Improved healthy tissue sparing in proton therapy of lung tumors using statistically sound robust optimization and evaluation

Time is NTCP: Should we maximize patient throughput or perform online adaptation on proton therapy systems?

BACKGROUND

Compared to conventional radiotherapy (XT), proton therapy (PT) may improve normal tissue complication probabilities (NTCP). However, PT typically requires higher adaptation rates due to an increased sensitivity to anatomical changes. Systematic online adaptation may address this issue, but it requires additional replanning time, decreasing patient throughput. Therefore, less patients would benefit in such case from PT for a given machine capacity, with results in worse NTCP.

AIM

To investigate the trade-off between PT patient throughput and NTCP gain as a function of the time needed for adaptation.

METHODS

A retrospective database of 14 lung patients with two repeated 4DCTs was used to compare NTCP values between XT and PT for NTCP2ym (2-year mortality), NTCPdysphagia and NTCPpneumonitis. Four scenarios were considered for PT: no adaptation using clinical robustness parameters (4D robust optimization, 3 % range error and PTV-equivalent setup errors); systematic online adaptation with clinical robustness parameters; setup errors reduced to 4 mm and to 2 mm. Dose was accumulated on the planning CT. The number of patients treated with PT depended on the extra time needed for adaptation, assuming an 8-hours capacity (assuming 14 patients a day; thus minimum 34.2 min per treatment session if there is no or instantaneous adaptation).

RESULTS

Baseline NTCP gains (PT against XT without adaptation) equaled 6.9 %, 6.1 %, and 7.7 % for NTCP2ym, NTCPdysphagia and NTCPpneumonitis, respectively. Using instantaneous online adaptation and setup errors of 2 mm, the overall gains were then 10.7 %, 13.6 % and 12.4 %. Taking into account loss of capacity, 13.7 min was the maximum extra-time allowed to complete adaptation and maintain an advantage on all three metrics for the 2-mm setup error scenario.

CONCLUSION

This study highlights the critical importance of keeping short online adaptation times when using systems with limited capacity like PT.

Robustness evaluation of pencil beam scanning proton therapy treatment planning: A systematic review

Compared to conventional radiotherapy using X-rays, proton therapy, in principle, allows better conformity of the dose distribution to target volumes, at the cost of greater sensitivity to physical, anatomical, and positioning uncertainties. Robust planning, both in terms of plan optimization and evaluation, has gained high visibility in publications on the subject and is part of clinical practice in many centers. However, there is currently no consensus on the methods and parameters to be used for robust optimization or robustness evaluation. We propose to overcome this deficiency by following the modified Delphi consensus method. This method first requires a systematic review of the literature. We performed this review using the PubMed and Web Of Science databases, via two different experts. Potential conflicts were resolved by a third expert. We then explored the different methods before focusing on clinical studies that evaluate robustness on a significant number of patients. Many robustness assessment methods are proposed in the literature. Some are more successful than others and their implementation varies between centers. Moreover, they are not all statistically or mathematically equivalent. The most sophisticated and rigorous methods have seen more limited application due to the difficulty of their implementation and their lack of widespread availability.

Selection of breathing phase number in 4D scanned proton treatment planning optimization for lung tumors

The standard four-dimensional (4D) treatment planning includes all breathing states in the optimization process, which is time-consuming. This work was aimed to optimize the number of intermediate phases needed for 4D proton treatment planning optimization to reduce the computational cost. Five 4D optimization strategies adopting different numbers of intermediate states and one three-dimensional (3D) optimization plan were studied for fifteen lung cancer patients treated with scanned protons, optimizing on all ten phases (4D_10), two extreme phases (4D_2), six phases during the exhalation stage (4D_6EX), six phases during the inhalation stage (4D_6IN), two extreme phases plus an intermediate state (4D_3) and average computed tomography image (3D), respectively. The 4D dose evaluation was conducted on all the ten phases, considering the interplay effect. The resulting doses accumulated on the reference phase were computed and compared. Compared to the 4D optimization plans, the 3D optimization plan performed inferiorly in target coverage, but superiorly in organ at risks (OARs) sparing. For the 4D optimization, all the five 4D plans showed similar performance in OARs protection. However, the 4D_6EX and 4D_6IN strategies out-performed the 4D_2 and 4D_3 plans in dose homogeneity. The computing times of the 4D_2, 4D_3, 4D_6EX and 4D_6IN approaches decreased to 32%, 41%, 66% and 67% of the 4D_10 method, respectively. Thus, our study suggested that the use of all phases during inhalation or exhalation stage might be a feasible approach substituting for the full phase strategy to reduce the calculation load while guaranteeing the plan quality for scanned proton therapy.

Proton versus photon radiation therapy: A clinical review

While proton radiation therapy offers substantially better dose distribution characteristics than photon radiation therapy in certain clinical applications, data demonstrating a quantifiable clinical advantage is still needed for many treatment sites. Unfortunately, the number of patients treated with proton radiation therapy is still comparatively small, in some part due to the lack of evidence of clear benefits over lower-cost photon-based treatments. This review is designed to present the comparative clinical outcomes between proton and photon therapies, and to provide an overview of the current state of knowledge regarding the effectiveness of proton radiation therapy.

Dosimetric robustness of lung tumor photon radiotherapy evaluated from multiple event CT imaging

PURPOSE

Intrafractional respiratory motion is a concern for lung tumor radiotherapy but full evaluation of its impact is hampered by the lack of images representing the true motion. This study presents a novel evaluation using free-breathing images acquired over realistic treatment times to study the dosimetric impact of respiratory motion in photon radiotherapy.

METHODS

Cine-CT images of 14 patients with lung cancer acquired during eight minutes of free-breathing at three occasions were used to simulate dose tracking of four different planning methods. These methods aimed to deliver 54 Gy in three fractions to D_50% of the target and were denoted as robust 4D (RB4), homogeneous fluence to the ITV (FLU) and an isodose prescription to the ITV with a high central dose (ISD), concurrently renormalized (IRN). Differences in dose coverage probability and homogeneity between the methods were quantified. Correlations between underdosage and attributes regarding the tumor and its motion were investigated.

RESULTS

Despite tumor motion amplitudes being larger than in the 4DCT all but FLU achieved the intended CTV D_50% for the cohort average. For all methods but IRN at least 93% of the patients would have received 95% of the intended dose. No differences in D_50% were found between RB4 and ISD nor IRN. However, RB4 led to better homogeneity.

CONCLUSIONS

Tumor motion in free-breathing not covered by the 4DCT had a small impact on dose. The RB4 is recommended for planning of free-breathing treatments. No factor was found that consistently correlated dose degradation with patient or motion attributes.