Assessing target localization accuracy across different soft-tissue matching protocols using end-exhalation breath-hold cone-beam computed tomography in patients with pancreatic cancer

Sasaki, Makoto; Kishi, Noriko; Ashida, Ryo; Nakata, Manabu; Yoshimura, Masataka; Mizutani, Takashi

doi:10.1093/jrr/rrad048

Cited by 1 publication

(3 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study also observed inter-observer variability, consistent with findings from previous studies. 3,8,9,[17][18][19] These findings emphasize the need for auto-matching techniques to minimize inter-observer variability and achieve consistent soft-tissue matching.…”

Section: Inter-observer Variabilitymentioning

confidence: 78%

“…3 Sasaki et al demonstrated substantial interobserver variability and increased time requirements for soft-tissue matching in pancreatic cancer, particularly among trainees with limited experience in IGRT. 8 Furthermore, Zhang et al conducted an analysis of the impact of inter-observer variability, underscoring its greater influence on organs at risk (OARs) than on the target in prostate cancer. 9 Current radiotherapy systems are unable to overcome the well-acknowledged challenges associated with softtissue matching.…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have consistently identified inter‐ and intra‐observer variability as great issues in soft‐tissue matching. 3 , 8 , 9 Hirose et al emphasized the importance of considering inter‐observer variability when determining the clinical target volume for PTV margins. 3 Sasaki et al demonstrated substantial inter‐observer variability and increased time requirements for soft‐tissue matching in pancreatic cancer, particularly among trainees with limited experience in IGRT.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy

Kishigami,

Nakamura,

Okamoto

et al. 2023

J Applied Clin Med Phys

Self Cite

View full text Add to dashboard Cite

PurposeThis study aimed to demonstrate the potential clinical applicability of an organ‐contour‐driven auto‐matching algorithm in image‐guided radiotherapy.MethodsThis study included eleven consecutive patients with cervical cancer who underwent radiotherapy in 23 or 25 fractions. Daily and reference magnetic resonance images were converted into mesh models. A weight‐based algorithm was implemented to optimize the distance between the mesh model vertices and surface of the reference model during the positioning process. Within the cost function, weight parameters were employed to prioritize specific organs for positioning. In this study, three scenarios with different weight parameters were prepared. The optimal translation and rotation values for the cervix and uterus were determined based on the calculated translations alone or in combination with rotations, with a rotation limit of ±3°. Subsequently, the coverage probabilities of the following two planning target volumes (PTV), an isotropic 5 mm and anisotropic margins derived from a previous study, were evaluated.ResultsThe percentage of translations exceeding 10 mm varied from 9% to 18% depending on the scenario. For small PTV sizes, more than 80% of all fractions had a coverage of 80% or higher. In contrast, for large PTV sizes, more than 90% of all fractions had a coverage of 95% or higher. The difference between the median coverage with translational positioning alone and that with both translational and rotational positioning was 1% or less.ConclusionThis algorithm facilitates quantitative positioning by utilizing a cost function that prioritizes organs for positioning. Consequently, consistent displacement values were algorithmically generated. This study also revealed that the impact of rotational corrections, limited to ±3°, on PTV coverage was minimal.

show abstract