High Spatial Resolution Contrast Research Articles

CT image quality and dose optimization by combining tube voltage, dose reduction setting and ASIR-V (explorative study using VCT phantom)

Utilization of ASIR-V software to improve CT scan images with lower exposure factor settings has enormous potential to produce CT scan images with minimal dose and optimal image quality. Otherwise, the excessive use of iterative reconstruction may lead to poor image quality. The purpose of this study was to determine the differences in radiation dose and image quality in the combination of tube voltage, dose reduction and ASIR-V settings and giving recommendation out of it. This type of research is quasi-experimental with a pretest posttest design. VCT Quality Assurance phantom scanned with abdominal CT parameters with the combination of tube voltage variations and dose reduction settings then reconstructed using ASIR-V. Image quality data including noise, LCD and HCR obtained were analyzed by using the paired t-test statistical test. The lowest dose (2.01 mGy) resulted from the combination of tube voltage setting 80 kV, 60% dose reduction, and the dose reduction in the treatment group was in the range of 49% - 87%. The lowest noise was produced by a combination of tube voltage settings of 80 kV, 60% dose reduction, and 100% ASIR-V and noise reduction in the treatment group in the range of 15% -68%. There are significant differences in low contrast detectability of image obtained from 15 combination of tube voltage settings, and dose reduction setting after ASIR-V reconstruction on CT scans. Meanwhile, there are significant differences of extreme contrast spatial resolution in 13 combinations of the tube voltage and dose reduction setting after ASIR-V reconstruction showed. Decreasing the tube voltage and increasing the dose reduction value results in a lesser radiation dose accompanied by a decrease in image quality, while the application of ASIR-V is proven to improve the quality of CT scan images including noise and low contrast detectability, in the other hand the excessive use of ASIR-V may also decrease high contrast spatial resolution of the image. The combination of image quality that is closest to the image quality of the control group is a combination of tube voltage settings of 120 kV, 60% dose reduction and 60% ASIR-V which produces a radiation dose of 6.37 mGy.

Super-resolution deep-learning reconstruction for cardiac CT: impact of radiation dose and focal spot size on task-based image quality.

This study aimed to evaluate the impact of radiation dose and focal spot size on the image quality of super-resolution deep-learning reconstruction (SR-DLR) in comparison with iterative reconstruction (IR) and normal-resolution DLR (NR-DLR) algorithms for cardiac CT. Catphan-700 phantom was scanned on a 320-row scanner at six radiation doses (small and large focal spots at 1.4-4.3 and 5.8-8.8mGy, respectively). Images were reconstructed using hybrid-IR, model-based-IR, NR-DLR, and SR-DLR algorithms. Noise properties were evaluated through plotting noise power spectrum (NPS). Spatial resolution was quantified with task-based transfer function (TTF); Polystyrene, Delrin, and Bone-50% inserts were used for low-, intermediate, and high-contrast spatial resolution. The detectability index (d') was calculated. Image noise, noise texture, edge sharpness of low- and intermediate-contrast objects, delineation of fine high-contrast objects, and overall quality of four reconstructions were visually ranked. Results indicated that among four reconstructions, SR-DLR yielded the lowest noise magnitude and NPS peak, as well as the highest average NPS frequency, TTF50%, d' values, and visual rank at each radiation dose. For all reconstructions, the intermediate- to high-contrast spatial resolution was maximized at 4.3mGy, while the lowest noise magnitude and highest d' were attained at 8.8mGy. SR-DLR at 4.3mGy exhibited superior noise performance, intermediate- to high-contrast spatial resolution, d' values, and visual rank compared to the other reconstructions at 8.8mGy. Therefore, SR-DLR may yield superior diagnostic image quality and facilitate radiation dose reduction compared to the other reconstructions, particularly when combined with small focal spot scanning.

Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI.

To compare a previous model-based image reconstruction (MBIR) with a newly developed deep learning (DL)-based image reconstruction for providing improved signal-to-noise ratio (SNR) in high through-plane resolution (1mm) T2-weighted spin-echo (T2SE) prostate MRI. Large-area contrast and high-contrast spatial resolution of the reconstruction methods were assessed quantitatively in experimental phantom studies. The methods were next evaluated radiologically in 17 subjects at 3.0 Tesla for whom prostate MRI was clinically indicated. For each subject, the axial T2SE raw data were directed to MBIR and to the DL reconstruction at three vendor-provided levels: (L)ow, (M)edium, and (H)igh. Thin-slice images from the four reconstructions were compared using evaluation criteria related to SNR, sharpness, contrast fidelity, and reviewer preference. Results were compared using the Wilcoxon signed-rank test using Bonferroni correction, and inter-reader comparisons were done using the Cohen and Krippendorf tests. Baseline contrast and resolution in phantom studies were equivalent for all four reconstruction pathways as desired. In vivo, all three DL levels (L, M, H) provided improved SNR versus MBIR. For virtually, all other evaluation criteria DL L and M were superior to MBIR. DL L and M were evaluated as superior to DL H in fidelity of contrast. For 44 of the 51 evaluations, the DL M reconstruction was preferred. The deep learning reconstruction method provides significant SNR improvement in thin-slice (1mm) T2SE images of the prostate while retaining image contrast. However, if taken to too high a level (DL High), both radiological sharpness and fidelity of contrast diminish.

The Dose Optimization and Evaluation of Image Quality in the Adult Brain Protocols of Multi-Slice Computed Tomography: A Phantom Study.

Computed tomography examinations have caused high radiation doses for patients, especially for CT scans of the brain. This study aimed to optimize the radiation dose and image quality in adult brain CT protocols. Images were acquired using a Catphan 700 phantom. Radiation doses were recorded as CTDIvol and dose length product (DLP). CT brain protocols were optimized by varying parameters such as kVp, mAs, signal-to-noise ratio (SNR) level, and Clearview iterative reconstruction (IR). The image quality was also evaluated using AutoQA Plus v.1.8.7.0 software. CT number accuracy and linearity had a robust positive correlation with the linear attenuation coefficient (µ) and showed more inaccurate CT numbers when using 80 kVp. The modulation transfer function (MTF) showed a higher value in 100 and 120 kVp protocols (p < 0.001), while high-contrast spatial resolution showed a higher value in 80 and 100 kVp protocols (p < 0.001). Low-contrast detectability and the contrast-to-noise ratio (CNR) tended to increase when using high mAs, SNR, and the Clearview IR protocol. Noise decreased when using a high radiation dose and a high percentage of Clearview IR. CTDIvol and DLP were increased with increasing kVp, mAs, and SNR levels, while the increasing percentage of Clearview did not affect the radiation dose. Optimized protocols, including radiation dose and image quality, should be evaluated to preserve diagnostic capability. The recommended parameter settings include kVp set between 100 and 120 kVp, mAs ranging from 200 to 300 mAs, SNR level within the range of 0.7-1.0, and an iterative reconstruction value of 30% Clearview to 60% or higher.

Physical Image Quality Metrics for the Characterization of X-ray Systems Used in Fluoroscopy-Guided Pediatric Cardiac Interventional Procedures: A Systematic Review.

Pediatric interventional cardiology procedures are essential in diagnosing and treating congenital heart disease in children; however, they raise concerns about potential radiation exposure. Managing radiation doses and assessing image quality in angiographs becomes imperative for safe and effective interventions. This systematic review aims to comprehensively analyze the current understanding of physical image quality metrics relevant for characterizing X-ray systems used in fluoroscopy-guided pediatric cardiac interventional procedures, considering the main factors reported in the literature that influence this outcome. A search in Scopus and Web of Science, using relevant keywords and inclusion/exclusion criteria, yielded 14 relevant articles published between 2000 and 2022. The physical image quality metrics reported were noise, signal-to-noise ratio, contrast, contrast-to-noise ratio, and high-contrast spatial resolution. Various factors influencing image quality were investigated, such as polymethyl methacrylate thickness (often used to simulate water equivalent tissue thickness), operation mode, anti-scatter grid presence, and tube voltage. Objective evaluations using these metrics ensured impartial assessments for main factors affecting image quality, improving the characterization of fluoroscopic X-ray systems, and aiding informed decision making to safeguard pediatric patients during procedures.

Evaluation of the spatial resolution of Gafchromic™ HD-V2 radiochromic film characterized by the modulation transfer function

The Modulation Transfer Function (MTF) characteristics of radiochromic film (RCF) dosimetry with optical systems were evaluated with an RCF, HD-V2, which is transferred with the line patterns of the resolution test chart. In the evaluation using a GT-X980 flatbed scanner, a high contrast spatial resolution with an MTF of ≥0.8 is limited to about 83.3 μm due to artifacts such as scattering of the HD-V2 transmitted light. To achieve high contrast at higher spatial frequencies, a test bench microdensitometer (TBMD) was developed, and its optical performance, dose equivalent response, and spatial resolution characteristics with MTF were evaluated. The TBMD had a minimum readout focal diameter of 13 μm, and its high contrast spatial resolution with an MTF of ≥0.8 is about 11.9 μm. The result that the optical density error increases with decreasing focal diameter in the TBMD supports our hypothesis that these errors are based on the non-uniformity of the shading and surface roughness of the HD-V2 active layer monomers.

Phantom comparison for MRI quality control tests according to manufacturers and national standards

Quality control tests are mandatory and essential to monitor Magnetic Resonance Imaging equipment. These assist in determining improper functioning or parameters below established reference levels. The objective of this study was to perform quality control tests in magnetic resonance imaging equipment and to compare their methodology with both FLUKE and KONEX phantoms. Different protocols were used for their evaluation, including the American Association of Physics in Medicine, the American College of Radiologists, and the Brazilian National Health Surveillance Agency. In this study, we demonstrated the results for the most critical tests: slice thickness accuracy, slice position accuracy, high-contrast spatial resolution, low-contrast resolution, magnetic field, and slice thickness uniformity. The results are that, although both phantom objects are efficient for carrying out the tests required in Brazilian regulations, the KONEX phantom consumes less time, as it requires less to image all its structures. The FLUKE phantoms need a longer acquisition time to obtain all test structures and object images. Nevertheless, the results obtained in both are within limits required by Brazilian regulations and limits suggested by the manufacturers' manuals. This work is expected to be a basis for other physicians and services using similar phantoms.

CT Image Quality Assessment by a Channelized Hotelling Observer: Optimization of Adaptive Statistical Iterative Reconstruction for Radiation Dose Reduction and Improving Image Quality of Pediatric Abdominal CT Scan

Background: Iterative reconstruction (IR) techniques have tried to reduce the radiation dose of computed tomography (CT) scans while maintaining the image quality. One of the IR techniques is the adaptive statistical iterative reconstruction (ASIR). Increasing the amount of ASIR in image reconstruction can lead to the emergence of artifacts and reduce the ability to detect objects with low contrast. Objective: This study aimed to optimize the ASIR technique to reduce the radiation dose and increase image quality in pediatric abdominal CT. Methods: This is a phantom study performed using variable tube current (40,100,140 and 200mA) and ASIR level (ASIR 10% to ASIR 100%). Various criteria including noise, high-contrast spatial resolution, and Channelized Hotelling observer’s model were used to compare image quality at different captured levels. In this study CHO model was used for low contrast detectability. Results: The result was quit promising in the term of CHO’s used for mentioned purposes. The noise of reconstructed images with 30% ASIR and higher levels had a significant difference compared to the reconstructed images by the Filter Back Projection (FBP) method (P &lt; 0.05). The spatial resolution of the images with tube currents of 140, 100, and 40 mA reconstructed with 30, 50, and 80% levels of ASIR technique was equal to 0.8 ± 0.144 pairs of lines per millimeter. The amount of the spatial resolution of images obtained with standard radiation dose and reconstructed by FBP method was 1 pair of lines per mm (p&gt; 0.05). Conclusion: Based on the results of this study, using 50% ASIR for the pediatric population can reduce the radiation dose on abdominal and pelvic CT scans by 50% while maintaining image quality. Furthermore using ASIR 50% only for the reconstruction of abdominal and pelvic images in children at standard radiation dose leads to optimal image quality.

Quality Assessment of Computed Tomography Images using a Channelized Hoteling Observer: Optimization of Protocols in Clinical Practice.

This study investigated the feasibility of channelized hoteling observer (CHO) model in computed tomography (CT) protocol optimization regarding the image quality and patient exposure. While the utility of using model observers such as to optimize the clinical protocol is evident, the pitfalls associated with the use of this method in practice require investigation. This study was performed using variable tube current and adaptive statistical iterative reconstruction (ASIR) level (ASIR 10% to ASIR 100%). Various criteria including noise, high-contrast spatial resolution, CHOs model were used to compare image quality at different captured levels. For the implementation of CHO, we first tuned the model in a restricted dataset and then it to the evaluation of a large dataset of images obtained with different reconstruction ASIR and filtered back projection (FBP) levels. The results were promising in terms of CHO use for the stated purposes. Comparisons of the noise of reconstructed images with 30% ASIR and higher levels of noise in rebuilding images using the FBP approach showed a significant difference (P < 0.05). The spatial resolution obtained using various ASIR levels and tube currents were 0.8 pairs of lines per millimeter, which did not differ significantly from the FBP method (P > 0.05). Based on the results, using 80% ASIR can reduce the radiation dose on lungs, abdomen, and pelvis CT scans while maintaining image quality. Furthermore using ASIR 60% only for the reconstruction of lungs, abdomen, and pelvis images at standard radiation dose leads to optimal image quality.

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.

Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study.

Background and purposeTo investigate the image quality and accurate bone mineral density (BMD) on quantitative CT (QCT) for osteoporosis screening by deep-learning image reconstruction (DLIR) based on a multi-phantom and patient study.Materials and methodsHigh-contrast spatial resolution, low-contrast detectability, modulation function test (MTF), noise power spectrum (NPS), and image noise were evaluated for physical image quality on Caphan 500 phantom. Three calcium hydroxyapatite (HA) inserts were used for accurate BMD measurement on European Spine Phantom (ESP). CT images were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction-veo 50% (ASiR-V50%), and three levels of DLIR(L/M/H). Subjective evaluation of the image high-contrast spatial resolution and low-contrast detectability were compared visually by qualified radiologists, whilst the statistical difference in the objective evaluation of the image high-contrast spatial resolution and low-contrast detectability, image noise, and relative measurement error were compared using one-way analysis of variance (ANOVA). Cohen’s kappa coefficient (k) was performed to determine the interobserver agreement in qualitative evaluation between two radiologists.ResultsOverall, for three levels of DLIR, 50% MTF was about 4.50 (lp/cm), better than FBP (4.12 lp/cm) and ASiR-V50% (4.00 lp/cm); the 2 mm low-contrast object was clearly resolved at a 0.5% contrast level, while 3mm at FBP and ASiR-V50%. As the strength level decreased and radiation dose increased, DLIR at three levels showed a higher NPS peak frequency and lower noise level, leading to leftward and rightward shifts, respectively. Measured L1, L2, and L3 were slightly lower than that of nominal HA inserts (44.8, 95.9, 194.9 versus 50.2, 100.6, 199.2mg/cm3) with a relative measurement error of 9.84%, 4.08%, and 2.60%. Coefficients of variance for the L1, L2, and L3 HA inserts were 1.51%, 1.41%, and 1.18%. DLIR-M and DLIR-H scored significantly better than ASiR-V50% in image noise (4.83 ± 0.34, 4.50 ± 0.50 versus 4.17 ± 0.37), image contrast (4.67 ± 0.73, 4.50 ± 0.70 versus 3.80 ± 0.99), small structure visibility (4.83 ± 0.70, 4.17 ± 0.73 versus 3.83 ± 1.05), image sharpness (3.83 ± 1.12, 3.53 ± 0.90 versus 3.27 ± 1.16), and artifacts (3.83 ± 0.90, 3.42 ± 0.37 versus 3.10 ± 0.83). The CT value, image noise, contrast noise ratio, and image artifacts in DLIR-M and DLIR-H outperformed ASiR-V50% and FBP (P<0.001), whilst it showed no statistically significant between DLIR-L and ASiR-V50% (P>0.05). The prevalence of osteoporosis was 74 (24.67%) in women and 49 (11.79%) in men, whilst the osteoporotic vertebral fracture rate was 26 (8.67%) in women and (5.29%) in men.ConclusionImage quality with DLIR was high-qualified without affecting the accuracy of BMD measurement. It has a potential clinical utility in osteoporosis screening.

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.

A phantom study comparing low-dose CT physical image quality from five different CT scanners.

To systematically evaluate the physical image quality of low-dose computed tomography (LDCT) on CT scanners from 5 different manufacturers using a phantom model. CT images derived from a Catphan 500 phantom were acquired using manufacturer-specific iterative reconstruction (IR) algorithms and deep learning image reconstruction (DLIR) on CT scanners from 5 different manufacturers and compared using filtered back projection with 2 radiation doses of 0.25 and 0.75 mGy. Image high-contrast spatial resolution and image noise were objectively characterized by modulation transfer function (MTF) and noise power spectrum (NPS). Image high-contrast spatial resolution and image low-contrast detectability were compared directly by visual evaluation. CT number linearity and image uniformity were compared with intergroup differences using one-way analysis of variance (ANOVA). The CT number linearity of 4 insert materials were as follows: acrylic (95% CI: 120.35 to 121.27; P=0.134), low-density polyethylene (95% CI: -98.43 to -97.43; P=0.070), air (95% CI: -996.16 to -994.51; P=0.018), and Teflon (95% CI: 984.40 to 986.87; P=0.883). The image uniformity values of GE Healthcare (95% CI: 3.24 to 3.83; P=0.138), Philips (95% CI: 2.62 to 3.70; P=0.299), Siemens (95% CI: 2.10 to 3.59; P=0.054), Minfound (95% CI: 2.35 to 3.65; P=0.589), and Neusoft (95% CI: 2.63 to 3.37; P=0.900) were evaluated and found to be within ±4 Hounsfield units (HU), with a range of 0.99-2.76 HU for standard deviations. There was no statistically significant difference in CT number linearity and image uniformity across the 5 CT scanners under different radiation doses with IR and DLIR algorithms (P>0.05). The resolution level at 10% MTF was 6.98 line-pairs-per-centimeter (lp/cm) on average, which was similar to the subjective evaluation results (mostly up to 7 lp/cm). DLIR at all 3 levels had the highest 50% MTF values among all reconstruction algorithms. For image low-contrast detectability, the minimum diameter of distinguishable contrast holes reached 4 mm at a 0.5% resolution. Increasing the radiation dose and IR strength reduced the image noise and NPS curve peak frequency while improving image low-contrast detectability. This study demonstrated that the image quality of CT scanners from 5 different manufacturers in LDCT is comparable and that the CT number linearity is unbiased and can contribute to accurate bone mineral density quantification.

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

Surgivisio® and O-arm®O2 cone beam CT mobile systems for guidance of lumbar spine surgery: Comparison of patient radiation dose.

To compare patient radiation doses in cone beam computed tomography (CBCT) of two mobile systems used for navigation-assisted mini-invasive orthopedic surgery: O-arm®O2 and Surgivisio®. The study focused on imaging of the spine. Thermoluminescent dosimeters were used to measure organs and effective doses (ED) during CBCT. An ionization-chamber and a solid-state sensor were used to measure the incident air-kerma (Ki) at the center of the CBCT field-of-view and Ki during 2D-imaging, respectively. The PCXMC software was used to calculate patient ED in 2D and CBCT configurations. The image quality in CBCT was evaluated with the CATPHAN phantom. The experimental ED estimate for the low-dose 3D-modes was 2.41 and 0.35mSv with O-arm®O2 (Low Dose 3D-small-abdomen) and Surgivisio® (3DSU-91 images), respectively. PCXMC results were consistent: 1.54 and 0.30mSv. Organ doses were 5 to 12 times lower with Surgivisio®. Ki at patient skin were comparable on lateral 2D-imaging (0.5mGy), but lower with O-arm®O2 on anteroposterior (0.3 versus 0.9mGy). Both systems show poor low contrast resolution and similar high contrast spatial resolution (7 line-pairs/cm). This study is the first to evaluate patient ED and organ doses with Surgivisio®. A significant difference in organs doses was observed between the CBCT systems. The study demonstrates that Surgivisio® used on spine delivers approximately five to six times less patient ED, compared to O-arm®O2, in low dose 3D-modes. Doses in 2D-mode preceding CBCT were higher with Surgivisio®, but negligible compared to CBCT doses under the experimental conditions tested.

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.

Development of ACR quality control procedure for automatic assessment of spatial metrics in MRI

Quality control of Magnetic Resonance Imaging (MRI) equipment based on the American College of Radiology (ACR) protocol is a crucial tool for assuring the optimal functionality of the MRI scanner. This protocol includes the test of several parameters in particular spatial properties such as Slice position accuracy, high-contrast spatial resolution, and slice thickness accuracy. Those parameters are usually evaluated visually and manually using a workstation. As we know that Visual assessment is operator dependant and results may vary, so making the process automatic will reduce the errors and improve the accuracy. We propose in this study an automatic algorithm which is able to extract the three spatial proprieties. We tested our automated quality control process on ten MRI scanners. We assessed the performance of the proposed pipeline by comparing the measurements with the manual analysis made by three experienced MRI technologists. We also compared the results against the recommended values provided by the ACR quality assurance manual. Afterward, all data sets are quantitatively evaluated using the Pearson test by computing the correlation coefficient and the p-value. The comparison between our automatic quantitative algorithm and manual evaluation confirms the effectiveness of the proposed approaches. Accordingly, the results of the Pearson test showed that automated analysis correlated highly with manual analysis and the P-value was less than the significance level of 0.05. An interesting finding was that the total analysis time was significantly shorter than the time needed for manual analysis.

A Novel Phantom and a Dedicated Developed Software for Image Quality Controls in X-Ray Intraoral Devices.

Background: Periodic quality control (QC) procedures are important in order to guarantee the image quality of radiological equipment and are also conducted using phantoms simulating human body. Objective: To perform (QC) measurements in intraoral imaging devices, a new and simple phantom was manufactured. Besides, to simplify QC procedures, computerized LabView-based software has been devised, enabling determination of image quantitative parameters in real time or during post processing.Material and Methods: In this experimental study, the novel developed phantom consists of a Polymethyl methacrylate (PMMA) circular insert. It is able to perform a complete QC image program of X-ray intraoral equipment and also causes the evaluation of image uniformity, high and low contrast spatial resolution, image linearity and artefacts, with only two exposures. Results: Three raters analyzed the images using the LabView dedicated software and determined the quantitative and qualitative parameters in an innovative and accurate way. Statistical analysis evaluated the reliability of this study. Good accuracy of the quantitative and qualitative measurements for the different intraoral systems was obtained and no statistical differences were found using the inter-rater analysis. Conclusion: The achieved results and the related statistical analysis showed the validity of this methodology, which could be proposed as an alternative to the commonly adopted procedures, and suggested that the novel phantom, coupled with the LabView based software, could be considered as an effective tool to carry out a QC image program in a reproducible manner.

VARIASI PENGGUNAAN REKONTRUSI ALGORITMA FBP, iDose4 DAN ITERATIVE MODEL RECONTRUCTION (IMR) TERHADAP KUALITAS CITRA MCST THORAK LOW DOSE UNTUK MENDETEKSI NODUL PARU

Background: Pulmonary nodules are often found accidentally when thorax imaging is done. The size and rate of nodule growth are the most important predictors of imaging for malignancy. When the low dose protocol applied to the thorax MSCT will affect image quality, such as increased noise and decreased spatial resolution, so that the detection of nodules becomes less accurate. For noise limitation the reconstruction of the FBP, iDose4 and IMR algorithm is used. The purpose of this literature study is to evaluate variations in the FBP, iDose4 and IMR algorithm in improving image quality.&#x0D; Methods: This method is a qualitative research with a descriptive approach using comprehensive literatures studies&#x0D; Results: The result show that noise reduction is highest at IMR and lowest at FBP. The highest number of detected nodules on IMR especially for solid nodules &lt; 4 mm and the lowest on FBP. Pathological findings with the best quality on IMR and quality are limited to FBP. Visibility of normal and abnormal findings, iDose4 is better than IMR and FBP especially for reticular patterns. Effective doses are reduced by 44 % to 59 % based on this literature study. In clinical practice, IMR shows the potential for pathological recovery at low dose level and IMR can improved measured image quality based on noise, high contrast spatial resolution and low contrast detectability.&#x0D; Conclusion: So IMR is the most effective algorithm applied for scanning low dose MSCT thorax for detection of pulmonary nodules.

Noise and spatial resolution properties of a commercially available deep learning-based CT reconstruction algorithm.

To characterize the noise and spatial resolution properties of a commercially available deep learning-based computed tomography (CT) reconstruction algorithm. Two phantom experiments were performed. The first used a multisized image quality phantom (Mercury v3.0, Duke University) imaged at five radiation dose levels (CTDIvol : 0.9, 1.2, 3.6, 7.0, and 22.3mGy) with a fixed tube current technique on a commercial CT scanner (GE Revolution CT). Images were reconstructed with conventional (FBP), iterative (GE ASiR-V), and deep learning-based (GE True Fidelity) reconstruction algorithms. Noise power spectrum (NPS), high-contrast (air-polyethylene interface), and intermediate-contrast (water-polyethylene interface) task transfer functions (TTF) were measured for each dose level and phantom size and summarized in terms of average noise frequency (fav ) and frequency at which the TTF was reduced to 50% (f50% ), respectively. The second experiment used a custom phantom with low-contrast rods and lung texture sections for the assessment of low-contrast TTF and noise spatial distribution. The phantom was imaged at five dose levels (CTDIvol : 1.0, 2.1, 3.0, 6.0, and 10.0mGy) with 20 repeated scans at each dose, and images reconstructed with the same reconstruction algorithms. The local noise stationarity was assessed by generating spatial noise maps from the ensemble of repeated images and computing a noise inhomogeneity index, , following AAPM TG233 methods. All measurements were compared among the algorithms. Compared to FBP, noise magnitude was reduced on average (± one standard deviation) by 74±6% and 68±4% for ASiR-V (at "100%" setting) and True Fidelity (at "High" setting), respectively. The noise texture from ASiR-V had substantially lower noise frequency content with 55±4% lower NPS fav compared to FBP while True Fidelity had only marginally different noise frequency content with 9±5% lower NPS fav compared to FBP. Both ASiR-V and True Fidelity demonstrated locally nonstationary noise in a lung texture background at all radiation dose levels, with higher noise near high-contrast edges of vessels and lower noise in uniform regions. At the 1.0mGy dose level values were 314% and 271% higher in ASiR-V and True Fidelity compared to FBP, respectively. High-contrast spatial resolution was similar between all algorithms for all dose levels and phantom sizes (<3% difference in TTF f50% ). Compared to FBP, low-contrast spatial resolution was lower for ASiR-V and True Fidelity with a reduction of TTF f50% of up to 42% and 36%, respectively. The deep learning-based CT reconstruction demonstrated a strong noise magnitude reduction compared to FBP while maintaining similar noise texture and high-contrast spatial resolution. However, the algorithm resulted in images with a locally nonstationary noise in lung textured backgrounds and had somewhat degraded low-contrast spatial resolution similar to what has been observed in currently available iterative reconstruction techniques.