field‐specific calculated 2D “time‐map,” which keeps track of the time elapsed from the last fluence delivered at each given point in the image to the end of the beam delivery.

Results:

Relative cumulative lag curves reveal that the lag alone can deviate the EPIDˈs perceived dose by as large as 6% (1 MU delivery, 60 s postirradiation). For signal nonlinearity relative to 100 MU, EPID signals per MU of 0.84 and 1.01 were observed for 2 and 500 MUs, respectively. Correction maps were applied to a 1 cm sweeping‐window 14 × 14 cm2 field and clinical head‐and‐neck IMRT field. A mean correction of 1.028 was implemented in the head‐and‐neck field, which significantly reduced lag‐related asymmetries in the EPID images, and restored linearity to the EPID imagerˈs dose response. Corrections made to the sweeping‐field showed good agreement with the treatment planning system‐predicted field, yielding an average percent difference of 0.05% ± 0.91%, compared to the −1.32% ± 1.02% before corrections, or 1.75% ± 1.04% when only a signal nonlinearity correction is made.

Conclusions:

Lag and signal‐nonlinearity have been quantified for an aS500 EPID imager, and an effective 2D correction method has been developed which effectively removes nonlinearity and lag effects. Both of these effects were shown to negatively impact IMRT verifications. Especially fields that involve prolonged irradiation and small overall MUs should be corrected for in 2D.