1. Determination of the optimal range for virtual monoenergetic images in dual‐energy CT based on physical quality parameters.
- Author
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Fernandez‐Velilla Cepria, Enric, González‐Ballester, Miguel Ángel, Quera Jordana, Jaume, Pera, Oscar, Sanz Latiesas, Xavier, Foro Arnalot, Palmira, Membrive Conejo, Ismael, Rodriguez de Dios, Nuria, Reig Castillejo, Anna, and Algara Lopez, Manuel
- Subjects
COMPUTED tomography ,IMAGING phantoms ,TRANSFER functions ,DUAL energy CT (Tomography) ,CONTRAST sensitivity (Vision) ,FIX-point estimation ,ABSOLUTE value - Abstract
Purpose: Virtual monoenergetic images (VMI) obtained from Dual‐Energy Computed Tomography (DECT) with iodinated contrast are used in radiotherapy of the Head and Neck to improve the delineation of target volumes and organs at‐risk (OAR). The energies used to vary from 40 to 70 keV, but noise at low keV and the use of Single Energy CT (SECT) at low kVp settings may shrink this interval. There is no guide about how to find out the optimal range where VMI has a significant improvement related to SECT images. Our study proposes a procedure to determine this optimal range, based on common image quality parameters, and establishes this range in a Siemens Somatom Confidence and a Head and Neck protocol. Methods: We compared the quality of the VMI series at 40–60 keV versus single X‐ray tube voltage computed tomography (SECT) at 80 and 120 kVp. Our reference was 120 kVp. DECT images were sequentially acquired using the Siemens Somatom Confidence RT Pro CT according to the head and neck protocol in our department. VMI series were constructed using the Syngo Via software Monoenergetic+ algorithm. Quality parameters were: image uniformity, high‐ and low‐contrast resolution, noise, and sensitivity to the iodinated contrast. We used the Catphan 604 phantom for quality control, except when assessing iodine sensitivity. To evaluate high contrast resolution, we calculated the modulation transfer function (MTF) using the point spread function estimation of a point bead and the slanted edge methods. For the low‐contrast resolution, we used a statistical method for assessing differences between contrast structures and local noise. To measure the absolute value of noise and compare its texture, we used the standard deviation and the noise power spectrum. We measured iodine sensitivity by dissolving the Optiray Ultraject iodinated contrast in water in concentrations of 0 to 4500 mg/l and then compared the contrast to noise ratio (CNR) and analyzed the linear correlation between concentration and HU. Results: The entire series met the minimum quality requirements. However, the one at 40 keV presented uniformity at the limits of acceptability. The high‐ and low‐contrast resolutions were similar between series. The noise of the VMI series decreased with increasing energy, while sensitivity to the contrast displayed the opposite behavior. All series showed linearity of HUs from very low iodine concentrations. Images at 60 keV presented lower iodine sensitivity than SECT at 80 kVp, while those at 55 keV were similar to them. Conclusions: Our method of image comparison based on standard quality parameters in phantom gave clear results about the optimal range and can be used as a guide to characterize any other DECT imaging protocols. The optimal range for using VMI images in iodinated contrasts in the Siemens system was 45–55 keV. Lower energies lacked noise and uniformity, while higher ones could be substituted by SECT images at low kilovoltage (80 kVp). [ABSTRACT FROM AUTHOR]
- Published
- 2021
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