Evaluation of multiple image-based modalities for image-guided radiation therapy (IGRT) of prostate carcinoma: a prospective study.

PURPOSE: Setup errors and prostate intrafraction motion are main sources of localization uncertainty in prostate cancer radiation therapy. This study evaluates four different imaging modalities 3D ultrasound (US), kV planar images, cone-beam computed tomography (CBCT), and implanted electromagnetic transponders (Calypso/Varian) to assess inter- and intrafraction localization errors during intensity-modulated radiation therapy based treatment of prostate cancer. METHODS: Twenty-seven prostate cancer patients were enrolled in a prospective IRB-approved study and treated to a total dose of 75.6 Gy (1.8 Gy/fraction). Overall, 1100 fractions were evaluated. For each fraction, treatment targets were localized using US, kV planar images, and CBCT in a sequence defined to determine setup offsets relative to the patient skin tattoos, intermodality differences, and residual errors for each patient and patient cohort. Planning margins, following van Herk's formalism, were estimated based on error distributions. Calypso-based localization was not available for the first eight patients, therefore centroid positions of implanted gold-seed markers imaged prior to and immediately following treatment were used as a motion surrogate during treatment. For the remaining 19 patients, Calypso transponders were used to assess prostate intrafraction motion. RESULTS: The means (µ), and standard deviations (SD) of the systematic (Σ) and random errors (σ) of interfraction prostate shifts (relative to initial skin tattoo positioning), as evaluated using CBCT, kV, and US, averaged over all patients and fractions, were: [µ CBCT = (-1.2, 0.2, 1.1) mm, Σ CBCT = (3.0, 1.4, 2.4) mm, σ CBCT = (3.2, 2.2, 2.5) mm], [µkV = (-2.9, -0.4, 0.5) mm, Σ kV = (3.4, 3.1, 2.6) mm, σ kV = (2.9, 2.0, 2.4) mm], and [µ US = (-3.6, -1.4, 0.0) mm, Σ US = (3.3, 3.5, 2.8) mm, σ US = (4.1, 3.8, 3.6) mm], in the anterior-posterior (A/P), superior-inferior (S/I), and the left-right (L/R) directions, respectively. In the treatment protocol, adjustment of couch was guided by US images. Residual setup errors as assessed by kV images were found to be: µ residual = (-0.4, 0.2, 0.2) mm, Σ residual = (1.0, 1.0,0.7) mm, and σ residual = (2.5, 2.3, 1.8) mm. Intrafraction prostate motion, evaluated using electromagnetic transponders, was: µ intrafxn = (0.0, 0.0, 0.0) mm, Σ intrafxn = (1.3, 1.5, 0.6) mm, and σ intrafxn = (2.6, 2.4, 1.4) mm. Shifts between pre- and post-treatment kV images were: µ kV(post-pre) = (-0.3, 0.8, -0.2), Σ kV(post-pre) = (2.4, 2.7, 2.1) mm, and σ kV(post-pre) = (2.7, 3.2, 3.1) mm. Relative to skin tattoos, planning margins for setup error were within 10-11 mm for all image-based modalities. The use of image guidance was shown to reduce these margins to less than 5 mm. Margins to compensate for both residual setup (interfraction) errors as well as intrafraction motion were 6.6, 6.8, and 3.9 mm in the A/P, S/I, and L/R directions, respectively. CONCLUSIONS: Analysis of interfraction setup errors, performed with US, CBCT, planar kV images, and electromagnetic transponders, from a large dataset revealed intermodality shifts were comparable (within 3-4 mm). Interfraction planning margins, relative to setup based on skin marks, were generally within the 10 mm prostate-to-planning target volume margin used in our clinic. With image guidance, interfraction residual planning margins were reduced to approximately less than 4 mm. These findings are potentially important for dose escalation studies using smaller margins to better protect normal tissues.

Repeat stereotactic body radiation therapy for patients with pulmonary malignancies who had previously received SBRT to the same or an adjacent tumor site.

OBJECTIVES: Retrospective analysis of patients with recurrences at or closely adjacent to the site of prior lung stereotactic body radiation therapy (SBRT) who received repeat SBRT. MATERIALS AND METHODS: Nine patients with non-small cell lung cancer (n = 8) or oligometastatic colonic adenocarcinoma (n = 1) were treated with image-guided lung SBRT to a median of 60 Gy (range, 30-60) in a median of 3 fractions (3-5). Patients developed in-field relapse (n = 3) or recurrence adjacent (≤ 3.5 cm away) to the previous tumor location (n = 6) and received 2 nd lung SBRT to a median of 60 Gy. RESULTS: Median follow-up after 2 nd SBRT was 22 months (4-40). All completed prescribed course of repeat SBRT and acute toxicity was limited. There was no grade >3 late toxicity. 3 (33.3%) patients developed Grade 3 late reactions: 2 pulmonary and 1 chest wall pain. Late pulmonary toxicity included 2 (22.2%) patients with Grade 3 and 3 (33.3%) with Grade 2. One patient (11.1%) had late Grade 3 and 1 (11.1%) Grade 2 chest wall pain. 1 (11.1%) developed Grade 2 late brachial plexopathy. No myelopathy was observed. Two patients developed progression of tumors treated by 2 nd SBRT. Local recurrence free survival and overall survival was 75% and 68.6%, respectively at 2 years. Relative volume of ipsilateral lung receiving 5 Gy (V5) and V10 were lower for 2 nd SBRT. CONCLUSION: Repeat image-guided SBRT for patients with small peripheral recurrences was feasible and severe toxicity was not observed. Additional studies are needed to evaluate the safety and efficacy of lung reirradiation using 2 nd SBRT.

Determination of the initial beam parameters in Monte Carlo linac simulation.

For Monte Carlo linac simulations and patient dose calculations, it is important to accurately determine the phase space parameters of the initial electron beam incident on the target. These parameters, such as mean energy and radial intensity distribution, have traditionally been determined by matching the calculated dose distributions with the measured dose distributions through a trial and error process. This process is very time consuming and requires a lot of Monte Carlo simulation experience and computational resources. In this paper, we propose an easy, efficient, and accurate method for the determination of the initial beam parameters. We hypothesize that (1) for one type of linacs, the geometry and material of major components of the treatment head are the same; the only difference is the phase space parameters of the initial electron beam incident on the target, and (2) most linacs belong to a limited number of linac types. For each type of linacs, Monte Carlo treatment planning system (MC-TPS) vendors simulate the treatment head and calculate the three-dimensional (3D) dose distribution in water phantom for a grid of initial beam energies and radii. The simulation results (phase space files and dose distribution files) are then stored in a data library. When a MC-TPS user tries to model their linac which belongs to the same type, a standard set of measured dose data is submitted and compared with the calculated dose distributions to determine the optimal combination of initial beam energy and radius. We have applied this method to the 6 MV beam of a Varian 21EX linac. The linac was simulated using EGSNRC/BEAM code and the dose in water phantom was calculated using EGSNRC/DOSXYZ. We have also studied issues related to the proposed method. Several common cost functions were tested for comparing measured and calculated dose distributions, including chi2, mean absolute error, dose difference at the penumbra edge point, slope of the dose difference of the lateral profile, and the newly proposed Kappaalpha factor (defined as the fraction of the voxels with absolute dose difference less than alpha%). It was found that the use of the slope of the lateral profile difference or the difference of the penumbra edge points may lead to inaccurate determination of the initial beam parameters. We also found that in general the cost function value is very sensitive to the simulation statistical uncertainty, and there is a tradeoff between uncertainty and specificity. Due to the existence of statistical uncertainty in simulated dose distributions, it is practically impossible to determine the best energy/radius combination; we have to accept a group of energy/radius combinations. We have also investigated the minimum required data set for accurate determination of the initial beam parameters. We found that the percent depth dose curves along or only a lateral profile at certain depth for a large field size is not sufficient and the minimum data set should include several lateral profiles at various depths as well as the central axis percent depth dose curve for a large field size.

On dose distribution comparison.

In radiotherapy practice, one often needs to compare two dose distributions. Especially with the wide clinical implementation of intensity-modulated radiation therapy, software tools for quantitative dose (or fluence) distribution comparison are required for patient-specific quality assurance. Dose distribution comparison is not a trivial task since it has to be performed in both dose and spatial domains in order to be clinically relevant. Each of the existing comparison methods has its own strengths and weaknesses and there is room for improvement. In this work, we developed a general framework for comparing dose distributions. Using a new concept called maximum allowed dose difference (MADD), the comparison in both dose and spatial domains can be performed entirely in the dose domain. Formulae for calculating MADD values for various comparison methods, such as composite analysis and gamma index, have been derived. For convenience in clinical practice, a new measure called normalized dose difference (NDD) has also been proposed, which is the dose difference at a point scaled by the ratio of MADD to the predetermined dose acceptance tolerance. Unlike the simple dose difference test, NDD works in both low and high dose gradient regions because it considers both dose and spatial acceptance tolerances through MADD. The new method has been applied to a test case and a clinical example. It was found that the new method combines the merits of the existing methods (accurate, simple, clinically intuitive and insensitive to dose grid size) and can easily be implemented into any dose/intensity comparison tool.

Synchronized moving aperture radiation therapy (SMART): improvement of breathing pattern reproducibility using respiratory coaching.

Recently, at Massachusetts General Hospital (MGH) we proposed a new treatment technique called synchronized moving aperture radiation therapy (SMART) to account for tumour motion during radiotherapy. The basic idea of SMART is to synchronize the moving radiation beam aperture formed by a dynamic multileaf collimator with the tumour motion induced by respiration. The two key requirements for being able to successfully use SMART in clinical practice are the precise and fast detection of tumour position during the simulation/treatment and the good reproducibility of the tumour motion pattern. To fulfil the first requirement, an integrated radiotherapy imaging system is currently being developed at MGH. The results of a previous study show that breath coaching techniques are required to make SMART an efficient technique in general. In this study, we investigate volunteer and patient respiratory coaching using a commercial respiratory gating system as a respiration coaching tool. Five healthy volunteers, observed during six sessions, and 33 lung cancer patients, observed during one session when undergoing 4D CT scans, were investigated with audio and visual promptings, with free breathing as a control. For all five volunteers, breath coaching was well tolerated and the intra- and inter-session reproducibility of the breathing pattern was greatly improved. Out of 33 patients, six exhibited a regular breathing pattern and needed no coaching, four could not be coached at all due to the patient's medical condition or had difficulty following the instructions, 13 could only be coached with audio instructions and 10 could follow the instructions of and benefit from audio-video coaching. We found that, for all volunteers and for those patients who could be properly coached, breath coaching improves the duty cycle of SMART treatment. However, about half of the patients could not follow both audio and video instructions simultaneously, suggesting that the current coaching technique requires improvements.

A software tool for 2D/3D visualization and analysis of phase-space data generated by Monte Carlo modelling of medical linear accelerators.

A computer program has been developed for novel 2D/3D visualization and analysis of the phase-space parameters of Monte Carlo simulations of medical accelerator radiation beams. The software is written in the IDL language and reads the phase-space data generated in the BEAMnrc/BEAM Monte Carlo code format. Contour and colour-wash plots of the fluence, mean energy, energy fluence, mean angle, spectra distribution, energy fluence distribution, angular distribution, and slices and projections of the 3D ZLAST distribution can be calculated and displayed. Based on our experience of using it at Massachusetts General Hospital, the software has proven to be a useful tool for analysis and verification of the Monte Carlo generated phase-space files. The software is in the public domain.

A technique for respiratory-gated radiotherapy treatment verification with an EPID in cine mode.

Respiratory gating based on external surrogates is performed in many clinics. We have developed a new technique for treatment verification using an electronic portal imaging device (EPID) in cine mode for gated 3D conformal therapy. Implanted radiopaque fiducial markers inside or near the target are required for this technique. The markers are contoured on the planning CT set, enabling us to create digitally reconstructed radiographs (DRRs) for each treatment beam. During the treatment, a sequence of EPID images can be acquired without disrupting the treatment. Implanted markers are visualized in the images and their positions in the beam's eye view are calculated off-line and compared to the reference position by matching the field apertures in corresponding EPID and DRR images. The precision of the patient set-up, the placement of the beam-gating window, as well as the residual tumour motion can be assessed for each treatment fraction. This technique has been demonstrated with a case study patient, who had three markers implanted in his liver. For this patient, the intra-fractional variation of all marker positions in the gating window had a 95% range of 4.8 mm in the SI direction (the primary axis of motion). This was about the same (5 mm) as the residual motion considered in the planning process. The inter-fractional variation of the daily mean positions of the markers, which indicates the uncertainty in the set-up procedure, was within +8.3 mm/-4.5 mm (95% range) in the SI direction for this case.

Synchronized moving aperture radiation therapy (SMART): average tumour trajectory for lung patients.

Synchronized moving aperture radiation therapy (SMART) is a new technique for treating mobile tumours under development at Massachusetts General Hospital (MGH). The basic idea of SMART is to synchronize the moving radiation beam aperture formed by a dynamic multileaf collimator (DMLC) with the tumour motion induced by respiration. SMART is based on the concept of the average tumour trajectory (ATT) exhibited by a tumour during respiration. During the treatment simulation stage, tumour motion is measured and the ATT is derived. Then, the original IMRT MLC leaf sequence is modified using the ATT to compensate for tumour motion. During treatment, the tumour motion is monitored. The treatment starts when leaf motion and tumour motion are synchronized at a specific breathing phase. The treatment will halt when the tumour drifts away from the ATT and will resume when the synchronization between tumour motion and radiation beam is re-established. In this paper, we present a method to derive the ATT from measured tumour trajectory data. We also investigate the validity of the ATT concept for lung tumours during normal breathing. The lung tumour trajectory data were acquired during actual radiotherapy sessions using a real-time tumour-tracking system. SMART treatment is simulated by assuming that the radiation beam follows the derived ATT and the tumour follows the measured trajectory. In simulation, the treatment starts at exhale phase. The duty cycle of SMART delivery was calculated for various treatment times and gating thresholds, as well as for various exhale phases where the treatment begins. The simulation results show that in the case of free breathing, for 4 out of 11 lung datasets with tumour motion greater than 1 cm from peak to peak, the error in tumour tracking can be controlled to within a couple of millimetres while maintaining a reasonable delivery efficiency. That is to say, without any breath coaching/control, the ATT is a valid concept for some lung tumours. However, to make SMART an efficient technique in general, it is found that breath coaching techniques are required.