Radiation dose optimization and thoracic computed tomography

Comparison of image quality and radiation dose of different scanning methods used for computed tomography of the unilateral shoulder

BACKGROUND

The effect of different computed tomography (CT) scanning methods of the shoulder on image quality is uncertain.

PURPOSE

To compare the effect of different methods of CT scanning of the right shoulder on image quality and radiation dose.

MATERIAL AND METHODS

A total of 30 adults were divided into five groups. Group A received scans centered on the body's long axis, a scout direction of 0° + 90°, and automatic tube current modulation (ATCM). The other four groups (B, C, D, E) received isocenter scans centered on the shoulder with different scout directions (B and C: 0° + 90°, D: 0°, E: 0° + 270°) and tube currents (B: 420 mA; C, D, E: ATCM). The volume CT dose index (CTDI_vol), dose-length product (DLP), image objective noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. Three subjective measures were also compared (noise, stripe artifacts, diagnostic confidence).

RESULTS

The five groups differed significantly in all subjective and objective indexes. The CTDI_vol and DLP decreased in the order of groups C, A, B, E, and D; the differences between groups A and B were not significant (P > 0.05). Groups B, C, and E had better SNR and CNR than groups A and D (P < 0.01). Subjective evaluations indicated group D was worse than groups B, C, and E (P < 0.05).

CONCLUSION

In the ATCM system that uses the last scout view, CT of the shoulder should use isocenter scanning with the lateral scout view when the tube is away from the long axis of the body as the last execution direction.

The influence of contrast enhancement and experience of observers on the assessment of mediastinal lymph nodes in sarcoidosis patients

Purpose

The aim of this study was to assess the influence of contrast enhancement (CE) and experience of observers on the assessment of chest lymph nodes in patients with sarcoidosis.

Material and methods

A retrospective analysis of chest lymph nodes on computed tomography (CT) examinations, including CE and non-contrast-enhanced (non-CE) phase, was performed on 40 patients with proven diagnosis of sarcoidosis. Phases were separated, anonymized, and randomized. The assessment was performed by 5 observers: 2 general radiologists, 2 residents, and a senior chest CT expert.

Results

There were no significant differences between radiologists and residents, apart from the determination of the 4R node short diameter on CE images. Agreement between the reference observer and both residents and specialists was equally high, without any significant difference in the assessment all chest nodes and hilar nodes, and between non-CE and CE images. There was a significant difference between all observers in the determination of the largest 4R node short diameter on non-CE images, but not on CE images. The number of affected node levels was found to be significantly higher when evaluated on CE images than on non-CE images. Compared to CE images, non-CE computed tomography has sensitivity of 0.94-1.00 and specificity of 0.98-1.00, depending on the observer.

Conclusions

The application of contrast medium has a limited impact on the quality of assessment of the chest lymph nodes in patients with sarcoidosis, regardless of the experience of the observer.

Does CT help in reducing RT-PCR false negative rate for COVID-19?

Background:

Early detection is the key to contain the ongoing pandemic. The current gold standard to detect SARS CoV2 is RT-PCR. However, it has a high false negative rate and long turnaround time.

Purpose:

In view of the high sensitivity of CT in detection of lower respiratory tract pathologies, a study of 2581 patients comparing RT-PCR status with CT findings was undertaken to see if it augments the diagnostic performance.

Materials and Methods:

A multi centre prospective study of consecutive cases was conducted. All CT studies suggestive of COVID 19 pneumonia were collated and evaluated independently by three Radiologists to confirm the imaging diagnosis of COVID-19 pneumonia. The RT-PCR values were retrospectively obtained, based on the RT-PCR values, CT studies were categorised into three subgroups, positive, negative and unknown. CT features from all three groups were compared to evaluate any communality or discordance.

Results:

Out of the 2581 patients with positive CT findings for COVID pneumonia, 825 were females and 1,756 were males in a wide age group of 28-90 years. Predominant CT features observed in all the subgroups were Ground glass densities 94.8%, in mixed distribution (peripheral and central) (59.12%), posterior segments in 92% and multilobar involvement in 70.9%. The CT features across the three subgroups were statistically significant with a P value <0.001.

Conclusion:

There was a communality of CT findings regardless of RT-PCR status. In a pandemic setting ground glass densities in a subpleural, posterior and basal distribution are indicative of COVID 19. Thus CT chest in conjunction to RT PCR augments the diagnosis of COVID 19 pneumonia; utilization of CT chest may just be the missing link in closing this pandemic.

Optimization of imaging parameters in chest CT for COVID-19 patients: an experimental phantom study

Background

With the global outbreak of coronavirus disease 2019 (COVID-19), chest computed tomography (CT) is vital for diagnosis and follow-up. The increasing contribution of CT to the population-collected dose has become a topic of interest. Radiation dose optimization for chest CT of COVID-19 patients is of importance in clinical practice. The present study aimed to investigate the factors affecting the detection of ground-glass nodules and exudative lesions in chest CT among COVID-19 patients and to find an appropriate combination of imaging parameters that optimize detection while effectively reducing the radiation dose.

Methods

The anthropomorphic thorax phantom, with 9 spherical nodules of different diameters and CT values of -800, -630, and 100 HU, was used to simulate the lesions of COVID-19 patients. Four custom-simulated lesions of porcine fat and ethanol were also scanned at 3 tube potentials (120, 100, and 80 kV) and corresponding milliampere-seconds (mAs) (ranging from 10 to 100). Separate scans were performed at pitches of 0.6, 0.8, 1.0, 1.15, and 1.49, and at collimations of 10, 20, 40, and 80 mm at 80 kV and 100 mAs. CT values and standard deviations of simulated nodules and lesions were measured, and radiation dose quantity (volume CT dose index; CTDIvol) was collected. Contrast-to-noise ratio (CNR) and figure of merit (FOM) were calculated. All images were subjectively evaluated by 2 radiologists to determine whether the nodules were detectable and if the overall image quality met diagnostic requirements.

Results

All simulated lesions, except -800 HU nodules, were detected at all scanning conditions. At a fixed voltage of 120 or 100 kV, with increasing mAs, image noise tended to decrease, and the CNR tended to increase (F=9.694 and P=0.033 for 120 kV; F=9.028 and P=0.034 for 100 kV). The FOM trend was the same as that of CNR (F=2.768 and P=0.174 for 120 kV; F=1.915 and P=0.255 for 100 kV). At 80 kV, the CNRs and FOMs had no significant change with increasing mAs (F=4.522 and P=0.114 for CNRs; F=1.212 and P=0.351 for FOMs). For the 4 nodules of -800 and -630 HU, CNRs had no statistical differences at each of the 5 pitches (F=0.673, P=0.476). The CNRs and FOMs at each of the 4 collimations had no statistical differences (F=2.509 and P=0.125 for CNRs; F=1.485 and P=0.309 for FOMs) for each nodule. CNRs and subjective evaluation scores increased with increasing parameter values for each imaging iteration. The CNRs of 4 -800 HU nodules in the qualified images at the thresholds of scanning parameters of 120 kV/20 mAs, 100 kV/40 mAs, and 80 kV/80 mAs, had statistical differences (P=0.038), but the FOMs had no statistical differences (P=0.085). Under the 3 threshold conditions, the CNRs and FOMs of the 4 nodules were highest at 100 kV and 40 mAs (1.6 mGy CTDIvol).

Conclusions

For chest CT among COVID-19 patients, it is recommended that 100 kV/40 mAs is used for average patients; the radiation dose can be reduced to 1.6 mGy with qualified images to detect ground-glass nodules and exudation lesions.

Noise Reduction in CT Images Using a Selective Mean Filter

Background

Noise reduction is a method for reducing CT dose; however, it can reduce image quality.

Objective

This study aims to propose a selective mean filter (SMF) and evaluate its effectiveness for noise suppression in CT images.

Material and Methods

This experimental study proposed and implemented the new noise reduction algorithm. The proposed algorithm is based on a mean filter (MF), but the calculation of the mean pixel value using the neighboring pixels in a kernel selectively applied a threshold value based on the noise of the image. The SMF method was evaluated using images of phantoms. The dose reduction was estimated by comparing the image noise acquired with a lower dose after implementing the SMF method and the noise in the original image acquired with a higher dose. For comparison, the images were also filtered with an adaptive mean filter (AMF) and a bilateral filter (BF).

Results

The spatial resolution of the image filtered with the SMF was similar to the original images and the images filtered with the BF. While using the AMF, spatial resolution was significantly corrupted. The noise reduction achieved using the SMF was up to 75%, while it was up to 50% using the BF.

Conclusion

SMF significantly reduces the noise and preserves the spatial resolution of the image. The noise reduction was more pronounced with BF, and less pronounced with AMF.

Accuracy of Pulmonary Nodule Volumetry Using Noise-Optimized Virtual Monoenergetic Image and Nonlinear Blending Image Algorithms in Dual-Energy Computed Tomography: A Phantom Study

OBJECTIVE

The aim of the study was to assess accuracy of pulmonary nodule volumetry using noise-optimized virtual monoenergetic image (VMI+) and nonlinear blending image (NBI) algorithms in dual-energy computed tomography (DECT).

METHODS

An anthropomorphic chest phantom with 10 simulated nodules (5 solid nodules and 5 ground-glass opacities) was scanned using DECT80/Sn140kV, DECT100/Sn140kV, and single-energy CT (SECT120kV/200mAs), respectively. The dual-energy images were reconstructed using VMI+ (70 keV) and NBI algorithms. The contrast-to-noise ratio and absolute percentage error (APE) of nodule volume were measured to assess image quality and accuracy of nodule volumetry. The radiation dose was also estimated.

RESULTS

The contrast-to-noise ratio of SECT120kV/200mAs was significantly higher than that of NBI80/Sn140kV and VMI+80/Sn140kV (both corrected P < 0.05), whereas there were no significant differences between NBI100/sn140kV and SECT120kV/200mAs and between VMI+100/sn140kV and SECT120kV/200mAs (both corrected P > 0.05). The APE of SECT120kV/200mAs was significantly lower than that of NBI80/Sn140kV and VMI+80/Sn140kV in both types of nodules (all corrected P < 0.05), whereas there were no significant differences between VMI+100/sn140kV and SECT120kV/200mAs in solid nodules and between NBI100/Sn140kV and SECT120kV/200mAs in ground-glass opacities (both corrected P > 0.05). The radiation dose of DECT100/Sn140kV and DECT80/Sn140kV were significantly lower than that of SECT120kV/200mAs (both corrected P < 0.05).

CONCLUSIONS

The DECT100/sn140kV can ensure image quality and nodule volumetry accuracy with lower radiation dose compared with SECT120kV/200mAs. Specifically, the VMI+ algorithm could be used in solid nodules and NBI algorithm in ground-glass opacities.

Multimodality imaging in connective tissue disease-related interstitial lung disease

Interstitial lung disease is a well-recognised manifestation and a major cause of morbidity and mortality in patients with connective tissue diseases. Interstitial lung disease may arise in the context of an established connective tissue disease or be the initial manifestation of an otherwise occult autoimmune disorder. Early detection and characterisation are paramount for adequate patient management and require a multidisciplinary approach, in which imaging plays a vital role. Computed tomography is currently the imaging method of choice; however, other imaging techniques have recently been investigated, namely ultrasound, magnetic resonance imaging, and positron-emission tomography, with promising results. The aim of this review is to describe the imaging findings of connective tissue disease-related interstitial lung disease and explain the role of each imaging technique in diagnosis and disease characterisation.

Vertical Off-Centering in Reduced Dose Chest-CT: Impact on Effective Dose and Image Noise Values

OBJECTIVES

To assess the effect of vertical off-centering in tube current modulation (TCM) on effective-dose and image-noise in reduced-dose (RD) chest-CT.

METHODS

One-hundred consecutive patients (36 female; mean age 56 years) were scanned on a 192-slice CT scanner with a standard-dose (ND) and a RD chest-CT protocol using tube current modulation. Image-noise was evaluated by placing circular regions of interest in the apical, middle, and lower lung regions. Two independent readers evaluated image quality. Study population was stratified according to patient position in the gantry: positioned in the gantry isocenter (i), higher than the gantry isocenter (ii), and lower than the gantry isocenter, (iii). Pearson correlation was used to determine the correlation between effective radiation dose and vertical off-centering. Student's t test was used to evaluate for differences in image-noise between groups (i-iii).

RESULTS

Mean vertical off-centering was of 10.6 mm below the gantry-isocenter (range -45.0-27.9 mm). Effective radiation dose varied in a linear trend, with the highest doses noted below gantry isocenter, and the lowest doses noted above gantry isocenter (ND: r = -0.296; p = 0.003 - RD: r = -0.258; p = 0.010). Lowest image-noise was observed where patients were positioned below the gantry isocenter, and highest in patients positioned above (ND: 79.35 HU vs. 94.86 HU - RD: 143.44 HU vs. 160.13 HU). Subjective image quality was not significantly affected by patient-position (p > 0.05). Overall, there was no over-proportional noise-increase from the ND to the RD protocol in patients which were positioned off-center.

CONCLUSION

Vertical off-centering influences effective radiation dose and image-noise on ND and RD protocols.

ADVANCES IN KNOWLEDGE

There is no over-proportional noise increase in RD compared to ND protocols when patients are positioned off-center.

Optimization of acquisition parameters for reduced-dose thoracic CT: A phantom study

PURPOSE

The purpose of this study was to analyze the impact of different options for reduced-dose computed tomography (CT) on image noise and visibility of pulmonary structures in order to define the best choice of parameters when performing ultra-low dose acquisitions of the chest in clinical routine.

MATERIALS AND METHODS

Using an anthropomorphic chest phantom, CT images were acquired at four defined low dose levels (computed tomography dose index [CTDI_vol]=0.15, 0.20, 0.30 and 0.40mGy), by changing tube voltage, pitch factor, or rotation time and adapting tube current to reach the predefined CTDI_vol-values. Images were reconstructed using two different levels of iteration (adaptive statistical iterative reconstruction [ASIR®]-v70% and ASIR®-v100%). Signal-to-noise ratio (SNR) as well as contrast-to-noise ratio (CNR) was calculated. Visibility of pulmonary structures (bronchi/vessels) were assessed by two readers on a 5-point-Likert scale.

RESULTS

Best visual image assessments and CNR/SNR were obtained with high tube voltage, while lowest scores were reached with lower pitch factor followed by high tube current. Protocols favoring lower pitch factor resulted in decreased visibility of bronchi/vessels, especially in the periphery. Decreasing radiation dose from 0.40 to 0.30mGy was not associated with a significant decrease in visual scores (P<0.05), however decreasing radiation dose from 0.30mGy to 0.15mGy was associated with a lower visibility of most of the evaluated structures (P<0.001). While image noise could be significantly reduced when ASIR®-v100% instead of ASIR®-v70% was used, the visibility-scores of pulmonary structures did not change significantly.

CONCLUSION

Favoring high tube voltage is the best option for reduced-dose protocols. A decrease of SNR and CNR does not necessarily go along with reduced visibility of pulmonary structures.

STRATEGY OF COMPUTED TOMOGRAPHY IMAGE OPTIMISATION IN CERVICAL VERTEBRAE AND NECK SOFT TISSUE IN EMERGENCY PATIENTS

INTRODUCTION

With regards to the use of ionisation radiation in the computed tomography (CT), optimal parameters should be used to reduce the risk of incidence of secondary cancers in patients who are constantly exposed to X-rays. The aim of this study was to optimise the parameters used in CT scan of cervical vertebrae and neck soft tissue with minimal loss of image quality in emergency patients.

MATERIALS AND METHODS

In this study, the patients were divided into two groups. The first group consisted of patients scanned with default parameters and the second group scanned with optimised parameters. All the study has been implemented in emergency settings. The cases included cervical vertebrae and soft tissue protocols. Common CT dose descriptors including weighted computed tomography dose index (CTDIw), volumetric CTDI (CTDIvol), dose length product (DLP), effective dose (ED) and image noise were measured for each group. The ImpactDose program was used to estimate the organs doses. Statistical analysis was performed using Kruskal-Wallis test using SPSS software.

RESULTS

There was no significant quality reduction in the optimised images. Decreasing in radiation dose parameters for the soft tissue was: kVp=16.7%, mAs=64.3% and pitch=24.1%, and for the cervical vertebrae was: kVp=16.7%, mAs=54.2% and pitch=48.3%. Consequently, decreasing these parameters reduced CTDIw=81.0%, CTDIvol=90.0% and DLP = 90.2% in the cervical vertebral protocol, as well as CTDIw=75.5%, CTDIvol=81.3% and DLP = 81.4% in the soft tissue protocol.

CONCLUSION

Regarding the results, the optimised parameters in the mentioned organ scan reduce the radiation dose in the target area and the organs surrounding. Therefore, these protocols can be used for reducing the risk of cancer.

Ultra-low dose chest computed tomography: Effect of iterative reconstruction levels on image quality

PURPOSE

To optimize image quality and radiation dose of chest CT with respect to various iterative reconstruction levels, detector collimations and body sizes.

METHOD

A Kyoto Kagaku Lungman with and without extensions was scanned using fixed ultra-low doses of 0.25, 0.49 and 0.74 mGy CTDI_vol, and collimations of 40 and 80 mm. Images were reconstructed with the lung kernel, filtered back projection (FBP) and different ASIR-V levels (10-100%). Contrast-to-noise ratios (CNR) were calculated for 12 mm simulated lesions of different densities in the lung. Image noise, signal-to-noise ratios (SNR), variations in Hounsfield units (HU), noise power spectrum (NPS) and noise texture deviations (NTD) were evaluated for all reconstructions. NTD was calculated as percentage of pixels outside 3 standard deviations to evaluate IR-specific artefacts.

RESULTS

Compared to the FBP, image noise reduced (5-55%) with ASIR-V levels irrespective of dose or collimation. SNR correlated positively (r ≥ 0.925, p ≤ 0.001) with ASIR-V levels at all doses, collimations, and phantom sizes. ASIR-V enhanced the CNR of the lesion with the lowest contrast from 12.7-42.1 (0-100% ASIR-V) at 0.74 mGy with 40 mm collimation. As expected, higher SNR and CNR were measured in the smaller phantom than the bigger phantom. Uniform HU were observed between FBP and ASIR-V levels at all doses, collimations, and phantom sizes. NPS curves left-shifted towards lower frequencies at increasing levels of ASIR-V irrespective of collimation. A positive correlation (r ≥ 0.946, p ≥ 0.001) was observed between NTD and ASIR-V levels. NTD of the FBP was not significantly (p ≤ 0.087) different from NTD of ASIR-V ≤ 20%. The data from the NPS and NTD indicates a blotchier and coarser noise texture at higher levels of ASIR-V, especially at 100% ASIR-V.

CONCLUSION

In comparison with the FBP technique, ASIR-V enhanced quantitative image quality parameters at all ultra-low doses tested. Moreover, the use of ASIR-V showed consistency with body size and collimation. Hence, ASIR-V may be useful for improving image quality of chest CT at ultra-low doses.

A Method of Accurate Bone Tunnel Placement for Anterior Cruciate Ligament Reconstruction Based on 3-Dimensional Printing Technology: A Cadaveric Study

PURPOSE

To explore a method of bone tunnel placement for anterior cruciate ligament (ACL) reconstruction based on 3-dimensional (3D) printing technology and to assess its accuracy.

METHODS

Twenty human cadaveric knees were scanned by thin-layer computed tomography (CT). To obtain data on bones used to establish a knee joint model by computer software, customized bone anchors were installed before CT. The reference point was determined at the femoral and tibial footprint areas of the ACL. The site and direction of the bone tunnels of the femur and tibia were designed and calibrated on the knee joint model according to the reference point. The resin template was designed and printed by 3D printing. Placement of the bone tunnels was accomplished by use of templates, and the cadaveric knees were scanned again to compare the concordance of the internal opening of the bone tunnels and reference points.

RESULTS

The twenty 3D printing templates were designed and printed successfully. CT data analysis between the planned and actual drilled tunnel positions showed mean deviations of 0.57 mm (range, 0-1.5 mm; standard deviation, 0.42 mm) at the femur and 0.58 mm (range, 0-1.5 mm; standard deviation, 0.47 mm) at the tibia.

CONCLUSIONS

The accuracy of bone tunnel placement for ACL reconstruction in cadaveric adult knees based on 3D printing technology is high.

CLINICAL RELEVANCE

This method can improve the accuracy of bone tunnel placement for ACL reconstruction in clinical sports medicine.

Assessment of chest CT at CTDIvol less than 1 mGy with iterative reconstruction techniques

OBJECTIVE

To assess the image quality of chest CT reconstructed with image-based iterative reconstruction (SafeCT; MedicVision^®, Tirat Carmel, Israel), adaptive statistical iterative reconstruction (ASIR; GE Healthcare, Waukesha, WI) and model-based iterative reconstruction (MBIR; GE Healthcare, Waukesha, WI) techniques at CT dose index volume (CTDI_vol) <1 mGy.

METHODS

In an institutional review board-approved study, 25 patients gave written informed consent for acquisition of three reduced dose (0.25-, 0.4- and 0.8-mGy) chest CT after standard of care CT (8 mGy) on a 64-channel multidetector CT (MDCT) and reconstructed with SafeCT, ASIR and MBIR. Two board-certified thoracic radiologists evaluated images from the lowest to the highest dose of the reduced dose CT series and subsequently for standard of care CT.

RESULTS

Out of the 182 detected lesions, the missed lesions were 35 at 0.25, 24 at 0.4 and 9 at 0.8 mGy with SafeCT, ASIR and MBIR, respectively. The most missed lesions were non-calcified lung nodules (NCLNs) 25/112 (<5 mm) at 0.25, 18/112 (<5 mm) at 0.4 and 3/112 (<4 mm) at 0.8 mGy. There were 78%, 84% and 97% lung nodules detected at 0.25, 0.4 and 0.8 mGy, respectively regardless of iterative reconstruction techniques (IRTs), Most mediastinum structures were not sufficiently seen at 0.25-0.8 mGy.

CONCLUSION

NCLNs can be missed in chest CT at CTDI_vol of <1 mGy (0.25, 0.4 and 0.8 mGy) regardless of IRTs. The most lung nodules (97%) were detected at CTDI_vol of 0.8 mGy. The most mediastinum structures were not sufficiently seen at 0.25-0.8 mGy. Advances in knowledge: NCLNs can be missed regardless of IRTs in chest CT at CTDI_vol of <1 mGy. The performance of ASIR, SafeCT and MBIR was similar for lung nodule detection at 0.25, 0.4 and 0.8 mGy.

Submillisievert Computed Tomography of the Chest Using Model-Based Iterative Algorithm: Optimization of Tube Voltage With Regard to Patient Size

OBJECTIVE

The aim of this study was to define optimal tube potential for soft tissue and vessel visualization in dose-reduced chest CT protocols using model-based iterative algorithm in average and overweight patients.

METHODS

Thirty-six patients receiving chest CT according to 3 protocols (120 kVp/noise index [NI], 60; 100 kVp/NI, 65; 80 kVp/NI, 70) were included in this prospective study, approved by the ethics committee. Patients' physical parameters and dose descriptors were recorded. Images were reconstructed with model-based algorithm. Two radiologists evaluated image quality and lesion conspicuity; the protocols were intraindividually compared with preceding control CT reconstructed with statistical algorithm (120 kVp/NI, 20). Mean and standard deviation of attenuation of the muscle and fat tissues and signal-to-noise ratio of the aorta were measured.

RESULTS

Diagnostic images (lesion conspicuity, 95%-100%) were acquired in average and overweight patients at 1.34, 1.02, and 1.08 mGy and at 3.41, 3.20, and 2.88 mGy at 120, 100, and 80 kVp, respectively. Data are given as CT dose index volume values.

CONCLUSIONS

Model-based algorithm allows for submillisievert chest CT in average patients; the use of 100 kVp is recommended.

Assessment of sub-milli-sievert abdominal computed tomography with iterative reconstruction techniques of different vendors

AIM: To assess diagnostic image quality of reduced dose (RD) abdominal computed tomography (CT) with 9 iterative reconstruction techniques (IRTs) from 4 different vendors to the standard of care (SD) CT.

METHODS: In an Institutional Review Board approved study, 66 patients (mean age 60 ± 13 years, 44 men, and 22 women) undergoing routine abdomen CT on multi-detector CT (MDCT) scanners from vendors A, B, and C (≥ 64 row CT scanners) (22 patients each) gave written informed consent for acquisition of an additional RD CT series. Sinogram data of RD CT was reconstructed with two vendor-specific and a vendor-neutral IRTs (A-1, A-2, A-3; B-1, B-2, B-3; and C-1, C-2, C-3) and SD CT series with filtered back projection. Subjective image evaluation was performed by two radiologists for each SD and RD CT series blinded and independently. All RD CT series (198) were assessed first followed by SD CT series (66). Objective image noise was measured for SD and RD CT series. Data were analyzed by Wilcoxon signed rank, kappa, and analysis of variance tests.

RESULTS: There were 13/50, 18/57 and 9/40 missed lesions (size 2-7 mm) on RD CT for vendor A, B, and C, respectively. Missed lesions includes liver cysts, kidney cysts and stone, gall stone, fatty liver, and pancreatitis. There were also 5, 4, and 4 pseudo lesions (size 2-3 mm) on RD CT for vendor A, B, and C, respectively. Lesions conspicuity was sufficient for clinical diagnostic performance for 6/24 (RD-A-1), 10/24 (RD-A-2), and 7/24 (RD-A-3) lesions for vendor A; 5/26 (RD-B-1), 6/26 (RD-B-2), and 7/26 (RD-B-3) lesions for vendor B; and 4/20 (RD-C-1) 6/20 (RD-C-2), and 10/20 (RD-C-3) lesions for vendor C (P = 0.9). Mean objective image noise in liver was significantly lower for RD A-1 compared to both RD A-2 and RD A-3 images (P < 0.001). Similarly, mean objective image noise lower for RD B-2 (compared to RD B-1, RD B-3) and RD C-3 (compared to RD C-1 and C-2) (P = 0.016).

CONCLUSION: Regardless of IRTs and MDCT vendors, abdominal CT acquired at mean CT dose index volume 1.3 mGy is not sufficient to retain clinical diagnostic performance.

Convolution-based estimation of organ dose in tube current modulated CT

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ([Formula: see text]) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate [Formula: see text] values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying [Formula: see text] with the organ dose coefficients ([Formula: see text]). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The discrepancy between the estimated organ dose and dose simulated using TCM Monte Carlo program was quantified. We further compared the convolution-based organ dose estimation method with two other strategies with different approaches of quantifying the irradiation field. The proposed convolution-based estimation method showed good accuracy with the organ dose simulated using the TCM Monte Carlo simulation. The average percentage error (normalized by CTDIvol) was generally within 10% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. This study developed an improved method that accurately quantifies the irradiation field under TCM scans. The results suggested that organ dose could be estimated in real-time both prospectively (with the localizer information only) and retrospectively (with acquired CT data).

American Thoracic Society-European Respiratory Society Classification of the Idiopathic Interstitial Pneumonias: Advances in Knowledge since 2002

In the updated American Thoracic Society-European Respiratory Society classification of the idiopathic interstitial pneumonias (IIPs), the major entities have been preserved and grouped into (a) "chronic fibrosing IIPs" (idiopathic pulmonary fibrosis and idiopathic nonspecific interstitial pneumonia), (b) "smoking-related IIPs" (respiratory bronchiolitis-associated interstitial lung disease and desquamative interstitial pneumonia), (c) "acute or subacute IIPs" (cryptogenic organizing pneumonia and acute interstitial pneumonia), and (d) "rare IIPs" (lymphoid interstitial pneumonia and idiopathic pleuroparenchymal fibroelastosis). Furthermore, it has been acknowledged that a final diagnosis is not always achievable, and the category "unclassifiable IIP" has been proposed. The diagnostic interpretation of the IIPs is often challenging because other diseases with a known etiology (most notably, connective tissue disease and hypersensitivity pneumonitis) may show similar morphologic patterns. Indeed, more emphasis has been given to the integration of clinical, computed tomographic (CT), and pathologic findings for multidisciplinary diagnosis. Typical CT-based morphologic patterns are associated with the IIPs, and radiologists play an important role in diagnosis and characterization. Optimal CT quality and a systematic approach are both pivotal for evaluation of IIP. Interobserver variation for the various patterns encountered in the IIPs is an issue. It is important for radiologists to understand the longitudinal behavior of IIPs at serial CT examinations, especially for providing a framework for cases that are unclassifiable or in which a histologic diagnosis cannot be obtained.

Assessment of Filtered Back Projection, Adaptive Statistical, and Model-Based Iterative Reconstruction for Reduced Dose Abdominal Computed Tomography

PURPOSE

To compare standard of care and reduced dose (RD) abdominal computed tomography (CT) images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), model-based iterative reconstruction (MBIR) techniques.

MATERIALS AND METHODS

In an Institutional Review Board-approved, prospective clinical study, 28 patients (mean age 59 ± 13 years ), undergoing clinically indicated routine abdominal CT on a 64-channel multi-detector CT scanner, gave written informed consent for acquisition of an additional RD (<1 milli-Sievert) abdomen CT series. Sinogram data of RD series were reconstructed with FBP, ASIR, and MBIR and compared with FBP images of standard dose abdomen CT. Two radiologists performed randomized, independent, and blinded comparison for lesion detection, lesion margin, visibility of normal structures, and diagnostic confidence.

RESULTS

Mean CT dose index volume was 10 ± 3.4 mGy and 1.3 ± 0.3 mGy for standard and RD CT, respectively. There were 73 "true positive" lesions detected on standard of care CT. Nine lesions (<8 mm in size) were missed on RD abdominal CT images which included liver lesions, liver cysts, kidney cysts, and paracolonic abscess. These lesions were missed regardless of patient size and types of iterative reconstruction techniques used for reconstruction of RD data sets. The visibility of lesion margin was suboptimal in (23/28) patients with RD FBP, (15/28) patients with RD ASIR, and (14/28) patients with RD MBIR compared to standard of care FBP images (P < 0.001). Diagnostic confidence for the assessment of lesions on RD images was suboptimal in most patients regardless of iterative reconstruction techniques.

CONCLUSIONS

Clinically significant lesions (< 8 mm) can be missed on abdominal CT examinations acquired at a CT dose index volume of 1.3 mGy regardless of patients' size and reconstruction techniques (FBP, ASIR, and MBIR).

Achievable dose reduction using iterative reconstruction for chest computed tomography: A systematic review

OBJECTIVES

Iterative reconstruction (IR) allows for dose reduction with maintained image quality in CT imaging. In this systematic review the reported effective dose reductions for chest CT and the effects on image quality are investigated.

METHODS

A systematic search in PubMed and EMBASE was performed. Primary outcome was the reported local reference and reduced effective dose and secondary outcome was the image quality with IR. Both non contrast-enhanced and enhanced studies comparing reference dose with reduced dose were included.

RESULTS

24 studies were included. The median number of patients per study was 66 (range 23-200) with in total 1806 patients. The median reported local reference dose of contrast-enhanced chest CT with FBP was 2.6 (range 1.5-21.8) mSv. This decreased to 1.4 (range 0.4-7.3) mSv at reduced dose levels using IR. With non contrast-enhanced chest CT the dose decreased from 3.4 (range 0.7-7.8) mSv to 0.9 (range 0.1-4.5) mSv. Objective mage quality and diagnostic confidence and acceptability remained the same or improved with IR compared to FBP in most studies while data on diagnostic accuracy was limited.

CONCLUSION

Radiation dose can be reduced to less than 2 mSv for contrast-enhanced chest CT and non contrast-enhanced chest CT is possible at a submillisievert dose using IR algorithms.

Pediatric Computed Tomography Dose Optimization Strategies: A Literature Review

INTRODUCTION

Computed tomography (CT) dose optimization is an important issue in radiography because CT is the largest contributor to medical radiation dose and its use is increasing. However, CT dose optimization for pediatric patients could be more challenging than their adult counterparts. The purpose of this literature review was to identify and discuss the current pediatric CT dose saving techniques. Optimized pediatric protocols were also proposed.

METHODS

A comprehensive literature search was conducted using the Medline, ProQuest Health and Medical Complete, PubMed, ScienceDirect, Scopus, Springer Link, and Web of Science databases and the keywords CT, pediatric, optimization, protocol, and radiation dose to identify articles focusing on pediatric CT dose optimization strategies published between 2004 and 2014.

RESULTS AND SUMMARY

Seventy-seven articles were identified in the literature search. Strategies for optimizing a range of scan parameters and technical considerations including tube voltage and current, iterative reconstruction, diagnostic reference levels, bowtie filters, scout view, pitch, scan collimation and time, overscanning, and overbeaming for pediatric patients with different ages and body sizes and compositions were discussed. An example of optimized pediatric protocols specific to age and body size for the 64-slice CT scanners was devised. It is expected that this example could provide medical radiation technologists, radiologists, and medical physicists with ideas to optimize their pediatric protocols.

Ultra low-dose chest CT using filtered back projection: comparison of 80-, 100- and 120 kVp protocols in a prospective randomized study

PURPOSE

To assess lesion detection and diagnostic image quality of filtered back projection (FBP) reconstruction technique in ultra low-dose chest CT examinations.

METHODS AND MATERIALS

In this IRB-approved ongoing prospective clinical study, 116 CT-image-series at four different radiation-doses were performed for 29 patients (age, 57-87 years; F:M - 15:12; BMI 16-32 kg/m(2)). All patients provided written-informed-consent for the acquisitions of additional ultra low-dose (ULD) series on a 256-slice MDCT (iCT, Philips Healthcare). In-addition to their clinical standard-dose chest CT (SD, 120 kV mean CTDIvol, 6 ± 1 mGy), ULD-CT was subsequently performed at three-dose-levels (0.9 mGy [120 kV]; 0.5 mGy [100 kV] and 0.2 mGy [80 kV]). Images were reconstructed with FBP (2.5mm 1.25 mm) resulting into four-stacks: SD-FBP (reference-standard), FBP0.9, FBP0.5, and FBP0.2. Four thoracic-radiologists from two-teaching-hospitals independently-evaluated data for lesion-detection and visibility-of-small-structures. Friedman's-non-parametric-test with post hoc Dunn's-test was used for data-analysis.

RESULTS

Interobserver-agreement was substantial between radiologists (k=0.6-0.8). With pooled analysis, 146-pulmonary (27-groundglass-opacities, 64-solid-lung-nodules, 7-consolidations, 27-emphysema) and 347-mediastinal/soft tissue lesions (87-mediastinal, 46-hilar, 62-axillary-lymph-nodes, and 11-mediastinal-masses) were evaluated. Compared to the SD-FBP, 100% pulmonary-lesions were seen with FBP0.9, up to 81% with FBP0.5 (missed: 4), and up to 30% with FBP0.2 images (missed:16). Compared to SD-FBP, all enlarged mediastinal-lymph-nodes were seen with FBP0.9 images. All mediastinal-masses (>2 cm, 11/11) were seen equivalent to SD-FBP images at 0.9 mGy. Across all sizes of patients, FBP0.9 images had optimal visualization for lung findings. They were optimal for mediastinal soft tissues for only non-obese patients.

CONCLUSION

Filtered-back-projection technique allows optimal lesion detection and acceptable image quality for chest-CT examinations at CDTIvol of 0.9 mGy for lung and mediastinal findings in selected sizes of patients.