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1.
Phys Med ; 103: 1-10, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36182764

RESUMO

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 D50% 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 D50% 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 D50% 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.


Assuntos
Tomografia Computadorizada Quadridimensional , Neoplasias Pulmonares , Humanos , Tomografia Computadorizada Quadridimensional/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/radioterapia , Radiometria , Respiração , Dosagem Radioterapêutica
2.
Int J Comput Assist Radiol Surg ; 14(6): 933-944, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30887421

RESUMO

PURPOSE: MRI slice reordering is a necessary step when three-dimensional (3D) motion of an anatomical region of interest has to be extracted from multiple two-dimensional (2D) dynamic acquisition planes, e.g., for the construction of motion models used for image-guided radiotherapy. Existing reordering methods focus on obtaining a spatially coherent reconstructed volume for each time. However, little attention has been paid to the temporal coherence of the reconstructed volumes, which is of primary importance for accurate 3D motion extraction. This paper proposes a fully automatic self-sorting four-dimensional MR volume construction method that ensures the temporal coherence of the results. METHODS: First, a pseudo-navigator signal is extracted for each 2D dynamic slice acquisition series. Then, a weighted graph is created using both spatial and motion information provided by the pseudo-navigator. The volume at a given time point is reconstructed following the shortest paths in the graph starting that time point of a reference slice chosen based on its pseudo-navigator signal. RESULTS: The proposed method is evaluated against two state-of-the-art slice reordering algorithms on a prospective dataset of 12 volunteers using both spatial and temporal quality metrics. The automated end-exhale extraction showed results closed to the median value of the manual operators. Furthermore, the results of the validation metrics show that the proposed method outperforms state-of-the-art methods in terms of both spatial and temporal quality. CONCLUSION: Our approach is able to automatically detect the end-exhale phases within one given anatomical position and cope with irregular breathing.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Neoplasias Hepáticas/radioterapia , Fígado/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Radioterapia Guiada por Imagem/métodos , Respiração , Algoritmos , Humanos , Imageamento Tridimensional/métodos , Neoplasias Hepáticas/diagnóstico por imagem , Movimento (Física)
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