There has been some concern that organ motion, especially intra-fraction organ motion due to breathing, can negate the potential merit of intensity-modulated radiotherapy (IMRT). We wanted to find out whether this concern is justified. Specifically, we wanted to investigate whether IMRT delivery techniques with moving parts, e.g., with a multileaf collimator (MLC), are particularly sensitive to organ motion due to the interplay between organ motion and leaf motion. We also wanted to know if, and by how much, fractionation of the treatment can reduce the effects. We performed a statistical analysis and calculated the expected dose values and dose variances for volume elements of organs that move during the delivery of the IMRT. We looked at the overall influence of organ motion during the course of a fractionated treatment. A linear-quadratic model was used to consider fractionation effects. Furthermore, we developed software to simulate motion effects for IMRT delivery with an MLC, with compensators, and with a scanning beam. For the simulation we assumed a sinusoidal motion in an isocentric plane. We found that the expected dose value is independent of the treatment technique. It is just a weighted average over the path of motion of the dose distribution without motion. If the treatment is delivered in several fractions, the distribution of the dose around the expected value is close to a Gaussian. For a typical treatment with 30 fractions, the standard deviation is generally within 1% of the expected value for MLC delivery if one assumes a typical motion amplitude of 5 mm (1 cm peak to peak). The standard deviation is generally even smaller for the compensator but bigger for scanning beam delivery. For the latter it can be reduced through multiple deliveries ('paintings') of the same field. In conclusion, the main effect of organ motion in IMRT is an averaging of the dose distribution without motion over the path of the motion. This is the same as for treatments with conventional beams. Additional effects that are specific to the IMRT delivery technique appear to be relatively small, except for the scanning beam.

Respiration-induced tumour motion can potentially compromise the use of intensity-modulated radiotherapy (IMRT) as a dose escalation tool for lung tumour treatment. We have experimentally investigated the intra-fractional organ motion effects in lung IMRT treatments delivered by multi-leaf collimator (MLC). An in-house made motor-driven platform, which moves sinusoidally with an amplitude of 1 cm and a period of 4 s, was used to mimic tumour motion. Tumour motion was simulated along cranial-caudal direction while MLC leaves moved across the patient from left to right, as in most clinical cases. The dose to a point near the centre of the tumour mass was measured according to geometric and dosimetric parameters from two five-field lung IMRT plans. For each field, measurement was done for two dose rates (300 and 500 MU min(-1)), three MLC delivery modes (sliding window, step-and-shoot with 10 and 20 intensity levels) and eight equally spaced starting phases of tumour motion. The dose to the measurement point delivered from all five fields was derived for both a single fraction and 30 fractions by randomly sampling from measured dose values of each field at different initial phases. It was found that the mean dose to a moving tumour differs slightly (<2-3%) from that to a static tumour. The variation in breathing phase at the start of dose delivery results in a maximum variation around the mean dose of greater than 30% for one field. The full width at half maximum for the probability distribution of the point dose is up to 8% for all five fields in a single fraction, but less than 1-2% after 30 fractions. In general, lower dose rate can reduce the motion-caused dose variation and therefore might be preferable for lung IMRT when no motion mitigation techniques are used. From the two IMRT cases we studied where tumour motion is perpendicular to MLC leaf motion, the dose variation was found to be insensitive to the MLC delivery mode.

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The 'tongue-and-groove problem' in step-and-shoot delivery of intensity modulated radiotherapy is investigated. A 'tongue-and-groove' index (TGI) is introduced to quantify the 'tongue-and-groove' effect in step-and-shoot delivery. Four different types of leaf sequencing methods are compared. The sliding window method and the reducing level method use the same number of field segments to deliver the same intensity map, but the TGI is much less for the reducing level method. The leaf synchronization method of Van Santvoort and Heijmen fails in step-and-shoot delivery, but a new method inspired by the method of Van Santvoort and Heijmen is shown to eliminate 'tongue-and-groove' underdosage completely.

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 ...

In standard teletherapy, a treatment plan is generated with the aid of a treatment planning system, but it is common to perform an independent monitor unit verification calculation (MUVC). In exact analogy, we propose and demonstrate that a simple and accurate MUVC in intensity modulated radiotherapy (IMRT) is possible. We introduce the concept of modified Clarkson integration (MCI). In MCI, we exploit the rotational symmetry of scattering to simplify the dose calculation. For dose calculation along a central axis (CAX), we first replace the incident IMRT fluence by an azimuthally averaged fluence. Second, the Clarkson integration is carried over annular sectors instead of over pie sectors. We wrote a computer code, implementing the MCI technique, in order to perform a MUVC for IMRT purposes. We applied the code to IMRT plans generated by CORVUS. The input to the code consists of CORVUS plan data (e.g., DMLC files, jaw settings, MU for each IMRT field, depth to isocenter for each IMRT field), and the output is dose contribution by individual IMRTs field to the isocenter. The code uses measured beam data for Sc, Sp, TPR, (D/MU)ref and includes effects from multileaf collimator transmission, and radiation field offset. On a 266 MHz desktop computer, the code takes less than 15 to calculate a dose. The doses calculated with the MCI algorithm agreed within +/-3% with the doses calculated by CORVUS, which uses a 1 cm x 1 cm pencil beam in dose calculation. In the present version of MCI, skin contour variations and inhomogeneities were neglected.

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In intensity modulated radiotherapy (IMRT), radiation is delivered in a multiple of multileaf collimator (MLC) subfields. A subfield with a small leaf-to-leaf opening is highly sensitive to a leaf-positional error. We introduce a method of identifying and rejecting IMRT plans that are highly sensitive to a systematic MLC gap error (sensitivity to possible random leaf-positional errors is not addressed here). There are two sources of a systematic MLC gap error: centerline mechanical offset (CMO) and, in the case of a rounded end MLC, radiation field offset (RFO). In IMRT planning system, using an incorrect value of RFO introduces a systematic error ARFO that results in all leaf-to-leaf gaps that are either too large or too small by (2*DeltaRFO), whereas assuming that CMO is zero introduces systematic error DeltaCMO that results in all gaps that are too large by DeltaCMO=CMO. We introduce a concept of the average leaf pair Opening (ALPO) that can be calculated from a dynamic MLC delivery file. We derive an analytic formula for a fractional average fluence error resulting from a systematic gap error of Deltax and show that it is inversely proportional to ALPO; explicitly it is equal to Deltax/(ALPO+ 2 * RFO+ epsilon), in which epsilon is generally of the order of 1 mm and Deltax =2 * Delta RFO + CMO. This analytic relationship is verified with independent numerical calculations.