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

Evaluation of Radiation Dose and Image Quality in Clinical Routine Protocols from Three Different CT Scanners

Computed tomography examination plays a vital role in imaging and its use has rapidly increased in radiology diagnosis. This study aimed to assess radiation doses of routine CT protocols of the brain, chest, and abdomen in three different CT scanners, together with a qualitative image quality assessment.

METHODS

A picture archiving and communication system (PACS) and Radimetrics software version 3.4.2 retrospectively collected patients' radiation doses. Radiation doses were recorded as the CTDIvol, dose length product, and effective dose. CT images were acquired using the Catphan700 phantom to evaluate image quality.

RESULTS

The findings revealed that median values for the CTDIvol and DLP across the brain, chest, and abdomen protocols were lower than the national and international DRLs. Effective doses for brain, chest, and abdomen protocols were also below the median value of R. Smith-Bindman. Neusoft achieved higher spatial frequencies in brain protocols, while Siemens outperformed others in chest protocols. Neusoft consistently exhibited superior high-contrast resolution. Siemens and Neusoft outperformed low-contrast detectability, while Siemens also outperformed the contrast-to-noise ratio. In addition, Siemens had the lowest image noise in brain protocols and high uniformity in chest and abdomen protocols. Neusoft showed the lowest noise in chest and abdomen protocols and high uniformity in the brain protocol. The noise power spectrum revealed that Philips had the highest noise magnitude with different noise textures across protocols and scanners.

CONCLUSIONS

This study provides a comprehensive evaluation of radiation doses and image quality for three different CT scanners using standard clinical protocols. Almost all CT protocols exhibited radiation doses below the DRLs and demonstrated varying image qualities across each protocol and scanner. Selecting the right CT scanner for each protocol is essential to ensure that the CT images exhibit the best quality among a wide range of CT machines. The MTF, HCR, LCD, CNR, NPS, noise, and uniformity are suitable parameters for evaluating and monitoring image quality.

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.

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

Background

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.

Materials and Methods

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.

Results

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).

Conclusions

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.

Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms

BACKGROUND

The effect of region of interest (ROI) size variation on producing accurate noise levels is not yet studied.

OBJECTIVE

This study aimed to evaluate the influence of ROI sizes on the accuracy of noise measurement in computed tomography (CT) by using images of a computational and American College of Radiology (ACR) phantoms.

MATERIAL AND METHODS

In this experimental study, two phantoms were used, including computational and ACR phantoms. A computational phantom was developed by using Matlab R215a software (Mathworks Inc., Natick, MA Natick, MA) with a homogeneously +100 Hounsfield Unit (HU) value and an added-Gaussian noise with various levels of 5, 10, 25, 50, 75, and 100 HU. The ACR phantom was scanned with a Philips MX-16 slice CT scanner in different slice thicknesses of 1.5, 3, 5, and 7 mm to obtain noise variation. Noise measurement was conducted at the center of the phantom images and four locations close to the edge of the phantom images using different ROI sizes from 3 × 3 to 41 × 41 pixels, with an increased size of 2 × 2 pixels.

RESULTS

The use of a minimum ROI size of 21 × 21 pixels shows noise in the range of ± 5% ground truth noise. The measured noise increases above the ± 5% range if the used ROI is smaller than 21 × 21 pixels.

CONCLUSION

A minimum acceptable ROI size is required to maintain the accuracy of noise measurement with a size of 21 × 21 pixels.

Automated development of the contrast-detail curve based on statistical low-contrast detectability in CT images

Purpose

We have developed a software to automatically find the contrast–detail (C–D) curve based on the statistical low‐contrast detectability (LCD) in images of computed tomography (CT) phantoms at multiple cell sizes and to generate minimum detectable contrast (MDC) characteristics.

Methods

A simple graphical user interface was developed to set the initial parameters needed to create multiple grid region of interest of various cell sizes with a 2‐pixel increment. For each cell in the grid, the average CT number was calculated to obtain the standard deviation (SD). Detectability was then calculated by multiplying the SD of the mean CT numbers by 3.29. This process was automatically repeated as many times as the cell size was set at initialization. Based on the obtained LCD, the C–D curve was obtained and the target size at an MDC of 0.6% (i.e., 6‐HU difference) was determined. We subsequently investigated the consistency of the target sizes for a 0.6% MDC at four locations within the homogeneous image. We applied the software to images with six noise levels, images of two modules of the American College of Radiology CT phantom, images of four different phantoms, and images of four different CT scanners. We compared the target sizes at a 0.6% MDC based on the statistical LCD and the results from a human observer.

Results

The developed system was able to measure C–D curves from different phantoms and scanners. We found that the C–D curves follow a power‐law fit. We found that higher noise levels resulted in a higher MDC for a target of the same size. The low‐contrast module image had a slightly higher MDC than the distance module image. The minimum size of an object detected by visual observation was slightly larger than the size using statistical LCD.

Conclusions

The statistical LCD measurement method can generate a C–D curve automatically, quickly, and objectively.

Studies on the radiation dose, image quality and low contrast detectability from MSCT abdomen by using low tube voltage

Background

To study radiation dose, image quality and low-contrast cylinder detectability from multislice CT (MSCT) abdomen by using low tube voltage using the American College of Radiology (ACR) phantom. The ACR phantom (low-contrast module) was scanned with 64 MSCT scanner (Brilliance, Philips Medical System, Eindhoven, Netherlands) with 80 and 120 KVP, utilizing different tube current time product (mAs) range from 50 to 380 mAs. The image noise (SD), signal to noise ratio, contrast-to-noise ratio (CNR), and scores of low contrast detectability were assessed for every image respectively.

Results

From images analyses, the noise essentially increased with the use of low tube voltage. The CNR was 0.94 ± 0.27 at 120 KVP, and CNR was 0.43 ± 0.22 at 80 KVP. However, with the same dose, there were no differences of statistical significance in scores of low-contrast detectability between 120 KVP at 300mAs and 80 KVP at (200–380) mAs (p > 0.05). At 300 mAs, the CTDIvol obtained at 80 KVP was about 29% of that at 120 KVP. The CTDIvol obtained at 80 KVP were decreased from 5% at 50 mAs, to 37% at 380 mAs.

Conclusions

There is a possibility to decrease exposure of radiation virtually by reducing KVP from 120 to 80 KVP in examination of abdominal CT when the high tube current is used, though increasing image noise at low tube voltage.

A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study

Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDI_vol range: 54.7–57.5 mGy) employed by the staff of various Radiology/Neuroradiology departments of our institution for routine head examinations. CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. Noise values ranged from 3.5 HU to 5.7 HU across scanners/acquisition protocols. NPS curves differed in terms of peak position (range: 0.21–0.30 mm^-1). A substantial variation of CNR values with scanner/acquisition protocol was observed for different contrast inserts. The coefficient of variation (standard deviation divided by mean value) of CNR values across scanners/acquisition protocols was 18.3%, 31.4%, 34.2%, 30.4% and 30% for teflon, delrin, LDPE, polystyrene and acrylic insert, respectively. An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f_50%/f_10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. A relevant difference in LCD performance of different scanners/acquisition protocols was found. The range of contrast threshold for a typical object size of 3 mm was 3.7–5.8 HU. Moreover, appreciable differences in terms of NUI values (range: 4.1%-8.3%) were found. The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. This highlights the importance of a physical in-depth characterization of image quality for each CT scanner as clinically used, in order to optimize CT imaging procedures.

Development of Upright Computed Tomography With Area Detector for Whole-Body Scans: Phantom Study, Efficacy on Workflow, Effect of Gravity on Human Body, and Potential Clinical Impact

OBJECTIVES

Multiple human systems are greatly affected by gravity, and many disease symptoms are altered by posture. However, the overall anatomical structure and pathophysiology of the human body while standing has not been thoroughly analyzed due to the limitations of various upright imaging modalities, such as low spatial resolution, low contrast resolution, limited scan range, or long examination time. Recently, we developed an upright computed tomography (CT), which enables whole-torso cross-sectional scanning with 3-dimensional acquisition within 15 seconds. The purpose of this study was to evaluate the performance, workflow efficacy, effects of gravity on a large circulation system and the pelvic floor, and potential clinical impact of upright CT.

MATERIALS AND METHODS

We compared noise characteristics, spatial resolution, and CT numbers in a phantom between supine and upright CT. Thirty-two asymptomatic volunteers (48.4 ± 11.5 years) prospectively underwent both CT examinations with the same scanning protocols on the same day. We conducted a questionnaire survey among these volunteers who underwent the upright CT examination to determine their opinions regarding the stability of using the pole throughout the acquisition (closed question), as well as safety and comfortability throughout each examination (both used 5-point scales). The total access time (sum of entry time and exit time) and gravity effects on a large circulation system and the pelvic floor were evaluated using the Wilcoxon signed-rank test and the Mann-Whitney U test. For a large circulation system, the areas of the vena cava and aorta were evaluated at 3 points (superior vena cava or ascending aorta, at the level of the diaphragm, and inferior vena cava or abdominal aorta). For the pelvic floor, distances were evaluated from the bladder neck to the pubococcygeal line and the anorectal junction to the pubococcygeal line. We also examined the usefulness of the upright CT in patients with functional diseases of spondylolisthesis, pelvic floor prolapse, and inguinal hernia.

RESULTS

Noise characteristics, spatial resolution, and CT numbers on upright CT were comparable to those of supine CT. In the volunteer study, all volunteers answered yes regarding the stability of using the pole, and most reported feeling safe (average rating of 4.2) and comfortable (average rating of 3.8) throughout the upright CT examination. The total access time for the upright CT was significantly reduced by 56% in comparison with that of supine CT (upright: 41 ± 9 seconds vs supine: 91 ± 15 seconds, P < 0.001). In the upright position, the area of superior vena cava was 80% smaller than that of the supine position (upright: 39.9 ± 17.4 mm vs supine: 195.4 ± 52.2 mm, P < 0.001), the area at the level of the diaphragm was similar (upright: 428.3 ± 87.9 mm vs supine: 426.1 ± 82.0 mm, P = 0.866), and the area of inferior vena cava was 37% larger (upright: 346.6 ± 96.9 mm vs supine: 252.5 ± 93.1 mm, P < 0.001), whereas the areas of aortas did not significantly differ among the 3 levels. The bladder neck and anorectal junction significantly descended (9.4 ± 6.0 mm and 8.0 ± 5.6 mm, respectively, both P < 0.001) in the standing position, relative to their levels in the supine position. This tendency of the bladder neck to descend was more prominent in women than in men (12.2 ± 5.2 mm in women vs 6.7 ± 5.6 mm in men, P = 0.006). In 3 patients, upright CT revealed lumbar foraminal stenosis, bladder prolapse, and inguinal hernia; moreover, it clarified the grade or clinical significance of the disease in a manner that was not apparent on conventional CT.

CONCLUSIONS

Upright CT was comparable to supine CT in physical characteristics, and it significantly reduced the access time for examination. Upright CT was useful in clarifying the effect of gravity on the human body: gravity differentially affected the volume and shape of the vena cava, depending on body position. The pelvic floor descended significantly in the standing position, compared with its location in the supine position, and the descent of the bladder neck was more prominent in women than in men. Upright CT could potentially aid in objective diagnosis and determination of the grade or clinical significance of common functional diseases.

Dose and blending fraction quantification for adaptive statistical iterative reconstruction based on low-contrast detectability in abdomen CT

Purpose

The utilization of iterative reconstruction makes it difficult to identify the dose‐noise relationship, resulting in empirical design of scan protocols and inconsistent conclusions on dose reduction for consistent image quality. This study was to quantitatively determine the dose and the blending fraction of adaptive statistical iterative reconstruction (ASIR) based on the specified low‐contrast detectability (LCD).

Methods

A tissue equivalent abdomen phantom and a GE discovery 750 HD computed tomography (CT) were utilized. The normality of the noise distribution was tested at various spatial scales (2.1–9.8 mm) in the presence of ASIR (10–100%) with a wide range of doses (2.24–38 mGy). The statically defined minimum detectable contrast (MDC) was used as the image quality metric. The parametric model decomposed the MDC into two terms: one with and the other without ASIR, each was related to the dose in the form of power law with factors and indices dependent on spatial scales. The parameters were identified by least‐square fitting to the experimental data. By considering the constraint of the blending fraction in the range of [0, 1], the dose and ASIR blending fraction were determined for any specified low‐contrast detectability (LCD), quantified by the MDC at the concerned lesion size.

Results

It was verified that noise distribution is normal in the presence of ASIR. It was also found that the noises obtained from the subtractions of adjacent slices had an underestimate of 20% as compared to the ground truth noises, regardless of the spatial scale, pitch, or ASIR blending fraction. The least‐square fitting for the parametric model resulted in correlation coefficients from 0.905 to 0.996. The root‐mean‐square errors ranged from 1.27% to 7.15%.

Conclusion

The parametric model can be used to form a look‐up‐table for dose and ASIR blending fraction. The dose choices may be substantially limited in some cases depending on the required LCD.