Cone beam computed tomography (CBCT) has been routinely used in image-guided radiation therapy (IGRT) for precise treatment guidance. One major concern that hinders its wide applications is the excessive imaging dose, especially when repeated scans are performed on a patient over a long IGRT treatment course up to 6 weeks. CBCT delivers up to 100~300 cGy per treatment course to healthy organs, elevating biologic risks such as secondary cancer or genetic defects. This is particularly risky for radiation sensitive patient groups, e.g. pediatric patients, for whom CBCT-guided IGRT is prohibited. Therefore, despite the tremendous image guidance capability of CBCT, the benefits of its daily use are counteracted by excessive x-ray dose. Developing novel CBCT technologies with much reduced imaging dose is critically necessary to address the clinical demands of safe image guidance and to maximally exploiting its potential in all clinical scenarios. One unique feature of CBCT in IGRT is that a patient is repeatedly imaged in a treatment course. Currently, the same CBCT protocol is used for all fractions, and research efforts are devoted to reduce dose to each individual scan. Yet, the inter-fraction variation of CBCT image contents is expected to be small. Exploiting this unique correlation along the temporal dimension can in principle offer a further dose reduction for CBCTs in IGRT, in addition to those current low-dose techniques. In light of this fact, we propose a Progressive Dose Control (PDC) scheme. Specifically, as opposed to the current CBCT practice using a static scan protocol, a dynamically adjusted protocol is applied, which gradually reduce the imaging dose at each fraction. The CBCT quality is maintained by incorporating all previously available images as prior knowledge via a Prior Image- based Non-Local Means (PINLM) method. The increased amount of prior knowledge prevents the loss of image quality due to dose reduction, allowing for a progressive dose reduction each time, and a significant overall reduction over the entire course. Over the years, we have accumulated necessary expertise for this project. We will accomplish our goal by pursuing the following specific aims (SAs): SA1. Protocol Optimization. We will 1) integrate various components previously developed into a whole system, and 2) perform Monte Carlo simulation studies to determine the optimal PDC scan protocol. SA2. Protocol Evaluation. Through both phantom studies and patient studies, we will evaluate our system with emphases on the clinical benefits and practicality of PDC. The PDC scheme maximally utilizes prior knowledge offered by the unique feature of repeated CBCT scans in IGRT. By effectively incorporating information extracted from the conventionally omitted temporal dimension, our approach empowers IGRT with a paradigm-shifting and practical dose reduction scheme. Clinical introduction will benefit patients under IGRT enormously by providing safe and accurate image guidance, especially those patients to whom CBCT-based IGRT is currently limited.
This project proposes a progressive dose control (PDC) scheme for cone beam CT (CBCT) based image guided radiation therapy that dynamically reduces CBCT dose over a treatment course. The daily CBCT image quality is maintained by incorporating prior information given by previously available images via a Prior-Image Non-Local Means approach, which is implemented on graphics processing units (GPUs) to achieve a clinically acceptable efficiency. This research will lead to a paradigm shift from current clinical practice using a static CBCT scan protocol, resulting in dramatically reduced imaging dose to patients.
|Yan, Hao; Tian, Zhen; Shao, Yiping et al. (2016) A new scheme for real-time high-contrast imaging in lung cancer radiotherapy: a proof-of-concept study. Phys Med Biol 61:2372-88|
|Xu, Yuan; Yan, Hao; Ouyang, Luo et al. (2015) A method for volumetric imaging in radiotherapy using single x-ray projection. Med Phys 42:2498-509|
|Xu, Yuan; Bai, Ti; Yan, Hao et al. (2015) A practical cone-beam CT scatter correction method with optimized Monte Carlo simulations for image-guided radiation therapy. Phys Med Biol 60:3567-87|
|Yan, Hao; Wang, Xiaoyu; Shi, Feng et al. (2014) Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: cone/ring artifact correction and multiple GPU implementation. Med Phys 41:111912|
|Lu, Wenting; Yan, Hao; Gu, Xuejun et al. (2014) Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study. Phys Med Biol 59:6251-66|