Kai Wang (王凯)

Kai Wang (王凯)

RadOnc, UMMC

I am Medical Physics Resident at the University of Maryland Medical Center. I got my PhD from the Biomedical Engineering Program Medical Physics Track at UT Southwestern Medical Center (UTSW), advised by Dr. Jing Wang. I worked at Medical Artificial Intelligence and Automation (MAIA) Lab and Advanced Imaging and Informatics for Radiation Therapy (AIRT) Lab for my PhD dissertation, my projects mainly focus on radiomics-based cancer radiotherapy outcome prediction . Before coming to UTSW, I worked with Dr. Xuanqin Mou and Dr. Xi Chen at the Institute of Image Processing and Pattern Recognition (IIPPR) on Field Emission X-ray Source Array based Imaging Methods for my master’s thesis.

My research interest includes medical image analysis, cancer treatment outcome prediction, radiomics, and medical imaging.

🎓 Educations

  • 2023.07 - 2025.06 (Expected), Medical Physics Residency Program, University of Maryland Medical Center (UMMC), Baltimore, MD
  • 2018.08 - 2023.05, PhD, BME Medical Physics (CAMPEP Accredited), University of Texas Southwestern Medical Center (UTSW), Dallas, TX
  • 2015.09 - 2018.06, MS, Information and Communication Engineering, Xi’an Jiaotong University (XJTU), Shaanxi, China
  • 2011.09 - 2015.06, BS, Information Engineering, Xi’an Jiaotong University (XJTU), Shaanxi, China

📚 Experience

  • 🏥 Clinical Observation

  • Varian TrueBeam/VitalBeam, Patient-specific/Weekly/Monthly/Annual Machine QA, UTSW, 2019.09 and 2022.09.
  • Elekta Unity MR Linac, Monthly/Annual Machine QA, UTSW, 2022.10.
  • Varian Halcyon, Patient-specific QA, UTSW, 2022.10.
  • Conventional Simulation (General), IMRT Planning, and Electron Planning, UTSW, 2019.10.

  • Gamma Knife Stereotactic Radiosurgery, UTSW, 2019.11.

  • 📖 Research

  • 2019.08 - 2022.08, Head and Neck Cancer Radiotherapy Treatment Outcome Prediction, UTSW.
  • 2021.10 - 2022.06, Optimal PTV Margin for Postoperative Prostatic Fossa Daily ART, UTSW.
  • 2021.05 - Present, Pancreatic Cancer Treatment Outcome Prediction, UTSW.
    • Built a delta-radiomics-based survival model for predicting the treatment outcome of patients undergoing surgical resection of PDAC following neoadjuvant therapy.
    • Evaluated the predictive ability of features extracted from peritumoral area and the therapy induced feature change for PDAC patient treatment outcome prediction.
  • 2019.05 - 2021.06, Lateral Skull Base Tumor Growth Prediction, UTSW.
  • 2019.08 - 2019.12, High-Resolution Brain PET Imaging, UTSW.
    • Simulated the coincidence signal can be detected by a high-resolution low-sensitivity detecor and a low-resolution high-sensitivity detector using Monte Carlo method.
    • Constructed a conversion (inverse method) matrix for calculating the coincidence signal can be detected by a virtual high-resolution and high-sensitivity detecor for high-resolution brain PET imaging.
  • 2019.01 - 2019.07, Similar Patients Retrieval for Radiotherapy Treatment Planning, UTSW.
    • Proposed a relational autoencoder based descriptor which considers patient’s geometry and the relationship of plan dose distributions between different patients for retrieving similar patient for prostate cancer radiotherapy treatment planning.
  • 2015.09 - 2018.05, Imaging Method Based on Field Emission X-ray Source Array, IIPPR, XJTU .

📝 Publications

📓 Journal Paper

Medical Physics
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Towards reliable head and neck cancers locoregional recurrence prediction using delta-radiomics and learning with rejection option
Kai Wang, Michael Dohopolski, Qiongwen Zhang, David Sher, Jing Wang, Medical physics, 2022.

Project |

  • Delta-radiomcis features calculated based on Pre- and Post-Therapy PET/CT.
  • Multi-modality model for early-stage locoregional recurrence prediction.
  • We performed patient-specific prediction uncertainty estimation for learning with rejection option to improve the model reliability (higher performance on high-confidence group).
The Laryngoscope
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Joint Vestibular Schwannoma Enlargement Prediction and Segmentation Using a Deep Multi-task Model
Kai Wang, Nicholas George-Jones, Liyuan Chen, Jacob Hunter, Jing Wang, The Laryngoscope, 2022.

Project |

  • We presented a deep multi-task (DMT) model to predict vestibular schwannoma enlargement and tumor segmentation mask simultaneously using the initial diagnostic ceT1 MRI.
  • The proposed DMT model is of higher learning efficiency and prediction accuracy than single-task prediction model.
Medical Physics
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A multi‐objective radiomics model for the prediction of locoregional recurrence in head and neck squamous cell cancer
Kai Wang, Zhiguo Zhou, Rongfang Wang, Liyuan Chen, Qiongwen Zhang, David Sher, Jing Wang, Medical physics 47.10 (2020): 5392-5400.

  • We built a multi-classifier, multi-objective, and multi-modality (mCOM) model for HNSCC LRR prediction.
  • Our study shows fusing multiple classifiers and multiple modalities can improve the robustness of the predictive model. Additionally, the multi-objective model could help to build a predictive model that can be flexibly adapted to different clinical preferences.

📑 Conference Proceeding

HECKTOR 2022
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Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers
Kai Wang, Yunxiang Li, Michael Dohopolski, Tao Peng, Weiguo Lu, You Zhang, Jing Wang (The first two authors contributed to this work equally, Oral 🎤)

  • Ranked No.3 in the recurrece-free survival (RFS) prediction task of the head and neck tumor segmentation and outcome prediction challenge (HECKTOR 2022).
  • nnUNet for GTVp and GTVn segmentation on a multi-institution dataset.
  • Extract radiomics feature from the AI-based auto-segmentated ROI for radiomics-based HNC RFS prediction.
  • Ensemble multi-modality model for more robust prediction.

📰 Conference Abstract

📰 Patent

✒️ In Preparation

🏅 Honors and Awards

  • 2022.09 Third place for Recurrence-Free Survival Prediction Task in the Head and Neck Tumor Segmentation and Outcome Prediction Challenge (HECKTOR2022)
  • 2016.10 Excellent Graduate Student, XJTU
  • 2012-2015 Siyuan Scholarship, XJTU
  • 2015.06 Outstanding Undergraduate Student Cadres, XJTU
  • 2014.10 Special Award in “TI Cup” Circuit Design Competition, Shaanxi, China
  • 2013.10 First Prize in Undergraduate Mathematical Contest in Modeling, Shaanxi, China

💻 Activities

📜 Journal Reviewer

  • Medical Physics
  • Physics in Medicine and Biology
  • International Journal of Radiation Oncology* Biology* Physics
  • IEEE Journal of Biomedical and Health Informatics
  • IEEE Transactions on Medical Imaging
  • The British Journal of Radiology
  • Scientific Reports
  • Biomedical Physics & Engineering Express

📯 Student Activities

  • 2017.06, Student conference coordinator, 14th Fully 3D International Conference, Xi’an, Shaanxi, China.
  • 2013.08-2014.06, Vice Chair, Senior Student Group, Wenzhi College, XJTU.
  • 2012.08-2013.06, Director, Campus Life Program, Student’s Association, Wenzhi College, XJTU.