ArticleMedical physics2020
LDeform: Longitudinal deformation analysis for adaptive radiotherapy of lung cancer.
Article in Medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Seq2Morph: A deep learning deformable image registration algorithm for longitudinal imaging studies and adaptive radiotherapy.Medical physics · 2023Article
- Image-Guided Percutaneous Ablation for Primary and Metastatic Tumors.Diagnostics (Basel, Switzerland) · 2022Review
- Deformation driven Seq2Seq longitudinal tumor and organs-at-risk prediction for radiotherapy.Medical physics · 2021Article
- Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field.Frontiers in oncology · 2021Review
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Authors and funding
6 authors.
Funding
Abstract
purposeConventional radiotherapy for large lung tumors is given over several weeks, during which the tumor typically regresses in a highly nonuniform and variable manner. Adaptive radiotherapy would ideally follow these shape changes, but we need an accurate method to extrapolate tumor shape changes. We propose a computationally efficient algorithm to quantitate tumor surface shape changes that makes minimal assumptions, identifies fixed points, and can be used to predict future tumor geometrical response.
methodsA novel combination of nonrigid iterative closest point (ICP) and local shape-preserving map algorithms, LDeform, is developed to enable visualization, prediction, and categorization of both diffeomorphic and nondiffeomorphic tumor deformations during an extended course of radiotherapy.
resultsWe tested and validated our technique on 31 longitudinal CT/MRI subjects, with five to nine time points each. Based on this tumor deformation analysis, regions of local growth, shrinkage, and anchoring are identified and tracked across multiple time points. This categorization in turn represents a rational biomarker of local response. Results demonstrate useful predictive power, with an averaged Dice coefficient and surface mean-squared error of 0.85 and 2.8 mm, respectively, over all images.
conclusionsWe conclude that the LDeform algorithm can facilitate the adaptive decision-making process during lung cancer radiotherapy.
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