AI Denoising Significantly Enhances Image Quality and Diagnostic Confidence in Interventional Cone-Beam Computed Tomography.

(1) To investigate whether interventional cone-beam computed tomography (cbCT) could benefit from AI denoising, particularly with respect to patient body mass index (BMI); (2) From 1 January 2016 to 1 January 2022, 100 patients with liver-directed interventions and peri-procedural cbCT were included. The unenhanced mask run and the contrast-enhanced fill run of the cbCT were reconstructed using weighted filtered back projection. Additionally, each dataset was post-processed using a novel denoising software solution. Place-consistent regions of interest measured signal-to-noise ratio (SNR) per dataset. Corrected mixed-effects analysis with BMI subgroup analyses compared objective image quality. Multiple linear regression measured the contribution of "Radiation Dose", "Body-Mass-Index", and "Mode" to SNR. Two radiologists independently rated diagnostic confidence. Inter-rater agreement was measured using Spearman correlation (r); (3) SNR was significantly higher in the denoised datasets than in the regular datasets (p < 0.001). Furthermore, BMI subgroup analysis showed significant SNR deteriorations in the regular datasets for higher patient BMI (p < 0.001), but stable results for denoising (p > 0.999). In regression, only denoising contributed positively towards SNR (0.6191; 95%CI 0.6096 to 0.6286; p < 0.001). The denoised datasets received overall significantly higher diagnostic confidence grades (p = 0.010), with good inter-rater agreement (r ≥ 0.795, p < 0.001). In a subgroup analysis, diagnostic confidence deteriorated significantly for higher patient BMI (p < 0.001) in the regular datasets but was stable in the denoised datasets (p ≥ 0.103).; (4) AI denoising can significantly enhance image quality in interventional cone-beam CT and effectively mitigate diagnostic confidence deterioration for rising patient BMI.

AI Denoising Significantly Improves Image Quality in Whole-Body Low-Dose Computed Tomography Staging.

(1) Background: To evaluate the effects of an AI-based denoising post-processing software solution in low-dose whole-body computer tomography (WBCT) stagings; (2) Methods: From 1 January 2019 to 1 January 2021, we retrospectively included biometrically matching melanoma patients with clinically indicated WBCT staging from two scanners. The scans were reconstructed using weighted filtered back-projection (wFBP) and Advanced Modeled Iterative Reconstruction strength 2 (ADMIRE 2) at 100% and simulated 50%, 40%, and 30% radiation doses. Each dataset was post-processed using a novel denoising software solution. Five blinded radiologists independently scored subjective image quality twice with 6 weeks between readings. Inter-rater agreement and intra-rater reliability were determined with an intraclass correlation coefficient (ICC). An adequately corrected mixed-effects analysis was used to compare objective and subjective image quality. Multiple linear regression measured the contribution of "Radiation Dose", "Scanner", "Mode", "Rater", and "Timepoint" to image quality. Consistent regions of interest (ROI) measured noise for objective image quality; (3) Results: With good-excellent inter-rater agreement and intra-rater reliability (Timepoint 1: ICC ≥ 0.82, 95% CI 0.74-0.88; Timepoint 2: ICC ≥ 0.86, 95% CI 0.80-0.91; Timepoint 1 vs. 2: ICC ≥ 0.84, 95% CI 0.78-0.90; all p ≤ 0.001), subjective image quality deteriorated significantly below 100% for wFBP and ADMIRE 2 but remained good-excellent for the post-processed images, regardless of input (p ≤ 0.002). In regression analysis, significant increases in subjective image quality were only observed for higher radiation doses (≥0.78, 95%CI 0.63-0.93; p < 0.001), as well as for the post-processed images (≥2.88, 95%CI 2.72-3.03, p < 0.001). All post-processed images had significantly lower image noise than their standard counterparts (p < 0.001), with no differences between the post-processed images themselves. (4) Conclusions: The investigated AI post-processing software solution produces diagnostic images as low as 30% of the initial radiation dose (3.13 ± 0.75 mSv), regardless of scanner type or reconstruction method. Therefore, it might help limit patient radiation exposure, especially in the setting of repeated whole-body staging examinations.

Diagnostic Performance of a Contrast-Enhanced Ultra-Low-Dose High-Pitch CT Protocol with Reduced Scan Range for Detection of Pulmonary Embolisms.

(1) Background: To evaluate the diagnostic performance of a simulated ultra-low-dose (ULD), high-pitch computed tomography pulmonary angiography (CTPA) protocol with low tube current (mAs) and reduced scan range for detection of pulmonary embolisms (PE). (2) Methods: We retrospectively included 130 consecutive patients (64 ± 16 years, 69 female) who underwent clinically indicated high-pitch CTPA examination for suspected acute PE on a 3rd generation dual-source CT scanner (SOMATOM FORCE, Siemens Healthineers, Forchheim, Germany). ULD datasets with a realistic simulation of 25% mAs, reduced scan range (aortic arch-basal pericardium), and Advanced Modeled Iterative Reconstruction (ADMIRE®, Siemens Healthineers, Forchheim, Germany) strength 5 were created. The effective radiation dose (ED) of both datasets (standard and ULD) was estimated using a dedicated dosimetry software solution. Subjective image quality and diagnostic confidence were evaluated independently by three reviewers using a 5-point Likert scale. Objective image quality was compared using noise measurements. For assessment of diagnostic accuracy, patients and pulmonary vessels were reviewed binarily for affection by PE, using standard CTPA protocol datasets as the reference standard. Percentual affection of pulmonary vessels by PE was computed for disease severity (modified Qanadli score). (3) Results: Mean ED in ULD protocol was 0.7 ± 0.3 mSv (16% of standard protocol: 4.3 ± 1.7 mSv, p < 0.001, r > 0.5). Comparing ULD to standard protocol, subjective image quality and diagnostic confidence were comparably good (p = 0.486, r > 0.5) and image noise was significantly lower in ULD (p < 0.001, r > 0.5). A total of 42 patients (32.2%) were affected by PE. ULD protocol had a segment-based false-negative rate of only 0.1%. Sensitivity for detection of any PE was 98.9% (95% CI, 97.2-99.7%), specificity was 100% (95% CI, 99.8-100%), and overall accuracy was 99.9% (95% CI, 98.6-100%). Diagnoses correlated strongly between ULD and standard protocol (Chi-square (1) = 42, p < 0.001) with a decrease in disease severity of only 0.48% (T = 1.667, p = 0.103). (4) Conclusions: Compared to a standard CTPA protocol, the proposed ULD protocol proved reliable in detecting and ruling out acute PE with good levels of image quality and diagnostic confidence, as well as significantly lower image noise, at 0.7 ± 0.3 mSv (84% dose reduction).

Simulated Radiation Dose Reduction in Whole-Body CT on a 3rd Generation Dual-Source Scanner: An Intraindividual Comparison.

To evaluate the effect of radiation dose reduction on image quality and diagnostic confidence in contrast-enhanced whole-body computed tomography (WBCT) staging. We randomly selected March 2016 for retrospective inclusion of 18 consecutive patients (14 female, 60 ± 15 years) with clinically indicated WBCT staging on the same 3rd generation dual-source CT. Using low-dose simulations, we created data sets with 100, 80, 60, 40, and 20% of the original radiation dose. Each set was reconstructed using filtered back projection (FBP) and Advanced Modeled Iterative Reconstruction (ADMIRE®, Siemens Healthineers, Forchheim, Germany) strength 1-5, resulting in 540 datasets total. ADMIRE 2 was the reference standard for intraindividual comparison. The effective radiation dose was calculated using commercially available software. For comparison of objective image quality, noise assessments of subcutaneous adipose tissue regions were performed automatically using the software. Three radiologists blinded to the study evaluated image quality and diagnostic confidence independently on an equidistant 5-point Likert scale (1 = poor to 5 = excellent). At 100%, the effective radiation dose in our population was 13.3 ± 9.1 mSv. At 20% radiation dose, it was possible to obtain comparably low noise levels when using ADMIRE 5 (p = 1.000, r = 0.29). We identified ADMIRE 3 at 40% radiation dose (5.3 ± 3.6 mSv) as the lowest achievable radiation dose with image quality and diagnostic confidence equal to our reference standard (p = 1.000, r > 0.4). The inter-rater agreement for this result was almost perfect (ICC ≥ 0.958, 95% CI 0.909-0.983). On a 3rd generation scanner, it is feasible to maintain good subjective image quality, diagnostic confidence, and image noise in single-energy WBCT staging at dose levels as low as 40% of the original dose (5.3 ± 3.6 mSv), when using ADMIRE 3.

Diagnostic Performance of Different Simulated Low-Dose Levels in Patients with Suspected Cervical Abscess Using a Third-Generation Dual-Source CT Scanner.

The aim of this study was to investigate the effects of dose reduction on diagnostic accuracy and image quality of cervical computed tomography (CT) in patients with suspected cervical abscess. Forty-eight patients (mean age 45.5 years) received a CT for suspected cervical abscess. Low-dose CT (LDCT) datasets with 25%, 50%, and 75% of the original dose were generated with a realistic simulation. The image data were reconstructed with filtered back projection (FBP) and with advanced modeled iterative reconstruction (ADMIRE) (strengths 3 and 5). A five-point Likert scale was used to assess subjective image quality and diagnostic confidence. The signal-to-noise ratio (SNR) of the sternocleidomastoid muscle and submandibular gland and the contrast-to-noise ratio (CNR) of the sternocleidomastoid muscle and submandibular glandular fat were calculated to assess the objective image quality. Diagnostic accuracy was calculated for LDCT using the original dose as the reference standard. The prevalence of cervical abscesses was high (72.9%) in the cohort; the mean effective dose for all 48 scans was 1.8 ± 0.8 mSv. Sternocleidomastoid and submandibular SNR and sternocleidomastoid muscle fat and submandibular gland fat CNR increased with higher doses and were significantly higher for ADMIRE compared to FBP, with the best results in ADMIRE 5 (all p < 0.001). Subjective image quality was highest for ADMIRE 5 at 75% and lowest for FBP at 25% of the original dose (p < 0.001). Diagnostic confidence was highest for ADMIRE 5 at 75% and lowest for FBP at 25% (p < 0.001). Patient-based diagnostic accuracy was high for all LDCT datasets, down to 25% for ADMIRE 3 and 5 (sensitivity: 100%; specificity: 100%) and lower for FBP at 25% dose reduction (sensitivity: 88.6-94.3%; specificity: 92.3-100%). The use of a modern dual-source CT of the third generation and iterative reconstruction allows a reduction in the radiation dose to 25% (0.5 mSv) of the original dose with the same diagnostic accuracy for the assessment of neck abscesses.