Comparable Image Quality Research Articles

Comparison of image quality, contrast administration, and radiation doses in pediatric abdominal dual-layer detector dual-energy CT using propensity score matching analysis

PurposeTo compare the image quality, contrast administration, and radiation dose between single-energy CT (SECT) and dual-energy CT (DECT) in pediatric patients. MethodsFrom March to December 2021, children who underwent abdominal SECT or DECT were retrospectively included in this study. The DECT group received 10–30 % less contrast than the routine dose. CT images were obtained at hepatic venous phase using a routine reconstruction method (iDose4). DECT scans were additionally reconstructed with a virtual monoenergetic image (VMI) at 40 and 65 keV. Quantitative image evaluations compared the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the liver, portal vein, and pancreas. Qualitative analysis assessed degree of contrast enhancement, lesion or organ conspicuity, image noise, artificiality, and overall image quality. ResultsAmong 318 patients, 112 (median age, 16 years; 56 in each group) were included after propensity score matching. Compared with the SECT group, DECT group with iDose4 demonstrated lower CNRs and SNRs, while VMI at 40 or 65 keV showed no significant difference. In qualitative analysis, iDose4 produced higher scores on artificiality, and VMI at 40 keV demonstrated superior contrast enhancement and lesion conspicuity in the DECT group. Overall image quality was higher with VMI 65 keV among the DECT patients, and there was no significant difference compared to SECT. The volume CT dose index (CTDIvol) did not differ significantly between the two groups (median, 2.8 mGy vs. 2.9 mGy; p = 0.802). The injected contrast volume was reduced by 10 % in the DECT group. ConclusionPediatric abdominal DECT with reduced contrast administration showed no significant differences in image quality and radiation dose compared to SECT.

Self-navigated coronary MR angiography for coronary aneurysm detection in Kawasaki disease at 3T: comparison with conventional diaphragm-navigated coronary MR angiography.

To assess the scan time, image quality, and diagnostic performance of self-navigated coronary MR angiography (SN-CMRA) for coronary aneurysm (CAA) detection in Kawasaki disease (KD) patients and compare it with diaphragm-navigated CMRA (DN-CMRA). SN-CMRA and DN-CMRA were performed on 76 pediatric patients with KD (48 males, 6.75 ± 3.59 years). Thirty-three of whom underwent coronary CT angiography (CCTA)/invasive coronary angiography (ICA). The scan time and qualitative and quantitative image quality assessment were compared between the two sequences. The diagnostic performance for CAA detection by the two approaches using CCTA/ICA as the reference standard was compared on per-patient, per-vessel, and per-segment basis. The scan time of SN-CMRA was significantly shorter than that of DN-CMRA (7.49 ± 2.31 min vs. 10.03 ± 4.47 min, p< 0.001). There was no difference in overall and segmental image quality to reach the clinical diagnostic criteria between the two sequences (all p> 0.05). No significant difference in vessel length of the three main coronary arteries was found between the two approaches (all p> 0.05). Moreover, SN-CMRA showed no difference from DN-CMRA in contrast ratio of blood-myocardium (1.25 (interquartile range [IQR], 1.06 to 1.51) vs. 1.18 (IQR, 0.95 to 1.64), p= 0.706). There was no difference in the diagnostic accuracy of SN-CMRA and DN-CMRA for CAA detection on per-patient, per-vessel, or per-segment basis (all p> 0.05). SN-CMRA at 3T showed reliable diagnostic performance and application value for CAA detection in children with KD. Compared with DN-CMRA, SN-CMRA can simplify the scanning procedure and shorten the scan time, achieving comparable image quality and diagnostic accuracy. Coronary aneurysm in children with Kawasaki disease (KD) can be detected by self-navigated coronary MR angiography (CMRA) non-invasively and without radiation, achieving comparable image quality and diagnostic performance as diaphragm-navigated CMRA while shortening scanning time. It can provide reference for risk stratification and treatment management of KD. • Evaluating the size of coronary aneurysm is important for risk stratification and treatment of Kawasaki disease. • Self-navigated coronary MR angiography (SN-CMRA) shortens scan time and achieves comparable image quality and diagnostic performance compared with diaphragm-navigated coronary MR angiography. • SN-CMRA can evaluate coronary aneurysm non-invasively and without radiation, providing information for risk stratification and treatment.

Association between Anesthesia Management and Preoperative Magnetic Resonance Image Quality in Patients Scheduled for Deep Brain Stimulation Surgery

Aim: To investigate magnetic resonance image quality and the number of motion artifact-related repeated sequences based on anesthesia or sedation management during preoperative MR imaging for DBS surgery.&#x0D; Material and Methods: The medical records of patients who underwent DBS procedures at the hospital of Ondokuz Mayis University, between April 2011 and October 2021 were retrospectively analyzed. Age, gender, and diagnosis information were recorded for each case. Patients were grouped into general anesthesia, sedation, no sedation groups. The evaluation of magnetic resonance images was performed by a specialized in neuroradiology. The radiologist classified the image quality as good, moderate, or poor based on artifacts resulting from unwanted motion.&#x0D; Results: A total of 127 patients, out of 190 patients, were included in the study. There were no significant differences in image quality based on anesthesia/sedation method and airway management (p&gt;0.05). No significant differences were observed in the number of repeated sequences when compared based on anesthesia/sedation method and airway management (p&gt;0.05).&#x0D; Conclusion: General anesthesia, sedation, or no sedation during preoperative magnetic resonance imaging in patients with movement disorders did not result in significant differences in image quality and the number of sequences requiring repetition.

Organ-based tube current modulation versus spectral shaping via tin prefiltration: What does bismuth breast shielding add in low-dose lung CT?

PurposeSince organ-based tube current modulation (OBTCM) and tin prefiltration are limited on their own in lowering the dose of lung CT examinations, this experimental study was designed to investigate whether combinations with anterior patient shielding can increase the dose reduction potential. Material and methodsThree pairs of scan protocols without/with breast shield (P1/P2: standard 120kVp, P3/P4: OBTCM at 100 kVp, P5/P6: Sn 100 kVp) were employed for radiation exposure and image quality comparisons on an anthropomorphic Alderson-Rando phantom. Equivalent doses were measured in eleven sites via thermoluminescent dosimetry and the effective dose was obtained by summation of the weighted organ doses. Dose-weighted contrast-to-noise ratios (CNRD) were calculated and four radiologists independently assessed the quality of images generated with each protocol. ResultsWhile no significant difference was determined between standard and OBTCM protocols regardless of breast shield (p ≥ 0.068), equivalent doses with spectral shaping were substantially lower (p ≤ 0.003). The highest effective dose was ascertained for standard scans (P1/P2: 7.3/6.8 mSv) with a dose reduction of 8.0 % via breast shielding. The use of a bismuth shield was more beneficial in OBTCM (P3/P4: 6.6/5.3 mSv) and spectral shaping (P5/P6: 0.7/0.6 mSv), reducing the effective dose by 19.8 % and 13.9 %, respectively. Subjective assessment favoured standard protocol P1 over tin prefiltration low-dose scans (p ≤ 0.032), however, no scan protocol entailed diagnostically insufficient image quality. ConclusionsWhereas breast shielding is particularly beneficial in combination with OBTCM, spectral shaping via tin prefiltration facilitates the most pronounced dose reduction in lung CT imaging with acceptable image quality.

Reduced versus standard dose contrast volume for contrast-enhanced abdominal CT in overweight and obese patients using photon counting detector technology vs. second-generation dual-source energy integrating detector CT

PurposeTo compare image quality of contrast-enhanced abdominal-CT using 1st-generation Dual Source Photon-Counting Detector CT (DS-PCD-CT) versus 2nd-generation Dual-Source Energy Integrating-Detector CT (DS-EID-CT) in patients with BMI ≥ 25, applying two different contrast agent volumes, vendor proposed protocols and different virtual monoenergetic images (VMI). Method68 overweight (BMI ≥ 25 kgm2) patients (median age: 65 years; median BMI 33.3 kgm2) who underwent clinically indicated, portal-venous contrast-enhanced abdominal-CT on a commercially available 1st-generation DS-PCD-CT were prospectively included if they already have had a pre-exam on 2nd-generation DS-EID-CT using a standardized exam protocol. Obesity were defined by BMI-calculation (overweight: 25–29.9, obesity grade I: 30–34.9; obesity grade II: 35–39.9; obesity grade III: > 40) and by the absolute weight value. Body weight adapted contrast volume (targeted volume of 1.2 mL/kg for the 1st study and 0.8 mL/kg for the 2nd study) was applied in both groups. Dual Energy mode was used for both the DS-PCD-CT and the DS-EID-CT. Polychromatic images and VMI (40 keV and 70 keV) were reconstructed for both the DS-EID-CT and the DS-PCD-CT data (termed T3D). Two radiologists assessed subjective image quality using a 5-point Likert-scale. Each reader drew ROIs within parenchymatous organs and vascular structures to analyze image noise, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). ResultsMedian time interval between scans was 12 months (Min: 6 months; Max: 36 months). BMI classification included overweight (n = 10, 14.7 %), obesity grade I (n = 38, 55.9 %), grade II (n = 13, 19.1 %) and grade III (n = 7, 10.3 %). The SNR achieved with DS-PCD-CT at QIR level 3was 12.61 vs. 11.47 (QIR 2) vs. 10.53 (DS-EID-CT), irrespective of parenchymatous organs. For vessels, the SNR were 16.73 vs. 14.20 (QIR 2) vs. 12.07 (DS-EID-CT). Moreover, the obtained median noise at QIR level 3 was as low as that of the DS-EID-CT (8.65 vs. 8.65). Both radiologists rated the image quality higher for DS-PCD-CT data sets (p < 0.05). The highest CNR was achieved at 40 keV for both scanners. T3D demonstrated significantly higher SNR and lower noise level compared to 40 keV and 70 keV. Median CTDIvol and DLP values for DS-PCD-CT and DS-EID-CT were 10.90 mGy (IQR: 9.31 – 12.50 mGy) vs. 16.55 mGy (IQR: 15.45 – 18.17 mGy) and 589.50 mGy * cm (IQR: 498.50 – 708.25 mGy * cm) vs. 848.75 mGy * cm (IQR: 753.43 – 969.58 mGy * cm) (p < 0.001). ConclusionImage quality can be maintained while significantly reducing the contrast volume and the radiation dose (27% and 34% lower DLP and 31% lower CDTIvol) for abdominal contrast-enhanced CT using a 1st-generation DS-PCD-CT. Moreover, polychromatic reconstruction T3D on a DS-PCD-CT enables sufficient diagnostic image quality for oncological imaging.

Highly accelerated knee magnetic resonance imaging using deep neural network (DNN)–based reconstruction: prospective, multi-reader, multi-vendor study

In this prospective, multi-reader, multi-vendor study, we evaluated the performance of a commercially available deep neural network (DNN)–based MR image reconstruction in enabling accelerated 2D fast spin-echo (FSE) knee imaging. Forty-five subjects were prospectively enrolled and randomly divided into three 3T MRIs. Conventional 2D FSE and accelerated 2D FSE sequences were acquired for each subject, and the accelerated FSE images were reconstructed and enhanced with DNN–based reconstruction software (FSE-DNN). Quantitative assessments and diagnostic performances were independently evaluated by three musculoskeletal radiologists. For statistical analyses, paired t-tests, and Pearson’s correlation were used for image quality comparison and inter-reader agreements. Accelerated FSE-DNN reduced scan times by 41.0% on average. FSE-DNN showed better SNR and CNR (p < 0.001). Overall image quality of FSE-DNN was comparable (p > 0.05), and diagnostic performances of FSE-DNN showed comparable lesion detection. Two of cartilage lesions were under-graded or over-graded (n = 2) while there was no significant difference in other image sets (n = 43). Overall inter-reader agreement between FSE-conventional and FSE-DNN showed good agreement (R2 = 0.76; p < 0.001). In conclusion, DNN-based reconstruction can be applied to accelerated knee imaging in multi-vendor MRI scanners, with reduced scan time and comparable image quality. This study suggests the potential for DNN-accelerated knee MRI in clinical practice.

Reduced-dose CT in detecting solid liver tumors: A comparison of image quality between automatic exposure control and organ effective modulation

PurposeTo evaluate the subjective and objective image quality of solid liver tumors as well as the radiation dose using organ effective modulation (OEM) technology for abdominopelvic computed tomography (CT). Material and methodsA total of 74 patients who underwent contrast-enhanced abdominopelvic CT between January and April 2022 were prospectively enrolled in this study. Patients were randomly assigned to two groups: the non-OEM group underwent CT scans with automatic exposure control (AEC), while the OEM group underwent CT scans with OEM. The radiation dose was compared between the two groups. Objective image quality was quantitatively assessed using image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Two experienced radiologists independently evaluated the CT images (5, best; 1, worst) by four characteristics including sharpness, contrast, noise, and diagnostic confidence. ResultsThe OEM group presented a significant reduction in volume CT dose index (CTDIvol), dose-length product (DLP), and effective dose (ED) by 11.4%, 12.2%, and 12.2%, respectively (p < 0.05). There were no significant differences between two groups concerning image noise, SNR, and CNR (p > 0.05). Expect for the left and right liver lobes in portal images, OEM was slightly higher than the non-OEM (p < 0.05). The subjective scores of two radiologists demonstrated good agreement (kappa value = 0.84). No statistically significant differences were observed in subjective grading (p > 0.05). ConclusionOEM technology can effectively reduce the radiation dose of abdominopelvic-enhanced CT without affecting the subjective and objective image quality of solid liver tumors.

Task-based assessment of digital mammography microcalcification detection with deep learning denoising algorithmss using in silico and physical phantom studies.

Recent research suggests that image quality degradation with reduced radiation exposure in mammography can be mitigated by postprocessing mammograms with denoising algorithms based on convolutional neural networks. Breast microcalcifications, along with extended soft-tissue lesions, are the primary breast cancer biomarkers in a clinical x-ray examination, with the former being more sensitive to quantum noise. We test one such publicly available denoising method to observe if an improvement in detection of small microcalcifications can be achieved when deep learning-based denoising is applied to half-dose phantom scans. An existing denoiser model (that was previously trained on clinical data) was applied to mammograms of an anthropomorphic physical phantom with hydroxyapatite microcalcifications. In addition, another model trained and tested using all synthetic (Monte Carlo) data was applied to a similar digital compressed breast phantom. Human reader studies were conducted to assess and compare image quality in a set of binary signal detection 4-AFC experiments, with proportion of correct responses used as a performance metric. In both physical phantom/clinical system and simulation studies, we saw no apparent improvement in small microcalcification signal detection in denoised half-dose mammograms. However, in a Monte Carlo study, we observed a noticeable jump in 4-AFC scores, when readers analyzed denoised half-dose images processed by the neural network trained on a dataset composed of 50% signal-present (SP) and 50% signal-absent regions of interest (ROIs). Our findings conjecture that deep-learning denoising algorithms may benefit from enriching training datasets with SP ROIs, at least in cases with clusters of 5 to 10 microcalcifications, each of size .

Dual-layer spectral computed tomography aortography using a seventy-five-percent-reduced iodine dose protocol and multiparameter spectral imaging: comparison with conventional computed tomography imaging.

Computed tomography angiography (CTA) is the recommended diagnostic and follow-up imaging modality for acute aortic dissection (AD). However, the high-contrast medium burden associated with repeated CT aortography follow-ups remains a significant concern. This prospective study aimed to assess whether an ultra-low contrast dose (75% cutoff) aortic CTA protocol on dual-layer spectral CT could achieve comparable image quality with the full dose protocol. We also investigated the image quality of the virtual noncontrast (VNC) images derived from the ultra-low dose protocol. This study included 37 consecutive patients who were referred to aortic CTA from May 2022 to August 2022. The enrolled patients underwent full-dose contrast CTA and ultra-low dose (reduced to 25% of conventional) contrast CTA on dual-layer spectral CT in 1 day. Virtual monochromatic images (VMIs) were reconstructed with 40 and 70 keV. The VNC images were reconstructed for both protocols. Objective image quality evaluation, recorded as signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs), was compared between the groups using 1-way analysis of variance and post hoc analysis with Bonferroni correction. Subjective image quality was also compared between the groups. Finally, VNC images derived from the low-dose (VNClow) and full-dose (VNCfull) protocols were compared to the true noncontrast (TNC) images. Neither CNR nor SNR was lower for the 40-keV images reconstructed from the ultra-low dose group compared to the conventional images. Both were significantly higher than those of the 70-keV images. Regarding subjective image quality, vessel enhancement was not significantly different between the 40-keV VMI and full-dose images [ascending aorta (AAO): 4.37±0.46 vs. 4.57±0.48, P=0.096; brachiocephalic arteries: 4.34±0.45 vs. 4.51±0.49, P=0.152; abdominal aortic side branch: 4.42±0.48 vs. 4.51±0.49, P=0.480]. The VNClow images were similar to the TNC images but significantly different from the VNCfull images (P<0.001). Ultra-low contrast aortic CTA with a 75%-reduced iodine dose using dual-layer spectral CT and the derived VNC achieved image quality comparable to that of conventional CTA and TNC images.

Evaluation of simultaneous multi-slice acquisition with advanced processing for free-breathing diffusion-weighted imaging in patients with liver metastasis

ObjectivesDiffusion-weighted imaging (DWI) with simultaneous multi-slice (SMS) acquisition and advanced processing can accelerate acquisition time and improve MR image quality. This study evaluated the image quality and apparent diffusion coefficient (ADC) measurements of free-breathing DWI acquired from patients with liver metastases using a prototype SMS-DWI acquisition (with/without an advanced processing option) and conventional DWI.MethodsFour DWI schemes were compared in a pilot 5-patient cohort; three DWI schemes were further assessed in a 24-patient cohort. Two readers scored image quality of all b-value images and ADC maps across the three methods. ADC measurements were performed, for all three methods, in left and right liver parenchyma, spleen, and liver metastases. The Friedman non-parametric test (post-hoc Wilcoxon test with Bonferroni correction) was used to compare image quality scoring; t-test was used for ADC comparisons.ResultsSMS-DWI was faster (by 24%) than conventional DWI. Both readers scored the SMS-DWI with advanced processing as having the best image quality for highest b-value images (b750) and ADC maps; Cohen’s kappa inter-reader agreement was 0.6 for b750 image and 0.56 for ADC maps. The prototype SMS-DWI sequence with advanced processing allowed a better visualization of the left lobe of the liver. ADC measured in liver parenchyma, spleen, and liver metastases using the SMS-DWI with advanced processing option showed lower values than those derived from the SMS-DWI method alone (t-test, p < 0.0001; p < 0.0001; p = 0.002).ConclusionsFree-breathing SMS-DWI with advanced processing was faster and demonstrated better image quality versus a conventional DWI protocol in liver patients.Clinical relevance statementFree-breathing simultaneous multi-slice- diffusion-weighted imaging (DWI) with advanced processing was faster and demonstrated better image quality versus a conventional DWI protocol in liver patients.Key Points• Diffusion-weighted imaging (DWI) with simultaneous multi-slice (SMS) can accelerate acquisition time and improve image quality.• Apparent diffusion coefficients (ADC) measured in liver parenchyma, spleen, and liver metastases using the simultaneous multi-slice DWI with advanced processing were significantly lower than those derived from the simultaneous multi-slice DWI method alone.• Simultaneous multi-slice DWI sequence with inline advanced processing was faster and demonstrated better image quality in liver patients.

Comparison of double-phase hologram and binary amplitude encoding: holographic projection andvortex beam generation.

Utilizing computer-generated holograms is a promising technique because these holograms can theoretically generate arbitrary waves with high light efficiency. In phase-only spatial light modulators, encoding complex amplitudes into phase-only holograms is a significant issue, and double-phase holograms have been a popular encoding technique. However, they reduce the light efficiency. In this study, our complex amplitude encoding, called binary amplitude encoding (BAE), and conventional methods including double-phase hologram, iterative algorithm, and error diffusion methods were compared in terms of the fidelity of reproduced light waves and light efficiency, considering the applications of lensless zoomable holographic projection and vortex beam generation. This study also proposes a noise reduction method for BAE holograms that is effective when the holograms have different aspect ratios. BAE is a non-iterative method, which allows holograms to be obtained more than 2 orders of magnitude faster than iterative holograms; BAE has about 3 times higher light efficiency with comparable image quality compared to double-phase holograms.

Hepatobiliary phase imaging in cirrhotic patients using compressed sensing and controlled aliasing in parallel imaging results in higher acceleration.

We aimed to compare the image quality and focal lesion detection ability of hepatobiliary phase (HBP) images obtained using compressed sensing (CS) and controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) in patients with liver cirrhosis. We retrospectively included 244 gadoxetic acid-enhanced liver MRI from 244 patients with cirrhosis obtained by two HBP images using CS and CAIPIRINHA from July 2020 to December 2020. The optimized resolution and scan time for CS-HBP and CAIPIRINHA-HBP were 0.9 × 0.9 × 1.5 mm3 and 15s and 1.3 × 1.3 × 3 mm3 and 16s, respectively. We compared the image quality between the two sets of images in 244 patients and focal lesion (n = 294) analyses for 112 patients. CS-HBP showed comparable overall image quality (3.7 ± 0.9 vs. 3.6 ± 0.8, p = 0.680), superior liver edge sharpness (3.9 ± 0.6 vs. 3.6 ± 0.5, p < 0.001), and fewer respiratory motion artifacts (4.0 ± 0.7 vs. 3.8 ± 0.5, p < 0.001), but higher non-respiratory artifacts (3.4 ± 0.7 vs. 3.6 ± 0.6, p < 0.001) and subjective image noise (3.5 ± 0.8 vs. 3.6 ± 0.7, p = 0.014) than CAIPIRINHA-HBP. CS-HBP showed a higher signal-to-noise ratio in the liver than CAIPIRINHA-HBP (20.9 ± 9.0 vs. 18.9 ± 7.1, p = 0.008). The pooled sensitivity, specificity, and AUC were 90.0%, 77.5%, and 0.84 for CS-HBP and 73.5%, 82.4%, and 0.78 for CAIPIRINHA-HBP, respectively. CS-HBP showed better focal lesion detection ability, comparable overall image quality, and fewer respiratory motion artifacts, but higher non-respiratory artifacts and noise compared to CAIPIRINHA-HBP. Thus, CS-HBP could be recommended for liver MRI in patients with cirrhosis to improve diagnostic performance. Thin-slice CS-HBP may be useful for detecting sub-centimeter hepatocellular carcinoma in cirrhotic patients with Child-Pugh classification A while maintaining comparable subjective image quality. • Compared with controlled aliasing in parallel imaging results in higher acceleration, compressed sensing hepatobiliary phase yielded thinner slices and shorter scan time at a higher accelerating factor. • Compressed sensing hepatobiliary phase showed comparable overall image quality, superior liver edge sharpness, and fewer respiratory motion artifacts, but higher non-respiratory artifacts and subjective image noise than controlled aliasing in parallel imaging results in higher acceleration-hepatobiliary phase. • Compressed sensing hepatobiliary phase can detect sub-centimeter hepatocellular carcinoma in cirrhotic patients with Child-Pugh classification A.

A frequency-domain model-based reconstruction method for transcranial photoacoustic imaging: A 2D numerical investigation

Phase aberration caused by the skull is a major barrier to achieving high quality photoacoustic images of human and non-human primates’ brains. To address this issue, time-reversal methods have been used but they are computationally demanding and slow due to relying on solving the full-wave equation. The proposed approach is based on model-based image reconstruction in the frequency-domain to achieve near real-time image reconstruction. The relationship between an imaging region and transducer array elements can be mathematically described as a model matrix and the image reconstruction can be performed by pseudo-inverse of the model matrix. The model matrix is numerically calculated due to the lack of analytical solutions for transcranial ultrasound. However, this calculation only needs to be performed once for a given experimental setup and the same acoustic medium, and is an offline process not affecting the actual image reconstruction time. This non-iterative mode-based method demonstrates a substantial improvement in image reconstruction time, being approximately 18 times faster than the time-reversal method, all while maintaining comparable image quality.

Evaluation of Image Quality for High Heart Rates for Coronary Computed Tomographic Angiography with Advancement in CT Technology: The CONVERGE Registry.

This study aims to evaluate image quality in patients with heart rates above or equal to 70 beats per minute (bpm), performed on a 16 cm scanner (256-slice General Electric Revolution) in comparison to a CT scanner with only 4 cm of coverage (64 slice Volume CT). Recent advancements in image acquisition, such as whole-heart coverage in a single rotation and post-processing methods in coronary computed tomographic angiography (CCTA), include motion-correction algorithms, such as SnapShot Freeze (SSF), which improve temporal resolution and allow for the assessment of coronary artery disease (CAD) with lower motion scores and better image qualities. Studies from the comprehensive evaluation of high temporal- and spatial-resolution cardiac CT using a wide coverage system (CONVERGE) registry (a multicenter registry at four centers) have shown the 16 cm CT scanner having a better image quality in comparison to the 4 cm scanner. However, these studies failed to include patients with undesirable or high heart rates due to well-documented poor image acquisition on prior generations of CCTA scanners. A prospective, observational, multicenter cohort study comparing image quality, quantitively and qualitatively, on scans performed on a 16 cm CCTA in comparison to a cohort of images captured on a 4 cm CCTA at four centers. Participants were recruited based on broad inclusion criteria, and each patient in the 16 cm CCTA arm of the study received a CCTA scan using a 256-slice, whole-heart, single-beat scanner. These patients were then matched by age, gender, and heart rate to patients who underwent CCTA scans on a 4 cm CT scanner. Image quality was graded based on the signal-to-noise ratio, contrast-to-noise ratio, and on a Likert scale of 0-4: 0, very poor-4, excellent. 104 patients were evaluated for this study. The mean heart rate was 75 ± 7 in the 4 cm scanner and 75 ± 7 in the 16 cm one (p = 0.426). The signal-to-noise and contrast-to-noise ratios were higher in the 16 cm scanner (p = 0.0001). In addition, more scans were evaluated as having an excellent quality on the 16 cm scanner than on the 4 cm scanner (p < 0.0001) based on a 4-point Likert scale. The 16 cm scanner has a superior image quality for fast heart rates compared to the 4 cm scanner. This study shows that there is a significantly higher frequency of excellent and good studies showing better contrast-to-noise and signal-to-noise ratios with the 16 cm scanner compared to the 4 cm scanner.

75% radiation dose reduction using deep learning reconstruction on low-dose chest CT

ObjectiveFew studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low dose (QLD) reconstructed with vendor-agnostic deep-learning image reconstruction (DLIR) and conventional low-dose (LD) CT reconstructed with iterative reconstruction (IR).Materials and methodsWe retrospectively collected 100 patients (median age, 61 years [IQR, 53–70 years]) who received LDCT using a dual-source scanner, where total radiation was split into a 1:3 ratio. QLD CT was generated using a quarter dose and reconstructed with DLIR (QLD-DLIR), while LDCT images were generated using a full dose and reconstructed with IR (LD-IR). Three thoracic radiologists reviewed subjective noise, spatial resolution, and overall image quality, and image noise was measured in five areas. The radiologists were also asked to detect all Lung-RADS category 3 or 4 nodules, and their performance was evaluated using area under the jackknife free-response receiver operating characteristic curve (AUFROC).ResultsThe median effective dose was 0.16 (IQR, 0.14–0.18) mSv for QLD CT and 0.65 (IQR, 0.57–0.71) mSv for LDCT. The radiologists’ evaluations showed no significant differences in subjective noise (QLD-DLIR vs. LD-IR, lung-window setting; 3.23 ± 0.19 vs. 3.27 ± 0.22; P = .11), spatial resolution (3.14 ± 0.28 vs. 3.16 ± 0.27; P = .12), and overall image quality (3.14 ± 0.21 vs. 3.17 ± 0.17; P = .15). QLD-DLIR demonstrated lower measured noise than LD-IR in most areas (P < .001 for all). No significant difference was found between QLD-DLIR and LD-IR for the sensitivity (76.4% vs. 72.2%; P = .35) or the AUFROCs (0.77 vs. 0.78; P = .68) in detecting Lung-RADS category 3 or 4 nodules. Under a noninferiority limit of -0.1, QLD-DLIR showed noninferior detection performance (95% CI for AUFROC difference, -0.04 to 0.06).ConclusionQLD-DLIR images showed comparable image quality and noninferior nodule detectability relative to LD-IR images.

Propagation-based phase-contrast imaging of the breast: image quality and the effect of X-ray energy and radiation dose.

Propagation-based phase-contrast computed tomography (PB-CT) is a new imaging technique that exploits refractive and absorption properties of X-rays to enhance soft tissue contrast and improve image quality. This study compares image quality of PB-CT and absorption-based CT (AB-CT) for breast imaging while exploring X-ray energy and radiation dose. Thirty-nine mastectomy samples were scanned at energy levels of 28-34keV using a flat panel detector at radiation dose levels of 4mGy and 2mGy. Image quality was assessed using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), spatial resolution (res) and visibility (vis). Statistical analysis was performed to compare PB-CT images against their corresponding AB-CT images scanned at 32keV and 4mGy. The PB-CT images at 4mGy, across nearly all energy levels, demonstrated superior image quality than AB-CT images at the same dose. At some energy levels, the 2mGy PB-CT images also showed better image quality in terms of CNR/Res and vis compared to the 4mGy AB-CT images. At both investigated doses, SNR and SNR/res were found to have a statistically significant difference across all energy levels. The difference in vis was statistically significant at some energy levels. This study demonstrates superior image quality of PB-CT over AB-CT, with X-ray energy playing a crucial role in determining image quality parameters. Our findings reveal that standard dose PB-CT outperforms standard dose AB-CT across all image quality metrics. Additionally, we demonstrate that low dose PB-CT can produce superior images compared to standard dose AB-CT in terms of CNR/Res and vis.

Coronary Stent Evaluation by CTA: Image Quality Comparison Between Super-Resolution Deep-Learning Reconstruction and Other Reconstruction Algorithms.

Background: A super-resolution deep-learning based reconstruction (SR-DLR) algorithm may provide better image sharpness than earlier reconstruction algorithms and thereby improve coronary stent assessment on coronary CTA. Objective: To compare SR-DLR and other reconstruction algorithms in terms of image quality measures related to coronary stent evaluation in patients undergoing coronary CTA. Methods: This retrospective study included patients with at least one coronary artery stent who underwent coronary CTA between January 2020 and December 2020. Examinations were performed using a 320-row normal-resolution scanner and reconstructed with hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), normal-resolution deep-learning reconstruction (NR-DLR), and SR-DLR algorithms. Quantitative image quality measures were determined. Two radiologists independently reviewed images to rank the four reconstructions (1=worst reconstruction, 4=best reconstruction) for qualitative measures, and to score diagnostic confidence (5-point scale; score≥3 indicating an assessable stent). Assessability rate was calculated for stents with diameter ≤3.0 mm. Results: The sample included 24 patients (18 men, 6 women; mean age, 72.8±9.8 years), with 51 stents. SR-DLR, in comparison with the other reconstructions, yielded lower stent-related blooming artifacts (median, 40.3 vs 53.4-58.2), stent-induced attenuation increase ratio (0.17 vs 0.27-0.31), and quantitative image noise (18.1 vs 20.9-30.4 HU), and higher in-stent lumen diameter (2.41 vs. 1.74-1.94 mm), stent strut sharpness (327 vs 147-210 ΔHU/mm), and CNR (30.0 vs 16.0-25.6), (all p<.001). For both observers, all ranked measures (image sharpness; image noise; noise texture; delineation of stent strut, in-stent lumen, coronary artery wall, and calcified plaque surrounding the stent) and diagnostic confidence showed a higher score for SR-DLR (median, 4.0 for all features) than for the other reconstructions (range, 1.0-3.0) (all p<.001). Assessability rate for stents with diameter ≤3.0 mm (n=37) was higher for SR-DLR (observer 1: 86.5%; observer 2: 89.2%) than for HIR (35.1%, 43.2%), MBIR (59.5%, 62.2%), or NR-DLR (62.2%, 64.9%) (all p<.05). Conclusion: SR-DLR yielded improved delineation of the stent strut and in-stent lumen, with better image sharpness and less image noise and blooming artifacts, in comparison with HIR, MBIR, and NR-DLR. Clinical Impact: SR-DLR may facilitate coronary stent assessment on a 320-row normal-resolution scanner, particularly for small-diameter stents.

High-pitch CT pulmonary angiography (CTPA) with ultra-low contrast medium volume for the detection of pulmonary embolism: a comparison with standard CTPA

ObjectiveTo investigate the feasibility and image quality of high-pitch CT pulmonary angiography (CTPA) with reduced iodine volume in normal weight patients.MethodsIn total, 81 normal weight patients undergoing CTPA for suspected pulmonary arterial embolism were retrospectively included: 41 in high-pitch mode with 20 mL of contrast medium (CM); and 40 with normal pitch and 50 mL of CM. Subjective image quality was assessed and rated on a 3-point scale. For objective image quality, attenuation and noise values were measured in all pulmonary arteries from the trunk to segmental level. Contrast-to-noise ratio (CNR) was calculated. Radiation dose estimations were recorded.ResultsThere were no statistically significant differences in patient and scan demographics between high-pitch and standard CTPA. Subjective image quality was rated good to excellent in over 90% of all exams with no significant group differences (p = 0.32). Median contrast opacification was lower in high-pitch CTPA (283.18 [216.06–368.67] HU, 386.81 [320.57–526.12] HU; p = 0.0001). CNR reached a minimum of eight in all segmented arteries, but was lower in high-pitch CTPA (8.79 [5.82–12.42], 11.01 [9.19–17.90]; p = 0.005). Median effective dose of high-pitch CTPA was lower (1.04 [0.72–1.27] mSv/mGy·cm; 1.49 [1.07–2.05] mSv/mGy·cm; p < 0.0001).ConclusionHigh-pitch CTPA using ultra-low contrast volume (20 mL) rendered diagnostic images for the detection of pulmonary arterial embolism in most instances. Compared to standard CTPA, the high-pitch CTPA exams with drastically reduced contrast medium volume had also concomitantly reduced radiation exposure. However, objective image quality of high-pitch CTPA was worse, though likely still within acceptable limits for confident diagnosis.Clinical relevanceThis study provides valuable insights on the performance of a high-pitch dual-source CTPA protocol, offering potential benefits in reducing contrast medium and radiation dose while maintaining sufficient image quality for accurate diagnosis in patients suspected of pulmonary embolism.Key Points• High-pitch CT pulmonary angiography (CTPA) with ultra-low volume of contrast medium and reduced radiation dose renders diagnostic examinations with comparable subjective image quality to standard CTPA in most patients.• Objective image quality of high-pitch CTPA is reduced compared to standard CTPA, but contrast opacification and contrast-to-noise ratio remain above diagnostic thresholds.• Challenges of high-pitch CTPA may potentially be encountered in patients with severe heart failure or when performing a Valsalva maneuver during the examination.

Deep Learning-Based Versus Iterative Image Reconstruction for Unenhanced Brain CT: A Quantitative Comparison of Image Quality.

This exploratory retrospective study aims to quantitatively compare the image quality of unenhanced brain computed tomography (CT) reconstructed with an iterative (AIDR-3D) and a deep learning-based (AiCE) reconstruction algorithm. After a preliminary phantom study, AIDR-3D and AiCE reconstructions (0.5 mm thickness) of 100 consecutive brain CTs acquired in the emergency setting on the same 320-detector row CT scanner were retrospectively analyzed, calculating image noise reduction attributable to the AiCE algorithm, artifact indexes in the posterior cranial fossa, and contrast-to-noise ratios (CNRs) at the cortical and thalamic levels. In the phantom study, the spatial resolution of the two datasets proved to be comparable; conversely, AIDR-3D reconstructions showed a broader noise pattern. In the human study, median image noise was lower with AiCE compared to AIDR-3D (4.7 vs. 5.3, p < 0.001, median 19.6% noise reduction), whereas AIDR-3D yielded a lower artifact index than AiCE (7.5 vs. 8.4, p < 0.001). AiCE also showed higher median CNRs at the cortical (2.5 vs. 1.8, p < 0.001) and thalamic levels (2.8 vs. 1.7, p < 0.001). These results highlight how image quality improvements granted by deep learning-based (AiCE) and iterative (AIDR-3D) image reconstruction algorithms vary according to different brain areas.

Bayesian Reconstruction Algorithms for Low-Dose Computed Tomography Are Not Yet Suitable in Clinical Context.

Computed tomography (CT) is a widely used examination technique that usually requires a compromise between image quality and radiation exposure. Reconstruction algorithms aim to reduce radiation exposure while maintaining comparable image quality. Recently, unsupervised deep learning methods have been proposed for this purpose. In this study, a promising sparse-view reconstruction method (posterior temperature optimized Bayesian inverse model; POTOBIM) is tested for its clinical applicability. For this study, 17 whole-body CTs of deceased were performed. In addition to POTOBIM, reconstruction was performed using filtered back projection (FBP). An evaluation was conducted by simulating sinograms and comparing the reconstruction with the original CT slice for each case. A quantitative analysis was performed using peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). The quality was assessed visually using a modified Ludewig's scale. In the qualitative evaluation, POTOBIM was rated worse than the reference images in most cases. A partially equivalent image quality could only be achieved with 80 projections per rotation. Quantitatively, POTOBIM does not seem to benefit from more than 60 projections. Although deep learning methods seem suitable to produce better image quality, the investigated algorithm (POTOBIM) is not yet suitable for clinical routine.