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Lucas McCullum

0000-0001-9788-7987

PhD Student (Computational imaging; Biomedical imaging)

Houston, TX

Before his current role as a PhD-student at the MD Anderson UT Health Graduate School of Biomedical Sciences in Medical Physics, Lucas McCullum was a full-time medical physics researcher at Massachusetts General Hospital (MGH) / Harvard Medical School (HMS) where he contributed to the development of novel computational tools used to enhance outcome prediction in the field of radiation oncology. Prior to that, he was a software engineer in the Laboratory for Computational Physiology at MIT where he contributed to the development of essential data-sharing platforms used in the fields of computational medicine, healthcare, and machine learning. Lucas earned his B.S. in Mechanical Engineering and B.A. in Applied Mathematics from the University of Maryland, Baltimore County. His current work at MD Anderson Cancer Center focuses on the fusion of quantitative imaging and outcome prediction utilizing Magnetic Resonance Imaging (MRI) for image-guided radiation therapy.

Publications

  • https://scholar.google.com/citations?hl=en&user=4916fzwAAAAJ
  • HEDOS—a computational tool to assess radiation dose to circulating blood cells during external beam radiotherapy based on whole-body blood flow simulations
  • Waveform Database Software Package (WFDB) for Python
  • Predicting Severity of Radiation Induced Lymphopenia in Individual Proton Therapy Patients for Varying Dose Rate and Fractionation Using Dynamic 4-Dimensional Blood Flow Simulations
  • Intra-brain vascular models within the ICRP mesh-type adult reference phantoms for applications to internal dosimetry
  • PhysioTag: An Open-Source Platform for Collaborative Annotation of Physiological Waveforms
  • Invited presentation for MIT Tarragona Dataton 2022
  • ASTRO 2023: Oral Presentation
  • The Use of Quantitative Metrics and Machine Learning to Predict Radiologist Interpretations of MRI Image Quality and Artifacts
  • Interdisciplinary collaboration in critical care alarm research: a bibliometric analysis
  • Advancing Equitable and Personalized Cancer Care: Novel Applications and Priorities of Artificial Intelligence for Fairness and Inclusivity in the Patient Care Workflow
  • Fuller Lab Presentation --- MRI Pulse Sequences
  • WIMP 2024 Poster
  • Data: Personalized Rescheduling of AdaptiveOrgan-at-Risk-Sparing Radiation Therapy for Headand Neck Cancer under Re-planning ResourceConstraints: A Novel Application of MarkovDecision Processes
  • Data: Personalized Rescheduling of AdaptiveOrgan-at-Risk-Sparing Radiation Therapy for Headand Neck Cancer under Re-planning ResourceConstraints: A Novel Application of MarkovDecision Processes
  • Personalized Rescheduling of Adaptive Organ-at-Risk-Sparing Radiation Therapy for Head and Neck Cancer under Re-planning Resource Constraints: A Novel Application of Markov Decision Processes
  • Markov models for clinical decision‐making in radiation oncology: A systematic review
  • 2024 Summer Student Presentation --- History of MRI in Head and Neck Cancer
  • ICCR 2024 Presentation... OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment
  • ICCR 2024 Presentation... OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment
  • Technical Feasibility of Integrating SyntheticMR into the Head and Neck Adaptive Radiation Therapy Workflow
  • Dataset: "Technical Development and In Silico Implementation of SyntheticMR in Head and Neck Adaptive Radiation Therapy: A Prospective R-IDEAL Stage 0/1 Technology Development Report"
  • Technical Development and In Silico Implementation of SyntheticMR in Head and Neck Adaptive Radiation Therapy: A Prospective R-IDEAL Stage 0/1 Technology Development Report
  • Fuller Lab Meeting - "Technical Feasibility of Integrating Simultaneous Quantitative MRI into the Head and Neck Adaptive Radiation Therapy Workflow"
  • Fuller Lab Meeting - "Technical Feasibility of Integrating Simultaneous Quantitative MRI into the Head and Neck Adaptive Radiation Therapy Workflow"
  • Interdisciplinary collaboration in critical care alarm research: A bibliometric analysis
  • VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors
  • VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors
  • Fuller Lab Meeting: "Technical Feasibility of Integrating Simultaneous Quantitative MRI into the Head and Neck Adaptive Radiation Therapy Workflow"
  • Use of Piezoelectric Material for Advanced and Cost-Effective Tumor Screening
  • Use Of Piezoelectric Material For Advanced And Cost-Effective Tumor Screening
  • Proceedings of the XX-th international conference on the use of computers in radiation therapy (ICCR)
  • OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment
  • Cost-Effectiveness of Personalized Policies for Implementing Organ-at-Risk Sparing Adaptive Radiation Therapy in Head and Neck Cancer: A Markov Decision Process Approach
  • Variable-Interval Temporal Feathering to Optimize Organ-at-Risk Repair for Head and Neck Adaptive Radiotherapy
  • 2024 MR-Linac Consortium Presentation
  • 2024 MR-Linac Consortium Presentation
  • A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR
  • Dataset: "A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR"
  • Dataset: "A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR"
  • Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints
  • Fuller Lab Seminar --- "Untapped Potential of the Clinical MRI Systems in Head and Neck Cancers"
  • Fuller Lab Seminar --- "Untapped Potential of the Clinical MRI Systems in Head and Neck Cancers"
  • Technical Optimization of SyntheticMR for the Head and Neck on a 3T MR-Simulator and 1.5T MR-Linac: A Prospective R-IDEAL Stage 2a Technology Innovation Report
  • Dataset: "Technical Optimization of SyntheticMR for the Head and Neck on a 3T MR-Simulator and 1.5T MR-Linac: A Prospective R-IDEAL Stage 2a Technology Innovation Report"

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