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SU‐E‐QI‐06: Design and Initial Validation of a Precise Capillary Phantom to Test Perfusion Systems
Author(s) -
Wood R,
Iacobucci G,
Khobragade P,
Ying L,
Snyder K,
Wack D,
Rudin S,
Ionita C
Publication year - 2014
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4888986
Subject(s) - imaging phantom , perfusion , biomedical engineering , subtraction , contrast (vision) , perfusion scanning , nuclear medicine , peristaltic pump , software , computer science , computer vision , radiology , physics , mathematics , medicine , arithmetic , meteorology , programming language
Purpose: To design a precise perfusion phantom mimicking capillaries of the brain vasculature which could be used to test various perfusion protocols and algorithms which generate perfusion maps. Methods: A perfusion phantom was designed in Solidworks and built using additive manufacturing. The phantom was an overall cylindrical shape of diameter and height 20mm and containing capillaries of 200μm or 300μm which were parallel and in contact making up the inside volume where flow was allowed. We created a flow loop using a peristaltic pump and contrast agent was injected manually. Digital Subtraction Angiographic images and low contrast images with cone beam CT were acquired after the contrast was injected. These images were analyzed by our own code in LabVIEW software and Time‐Density Curve, MTT and TTP was calculated. Results: Perfused area was visible in the cone beam CT images; however, individual capillaries were not distinguishable. The Time‐Density Curve acquired was accurate, sensitive and repeatable. The parameters MTT, and TTP offered by the phantom were very sensitive to slight changes in the TDC shape. Conclusion: We have created a robust calibrating model for evaluation of existing perfusion data analysis systems. This approach is extremely sensitive to changes in the flow due to the high temporal resolution and could be used as a golden standard to assist developers in calibrating and testing of imaging perfusion systems and software algorithms. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation