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Photon-Counting Detector CT of the Brain Reduces Variability of Hounsfield Units and Has a Mean Offset Compared with Energy-Integrating Detector CT

霍恩斯菲尔德秤 医学 探测器 核医学 光子 偏移量(计算机科学) 光子计数 能量(信号处理) 计算机断层摄影术 光学 放射科 物理 计算机科学 量子力学 程序设计语言
作者
Thomas Stein,Friederike Lang,Stephan Rau,Marco Reisert,Maximilian Frederik Russe,Till Schürmann,Anna Maria Fink,Elias Kellner,Jakob Weiss,Fabian Bamberg,Horst Urbach,Alexander Rau
出处
期刊:American Journal of Neuroradiology [American Society of Neuroradiology]
卷期号:46 (12): 2624-2630 被引量:4
标识
DOI:10.3174/ajnr.a8910
摘要

ABSTRACT

BACKGROUND AND PURPOSE:

Distinguishing gray matter (GM) from white matter (WM) is essential for CT of the brain. The recently established photon-counting detector CT (PCD-CT) technology employs a novel detection technique that might allow more precise measurement of tissue attenuation for an improved delineation of attenuation values (Hounsfield units – HU) and improved image quality in comparison with energy-integrating detector CT (EID-CT). To investigate this, we compared HU, GM vs. WM contrast, and image noise using automated deep learning-based brain segmentations.

MATERIALS AND METHODS:

We retrospectively included patients who received either PCD-CT or EID-CT and did not display a cerebral pathology. A deep learning-based segmentation of the GM and WM was used to extract HU. From this, the gray-to-white ratio and contrast-to-noise ratio were calculated.

RESULTS:

We included 329 patients with EID-CT (mean age 59.8 ± 20.2 years) and 180 with PCD-CT (mean age 64.7 ± 16.5 years). GM and WM showed significantly lower HU in PCD-CT (GM: 40.4 ± 2.2 HU; WM: 33.4 ± 1.5 HU) compared to EID-CT (GM: 45.1 ± 1.6 HU; WM: 37.4 ± 1.6 HU, p < .001). Standard deviations of HU were also lower in PCD-CT (GM and WM both p < .001) and contrast-tonoise ratio was significantly higher in PCD-CT compared to EID-CT (p < .001). Gray-to-white matter ratios were not significantly different across both modalities (p > .99). In an age-matched subset (n = 157 patients from both cohorts), all findings were replicated.

CONCLUSIONS:

This comprehensive comparison of HU in cerebral gray and white matter revealed substantially reduced image noise and an average offset with lower HU in PCD-CT while the ratio between GM and WM remained constant. The potential need to adapt windowing presets based on this finding should be investigated in future studies. ABBREVIATIONS: CNR = Contrast-to-Noise Ratio; CTDIvol = Volume Computed Tomography Dose Index; EID = Energy-Integrating Detector; GWR = Gray-to-White Matter Ratio; HU = Hounsfield Units; PCD = Photon-Counting Detector; ROI = Region of Interest; VMI = Virtual Monoenergetic Images;
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