Effective text-based communication, through radiologist reports, of imaging findings in term Hypoxic Ischemic Injury (HII) to family members, non-radiologist colleagues and members of the legal profession can be extremely challenging. Utilization of 3D printed models, where the actual findings of the brain can be communicated via tactile perception and rotating/grasping the models is a potential solution which has not been tested in practice. We aimed to determine the sensitivity and specificity of different groups, comprising trained radiologists, non-radiologist physicians and non-physicians, in the detection of gross disease of the cerebral cortex from 3D printed brain models derived from MRI scans of children. Read More

Meeting name: SPR 2023 Annual Meeting & Postgraduate Course , 2023

Authors: Venkatakrishna Shyam Sunder, Chacko Anith, Schoeman Sean, Andronikou Savvas

Keywords: Magnetic Resonance Imaging, 3D Printing, Hypoxic Ischemic Injury

To assess the utility and adaptability of some widely used automated segmentation methods when applied to abnormal pediatric magnetic resonance imaging (MRI) brain scans. Segmentation is an essential component of the workflow when building 3D anatomical models of abnormal pediatric brains to demonstrate surface pathology. Read More

Meeting name: SPR 2023 Annual Meeting & Postgraduate Course , 2023

Authors: Schoeman Sean, Venkatakrishna Shyam Sunder, Chacko Anith, Andronikou Savvas

Keywords: Segmentation, 3D Printing, MRI Brain

Risk stratification of the most common pediatric primary liver malignancies, hepatoblastoma and hepatocellular carcinoma, is dependent on imaging criteria that ultimately inform work-up and clinical management. The Pediatric Liver Reporting and Data System (LI-RADS) Working Group recommends use of the PRETEXT (PRE-Treatment EXTent of tumor) staging system, which is utilized in the ongoing Pediatric International Tumor Trial (1). PRETEXT staging is first performed by dividing the liver into four sections. Based on how many contiguous sections are free of tumor, a group is assigned from I-IV. Second, annotations factors are assessed depending on the presence of vessel involvement, rupture, multifocality, extrahepatic spread, or metastatic disease, which portend higher risk (2). Understanding and applying the PRETEXT system should be a core competency for all current and aspiring pediatric radiologists. The PRETEXT system has some barriers to learning, namely in discerning the anatomical liver sections from the functional ‘Couinaud’ segments and accurately determining vessel involvement. We saw the opportunity to combine our diagnostic pediatric radiologic experience/expertise with the application of 3D printing technology. Through the segmentation of post-contrast T1 fat-saturated MRI images, we were able to build 3D models of different PRETEXT stage disease. The aim of this educational exhibit is to provide pediatric radiologists with an alternative learning tool to appreciate the PRETEXT system and its application. It will combine the proficiency of a 3D pediatric additive manufacturing lab and diagnostic pediatric radiologists with expertise in oncologic imaging and fellowship teaching. Models and their representative 3D renderings will demonstrate the differences between PRETEXT stages, with and without the presence of various annotation factors. 1. Schooler GR, Squires JH, Alazraki A, Chavhan GB, Chernyak V, Davis JT, et al. Pediatric Hepatoblastoma, Hepatocellular Carcinoma, and Other Hepatic Neoplasms: Consensus Imaging Recommendations from American College of Radiology Pediatric Liver Reporting and Data System (LI-RADS) Working Group. Radiology. 2020 Sep;296(3):493–7. 2. Towbin AJ, Meyers RL, Woodley H, Miyazaki O, Weldon CB, Morland B, et al. 2017 PRETEXT: radiologic staging system for primary hepatic malignancies of childhood revised for the Paediatric Hepatic International Tumour Trial (PHITT). Pediatr Radiol. 2018 Apr;48(4):536–54. Read More

Meeting name: SPR 2023 Annual Meeting & Postgraduate Course , 2023

Authors: Schoeman Sean, Venkatakrishna Shyam Sunder, Silvestro Elizabeth, Cajigas-loyola Stephanie, Acord Michael

Keywords: PRETEXT Staging, 3D Printing, MRI