Intensity modulation using multileaf collimators: current status

Influence and optimization strategy of the magnetic field in 1.5 T MR-linac liver stereotactic radiotherapy

OBJECTIVE

To compare intensity reduction plans for liver cancer with or without a magnetic field and optimize field and subfield numbers in the intensity-modulated radiotherapy (IMRT) plans designed for liver masses in different regions.

METHODS

This retrospective study included 62 patients who received radiotherapy for liver cancer at Shandong Cancer Hospital. Based on each patient's original individualized intensity-modulated plan (plan1.5 T), a magnetic field-free plan (plan0 T) and static intensity-modulated plan with four different optimization schemes were redesigned for each patient. The differences in dosimetric parameters among plans were compared.

RESULTS

In the absence of a magnetic field in the first quadrant, PTV Dmin increased (97.75 ± 17.55 vs. 100.96 ± 22.78)%, Dmax decreased (121.48 ± 29.68 vs. 119.06 ± 28.52)%, D98 increased (101.35 ± 7.42 vs. 109.35 ± 26.52)% and HI decreased (1.14 ± 0.14 vs. 1.05 ± 0.01). In the absence of a magnetic field in the second quadrant, PTV Dmin increased (84.33 ± 19.74 vs. 89.96 ± 21.23)%, Dmax decreased (105 ± 25.08 vs. 104.05 ± 24.86)%, and HI decreased (1.04 ± 0.25 vs. 0.99 ± 0.24). In the absence of a magnetic field in the third quadrant, PTV Dmax decreased (110.21 ± 2.22 vs. 102.31 ± 26)%, L-P V30 decreased (10.66 ± 9.19 vs. 5.81 ± 3.22)%, HI decreased (1.09 ± 0.02 vs. 0.98 ± 0.25), and PTV Dmin decreased (92.12 ± 4.92 vs. 89.1 ± 22.35)%. In the absence of a magnetic field in the fourth quadrant, PTV Dmin increased (89.78 ± 6.72 vs. 93.04 ± 4.86)%, HI decreased (1.09 ± 0.01 vs. 1.05 ± 0.01) and D98 increased (99.82 ± 0.82 vs. 100.54 ± 0.84)%. These were all significant differences. In designing plans for tumors in each liver region, a total number of subfields in the first area of 60, total subfields in the second zone of 80, and total subfields in the third and fourth zones of 60 or 80 can achieve the dose effect without a magnetic field.

CONCLUSION

In patients with liver cancer, the effect of a magnetic field on the target dose is more significant than that on doses to organs at risk. By controlling the max total number of subfields in different quadrants, the effect of the magnetic field can be greatly reduced or even eliminated.

Detection of IMRT delivery errors using a quantitative 2D dosimetric verification system

We investigated the feasibility of detecting intensity modulated radiotherapy delivery errors automatically using a scalar evaluation of two-dimensional (2D) transverse dose measurement of the complete treatment delivery. Techniques using the gamma index and the normalized agreement test (NAT) index were used to parametrize the agreement between measured and computed dose distributions to seven different scalar metrics. Simulated verifications with delivery errors calculated using a commercially available treatment planning system for 9 prostate and 7 paranasal sinus cases were compared to 433 clinical verifications. The NAT index with 5% and 3 mm criteria that included cold areas outside the planning target volume detected the largest percent of delivery errors. Assuming a false positive rate of 5%, it was able to detect 88% of beam energy changes, 94% of a different patient's plan being delivered, 25% of plans with one beam's collimator rotated by 90 degrees, 81% of rotating one beam's gantry angle by 10 degrees, and 100% of omitting the delivery of one beam. However, no instances of changing one beam's monitor unit setting by 10% or shifting the isocenter by 5 mm were detected. Although the phantom shift could not be detected by the small change it made in the dose distribution, our autopositioning algorithm clearly identified the spatial anomaly. Using tighter 3 %/2 mm criteria or combining dose and distance disagreements in an either/or fashion resulted in poorer delivery error detection. The mean value of the 2D gamma index distribution was less sensitive to delivery errors than the other scalar metrics studied. Although we found that scalar metrics do not have sufficient delivery error detection rates to be used as the sole clinical analysis technique, manually examining 2D dose comparison images would result in a near 100% detection rate while performing an ion chamber measurement alone would only detect 54% of these errors.

MLC leaf width impact on the clinical dose distribution: a Monte Carlo approach

PURPOSE

The influence of the multileaf collimator (MLC) leaf width on the dose distribution in patients treated with conformal radiotherapy and intensity-modulated radiotherapy has been analyzed. This study was based on the Monte Carlo simulation with the beams generated by a linac with the double-focused MLC.

MATERIALS AND METHODS

The transmission through the leaves and the exact shape of the penumbra regions are difficult to model by treatment planning system algorithms. An accurate assessment of the dose variations due to the leaf width change can be achieved by means of Monte Carlo simulation. The BEAM/EGS4 code was used at the Hospital of the Virgen Macarena to model a Siemens PRIMUS linac, featuring an MLC with a leaf width projecting 1 cm at the isocenter. Based on this real model, a virtual head was designed while allowing for a variation of the leaf width projection. Both the real linac and the virtual linac, with leaves projecting 0.5 cm, were used to obtain the dose distributions for several treatments. A few disease sites, including the prostate, head and neck, and endometrium, were selected for the design of the conformal and intensity-modulated radiotherapy treatments with a forward planning algorithm sensitive to the different shapes of the volumes of interest. Isodose curves, differential matrix, gamma function, and the dose-volume histograms (DVHs) corresponding to both MLC models were obtained for all cases. The tumor control probability and the normal tissue complication probability were derived for those cases studied featuring the greatest differences between results for both MLCs.

RESULTS

The impact on the DVHs of changing leaf width projections at the isocenter from 1.0 cm to 0.5 cm was low. Radiobiologic models showed slightly better tumor control probability/normal tissue complication probability values using the virtual MLC with a leaf width projecting 0.5 cm at isocenter in those cases presenting greater differences in the DVHs.

CONCLUSIONS

The impact on the clinical dose distribution due to the MLC leaf width change is low based on the design and conditions used in this study.

Dependence of fluence errors in dynamic IMRT on leaf-positional errors varying with time and leaf number

In d-MLC based IMRT, leaves move along a trajectory that lies within a user-defined tolerance (TOL) about the ideal trajectory specified in a d-MLC sequence file. The MLC controller measures leaf positions multiple times per second and corrects them if they deviate from ideal positions by a value greater than TOL. The magnitude of leaf-positional errors resulting from finite mechanical precision depends on the performance of the MLC motors executing leaf motions and is generally larger if leaves are forced to move at higher speeds. The maximum value of leaf-positional errors can be limited by decreasing TOL. However, due to the inherent time delay in the MLC controller, this may not happen at all times. Furthermore, decreasing the leaf tolerance results in a larger number of beam hold-offs, which, in turn leads, to a longer delivery time and, paradoxically, to higher chances of leaf-positional errors (< or = TOL). On the other end, the magnitude of leaf-positional errors depends on the complexity of the fluence map to be delivered. Recently, it has been shown that it is possible to determine the actual distribution of leaf-positional errors either by the imaging of moving MLC apertures with a digital imager or by analysis of a MLC log file saved by a MLC controller. This leads next to an important question: What is the relation between the distribution of leaf-positional errors and fluence errors. In this work, we introduce an analytical method to determine this relation in dynamic IMRT delivery. We model MLC errors as Random-Leaf Positional (RLP) errors described by a truncated normal distribution defined by two characteristic parameters: a standard deviation sigma and a cut-off value deltax0 (deltaxo approximately TOL). We quantify fluence errors for two cases: (i) deltax0 >> sigma (unrestricted normal distribution) and (ii) deltax0 << sigma (deltax0--limited normal distribution). We show that an average fluence error of an IMRT field is proportional to (i) sigma/ALPO and (ii) deltax0/ALPO, respectively, where ALPO is an Average Leaf Pair Opening (the concept of ALPO was previously introduced by us in Med. Phys. 28, 2220-2226 (2001). Therefore, dose errors associated with RLP errors are larger for fields requiring small leaf gaps. For an N-field IMRT plan, we demonstrate that the total fluence error (if we neglect inhomogeneities and scatter) is proportional to 1/square root of N, where N is the number of fields, which slightly reduces the impact of RLP errors of individual fields on the total fluence error. We tested and applied the analytical apparatus in the context of commercial inverse treatment planning systems used in our clinics (Helios and BrainScan). We determined the actual distribution of leaf-positional errors by studying MLC controller (Varian Mark II and Brainlab Novalis MLCs) log files created by the controller after each field delivery. The analytically derived relationship between fluence error and RLP errors was confirmed by numerical simulations. The equivalence of relative fluence error to relative dose error was verified by a direct dose calculation. We also experimentally verified the truthfulness of fluences derived from the log file data by comparing them to film data.

The design and testing of novel clinical parameters for dose comparison

PURPOSE

New multidimensional dose comparison parameters, normalized agreement test (NAT) values and the NAT index, are introduced and compared with an ideal dose comparison parameter. In this article, we analyze a clinically based two-dimensional (2D) quantitative dose comparison case using a wide range of new and old comparison tools. In doing so, we address the benefits and limitations of many common dose comparison tools.

METHODS AND MATERIALS

An in-house software program was developed using the MATLAB 6.5 programming language. Using this software, several 2D quantitative dose comparison parameters were calculated for the computed and measured dose distributions in an intensity-modulated radiotherapy (IMRT) prostate cancer treatment. The experiences gained in the design and testing of this software program form the basis of the dose comparison tool analysis.

RESULTS

Each dose comparison tool has unique strengths and weaknesses. The underlying assumptions of the NAT values and NAT index lead to acceptable generalized behavior, but are not always valid.

CONCLUSION

A thorough 2D quantitative dose comparison analysis can only be accomplished through the use of many dose comparison tools. The introduction of the NAT index allows a 2D dose comparison to be reduced to a single value, and is thus ideal for setting clinical acceptance criteria for IMRT verifications.

Commissioning and quality assurance for MLC-based IMRT

The commissioning and quality assurance (QA) associated with the implementation of linear accelerator multileaf collimator (MLC)-based intensity-modulated radiation therapy (IMRT) at the University of Nebraska Medical Center are described. Our MLC-based IMRT is implemented using the PRIMUS linear accelerator interface through the IMPAC record and verification system to the CORVUS treatment planning system. The "step-and-shoot" technique is used for this MLC-based IMRT. Commissioning process requires the verification of predefined parameters available on the CORVUS and the collection of some machine data. The machine data required are output factor in air and output factor in phantom, and percent depth dose for a number of field sizes. In addition, inplane and crossplane dose profiles of 4 x 4 cm and 20 x 20 cm field sizes and diagonal dose profiles of a large field size have to be measured. Validation of connectivity and dose model includes the use of uniform intensity bar strips, triangular-shaped nonuniform intensity bar strip, and N-shaped target. QA procedure follows the recommendation of the AAPM Task Group No. 40 report. In addition, the leaf position accuracy and reproducibility of the MLC should be checked at regular intervals. The dose validation is implemented through the hybrid plan where the patient beam parameters are applied to a flat phantom. Independent dose calculation method is used to confirm the dose delivery plan and data input to the CORVUS.