3D printed model of liver tumors based on CT and elastography data used for didactic purposes

Congress:

ECR 2019

Poster Number:

C-1086

Type:

Educational Exhibit

Keywords:

Abdomen, Liver, Oncology, CT, MR, Elastography, Computer Applications-3D, Computer Applications-Virtual imaging, CAD, Cancer, Neoplasia, Education and training

Authors:

L. M. Florescu, M. S. Popescu, C. T. Streba, D. N. Pirici, M. Vladaia, D. I. Gheonea, I. A. Gheonea; Craiova/RO

DOI:

10.26044/ecr2019/C-1086

DOI-Link:

https://dx.doi.org/10.26044/ecr2019/C-1086

Fig. 1: InVesalius application – selecting the ROI in three distinct planes in order...

Fig. 2: A) Tumor located inside the liver parenchyma; B) Central necrotic area within...

Fig. 3: The internal structure of the printed tumor represented by the lattice hex grid...

Fig. 4: 3D printed tumor – multiple viewing angles.

Fig. 5: 3D printed liver tumors.

Learning objectives

Our aim was to acquire, process and combine tumor data from abdominal CT and MRI scans combined with liver elastography into a computerized model and devise a method to print it using a conventional, commercially available, 3D printer and materials while being able to realistically simulate varying tumor stiffness.

Background

Hepatocellular carcinoma (HCC) is the most frequently encountered primary malignancy of the liver [1, 2]. HCC represents a major health concern due to its slow progression and increased mortality rate. Modern medical imaging methods like contrast-aided Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) play a central role in diagnosing and staging HCC [3, 4]. One of the basic skills acquired during medical training is palpation, but its importance constantly decreased over time, with the advent of modern imaging techniques. Palpation of deep abdominal tumors...

Findings and procedure details

Ethical clearance was obtained from the local board and, based on previously given informed consent, anonymized imaging data was obtained from 10 patients diagnosed with HCC. Initially, CT and MRI DICOM sequences were segmented using a semi-automated protocol developed with the free software InVesalius v3.1.1 (Renato Archer Information Technology Center, Brazil) running on a high performance Microsoft Windows mobile workstation. This software allowed us to select a region of interest (ROI) in three distinct planes (axial, sagittal and coronal) under the supervision of a radiologist,...

Conclusion

The method presented here represents a first attempt to easily replicate a 1:1 scale model of a real liver tumor, as reconstructed from abdominal CT and MRI scans combined with liver elastography data, with various stiffness levels. It can be used as part of medical training, simulating palpatory techniques and helping medical students better understand the morphology and appearance of parenchymatous tumors.

Personal information

Florescu Lucian Mihai Resident doctor in my 3rd year of practice County Clinical Emergency Hospital of Craiova e-mail: [email protected]

References

1. Bodzin AS, Busuttil RW. Hepatocellular carcinoma: advances in diagnosis, management, and long term outcome. World J Hepatol, 2015, 7(9):1157–1167. 2. Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin, 2014, 64(1):9–29. 3. Gheonea IA, Streba CT, Cristea CG, Stepan AE, Ciurea ME, Sas T, Bondari S. MRI and pathology aspects of hypervascular nodules in cirrhotic liver: from dysplasia to hepatocarcinoma. Rom J Morphol Embryol, 2015, 56(3):925–935. 4. Gheonea DI, Streba CT, Vere CC, Şerbănescu M, Pirici D, Comănescu...