About

Matthew Trovillion Bramlet is a Clinical Assistant Professor in the Department of Bioengineering at the University of Illinois Urbana-Champaign. His contact email is mbramlet@illinois.edu. The bio indicates his involvement in bioengineering education and research, with a focus on the facets of bioengineering related to detecting and treating health issues. His work is associated with the Grainger College of Engineering, and he is involved in the department's activities, including research and teaching. Specific details about his research focus, background, or key contributions are not provided in the page text.

Research topics

• Computer Science
• Medicine
• Mechanical engineering
• Internal medicine
• Biomedical engineering
• Medical physics
• Materials science
• General surgery
• Composite material
• Engineering
• Radiology
• Surgery

Selected publications

• Assessing the impact of virtual reality on surgeons’ mental models of complex congenital heart cases

  International Journal of Computer Assisted Radiology and Surgery · 2025-11-05

  articleOpen access

  PURPOSE: Virtual reality (VR) has attracted attention in healthcare for many promising applications including pre-surgical planning. Currently, there exists a critical gap in comprehension of the impact of VR on physicians' thinking. Self-reported data from surveys and metrics based on confidence and task completion may not yield sufficiently detailed understanding of the complex decision making and cognitive load experienced by surgeons during VR-based pre-surgical planning. METHODS: Our research aims to address the gap in understanding the impact of VR on physicians' mental models through a novel methodology of self-directed think-aloud protocols, offering deeper perspectives into physicians' thought processes within the virtual 3D environment. We performed qualitative analysis of recorded verbalizations and actions in VR in addition to quantitative measures from the NASA task load index (NASA-TLX). Analysis was conducted to identify thematic sequences in VR which influenced clinical decision making when reviewing patient anatomy. RESULTS: We find a significant increase in reported physician confidence in understanding of the patient anatomy from before VR to after (p = 0.012) and identified several common patterns of 3D exploration of the anatomy in VR. Physicians also reported low cognitive stress on the NASA-TLX. CONCLUSION: Our findings indicate VR has value beyond simulating surgery, helping physicians to confirm findings from conventional medical imaging, visualize approaches with detail, and help make complex decisions while mentally preparing for surgery. These findings provide evidence that VR and related 3D visualization are helpful for pre-surgical planning of complex cases.

  PublisherOA PDFDOI

• Pioneering Patient-Specific Approaches for Precision Surgery Using Imaging and Virtual Reality

  Journal of Visualized Experiments · 2024-04-05 · 3 citations

  articleSenior author

  Endovascular treatment of complex vascular anomalies shifts the risk of open surgical procedures to the benefit of minimally invasive endovascular procedural solutions. Complex open surgical procedures used to be the only option for the treatment of a myriad of conditions like pulmonary and aortic valve replacement as well as cerebral aneurysm repair. However, due to advancements in catheter-delivered devices and operator expertise, these procedures (along with many others) can now be performed through minimally invasive procedures delivered through a central or peripheral vein or artery. The decision to shift from an open procedure to an endovascular approach is based on multi-modal imaging, often including 3D Digital Imaging and Communications in Medicine (DICOM) imaging datasets. Utilizing these 3D images, our lab generates 3D models of the pathologic anatomy, thereby allowing the pre-procedural analysis necessary to pre-plan critical components of the catheterization lab procedure, namely, C-arm positioning, 3D measurement, and idealized road-map generation. This article describes how to take segmented 3D models of patient-specific pathology and predict generalized C-arm positions, how to measure critical two-dimensional (2D) measurements of 3D structures relevant to the 2D fluoroscopy projections, and how to generate 2D fluoroscopy roadmap analogs that can assist in proper C-arm positioning during catheterization lab procedures.

  PublisherDOI

• Automating Aortic Cross-sectional Measurement of 3D Aorta Models

  Journal of Cardiovascular Magnetic Resonance · 2024-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• Automating aortic cross-sectional measurement of 3D aorta models

  Journal of Medical Imaging · 2024-05-29

  articleOpen access1st authorCorresponding

  PurposeAortic dissection carries a mortality as high as 50%, but surgical palliation is also fraught with morbidity risks of stroke or paralysis. As such, a significant focus of medical decision making is on longitudinal aortic diameters. We hypothesize that three-dimensional (3D) modeling affords a more efficient methodology toward automated longitudinal aortic measurement. The first step is to automate the measurement of manually segmented 3D models of the aorta. We developed and validated an algorithm to analyze a 3D segmented aorta and output the maximum dimension of minimum cross-sectional areas in a stepwise progression from the diaphragm to the aortic root. Accordingly, the goal is to assess the diagnostic validity of the 3D modeling measurement as a substitute for existing 2D measurements.ApproachFrom January 2021 to June 2022, 66 3D non-contrast steady-state free precession magnetic resonance images of aortic pathology with clinical aortic measurements were identified; 3D aorta models were manually segmented. A novel mathematical algorithm was applied to each model to generate maximal aortic diameters from the diaphragm to the root, which were then correlated to clinical measurements.ResultsWith a 76% success rate, we analyzed the resulting 50 3D aortic models utilizing the automated measurement tool. There was an excellent correlation between the automated measurement and the clinical measurement. The intra-class correlation coefficient and p-value for each of the nine measured locations of the aorta were as follows: sinus of valsalva, 0.99, <0.001; sino-tubular junction, 0.89, <0.001; ascending aorta, 0.97, <0.001; brachiocephalic artery, 0.96, <0.001; transverse segment 1, 0.89, <0.001; transverse segment 2, 0.93, <0.001; isthmus region, 0.92, <0.001; descending aorta, 0.96, <0.001; and aorta at diaphragm, 0.3, <0.001.ConclusionsAutomating diagnostic measurements that appease clinical confidence is a critical first step in a fully automated process. This tool demonstrates excellent correlation between measurements derived from manually segmented 3D models and the clinical measurements, laying the foundation for transitioning analytic methodologies from 2D to 3D.

  PublisherOA PDFDOI

• VISTA: Visualization of Image Segmentation by Transformation and Analysis

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2024-11-26

  article

  Motivation: Complex medical procedures often require clinicians to construct a (3D) three-dimensional mental model of a patient's anatomy from 2D medical imaging data. Goal(s): Our goal was to develop a set of tools which convert 2D imaging data into 3D objects to view in virtual reality (VR). Approach: Two pipelines were created, one for brain imaging data and another for label mask images, which automatically segment the images, convert them to objects, and merge them into a VR viewable model. Results: Our software has been successfully used to transform a variety of medical imaging data into 3D files which are viewable on VR platforms. Impact: Some of the challenges with mentally visualizing two-dimensional medical imaging data should be alleviated by using our software to automatically make the data viewable in a three-dimensional format.

  PublisherDOI

• Virtual reality applications in pediatric surgery

  Seminars in Pediatric Surgery · 2024-01-12 · 13 citations

  articleOpen accessSenior author

  Virtual reality modeling (VRM) is a 3-dimensional (3D) simulation. It is a powerful tool and has multiple uses and applications in pediatric surgery. Patient-specific 2-dimensional imaging can be used to generate a virtual reality model, which can improve anatomical perception and understanding, and can aid in preoperative planning for complex operations. VRM can also be used for realistic training and simulation. It has also proven effective in distraction for pediatric patients experiencing pain and/or anxiety. We detail the technical requirements and process required for VRM generation, the applications, and future directions.

  PublisherDOI

• JoVE Video Dataset

  2024-04-06

  articleOpen accessSenior author

  Endovascular treatment of complex vascular anomalies shifts the risk of open surgical procedures to the benefit of minimally invasive endovascular procedural solutions. Complex open surgical procedures used to be the only option for the treatment of a myriad of conditions like pulmonary and aortic valve replacement as well as cerebral aneurysm repair. However, due to advancements in catheter-delivered devices and operator expertise, these procedures (along with many others) can now be performed through minimally invasive procedures delivered through a central or peripheral vein or artery. The decision to shift from an open procedure to an endovascular approach is based on multi-modal imaging, often including 3D Digital Imaging and Communications in Medicine (DICOM) imaging datasets. Utilizing these 3D images, our lab generates 3D models of the pathologic anatomy, thereby allowing the pre-procedural analysis necessary to pre-plan critical components of the catheterization lab procedure, namely, C-arm positioning, 3D measurement, and idealized road-map generation. This article describes how to take segmented 3D models of patient-specific pathology and predict generalized C-arm positions, how to measure critical two-dimensional (2D) measurements of 3D structures relevant to the 2D fluoroscopy projections, and how to generate 2D fluoroscopy roadmap analogs that can assist in proper C-arm positioning during catheterization lab procedures.

  PublisherOA PDFDOI

• Utilization of 4D Flow Imaging to Create a 5 Foot Tall Heart for a Museum Exhibit

  Journal of Cardiovascular Magnetic Resonance · 2024-01-01

  articleOpen accessSenior author
  PublisherDOI

• Virtual Reality for Preoperative Surgical Planning in Complex Pediatric Oncology

  Journal of Laparoendoscopic & Advanced Surgical Techniques · 2024-07-15 · 4 citations

  article1st authorCorresponding

  Background: Virtual reality modeling (VRM) is a 3-dimensional simulation created from patient-specific 2-dimensional (2D) imaging. VRM creates a more accurate representation of the patient anatomy and can improve anatomical perception. We surveyed surgeons on their operative plan in complex pediatric oncology cases based on review of 2D imaging and subsequently after review of VRM. We hypothesized that the confidence level would increase with the use of virtual reality and that VRM may change the operative plan. Methods: Patients were selected and enrolled based on age (&lt;18) and oncological diagnosis. VRM was created based on the 2D imaging. Surgeons identified surgical plans based on 2D imaging and again after VRM. A blinded surgeon not involved with the case also gave opinions on surgical plans after viewing both the 2D and the VRM imaging. These assessments were compared with the actual operation. Results: A total of 12 patients were enrolled. Diagnoses included six neuroblastomas, two Wilms tumors, one Ewing’s sarcoma, one pseudopapillary tumor of the pancreas, one rhabdomyosarcoma, and one mediastinal germ cell tumor. VRM increased the operating surgeon’s confidence 63% of the time. The operative plan changed 8.3% of the time after VRM. Conclusion: VRM is useful to help clarify operative plans for more complex pediatric cases.

  PublisherDOI

• Applications of mixed reality with medical imaging for training and clinical practice

  Journal of Medical Imaging · 2024-12-26 · 6 citations

  reviewOpen access

  Purpose: This review summarizes the current use of extended reality (XR) including virtual reality (VR), mixed reality, and augmented reality (AR) in the medical field, ranging from medical imaging to training to preoperative planning. It covers the integration of these technologies into clinical practice and within medical training while discussing the challenges and future opportunities in this sphere. This will hopefully encourage more physicians to collaborate on integrating medicine and technology. Approach: The review was written by experts in the field based on their knowledge and on recent publications exploring the topic of extended realities in medicine. Results: Based on our findings, XR including VR, mixed reality, and AR are increasingly utilized within surgery both for preoperative planning and intraoperative procedures. These technologies are also promising means for improved education at every level of physician training. However, there are still barriers to the widespread adoption of VR, mixed reality, and AR, including human factors, technological challenges, and regulatory issues. Conclusions: Based on the current use of VR, mixed reality, and AR, it is likely that the use of these technologies will continue to grow over the next decade. To support the development and integration of XR into medicine, it is important for academic groups to collaborate with industrial groups and regulatory agencies in these endeavors. These joint projects will help address the current limitations and mutually benefit both fields.

  PublisherOA PDFDOI

Frequent coauthors

• Kanwal M. Farooqi

  Morgan Stanley Children's Hospital

  90 shared

• Meghan F. Coakley

  National Institutes of Health

  90 shared

• Beth Ripley

  VA Puget Sound Health Care System

  90 shared

• Laura Olivieri

  81 shared

• Alexa L. Waltz

  OSF HealthCare

  19 shared

• Bradley P. Sutton

  15 shared

• Sister M. Pieta Keller

  OSF HealthCare

  13 shared

• Daniel J. Robertson

  Children's Hospital of Illinois

  12 shared

Education

• Ph.D., Bioengineering

  University of Illinois Urbana-Champaign

  2008

• M.S., Bioengineering

  University of Illinois Urbana-Champaign

  2004

• B.S., Bioengineering

  University of Illinois Urbana-Champaign

  2002