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Noise reduction and image quality improvement of low dose and ultra low dose brain perfusion CT by HYPR-LR processing.

Krissak R, Mistretta CA, Henzler T, Chatzikonstantinou A, Scharf J, Schoenberg SO, Fink C - PLoS ONE (2011)

Bottom Line: SNR was improved by HYPR: ULD vs.This can be used to substantially reduce radiation dose.Alternatively, LD images can be improved by HYPR-LR to higher diagnostic quality.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany. radko.krissak@umm.de

ABSTRACT

Purpose: To evaluate image quality and signal characteristics of brain perfusion CT (BPCT) obtained by low-dose (LD) and ultra-low-dose (ULD) protocols with and without post-processing by highly constrained back-projection (HYPR)-local reconstruction (LR) technique.

Methods and materials: Simultaneous BPCTs were acquired in 8 patients on a dual-source-CT by applying LD (80 kV, 200 mAs, 14×1.2 mm) on tube A and ULD (80 kV, 30 mAs, 14×1.2 mm) on tube B. Image data from both tubes was reconstructed with identical parameters and post-processed using the HYPR-LR. Correlation coefficients between mean and maximum (MAX) attenuation values within corresponding ROIs, area under attenuation curve (AUC), and signal to noise ratio (SNR) of brain parenchyma were assessed. Subjective image quality was assessed on a 5-point scale by two blinded observers (1: excellent, 5: non-diagnostic).

Results: Radiation dose of ULD was more than six times lower compared to LD. SNR was improved by HYPR: ULD vs. ULD+HYPR: 1.9±0.3 vs. 8.4±1.7, LD vs. LD+HYPR: 5.0±0.7 vs. 13.4±2.4 (both p<0.0001). There was a good correlation between the original datasets and the HYPR-LR post-processed datasets: r = 0.848 for ULD and ULD+HYPR and r = 0.933 for LD and LD+HYPR (p<0.0001 for both). The mean values of the HYPR-LR post-processed ULD dataset correlated better with the standard LD dataset (r = 0.672) than unprocessed ULD (r = 0.542), but both correlations were significant (p<0.0001). There was no significant difference in AUC or MAX. Image quality was rated excellent (1.3) in LD+HYPR and non-diagnostic (5.0) in ULD. LD and ULD+HYPR images had moderate image quality (3.3 and 2.7).

Conclusion: SNR and image quality of ULD-BPCT can be improved to a level similar to LD-BPCT when using HYPR-LR without distorting attenuation measurements. This can be used to substantially reduce radiation dose. Alternatively, LD images can be improved by HYPR-LR to higher diagnostic quality.

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Mean attenuation values in a corresponding 60 s time series of the ultra low dose (ULD), the HYPR-LR-post-processed ultra low dose (ULD+HYPR), the low dose (LD) and the HYPR-LR-post-processed low dose (HYPR+LD) images.
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pone-0017098-g006: Mean attenuation values in a corresponding 60 s time series of the ultra low dose (ULD), the HYPR-LR-post-processed ultra low dose (ULD+HYPR), the low dose (LD) and the HYPR-LR-post-processed low dose (HYPR+LD) images.

Mentions: There was a good correlation between the mean attenuation values of the original datasets and the HYPR-LR-post-processed datasets for ULD vs. ULD+HYPR and LD vs. LD+HYPR, respectively (r = 0.848 and r = 0.933, p<0.0001). The mean attenuation values of the HYPR-LR-post-processed ULD dataset showed a higher correlation with the standard LD dataset than with the unprocessed ULD dataset (r = 0.672 vs. 0.542), but both correlations were significant (p<0.0001). The correlation coefficients with 95% confidence intervals are summarized in Table 1. The agreement between the mean attenuation values of the datasets is also visualized in Bland-Altman plots in Figure 5. There was no significant difference in the calculated AUC and in the maximum attenuation values. There was a significant difference between the minimum attenuation values between the ULD and the LD datasets (36±5 HU vs. 40±3 HU, p = 0.001). However, there was no significant difference in minimum attenuation values between the ULD+HYPR dataset and the LD dataset (38±4 vs. 40±3 HU, p = 0.13). Example attenuation curves of the corresponding time series are provided in Figure 6. SNR could be significantly improved by HYPR-LR compared to the original datasets: ULD vs. ULD+HYPR: 1.9±0.3 vs. 8.4±1.7 (p<0.0001), LD vs. LD+HYPR: 5.0±0.7 vs. 13.4±2.4 (p<0.0001). The SNR of ULD+HYPR was also significantly higher than that of LD (p<0.001). The values are summarized in Table 2.


Noise reduction and image quality improvement of low dose and ultra low dose brain perfusion CT by HYPR-LR processing.

Krissak R, Mistretta CA, Henzler T, Chatzikonstantinou A, Scharf J, Schoenberg SO, Fink C - PLoS ONE (2011)

Mean attenuation values in a corresponding 60 s time series of the ultra low dose (ULD), the HYPR-LR-post-processed ultra low dose (ULD+HYPR), the low dose (LD) and the HYPR-LR-post-processed low dose (HYPR+LD) images.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3037968&req=5

pone-0017098-g006: Mean attenuation values in a corresponding 60 s time series of the ultra low dose (ULD), the HYPR-LR-post-processed ultra low dose (ULD+HYPR), the low dose (LD) and the HYPR-LR-post-processed low dose (HYPR+LD) images.
Mentions: There was a good correlation between the mean attenuation values of the original datasets and the HYPR-LR-post-processed datasets for ULD vs. ULD+HYPR and LD vs. LD+HYPR, respectively (r = 0.848 and r = 0.933, p<0.0001). The mean attenuation values of the HYPR-LR-post-processed ULD dataset showed a higher correlation with the standard LD dataset than with the unprocessed ULD dataset (r = 0.672 vs. 0.542), but both correlations were significant (p<0.0001). The correlation coefficients with 95% confidence intervals are summarized in Table 1. The agreement between the mean attenuation values of the datasets is also visualized in Bland-Altman plots in Figure 5. There was no significant difference in the calculated AUC and in the maximum attenuation values. There was a significant difference between the minimum attenuation values between the ULD and the LD datasets (36±5 HU vs. 40±3 HU, p = 0.001). However, there was no significant difference in minimum attenuation values between the ULD+HYPR dataset and the LD dataset (38±4 vs. 40±3 HU, p = 0.13). Example attenuation curves of the corresponding time series are provided in Figure 6. SNR could be significantly improved by HYPR-LR compared to the original datasets: ULD vs. ULD+HYPR: 1.9±0.3 vs. 8.4±1.7 (p<0.0001), LD vs. LD+HYPR: 5.0±0.7 vs. 13.4±2.4 (p<0.0001). The SNR of ULD+HYPR was also significantly higher than that of LD (p<0.001). The values are summarized in Table 2.

Bottom Line: SNR was improved by HYPR: ULD vs.This can be used to substantially reduce radiation dose.Alternatively, LD images can be improved by HYPR-LR to higher diagnostic quality.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany. radko.krissak@umm.de

ABSTRACT

Purpose: To evaluate image quality and signal characteristics of brain perfusion CT (BPCT) obtained by low-dose (LD) and ultra-low-dose (ULD) protocols with and without post-processing by highly constrained back-projection (HYPR)-local reconstruction (LR) technique.

Methods and materials: Simultaneous BPCTs were acquired in 8 patients on a dual-source-CT by applying LD (80 kV, 200 mAs, 14×1.2 mm) on tube A and ULD (80 kV, 30 mAs, 14×1.2 mm) on tube B. Image data from both tubes was reconstructed with identical parameters and post-processed using the HYPR-LR. Correlation coefficients between mean and maximum (MAX) attenuation values within corresponding ROIs, area under attenuation curve (AUC), and signal to noise ratio (SNR) of brain parenchyma were assessed. Subjective image quality was assessed on a 5-point scale by two blinded observers (1: excellent, 5: non-diagnostic).

Results: Radiation dose of ULD was more than six times lower compared to LD. SNR was improved by HYPR: ULD vs. ULD+HYPR: 1.9±0.3 vs. 8.4±1.7, LD vs. LD+HYPR: 5.0±0.7 vs. 13.4±2.4 (both p<0.0001). There was a good correlation between the original datasets and the HYPR-LR post-processed datasets: r = 0.848 for ULD and ULD+HYPR and r = 0.933 for LD and LD+HYPR (p<0.0001 for both). The mean values of the HYPR-LR post-processed ULD dataset correlated better with the standard LD dataset (r = 0.672) than unprocessed ULD (r = 0.542), but both correlations were significant (p<0.0001). There was no significant difference in AUC or MAX. Image quality was rated excellent (1.3) in LD+HYPR and non-diagnostic (5.0) in ULD. LD and ULD+HYPR images had moderate image quality (3.3 and 2.7).

Conclusion: SNR and image quality of ULD-BPCT can be improved to a level similar to LD-BPCT when using HYPR-LR without distorting attenuation measurements. This can be used to substantially reduce radiation dose. Alternatively, LD images can be improved by HYPR-LR to higher diagnostic quality.

Show MeSH
Related in: MedlinePlus