Detection Of Low-contrast Objects Research Articles

Detection of low-contrast objects by electrical prospecting methods

Many geological problems cannot be solved by electrical prospecting methods. Often the reason for this is a slight difference in the electrical resistivity of target objects from that of the host medium. At the same time, the use of the transverse magnetic (TM) type field makes it possible to identify low-contrast objects and delineate their boundaries with high accuracy. TM-type prospecting is more efficient since its signal is much more strongly affected by changes in resistivity and other electrodynamic parameters. The article examines one of the difficult cases – a search for kimberlite pipes in Yakutia. Such objects differ very little from the host medium in terms of the horizontal resistivity. Exploration works to search for kimberlite pipes in Yakutia, carried out by conventional electrical prospecting methods, have many problems. The article considers the results of successful TM-type prospecting field surveys where kimberlite pipes stood out very prominently. Also presented are the results of modeling an even more complex situation in which the pipes are located at depths of over 140 m and overlain by traps; there are many objects in the area that create additional anomalies.

Surface topography detection based on an optical differential metasurface.

Surface topography detection can extract critical characteristics from objects, playing an important role in target identification and precision measurement. Here, an optical method with the advantages of low power consumption, high speed, and simple devices is proposed to realize the surface topography detection of low-contrast phase objects. By constructing reflected light paths, a metasurface can perform spatial differential operation via receiving the light directly reflected from a target. Therefore, our scheme is experimentally demonstrated as having remarkable universality, which can be used not only for opaque objects, but also for transparent pure phase objects. It provides a new, to the best of our knowledge, application for optical differential metasurfaces in precise detection of microscale surface topography.

UNet and MobileNet CNN-based model observers for CT protocol optimization: comparative performance evaluation by means of phantom CT images.

The aim of this work is the development and characterization of a model observer (MO) based on convolutional neural networks (CNNs), trained to mimic human observers in image evaluation in terms of detection and localization of low-contrast objects in CT scans acquired on a reference phantom. The final goal is automatic image quality evaluation and CT protocol optimization to fulfill the ALARA principle. Preliminary work was carried out to collect localization confidence ratings of human observers for signal presence/absence from a dataset of 30,000 CT images acquired on a PolyMethyl MethAcrylate phantom containing inserts filled with iodinated contrast media at different concentrations. The collected data were used to generate the labels for the training of the artificial neural networks. We developed and compared two CNN architectures based respectively on Unet and MobileNetV2, specifically adapted to achieve the double tasks of classification and localization. The CNN evaluation was performed by computing the area under localization-ROC curve (LAUC) and accuracy metrics on the test dataset. The mean of absolute percentage error between the LAUC of the human observer and MO was found to be below 5% for the most significative test data subsets. An elevated inter-rater agreement was achieved in terms of S-statistics and other common statistical indices. Very good agreement was measured between the human observer and MO, as well as between the performance of the two algorithms. Therefore, this work is highly supportive of the feasibility of employing CNN-MO combined with a specifically designed phantom for CT protocol optimization programs.

Image quality comparisons of coil setups in 3T MRI for brain and head and neck radiotherapy simulations.

MRI is increasingly used for brain and head and neck radiotherapy treatment planning due to its superior soft tissue contrast. Flexible array coils can be arranged to encompass treatment immobilization devices, which do not fit in diagnostic head/neck coils. Selecting a flexible coil arrangement to replace a diagnostic coil should rely on image quality characteristics and patient comfort. We compared image quality obtained with a custom UltraFlexLarge18 (UFL18) coil setup against a commercial FlexLarge4 (FL4) coil arrangement, relative to a diagnostic Head/Neck20 (HN20) coil at 3T. The large American College of Radiology (ACR) MRI phantom was scanned monthly in the UFL18, FL4, and HN20 coil setup over 2 years, using the ACR series and three clinical sequences. High-contrast spatial resolution (HCSR), image intensity uniformity (IIU), percent-signal ghosting (PSG), low-contrast object detectability (LCOD), signal-to-noise ratio (SNR), and geometric accuracy were calculated according to ACR recommendations for each series and coil arrangement. Five healthy volunteers were scanned with the clinical sequences in all three coil setups. SNR, contrast-to-noise ratio (CNR) and artifact size were extracted from regions-of-interest along the head for each sequence and coil setup. For both experiments, ratios of image quality parameters obtained with UFL18 or FL4 over those from HN20 were formed for each coil setup, grouping the ACR and clinical sequences. Wilcoxon rank-sum tests revealed significantly higher (p<0.001) LCOD, IIU and SNR, and lower PSG ratios with UFL18 than FL4 on the phantom for the clinical sequences, with opposite PSG and SNR trends for the ACR series. Similar statistical tests on volunteer data corroborated that SNR ratios with UFL18 (0.58±0.19) were significantly higher (p<0.001) than with FL4 (0.51±0.18) relative to HN20. The custom UFL18 coil setup was selected for clinical application in MR simulations due to the superior image quality demonstrated on a phantom and volunteers for clinical sequences and increased volunteer comfort.

Computational scatter correction in near real-time with a fast Monte Carlo photon transport model for high-resolution flat-panel CT

In computed tomography (CT), scattering causes server quality degradation of the reconstructed CT images by introducing streaks and cupping artifacts which reduce the detectability of low contrast objects. Monte Carlo (MC) simulation is considered the most accurate approach for scatter estimation. However, the existing MC estimators are computationally expensive, especially for high-resolution flat-panel CT. In this paper, we propose a fast and accurate MC photon transport model which describes the physics within the 1 keV to 1 MeV range using multiple controllable key parameters. Based on this model, scatter computation for a single projection can be completed within a range of a few seconds under well-defined model parameters. Smoothing and interpolation are performed on the estimated scatter to accelerate the scatter calculation without compromising accuracy too much compared to measured near scatter-free projection images. Combining the fast scatter estimation with the filtered backprojection (FBP), scatter correction is performed effectively in an iterative manner. To evaluate the proposed MC model, we have conducted extensive experiments on the simulated data and real-world high-resolution flat-panel CT. Compared to the state-of-the-art MC simulators, the proposed MC model achieved a 15times acceleration on a single-GPU compared to the GPU implementation of the Penelope simulator (MCGPU) utilizing several acceleration techniques, and a 202 times speed-up on a multi-GPU system compared to the multi-threaded state-of-the-art EGSnrc MC simulator. Furthermore, it is shown that for high-resolution images, scatter correction with sufficient accuracy is accomplished within one to three iterations using a FBP and the proposed fast MC photon transport model.

An evaluation of quality assurance guidelines comparing the American College of Radiology and American Association of Physicists in Medicine task group 284 for magnetic resonance simulation.

PurposeThe purpose of this study was to evaluate similarities and differences in quality assurance (QA) guidelines for a conventional diagnostic magnetic resonance (MR) system and a MR simulator (MR‐SIM) system used for radiotherapy.MethodsIn this study, we compared QA testing guidelines from the American College of Radiology (ACR) MR Quality Control (MR QC) Manual to the QA section of the American Association of Physicists in Medicine (AAPM) Task Group 284 report (TG‐284). Differences and similarities were identified in testing scope, frequency, and tolerances. QA testing results from an ACR accredited clinical diagnostic MR system following ACR MR QC instructions were then evaluated using TG‐284 tolerances.ResultsFive tests from the ACR MR QC Manual were not included in TG‐284. Five new tests were identified for MR‐SIM systems in TG‐284 and pertained exclusively to the external laser positioning system of MR‐SIM systems. “Low‐contrast object detectability” (LCD), “table motion smoothness and accuracy,” “transmitter gain,” and “geometric accuracy” tests differed between the two QA guides. Tighter tolerances were required in TG‐284 for “table motion smoothness and accuracy” and “low contrast object detectability.” “Transmitter gain” tolerance was dependent on initial baseline measurements, and TG‐284 required that geometric accuracy be tested over a larger field of view than the ACR testing method. All tests from the ACR MR QC Manual for a conventional MR system passed ACR tolerances. The T2‐weighted image acquired with ACR sequences failed the 40‐spoke requirement from TG‐284, transmitter gain was at the 5% tolerance of TG‐284, and geometric accuracy could not be evaluated because of required equipment differences. Table motion passed both TG‐284 and ACR required tolerances.ConclusionOur study evaluated QA guidelines for an MR‐SIM and demonstrated the additional QA requirements of a clinical diagnostic MR system to be used as an MR‐SIM in radiotherapy as recommended by TG‐284.

Assessing the performance of 360[formula omitted] ultrasound probes designed for endoanal ultrasound

A bespoke phantom has been designed, with clinically relevant features for endoanal ultrasound (EAUS), capable of rigorously assessing the performance of 360∘ ultrasound probes.The performance of three, commercially available, anorectal probes, capable of producing both 2D and 3D images, was assessed. One of the probes was also assessed in two states: before failure and after a repair to correct a failure. For each probe the signal to noise ratio (SNR), contrast to noise ratio (CNR), penetration depth, resolution, focus depth, distance accuracy and low contrast object detectability (LCOD) were assessed at varying dynamic ranges, receive gains and operating frequencies. A Python program (SAUQA) was developed to semi-automate the analysis.In general the measured parameters varied as expected. However, at intermediate receive gains, adjusting the receive gain resulted in the SNR, CNR, penetration depth and LCOD varying in an unexpected manner. The reason for this is not known, but because it was exhibited by all probes it is believed to be related to the ultrasound machine itself and/or an inherent characteristic of the probe design.The quantitative results suggest that all probes tested offer an effective method of assessing the integrity of the Internal Anal Sphincter (IAS) and the repair of the probe appears to have been successful. However, differences between the probes were observed both quantitatively and qualitatively, with the original probe providing the best results for EAUS.In light of the results, a recommendation was made, to the EAUS service at University Hospitals Dorset, to adjust the default machine start-up settings for EAUS.

Comparison of a Zero-filling Interpolation with a Real Matrix Size at 1.5 Tesla Based on Spin-echo Weighted Imaging with Various Spatial Resolutions: An ACR Phantom Study

This study aimed to assess the effect of zero-filling interpolation (ZIP) and various spatial resolutions on quality assurance (QA). Two important variables for the assessments of magnetic resonance image quality were included with recommended acceptance criteria: high-contrast spatial resolution and low-contrast object detectability with reference limits. All acquired data were divided into two groups: group A (without ZIP) and group B (with ZIP). The spatial resolutions of both images of T1-weighted and T2-weighted imaging in both directions fulfilled the American College of Radiology (ACR) criterion in group B. The observed high-contrast spatial resolution values were significantly different between the two groups up to a matrix size of 320 × 320 (p 0.05). On the other hand, with a matrix size ≥ 384 × 384, no significant differences between the two groups were observed in terms of high-contrast spatial resolution (p 0.05). For low-contrast object detectability, the total number of measured spokes in all groups fulfilled the ACR criterion. However, the low-contrast object detectability values without ZIP tended to decrease as the matrix size decreased. The use of ZIP can improve high-contrast spatial resolution and low-contrast object detectability while reducing image blurriness.

Detection of Multi-Pixel Low Contrast Object on a Real Sea Surface

Video images captured at long range often show low-contrast floating objects of interest on a sea surface. A comparative experimental study of the statistical characteristics of reflections from floating objects and from the agitated sea surface showed differences in the correlation and spectral characteristics of these reflections. The functioning of the recently proposed modified matched subspace detector (MMSD) is based on the separation of the observed data spectrum on two subspaces: relatively low and relatively high frequencies. In the literature, the MMSD performance has been evaluated in general and using only a sea model (i.e., additive Gaussian background clutter). This paper extends the performance evaluating methodology for low contrast object detection using only a real sea dataset. The methodology assumes an object of low contrast if the mean and variance of the object and the surrounding background are the same. The paper assumes that the energy spectrum of the object and the sea are different. The paper investigates a scenario in which an artificially created model of a floating object with specified statistical parameters is placed on the surface of a real sea image. The paper compares the efficiency of the classical matched subspace detector (MSD) and MMSD for detecting low-contrast objects on the sea surface. The article analyzes the dependence of the detection probability at a fixed false alarm probability on the difference between the statistical means and variances of a floating object and the surrounding sea.

PROPELLER (periodically rotated overlapping parallel lines) Comparable Image Quality to the Conventional Cartesian Magnetic Resonance Images: A Phantom Study

To the best of our knowledge, studies comparing PROPELLER and the conventional Cartesian MRI have mostly been reported on motion sensitivity, and there has been no focused study on the standard phantom imaging to compare them. The purpose of this study was to investigate the effect of PROPELLER method on ACR guideline QA protocol compared to Cartesian method. In this study, we compared the ACR phantom image quality of T2WI acquired on PROPELLER and conventional Cartesian method. In addition, we performed comparisons using different AFs (acceleration factors). For quantitative analysis SNR, geometric accuracy, high-contrast spatial resolution, slice thickness accuracy, slice position accuracy and low-contrast object detectability were measured on the acquired images. There were no statistically significant differences in the 6 quantification values for both methods (p 0.05). In conclusion, we found that PROPELLER method provided a comparable SNR to Cartesian method, regardless of the various Afs

Health and safety control measures and MR quality control results in the MRI units of two public hospitals within the Mangaung metropolitan

This study aimed to identify risks and hazards in the magnetic resonance imaging (MRI) units, and assess the quality compliance of the scanners within two public hospitals in Mangaung. This is a follow-up study from a previously published study that measured static magnetic fields and radiofrequency magnetic fields in the MRI units included here. An observational checklist was used to identify risks and hazards which were later fed into a baseline risk assessment to classify and review existing control measures in the MRI units of hospitals A and B. The availability of MRI Health and Safety measures were benchmarked against the latest American College of Radiology (ACR) MRI safety requirements. The probability of risk occurrence and severity of hazards were assigned a score ranging from improbable (1) to very likely (5) and minimal (1) to irreversible effect (5). The weekly quality control test results obtained from both units were measured against the ACR quality control acceptable criteria. Similar risks were observed in both MRI units but the multiplication of probability and consequence in all risk categories resulted in a moderate risk-rating score of 12.3 for hospital A and 13.1 for hospital B. Lack of demarcation of four MRI safety zones, ferromagnetic detectors, 5-gauss line, and access control in both units scored above 15 and were classified as high risk. The defective air-cooling systems influenced the temperature of the scanner room, which affected the apparent diffusion coefficient (ADC) measurements performed from 1.5 T Siemens. On a 3.0 T Philips, a low contrast object detectability had 29 spokes for ACR T2, while the percent integral uniformity for image intensity uniformity was 78.2 %. High and moderate risks observed in both units could be reduced by the implementation of an effective health and safety programme. The ambient temperature within the scanner room should be maintained at 21 °C to attain well-performing ADC measurements and RF subsystems should be visually inspected and maintained regularly to obtain optimal image quality.

Technical Note: Validation of an automatic ACR phantom quality assurance tool for an MR-guided radiotherapy system.

To modify and evaluate an automatic American College of Radiology (ACR) phantom analysis toolbox for ACR quality assurance (QA) on a low-field MR-guided radiotherapy system (ViewRay). An open-source toolbox was modified for ACR QA of a 0.35T MRI system (ViewRay MRIdian). A total of 17 ACR datasets were evaluated, including 10 datasets acquired from different systems across the world, and seven datasets acquired at our center between 2014 and 2020. All required ACR tests, geometric accuracy (GA), high-contrast spatial resolution (HCSR), slice thickness accuracy (ST), slice position accuracy (SP), percent integral uniformity (PIU), percentage signal ghosting (PSG), and low-contrast object detectability (LCOD), were assessed manually and using the toolbox automatically. Measurements between manual and automatic analysis were compared. Precision, recall, and accuracy were calculated, where the manual results were used as the ground truth. The software took less than 2min to complete all seven tests, which usually requires 40min or more if analyzed manually. Overall, the automatic measurement was consistent with the manual result. The absolute differences between the two measurements were 0.72±0.66 (mm), 0.01±0.03, 0.50±0.60 (mm), 0.39±0.41 (mm), 1.01±1.00 (%), 0.0016±0.0019, and 2.79±2.29 for the seven tests. The precision of the automatic toolbox was 100% for all tests, indicating that a test would 100% pass a manual analysis if it had passed the automatic analysis. Recall and accuracy were≥96% for GA, HCSR, SP, PIU, PSG, and LCOD tests, and 91% for the ST test. An automatic ACR QA tool was adopted and evaluated for the low-field MR-guided radiotherapy (MRgRT) system. Overall, the toolbox provided comparable results as manual analysis, and reduced the processing time from over 40min to <2min. This toolbox holds the potential to be widely adopted either as a second check tool or partially replace human measurement for MRgRT programs using the same system.

72. Digital breast tomosynthesis: Flat panel and photon counting detector comparison

Purpose In this study three digital breast tomosynthesis (DBT) devices equipped with different flat panel detectors (FPD) and a prototype equipped with a scan-spectral photon counting detector (PCD) are compared. The aim is to evaluate if a PCD device can guarantee a comparable or even better image quality delivering lower radiation doses than FPD devices. Methods Image quality performances were evaluated exposing two image quality DBT phantoms, Tomophan and Agatha and a homemade phantom for the evaluation of low contrast detectability (LCD). Exposures were performed in automatic exposure control (AEC) mode, both with standard (ST) and high resolution (HR) modality when available. Images with the lowest achievable post-processing were analyzed. Geometric distortion, signal-difference-to-noise ratio (SDNR), LCD with the statistical method, in-plane resolution in terms of modulation transfer function (MTF) in scan and sub-scan directions, slice-sensitivity profile (SSP) and artifact spread function (ASF) were evaluated. Results Geometric distortion resulted comparable between PCD and FPD devices. SDNR for PCD was comparable to two of the FDP devices. PCD device showed the best LCD. In-plane resolution was higher for PCD device: FPD devices exhibit a reduction in MTF 10% between 38% and 62%, both in scan and sub-scan direction. SSP evaluation showed comparable results for PCD and one of the FPD devices, while it was up to 60% worse for the others. PCD device showed a slightly worse ASF compared to FPD devices. Delivered dose in AEC with PCD device was 50% lower than doses delivered with FPD devices. Conclusions PCD device ensures a comparable or even better image quality than FPD devices, especially for spatial resolution and detectability of low contrast objects, delivering much lower radiation dose. Photon counting seems to be really an impressive approach to DBT. Download : Download high-res image (129KB) Download : Download full-size image

OA160] A simple method for low contrast detectability, image quality and dose optimization with CT iterative reconstruction algorithms and model observers

Purpose The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Methods Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four alternative forced-choice test) and model observers were performed across the various images. Results Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. Conclusions IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low contrast detection tasks and in dose optimization.

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers

BackgroundThe aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment.MethodsImages of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images.ResultsCompared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result.ConclusionIR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

Image quality assessment of a 1.5T dedicated magnetic resonance-simulator for radiotherapy with a flexible radio frequency coil setting using the standard American College of Radiology magnetic resonance imaging phantom test.

A flexible RF coil setting has to be used on an MR-simulator (MR-sim) in the head and neck simulation scan for radiotherapy (RT) purpose, while the image quality might be compromised due to the sub-optimized flexible coil compared to the normal diagnostic radiological (DR) head coil. In this study, we assessed the image quality of an MR-sim by conducting the standard American College of Radiology (ACR) MRI phantom test on a 1.5T MR-sim under RT-setting and comparing it to DR-setting. A large ACR MRI phantom was carefully positioned, aligned and scanned 9 times for each under RT- and DR-setting on a 1.5T MR-sim, following the ACR scanning instruction. Images were analyzed following the ACR guidance. Measurement results under two coil settings were quantitatively compared. Inter-observer disagreements under RT-setting between two physicists were compared using Bland-Altman (BA) analysis and intra-class correlation coefficient (ICC). The MR-sim with RT-setting obtained sufficiently good image quality to pass all ACR recommended criteria. No significant difference was found in phantom length accuracy, high-contrast spatial resolution, slice thickness accuracy, slice position accuracy, and percent-signal ghosting. RT-setting significantly under-performed in low-contrast object detectability, while better performed in image intensity uniformity. BA analysis showed that 95% limit of agreement and biases of phantom test measurement under RT-setting between two observers were very small. Excellent inter-observer agreement (ICC >0.75) was achieved in all measurements except for slice thickness accuracy (ICC =0.42, moderate agreement) under RT-setting. Very good and highly reproducible image quality could be achieved on a 1.5T MR-sim with a flexible coil setting as revealed by the standard ACR MRI phantom test. The flexible RT-setting compromised in image signal-to-noise ratio (SNR) compared to the normal DR-setting, and resulted in reduced low-contrast object detectability.

The effect of quality control on the function of magnetic resonance imaging (MRI), using American College of Radiology (ACR) phantom

ObjectiveTo study image quality of MRI scanner using the American College of Radiology (ACR) phantom. Material and methodsImage quality of 1.5T MRI scanner was tested using ACR phantom. A standard head coil with standard restraints was used to fix the phantom head position. The phantom included seven modules for measuring MRI scanner image quality. MRI images for each module were analyzed. ResultsFor the Geometric accuracy test the inside length of the phantom was 146mm and the inside diameter was 189.4mm. For the High-contrast spatial resolution, individual small bright spots on the image were three pairs of hole arrays and were distinguishable. For the slice thickness test, the top signal ramp length was 54.4mm and bottom signal ramp length was 54.8mm so the slice thickness was 5.46mm. For the slice position accuracy, the bar length differences of intensity uniformity a value, called percent integral uniformity (PIU), was 96.15%. For the percent-signal ghosting, ghosting ratio was 0.0002. For the low contrast object detectability, the sum of numbers of complete spokes scored was 30 spokes. ConclusionsImage quality tests were very important in acceptance of any MRI scanner after installation and during maintenance. Using ACR phantom, these tests approve that the image parameters are acceptable.

Basic quality control in routine MRI

Aim Magnetic Resonance Imaging (MRI) has evolved a valid clinical tool in everyday practice. Its unique capabilities of imaging soft tissue human anatomy and physiology with excellent spatial, temporal and contrast resolution explain its outstanding role in clinical imaging. The aim of this lecture is to present the rationale of Quality Control (QC) and Quality Assurance (QA) in MRI and to briefly present a set of basic QC tests that can ensure MRI system’s performance and help on maintain diagnostic quality in routine clinical MRI examinations. Learning objectives • Understand the general rationale of QC and QA in MRI. • Presentation of the AAPM 100 protocol. Basic procedures and methodologies. • Presentation of accredited phantoms and tools used for basic QC and QA in MRI. • Presentation of a set of basic QC tests for assessing MRI system’s performance based solely on simple imaging post-processing methods. This will include assessments of the following system’s parameters: – H0 static field homogeneity – Signal to Noise (SNR) and Contrast to Noise (CNR) measurements – Spatial Uniformity of SNR – Chosting Ratio and MR image uniformity – Geometric Distortion and Spatial Linearity – Slice thickness – High Contrast Spatial Resolution – Low Contrast Object Detectability

Impact of iterative reconstructions on image noise and low-contrast object detection in low kVp simulated abdominal CT: a phantom study.

Low kilovoltage (kVp) computed tomography (CT) may be used to reduce contrast medium dose in patients at risk of contrast nephropathy, at the cost of increased image noise. To evaluate: (i) the impact of iterative reconstructions (Siemens SAFIRE) on low-contrast object detection to compensate for increased noise instead of increased tube loading when decreasing tube potential; and (ii) the change in iodine attenuation in simulated abdominal CT. A phantom was scanned at 70, 80, 100, and 120 kVp at fixed effective tube loading (170 mAsEFF) and fixed radiation dose (CTDIVOL 10 mGy). Images were reconstructed with filtered back-projection (FBP) and SAFIRE strengths S1-S5. Iodine attenuation, objective image noise, contrast-to-noise ratio (CNR), noise power spectrum (NPS), spatial resolution, and subjective detectability of low-contrast objects were evaluated. Compared with 120 kVp iodine attenuation increased by a factor 1.6 and 2.0, and image noise increased by a factor 1.9 and 2.5 at 80 and 70 kVp, respectively. Compared with FBP, SAFIRE showed objective reduction in image noise and increased CNR without loss of spatial resolution or any significant NPS alteration, with general tendency to improve subjective detectability of low-contrast objects. At 170 mAsEFF the number of discernible 1.0% contrast objects at 70 kVp/S5 and 80 kVp/S5 was similar to that at 120 kVp/FBP. With the SAFIRE algorithm image noise, CNR and detectability of low-contrast objects may be kept unchanged without increased tube loading when using low kVp settings to reduce contrast medium dose in azotemic patients.

SU‐F‐J‐159: Influence of the Elevated Posterior Position by Using the Customized Vacuum‐Bag On the Abdominal MR Image Quality: A Quantitative Phantom Study

Purpose:Signal‐to‐noise ratio(SNR) of MR abdominal imaging in diagnostic radiology is maximized by minimizing the coil‐to‐patient distance. However, for radiotherapy applications, customized vacuum‐bag is needed for abdominal immobilization at the cost of the increasing distance to the posterior spine coil. This sub‐optimized coil setting for RT applications may compromise image quality, such as SNR and homogeneity, thus potentially affect tissue delineation. In this study, we quantitatively evaluate the effect of the vertical position change on SNR and image quality change using an ACR MR phantom.Methods:An ACR MR phantom was placed on the flat couch top. Images were acquired using an 18‐channel body array coil and spine coil on a dedicated 1.5T MR‐simulator. The scan was repeated three times with the ACR phantom elevated up to 7.5cm from the couch top, with a step size of 2.5cm. All images were acquired using standard ACR test sequence protocol of 2D spin‐echo T1‐weighted(TR/TE=500/200ms) and T2‐weighted(TR/TE1/TE2=2000/20/80) sequences. For all scans, pre‐scan normalization was turned on, and the distance between the phantom and the anterior 18‐channel body array coil was kept constant. SNR was calculated using the slice with a large water‐only region of the phantom. Percent intensity uniformity(PIU) and low contrast object detectability(LCD) were assessed by following ACR test guidelines.Results:The decrease in image SNR(from 335.8 to 169.3) and LCD(T1: from 31 to 19 spokes, T2: 26 to 16 spokes) were observed with increasing vertical distance. After elevating the phantom by 2.5cm(approximately the thickness of standard vacuum‐bag), SNR change(from 335.8 to 275.5) and LCD(T1: 31 to 26 spokes, T2: 26 to 21 spokes) change were noted. However, similar PIU was obtained for all choices of vertical distance (T1: 94.5%–95.0%, T2: 94.4%–96.8%).Conclusion:After elevating the scan object, reduction in SNR level and contrast detectability but no change in image homogeneity was observed.