Saito M, Saito T. A simple algorithm to derive virtual non-contrast electron density from dual-energy computed tomography data for radiotherapy treatment planning.
Med Phys 2025;
52:3107-3116. [PMID:
39865311 DOI:
10.1002/mp.17648]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2024] [Revised: 12/28/2024] [Accepted: 01/09/2025] [Indexed: 01/28/2025] Open
Abstract
BACKGROUND
The use of iodinated contrast-enhancing agents in computed tomography (CT) improves the visualization of relevant structures for radiotherapy treatment planning (RTP). However, it can lead to dose calculation errors by incorrectly converting a CT number to electron density.
PURPOSE
This study aimed to propose an algorithm for deriving virtual non-contrast (VNC) electron density from dual-energy CT (DECT) data. This algorithm was developed by extending the formula previously developed by Saito, which enables the calculation of the electron density of human tissue through weighted subtraction of CT numbers acquired from DECT scans.
METHODS
To investigate the feasibility of the proposed VNC algorithm, we performed analytical DECT image simulations at 90 and 150 kV/Sn on virtual phantoms consisting of various tissue/iodine surrogates with known mass densities and elemental compositions. Two different shapes of phantoms made of water-mimicking surrogates were generated as inputs: a circular phantom (33 cm diameter) for calibration and an elliptical phantom (33 cm width and 28 cm height) for validation. The circular phantom was equipped with inserts of human-tissue-mimicking substitutes, pure water, and iodine-enhanced soft-tissue substitutes (2, 5, 10, and 15 mg/mL iodine). The elliptical phantom contained inserts of reference human tissues, iodine-enhanced soft-tissue substitutes (2, 2.5, 5, 7.5, 10, 15, and 20 mg/mL iodine), and a 10-mm-diameter core of 4 mg/mL iodine surrounded by a blood-mimicking base material. The performance of the proposed algorithm was evaluated by comparing the accuracy of VNC electron densities with those of non-contrast (NC) base materials (water- or blood-mimicking surrogates).
RESULTS
The derived algorithm enabled the calculation of VNC electron density in a manner similar to that of unenhanced human tissues by adapting a VNC-specific weighting factor, thereby eliminating the intermediate step of converting CT numbers to electron density. The simulated results showed that the VNC algorithm could almost completely remove the contrast in the electron density image between iodine-enhanced and base materials. The relative deviations of simulated VNC electron density values from the corresponding pre-contrast value were within ± 0.4% for all tested materials, with a root-mean-square error (RMSE) of 0.2%.
CONCLUSIONS
Within the limits of the analytical DECT image simulation used in this study, the simple VNC algorithm could effectively provide accurate VNC electron densities for iodine-enhanced materials. This may allow the contrast agent to be used for CT scans during RTP without compromising dose calculation accuracy.
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