Evidence map›Paper›PMID 28380247›Full record

ArticleMedical physics2017

A new CT reconstruction technique using adaptive deformation recovery and intensity correction (ADRIC).

You Zhang, Jianhua Ma, Puneeth Iyengar, Yuncheng Zhong, Jing Wang

Abstract read
In one paragraph

Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

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21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  14. Virtual clinical trials in medical imaging: a review.Journal of medical imaging (Bellingham, Wash.) · 2020
    Review
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

You ZhangDepartment of Radiation Oncology, UT Southwestern Medical Center at Dallas, Dallas, TX, 75390, USA.
Jianhua MaDepartment of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Puneeth IyengarDepartment of Radiation Oncology, UT Southwestern Medical Center at Dallas, Dallas, TX, 75390, USA.
Yuncheng ZhongDepartment of Radiation Oncology, UT Southwestern Medical Center at Dallas, Dallas, TX, 75390, USA.
Jing WangDepartment of Radiation Oncology, UT Southwestern Medical Center at Dallas, Dallas, TX, 75390, USA.

Funding

Next generation 4D-CBCT for lung cancer radiation therapyR01EB020366 · NIBIB · UT SOUTHWESTERN MEDICAL CENTER · PI WANG, JING · 2015 to 2018
$1.4M
NIBIB NIH HHS R01 EB020366
6 · The paper itself

Abstract

purposeSequential same-patient CT images may involve deformation-induced and non-deformation-induced voxel intensity changes. An adaptive deformation recovery and intensity correction (ADRIC) technique was developed to improve the CT reconstruction accuracy, and to separate deformation from non-deformation-induced voxel intensity changes between sequential CT images. MATERIALS AND

methodsADRIC views the new CT volume as a deformation of a prior high-quality CT volume, but with additional non-deformation-induced voxel intensity changes. ADRIC first applies the 2D-3D deformation technique to recover the deformation field between the prior CT volume and the new, to-be-reconstructed CT volume. Using the deformation-recovered new CT volume, ADRIC further corrects the non-deformation-induced voxel intensity changes with an updated algebraic reconstruction technique ("ART-dTV"). The resulting intensity-corrected new CT volume is subsequently fed back into the 2D-3D deformation process to further correct the residual deformation errors, which forms an iterative loop. By ADRIC, the deformation field and the non-deformation voxel intensity corrections are optimized separately and alternately to reconstruct the final CT. CT myocardial perfusion imaging scenarios were employed to evaluate the efficacy of ADRIC, using both simulated data of the extended-cardiac-torso (XCAT) digital phantom and experimentally acquired porcine data. The reconstruction accuracy of the ADRIC technique was compared to the technique using ART-dTV alone, and to the technique using 2D-3D deformation alone. The relative error metric and the universal quality index metric are calculated between the images for quantitative analysis. The relative error is defined as the square root of the sum of squared voxel intensity differences between the reconstructed volume and the "ground-truth" volume, normalized by the square root of the sum of squared "ground-truth" voxel intensities. In addition to the XCAT and porcine studies, a physical lung phantom measurement study was also conducted. Water-filled balloons with various shapes/volumes and concentrations of iodinated contrasts were put inside the phantom to simulate both deformations and non-deformation-induced intensity changes for ADRIC reconstruction. The ADRIC-solved deformations and intensity changes from limited-view projections were compared to those of the "gold-standard" volumes reconstructed from fully sampled projections.

resultsFor the XCAT simulation study, the relative errors of the reconstructed CT volume by the 2D-3D deformation technique, the ART-dTV technique, and the ADRIC technique were 14.64%, 19.21%, and 11.90% respectively, by using 20 projections for reconstruction. Using 60 projections for reconstruction reduced the relative errors to 12.33%, 11.04%, and 7.92% for the three techniques, respectively. For the porcine study, the corresponding results were 13.61%, 8.78%, and 6.80% by using 20 projections; and 12.14%, 6.91%, and 5.29% by using 60 projections. The ADRIC technique also demonstrated robustness to varying projection exposure levels. For the physical phantom study, the average DICE coefficient between the initial prior balloon volume and the new "gold-standard" balloon volumes was 0.460. ADRIC reconstruction by 21 projections increased the average DICE coefficient to 0.954.

conclusionThe ADRIC technique outperformed both the 2D-3D deformation technique and the ART-dTV technique in reconstruction accuracy. The alternately solved deformation field and non-deformation voxel intensity corrections can benefit multiple clinical applications, including tumor tracking, radiotherapy dose accumulation, and treatment outcome analysis.

Indexed as

Phantoms, ImagingTomography, X-Ray ComputedAnimalsSwineCT reconstructiondeformation recoveryintensity correctionmyocardial perfusiontotal variation

Identifiers

PMID28380247
PMCPMC5498224

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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.