Reduced Patient Dose and Improved Image Quality in Computed Tomography Examinations with On-Line Anatomically Adapted Tube Current Modulation

1998 ◽  
Vol 80 (1) ◽  
pp. 287-289
Author(s):  
D. Hentschel ◽  
K. Klingenbeck-Regn ◽  
S. Popescu ◽  
C. Suess ◽  
H. Wolf ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Patient Dose ◽  
Tube Current Modulation ◽  
Current Modulation ◽  
Tube Current ◽  
On Line

scholarly journals Evaluation of tube current modulation programms for the optimization of scan protocols in computed tomography

2019 ◽  
Vol 12 (1) ◽  
pp. 104-114 ◽  
Author(s):  
L. A. Chipiga
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Patient Dose ◽  
Tube Current Modulation ◽  
Ct Image ◽  
Tube Voltage ◽  
Current Modulation ◽  
Tube Current ◽  
Patient Doses ◽  
Patient Dose Reduction

Computed tomography (CT) is commonly associated with relatively high patient doses. In order to keep the patient doses from the CT examinations on the acceptable level it is necessary to apply the principle of optimization. An essential part of optimization is the achievement of the compromise between the patient dose reduction and the maintenance of the image quality that provides accurate diagnostic information. The aim of the study was to determine the relations between the patient doses, CT image quality and the parameters of the tube current modulation program (Auto mA, CareDose and DoseRight) for the examination of the chest. The study was performed on the three most common modern tomographs in Russia: Ingenuity Core 128, Philips; Optima 64, General Electric; Definition AS, Siemens. The anthropomorphic phantom Lungman (Kyoto Kagaku CO., LTD) was used in the study. In order to assess the tube current modulation for the range of tube voltage (80–120 kV), the reference mA∙s (ref. mAs), Noise Index (NI) and Dose Right Index (DRI) were changed for the CareDose (Siemens), Auto mA (GE) and RightDose (Philips),  respectively. Estimation of the effective dose was performed using the method from Methodical guidance 2.6.1.2944-11 (MU 2.6.1.2944-11). In order to evaluate the image quality, the noise of a CT image in the mediastinum was selected as the most homogenous for chest region. It was estimated, that for the GE units with Auto mA, the noise of CT image had a liner relationship with NI; the patient dose decreased with the increase of NI. For the Siemens units with CareDose, the noise of CT image decreased with the ref.mAs for the range of tube voltage (80–120 kV); the patient dose was directly proportional to the ref.mAs and increased with the tube voltage. For the Philips units with DoseRight, the noise of CT image decreased with the DRI for the range of tube voltage (80–120 kV); the patient dose was directly proportional to the DRI and had no dependence on the tube voltage. The tube current modulations are proprietary for each manufacturer; it is necessary to consider  them for the protocol development. The obtained dependences could be useful for optimization of CT protocols. 

scholarly journals Image quality assessment of deep learning image reconstruction in computed tomography using tube current modulation: a phantom study

2021 ◽  
Author(s):  
kazuhiro takeuchi ◽  
Yasuhiro Ide ◽  
Yuichiro Mori ◽  
Yusuke Uehara ◽  
Hiroshi Sukeishi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Image Reconstruction ◽  
Image Quality ◽  
Quality Characteristics ◽  
Image Noise ◽  
Tube Current Modulation ◽  
Current Modulation ◽  
Tube Current ◽  
The Impact

Abstract The novel deep learning image reconstruction (DLIR) is known to change its image quality characteristics according to object contrast and image noise. In clinical practice, computed tomography (CT) image noise is usually controlled by tube current modulation (TCM) to accommodate changes in object size. This study aimed to evaluate the image quality characteristics of DLIR for different object sizes when in-plane noise is controlled by TCM. We used Mercury 4.0 phantoms with different object sizes. Phantom image acquisition was performed on a GE Revolution CT system to investigate the impact of the DLIR algorithm compared to standard reconstructions: filtered back projection (FBP) and hybrid iterative reconstruction (hybrid-IR). For image quality evaluation, the noise power spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were determined. The NPS of DLIR was very similar to that of FBP, and the information in the high-frequency region was maintained. In terms of TTF, DLIR showed higher resolution than hybrid-IR at low- to medium-contrast (Δ50, Δ90HU), but not necessarily higher than FBP. At the simulated contrast and lesion size, DLIR showed higher detectability than hybrid-IR, regardless of the phantom size. In this study, we evaluated a novel DLIR algorithm by reproducing clinical behaviors. The findings indicate that DLIR produces higher image quality than hybrid-IR regardless of the phantom size, although it depends on the reconstruction strength.

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