Adaptive Radiation for Lung Cancer

Gomez, Daniel R.; Chang, Joe Y.

doi:10.1155/2011/898391

Cited by 29 publications

(21 citation statements)

References 55 publications

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“…Moreover, various clinical works have also been reported, which highlights the use of 4D-CT in planning the radiation therapy. 3,4 Thus, the usefulness of 4D-CT is clearly being appreciated in the medical imaging and radiological community.…”

Section: Introductionmentioning

confidence: 99%

Resolution enhancement of lung 4D‐CT via group‐sparsity

Bhavsar

Lian

et al. 2013

Medical Physics

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Purpose: 4D-CT typically delivers more accurate information about anatomical structures in the lung, over 3D-CT, due to its ability to capture visual information of the lung motion across different respiratory phases. This helps to better determine the dose during radiation therapy for lung cancer. However, a critical concern with 4D-CT that substantially compromises this advantage is the low superior-inferior resolution due to less number of acquired slices, in order to control the CT radiation dose. To address this limitation, the authors propose an approach to reconstruct missing intermediate slices, so as to improve the superior-inferior resolution. Methods: In this method the authors exploit the observation that sampling information across respiratory phases in 4D-CT can be complimentary due to lung motion. The authors' approach uses this locally complimentary information across phases in a patch-based sparse-representation framework. Moreover, unlike some recent approaches that treat local patches independently, the authors' approach employs the group-sparsity framework that imposes neighborhood and similarity constraints between patches. This helps in mitigating the trade-off between noise robustness and structure preservation, which is an important consideration in resolution enhancement. The authors discuss the regularizing ability of group-sparsity, which helps in reducing the effect of noise and enables better structural localization and enhancement. Results: The authors perform extensive experiments on the publicly available DIR-Lab Lung 4D-CT dataset [R. Castillo, E. Castillo, R. Guerra, V. Johnson, T. McPhail, A. Garg, and T. Guerrero, "A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets," Phys. Med. Biol. 54, 1849-1870 (2009)]. First, the authors carry out empirical parametric analysis of some important parameters in their approach. The authors then demonstrate, qualitatively as well as quantitatively, the ability of their approach to achieve more accurate and better localized results over bicubic interpolation as well as a related state-of-the-art approach. The authors also show results on some datasets with tumor, to further emphasize the clinical importance of their method. Conclusions:The authors have proposed to improve the superior-inferior resolution of 4D-CT by estimating intermediate slices. The authors' approach exploits neighboring constraints in the group-sparsity framework, toward the goal of achieving better localization and noise robustness. The authors' results are encouraging, and positively demonstrate the role of group-sparsity for 4D-CT resolution enhancement.

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Section: Introductionmentioning

confidence: 99%

Resolution enhancement of lung 4D‐CT via group‐sparsity

Bhavsar

Lian

et al. 2013

Medical Physics

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“…Image-guided radiotherapy has also provided the ability to accurately and reproducibly position targets on a daily basis (7). These advances have opened the door to the concept of adapting radiation therapy during the course of treatment to maximize target coverage and minimize the dose to normal tissues (8). As this relatively new concept develops and is integrated into practice, questions about how adaptive replanning may affect clinical outcomes, such as local control and toxicity, need to be addressed.…”

Section: Introductionmentioning

confidence: 99%

Adaptive/Nonadaptive Proton Radiation Planning and Outcomes in a Phase II Trial for Locally Advanced Non-small Cell Lung Cancer

Koay

Lege

Mohan

et al. 2012

International Journal of Radiation Oncology*Biology*Physics

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Purpose To analyze dosimetric variables and outcomes after adaptive replanning of radiotherapy during concurrent high-dose protons and chemotherapy for locally advanced non-small cell lung cancer (NSCLC). Methods and Materials Nine of 44 patients with stage III NSCLC in a prospective phase II trial of concurrent paclitaxel/carboplatin with proton radiation [74 Gy(RBE) in 37 fractions] had modifications to their original treatment plans after re-evaluation revealed changes that would compromise coverage of the target volume or violate dose constraints; plans for the other 35 patients were not changed. We compared patients with adaptive plans with those with nonadaptive plans in terms of dosimetry and outcomes. Results At a median follow-up of 21.2 months (median overall survival, 29.6 months), no differences were found in local, regional, or distant failure or overall survival between groups. Adaptive planning was used more often for large tumors that shrank to a greater extent (median, 107.1 cm3 adaptive and 86.4 cm3 non-adaptive; median changes in volume, 25.3% adaptive and 1.2% non-adaptive; p<0.01). The median number of fractions delivered using adaptive planning was 13 (range, 4–22). Adaptive planning generally improved sparing of the esophagus (median absolute decrease in V70, 1.8%; range, 0–22.9%) and spinal cord (median absolute change in maximum dose, 3.7 Gy; range, 0–13.8 Gy). Without adaptive replanning, target coverage would have been compromised in 2 cases (57% and 82% coverage without adaptation vs. 100% for both with adaptation); neither patient experienced local failure. Radiation-related grade 3 toxicity rates were similar between groups. Conclusions Adaptive planning can reduce normal tissue doses and prevent target misses, particularly for patients with large tumors that shrink substantially during therapy. Adaptive plans seem to have acceptable toxicity and achieve similar local, regional, and distant control and overall survival, even in patients with larger tumors, versus non-adaptive plans.

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“…Exceptions can be made per physicians' discretion for cases that normal tissue sparing is critical, such as for patients with a very large initial tumor volume and normal dose can be close or exceed the tolerance with the initial plan. One proposal is to treat the initial target volume for at least 50 Gy, the standard dose for microscopic disease, and then treat the reduced volume to the full dose with a boost [35].…”

Section: Treatment Volume With Tumor Shrinkagementioning

confidence: 99%

Adaptive Radiotherapy for Lung Cancer Using Uniform Scanning Proton Beams

Zheng¹

2017

Radiotherapy

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Lung cancer remains the leading cause of cancer death in North America and is one of the major indications for proton therapy. Proton beams provide a superior dose distribution due to their finite ranges, but where they stop in the tissue is very sensitive to anatomical change. To ensure optimal target coverage and normal tissue sparing in the presence of geometrical variations, such as tumor shrinkage and other anatomical changes, adaptive planning is necessary in proton therapy of lung cancer. The objective of the chapter is to illustrate the rationale, process, and strategies in adaptive lung cancer treatment using uniform scanning proton beams. In addition, practical considerations for adaptive proton planning are discussed, such as software limitations, the associated costs and risks, and the criteria on whether and how to adapt a plan.

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Adaptive Radiation for Lung Cancer

Cited by 29 publications

References 55 publications

Resolution enhancement of lung 4D‐CT via group‐sparsity

Resolution enhancement of lung 4D‐CT via group‐sparsity

Adaptive/Nonadaptive Proton Radiation Planning and Outcomes in a Phase II Trial for Locally Advanced Non-small Cell Lung Cancer

Adaptive Radiotherapy for Lung Cancer Using Uniform Scanning Proton Beams

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