Ultra-low-dose lung multidetector computed tomography in children - Approaching 0.2 millisievert

Artificial Intelligence Iterative Reconstruction for Dose Reduction in Pediatric Chest CT: A Clinical Assessment via Below 3 Years Patients With Congenital Heart Disease

PURPOSE

To assess the performance of a newly introduced deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in reducing the dose of pediatric chest CT by using the image data of below 3-year-old patients with congenital heart disease (CHD).

MATERIALS AND METHODS

The lung image available from routine-dose cardiac CT angiography (CTA) on below 3 years patients with CHD was employed as a reference for evaluating the paired low-dose chest CT. A total of 191 subjects were prospectively enrolled, where the dose for chest CT was reduced to ~0.1 mSv while the cardiac CTA protocol was kept unchanged. The low-dose chest CT images, obtained with the AIIR and the hybrid iterative reconstruction (HIR), were compared in image quality, ie, overall image quality and lung structure depiction, and in diagnostic performance, ie, severity assessment of pneumonia and airway stenosis.

RESULTS

Compared with the reference, lung image quality was not found significantly different on low-dose AIIR images (all P>0.05) but obviously inferior with the HIR (all P<0.05). Compared with the HIR, low-dose AIIR images also achieved a closer pneumonia severity index (AIIR 4.32±3.82 vs. Ref 4.37±3.84, P>0.05; HIR 5.12±4.06 vs. Ref 4.37±3.84, P<0.05) and airway stenosis grading (consistently graded: AIIR 88.5% vs. HIR 56.5% ) to the reference.

CONCLUSIONS

AIIR has the potential for large dose reduction in chest CT of patients below 3 years of age while preserving image quality and achieving diagnostic results nearly equivalent to routine dose scans.

Long-term trends in total administered radiation dose from brain [18F]FDG-PET in children with drug-resistant epilepsy

PURPOSE

To assess the trends in administered 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) doses, computed tomography (CT) radiation doses, and image quality over the last 15 years in children with drug-resistant epilepsy (DRE) undergoing hybrid positron emission tomography (PET) brain scans.

METHODS

We retrospectively analyzed data from children with DRE who had [18F]FDG-PET/CT or magnetic resonance scans for presurgical evaluation between 2005 and 2021. We evaluated changes in injected [18F]FDG doses, administered activity per body weight, CT dose index volume (CTDIvol), and dose length product (DLP). PET image quality was assessed visually by four trained raters. Conversely, CT image quality was measured using region-of-interest analysis, normalized by signal-to-noise (SNR) and contrast-to-noise ratio (CNR).

RESULTS

We included 55 children (30 male, mean age: 9 ± 6 years) who underwent 61 [18F]FDG-PET scans (71% as PET/CT). Annually, the injected [18F]FDG dose decreased by ~ 1% (95% CI: 0.92%-0.98%, p < 0.001), with no significant changes in administered activity per body weight (p = 0.51). CTDIvol and DLP decreased annually by 16% (95% CI: 9%-23%) and 15% (95% CI: 8%-21%, both p < 0.001), respectively. PET image quality improved by 9% year-over-year (95% CI: 6%-13%, p < 0.001), while CT-associated SNR and CNR decreased annually by 7% (95% CI: 3%-11%, p = 0.001) and 6% (95% CI: 2%-10%, p = 0.008), respectively.

CONCLUSION

Our findings indicate stability in [18F]FDG administered activity per body weight alongside improvements in PET image quality. Conversely, CT-associated radiation doses reduced. These results reaffirm [18F]FDG-PET as an increasingly safer and higher-resolution auxiliary imaging modality for children with DRE. These improvements, driven by technological advancements, may enhance the diagnostic precision and patient outcomes in pediatric epilepsy surgery.

Low-dose lung CT: Optimizing diagnostic radiation dose - A phantom study

Background/purpose

To investigate a quantitative method for assessing image quality of low dose lung computed tomography (CT) and find the lowest exposure dose providing diagnostic images.

Methods

Axial volumetric lung CT acquisitions (256 slice scanner) were performed on three different sized anthropomorphic phantoms at different dose levels. The maximum steepness of sigmoid curves fitted to line density profiles was measured at lung-to-pleura interfaces. For each phantom, image sharpness was calculated as the median of 468 measurements from 39 different locations. Diagnostic image quality for the adult and paediatric phantom was rated by three radiologists using 4-point Likert scales. The image sharpness cut-off for obtaining adequate image quality was determined from qualitative ratings.

Results

Adequate diagnostic image quality was reached at a median steepness of 713 HU/mm in the adult phantom with a corresponding CTDIvol of 0.14 mGy and an effective dose of 0.13 mSv at a dose level of 100 kVp and 10 mA. In the paediatric phantom diagnostic image quality was reached at a median steepness of 1139 HU/mm with a corresponding CTDIvol of 0.13 mGy and an effective dose of 0.08 mSv at a dose level of 100 kVp and 10 mA.

Conclusions

Determination of image sharpness on line density profiles can be used as quantitative measure for image quality of lung CT. Sufficient-quality lung CT can be achieved at effective radiation doses of 0.13 mSv (adult phantom) and 0.08 mSv (paediatric phantom). These findings suggest that substantial dose reduction is feasible without compromising diagnostic accuracy.

Pathology-based radiation dose in computed tomography: investigation of the effect of lung lesions on water-equivalent diameter, CTDIVol and SSDE in COVID-19 patients

Lung lesions can increase the CT number and affect the water-equivalent diameter (Dw), Dw-based conversion factor (CFw), and Dw-based size-specific dose estimate (SSDEw). We evaluated the effect of COVID-19 lesions and total severity score (TSS) on radiation dose considering the effect of automatic tube current modulation (ATCM) and fixed tube current (FTC). A total of 186 chest CT scans were categorised into five TSS groups, including healthy, minimal, mild, moderate and severe. The effective diameter (Deff), Dw, CFw, Deff-based conversion factor (CFeff), volume computed tomography dose index (CTDIVol), pathological dose impact factor (PDIF) 1 and SSDEw were calculated. TSS was correlated with Dw (r = 0.29, p-value = 0.001), CTDIVol (ATCM) (r = 0.23, p = 0.001) and PDIF (r = - 0.51, p-value = 0.001). $\overline{{\mathrm{SSDE}}_{\mathrm{w}}}$ (FTC) was significantly different among all groups. $\overline{{\mathrm{SSDE}}_{\mathrm{w}}}$ (ATCM) was greater for moderate (13%) and mild (14%) groups. Increasing TSS increase the Dw and causes a decrease in CFw and $\overline{{\mathrm{SSDE}}_{\mathrm{w}}}$ (FTC), and can increase $\overline{{\mathrm{SSDE}}_{\mathrm{w}}}$ (ATCM) in some Dw ranges.

Paediatric CT made easy

Paediatric computed tomography (CT) imaging has always been associated with challenges. Although the technical background of CT imaging is complex, it is worth considering the baseline aspects of radiation exposure to prevent unwanted excess radiation in paediatric patients. In this review, we discuss the most relevant factors influencing radiation exposure, and provide a simplified and practical approach to optimise paediatric CT.