Guest Podcast: Transforming Healthcare, VR Surgical Planning
Inside this episode
Kai, the Library's AI content creator,
listened to this episode and mapped who's speaking, the chapters,
key claims, and cases. Every item links to the exact moment in the
recording.
AI-enriched
Inside this episode
Who's speaking
- Anton Bash — host
- Todd Ponsky — host
- Rami Shain — host
- Matthew Bramblett — guest_expert
Chapters
- 0:00Introduction and Clinical Scenario — Anton Bash introduces the podcast and presents a clinical scenario of a pediatric patient with heterotaxy syndrome requiring complex cardiac surgery, setting up the discussion of VR surgical planning.
- 3:07Stage 1: Order Entry and Content Acquisition — Discussion of patient selection criteria and imaging requirements, including coordination with radiology for appropriate CT or MRI protocols with thinner slices for 3D modeling.
- 4:35Stage 2: Segmentation and Quality Assurance — Explanation of the segmentation process where 2D imaging slices are converted to 3D models, including the availability of free segmentation services through Jump Simulation and the QA process with radiologists and surgeons.
- 6:08Stage 3: Content Optimization and VR Implementation — Description of content optimization for VR, including standardized cutting approaches, fluorescent tumor coloring, and the transition to nearly 100% VR usage since 2018. Surgeons report feeling like they had "been there before" after VR-prepared surgeries.
- 7:56Workflow Timing and Software Tools — Discussion of construction time (30 minutes to 1.5 hours for congenital heart cases), clinical lag time (typically one week), use of Induvo software for VR, and development of automated segmentation using machine learning for faster turnaround.
- 11:57Advantages, Limitations, and Future Directions — Analysis of VR advantages (exact anatomic replication, spatial orientation) and limitations (valve visualization, imaging-dependent accuracy). Discussion of 4D beating heart models and the potential for real-time dynamic modeling.
- 15:15Implementation Advice and Closing — Dr. Bramblett's recommendations for institutions adopting VR surgical planning, emphasizing investment in segmentation resources and training existing radiology technologists rather than purchasing 3D printers.
Key claims
- 2:38At Children's Hospital of Illinois, every complex congenital heart or surgical oncology patient is viewed in VR before they go into the operating room. — Matthew Bramblett
- 0:54Without corrective surgery, most children with heterotaxy syndrome and congenital heart problems will not survive beyond the first year of their life. — Anton Bash
- 3:41For 3D modeling, thinner slices on CT scan are required rather than the standard thicker slices. — Matthew Bramblett
- 3:51For soft tissue tumors, MRI is preferred over CT for generating 3D models. — Anton Bash
- 4:24Jump Simulation offers segmentation service at no cost to any institution worldwide. — Anton Bash
- 4:45VR models can be turned around in one day if the requesting institution has VR hardware. — Matthew Bramblett
- 4:50Shipping a 3D printed heart takes more cost and time compared to VR delivery, but will be done if believed to help the surgeon prepare for the case. — Matthew Bramblett
- 5:11The QA process is done hand in hand with the radiologist and surgeon or cardiologist for the purpose of creating an exact replica of that specific patient. — Matthew Bramblett
- 6:57Placing tumors in fluorescent color in VR is beneficial because the fluorescent tumor maintains its presence as other structures are made to disappear. — Matthew Bramblett
- 7:09Since 2018, the institution is nearly 100% VR for surgical planning. — Matthew Bramblett
- 7:47Four or five surgeons have reported after surgery that they felt like they had been there before when using VR surgical planning. — Matthew Bramblett
- 8:09The average construction time for VR images is between 30 minutes to 1.5 hours for congenital heart diseases. — Anton Bash
- 8:09There is usually about a week clinical lag time between imaging and surgery. — Anton Bash
- 8:24The software used for VR is Induvo, which originated in Dr. Bramblett's lab and was the lab's first commercial exit. — Matthew Bramblett
- 8:39Induvo allows surgeons to record in the VR space, creating derivative clinical vignettes for education. — Matthew Bramblett
- 9:32There is a study where parents and sometimes patients review the case in VR as surgeons walk them through what will happen in surgery. — Anton Bash
- 10:59Multiple CAD programs exist for segmentation, including 3D Slicer (open source freeware) and Mimics Biomaterials (expensive commercial software). — Matthew Bramblett
- 11:14A machine learning program has been built that can generate a heart model from a non-contrast 3D data set with a click of a button using a supercomputer. — Matthew Bramblett
- 11:26Dr. Bramblett's team presented automated segmentation for brain tumors to address the problem that stealth images are obtained only 1-2 hours before surgery. — Anton Bash
- 12:09The main advantage of VR surgical planning is creating a mental representation of the anatomy, with every surgeon reporting that the VR model is exactly what they found in the OR. — Matthew Bramblett
- 12:30One disadvantage of 3D modeling for cardiac cases is the inability to replicate valves because if you cannot see it on the image, you cannot replicate it. — Anton Bash
- 12:44The lab has developed a 4D heart by segmenting 18 phases of a beating heart, creating a beating heart model with two VSDs. — Matthew Bramblett
- 14:39The institution has not printed a heart for surgical planning since 2018, when they transitioned to VR. — Anton Bash
- 14:46In one recent case, the 3D printed heart showed the cardiac problem, but the critical issue was the orientation inside the chest, which was only apparent in VR. — Matthew Bramblett
- 14:24Dr. Bramblett advises institutions to use existing radiology technologists for segmentation but they require training in new software, and recommends prioritizing segmentation resources over purchasing 3D printers. — Matthew Bramblett
Cases discussed
- 0:51Pediatric patient with heterotaxy syndrome requiring assessment for two-ventricle repair
Open questions
- How will VR surgical planning impact patient outcomes in prospective studies compared to traditional planning methods?
- Can real-time dynamic modeling with physiologic responses be achieved to create true digital twins for surgical planning?
- What is the optimal balance between automated and manual segmentation for different anatomic structures and pathologies?
- How can valve structures be better visualized and modeled in cardiac VR planning given current imaging limitations?
Topic overview
This podcast episode discusses the use of virtual reality (VR) for surgical planning in pediatric congenital heart disease and surgical oncology at Children's Hospital of Illinois. The discussion covers the five-stage process from patient selection and imaging acquisition through segmentation, quality assurance, content optimization, and final VR delivery. Dr. Matthew Bramblett describes how every complex congenital heart or surgical oncology patient at their institution is viewed in VR before surgery, with surgeons reporting they "felt like I'd been there before" after operating. The team has transitioned entirely from 3D printing to VR since 2018, offers free segmentation services globally through Jump Simulation, and is developing automated segmentation using machine learning to reduce turnaround time.
Key takeaways
- VR surgical planning creates accurate mental maps: surgeons consistently report the VR model matches OR findings exactly. (7:47)
- VR has replaced 3D printing for cardiac planning since 2018, offering faster turnaround and revealing spatial orientation issues. (7:09)
- Jump Simulation provides free global segmentation services with 1-day VR turnaround if institutions have hardware. (4:24)
- Machine learning automation can generate heart models from non-contrast 3D datasets, addressing time constraints in surgical workflows. (11:14)
- Train existing radiology techs for segmentation rather than buying printers; prioritize human expertise over hardware. (14:24)
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Transcript
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