Dose reduction in abdominal CT: The road to submillisievert imaging

Application of deep learning reconstruction of ultra-low-dose abdominal CT in the diagnosis of renal calculi

BACKGROUND

Renal calculi are a common and recurrent urological disease and are usually detected by CT. In this study, we evaluated the diagnostic capability, image quality, and radiation dose of abdominal ultra-low-dose CT (ULDCT) with deep learning reconstruction (DLR) for detecting renal calculi.

METHODS

Sixty patients with suspected renal calculi were prospectively enrolled. Low-dose CT (LDCT) images were reconstructed with hybrid iterative reconstruction (LD-HIR) and was regarded as the standard for stone and lesion detection. ULDCT images were reconstructed with HIR (ULD-HIR) and DLR (ULD-DLR). We then compared stone detection rate, abdominal lesion detection rate, image quality and radiation dose between LDCT and ULDCT.

RESULTS

A total of 130 calculi were observed on LD-HIR images. Stone detection rates of ULD-HIR and ULD-DLR images were 93.1% (121/130) and 95.4% (124/130). A total of 129 lesions were detected on the LD-HIR images. The lesion detection rate on ULD-DLR images was 92.2%, with 10 cysts < 5 mm in diameter missed. The CT values of organs on ULD-DLR were similar to those on LD-HIR and lower than those on ULD-HIR. Signal-to-noise ratio was highest and noise lowest on ULD-DLR. The subjective image quality of ULD-DLR was similar to that of LD-HIR and better than that of ULD-HIR. The effective radiation dose of ULDCT (0.64 ± 0.17 mSv) was 77% lower than that of LDCT (2.75 ± 0.50 mSv).

CONCLUSION

ULDCT combined with DLR could significantly reduce radiation dose while maintaining suitable image quality and stone detection rate in the diagnosis of renal calculi.

Sparse-sampling computed tomography for detection of endoleak after endovascular aortic repair (EVAR)

OBJECTIVES

To evaluate sparse sampling computed tomography (SpSCT) for detection of endoleak after endovascular aortic repair (EVAR) at different dose levels in terms of subjective image criteria and diagnostic accuracy.

METHODS

Twenty clinically indicated computed tomography aortic angiography (CTA) scans were used to obtain simulated low-dose scans with 100%, 50%, 25%, 12.5% and 6.25% of the applicated clinical dose, resulting in five dose levels (DL). From full sampling (FS) data sets, every second (2-SpSCT) or fourth (4-SpSCT) projection was used to generate simulated sparse sampling scans. All examinations were evaluated by four blinded radiologists regarding subjective image criteria and diagnostic performance.

RESULTS

Sensitivity was higher than 93% in 4-SpSCT at the 25% DL which is the same as with FS at full dose (100% DL). High accuracies and relative high AUC-values were obtained for 2- and 4-SpSCT down to the 12.5% DL, while for FS similar values were shown down to 25% DL only. Subjective image quality was significantly higher for 4-SpSCT compared to FS at each dose level. More than 90% of all cases were rated with a high or medium confidence for FS and 2-SpSCT at the 50% DL and for 4-SpSCT at the 25% DL. At DL 25% and 12.5%, more cases showed a high confidence using 2- and 4-SpSCT compared with FS.

CONCLUSIONS

Via SpSCT, a dose reduction down to a 25% dose level (mean effective dose of 1.49 mSv in the current study) for CTA is possible while maintaining high image quality and full diagnostic confidence.

Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT

OBJECTIVE. The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. MATERIALS AND METHODS. Our prospective multiinstitutional study included 59 adult patients (33 women, 26 men; mean age ± SD, 65 ± 12 years old; mean body mass index [weight in kilograms divided by the square of height in meters] = 27 ± 5) who underwent routine chest (n = 22; 16 women, six men) and abdominopelvic (n = 37; 17 women, 20 men) CT on a 640-MDCT scanner (Aquilion ONE, Canon Medical Systems). All patients gave written informed consent for the acquisition of low-dose (LD) CT (LDCT) after a clinically indicated standard-dose (SD) CT (SDCT). The SDCT series (120 kVp, 164-644 mA) were reconstructed with interactive reconstruction (IR) (adaptive iterative dose reduction [AIDR] 3D, Canon Medical Systems), and the LDCT (100 kVp, 120 kVp; 30-50 mA) were reconstructed with filtered back-projection (FBP), IR (AIDR 3D and forward-projected model-based iterative reconstruction solution [FIRST], Canon Medical Systems), and deep learning reconstruction (DLR) (Advanced Intelligent Clear-IQ Engine [AiCE], Canon Medical Systems). Four subspecialty-trained radiologists first read all LD image sets and then compared them side-by-side with SD AIDR 3D images in an independent, randomized, and blinded fashion. Subspecialty radiologists assessed image quality of LDCT images on a 3-point scale (1 = unacceptable, 2 = suboptimal, 3 = optimal). Descriptive statistics were obtained, and the Wilcoxon sign rank test was performed. RESULTS. Mean volume CT dose index and dose-length product for LDCT (2.1 ± 0.8 mGy, 49 ± 13mGy·cm) were lower than those for SDCT (13 ± 4.4 mGy, 567 ± 249 mGy·cm) (p < 0.0001). All 31 clinically significant abdominal lesions were seen on SD AIDR 3D and LD DLR images. Twenty-five, 18, and seven lesions were detected on LD AIDR 3D, LD FIRST, and LD FBP images, respectively. All 39 pulmonary nodules detected on SD AIDR 3D images were also noted on LD DLR images. LD DLR images were deemed acceptable for interpretation in 97% (35/37) of abdominal and 95-100% (21-22/22) of chest LDCT studies (p = 0.2-0.99). The LD FIRST, LD AIDR 3D, and LD FBP images had inferior image quality compared with SD AIDR 3D images (p < 0.0001). CONCLUSION. At submillisievert chest and abdominopelvic CT doses, DLR enables image quality and lesion detection superior to commercial IR and FBP images.

Effects of virtual tube current reduction and sparse sampling on MDCT-based femoral BMD measurements

This study investigates the impact of tube current reduction and sparse sampling on femoral bone mineral density (BMD) measurements derived from multi-detector computed tomography (MDCT). The application of sparse sampling led to robust and clinically acceptable BMD measurements. In contrast, BMD measurements derived from MDCT with virtually reduced tube currents showed a considerable increase when compared to original data.

INTRODUCTION

The study aims to evaluate the effects of radiation dose reduction by using virtual reduction of tube current or sparse sampling combined with standard filtered back projection (FBP) and statistical iterative reconstruction (SIR) on femoral bone mineral density (BMD) measurements derived from multi-detector computed tomography (MDCT).

METHODS

In routine MDCT scans of 41 subjects (65.9% men; age 69.3 ± 10.1 years), reduced radiation doses were simulated by lowering tube currents and applying sparse sampling (50, 25, and 10% of the original tube current and projections, respectively). Images were reconstructed using FBP and SIR. BMD values were assessed in the femoral neck and compared between the different dose levels, numbers of projections, and image reconstruction approaches.

RESULTS

Compared to full-dose MDCT, virtual lowering of the tube current by applying our simulation algorithm resulted in increases in BMD values for both FBP (up to a relative change of 32.5%) and SIR (up to a relative change of 32.3%). In contrast, the application of sparse sampling with a reduction down to 10% of projections showed robust BMD values, with clinically acceptable relative changes of up to 0.5% (FBP) and 0.7% (SIR).

CONCLUSIONS

Our simulations, which still require clinical validation, indicate that reductions down to ultra-low tube currents have a significant impact on MDCT-based femoral BMD measurements. In contrast, the application of sparse-sampled MDCT seems a promising future clinical option that may enable a significant reduction of the radiation dose without considerable changes of BMD values.