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

Establishing ADC-Based Histogram and Texture Features for Early Treatment-Induced Changes in Head and Neck Squamous Cell Carcinoma.

The purpose of this study was to assess baseline variability in histogram and texture features derived from apparent diffusion coefficient (ADC) maps from diffusion-weighted MRI (DW-MRI) examinations and to identify early treatment-induced changes to these features in patients with head and neck squamous cell carcinoma (HNSCC) undergoing definitive chemoradiation. Patients with American Joint Committee on Cancer Stage III-IV (7th edition) HNSCC were prospectively enrolled on an IRB-approved study to undergo two pre-treatment baseline DW-MRI examinations, performed 1 week apart, and a third early intra-treatment DW-MRI examination during the second week of chemoradiation. Forty texture and six histogram features were derived from ADC maps. Repeatability of the features from the baseline ADC maps was assessed with the intra-class correlation coefficient (ICC). A Wilcoxon signed-rank test compared average baseline and early treatment feature changes. Data from nine patients were used for this study. Comparison of the two baseline ADC maps yielded 11 features with an ICC ≥ 0.80, indicating that these features had excellent repeatability: Run Gray-Level Non-Uniformity, Coarseness, Long Zone High Gray-Level, Variance (Histogram Feature), Cluster Shade, Long Zone, Variance (Texture Feature), Run Length Non-Uniformity, Correlation, Cluster Tendency, and ADC Median. The Wilcoxon signed-rank test resulted in four features with significantly different early treatment-induced changes compared to the baseline values: Run Gray-Level Non-Uniformity (p = 0.005), Run Length Non-Uniformity (p = 0.005), Coarseness (p = 0.006), and Variance (Histogram) (p = 0.006). The feasibility of histogram and texture analysis as a potential biomarker is dependent on the baseline variability of each metric, which disqualifies many features.
Authors
Rodrigues, A; Loman, K; Nawrocki, J; Hoang, JK; Chang, Z; Mowery, YM; Oyekunle, T; Niedzwiecki, D; Brizel, DM; Craciunescu, O
MLA Citation
Rodrigues, Anna, et al. “Establishing ADC-Based Histogram and Texture Features for Early Treatment-Induced Changes in Head and Neck Squamous Cell Carcinoma.Front Oncol, vol. 11, 2021, p. 708398. Pubmed, doi:10.3389/fonc.2021.708398.
URI
https://scholars.duke.edu/individual/pub1497057
PMID
34540674
Source
pubmed
Published In
Frontiers in Oncology
Volume
11
Published Date
Start Page
708398
DOI
10.3389/fonc.2021.708398