Increase In Contrast-to-noise Ratio Research Articles

Contrast-To-Noise Ratio Differences between Iodine and Calcium on Virtual Monochromatic Images (VMI) In Dual Energy Computed Tomography (DECT)

Contrast-to-noise ratio (CNR) is an important parameter in evaluating the quality of virtual monochromatic images (VMI), especially for distinguishing materials with different atomic numbers. This study aims to evaluate the CNR difference between iodine and calcium on VMI images in dual energy computed tomography (DECT) using an in-house phantom. The in-house phantom had ten holes filled with iodine (with concentrations of 5, 7.5, 10, and 15 mg/ml) and calcium (with concentrations of 200, 300, 500, and 600 mg/ml). The in-house phantom was scanned using a GE Revolution DECT type Ultrafast kV Switching. The input parameters were tube voltage of 80/140 kV, tube current of 370 mA, rotation time of 0.5 s, slice thickness of 5 mm, field of view of 25 cm. Projection data were reconstructed to obtain VMI images (with energies of 50, 60, 70, 80, 90, and 100 keV). The results showed that increasing concentrations of iodine and calcium lead to in CNR. At low energies (50-70 keV), the CNR of calcium is higher than that of iodine, while at high energies (80-100 keV), the difference in CNR is more pronounced. In conclusion, calcium showed a more significant increase in CNR compared to iodine, particularly at low energies and high concentrations, with the difference becoming more pronounced at high energies.

Characterization of kilovoltage x-ray image guidance system with a novel post-processing algorithm on a new slip ring-mounted radiotherapy system.

This study evaluates the performance of a kilovoltage x-ray image-guidance system equipped with a novel post-processing optimization algorithm on the newly introduced TAICHI linear accelerator (Linac). A comparative study involving image quality tests and radiation dose measurements was conducted across six scanning protocols of the kV-cone beam computed tomography (CBCT) system on the TAICHI Linac. The performance assessment utilized the conventional Feldkamp-Davis-Kress (FDK) algorithm and a novel Non-Local Means denoising and adaptive scattering correction (NLM-ASC) algorithm. Image quality metrics, including spatial resolution, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR), were evaluated using a Catphan 604 phantom. Radiation doses for low-dose and standard protocols were measured using a computed tomography dose index (CTDI) phantom, with comparative measurements from the Halcyon Linac's iterative CBCT (iCBCT). The NLM-ASC algorithm significantly improved image quality, achieving a 300%-1000% increase in CNR and SNR over the FDK-only images and it also showed a 100%-200% improvement over the iCBCT images from Halcyon's head protocol. The optimized low-dose protocols yielded higher image quality than the standard FDK protocols, indicating potential for reduced radiation exposure. Clinical implementation confirmed the TAICHI system's utility for precise and adaptive radiotherapy. The kV-IGRT system on the TAICHI Linac, with its novel post-processing algorithm, demonstrated superior image quality suitable for routine clinical use, effectively reducing image noise without compromising other quality metrics.

Diffusion MRI in prostate cancer with ultra-strong whole-body gradients.

Diffusion-weighted MRI (dMRI) is universally recommended for the detection and classification of prostate cancer (PCa), with PI-RADS recommendations to acquire b-values of ≥1.4ms/μm2. However, clinical dMRI suffers from a low signal-to-noise ratio (SNR) as the consequence of prolonged echo times (TEs) attributable to the limited gradient power in the range of 40-80 mT/m. To overcome this, MRI systems with strong gradients have been designed but so far have mainly been applied in the brain. The aim of this work was to assess the feasibility, data quality, SNR and contrast-to-noise ratio (CNR) of measurements in PCa with a 300 mT/m whole-body system. A cohort of men without and with diagnosed PCa were imaged on a research-only 3T Connectom Siemens MRI system equipped with a gradient amplitude of 300 mT/m. dMRI at high b-values were acquired using high gradient amplitudes and compared with gradient capabilities mimicking clinical systems. Data artefacts typically amplified with stronger gradients were assessed and their correction evaluated. The SNR gains and lesion-to-healthy tissue CNR were statistically tested investigating the effect of protocol and b-value. The diagnostic quality of the images for different dMRI protocols was assessed by an experienced radiologist using a 5-point Likert scale and an adapted PI-QUAL scoring system. The strong gradients for prostate dMRI allowed a significant gain in SNR per unit time compared with clinical gradients. Furthermore, a 1.6-2.1-fold increase in CNR was observed. Despite the more pronounced artefacts typically associated with strong gradients, a satisfactory correction could be achieved. Smoother and less biased parameter maps were obtained with protocols at shorter TEs. The results of this study show that dMRI in PCa with a whole-body 300-mT/m scanner is feasible without a report of physiological effects, SNR and CNR can be improved compared with lower gradient strengths, and artefacts do not negate the benefits of strong gradients and can be ameliorated. This assessment provides the first essential step towards unveiling the full potential of cutting-edge scanners, now increasingly becoming available, to advance early detection and diagnostic precision.

Deep Learning Reconstruction of Prospectively Accelerated MRI of the Pancreas: Clinical Evaluation of Shortened Breath-Hold Examinations With Dixon Fat Suppression.

Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerated MRI of the upper abdomen in the context of pancreatic pathologies are lacking. In a clinical setting, the purpose of this study is to investigate the performance of a novel DL-based reconstruction algorithm in T1-weighted volumetric interpolated breath-hold examinations with partial Fourier sampling and Dixon fat suppression (hereafter, VIBE-DixonDL). The objective is to analyze its impact on acquisition time, image sharpness and quality, diagnostic confidence, pancreatic lesion conspicuity, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). This prospective single-center study included participants with various pancreatic pathologies who gave written consent from January 2023 to September 2023. During the same session, each participant underwent 2 MRI acquisitions using a 1.5 T scanner: conventional precontrast and postcontrast T1-weighted VIBE acquisitions with Dixon fat suppression (VIBE-Dixon, reference standard) using 4-fold parallel imaging acceleration and 6-fold accelerated VIBE-Dixon acquisitions with partial Fourier sampling utilizing a novel DL reconstruction tailored to the acquisition. A qualitative image analysis was performed by 4 readers. Acquisition time, image sharpness, overall image quality, image noise and artifacts, diagnostic confidence, as well as pancreatic lesion conspicuity and size were compared. Furthermore, a quantitative analysis of SNR and CNR was performed. Thirty-two participants were evaluated (mean age ± SD, 62 ± 19 years; 20 men). The VIBE-DixonDL method enabled up to 52% reduction in average breath-hold time (7 seconds for VIBE-DixonDL vs 15 seconds for VIBE-Dixon, P < 0.001). A significant improvement of image sharpness, overall image quality, diagnostic confidence, and pancreatic lesion conspicuity was observed in the images recorded using VIBE-DixonDL (P < 0.001). Furthermore, a significant reduction of image noise and motion artifacts was noted in the images recorded using the VIBE-DixonDL technique (P < 0.001). In addition, for all readers, there was no evidence of a difference in lesion size measurement between VIBE-Dixon and VIBE-DixonDL. Interreader agreement between VIBE-Dixon and VIBE-DixonDL regarding lesion size was excellent (intraclass correlation coefficient, >90). Finally, a statistically significant increase of pancreatic SNR in VIBE-DIXONDL was observed in both the precontrast (P = 0.025) and postcontrast images (P < 0.001). Also, an increase of splenic SNR in VIBE-DIXONDL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images (P = 0.34 and P = 0.003, respectively). Similarly, an increase of pancreas CNR in VIBE-DIXONDL was observed in both the precontrast and postcontrast images, but only reaching statistical significance in the postcontrast images (P = 0.557 and P = 0.026, respectively). The prospectively accelerated, DL-enhanced VIBE with Dixon fat suppression was clinically feasible. It enabled a 52% reduction in breath-hold time and provided superior image quality, diagnostic confidence, and pancreatic lesion conspicuity. This technique might be especially useful for patients with limited breath-hold capacity.

Thrombus discrimination with electron density: potential implications for non-contrast computed tomography imaging.

The potential clinical usefulness of electron density (ED) imaging, that can be directly estimated using dual-layer spectral computed tomography (CT), has been poorly investigated. We explored whether ED imaging might improve thrombus identification compared to conventional imaging in vitro. We evaluated mechanical thrombectomy material obtained from patients with acute ischemic stroke (AIS) treated in a tertiary level stroke center and immediately fixed in 10% neutral buffered formalin and stored in polystyrene test tubes. The test tubes were immersed in a bucket of water for evaluation by spectral CT, along with scattered control tubes. All images were obtained using a dual-layer detector CT scanner. Each tube was assessed using multiparametric side-by-side view of conventional CT (120 kVp), low monoenergetic imaging (40 keV), and ED images. Fifty-eight polystyrene tubes were analyzed, comprising 52 tubes with thrombectomy material of at least 1 mm2 size obtained from 52 AIS patients, and six control tubes filled with formalin. ED imaging identified accurately the presence of material in all tubes, whereas 2 (3%) of the tubes containing thrombus were not identified by conventional CT, leading to a very good agreement between observers for the presence of material using conventional CT and ED imaging (kappa =0.84, P<0.001). Using ED imaging, thrombus material showed a mean density of 108.8±2.9 percent ED relative to water (%EDW), water had a mean density of 100.0±0.3 %EDW, and formalin a mean density of 103.5±1.2 %EDW. Compared to conventional imaging and 40 keV monoenergetic, ED imaging had a significantly higher signal-to-noise ratio (conventional 10.4±7.0, vs. 40 keV 11.5±8.4, vs. ED 490.0±304.5, P<0.001) and contrast-to-noise ratio (CNR) (conventional 4.3±4.3, vs. 40 keV 5.7±11.2, vs. ED 37.8±29.1, P<0.001). In this in-vitro study, we demonstrated improved visualization of thrombus with ED imaging compared to conventional imaging and low monoenergetic imaging, with a significant increase in CNR.

In-vitro Detection of Intramammary-like Macrocalcifications Using Susceptibility-weighted MR Imaging Techniques at 1.5T.

The aim of our study was to investigate the technical accuracy of susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM) created to detect intramammary-like calcifications depending on different TEs, volume, and type of calcification samples at 1.5T. Jello-embedded particles of blackboard chalk and ostrich eggshell ranging in size from 4 to 25 mm2 were used to simulate intramammary calcifications after testing different base substances and calcifications for their suitability to be used in breast phantoms. Breast phantoms were systematically examined using CT and an optimized 3D multi-echo gradient echo pulse sequence with following parameters: TR/TE, 22/1.88-15.52 ms in 1.24 ms increments; reconstructed voxel, 0.5 × 0.5 × 1.1 mm3; receiver bandwidth, 1120 Hz/Px; flip angle, 15°; integrated parallel imaging technique with a GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA) factor of 2/24; and a total acquisition time of 3:00 min. A qualitative evaluation of the dependence of the visualization of calcification samples on volume and TE value was followed by a calculation of the SNR, the contrast-to-noise ratio (CNR) and the creation of SWI and QSM in the sense of a (semi)-quantitative analysis of the images. Jello proved to be a suitable base substance for preparing breast phantoms for SW MRI. Blackboard chalk and ostrich eggshell proved to be suitable for mimicking intramammary-like calcifications. The decrease in the median SNR of the blackboard chalk samples was significantly higher than the corresponding value of the ostrich eggshell samples over the entire TE range (47.5 to 17.0 vs. 16.0 to 6.56, P < 0.0001). The increase in the median CNR of the blackboard chalk samples was significantly higher than the corresponding value of the ostrich eggshell samples over the entire TE range (2.46 to 35.0 vs. 20.2 to 36.8, P = 0.007). With increasing TE value, the signal void volume of the calcification particle increases in the magnitude images as well as in SWI and QSM. Due to the blooming effect, the median gradients of the TE-based changes in signal void volumes were higher in SWI than in magnitude images and in QSM, regardless of the type of calcification particle examined. The maximum magnetic susceptibility of ostrich eggshell samples varied in a TE range of 1.88 to 15.52 ms from -7.2 to -2.51 ppm and that of blackboard chalk from -2.0 to -1.7 ppm. Compared to the manually measured volumes of the calcification particles, both MR-based measurements and CT examinations overestimated the actual sample size. The (non)-significant overestimation in the MRI-data is dependent on the set TE. The CT-based hyperdense volumes were overestimated compared to the corresponding manually measured sample volumes in a range of 109.8%-315.2% for ostrich eggshell samples (P = 0.016) and in a range of 39.9%-156.4% for blackboard chalk samples (P = 0.69). Our systematic in-vitro investigation of magnitude images, SWI, and QSM revealed that various set TE values, different volumes, and compositions of calcifications have a significant impact on visualizing intramammary(-like) calcifications.

Impact of uptake time on image quality of [68 Ga]Ga-PSMA-11 PET/CT.

With the introduction of prostate specific membrane antigen (PSMA) PET/CT, the detection rate of prostate cancer metastases has improved significantly, both for primary staging and for biochemical recurrence. EANM/SNMMI guidelines recommend a 60min time interval between [68 Ga]Ga-PSMA administration and acquisition. This study evaluates the possibility of a shorter time interval by investigating the dynamic change in image quality measures. We retrospectively analyzed 10 consecutive prostate cancer patients who underwent a dynamic whole body [68 Ga]Ga-PSMA-11 PET/CT of 75min from skull vertex to mid-thigh using Siemens FlowMotion. PET images were acquired directly after injection of 1.5MBq/kg [68 Ga]Ga-PSMA-11. Image quality measures included lesion maximum standardized uptake value corrected for lean body mass (SULmax ), tumor-to-background ratio (TBR), and contrast-to-noise ratio (CNR). Quantitative analysis of image quality in dynamic PET was performed using PMOD (version 4.2). Regions of interest (ROIs), drawn included different types of prostate lesions (primary tumor, lymph nodes, and bone metastasis), organ tissue (liver, spleen, lacrimal gland, submandibular gland, parotid gland, urinary bladder, kidneys blood pool [ascending aorta], left ventricle), bone tissue (4th lumbar vertebral body [L4]) and muscle tissue (gluteus maximus). To further investigate image quality four 10min multi-frame reconstructions with clinical parameters were made at different post-injection times (15, 30, 45, and 60min). A nuclear medicine physician performed a blinded lesion detectability evaluation on these multi-frame reconstructions for different prostate cancer lesions. Six primary prostate tumors in seven patients with prostate in situ, 13 lymph node metastases in six patients and up to 12 bone metastases in three patients were found. The different prostate lesion types (lymph nodes metastases, bone metastases, and primary prostate tumor) all show an increase in average SULmax , TBR, and CNR over time during the scan. The normalized average SULmax , TBR, and CNR of the combined prostate lesions at 15, 30, and 45min post-injection scans were all significant p<0.05 lower from the 60min post-injection [68 Ga]Ga-PSMA-11 PET/CT (9.5±4.5, 12.7±6.2, and 41.8±24.5, respectively). At patient level, the reader concluded the same regarding the presence/absence of primary prostate cancer recurrence, lymph node metastases, and/or bone metastases on all <60min post-injection [68 Ga]Ga-PSMA-11 PET/CT's in comparison to the reference scan (60min post-injection). At lesion level, all bone metastases seen on the reference scan were also seen on all <60min post-injection [68 Ga]Ga-PSMA-11 PET/CT's but there were some lymph nodes (n=2) metastases missed on the 15, 30, and 45min post-injection scans. One lymph node metastasis on both the 15 and 30min post-injection [68 Ga]Ga-PSMA-11 PET/CT's was missed and one lymph node metastasis was missed, only on the 45min post-injection [68 Ga]Ga-PSMA-11 PET/CT. Shorter post-injection times (15, 30, and 45min) compared to the recommended post-injection time of 60min are not optimal. However, the impact of a shorter time interval of 45min instead of 60min between [68 Ga]Ga-PSMA-11 administration and the start of PET/CT acquisition on both image quality (SULmax , TBR, and CNR) and lesion detection, while significant, is small.

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification

BackgroundDeep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative reconstruction (IR) algorithms for computed tomography (CT) image reconstruction. The aim of this study was to evaluate the effect of DLIR on image quality and quantification of coronary artery calcium (CAC) in comparison to FBP.MethodsOne hundred patients were consecutively enrolled. Image quality–associated variables (noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)) as well as CAC-derived parameters (Agatston score, mass, and volume) were calculated from images reconstructed by using FBP and three different strengths of DLIR (low (DLIR_L), medium (DLIR_M), and high (DLIR_H)). Patients were stratified into 4 risk categories according to the Coronary Artery Calcium - Data and Reporting System (CAC-DRS) classification: 0 Agatston score (very low risk), 1–99 Agatston score (mildly increased risk), Agatston 100–299 (moderately increased risk), and ≥ 300 Agatston score (moderately-to-severely increased risk).ResultsIn comparison to standard FBP, increasing strength of DLIR was associated with a significant and progressive decrease of image noise (p < 0.001) alongside a significant and progressive increase of both SNR and CNR (p < 0.001). The use of incremental levels of DLIR was associated with a significant decrease of Agatston CAC score and CAC volume (p < 0.001), while mass score remained unchanged when compared to FBP (p = 0.232). The underestimation of Agatston CAC led to a CAC-DRS misclassification rate of 8%.ConclusionDLIR systematically underestimates Agatston CAC score. Therefore, DLIR should be used cautiously for cardiovascular risk assessment.Key Points• In coronary artery calcium imaging, the implementation of deep learning image reconstructions improves image quality, by decreasing the level of image noise.• Deep learning image reconstructions systematically underestimate Agatston coronary artery calcium score.• Deep learning image reconstructions should be used cautiously in clinical routine to measure Agatston coronary artery calcium score for cardiovascular risk assessment.

Sub-pixel energy-weighting techniques for metallic contaminant highlighting in a pharmaceutical hard capsule using a Timepix3 CdZnTe hybrid pixel detector

The presented work describes the capabilities of a state-of-the-art spectroscopic photon-counting hybrid pixel detector for use in non-destructive testing, as a contaminant detector with potential uses in the food and pharmaceutical industries. A pharmaceutical hard capsule containing vitamin powder, contaminated with Steel (ST) and Tungsten (W) was prepared under controlled conditions. Both contaminants are distinguished from the powder by combining sub-pixel imaging with spectroscopic imaging analysis, made possible by the use of a 2 mm CdZnTe sensor coupled to a Timepix3 ASIC, operated in Time-over-Threshold and Time-of-Arrival mode. The sub-pixelization technique achieves a spatial resolution of 18.3 μm, with a maximum photon flux of 2.5× 106 photons/s· cm2. For the spectral analysis technique implemented, each energy bin image is energy-weighted, with weights optimally defined by considering the bin contrast and noise behavior, and combined to form an integrated-spectrum enhanced image with increased contaminant visibility. Contrast-to-Noise Ratio (CNR) for each contaminant type was used for performance assessment of the approach. A CNR increase of 106% above the reference unweighted-spectrum image was achieved for the ST contaminant, while the denser W contaminant showed a CNR increase of 80%. This means that the presented spectroscopic imaging technique is feasible for implementation in material visibility enhancement.

Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction

BackgroundEfforts to reduce the radiation dose have continued steadily, with new reconstruction techniques. Recently, image denoising algorithms using artificial neural networks, termed deep learning reconstruction (DLR), have been applied to CT image reconstruction to overcome the drawbacks of iterative reconstruction (IR). The purpose of our study was to compare the objective and subjective image quality of DLR and IR on pediatric abdomen and chest CT images.MethodsThis retrospective study included pediatric body CT images from February 2020 to October 2020, performed on 51 patients (34 boys and 17 girls; age 1–18 years). Non-contrast chest CT (n = 16), contrast-enhanced chest CT (n = 12), and contrast-enhanced abdomen CT (n = 23) images were included. Standard 50% adaptive statistical iterative reconstruction V (ASIR-V) images were compared to images with 100% ASIR-V and DLR at medium and high strengths. Attenuation, noise, contrast to noise ratio (CNR), and signal to noise (SNR) measurements were performed. Overall image quality, artifacts, and noise were subjectively assessed by two radiologists using a four-point scale (superior, average, suboptimal, and unacceptable). A phantom scan was performed including the dose range of the clinical images used in our study, and the noise power spectrum (NPS) was calculated. Quantitative and qualitative parameters were compared using repeated-measures analysis of variance (ANOVA) with Bonferroni correction and Wilcoxon signed-rank tests.ResultsDLR had better CNR and SNR than 50% ASIR-V in both pediatric chest and abdomen CT images. When compared with 50% ASIR-V, high strength DLR was associated with noise reduction in non-contrast chest CT (33.0%), contrast-enhanced chest CT (39.6%), and contrast-enhanced abdomen CT (38.7%) with increases in CNR at 149.1%, 105.8%, and 53.1% respectively. The subjective assessment of overall image quality and the noise was also better on DLR images (p < 0.001). However, there was no significant difference in artifacts between reconstruction methods. From NPS analysis, DLR methods showed a pattern of reducing the magnitude of noise while maintaining the texture.ConclusionCompared with 50% ASIR-V, DLR improved pediatric body CT images with significant noise reduction. However, artifacts were not improved by DLR, regardless of strength.

Frequency-dependent optimal weighting approach for megavoltage multilayer imagers

Multi-layer imaging (MLI) devices improve the detective quantum efficiency (DQE) while maintaining the spatial resolution of conventional mega-voltage (MV) x-ray detectors for applications in radiotherapy. To date, only MLIs with identical detector layers have been explored. However, it may be possible to instead use different scintillation materials in each layer to improve the final image quality. To this end, we developed and validated a method for optimally combining the individual images from each layer of MLI devices that are built with heterogeneous layers. Two configurations were modeled within the GATE Monte Carlo package by stacking different layers of a terbium doped gadolinium oxysulfide Gd2O2S:Tb (GOS) phosphor and a LKH-5 glass scintillator. Detector response was characterized in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE. Spatial frequency-dependent weighting factors were then analytically derived for each layer such that the total DQE of the summed combination image would be maximized across all spatial modes. The final image is obtained as the weighted sum of the sub-images from each layer. Optimal weighting factors that maximize the DQE were found to be the quotient of MTF and NNPS of each layer in the heterogeneous MLI detector. Results validated the improvement of the DQE across the entire frequency domain. For the LKH-5 slab configuration, DQE(0) increases between 2%–3% (absolute), while the corresponding improvement for the LKH-5 pixelated configuration was 7%. The performance of the weighting method was quantitatively evaluated with respect to spatial resolution, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated planar images of phantoms at 2.5 and 6 MV. The line pair phantom acquisition exhibited a twofold increase in CNR and SNR, however MTF was degraded at spatial frequencies greater than 0.2 lp mm−1. For the Las Vegas phantom, the weighting improved the CNR by around 30% depending on the contrast region while the SNR values are higher by a factor of 2.5. These results indicate that the imaging performance of MLI systems can be enhanced using the proposed frequency-dependent weighting scheme. The CNR and SNR of the weighted combined image are improved across all spatial scales independent of the detector combination or photon beam energy.

Image Quality Assessment of Low-Dose CT using Hybrid Iterative Reconstruction

Background: X-ray computed tomography is the first imaging technology that supports accurate nondestructive interior image reconstruction of an object from sufficient projection data. Low-dose computed tomography (LDCT) has been considered to relieve the harm to patients caused by X-ray radiation. However, LDCT images can be degraded by quantum noise and streak artifacts. Methods: The objective of the authors’ study is to evaluate the optimal level of the hybrid iterative reconstruction (HIR) that generates images with the best diagnostic quality on different dose and noise levels. HIR with optimizations is proposed to reduce image noise and provide better performance at a low dose. The Catphan R 504 phantom is employed to assess various image qualities (IQ). Results: For any given scanning protocols, there is linear noise reduction and linear increase of contrast-to- noise ratio (CNR) using optimal HIR. The evidence from various module tests demonstrates that the shape of the noise power spectrum is continuously shifted to low frequency with increasing HIR levels compared with that of filtered-back-projection (FBP). This may describe the difference between the human observer performance and features of the ideal low-contrast objects. Conclusion: Optimal HIR is clearly demonstrated to be a superior method for reducing image noise and improving CNR compared to FBP. Optimal HIR also inhibits texture change or spectrum shift compared with the pure IR method. Even though there are continuous noise reduction and CNR increase with HIR at increasing levels, the human observer performance does not seem to improve simultaneously due to coarser noise (low-frequency noise). HIR level 3 to 5 is optimal for their study. It is possible for the optimal HIR to offer equivalent diagnostic IQ at a lower dose compared with FBP at a routine dose.

Salvage of Suboptimal Enhancement of Pulmonary Artery in Pulmonary CT Angiography Studies: Rapid kVp Switch Dual Energy CT Experience

Background: Multidetector computed tomography (MDCT) angiography is considered as the gold standard imaging modality in the evaluation of acute pulmonary embolism. Optimum vascular enhancement is critical for MDCT studies. The suboptimal opacification in pulmonary artery could be salvaged using low-energy virtual monoenergetic images (VMI) at rapid kVp switch dual energy CT. Objectives: To explore the potential improvement in pulmonary artery opacification and to assess the change in image quality parameters in VMI using fast switch kVp dual energy CT. Patients and Methods: The CT images of 877 patients who were referred with a preliminary diagnosis of pulmonary embolism were reviewed. Sixty patients with suboptimal enhancement (&lt; 200 Hounsfeld Unit [HU]) were involved. Standard images (140 kVp) and VMI from 40 to 120 keV were generated. Attenuation, noise, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were measured in the pulmonary artery. Using VMIs, the best image was determined as the image with the main pulmonary artery opacification greater than 200 HU and image quality ≥ 3. Fifty six studies that met these criteria were considered as salvaged. At this best energy level, quantitative parameters were compared with standard images. Results: The mean attenuation of pulmonary arteries was 169.80 HU in standard images in patients with suboptimal enhancement. The attenuations of VMIs at 40, 45, 50, 55, 60, 65, and 70 keV were significantly higher than standard images (P &lt; 0.001). Similar findings were observed with SNR and CNR. In the salvaged patients, the average increase in mean pulmonary artery attenuation was 62% (from 172.61 ± 23.4 to 280.55 ± 40.7), the average increase in SNR was 38% (from 12.1 ± 5.3 to 16.7 ± 7.1) and the average increase in CNR was 48% (9.2 ± 4.3 to 13.7 ± 6) (P &lt; 0.001). Conclusions: Low keV VMI reconstructions significantly increase pulmonary artery attenuation, CNR and SNR compared to standard image reconstructions. Suboptimal CT studies could be salvaged using low keV VMIs.

Relationship between CNR and visibility of anatomical structures of cone-beam computed tomography images under different exposure parameters.

The purpose of this study was to investigate the image quality of cone beam CT (CBCT) under different exposure parameters and the relationship between contrast-to-noise and visibility of eight anatomical structures. CBCT images for the evaluation of subjective image quality were acquired on an anthropopathic phantom containing a human skeleton embedded in soft tissue equivalent materials using 25 exposure protocols. Visibility of eight anatomical structures was evaluated by five independent observers. Using the SEDENTEXCT IQ Image Quality phantom, the contrast-to-noise ratio (CNR) was calculated by ImageJ software. A reduction on the visibility of anatomical structures was seen under lower exposure parameters. However, for 84% of the protocols, visibility of anatomical structures remained acceptable even under some lower parameter settings. As CNR increased, the visibility of anatomical structures also increased correspondingly. A change point could be found in the CNR interval 29.42-36.51 after which the visibility of anatomical structures no longer increases with the increase of CNR. Although CNR decrease under a lower exposure parameter, the image quality often remained acceptable at exposure levels below the manufacture's recommended settings. It is possible to standardize subjective image quality by physical factors. Currently, it is not possible to predetermine a change point CNR value due to different CBCT machine and variation of diagnostic tasks.

A compact system for intraoperative specimen imaging based on edge illumination x-ray phase contrast

A significant number of patients receiving breast-conserving surgery (BCS) for invasive carcinoma and ductal carcinoma in situ (DCIS) may need reoperation following tumor-positive margins from final histopathology tests. All current intraoperative margin assessment modalities have specific limitations. As a first step towards the development of a compact system for intraoperative specimen imaging based on edge illumination x-ray phase contrast, we prove that the system’s dimensions can be reduced without affecting imaging performance.We analysed the variation in noise and contrast to noise ratio (CNR) with decreasing system length using the edge illumination x-ray phase contrast imaging setup. Two-(planar) and three-(computed tomography (CT)) dimensional imaging acquisitions of custom phantoms and a breast tissue specimen were made. Dedicated phase retrieval algorithms were used to separate refraction and absorption signals. A ‘single-shot’ retrieval method was also used, to retrieve thickness map images, due to its simple acquisition procedure and reduced acquisition times. Experimental results were compared to numerical simulations where appropriate.The relative contribution of dark noise signal in integrating detectors is significant for low photon count statistics acquisitions. Under constant exposure factors and magnification, a more compact system provides an increase in CNR. Superior CNR results were obtained for refraction and thickness map images when compared to absorption images. Results indicate that the ‘single-shot’ acquisition method is preferable for a compact CT intraoperative specimen scanner; it allows for shorter acquisition times and its combination of the absorption and refraction signals ultimately leads to a higher contrast. The first CT images of a breast specimen acquired with the compact system provided promising results when compared to those of the longer length system.

Dual-probe molecular MRI for the in vivo characterization of atherosclerosis in a mouse model: Simultaneous assessment of plaque inflammation and extracellular-matrix remodeling

Molecular MRI is a promising in-vivo modality to detect and quantify morphological and molecular vessel-wall changes in atherosclerosis. The combination of different molecular biomarkers may improve the risk stratification of patients. This study aimed to investigate the feasibility of simultaneous visualization and quantification of plaque-burden and inflammatory activity by dual-probe molecular MRI in a mouse-model of progressive atherosclerosis and in response-to-therapy. Homozygous apolipoprotein E knockout mice (ApoE−/−) were fed a high-fat-diet (HFD) for up to four-months prior to MRI of the brachiocephalic-artery. To assess response-to-therapy, a statin was administered for the same duration. MR imaging was performed before and after administration of an elastin-specific gadolinium-based and a macrophage-specific iron-oxide-based probe. Following in-vivo MRI, samples were analyzed using histology, immunohistochemistry, inductively-coupled-mass-spectrometry and laser-inductively-coupled-mass-spectrometry. In atherosclerotic-plaques, intraplaque expression of elastic-fibers and inflammatory activity were not directly linked. While the elastin-specific probe demonstrated the highest accumulation in advanced atherosclerotic-plaques after four-months of HFD, the iron-oxide-based probe showed highest accumulation in early atherosclerotic-plaques after two-months of HFD. In-vivo measurements for the elastin and iron-oxide-probe were in good agreement with ex-vivo histopathology (Elastica-van-Giesson stain: y = 298.2 + 5.8, R2 = 0.83, p < 0.05; Perls‘ Prussian-blue-stain: y = 834.1 + 0.67, R2 = 0.88, p < 0.05). Contrast-to-noise-ratio (CNR) measurements of the elastin probe were in good agreement with ICP-MS (y = 0.11x-11.3, R² = 0.73, p < 0.05). Late stage atherosclerotic-plaques displayed the strongest increase in both CNR and gadolinium concentration (p < 0.05). The gadolinium probe did not affect the visualization of the iron-oxide-probe and vice versa. This study demonstrates the feasibility of simultaneous assessment of plaque-burden and inflammatory activity by dual-probe molecular MRI of progressive atherosclerosis. The in-vivo detection and quantification of different MR biomarkers in a single scan could be useful to improve characterization of atherosclerotic-lesions.

Feasibility of fast non local means filter in pediatric chest x-ray for increasing of pulmonary nodule detectability with 3D printed lung nodule phantom

General x-ray images have a lower probability of nodule detection than other modalities. Especially in children, the probability of nodule detection can likely drop due to poor image quality from using low radiation dose. To demonstrate the effectiveness of fast non-local means (FNLM) filter to increase the probability of nodule detection in pediatric chest x-ray images and reduce radiation dose while maintaining image quality. Quantitative assessment of normalised noise power spectrum (NNPS), coefficient of variation (COV) and contrast to noise ratio (CNR) were performed after applying four filters (median, Wiener, total variation and FNLM) on a 1-year-old child phantom. A 3D-printed patient nodule phantom was inserted into the phantom. Assessment was performed on AP and LAT view images acquired with the tube voltage reduced to 38 and 27%, and tube current reduced to 84 and 61%, respectively. The results showed the lowest NNPS and COV values and the highest CNR value when the FNLM filter applied. Moreover, the AP view results showed 37% decrease in COV and 30% increase in CNR in images with the FNLM filter applied (images exposed with the tube voltage and current reduced to 29% and 50%, respectively). The LAT view results showed 5% decrease in COV and 36% increase in CNR in images with the FNLM filter applied (images exposed with the tube current reduced by 27%). By applying the FNLM filter, the probability of nodule detection could be increased by denoising and contrast enhancement. Moreover, using the FNLM filter could reduce cancer risk in pediatric patients by reducing radiation dose about 30% to 44%.

Known-component 3D image reconstruction for improved intraoperative imaging in spine surgery: A clinical pilot study.

Intraoperative imaging plays an increased role in support of surgical guidance and quality assurance for interventional approaches. However, image quality sufficient to detect complications and provide quantitative assessment of the surgical product is often confounded by image noise and artifacts. In this work, we translated a three-dimensional model-based image reconstruction (referred to as "Known-Component Reconstruction," KC-Recon) for the first time to clinical studies with the aim of resolving both limitations. KC-Recon builds upon a penalized weighted least-squares (PWLS) method by incorporating models of surgical instrumentation ("known components") within a joint image registration-reconstruction process to improve image quality. Under IRB approval, a clinical pilot study was conducted with 17 spine surgery patients imaged under informed consent using the O-arm cone-beam CT system (Medtronic, Littleton MA) before and after spinal instrumentation. Volumetric images were generated for each patient using KC-Recon in comparison to conventional filtered backprojection (FBP). Imaging performance prior to instrumentation ("preinstrumentation") was evaluated in terms of soft-tissue contrast-to-noise ratio (CNR) and spatial resolution. The quality of images obtained after the instrumentation ("postinstrumentation") was assessed by quantifying the magnitude of metal artifacts (blooming and streaks) arising from pedicle screws. The potential low-dose advantages of the algorithm were tested by simulating low-dose data (down to one-tenth of the dose of standard protocols) from images acquired at normal dose. Preinstrumentation images (at normal clinical dose and matched resolution) exhibited an average 24.0% increase in soft-tissue CNR with KC-Recon compared to FBP (N=16, P=0.02), improving visualization of paraspinal muscles, major vessels, and other soft-tissues about the spine and abdomen. For a total of 72 screws in postinstrumentation images, KC-Recon yielded a significant reduction in metal artifacts: 66.3% reduction in overestimation of screw shaft width due to blooming (P<0.0001) and reduction in streaks at the screw tip (65.8% increase in attenuation accuracy, P<0.0001), enabling clearer depiction of the screw within the pedicle and vertebral body for an assessment of breach. Depending on the imaging task, dose reduction up to an order of magnitude appeared feasible while maintaining soft-tissue visibility and metal artifact reduction. KC-Recon offers a promising means to improve visualization in the presence of surgical instrumentation and reduce patient dose in image-guided procedures. The improved soft-tissue visibility could facilitate the use of cone-beam CT to soft-tissue surgeries, and the ability to precisely quantify and visualize instrument placement could provide a valuable check against complications in the operating room (cf., postoperative CT).

Image quality assessment of a photon counting detector in x-ray projection imaging.

The recent advancements in the photon counting detection have created a significant growing research interest in the x-ray imaging. It is essential to objectively understand the image quality parameters of a photon counting detector before developing imaging applications. In this work, we have assessed the imaging quality of a cadmium telluride (CdTe) based PCD in projection imaging mode. The detector is 70.4 mm × 6.6 mm dimensions. The detector has a pixel array of 64×4 with a pixel pitch of 1.1 mm×1.65 mm. With each pixel having 4 channels in its corresponding ASIC, this PCD can create three bin images from a single projection. With a microfocus x-ray source, the imaging quality in each bin image was measured in terms of the spatial resolution, noise, and contrast to noise ratio (CNR). We used 70 kV, 50μA, 10 s (0.5mAs) with 0.5mm thick aluminum (Al) filter for the acquisition of each image. The MTF curves indicated that the spatial resolution for the bin-1, bin-2, and bin-3 was almost identical. The NNPS curves indicated that the noise in bin 1 and bin 2 images was almost the same for all frequencies while bin 3 image had relatively less noise. The CNR analyses showed that the bin-1 image had the highest CNR. As the flux was increased from 0.5 to 1 mAs, the number of detected counts also increased that resulted in the CNR increase. Beyond this flux, the pulse pileup occurred due to which multiple counts were read as single that resulted in few detected counts and lower CNR. The knowledge of the spatial resolution, noise, and CNR in terms of energy binning allows the determination and optimization of imaging techniques necessary for various applications.

Hidden Infarcts Detected by a High b-Value Diffusion-Weighted Imaging: A Parameter-Optimized Study

Objective: Small infarcts are easily missed on conventional sequences or a standard b-value diffusion-weighted imaging (DWI). This study aims to investigate the signal characteristics of DWI with different b-values and matrixes in acute cerebral infarction, and evaluate the feasibility of high b-values used in DWI. Methods: Twenty-nine cases of clinically diagnosed acute cerebral infarction were included prospectively in this study. The patients underwent MRI examinations, including routine T1WI, T2WI, T2 Flair, and different b-value DWIs (b = 1000, 1500, and 2000 s/mm2 with matrix 160 × 160. In addition, b = 1000 DWI was divided into two groups with different matrixes of 128 × 128 and 160 × 160. The differences of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), contrast ratio (CR), and apparent diffusion coefficient (ADC) values between the different b-values and matrixes DWI were compared. Results: Visually, b =1500 and b = 2000 DWI showed more scattering and micro-lesions than a standard DWI. The lesions shown in the high b-value DWI were more conspicuous and brighter. Quantitatively, with the increase in b-values, the SNR, CNR, and ADC values decreased gradually, but the CR increased gradually. With a reduction in the matrix size, the SNR and CNR improved (all the results were statistically significant with good inter-observer reliability). Conclusions: A high b-value for DWI is beneficial for the detection of micro- and hyperacute infarction, but the image quality declines. However, reducing the matrix size appropriately could make up for this deficiency.