Zheng Chang

Overview:

Dr. Chang's research interests include radiation therapy treatment assessment using MR quantitative imaging, image guided radiation therapy (IGRT), fast MR imaging using parallel imaging and strategic phase encoding, and motion management for IGRT.

Positions:

Professor of Radiation Oncology

Radiation Oncology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 2006

University of British Columbia (Canada)

Grants:

Publications:

Commissioning of a 3.0T MR Simulator Dedicated for Radiation Oncology Application

Authors
Wang, C; Yin, F; Craciunescu, O; Faught, A; Chang, Z
MLA Citation
Wang, C., et al. “Commissioning of a 3.0T MR Simulator Dedicated for Radiation Oncology Application.” Medical Physics, vol. 44, no. 6, WILEY, 2017.
URI
https://scholars.duke.edu/individual/pub1308107
Source
wos
Published In
Medical Physics
Volume
44
Published Date

Computer vision analysis captures atypical attention in toddlers with autism.

To demonstrate the capability of computer vision analysis to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder. One hundered and four toddlers of 16-31 months old (mean = 22) participated in this study. Twenty-two of the toddlers had autism spectrum disorder and 82 had typical development or developmental delay. Toddlers watched video stimuli on a tablet while the built-in camera recorded their head movement. Computer vision analysis measured participants' attention and orienting in response to name calls. Reliability of the computer vision analysis algorithm was tested against a human rater. Differences in behavior were analyzed between the autism spectrum disorder group and the comparison group. Reliability between computer vision analysis and human coding for orienting to name was excellent (intra-class coefficient 0.84, 95% confidence interval 0.67-0.91). Only 8% of toddlers with autism spectrum disorder oriented to name calling on >1 trial, compared to 63% of toddlers in the comparison group (p = 0.002). Mean latency to orient was significantly longer for toddlers with autism spectrum disorder (2.02 vs 1.06 s, p = 0.04). Sensitivity for autism spectrum disorder of atypical orienting was 96% and specificity was 38%. Older toddlers with autism spectrum disorder showed less attention to the videos overall (p = 0.03). Automated coding offers a reliable, quantitative method for detecting atypical social orienting and reduced sustained attention in toddlers with autism spectrum disorder.
Authors
Campbell, K; Carpenter, KL; Hashemi, J; Espinosa, S; Marsan, S; Borg, JS; Chang, Z; Qiu, Q; Vermeer, S; Adler, E; Tepper, M; Egger, HL; Baker, JP; Sapiro, G; Dawson, G
MLA Citation
Campbell, Kathleen, et al. “Computer vision analysis captures atypical attention in toddlers with autism.Autism, vol. 23, no. 3, Apr. 2019, pp. 619–28. Pubmed, doi:10.1177/1362361318766247.
URI
https://scholars.duke.edu/individual/pub1308691
PMID
29595333
Source
pubmed
Published In
Autism
Volume
23
Published Date
Start Page
619
End Page
628
DOI
10.1177/1362361318766247

Assessment of Concurrent Stereotactic Radiosurgery and Bevacizumab Treatment of Recurrent Malignant Gliomas Using Multi-Modality MRI Imaging and Radiomics Analysis

URI
https://scholars.duke.edu/individual/pub1308108
Source
wos
Published In
Medical Physics
Volume
44
Published Date
Start Page
3029
End Page
3029

Quality Assurance in Adaptive Radiation Therapy

To ensure measurement accuracy, it is necessary to generate a comprehensive quality assurance (QA) program. “The ‘quality’ of radiation oncology can be defined as the totality of features or characteristics of the radiation oncology service that bear on its ability to satisfy the stated or implied goal of effective patient care” (Kutcher et al. 1994, p. 585). The comprehensive QA program is used to maintain and monitor the performance characteristics of the treatment system, which includes, but is not limited to, the treatment machine, imaging technology, and the planning system. If necessary, action should be taken to correct any unacceptable deviations from the baseline values acquired during acceptance testing and commissioning. Deviation from the baseline values could compromise patient treatment, resulting in suboptimal treatment response and undesirable complication effects. The quality of radiation oncology is therefore directly affected by the acceptance testing and commissioning process. The signifi-cance of the acceptance testing and commissioning process is well-acknowledged, and the corresponding procedures have been published in the literature (Nath et al. 1994; Svensson et al. 1984; Das et al. 2008).
Authors
Chang, Z; O’Daniel, J; Yin, FF
MLA Citation
Chang, Z., et al. “Quality Assurance in Adaptive Radiation Therapy.” Adaptive Radiation Therapy, 2011, pp. 229–44. Scopus, doi:10.1201/b10517-22.
URI
https://scholars.duke.edu/individual/pub1547291
Source
scopus
Published Date
Start Page
229
End Page
244
DOI
10.1201/b10517-22

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy.

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.
Authors
Wang, C; Padgett, KR; Su, M-Y; Mellon, EA; Maziero, D; Chang, Z
MLA Citation
Wang, Chunhao, et al. “Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy.Med Phys, vol. 49, no. 4, Apr. 2022, pp. 2794–819. Pubmed, doi:10.1002/mp.15130.
URI
https://scholars.duke.edu/individual/pub1493024
PMID
34374098
Source
pubmed
Published In
Med Phys
Volume
49
Published Date
Start Page
2794
End Page
2819
DOI
10.1002/mp.15130