Radiation Dose Reduction by Using CT with Iterative Model Reconstruction in Patients with Pulmonary Invasive Fungal
Chenggong Yan1, Jun Xu1, Chunyi Liang1
1From the Department of Medical Imaging Center (C.Y., C.L., Y.W., W.X., H.Z., Y.X.) and Department of Hematology (J.X., Q.W.), Nanfang Hospital, Southern Medical University, No. 1838 Guangzhou Avenue North, Guangzhou 510515, Guangdong, People's Republic of China.
Abstract:
Purpose To compare the diagnostic quality of reduced radiation dose computed tomography (CT) with iterative model reconstruction (IMR) versus that of conventional low-dose CT in patients with pulmonary invasive fungal infection. Materials and Methods This prospective observational study included 48 patients (mean age ± standard deviation, 39.9 years ± 11.3) known to have or suspected of having pulmonary invasive fungal infection between October 2016 and July 2017. Patients underwent CT with IMR (at 80 kV with 20 mA) immediately after low-dose CT (at 80 kV with automatic exposure control). Images were reconstructed by using a hybrid iterative reconstruction (HIR) algorithm and IMR. Two radiologists independently assessed subjective image quality, noise, and visibility of normal and abnormal findings by using a five-point scale. Objective measurements, including image noise, contrast-to-noise ratio (CNR), and corresponding figure of merit (FOM), were compared by using repeated-measures analysis of variance with Bonferroni post hoc tests for multiple comparisons. Results The mean effective dose was 0.3 mSv ± 0.3 for CT with IMR and 0.7 mSv ± 0.2 for low-dose CT (P < .01). When the image noise and CNR were normalized to the effective dose, CT images obtained with IMR had significantly higher FOM than did other image series (P < .0001). Subjectively, visibility of CT features of invasive fungal infection on CT scans reconstructed with IMR was rated as noninferior to that on low-dose CT scans reconstructed with HIR, except for the halo sign. Conclusion CT with IMR had approximately 60% dose reduction compared with conventional low-dose CT, with reduced noise and improved depiction of abnormal findings, in patients with pulmonary invasive fungal infection.
Insights
Iterative model reconstruction (IMR) computed tomography (CT) significantly reduces radiation dose by approximately 60% in patients with invasive fungal infections. This advanced CT technique offers improved image quality and better visualization of abnormalities compared to conventional low-dose CT.
Area of Science:
- Radiology
- Medical Imaging
- Pulmonology
Background:
- Pulmonary invasive fungal infections require accurate and timely diagnosis.
- Low-dose computed tomography (CT) is crucial for evaluating these infections.
- Optimizing radiation dose while maintaining diagnostic quality is a key challenge.
Purpose of the Study:
- To compare the diagnostic performance of reduced radiation dose CT with iterative model reconstruction (IMR) against conventional low-dose CT.
- To assess image quality, noise levels, and the visibility of findings in patients with suspected or confirmed pulmonary invasive fungal infections.
Main Methods:
- A prospective observational study involving 48 patients with suspected or confirmed pulmonary invasive fungal infection.
- Patients underwent both conventional low-dose CT and reduced radiation dose CT with IMR.
- Image quality was evaluated subjectively by two radiologists and objectively through noise and contrast-to-noise ratio (CNR) measurements.
Main Results:
- CT with IMR achieved a mean effective dose of 0.3 mSv, a 60% reduction compared to 0.7 mSv for conventional low-dose CT (P < .01).
- Images reconstructed with IMR demonstrated significantly higher figure of merit (FOM) when normalized for effective dose (P < .0001).
- Subjective image quality for IMR was non-inferior to conventional methods, with improved depiction of abnormal findings, except for the halo sign.
Conclusions:
- CT with IMR offers substantial radiation dose reduction in patients with pulmonary invasive fungal infections.
- IMR enhances image quality, reduces noise, and improves the visualization of abnormalities.
- This technique holds promise for optimizing diagnostic imaging in this patient population.
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