Evidence map›Paper›PMID 37665760›Full record

ArticleMedical physics2023

A quantitative CBCT pipeline based on 2D antiscatter grid and grid-based scatter sampling for image-guided radiation therapy.

Farhang Bayat, Dan Ruan, Moyed Miften, Cem Altunbas

Open access · bronzeAbstract read
In one paragraph

Article in Medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Farhang BayatDepartment of Radiation Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA.
Dan RuanDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Moyed MiftenDepartment of Radiation Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA.
Cem AltunbasDepartment of Radiation Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA.
University of Colorado Denver · USUniversity of California, Los Angeles · US

Funding

Improving quantitative accuracy and tissue visualization in CBCT guided radiation therapyR01CA245270 · NCI · UNIVERSITY OF COLORADO DENVER · PI ALTUNBAS, CEM · 2020 to 2025
$2.1M
A dedicated two dimensional antiscatter grid for CBCT in radiation therapyR21CA198462 · NCI · UNIVERSITY OF COLORADO DENVER · PI ALTUNBAS, CEM · 2016 to 2017
$372k
NCI NIH HHS R01 CA245270NCI NIH HHS R21 CA198462
6 · The paper itself

Abstract

backgroundQuantitative accuracy is critical for expanding the role of cone beam CT (CBCT) imaging from target localization to quantitative treatment monitoring and plan adaptations in radiation therapy. Despite advances in CBCT image quality improvement methods, quantitative accuracy gap between CBCT and multi-detector CT (MDCT) remains. PURPOSE: In this work, a physics-driven approach was investigated that combined robust scatter rejection, raw data correction and iterative image reconstruction to further improve CBCT image quality and quantitative accuracy, referred to as quantitative CBCT (qCBCT).

methodsQCBCT approach includes tungsten 2D antiscatter grid hardware, residual scatter correction with grid-based scatter sampling, image lag, and beam hardening correction for offset detector geometry linac-mounted CBCT. Images were reconstructed with iterative image reconstruction to reduce image noise. qCBCT was evaluated using a variety of phantoms to investigate the effect of object size and its composition on image quality, and image quality was benchmarked against clinical CBCT and gold standard MDCT images used for treatment planning.

resultsQCBCT provided statistically significant improvement in CT number accuracy and reduced image artifacts when compared to clinical CBCT images. When compared to gold standard MDCT, mean HU errors in qCBCT and clinical CBCT were 17 ± 9 and 38 ± 29 HU, respectively. Magnitude of phantom size dependent HU variations were comparable between MDCT and qCBCT images. With iterative reconstruction, contrast-to-noise ratio improved by 25% when compared to clinical CBCT protocols.

conclusionsCombination of novel scatter suppression techniques and other data correction methods in qCBCT provided CT number accuracy comparable to gold standard MDCT used for treatment planning. This approach may potentially improve CBCT's promise in fulfilling the tasks that demand high quantitative accuracy, such as online dose calculations and treatment response assessment, in image guided radiation therapy.

Indexed as

Radiotherapy, Image-GuidedSpiral Cone-Beam Computed TomographyAlgorithmsArtifactsCone-Beam Computed TomographyImage Processing, Computer-AssistedPhantoms, ImagingScattering, Radiationadaptive radiation therapycone beam computed tomography (CBCT)IGRTquantitative imaging

Identifiers

PMID37665760
PMCPMC10840737
OpenAlexW4386415730

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.