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Overview
The continuing evolution of 3D printing technologies has provided the ability to manufacture reproducible and sophisticated 3D printed biomedical phantom models that accurately recreate areas of human anatomy and mimic human tissue. These models are used by clinicians to enhance the surgical planning process such as allowing for more accurate dosimetry measurements that minimizes the impact of often invasive surgical procedures on the patient’s longer-term rehabilitation.
A number of 3D printed phantom solutions in conjunction with the UK’s National Health Service have been recently developed commercially.
In a recent project at 3D LifePrints, we developed and manufactured a patient-specific 3D printed liver for a patient with liver cancer who was about to undergo radiation treatment. There are multiple approaches available for treating patients with liver tumors, including ablation, embolization, targeted therapy, immunotherapy, chemotherapy, and radiation therapy. Radiation therapy is one of the most effective methods but comes with its own risks and complexities. Accurate dosage measurements for radiation therapy is critical in providing effective treatment.
The normal procedure for pre-assessment and planning prior to the interventional procedure relies on the clinicians looking for a variety of patient image data scans. The subsequent procedure uses X-rays to provide the targeted radiation dose for the area of interest. There are currently few options for planning other than CT/MRI scans shown on a 2D screen. The 3D printed phantoms manufactured allowed the surgeons to better understand the patient’s anatomy and by using the measured dosage and known cavity volume for the patient, the surrounding exposure on the liver could be estimated.
From 3D medical segmentation to 3D printing
In this particular case, patient-specific image data from an MRI scan was imported into medical modeling software to segment the anatomical region of interest, in this case, a realistic model of the liver. Following work on the image data, the software was used to generate a model of the liver with high accuracy for 3D printing using a Polyjet 3D Printer. The stacked image DICOM data was imported directly into the specialized medical segmentation software and aligned appropriately in the axial and planar directions. Using the integrated thresholding tools, a general 3D render could be produced and visualized. Further refinement could then be achieved with the ‘paint with threshold’ and automatic global mask optimization tools. The 3D mesh created from the segmentation process could then be exported into the 3D printer slicing software for pre-print-processing. The 3D model contained three chambers suitable for holding radioisotope samples, with the chambers varying in size (4mm, 11m, and 40mm diameters) to mimic different-sized tumors. The 3D-printed phantom was then scanned (Phillips PET/CT) in the correct anatomical orientation and used as part of a surgical plan. By using the measured dosage and known cavity volume for the patient, the surrounding exposure on the liver could be estimated.
Conclusion
There are over 6,000 new liver cancer cases every year in the UK and the 5-year relative survival rate for localized stage conditions is ~31%. Liver cells are very sensitive to radiation. Highly targeted and planned interventions are required to limit adverse long term side effects on the patients liver while maximizing the impact of the procedure. 3D medical modeling and 3D printing capabilities can be used to create patient-specific 3D models. The identification of the boundaries separating the liver and the tumor is particularly important, in this case, for identifying a more accurate and case-specific radiation dosage than with traditional 2D visualization of CT or MRI scans. A 3D model helps the clinician understand the irregularities of a tumor before a treatment pathway is decided, reducing the risk of radiation exposure to surrounding tissues, as well as reduced damage to kidneys. Having the 3D model also means that clinicians have a better sense of the shape and size of the tumor, giving them more confidence in treatment planning.
About the author:
Paul Fotheringham is the founder of 3D LifePrints (3DLP) and is an experienced Technologist, Entrepreneur, and 3D printing expert who focuses on the medical sector. He holds a joint Batchelor of Science degree in Computer & Management Science from the University of Edinburgh. After graduating, he worked in over 10 countries including the US, UK, HK, Japan, and South Korea as an Enterprise Architect for organizations such as the London Stock Exchange, British Petroleum, Accenture and Macquarie Group. In 2012 he took up a post as Chief Technology Officer for a global Micro-finance organization in Kenya where he subsequently started 3DLP initially as a Social Enterprise in order to provide sustainable, affordable and suitable 3D printed prosthetics for developing world amputees. He currently overseas 3DLP’s European operations from Barcelona that provide a variety of innovative medical 3D printing products and services to medical institutions.
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