IMRT vs. Passively Scattered Proton Therapy (PSPT) for Locally Advanced Non-small Cell Lung CA (LA NSCLC) Randomized Trial - Is there Equipoise?

New radiotherapy approaches in locally advanced non-small cell lung cancer

Radiotherapy plays a major role in the treatment of patients with locally advanced non-small cell lung cancer (NSCLC), particularly since most patients are not suitable for surgery due to the extent of their disease, advanced age and multiple co-morbidities. Despite advances in local and systemic therapies local control and survival remain poor and there is a sense that a therapeutic plateau has been reached with conventional approaches. Strategies for the intensification of radiotherapy such as dose escalation have shown encouraging results in phase I-II trials, but the outcome of the phase III Radiation Therapy Oncology Group 0617 trial was surprisingly disappointing. Hyperfractionated and/or accelerated fractionating schedules have demonstrated superior survival compared to conventional fractionation at the expense of greater oesophageal toxicity. Modern radiotherapy techniques such as the integration of 4-dimensional computed tomography for planning, intensity modulated radiotherapy and image-guided radiotherapy have substantially enhanced the accuracy of the radiotherapy delivery through improved target conformality and incorporation of tumour respiratory motion. A number of studies are evaluating personalised radiation treatment including the concept of isotoxic radiotherapy and the boosting of the primary tumour based on functional imaging. Proton beam therapy is currently under investigation in locally advanced NSCLC. These approaches, either alone or in combination could potentially allow for further dose escalation and improvement of the therapeutic ratio and survival for patients with NSCLC.

A novel dose-based positioning method for CT image-guided proton therapy

PURPOSE

Proton dose distributions can potentially be altered by anatomical changes in the beam path despite perfect target alignment using traditional image guidance methods. In this simulation study, the authors explored the use of dosimetric factors instead of only anatomy to set up patients for proton therapy using in-room volumetric computed tomographic (CT) images.

METHODS

To simulate patient anatomy in a free-breathing treatment condition, weekly time-averaged four-dimensional CT data near the end of treatment for 15 lung cancer patients were used in this study for a dose-based isocenter shift method to correct dosimetric deviations without replanning. The isocenter shift was obtained using the traditional anatomy-based image guidance method as the starting position. Subsequent isocenter shifts were established based on dosimetric criteria using a fast dose approximation method. For each isocenter shift, doses were calculated every 2 mm up to ± 8 mm in each direction. The optimal dose alignment was obtained by imposing a target coverage constraint that at least 99% of the target would receive at least 95% of the prescribed dose and by minimizing the mean dose to the ipsilateral lung.

RESULTS

The authors found that 7 of 15 plans did not meet the target coverage constraint when using only the anatomy-based alignment. After the authors applied dose-based alignment, all met the target coverage constraint. For all but one case in which the target dose was met using both anatomy-based and dose-based alignment, the latter method was able to improve normal tissue sparing.

CONCLUSIONS

The authors demonstrated that a dose-based adjustment to the isocenter can improve target coverage and/or reduce dose to nearby normal tissue.

A methodology for automatic intensity-modulated radiation treatment planning for lung cancer

In intensity-modulated radiotherapy (IMRT), the quality of the treatment plan, which is highly dependent upon the treatment planner's level of experience, greatly affects the potential benefits of the radiotherapy (RT). Furthermore, the planning process is complicated and requires a great deal of iteration, and is often the most time-consuming aspect of the RT process. In this paper, we describe a methodology to automate the IMRT planning process in lung cancer cases, the goal being to improve the quality and consistency of treatment planning. This methodology (1) automatically sets beam angles based on a beam angle automation algorithm, (2) judiciously designs the planning structures, which were shown to be effective for all the lung cancer cases we studied, and (3) automatically adjusts the objectives of the objective function based on a parameter automation algorithm. We compared treatment plans created in this system (mdaccAutoPlan) based on the overall methodology with plans from a clinical trial of IMRT for lung cancer run at our institution. The 'autoplans' were consistently better, or no worse, than the plans produced by experienced medical dosimetrists in terms of tumor coverage and normal tissue sparing. We conclude that the mdaccAutoPlan system can potentially improve the quality and consistency of treatment planning for lung cancer.