Faculty Bibliography

Purpose: This study was to investigate the setup accuracy for automatic rotational corrections using 6 degree of freedom (6DoF) couch and online cone beam computerized tomography (CBCT).
Method(s): A commercial phantom (BAT phantom) with tissue and air equivalent materials was scanned with CT Sim at 1.25 mm plane spacing and 0.98 mm pixel size. A 3D plan was generated in Eclipse for the spherical target of 3 cm diameter located at the center of the phantom. Several lowdensity structures were also outlined as organ at risks (OARs) surrounding the target. The phantom was aligned to the treatment position on the 6DoF couch of a Varian TrueBeam with CBCTverification for both target and OARs outlined before varied rotational errors were introduced in pitch and roll using a titled supporting platform and verified by a calibrated digital level. Following CBCT imaging, the setup corrections were calculated online using the 3D-to-3D auto-matching function on Truebeam and compared against the actual rotational error. We analyzed the deviations at different levels of error.
Result(s): The auto-matching on TrueBeam appeared of good quality even for low contrast and small structures. Deviations of the rotational corrections calculated with 6DoF from the measured are summarized in Tables I-III. The max difference in rotation is 0.7degree for both pitch and roll. However, it also has been observed that there were deviations in every degree of both translational and rotational freedom, which may lead to over-correction in clinic
Conclusion(s): 6 DoF couch and auto-matching offers the convenience for automatic corrections of patient setup in conjunction with CBCT imaging. This preliminary study using a phantom revealed the uncertainties of rotational correction by 6DoF without a deformation of the image. Further study is warranted to establish the criteria for the clinical applications of the auto correction with 6DoF and for the necessary physics QA

Purpose: The purpose of this study is to quantify interfractional dosimetric variations in radiotherapy of oropharyngeal cancer and investigate the application of statistical process control (SPC) to determine significantly deviated fractions for management.
Method(s): Thirteen oropharyngeal cancer patients treated by IMRT or VMAT with daily CBCT were retrospectively reviewed. CBCT images of every other fraction were imported to the software Velocity and registered to planning CT using the 6DOF couch shifts generated during patient setup. Using Velocity Adaptive Monitoring module, the setup-corrected CBCT was matched to planning CT using a deformable registration. The module also generated dose volume histograms (DVHs) at each CBCT from planning doses for the deformed plan structure sets. Volumes and dose metrics at each fraction were calculated and rated with plan values to evaluate interfractional dosimetric variations using a SPC framework. T-tests between plan and fraction volumes were performed to find statistically insignificant fractions. Average, upper and lower process capacity limits (UCL, LCL) of each dose metric were derived from these fractions using conventional SPC guidelines.
Result(s): GTV and OAR volumes in first 13 fractions had no significantly changes from the plan, subsequently reduced by 10% to treatment completion, except oral cavity. There were 3%-4% increases in parotid mean doses, but no significant differences in dose metrics of GTVand other OARs. The changes were organ and patient dependent. Control charts for various dose metrics were generated to assess the metrics for individual patient. The occurrences of one or several dose metrics out of the control limits warrant immediate investigation of the fraction.
Conclusion(s): Daily CBCT could be used to monitor dosimetric variations of targets and OARs resulting from volume changes and tissue deformation in oropharyngeal cancer radiotherapy. Treatment review with guidance of a SPC tool may enable objectively and consistently identify significantly deviated fractions

OBJECTIVE:Radiobiological models have been used to calculate the outcomes of treatment plans based on dose-volume relationship. This study examines several radiobiological models for the calculation of tumor control probability (TCP) of intensity modulated radiotherapy plans for the treatment of lung, prostate, and head and neck (H&N) cancers. METHODS:Dose volume histogram (DVH) data from the intensity modulated radiotherapy plans of 36 lung, 26 prostate, and 87  H&N cases were evaluated. The Poisson, Niemierko, and Marsden models were used to calculate the TCP of each disease group treatment plan. The calculated results were analyzed for correlation and discrepancy among the three models, as well as different treatment sites under study. RESULTS:The median value of calculated TCP in lung plans was 61.9% (34.1-76.5%), 59.5% (33.5-73.9%) and 32.5% (0.0-93.9%) with the Poisson, Niemierko, and Marsden models, respectively. The median value of calculated TCP in prostate plans was 85.1% (56.4-90.9%), 81.2% (56.1-88.7%) and 62.5% (28.2-75.9%) with the Poisson, Niemierko, and Marsden models, respectively. The median value of calculated TCP in H&N plans was 94.0% (44.0-97.8%) and 94.3% (0.0-97.8%) with the Poisson and Niemierko models, respectively. There were significant differences between the calculated TCPs with the Marsden model in comparison with either the Poisson or Niemierko model (p < 0.001) for both lung and prostate plans. The TCPs calculated by the Poisson and Niemierko models were significantly correlated for all three tumor sites. CONCLUSION/CONCLUSIONS:There are variations with different radiobiological models. Understanding of the correlation and limitation of a TCP model with dosimetric parameters can help develop the meaningful objective functions for plan optimization, which would lead to the implementation of outcome-based planning. More clinical data are needed to refine and consolidate the model for accuracy and robustness. Advances in knowledge: This study has tested three radiobiological models with varied disease sites. It is significant to compare different models with the same data set for better understanding of their clinical applicability.

Technical innovations and developments in areas such as disease localization, dose calculation algorithms, motion management and dose delivery technologies have revolutionized radiation therapy resulting in improved patient care with superior outcomes. A consequence of the ability to design and accurately deliver complex radiation fields is the need for improved target visualization through imaging. While CT imaging has been the standard of care for more than three decades, the superior soft tissue contrast afforded by MR has resulted in the adoption of this technology in radiation therapy. With the development of real time MR imaging techniques, the problem of real time motion management is enticing. Currently, the integration of an MR imaging and megavoltage radiation therapy treatment delivery system (MR-linac or MRL) is a reality that has the potential to provide improved target localization and real time motion management during treatment. Higher magnetic field strengths provide improved image quality potentially providing the backbone for future work related to image texture analysis - a field known as Radiomics - thereby providing meaningful information on the selection of future patients for radiation dose escalation, motion-managed treatment techniques and ultimately better patient care. On-going advances in MRL technologies promise improved real time soft tissue visualization, treatment margin reductions, beam optimization, inhomogeneity corrected dose calculation, fast multileaf collimators and volumetric arc radiation therapy. This review article provides rationale, advantages and disadvantages as well as ideas for future research in MRI related to radiation therapy mainly in adoption of MRL.

Advances in multimodality imaging, providing accurate information of the irradiated target volume and the adjacent critical structures or organs at risk (OAR), has made significant improvements in delivery of the external beam radiation dose. Radiation therapy conventionally has used computed tomography (CT) imaging for treatment planning and dose delivery. However, magnetic resonance imaging (MRI) provides unique advantages: added contrast information that can improve segmentation of the areas of interest, motion information that can help to better target and deliver radiation therapy, and posttreatment outcome analysis to better understand the biologic effect of radiation. To take advantage of these and other potential advantages of MRI in radiation therapy, radiologists and MRI physicists will need to understand the current radiation therapy workflow and speak the same language as our radiation therapy colleagues. This review article highlights the emerging role of MRI in radiation dose planning and delivery, but more so for MR-only treatment planning and delivery. Some of the areas of interest and challenges in implementing MRI in radiation therapy workflow are also briefly discussed.