Assessment of image quality and low-contrast detectability in abdominal CT of obese patients: comparison of a novel integrated circuit with a conventional discrete circuit detector at different tube voltages

Detectability of Hypoattenuating Liver Lesions with Deep Learning CT Reconstruction: A Phantom and Patient Study

Background CT deep learning image reconstruction (DLIR) improves image quality by reducing noise compared with adaptive statistical iterative reconstruction-V (ASIR-V). However, objective assessment of low-contrast lesion detectability is lacking. Purpose To investigate low-contrast detectability of hypoattenuating liver lesions on CT scans reconstructed with DLIR compared with CT scans reconstructed with ASIR-V in a patient and a phantom study. Materials and Methods This single-center retrospective study included patients undergoing portal venous phase abdominal CT between February and May 2021 and a low-contrast-resolution phantom scanned with the same protocol. Four reconstructions (ASIR-V at 40% strength [ASIR-V 40] and DLIR at three strengths) were generated. Five radiologists qualitatively assessed the images using the five-point Likert scale for image quality, lesion diagnostic confidence, conspicuity, and small lesion (≤1 cm) visibility. Up to two key lesions per patient, confirmed at histopathologic testing or at prior or follow-up imaging studies, were included. Lesion-to-background contrast-to-noise ratio was calculated. Interreader variability was analyzed. Intergroup qualitative and quantitative metrics were compared between DLIR and ASIR-V 40 using proportional odds logistic regression models. Results Eighty-six liver lesions (mean size, 15 mm ± 9.5 [SD]) in 50 patients (median age, 62 years [IQR, 57-73 years]; 27 [54%] female patients) were included. Differences were not detected for various qualitative low-contrast detectability metrics between ASIR-V 40 and DLIR (P > .05). Quantitatively, medium-strength DLIR and high-strength DLIR yielded higher lesion-to-background contrast-to-noise ratios than ASIR-V 40 (medium-strength DLIR vs ASIR-V 40: odds ratio [OR], 1.96 [95% CI: 1.65, 2.33]; high-strength DLIR vs ASIR-V 40: OR, 5.36 [95% CI: 3.68, 7.82]; P < .001). Low-contrast lesion attenuation was reduced by 2.8-3.6 HU with DLIR. Interreader agreement was moderate to very good for the qualitative metrics. Subgroup analysis based on lesion size of larger than 1 cm and 1 cm or smaller yielded similar results (P > .05). Qualitatively, phantom study results were similar to those in patients (P > .05). Conclusion The detectability of low-contrast liver lesions was similar on CT scans reconstructed with low-, medium-, and high-strength DLIR and ASIR-V 40 in both patient and phantom studies. Lesion-to-background contrast-to-noise ratios were higher for DLIR medium- and high-strength reconstructions compared with ASIR-V 40. © RSNA, 2024 Supplemental material is available for this article.

Accuracy of non-gated low-dose non-contrast chest CT with tin filtration for coronary artery calcium scoring

Objective

The study investigated the accuracy of coronary artery calcium scores (CACS) and the potential for reducing radiation dose using non-gated low-dose non-contrast chest computed tomography (CT) scanning with tin filtration for one-stop screening of the lungs and heart.

Methods

A prospective study was conducted,193 Patients received two scans for determining CACS, including an ECG-gated CT at 120 kV (ECG-gated CT), followed by a non-gated low-dose chest CT using 100 kV with tin filtration (non-gated Sn100 kV-LDCT). The Agatston score (AS), risk stratification, and radiation dose were compared between the scan types.

Results

There was good consistency in the AS from both an ECG-gated CT and a non-gated low-dose chest CT scan, which had a high correlation (r = 0.970). The Kappa value of risk stratification of the two scan types was 0.549. The area under the ROC curve (AUC) of the CACS was used to develop a new risk stratification standard for non-gated Sn100 kV-LDCT evaluation of CACS. In comparison to the CACS measured by ECG-gated CT, non-gated Sn100 kV-LDCT had an AUC of 0.951 and an optimal critical value of 4.6 in the low-risk category. The AUC of low-medium risk was 0.966, and the optimal critical value was 41.2. The AUC of the medium-high risk category was 0.968, and the optimal critical value was 230. The consistency in CACS measured by ECG-gated CT and non-gated Sn100 kV-LDCT had a Kappa value of 0.831. The Effective dose (ED) of non-gated Sn100 kV-LDCT and ECG-gated CT was 0.056 ± 0.017 mSv and 0.685 ± 0.455 mSv, respectively (p < 0.05).

Conclusion

The Agatston score of CACS using non-gated low-dose chest CT was accurate, but there was an underestimation in risk stratification. This study developed a new risk stratification standard for non-gated Sn100 kV-LDCT evaluation of CACS, which is in closer agreement with CACS derived from ECG-gated CT scans.

Initial Results of a Single-Source Dual-Energy Computed Tomography Technique Using a Split-Filter: Assessment of Image Quality, Radiation Dose, and Accuracy of Dual-Energy Applications in an In Vitro and In Vivo Study

OBJECTIVE

The aim of this study was to investigate the image quality, radiation dose, and accuracy of virtual noncontrast images and iodine quantification of split-filter dual-energy computed tomography (CT) using a single x-ray source in a phantom and patient study.

MATERIALS AND METHODS

In a phantom study, objective image quality and accuracy of iodine quantification were evaluated for the split-filter dual-energy mode using a tin and gold filter. In a patient study, objective image quality and radiation dose were compared in thoracoabdominal CT of 50 patients between the standard single-energy and split-filter dual-energy mode. The radiation dose was estimated by size-specific dose estimate. To evaluate the accuracy of virtual noncontrast imaging, attenuation measurements in the liver, spleen, and muscle were compared between a true noncontrast premonitoring scan and the virtual noncontrast images of the dual-energy scans. Descriptive statistics and the Mann-Whitney U test were used.

RESULTS

In the phantom study, differences between the real and measured iodine concentration ranged from 2.2% to 21.4%. In the patient study, the single-energy and dual-energy protocols resulted in similar image noise (7.4 vs 7.1 HU, respectively; P = 0.43) and parenchymal contrast-to-noise ratio (CNR) values for the liver (29.2 vs 28.5, respectively; P = 0.88). However, the vascular CNR value for the single-energy protocol was significantly higher than for the dual-energy protocol (10.0 vs 7.1, respectively; P = 0.006). The difference in the measured attenuation between the true and the virtual noncontrast images ranged from 3.1 to 6.7 HU. The size-specific dose estimate of the dual-energy protocol was, on average, 17% lower than that of the single-energy protocol (11.7 vs 9.7 mGy, respectively; P = 0.008).

CONCLUSIONS

Split-filter dual-energy compared with single-energy CT results in similar objective image noise in addition to dual-energy capabilities at 17% lower radiation dose. Because of beam hardening, split-filter dual-energy can lead to decreased CNR values of iodinated structures.

Metal artifact reduction (MAR) based on two-compartment physical modeling: evaluation in patients with hip implants

BACKGROUND

Artifacts from metallic implants can hinder image interpretation in computed tomography (CT). Image quality can be improved using metal artifact reduction (MAR) techniques.

PURPOSE

To evaluate the impact of a MAR algorithm on image quality of CT examinations in comparison to filtered back projection (FBP) in patients with hip prostheses.

MATERIAL AND METHODS

Twenty-two patients with 25 hip prostheses who underwent clinical abdominopelvic CT on a 64-row CT were included in this retrospective study. Axial images were reconstructed with FBP and five increasing MAR levels (M30-34). Objective artifact strength (OAS) (SI_art-SI_norm) was assessed by region of interest (ROI) measurements in position of the strongest artifact (SI_art) and in an osseous structure without artifact (SI_norm) (in Hounsfield units [HU]). Two independent readers evaluated subjective image quality regarding metallic hardware, delineation of bone, adjacent muscle, and pelvic organs on a 5-point scale (1, non-diagnostic; 5, excellent image quality). Artifacts in the near field, far field, and newly induced artifacts due to the MAR technique were analyzed.

RESULTS

OAS values were: M34: 243.8 ± 155.4 HU; M33: 294.3 ± 197.8 HU; M32: 340.5 ± 210.1 HU; M31: 393.6 ± 225.2 HU; M30: 446.8 ± 224.2 HU and FBP: 528.9 ± 227.7 HU. OAS values were significantly lower for M32-34 compared to FBP (P < 0.01). For overall subjective image quality, results were: FBP, 2.0 ± 0.2; M30, 2.3 ± 0.8; M31, 2.6 ± 0.5; M32, 3.0 ± 0.6; M33, 3.5 ± 0.6; and M34, 3.8 ± 0.4 (P < 0.001 for M30-M34 vs. FBP, respectively). Increasing MAR levels resulted in new artifacts in 17% of reconstructions.

CONCLUSION

The investigated MAR algorithm led to a significant reduction of artifacts from metallic hip implants. The highest MAR level provided the least severe artifacts and the best overall image quality.

Ultralow-dose CT with tin filtration for detection of solid and sub solid pulmonary nodules: a phantom study

OBJECTIVES

To investigate the diagnostic performance of advanced modelled iterative reconstruction (ADMIRE) to filtered back projection (FBP) when using an ultralow-dose protocol for the detection of solid and subsolid pulmonary nodules.

METHODS

Single-energy CT was performed at 100 kVp with tin filtration in an anthropomorphic chest phantom with solid and subsolid pulmonary nodules (2-10 mm, attenuation, 20 to -800 HU at 120 kVp). The mean volume CT dose index (CTDIvol) of the standard chest protocol was 2.2 mGy. Subsequent scans were obtained at 1/8 (0.28 mGy), 1/20 (0.10 mGy) and 1/70 (0.03 mGy) dose levels by lowering tube voltage and tube current. Images were reconstructed with FBP and ADMIRE. One reader measured image noise; two readers determined image quality and assessed nodule localization.

RESULTS

Image noise was significantly reduced using ADMIRE compared with FBP (ADMIRE at a strength level of 5 : 70.4% for 1/20; 71.6% for 1/8; p < 0.001). Interobserver agreement for image quality was excellent (k = 0.88). Image quality was considered diagnostic for all images at 1/20 dose using ADMIRE. Sensitivity of nodule detection was 97.1% (100% for solid, 93.8% for subsolid nodules) at 1/20 dose and 100% for both nodule entities at 1/8 dose using ADMIRE 5. Images obtained with 1/70 dose had moderate sensitivity (overall 85.7%; solid 95%; subsolid 73.3%).

CONCLUSION

Our study suggests that with a combination of tin filtration and ADMIRE, the CTDIvol of chest CT can be lowered considerably, while sensitivity for nodule detection remains high. For solid nodules, CTDIvol was 0.10 mGy, while subsolid nodules required a slightly higher CTDIvol of 0.28 mGy.

ADVANCES IN KNOWLEDGE

Detection of subsolid nodules is feasible with ultralow-dose protocols.