Iterative volume of interest based 4D cone‐beam <scp>CT</scp>

Martin, Ross; Ahmad, Moiz; Hugo, Geoffrey D.; Pan, Tinsu

doi:10.1002/mp.12575

Cited by 3 publications

(3 citation statements)

References 18 publications

(23 reference statements)

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“…Several efforts are being made for improving the image quality of CBCT images, e.g. using artifact reduction techniques, hardware developments, improvement of 4D imaging or the implementation of iterative reconstruction methods [26], [27], [28]. In this study three different CBCT systems were involved: Varian Truebeam (Dataset 1), Elekta Synergy (Datasets 2 and 4) and Varian Clinac (Dataset 3).…”

Section: Discussionmentioning

confidence: 99%

Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence

Timmeren

Elmpt

Leijenaar

et al. 2019

Radiotherapy and Oncology

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Section: Discussionmentioning

confidence: 99%

Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence

Timmeren

Elmpt

Leijenaar

et al. 2019

Radiotherapy and Oncology

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“…However, 4D‐CBCT faced obstacles immediately from its onset, such as poor image quality and low contrast due to undersampling streaking artifacts, remediated with long acquisition times and high radiation doses to fulfill the required projection sampling. In order to address these challenges, investigators proposed different solutions such as using prior information, compressed sensing, motion modeling, deformable registration, and a large variety of other software reconstruction techniques to alleviate the lack of sufficient projection data within each phase bin 235–285 ; optimizing the gantry acquisition protocol specific to the patient respiration and/or fiducial markers to adequately sample the patient respiration while minimizing both scan time and dose 286–300 ; and even developing 4D digital tomosynthesis to get time‐resolved motion data in the most efficient manner, albeit at the expense of full volumetric information 301–305 …”

Section: Daily Image Guidance Of Lung Treatmentsmentioning

confidence: 99%

A modern review of the uncertainties in volumetric imaging of respiratory‐induced target motion in lung radiotherapy

Vergalasova

Cai

2020

Medical Physics

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Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.

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“…Recently developed angiography systems with a flat-panel detector (FPD) allow acquisition of computed tomography (CT)-like cross-sectional images—C-arm-based cone-beam CT images (CBCT), [1–4] and new imaging methods have been investigated for CBCT. [5–7] C-arm-based CBCT setups are classified into 2 types: C-arm-based interventional CBCT systems and dedicated C-arm-based CBCT systems for dental, head and neck, extremity imaging, and mammography. [8] C-arm-based interventional CBCT images aid minimally invasive imaging-guided interventions.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of three-dimensional iterative image reconstruction in C-arm-based interventional cone-beam CT

et al. 2019

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We compared images obtained using a three-dimensional iterative image reconstruction (3D-IIR) algorithm for C-arm-based interventional cone-beam computed tomography (CBCT) with that using the customary reconstruction technique to quantify the effect of reconstruction techniques on image quality. We scanned 2 phantoms using an angiography unit with digital flat-panel system—an elliptical cylinder acrylic phantom to evaluate spatial resolution and a Catphan phantom to evaluate CT number linearity, image noise, and low-contrast resolution. Three-dimensional imaging was calculated using Feldkamp algorithms, and additional image sets were reconstructed using 3D-IIR at 5 settings (Sharp, Default, Soft+, Soft++, Soft+++). We evaluated quality of images obtained using the 6 reconstruction techniques and analyzed variance to test values of the 10% value of each MTF, mean CT number, and contrast-to-noise ratio (CNR), with P < .05 considered statistically significant. Modulation transfer function curves and CT number linearity among images obtained using the customary technique and the 5 3D-IIR techniques showed excellent agreement. Noise power spectrum curves demonstrated uniform noise reduction across the spatial frequency in the iterative reconstruction, and CNR obtained using all but the Sharp 3D-IIR technique was significantly better than that using the customary reconstruction technique (Sharp, P = .1957; Default, P = .0042; others, P < .0001). Use of 3D-IIR, especially the Soft++ and Soft+++ settings, improved visualization of low-contrast targets. Use of a 3D-IIR can significantly improve image noise and low-contrast resolution while maintaining spatial resolution in C-arm-based interventional CBCT, yielding higher quality images that may increase safety and efficacy in interventional radiology.

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Iterative volume of interest based 4D cone‐beam CT

Cited by 3 publications

References 18 publications

Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence

Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence

A modern review of the uncertainties in volumetric imaging of respiratory‐induced target motion in lung radiotherapy

Evaluation of three-dimensional iterative image reconstruction in C-arm-based interventional cone-beam CT

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