Intelligent 4D CT sequence scanning (i4DCT): Concept and performance evaluation

Werner, René; Sentker, Thilo; Madesta, Frederic; Gauer, Tobias; Hofmann, Christian

doi:10.1002/mp.13632

Cited by 27 publications

(55 citation statements)

References 31 publications

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“…The present letter demonstrates feasibility of implementing the recently proposed concept of intelligent 4D CT sequence scanning (i4DCT) on a CT scanner platform. It extends the i4DCT concept paper 15 and earlier RSG 4D CT articles, [11][12][13] which were mainly in silico and theoretical proof of concept studies, by presenting the first measurements using an automated breathing signal-guided 4D CT scanning protocol and resulting image data.…”

Section: Discussionmentioning

confidence: 82%

“…Issues related to the >100% breathing cycle were reduced by the implemented reference curvebased projection binning, 7 during which projection data corresponding to breathing signal amplitudes above the reference curve height were not used for reconstruction. Moreover, based on the parameterization of i4DCT, 15 the <50% amplitude breathing cycle was not considered during reconstruction after i4DCT projection data acquisition. Overall i4DCT scan and beam on time for this scenario was 82% and 20% longer compared to spiral 4D CT.…”

Section: Resultsmentioning

confidence: 99%

“…The present study was intended to illustrate the feasibility of implementing i4DCT (more precisely the i4DCT core functionality 15 ) on a CT scanner. Due to the prototypical character of the implementation, acquisition of patient image data is not yet feasible.…”

Section: Methodsmentioning

confidence: 99%

“…Inner workings and parameters of i4DCT are detailed in our concept article. 15 The implemented i4DCT core workflow consists of two central steps: (a) an initial learning period to establish a reference patient-specific breathing cycle representation for data-driven i4DCT parameter adaptation and (b) online breathing signal-guided sequence mode scanning. While (a) is already part of the current generation CT scanners, (b) was to be implemented on the scanner.…”

Section: A the I4dct Core Conceptmentioning

confidence: 99%

“…14 Actual implementation of the RSG 4D CT principle as an automated protocol on an existing CT scanner that is ready to be seamlessly integrated into existing clinical workflows has not been described so far. With intelligent 4D CT sequence scanning (i4DCT), 15 we recently proposed a novel sequence scanning concept that builds on the idea of RSG 4D CT, but the i4DCT workflow and selected parameters were specifically designed to allow for direct CT scanner implementation. The presented data supported the potential of online breathing signal analysis to improve projection data coverage and 4D CT reconstruction.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent 4D CT sequence scanning (i4DCT): First scanner prototype implementation and phantom measurements of automated breathing signal‐guided 4D CT

et al. 2020

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Four-dimensional (4D) computed tomography (CT) imaging is an essential part of current 4D radiotherapy treatment planning workflows, but clinical 4D CT images are often affected by artifacts. The artifacts are mainly caused by breathing irregularity during data acquisition, which leads to projection data coverage issues for currently available commercial 4D CT protocols. It was proposed to improve projection data coverage by online respiratory signal analysis and signal-guided CT tube control, but related work was always theoretical and presented as pure in silico studies. The present work demonstrates a first CT prototype implementation along with respective phantom measurements for the recently introduced intelligent 4D CT (i4DCT) sequence scanning concept (

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Section: Discussionmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: A the I4dct Core Conceptmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Intelligent 4D CT sequence scanning (i4DCT): First scanner prototype implementation and phantom measurements of automated breathing signal‐guided 4D CT

et al. 2020

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Investigating the effects of table movement and sag on optical surrogate‐driven respiratory‐guided computed tomography

Lackner,

Dietrich,

Karius

et al. 2024

J Applied Clin Med Phys

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PurposeRespiratory‐guided computed tomography (CT) typically employs breathing motion surrogates to feed image reconstruction or visual breathing coaching. Our study aimed to assess the impact of table movements and table sag on the breathing curves recorded in four‐dimensional (4D) CT and deep‐inspiration breath‐hold (DIBH) CT.MethodsFor breathing curve measurements, static and dynamic phantom scenarios were used. Breathing curves were recorded using three different surrogate systems and the impact of table sag due to weights of up to 130 kg was analyzed and compared to a non‐weighted setting, respectively. The calibration procedure of the system used as an input for the visual coaching device used for clinical DIBH CT scans was adapted. We evaluated corresponding breathing curves acquired during DIBH and 4DCT scans of altogether 70 patients using various stability metrics.ResultsThe various surrogate systems showed consistent table sag measurements below 4 mm, even under loads up to 130 kg, compared to a reference scan conducted without additional weight. Higher weight loads were related to steeper table sag fall‐offs towards the deepest table position. For DIBH CT scans, the visual guidance was heavily affected by artifacts. This resulted in breathing threshold limits, which could not be achieved by 48% (n = 21) of the, respectively, examined patients. Using the new calibration workflow, the baseline drift was compensated better and 90% (n = 20) of the addressed patients stayed within the thresholds. The evaluated table sag in clinical 4DCT scans (n = 29) stayed below 3 mm compared to the non‐weighted situation.ConclusionTable movement and sag can impact breathing curves recorded by different surrogate systems. Correcting table movement and sag artifacts is crucial for reliable breathing curve acquisition in respiratory‐guided CT.

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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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Intelligent 4D CT sequence scanning (i4DCT): Concept and performance evaluation

Cited by 27 publications

References 31 publications

Intelligent 4D CT sequence scanning (i4DCT): First scanner prototype implementation and phantom measurements of automated breathing signal‐guided 4D CT

Intelligent 4D CT sequence scanning (i4DCT): First scanner prototype implementation and phantom measurements of automated breathing signal‐guided 4D CT

Investigating the effects of table movement and sag on optical surrogate‐driven respiratory‐guided computed tomography

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

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