A novel protocol for abdominal low-dose CT scans adapted with a model-based iterative reconstruction method.

PURPOSE: This study aims to introduce a novel low-dose abdominal computed tomography (CT) protocol adapted with model-based iterative reconstruction (MBIR), To validate the adaptability of this protocol, objective image quality and subjective clinical scores of low-dose MBIR images are compared with the normal-dose images. METHODS: Normal-dose abdominal CT images of 58 patients and low-dose abdominal CT images of 52 patients are reconstructed using both conventional filtered back projection (FBP) and MBIR methods with and without smooth applying. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) are used to compare image quality between the normal-dose and low-dose CT scans. CT dose indices (CTDI) of normal-dose and low-dose abdominal CT images on post-contrast venous phase are also compared. RESULTS: The SNR, CNR and clinical score of low-dose MBIR images all show significant higher values (Bonferroni p < 0.05) than those of normal-dose images with conventional FBP method. A total of around 40% radiation dose reduction (CTDI: 5.3 vs 8.7 mGy) could be achieved via our novel abdominal CT protocol. CONCLUSIONS: With the higher SNR/CNR and clinical scores, the low-dose CT abdominal imaging protocol with MBIR could effectively reduce the radiation for patients and provide equal or even higher image quality and also its adaptability in clinical abdominal CT image diagnosis.

Manganese-enhanced MRI (ME MRI) in evaluation of the auditory pathway in an experimental rat model.

This study aimed to explore the optimal dose and manner of administration for visualization of the auditory pathway on manganese-enhanced MRI (ME MRI). Twenty-four healthy male Sprague-Dawley rats were randomly divided into three experimental groups (n = 8 for Groups A, B and C). The rats in Groups A, B and C were subjected to MnCl2 injection through the tympanum, inner ear endolymph and perilymph, respectively (0.2 M for four rats and 0.4 M for the others in each group) and observed at 1, 2, 3, 4, 7 and 10 days after the operation with 3.0 T MRI. The signal intensity (SI) and dynamic changes of the auditory pathways at various times, and at two doses through three injection routes, were compared by statistical analysis. Administration of MnCl2 through the perilymph best showed the complete auditory pathway (P < 0.01), whereas administration though the tympanum only demonstrated part of the pathway. The SI was highest at 24 h after administration of the tracer and began to decline at 48 h. The SI of the auditory cortex was higher after the injection of 0.4 M MnCl2 than that of 0.2 M MnCl2 . ME MRI best demonstrated the whole auditory pathway at 24 h after the injection of 0.4 M MnCl2 through the perilymph in the rat, which provided an optimal method for the study of ME MRI of the auditory pathway in the animal model.

Proposal of a New Index Based on Signal-to-Noise Ratio for Low-contrast Detectability in Computed Tomographic Imaging.

The low-contrast detectability of computed tomography (CT) images is commonly evaluated by the contrast-to-noise ratio (CNR) because of its convenience to measure. However, the correlation between CNR and visual detectability is poor because the CNR is a simple index determined by both the contrast of the object and the standard deviation of the image noise. On the other hand, the signal-to-noise ratio (SNR), especially SNR based on the statistical decision theory model (SNRS, D) and SNR based on the matched-filter model (SNRM) are considered superior to CNR. In this study, we investigated a new physical image quality index for evaluating low-contrast detectability (SNRA), which is approximately derived from SNRS, D and SNRM. The new index, which was calculated using the object size, contrast of the object and the noise power spectrum, provided good approximations when the diameter of the rod object was equal and >5 mm. The diameter dependency of the SNRA was also found to provide better sensitivity than the sensitivities of CNR and object-specific CNR, similar to SNRS, D and SNRM. The results suggested that the proposed convenient index should be useful for evaluating the low-contrast detectability of CT images.

A cross-sectional study on the correlation of image quality, effective dose, and body composition with thyroid, chest, and abdominal computed tomography scans.

Background: The rapid increase in the use of radiodiagnostic examinations in China, especially computed tomography (CT) scans, has led to these examinations being the largest artificial source of per capita effective dose (ED). This study conducted a retrospective analysis of the correlation between image quality, ED, and body composition in 540 cases that underwent thyroid, chest, or abdominal CT scans. The aim of this analysis was to evaluate the correlation between the parameters of CT scans and body composition in common positions of CT examination (thyroid, chest, and abdomen) and ultimately inform potential measures for reducing radiation exposure. Methods: This study included 540 patients admitted to Fudan University Shanghai Cancer Center from January 2015 to December 2019 who underwent both thyroid or chest or abdominal CT scan and body composition examination. Average CT values and standard deviation (SD) values were collected for the homogeneous areas of the thyroid, chest, or abdomen, and the average CT values and SD values of adjacent subcutaneous fat tissue were measured in the same region of interest (ROI). All data were measured three times, and the average was taken to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for each area. The dose-length product (DLP) was recorded, and the ED was calculated with the following: formula ED = k × DLP. Dual-energy X-ray was used to determine body composition and obtain indicators such as percentage of spinal and thigh muscle. Pearson correlation coefficient was used to analyze the correlations between body composition indicators, height, weight, body mass index (BMI), and ED. Results: The correlation coefficients between the SNR of abdominal CT scan and weight, BMI, and body surface area (BSA) were -0.470 (P=0.001), -0.485 (P=0.001), and -0.437 (P=0.002), representing a moderate correlation strength with statistically significant differences. The correlation coefficients between the ED of chest CT scans and weight, BMI, spinal fat percentage, and BSA were 0.488 (P=0.001), 0.473 (P=0.002), 0.422 (P=0.001), and 0.461 (P=0.003), respectively, indicating a moderate correlation strength with statistical differences. There was a weak statistically significant correlation between the SNR, CNR, and ED of the other scans with each physical and body composition index (P=0.023). Conclusions: There were varying degrees of correlation between CT image quality and ED and physical and body composition indices, which may inform novel solutions for reducing radiation exposure.

Evaluation of four computed tomography reconstruction algorithms using a coronary artery phantom.

Background: Despite advancements in coronary computed tomography angiography (CTA), challenges in positive predictive value and specificity remain due to limited spatial resolution. The purpose of this experimental study was to investigate the effect of 2nd generation deep learning-based reconstruction (DLR) on the quantitative and qualitative image quality in coronary CTA. Methods: A vessel model with stepwise non-calcified plaque was scanned using 320-detector CT. Image reconstruction was performed using four techniques: hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), DLR, and 2nd generation DLR. The luminal peak CT number, contrast-to-noise ratio (CNR), and edge rise slope (ERS) were quantitatively evaluated via profile curve analysis. Two observers qualitatively graded the graininess, lumen sharpness, and overall lumen visibility on the basis of the degree of confidence for the stenosis severity using a five-point scale. Results: The image noise with HIR, MBIR, DLR, and 2nd generation DLR was 23.0, 21.0, 16.9, and 9.5 HU, respectively. The corresponding CNR (25% stenosis) was 15.5, 15.9, 22.1, and 38.3, respectively. The corresponding ERS (25% stenosis) was 203.2, 198.6, 228.9, and 262.4 HU/mm, respectively. Among the four reconstruction methods, the 2nd generation DLR achieved the significantly highest CNR and ERS values. The score of 2nd generation DLR in all evaluation points (graininess, sharpness, and overall lumen visibility) was higher than those of the other methods (overall vessel visibility score, 2.6±0.5, 3.8±0.6, 3.7±0.5, and 4.6±0.5 with HIR, MBIR, DLR, and 2nd generation DLR, respectively). Conclusions: 2nd generation DLR provided better CNR and ERS in coronary CTA than HIR, MBIR, and previous-generation DLR, leading to the highest subjective image quality in the assessment of vessel stenosis.

Image Quality Assessment Tool for Conventional and Dynamic Magnetic Resonance Imaging Acquisitions.

Image quality assessment of magnetic resonance imaging (MRI) data is an important factor not only for conventional diagnosis and protocol optimization but also for fairness, trustworthiness, and robustness of artificial intelligence (AI) applications, especially on large heterogeneous datasets. Information on image quality in multi-centric studies is important to complement the contribution profile from each data node along with quantity information, especially when large variability is expected, and certain acceptance criteria apply. The main goal of this work was to present a tool enabling users to assess image quality based on both subjective criteria as well as objective image quality metrics used to support the decision on image quality based on evidence. The evaluation can be performed on both conventional and dynamic MRI acquisition protocols, while the latter is also checked longitudinally across dynamic series. The assessment provides an overall image quality score and information on the types of artifacts and degrading factors as well as a number of objective metrics for automated evaluation across series (BRISQUE score, Total Variation, PSNR, SSIM, FSIM, MS-SSIM). Moreover, the user can define specific regions of interest (ROIs) to calculate the regional signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), thus individualizing the quality output to specific use cases, such as tissue-specific contrast or regional noise quantification.

Possible use of Digital Variance Angiography in Liver Transarterial Chemoembolization: A Retrospective Observational Study.

PURPOSE: Digital variance angiography (DVA), a recently developed image processing technology, provided higher contrast-to-noise ratio (CNR) and better image quality (IQ) during lower limb interventions than digital subtraction angiography (DSA). Our aim was to investigate whether this quality improvement can be observed also during liver transarterial chemoembolization (TACE). MATERIALS AND METHODS: We retrospectively compared the CNR and IQ parameters of DSA and DVA images from 25 patients (65% male, mean ± SD age: 67.5 ± 11.2 years) underwent TACE intervention at our institute. CNR was calculated on 50 images. IQ of every image set was evaluated by 5 experts using 4-grade Likert scales. Both single image evaluation and paired image comparison were performed in a blinded and randomized manner. The diagnostic value was evaluated based on the possibility to identify lesions and feeding arteries. RESULTS: DVA provided significantly higher CNR (mean CNRDVA/CNRDSA was 1.33). DVA images received significantly higher individual Likert score (mean ± SEM 3.34 ± 0,08 vs. 2.89 ± 0.11, Wilcoxon signed-rank p < 0.001) and proved to be superior also in paired comparisons (median comparison score 1.60 [IQR:2.40], one sample Wilcoxon p < 0.001 compared to equal quality level). DSA could not detect lesion and feeding artery in 28 and 36% of cases, and allowed clear detection only in 22% and 16%, respectively. In contrast, DVA failed only in 8 and 18% and clearly revealed lesions and feeding arteries in 32 and 26%, respectively. CONCLUSION: In our study, DVA provided higher quality images and better diagnostic insight than DSA; therefore, DVA could represent a useful tool in liver TACE interventions. LEVEL OF EVIDENCE: III Non-consecutive study.

Functional magnetic particle imaging (fMPI) of cerebrovascular changes in the rat brain during hypercapnia.

Objective.Non-invasive functional brain imaging modalities are limited in number, each with its own complex trade-offs between sensitivity, spatial and temporal resolution, and the directness with which the measured signals reflect neuronal activation. Magnetic particle imaging (MPI) directly maps the cerebral blood volume (CBV), and its high sensitivity derives from the nonlinear magnetization of the superparamagnetic iron oxide nanoparticle (SPION) tracer confined to the blood pool. Our work evaluates functional MPI (fMPI) as a new hemodynamic functional imaging modality by mapping the CBV response in a rodent model where CBV is modulated by hypercapnic breathing manipulation.Approach.The rodent fMPI time-series data were acquired with a mechanically rotating field-free line MPI scanner capable of 5 s temporal resolution and 3 mm spatial resolution. The rat's CBV was modulated for 30 min with alternating 5 min hyper-/hypocapnic states, and processed using conventional fMRI tools. We compare our results to fMRI responses undergoing similar hypercapnia protocols found in the literature, and reinforce this comparison in a study of one rat with 9.4T BOLD fMRI using the identical protocol.Main results.The initial image in the time-series showed mean resting brain voxel SNR values, averaged across rats, of 99.9 following the first 10 mg kg-1SPION injection and 134 following the second. The time-series fit a conventional General Linear Model with a 15%-40% CBV change and a peak pixel CNR between 12 and 29, 2-6× higher than found in fMRI.Significance.This work introduces a functional modality with high sensitivity, although currently limited spatial and temporal resolution. With future clinical-scale development, a large increase in sensitivity could supplement other modalities and help transition functional brain imaging from a neuroscience tool focusing on population averages to a clinically relevant modality capable of detecting differences in individual patients.

Characterization of single- and multi-energy CT performance of an oral dark borosilicate contrast media using a clinical photon-counting-detector CT platform.

BACKGROUND: The feasibility of oral dark contrast media is under exploration in abdominal computed tomography (CT) applications. One of the experimental contrast media in this class is dark borosilicate contrast media (DBCM), which has a CT attenuation lower than that of intra-abdominal fat. PURPOSE: To evaluate the performances of DBCM using single- and multi-energy CT imaging on a clinical photon-counting-detector CT (PCD-CT). METHODS: Five vials, three with iodinated contrast agent (5, 10, and 20 mg/mL; Omnipaque 350) and two with DBCM (6% and 12%; Nextrast, Inc.), and one solid-water rod (neutral contrast agent) were inserted into two multi-energy CT phantoms, and scanned on a clinical PCD-CT system (NAEOTOM Alpha) at 90, 120, 140, Sn100, and Sn140 kV (Sn: tin filter) in multi-energy mode. CARE keV IQ level was 180 (CTDIvol: 3.0 and 12.0 mGy for the small and large phantoms, respectively). Low-energy threshold images were reconstructed with a quantitative kernel (Qr40, iterative reconstruction strength 2) and slice thickness/increment of 2.0/2.0 mm. Virtual monoenergetic images (VMIs) were reconstructed from 40 to 140 keV at 10 keV increments. On all images, average CT numbers for each vial/rod were measured using circular region-of-interests and averaged over eight slices. The contrast-to-noise ratio (CNR) of iodine (5 mg/mL) against DBCM was calculated and plotted against tube potential and VMI energy level, and compared to the CNR of iodine against water. Similar analyses were performed on iodine maps and VNC images derived from the multi-energy scan at 120 kV. RESULTS: With increasing kV or VMI keV, the negative HU of DBCM decreased only slightly, whereas the positive HU of iodine decreased across all contrast concentrations and phantom sizes. CT numbers for DBCM decreased from -178.5 ± 9.6 to -194.4 ± 6.3 HU (small phantom) and from -181.7 ± 15.7 to -192.1 ± 11.9 HU (large phantom) for DBCM-12% from 90 to Sn140 kV; on VMIs, the CT numbers for DBCM decreased minimally from -147.1 ± 15.7 to -185.1 ± 9.2 HU (small phantom) and -158.8 ± 28.6 to -188.9 ± 14.7 HU (large phantom) from 40 to 70 keV, but remained stable from 80 to 140 keV. The highest iodine CNR against DBCM in low-energy threshold images was seen at 90 or Sn140 kV for the small phantom, whereas all CNR values from low-energy threshold images for the large phantom were comparable. The CNR values of iodine against DBCM computed on VMIs were highest at 40 or 70 keV depending on iodine and DBCM concentrations. The CNR values of iodine against DBCM were consistently higher than iodine to water (up to 460% higher dependent on energy level). Further, the CNR of iodine compared to DBCM is less affected by VMI energy level than the identical comparison between iodine and water: CNR values at 140 keV were reduced by 46.6% (small phantom) or 42.6% (large phantom) compared to 40 keV; CNR values for iodine compared to water were reduced by 86.3% and 83.8% for similar phantom sizes, respectively. Compared to 70 keV VMI, the iodine CNR against DBCM was 13%-79% lower on iodine maps and VNC. CONCLUSIONS: When evaluated at different tube potentials and VMI energy levels using a clinical PCD-CT system, DBCM showed consistently higher CNR compared to iodine versus water (a neutral contrast).

Exploration of the pulse pileup effects in a clinical CdTe-based photon-counting computed tomography.

BACKGROUND: High tube current generates a high flux of x-rays to photon counting detectors (PCDs) that can potentially result in the piling up of pulses formed by concurrent photons, which can cause count loss and energy resolution degradation. PURPOSE: To evaluate the performance of clinical photon-counting CT (PCCT) systems in high flux, potentially influenced by pulse pileup effects, in terms of task-generic image quality metrics. METHODS: A clinical phantom was scanned on a commercial PCCT scanner (NAEOTOM Alpha, Siemens) at 120 kV under fourteen different tube current levels (40-1000 mA) with a rotation time of 0.25 s and a pitch of 1. The dose levels corresponded to CTDIvol (32 cm phantom) of 0.79-19.8 mGy. CT sinograms were reconstructed using QIR-off mode (noniterative reconstruction algorithm), Br44 kernel, and a voxel size of 0.4102 × 0.4102 × 3 mm 3 $0.4102 \times 0.4102 \times 3{\mathrm{\ mm}}^3$ . imQuest, an open-source MATLAB-based software package was used to calculate noise power spectrum (NPS), task transfer function (TTF), contrast-to-noise ratio (CNR), and CT number according to AAPM Task Group 233 metrology. RESULTS: The 50% cut-off frequency of TTF (f50 ) remained mostly constant across all higher tube currents for all inserts, namely polyethylene, bone, air, and acrylic. Using the lowest two data points (40 and 80 mA), the expected relationship between noise magnitude and tube current was determined to be noise ∝ $ \propto \ $ mA-0.47 . The measured noise magnitude were up to 11.1% higher than the expected value at the highest tube current. The average frequency of NPS (fav ) decreased from 0.32 to 0.29 mm-1 as tube current increased from 40 to 1000 mA. No considerable effects were observed in CT number measurement of any insert; however, CT numbers for air and bone changed almost monotonically as tube current increased. Absolute CNR increased monotonically for all inserts; however, the difference between measured and expected CNRs were approximately -6% to 12% across all tube currents. CONCLUSIONS: Increasing tube currents did not affect the spatial resolution, but slightly affected the CT number and noise measurements of the clinical PCCT system. However, the effects were only considerable at clinically irrelevant tube currents used on a small 20-cm phantom. In general clinical practices, automatic exposure control techniques are used to decrease the variation of flux on the detector, which alleviates the chances of detector saturation due to high count rates. The observed effects could be due to pulse pileup, signal-dependent filtration of the system, or nonlinearities in the reconstruction algorithm. In conclusion, either the deadtime of the detector used in the photon-counting CT system is shorter such that count losses due to pulse pileup are negligible, or pulse pileup has inconsiderable effects on the image quality of clinical photon-counting CT systems in routine clinical practice due to possible corrections applied on the system.

A Novel Method for Evaluating Early Tumor Response Based on Daily CBCT Images for Lung SBRT.

BACKGROUND: We aimed to develop a new tumor response assessment method for lung SBRT. METHODS: In total, 132 lung cancer patients with 134 tumors who received SBRT treatment with daily CBCT were included in this study. The information about tumor size (area), contrast (contrast-to-noise ratio (CNR)), and density/attenuation (µ) was derived from the CBCT images for the first and the last fractions. The ratios of tumor area, CNR, and µ (RA, RCNR, Rµ) between the last and first fractions were calculated for comparison. The product of the three rations was defined as a new parameter (R) for assessment. Tumor response was independently assessed by a radiologist based on a comprehensive analysis of the CBCT images. RESULTS: R ranged from 0.27 to 1.67 with a mean value of 0.95. Based on the radiologic assessment results, a receiver operation characteristic (ROC) curve with the area under the curve (AUC) of 95% was obtained and the optimal cutoff value (RC) was determined as 1.1. The results based on RC achieved a 94% accuracy, 94% specificity, and 90% sensitivity. CONCLUSION: The results show that R was correlated with early tumor response to lung SBRT and that using R for evaluating tumor response to SBRT would be viable and efficient.

Deep learning reconstruction allows low-dose imaging while maintaining image quality: comparison of deep learning reconstruction and hybrid iterative reconstruction in contrast-enhanced abdominal CT.

We aimed to compare the radiation dose and image quality of a low-dose abdominal computed tomography (CT) protocol reconstructed with deep learning reconstruction (DLR) with those of a routine-dose protocol reconstructed with hybrid-iterative reconstruction. This retrospective study enrolled 71 patients [61 men; average age, 71.9 years; mean body mass index (BMI), 24.3 kg/m2] who underwent both low-dose abdominal CT with DLR [advanced intelligent clear-IQ engine (AiCE)] and routine-dose abdominal CT with hybrid-iterative reconstruction [adaptive iterative dose reduction 3D (AIDR 3D)]. Radiation dose parameters included volume CT dose index (CTDIvol), effective dose (ED), and size-specific dose estimate (SSDE). Mean image noise and contrast-to-noise ratio (CNR) were calculated. Image noise was measured in the hepatic parenchyma and bilateral erector spinae muscles. Moreover, subjective assessment of perceived image quality and diagnostic acceptability was performed. The low-dose protocol helped reduce the CTDIvol by 44.3%, ED by 43.7%, and SSDE by 44.9%. Moreover, the noise was significantly lower and CNR significantly higher with the low-dose protocol than with the normal-dose protocol (P<0.001). In the subjective assessment of image quality, there was no significant difference between the protocols with regard to image noise. Overall, AiCE was superior to AIDR 3D in terms of diagnostic acceptability (P=0.001). The use of AiCE can reduce overall radiation dose by more than 40% without loss of image quality compared to routine-dose abdominal CT with AIDR 3D.

[Study of X-ray Beam Quality and Contrast-to-Noise Ratio of Lung Nodules in Chest FPD Radiography: Monte Carlo Simulation Using Chest Model Phantom].

OBJECTIVES: Contrast-to-noise ratio (CNR) of four X-ray beams (90 kV with 0.15-mm Cu filter, 90 kV with 0.2-mm Cu filter, 120 kV without filter and 120 kV with 0.2-mm Cu filter) in CsI-flat panel detector (FPD) radiography for lung cancer diagnosis was investigated using Monte Carlo simulation. METHOD: Two billion photons were injected to the chest phantom model (width: 300 mm, length: 300 mm, thickness: 200 mm) with imitated lung nodules (10 mm diameter, CT value: +30 Hounsfield unit (HU), -375 HU, and -620 HU). Individual primary and secondary photon's process (absorption, scattering and penetration) in the phantom and CsI-detector was recorded by Monte Carlo simulation. CNR was calculated using primary and secondary absorbed photon's number in the CsI-detector. RESULTS: CNR of 90 kV X-ray beam with 0.15 mm and 0.2 mm Cu filters was higher to 120 kV X-ray beam because of higher primary object contrast and photon's contribution, and high photon's absorption to CsI. CONCLUSION: By Monte Carlo calculation, it was verified that 90 kV X-ray beam with 0.15 mm and 0.2 mm Cu filters yielded higher CNR to 120 kV X-ray beam.

Binarization Mechanism Evaluation for Water Ingress Detectability in Honeycomb Sandwich Structure Using Lock-In Thermography.

The growing use of composite honeycomb structures in several industries including aircraft has demonstrated the need to develop effective and efficient non-destructive evaluation methods. In recent years, active thermography has attracted great interest as a reliable technology for non-destructive testing and evaluation of composite materials due to its advantages of non-contact, non-destructive, full-area coverage, high speed, qualitative, and quantitative testing. However, non-uniform heating, low spatial resolution, and ambient environmental noise make the detection and characterization of defects challenging. Therefore, in this study, lock-in thermography (LIT) was used to detect water ingress into an aircraft composite honeycomb sandwich structure, and the phase signals were binarized through the Otsu algorithm. A square composite honeycomb with dimensions of 210 mm × 210 mm along with 16 different defective areas of various sizes in groups filled with water by 25%, 50%, 75%, and 100% of the cell volume was considered. The sample was excited at multiple modulation frequencies (i.e., 1 Hz to 0.01 Hz). The results were compared in terms of phase contrast and CNR according to the modulation frequency. In addition, the detectability was analyzed by comparing the number of pixels of water ingress in the binarized image and the theoretical calculation.

[Optimal Beam Quality in Chest Radiography Using CsI-flat Panel Detector for Detection of Pulmonary Nodules].

OBJECTIVES: Optimal beam quality for detection of pulmonary nodules in digital chest radiography using CsI-flat panel detector (FPD) was investigated in consideration of image quality and patient dose. METHODS: The human chest phantom with inserted imitated nodules (diameter: 10 mm, CT value: +30 Hounsfield unit (HU), -375 HU, -620 HU) was used for the measurement of contrast-to-noise ratio (CNR) of imitated nodules by twenty beams arranged by five tube voltages and four filters. RESULTS: The CNR varies with X-ray tube voltage and added filter. CNR correlates weakly to the tube voltage, fairly to the effective energy in second-order polynomial and strongly to the quality index (effective energy divided X-ray tube voltage). In order to improve the CNR, the effective energy and the quality index are kept about 50 keV and more than 0.5, respectively, using an 80-100 kV beam with a copper filter. CONCLUSION: A 90 kV (2.5 mm Al inherent filtration) beam with a 0.15 mm copper filter and a 90 kV or 100 kV (2.5 mm Al inherent filtration) beam with a 0.2 mm copper filter are appropriate for chest radiography using CsI-FPD.

The effects of three different contrast agents (Gd-BOPTA, Gd-DTPA, and Gd-DOTA) on brachial plexus magnetic resonance imaging.

BACKGROUND: MRI is very important for guiding the diagnosis and treatment of brachial plexus diseases. The most used type of MRI brachial plexus imaging is the 3D Short Term Inversion Recovery (STIR) sequence with contrast agent. This study aimed to investigate the effect of three contrast agents; gadobenate dimeglumine (Gd-BOPTA), gadopentetate dimeglumine (Gd-DTPA), and Gadoteric Acid Meglumine (Gd-DOTA) on brachial plexus magnetic resonance imaging (MRI). METHODS: We recruited 60 patients with suspected brachial plexus injury randomly into three groups. MRI images were obtained from each patient. Prior to scanning, the first group was injected with GD-BOPTA, the second group with Gd-DTPA, and the third with Gd-DOTA. The amount of contrast agent was 0.1 mmol/kg according to the weight of each patient, the injection rate was 1.5 mL/s, and 20 mL saline was injected at the same rate with a high-pressure injector. Immediately after the injection of contrast agent and saline, a 3D Sampling perfection with application optimized contrasts using different flip angle evolutions (SPACE) STIR sequence was used for scanning. The Signal Intensity (SI) and Standard Deviation (SD) of Maximal intensity projection (MIP) images for regions outside the anatomy (ROI background) with area of 17 mm2 on both sides of the C6 peripheral nerves (ROI nerve), and tissue adjacent to the peripheral nerves (ROI tissue) were obtained. Signal to noise ratio (SNR) and contrast to noise ratio (CNR) were then calculated. RESULTS: The SNR was 40.66±25.27, 34.65±14.86, and 44.63±30.79 for Gd-BOPTA, Gd-DTPA, and Gd-DOTA, respectively and the CNR was 20.24±15.17, 16.07±7.50, and 20.84±15.53 for Gd-BOPTA, Gd-DTPA, and Gd-DOTA, respectively. In addition, there was no statistical difference in the SNR or CNR of brachial plexus nerves using the three contrast agents to enhance the 3D SPACE sequence χ2=1.877, P=0.391>0.05 and χ2=1.717, P=0.424, respectively. CONCLUSIONS: There were no significant differences in the efficacy of three contrast agents in imaging the brachial plexus.

The Feasibility of Contrast-to-Noise Ratio on Measurements to Evaluate CT Image Quality in Terms of Low-Contrast Detailed Detectability.

Background: To evaluate contrast-to-noise ratio (CNR) measurements in assessing image quality, in the context of the detectability performance of low-contrast detail (LCD), in computed tomography (CT) images, since exposure to elevated ionising-type radiation is considered to present excessive carcinogenic risk, whilst also causing distress in study subjects. Methods: An LCD phantom module (CTP515) was utilised in the study. Three dissimilar contrast items were used to analyse the ramifications of the proportions of an object on the CNR. Three multidetector CT (MDCT) scanners were used, with 16-MDCT, 64-MDCT and 80-MDCT frameworks, respectively. The CT scans were recreated using three dissimilar remaking algorithms-soft, standard and lung. The effects exerted on the CNR by various remodelling algorithms, as well as the contrast of various objects along with the size of the objects, were explored. The Hounsfield units of each chosen object (one unit representing the outer portion of the object) and the background and the standard deviation of the noise parameter were quantified, and algorithms were developed using MATLAB. Results: The CNR information was greatly influenced by changing the image recreation calculations and was very much increased in the soft-tissue recreation images using 16-MDCT and 64-MDCT. The CNR information was also increased more in the optimum recreation images than in the reproduced images from the computational procedure used in the 80-MDCT. The results did not show any remarkable contrasts in the CNR values between the different object sizes. Overall, a higher kVp produced an improved CNR in all the CT scanners. In particular, there were prominent upgrades in the CNR information when the kVp was increased from 80 to 120. Higher mAs levels gave better CNR values overall, especially for greater section thicknesses. Based on the CNR estimations, the 64-MDCT provided the best correlation among the CT scanners. Conclusions: The objective LCD appraisal method, based on CNR measurements, was confirmed as being useful for checking the different impacts of kVp, mAs and section thickness on the nature of the picture. This procedure was similarly viable in assessing the impacts of the different reconstruction calculations and the different differentiation questions on the nature of the image.

T1-weighted parenchyma attenuated inversion recovery: A novel sequence that improves contrast ratio of enhancing brain lesions.

PURPOSE: The purpose of this study was to develop and test a parenchyma attenuated T1-weighted inversion recovery MR sequence (PAIR) that increases the contrast between enhancing and non-enhancing tissues in the brain and to compare the contrast ratio of enhancing brain tumors on this sequence compared to spin echo magnetization transfer (SEMT). PATIENTS AND METHODS: PAIR sequence parameters were developed to reduce signal from gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) in a healthy adult volunteer. Forty-one patients (17 men and 24 women) with a mean age of 55±13 (SD) years (range: 21-78years) with known or suspected brain tumors underwent PAIR and SEMT imaging after intravenous administration of gadobenate dimeglumine. In patients with confirmed tumors, PAIR and SEMT images were compared for contrast ratio of tumor-to-WM, tumor-to-GM, and tumor-to-CSF. RESULTS: A total of 23 enhancing neoplastic lesions were found in 14/41 patients. All tumors were visualized on both contrast enhanced PAIR and SEMT images. PAIR images showed a 2.5 fold increase in maximum tumor-to-GM contrast ratio (P<0.0001), a 1.4 fold increase in maximum tumor-to-WM contrast ratio (P=0.0007) and a 5-fold increase in maximum tumor-to-CSF contrast ratio (P<0.0001). CONCLUSION: PAIR provides improved lesion-to-background contrast ratio compared to SEMT and may be useful as an added sequence in tumor evaluation.

Needle Tip Visibility in 3D Ultrasound Images.

AIM: Needle visibility is crucial for effective and safe ultrasound-guided interventional procedures. Several studies have investigated needle visibility in 2D ultrasound imaging, but less information is available for 3D ultrasound imaging, a modality that has great potential for image guidance interventions. We performed a prospective study, to quantitatively compare the echogenicity of various commercially available needles in 3D ultrasound images used in clinical practice under freehand needle introduction. MATERIALS AND METHODS: A set of seven needles, containing biopsy needles, a TIPS needle, an ablation needle and a puncture needle, were included in the study. A liver-mimicking phantom and cow liver were punctured by each needle. 3D sweeps and real-time 3D data were acquired at three different angles (20°, 55° and 90°). Needle visibility was quantified by calculating contrast-to-noise ratio. RESULTS: In the liver-mimicking phantom, all needles showed better visibility than in the cow liver. At large angles, contrast-to-noise ratio and needle visibility were almost similar in both cases, but at lower angles differences in visibility were observed with different types of needles. CONCLUSION: The contrast-to-noise ratio increased with the increase in angle of insonation. The difference in visibility of different needles is more pronounced at 20° angle. The echogenic properties of inhomogeneous cow liver tissues make the needles visibility worse as compared to a homogenous phantom. The needle visibility becomes worse in 3D real-time data as compared to 3D ultrasound sweeps.

A theoretical analysis of chemical exchange saturation transfer echo planar imaging (CEST-EPI) steady state solution and the CEST sensitivity efficiency-based optimization approach.

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute labile protons and microenvironmental properties, augmenting routine relaxation-based MRI. Recent developments of quantitative CEST (qCEST) analysis such as omega plots and RF-power based ratiometric calculation have extended our ability to elucidate the underlying CEST system beyond the simplistic apparent CEST measurement. CEST MRI strongly varies with experimental factors, including the RF irradiation level and duration as well as repetition time and flip angle. In addition, the CEST MRI effect is typically small, and experimental optimization strategies have to be carefully evaluated in order to enhance the CEST imaging sensitivity. Although routine CEST MRI has been optimized largely based on maximizing the magnitude of the CEST effect, the CEST signal-to-noise (SNR) efficiency provides a more suitable optimization index, particularly when the scan time is constrained. Herein, we derive an analytical solution of the CEST effect that takes into account key experimental parameters including repetition time, imaging flip angle and RF irradiation level, and solve its SNR efficiency. The solution expedites CEST imaging sensitivity calculation, substantially faster than the Bloch-McConnell equation-based numerical simulation approach. In addition, the analytical solution-based SNR formula enables the exhaustive optimization of CEST MRI, which simultaneously predicts multiple optimal parameters such as repetition time, flip angle and RF saturation level based on the chemical shift and exchange rate. The sensitivity efficiency-based optimization approach could simplify and guide imaging of CEST agents, including glycogen, glucose, creatine, gamma-aminobutyric acid and glutamate. Copyright © 2016 John Wiley & Sons, Ltd.