ACR White Paper–Based Comprehensive Dose Reduction Initiative Is Associated With a Reversal of the Upward Trend in Radiation Dose for Chest CT

2015 ◽  
Vol 12 (12) ◽  
pp. 1251-1256 ◽  
Author(s):  
Udit Rawat ◽  
Stuart L. Cohen ◽  
Jeffrey M. Levsky ◽  
Linda B. Haramati
2014 ◽  
Vol 4 ◽  
pp. 38 ◽  
Author(s):  
Lukas Ebner ◽  
Felix Knobloch ◽  
Adrian Huber ◽  
Julia Landau ◽  
Daniel Ott ◽  
...  

Objective: The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated. Materials and Methods: 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. Results: Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P = 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P = 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP. Conclusion: The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.


Author(s):  
Eray Atlı ◽  
Sadık Ahmet Uyanık ◽  
Umut Öğüşlü ◽  
Halime Çevik Cenkeri ◽  
Birnur Yılmaz ◽  
...  

Objective: To investigate the feasibility of low dose chest CT acquisition protocol for the imaging of either the confirmed case of COVID-19 disease or the suspected case of this disease in adults. Method: In this retrospective case-control study, the study group consisted of 141 patients who were imaged with low dose chest CT acquisition protocol. The control group consisted of 92 patients who were imaged with the standard protocol. Anteroposterior and lateral diameters of chest, effective diameter and scan length, qualitative and quantitative noise levels, volumetric CT dose index (CTDIvol), dose length product (DLP), and size-specific dose estimations were compared between groups. Results: Radiation dose reduction by nearly 90% (CTDIvol and DLP values 1.06 mGy and 40.3 mGy.cm vs. 8.07 mGy and 330 mGy.cm, p < 0.001, respectively) was achieved with the use of low dose acquisition chest CT protocol. Despite higher image noise with low dose acquisition protocol, no significant effect on diagnostic confidence was encountered. Cardiac and diaphragm movement-related artifacts were similar in both groups (p = 0.275). Interobserver agreement was very good in terms of diagnostic confidence assessment. Conclusion: For the imaging of either the confirmed case of COVID-19 related pneumonia or the suspected case of this disease in adults, low dose chest CT acquisition protocol provides remarkable radiation dose reduction without adversely affecting image quality and diagnostic confidence.


2013 ◽  
Vol 37 (2) ◽  
pp. 334-341 ◽  
Author(s):  
Teresa Chapman ◽  
Jonathan O. Swanson ◽  
Grace S. Phillips ◽  
Marguerite T. Parisi ◽  
Adam M. Alessio

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