Dose reduction with iterative reconstruction: Optimization of CT protocols in clinical practice

Abdominal image quality and dose reduction with energy-integrating or photon-counting detectors dual-source CT: A phantom study

PURPOSE

The purpose of this study was to assess image-quality and dose reduction potential using a photon-counting computed tomography (PCCT) system by comparison with two different dual-source CT (DSCT) systems using two phantoms.

MATERIALS AND METHODS

Acquisitions on phantoms were performed using two DSCT systems (DSCT1 [Somatom Force] and DSCT2 [Somatom Pro.Pulse]) and one PCCT system (Naeotom Alpha) at four dose levels (13/6/3.4/1.8 mGy). Noise power spectrum (NPS) and task-based transfer function (TTF) were computed to assess noise magnitude and noise texture and spatial resolution (f50), respectively. Detectability indexes (d') were computed to model the detection of abdominal lesions: one unenhanced high-contrast task, one contrast-enhanced high-contrast task and one unenhanced low-contrast task. Image quality was subjectively assessed on an anthropomorphic phantom by two radiologists.

RESULTS

For all dose levels, noise magnitude values were lower with PCCT than with DSCTs. For all CT systems, similar noise texture values were found at 13 and 6 mGy, but the greatest noise texture values were found for DSCT2 and the lowest for PCCT at 3.4 and 1.8 mGy. For high-contrast inserts, similar or lower f50 values were found with PCCT than with DSCT1 and the opposite pattern was found for the low-contrast insert. For the three simulated lesions, d' values were greater with PCCT than with DSCTs. Abdominal images were rated satisfactory for clinical use by the radiologists for all dose levels with PCCT and for 13 and 6 mGy with DSCTs.

CONCLUSION

By comparison with DSCTs, PCCT reduces image-noise and improves detectability of simulated abdominal lesions without altering the spatial resolution and image texture. Image-quality obtained with PCCT seem to indicate greater potential for dose optimization than those obtained with DSCTs.

Ultra-low dose chest CT for the diagnosis of pulmonary arteriovenous malformation in patients with hereditary hemorrhagic telangiectasia

PURPOSE

The purpose of this study was to compare ultra-low dose (ULD) and standard low-dose (SLD) chest computed tomography (CT) in terms of radiation exposure, image quality and diagnostic value for diagnosing pulmonary arteriovenous malformation (AVM) in patients with hereditary hemorrhagic telangiectasia (HHT).

MATERIALS AND METHODS

In this prospective board-approved study consecutive patients with HHT referred to a reference center for screening and/or follow-up chest CT examination were prospectively included from December 2020 to January 2022. Patients underwent two consecutive non-contrast chest CTs without dose modulation (i.e., one ULD protocol [80 kVp or 100 kVp, CTDIvol of 0.3 mGy or 0.6 mGy] and one SLD protocol [140 kVp, CTDIvol of 1.3 mGy]). Objective image noises measured at the level of tracheal carina were compared between the two protocols. Overall image quality and diagnostic confidence were scored on a 4-point Likert scale (1 = insufficient to 4 = excellent). Sensitivity, specificity, positive predictive value and negative predictive value of ULD CT for diagnosing pulmonary AVM with a feeding artery of over 2 mm in diameter were calculated along with their 95% confidence intervals (CI) using SLD images as the standard of reference.

RESULTS

A total of 44 consecutive patients with HHT (31 women; mean age, 42 ± 16 [standard deviation (SD)] years; body mass index, 23.2 ± 4.5 [SD] kg/m2) were included. Thirty-four pulmonary AVMs with a feeding artery of over 2 mm in diameter were found with SLD images versus 35 with ULD images. Sensitivity, specificity, predictive positive value, and predictive negative value of ULD CT for the diagnosis of PAVM were 100% (34/34; 95% CI: 90-100), 96% (18/19; 95% CI: 74-100), 97% (34/35; 95% CI: 85-100) and 100% (18/18; 95% CI: 81-100), respectively. A significant difference in diagnostic confidence scores was found between ULD (3.8 ± 0.4 [SD]) and SLD (3.9 ± 0.1 [SD]) CT images (P = 0.03). No differences in overall image quality scores were found between ULD CT examinations (3.9 ± 0.2 [SD]) and SLD (4 ± 0 [SD]) CT examinations (P = 0.77). Effective radiation dose decreased significantly by 78.8% with ULD protocol, with no significant differences in noise values between ULD CT images (16.7 ± 5.0 [SD] HU) and SLD images (17.7 ± 6.6 [SD] HU) (P = 0.07).

CONCLUSION

ULD chest CT provides 100% sensitivity and 96% specificity for the diagnosis of treatable pulmonary AVM with a feeding artery of over 2 mm in diameter, leading to a 78.8% dose-saving compared with a standard low-dose protocol.

Photon-counting CT systems: A technical review of current clinical possibilities

In recent years, computed tomography (CT) has undergone a number of developments to improve radiological care. The most recent major innovation has been the development of photon-counting detectors. By comparison with the energy-integrating detectors traditionally used in CT, these detectors offer better dose efficiency, eliminate electronic noise, improve spatial resolution and have intrinsic spectral sensitivity. These detectors also allow the energy of each photon to be counted, thus improving the sampling of the X-ray spectrum in multiple energy bins, to better distinguish between photoelectric and Compton attenuation coefficients, resulting in better spectral images and specific color K-edge images. The purpose of this article was to make the reader more familiar with the basic principles and techniques of new photon-counting CT systems equipped with photon-counting detectors and also to describe the currently available devices that could be used in clinical practice.

Survey of CT radiation doses and iodinated contrast medium administration: an international multicentric study

OBJECTIVE

To assess the relationship between intravenous iodinated contrast media (ICM) administration usage and radiation doses for contrast-enhanced (CE) CT of head, chest, and abdomen-pelvis (AP) in international, multicenter settings.

METHODS

Our international (n = 16 countries), multicenter (n = 43 sites), and cross-sectional (ConRad) study had two parts. Part 1: Redcap survey with questions on information related to CT and ICM manufacturer/brand and respective protocols. Part 2: Information on 3,258 patients (18-96 years; M:F 1654:1604) who underwent CECT for a routine head (n = 456), chest (n = 528), AP (n = 599), head CT angiography (n = 539), pulmonary embolism (n = 599), and liver CT examinations (n = 537) at 43 sites across five continents. The following information was recorded: hospital name, patient age, gender, body mass index [BMI], clinical indications, scan parameters (number of scan phases, kV), IV-contrast information (concentration, volume, flow rate, and delay), and dose indices (CTDIvol and DLP).

RESULTS

Most routine chest (58.4%) and AP (68.7%) CECT exams were performed with 2-4 scan phases with fixed scan delay (chest 71.4%; AP 79.8%, liver CECT 50.7%) following ICM administration. Most sites did not change kV across different patients and scan phases; most CECT protocols were performed at 120-140 kV (83%, 1979/2685). There were no significant differences between radiation doses for non-contrast (CTDIvol 24 [16-30] mGy; DLP 633 [414-702] mGy·cm) and post-contrast phases (22 [19-27] mGy; 648 [392-694] mGy·cm) (p = 0.142). Sites that used bolus tracking for chest and AP CECT had lower CTDIvol than sites with fixed scan delays (p < 0.001). There was no correlation between BMI and CTDIvol (r2 ≤ - 0.1 to 0.1, p = 0.931).

CONCLUSION

Our study demonstrates up to ten-fold variability in ICM injection protocols and radiation doses across different CT protocols. The study emphasizes the need for optimizing CT scanning and contrast protocols to reduce unnecessary contrast and radiation exposure to patients.

CLINICAL RELEVANCE STATEMENT

The wide variability and lack of standardization of ICM media and radiation doses in CT protocols suggest the need for education and optimization of contrast usage and scan factors for optimizing image quality in CECT.

KEY POINTS

There is a lack of patient-centric CT protocol optimization taking into consideration mainly patients' size. There is a lack of correlation between ICM volume and CT radiation dose across CT protocol. A ten-fold variation in iodine-load for the same CT protocol in sites suggests a lack of standardization.

Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions

To assess the image quality parameters of dual-energy computed tomography angiography (DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep learning-based image reconstruction model (DLM) and iterative reconstructions (IR). CT scans of 28 post EVAR patients were enrolled. The 60 s delayed phase of DECTA was evaluated. Objective [noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR)] and subjective (overall image quality and endoleak conspicuity - 3 blinded readers assessment) image quality analyses were performed. The following reconstructions were evaluated: VMI 40, 60 keV VMI; IR VMI 40, 60 keV; DLM VMI 40, 60 keV. The noise level of the DLM VMI images was approximately 50% lower than that of VMI reconstruction. The highest CNR and SNR values were measured in VMI DLM images. The mean CNR in endoleak in 40 keV was accounted for as 1.83 ± 1.2; 2.07 ± 2.02; 3.6 ± 3.26 in VMI, VMI IR, and VMI DLM, respectively. The DLM algorithm significantly reduced noise and increased lesion conspicuity, resulting in higher objective and subjective image quality compared to other reconstruction techniques. The application of DLM algorithms to low-energy VMIs significantly enhances the diagnostic value of DECTA in evaluating endoleaks. DLM reconstructions surpass traditional VMIs and IR in terms of image quality.

Image quality assessment in low-dose COVID-19 chest CT examinations

BACKGROUND

Low-dose thoracic protocols were developed massively during the COVID-19 outbreak.

PURPOSE

To study the impact on image quality (IQ) and the diagnosis reliability of COVID-19 low-dose chest computed tomography (CT) protocols.

MATERIAL AND METHODS

COVID-19 low-dose protocols were implemented on third- and second-generation CT scanners considering two body mass index (BMI) subgroups (<25 kg/m2 and >25 kg/m2). Contrast-to-noise ratios (CNR) were compared with a Catphan phantom. Next, two radiologists retrospectively assessed IQ for 243 CT patients using a 5-point Linkert scale for general IQ and diagnostic criteria. Kappa score and Wilcoxon rank sum tests were used to compare IQ score and CTDIvol between radiologists, protocols, and scanner models.

RESULTS

In vitro analysis of Catphan inserts showed in majority significantly decreased CNR for the low dose versus standard acquisition protocols on both CT scanners. However, in vivo, there was no impact on the diagnosis: sensitivity and specificity were ≥0.8 for all protocols and CT scanners. The third-generation scanner involved a significantly lower dose compared to the second-generation scanner (CTDIvol of 1.8 vs. 2.6 mGy for BMI <25 kg/m2 and 3.3 vs. 4.6 mGy for BMI >25 kg/m2). Still, the third-generation scanner showed a significantly higher IQ with the low-dose protocol compared to the second-generation scanner (30.9 vs. 28.1 for BMI <25 kg/m2 and 29.9 vs. 27.8 for BMI >25 kg/m2). Finally, the two radiologists had good global inter-reader agreement (kappa ≥0.6) for general IQ.

CONCLUSION

Low-dose protocols provided sufficient IQ independently of BMI subgroups and CT models without any impact on diagnosis reliability.

Implementation of AI image reconstruction in CT-how is it validated and what dose reductions can be achieved

CT reconstruction has undergone a substantial change over the last decade with the introduction of iterative reconstruction (IR) and now with deep learning reconstruction (DLR). In this review, DLR will be compared to IR and filtered back-projection (FBP) reconstructions. Comparisons will be made using image quality metrics such as noise power spectrum, contrast-dependent task-based transfer function, and non-prewhitening filter detectability index (dNPW'). Discussion on how DLR has impacted CT image quality, low-contrast detectability, and diagnostic confidence will be provided. DLR has shown the ability to improve in areas that IR is lacking, namely: noise magnitude reduction does not alter noise texture to the degree that IR did, and the noise texture found in DLR is more aligned with noise texture of an FBP reconstruction. Additionally, the dose reduction potential for DLR is shown to be greater than IR. For IR, the consensus was dose reduction should be limited to no more than 15-30% to preserve low-contrast detectability. For DLR, initial phantom and patient observer studies have shown acceptable dose reduction between 44 and 83% for both low- and high-contrast object detectability tasks. Ultimately, DLR is able to be used for CT reconstruction in place of IR, making it an easy "turnkey" upgrade for CT reconstruction. DLR for CT is actively being improved as more vendor options are being developed and current DLR options are being enhanced with second generation algorithms being released. DLR is still in its developmental early stages, but is shown to be a promising future for CT reconstruction.

"Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose4: a phantom study at different dose levels"

PURPOSE

To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR) algorithm for abdominal Computed Tomography (CT) imaging.

METHODS

CT images of the Catphan-600 phantom (equipped with an external annulus) were acquired using an abdominal protocol at four dose levels and reconstructed using FBP, iDose⁴ (levels 2,5) and PI ('Soft Tissue' definition, levels 'Sharper','Sharp','Standard','Smooth','Smoother'). Image noise, image non-uniformity, noise power spectrum (NPS), target transfer function (TTF), detectability index (d'), CT numbers accuracy and image histograms were analyzed.

RESULTS

The behavior of the PI algorithm depended strongly on the selected level of reconstruction. The phantom analysis suggested that the PI image noise decreased linearly by varying the level of reconstruction from Sharper to Smoother, expressing a noise reduction up to 80% with respect to FBP. Additionally, the non-uniformity decreased, the histograms became narrower, and d' values increased as PI reconstruction levels changed from Sharper to Smoother. PI had no significant impact on the average CT number of different contrast objects. The conventional FBP NPS was deeply altered only by Smooth and Smoother levels of reconstruction. Furthermore, spatial resolution was found to be dose- and contrast-dependent, but in each analyzed condition it was greater than or comparable to FBP and iDose⁴ TTFs.

CONCLUSIONS

The PI algorithm can reduce image noise with respect to FBP and iDose⁴; spatial resolution, CT numbers and image uniformity are generally preserved by the algorithm but changes in NPS for the Smooth and Smoother levels need to be considered in protocols implementation.

Early results of ultra-low-dose CT-scan for extremity traumas in emergency room

Background

Ultra-low dose computed tomography (ULD-CT) was shown to be a good alternative to digital radiographs in various locations. This study aimed to assess the diagnostic sensitivity and specificity of ULD-CT versus digital radiographs in patients consulting for extremity traumas in emergency room.

Methods

Digital radiography and ULD-CT scan were performed in patients consulting at the emergency department (February-August 2018) for extremity traumas. Fracture detection was evaluated retrospectively by two blinded independent radiologists. Sensitivity and specificity were evaluated using best value comparator (BVC) and a Bayesian latent class model (LCM) approaches and clinical follow-up. Image quality, quality diagnostic and diagnostic confidence level were evaluated (Likert scale). The effective dose received was calculated.

Results

Seventy-six consecutive patients (41 men, mean age: 35.2±13.2 years), with 31 wrists/hands and 45 ankles/feet traumas were managed by emergency physicians. According to clinical data, radiography had 3 false positive and 10 false negative examinations, and ULD-CT, 2 of each. Radiography and ULD-CT specificities were similar; sensitivities were lower for radiography, with BVC and Bayesian. With Bayesian, ULD-CT and radiography sensitivities were 90% (95% CI: 87-93%) and 76% (95% CI: 71-81%, P<0.0001) and specificities 96% (95% CI: 93-98%) and 93% (95% CI: 87-97%, P=0.84). The inter-observer agreement was higher for ULD-CT for all subjective indexes. The effective dose for ULD-CT and radiography was 0.84±0.14 and 0.58±0.27 µSv (P=0.002) for hand/wrist, and 1.50±0.32 and 1.44±0.78 µSv (P=NS) for foot/ankle.

Conclusions

With an effective dose level close to radiography, ULD-CT showed better detection of extremities fractures in the emergency room and may allow treatment adaptation. Further studies need to be performed to assess impact of such examination in everyday practice.

Trial Registration

ClinicalTrials.gov Identifier: NCT04832490.

Optimization of a customized simultaneous algebraic reconstruction technique algorithm for phase-contrast breast computed tomography

Objective. To introduce the optimization of a customized GPU-based simultaneous algebraic reconstruction technique (cSART) in the field of phase-contrast breast computed tomography (bCT). The presented algorithm features a 3D bilateral regularization filter that can be tuned to yield optimal performance for clinical image visualization and tissues segmentation. Approach. Acquisitions of a dedicated test object and a breast specimen were performed at Elettra, the Italian synchrotron radiation (SR) facility (Trieste, Italy) using a large area CdTe single-photon counting detector. Tomographic images were obtained at 5 mGy of mean glandular dose, with a 32 keV monochromatic x-ray beam in the free-space propagation mode. Three independent algorithms parameters were optimized by using contrast-to-noise ratio (CNR), spatial resolution, and noise texture metrics. The results obtained with the cSART algorithm were compared with conventional SART and filtered back projection (FBP) reconstructions. Image segmentation was performed both with gray scale-based and supervised machine-learning approaches. Main results. Compared to conventional FBP reconstructions, results indicate that the proposed algorithm can yield images with a higher CNR (by 35% or more), retaining a high spatial resolution while preserving their textural properties. Alternatively, at the cost of an increased image ‘patchiness’, the cSART can be tuned to achieve a high-quality tissue segmentation, suggesting the possibility of performing an accurate glandularity estimation potentially of use in the realization of realistic 3D breast models starting from low radiation dose images. Significance. The study indicates that dedicated iterative reconstruction techniques could provide significant advantages in phase-contrast bCT imaging. The proposed algorithm offers great flexibility in terms of image reconstruction optimization, either toward diagnostic evaluation or image segmentation.

Evaluation and comparison of performance of low-dose 128-slice CT scanner with different mAs values: A phantom study

OBJECTIVE:

Radiation dose in computed tomography (CT) has been the concern of physicists ever since the introduction of CT scan. The objective of this study was to evaluate the performance of low-dose 128-slice CT scanner with different mAs values.

MATERIALS AND METHODS:

Quantitative study was carried out at different values of mAs. Philips brilliance CT phantom with Philips ingenuity 128-slice low-dose CT scanner was chosen for this study. CT number linearity, CT number accuracy, slice thickness accuracy, high-contrast resolution, and low-contrast resolution were calculated and estimated computed tomography dose index volume (CTDI_vol) for all the mAs values were recorded. Noise was calculated for all mAs values for comparison.

RESULTS:

Data analysis shows that image quality was acceptable for all protocols. High-contrast resolution for all protocols was 20 line pairs per centimeter. Low-contrast resolution for 50 mAs images was 4 mm and 3 mm for other mAs protocols. Images acquired using 100 mAs revealed ring artifacts. CTDI_vol using 50 mAs was 33% of the CTDI_vol using 150 mAs. The dose–length product at 100 mAs was reduced to 66% of the dose–length product at 150 mAs, and the same at 50 mAs was reduced to 33%.

CONCLUSION:

It is evident here that mAs has direct impact on the radiation dose to patient. With iDose4, mAs can be reduced to 50 mAs in multislice low-dose CT scan to reduce the radiation dose with minimal effect on image quality for slice thickness 4 mm. However, noise would dominate at tube current lower than 50 mAs for 120 kVp.

Image Quality Assessment of Low-Dose CT using Hybrid Iterative Reconstruction

Abstract Background: X-ray computed tomography is the first imaging technology that supports accurate nondestructive interior image reconstruction of an object from sufficient projection data. Low-dose computed tomography (LDCT) has been considered to relieve the harm to patients caused by X-ray radiation. However, LDCT images can be degraded by quantum noise and streak artifacts.Methods: The objective of the authors’ study is to evaluate the optimal level of the hybrid iterative reconstruction (HIR) that generates images with the best diagnostic quality on different dose and noise levels. HIR with optimizations is proposed to reduce image noise and provide better performance at a low dose. The Catphan®504 phantom is employed to assess various image qualities (IQ).Results: For any given scanning protocols, there is linear noise reduction and linear increase of contrast-to-noise ratio (CNR) using optimal HIR. The evidence from various module tests demonstrates that the shape of the noise power spectrum is continuously shifted to low frequency with increasing HIR levels compared with that of filtered-back-projection (FBP). This may describe the difference between the human observer performance and features of the ideal low-contrast objects.Conclusion: Optimal HIR is clearly demonstrated to be a superior method for reducing image noise and improving CNR compared to FBP. Optimal HIR also inhibits texture change or spectrum shift compared with the pure IR method. Even though there are continuous noise reduction and CNR increase with HIR at increasing levels, the human observer performance does not seem to improve simultaneously due to coarser noise (low-frequency noise). HIR level 3 to 5 is optimal for their study. It is possible for the optimal HIR to offer equivalent diagnostic IQ at a lower dose compared with FBP at a routine dose.

Comparison of two deep learning image reconstruction algorithms in chest CT images: A task-based image quality assessment on phantom data

PURPOSE

The purpose of this study was to compare the effect of two deep learning image reconstruction (DLR) algorithms in chest computed tomography (CT) with different clinical indications.

MATERIAL AND METHODS

Acquisitions on image quality and anthropomorphic phantoms were performed at six dose levels (CTDI_vol: 10/7.5/5/2.5/1/0.5mGy) on two CT scanners equipped with two different DLR algorithms (TrueFidelity^TM and AiCE). Raw data were reconstructed using the filtered back-projection (FBP) and the lowest/intermediate/highest DLR levels (L-DLR/M-DLR/H-DLR) of each algorithm. Noise power spectrum, task-based transfer function (TTF) and detectability index (d') were computed: d' modelled detection of a soft tissue mediastinal nodule, ground-glass opacity, or high-contrast pulmonary lesion. Subjective image quality of anthropomorphic phantom images was analyzed by two radiologists.

RESULTS

For the L-DLR/M-DLR levels, the noise magnitude was lower with TrueFidelity^TM than with AiCE from 2.5 to 10 mGy. For H-DLR, noise magnitude was lower with AiCE . For L-DLR and M-DLR, the average NPS spatial frequency (f_av) values were greater for AiCE except for 0.5 mGy. For H-DLR levels, f_av was greater for TrueFidelity^TM than for AiCE. TTF_50% values were greater with AiCE for the air insert, and lower than TrueFidelity^TM for the polyethylene insert. From 2.5 to10 mGy, d' was greater for AiCE than for TrueFidelity^TM for H-DLR for all lesions, but similar for L-DLR and M-DLR. Image quality was rated clinically appropriate for all levels of both algorithms, for dose from 2.5 to 10 mGy, except for L-DLR of AiCE.

CONCLUSION

DLR algorithms reduce the image-noise and improve lesion detectability. Their operations and properties impacted both noise-texture and spatial resolution.

Diagnostic performance and image quality of deep learning image reconstruction (DLIR) on unenhanced low-dose abdominal CT for urolithiasis

BACKGROUND

Patients with urolithiasis undergo radiation overexposure from computed tomography (CT) scans. Improvement of image reconstruction is necessary for radiation dose reduction.

PURPOSE

To evaluate a deep learning-based reconstruction algorithm for CT (DLIR) in the detection of urolithiasis at low-dose non-enhanced abdominopelvic CT.

MATERIAL AND METHODS

A total of 75 patients who underwent low-dose abdominopelvic CT for urolithiasis were retrospectively included. Each examination included three reconstructions: DLIR; filtered back projection (FBP); and hybrid iterative reconstruction (IR; ASiR-V 70%). Image quality was subjectively and objectively assessed using attenuation and noise measurements in order to calculate the signal-to-noise ratio (SNR), absolute contrast, and contrast-to-noise ratio (CNR). Attenuation of the largest stones were also compared. Detectability of urinary stones was assessed by two observers.

RESULTS

Image noise was significantly reduced with DLIR: 7.2 versus 17 and 22 for ASiR-V 70% and FBP, respectively. Similarly, SNR and CNR were also higher compared to the standard reconstructions. When the structures had close attenuation values, contrast was lower with DLIR compared to ASiR-V. Attenuation of stones was also lowered in the DLIR series. Subjective image quality was significantly higher with DLIR. The detectability of all stones and stones >3 mm was excellent with DLIR for the two observers (intraclass correlation [ICC] = 0.93 vs. 0.96 and 0.95 vs. 0.99). For smaller stones (<3 mm), results were different (ICC = 0.77 vs. 0.86).

CONCLUSION

For low-dose abdominopelvic CT, DLIR reconstruction exhibited image quality superior to ASiR-V and FBP as well as an excellent detection of urinary stones.

Ultra-low-dose chest CT performance for the detection of viral pneumonia patterns during the COVID-19 outbreak period: a monocentric experience

Background

Ultra low dose chest computed tomography (CT) acquisitions have been used for selected emergency room patients with acute dyspnea or minor thoracic trauma. The purpose of this study was to evaluate the diagnostic performance of ultra-low-dose (ULD) chest CT for detecting viral pneumonia patterns compared to standard (STD) dose chest CT.

Methods

All consecutive adult patients with two non-enhanced chest CT acquisitions, one STD and one ULD, for suspicion of viral pneumonia between March 5^th and April 2^nd 2020 were included. CT results were divided into two groups: non-viral pneumonia CT or compatible with viral pneumonia CT based on viral pneumonia CT patterns: ground-glass opacity (GGO), consolidation, crazy paving, air bronchogram signs and fibrous stripes. The diagnostic performance of ULD CT for suspicion of viral pneumonia was evaluated. For CTs compatible with viral pneumonia, CT pattern detection on ULD CT was assessed and STD CT was used as a reference.

Results

The study included 380 patients with 97 CTs (25.5%) compatible with viral pneumonia. The mean effective doses (EDs) were 1.66 (1.29; 2.18) mSv for STD and 0.20 (0.18; 0.22) mSv for ULD CT (P<0.001). The sensitivity and specificity of ULD CT for viral pneumonia detection were 98.9% and 99.0%, respectively. GGO, consolidation and fibrous stripes were equally visible in STD and ULD in 100% (n=97), 36% (n=35) and 23% (n=22) of compatible viral pneumonia-CT patients, respectively. Air bronchogram sign detection was equivalent, concerning 23% (n=22) of patients in STD and 22% (n=21) in ULD. Crazy paving was visible in 24% (n=23) of patients in STD and only 8% (n=8) in ULD (P=0.003).

Conclusions

In comparison to STD dose chest CT, ULD chest CT, with a mean reduction dose of 88.0%, has comparable diagnostic performance for detecting viral pneumonia on CT.

Diagnostic performance of ultra-low dose versus standard dose CT for non-traumatic abdominal emergencies

PURPOSE

The purpose of this study was to compare the diagnostic performance of ultra-low dose (ULD) to that of standard (STD) computed tomography (CT) for the diagnosis of non-traumatic abdominal emergencies using clinical follow-up as reference standard.

MATERIALS AND METHODS

All consecutive patients requiring emergency abdomen-pelvic CT examination from March 2017 to September 2017 were prospectively included. ULD and STD CTs were acquired after intravenous administration iodinated contrast medium (portal phase). CT acquisitions were performed at 125mAs for STD and 55mAs for ULD. Diagnostic performance was retrospectively evaluated on ULD and STD CTs using clinical follow-up as a reference diagnosis.

RESULTS

A total of 308 CT examinations from 308 patients (145 men; mean age 59.1±20.7 (SD) years; age range: 18-96 years) were included; among which 241/308 (78.2%) showed abnormal findings. The effective dose was significantly lower with the ULD protocol (1.55±1.03 [SD] mSv) than with the STD (3.67±2.56 [SD] mSv) (P<0.001). Sensitivity was significantly lower for the ULD protocol (85.5% [95%CI: 80.4-89.4]) than for the STD (93.4% [95%CI: 89.4-95.9], P<0.001) whereas specificities were similar (94.0% [95%CI: 85.1-98.0] vs. 95.5% [95%CI: 87.0-98.9], respectively). ULD sensitivity was equivalent to STD for bowel obstruction and colitis/diverticulitis (96.4% [95%CI: 87.0-99.6] and 86.5% [95%CI: 74.3-93.5] for ULD vs. 96.4% [95%CI: 87.0-99.6] and 88.5% [95%CI: 76.5-94.9] for STD, respectively) but lower for appendicitis, pyelonephritis, abscesses and renal colic (75.0% [95%CI: 57.6-86.9]; 77.3% [95%CI: 56.0-90.1]; 90.5% [95%CI: 69.6-98.4] and 85% [95%CI: 62.9-95.4] for ULD vs. 93.8% [95%CI: 78.6-99.2]; 95.5% [95%CI: 76.2-100.0]; 100.0% [95%CI: 81.4-100.0] and 100.0% [95%CI: 80.6-100.0] for STD, respectively). Sensitivities were significantly different between the two protocols only for appendicitis (P=0.041).

CONCLUSION

In an emergency context, for patients with non-traumatic abdominal emergencies, ULD-CT showed inferior diagnostic performance compared to STD-CT for most abdominal conditions except for bowel obstruction and colitis/diverticulitis detection.

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.

Ultra-low-dose CT versus radiographs for minor spine and pelvis trauma: a Bayesian analysis of accuracy

OBJECTIVES

To compare diagnosis performance and effective dose of ultra-low-dose CT (ULD CT) versus radiographs in suspected spinal or pelvic ring or hip fracture for minor trauma.

METHODS

ULD CT, in addition to radiography, was prospectively performed in consecutive patients admitted to the emergency department for minor traumas, during working hours over 2 months. Presence of a recent fracture was assessed by two blind radiologists independently. Sensitivities and specificities were estimated using the best valuable comparator (BVC) as a reference and using a latent class model in Bayesian inference (BLCM). Dosimetric indicators were recorded and effective doses (E) were calculated using conversion coefficient.

RESULTS

Eighty areas were analyzed in 69 patients, including 22 dorsal spine, 28 lumbar spine, and 30 pelvic ring/hip. Thirty-six fractures (45%) were observed. Applying the BVC method, depending on location, ULD CT sensitivity was 80 to 100% for reader 1 and 85 to 100% for reader 2, whereas radiographic sensitivity was 60 to 85% for reader 1 and 50 to 92% for reader 2. With BLCM approach for reader 2, ULD CT sensitivity for all locations/dorsal spine/lumbar spine and pelvic ring-hip was 87.1/75.9/84.2/76.9% respectively. Corresponding radiograph sensitivity was 73.8, 54.8, 80.4, and 68.7%. Effective doses of ULD CT were similar to radiographs for dorsal and hip locations whereas for lumbar spine, ULD CT effective dose was 1.83 ± 0.59 mSv compared with 0.96 ± 0.59 mSv (p < 0.001).

CONCLUSION

Sensitivity for fracture detection was higher for ULD CT compared with radiographs with an effective dose comparable to radiographs.

KEY POINTS

• Ultra-low-dose spine and pelvis CT demonstrates better fracture detection when compared with radiographs. • The effective dose of ultra-low-dose spine and pelvis CT scan and radiographs is comparable. • Replacement of radiographs by ULD CT in daily practice for trauma patients is an option to consider and should be evaluated by a randomized trial.

Protocol Optimization for Renal Mass Detection and Characterization

Renal masses increasingly are found incidentally, largely due to the frequent use of medical imaging. Computed tomography (CT) and MR imaging are mainstays for renal mass characterization, presurgical planning of renal tumors, and surveillance after surgery or systemic therapy for advanced renal cell carcinomas. CT protocols should be tailored to different clinical indications, balancing diagnostic accuracy and radiation exposure. MR imaging protocols should take advantage of the improved soft tissue contrast for renal tumor diagnosis and staging. Optimized imaging protocols enable analysis of imaging features that help narrow the differential diagnoses and guide management in patients with renal masses.

Cone-beam breast computed tomography using ultra-fast image reconstruction with constrained, total-variation minimization for suppression of artifacts

Compressed sensing based iterative reconstruction algorithms for computed tomography such as adaptive steepest descent-projection on convex sets (ASD-POCS) are attractive due to their applicability in incomplete datasets such as sparse-view data and can reduce radiation dose to the patients while preserving image quality. Although IR algorithms reduce image noise compared to analytical Feldkamp-Davis-Kress (FDK) algorithm, they may generate artifacts, particularly along the periphery of the object. One popular solution is to use finer image-grid followed by down-sampling. This approach is computationally intensive but may be compensated by reducing the field of view. Our proposed solution is to replace the algebraic reconstruction technique within the original ASD-POCS by ordered subsets-simultaneous algebraic reconstruction technique (OS-SART) and with initialization using FDK image. We refer to this method as Fast, Iterative, TV-Regularized, Statistical reconstruction Technique (FIRST). In this study, we investigate FIRST for cone-beam dedicated breast CT with large image matrix. The signal-difference to noise ratio (SDNR), the difference of the mean value and the variance of adipose and fibroglandular tissues for both FDK and FIRST reconstructions were determined. With FDK serving as the reference, the root-mean-square error (RMSE), bias, and the full-width at half-maximum (FWHM) of microcalcifications in two orthogonal directions were also computed. Our results suggest that FIRST is competitive to the finer image-grid method with shorter reconstruction time. Images reconstructed using the FIRST do not exhibit artifacts and outperformed FDK in terms of image noise. This suggests the potential of this approach for radiation dose reduction in cone-beam breast CT.

Design and evaluation of an accurate CNR-guided small region iterative restoration-based tumor segmentation scheme for PET using both simulated and real heterogeneous tumors

Tumor delineation accuracy directly affects the effectiveness of radiotherapy. This study presents a methodology that minimizes potential errors during the automated segmentation of tumors in PET images. Iterative blind deconvolution was implemented in a region of interest encompassing the tumor with the number of iterations determined from contrast-to-noise ratios. The active contour and random forest classification-based segmentation method was evaluated using three distinct image databases that included both synthetic and real heterogeneous tumors. Ground truths about tumor volumes were known precisely. The volumes of the tumors were in the range of 0.49-26.34 cm³, 0.64-1.52 cm³, and 40.38-203.84 cm³ respectively. Widely available software tools, namely, MATLAB, MIPAV, and ITK-SNAP were utilized. When using the active contour method, image restoration reduced mean errors in volumes estimation from 95.85 to 3.37%, from 815.63 to 17.45%, and from 32.61 to 6.80% for the three datasets. The accuracy gains were higher using datasets that include smaller tumors for which PVE is known to be more predominant. Computation time was reduced by a factor of about 10 in the smaller deconvolution region. Contrast-to-noise ratios were improved for all tumors in all data. The presented methodology has the potential to improve delineation accuracy in particular for smaller tumors at practically feasible computational times. Graphical abstract Evaluation of accurate lesion volumes using CNR-guided and ROI-based restoration method for PET images.

Noise assessment across two generations of iterative reconstruction algorithms of three manufacturers using bone reconstruction kernel

PURPOSE

To compare the noise-magnitude and noise-texture obtained using strong kernel across two generations of iterative reconstruction (IR) algorithms proposed by three manufacturers.

MATERIALS AND METHODS

Five computed tomography (CT) systems equipped with two generations of IR algorithm (hybrid/statistical IR [H/SIR] or full/partial model-based IR [MBIR]) were compared. Acquisitions on Catphan 600 phantom were performed at 120kV and three dose levels (CTDI_vol: 3, 7 and 12mGy). Raw data were reconstructed using standard "bone" kernel for filtered back projection and one iterative level of two generations of IR algorithms. Contrast-to-noise ratio (CNR) was computed using three regions of interest placed semi-automatically: two placed in the low-density polyethylene and Teflon inserts and another placed on the solid water. Noise power spectrum (NPS) was computed to assess the NPS-peak and noise-texture.

RESULTS

CNR was significantly greater in MBIR compared to H/SIR algorithms for all CT systems (P<0.01). CNR were improved on average from H/SIR to MBIR of 36±14% [SD] (range: 24-57%) for GE-Healthcare, 109±19 [SD] % (range: 89-139%) for Philips Healthcare and 42±5 [SD] % (range: 36-47%) for Siemens Healthineers. The mean NPS peak decreased from H/SIR to MBIR by -41±6 [SD] % (range: -47--35%) for GE Healthcare, -79±3 [SD] % (range: -82--76%) for Philips Healthcare and -52±2 [SD] % (range: -54--51%) for Siemens Healthineers systems. NPS spatial frequencies were greater with MBIR than with H/SIR for Philips Healthcare (20 ± 2 [SD] %; range: 19-22%) and for Siemens Healthineers (9±5 [SD] %; range: 4-14%) but lower for GE Healthcare (-17±3 [SD] %; range: -14--20%).

CONCLUSION

Using bone kernel with recent MBIR algorithms reduces the noise-magnitude for all CT systems assessed. Noise texture shifted towards high frequency for Siemens Healthineers and Philips Healthcare but the opposite for GE Healthcare.

The effect of vertical centering and scout direction on automatic tube voltage selection in chest CT: a preliminary phantom study on two different CT equipments

Purpose

To determine the effect of patient's vertical off-centering and scout direction on the function of automatic tube voltage selection (ATVS) and tube current modulation (TCM) in chest computed tomography (CT).

Methods

Chest phantom was scanned with Siemens and GE CT systems using three clinical chest CT protocols exploiting ATVS and a fixed 120 kVp chest protocol. The scans were performed at five vertical positions of the phantom (-6 to +6 cm from the scanner isocenter). The effects of scout direction (posterior-to-anterior, anterior-to-posterior, and lateral) and vertical off-centering on the function of ATVS and TCM were studied by examining changes in selected voltage, radiation dose (volume CT dose index, CTDI_vol), and image noise and contrast.

Results

Both scout direction and vertical off-centering affected ATVS. The effect differed between the vendors for the studied geometry, demonstrating differences in technical approaches. The greatest observed increase in CTDI_vol due to off-centering was 91%. Anterior-to-posterior scout produced highest doses at the uppermost table position, whereas posterior-to-anterior scout produced highest doses at the lowermost table position. Dose varied least using lateral scouts. Vertical off-centering impacted image noise and contrast due to the combined effect of ATVS, TCM, structural noise, and bowtie filters.

Conclusions

Patient vertical off-centering and scout direction affected substantially the CTDI_vol and image quality in chest CT examinations. Vertical off-centering caused variation also in the selected tube voltage. The function of ATVS and TCM methods differ significantly between the CT vendors, resulting in differences in CTDI_vol and image noise characteristics.

Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions

OBJECTIVE

The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP).

METHODS AND MATERIALS

Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed.

RESULTS

Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P < 0.05). Adaptive statistical iterative reconstruction-V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P <0.0001). Veo 3.0 and ASIR 80% had the best and worst spatial resolution, respectively.

CONCLUSIONS

Adaptive statistical iterative reconstruction-V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

Estimation of lifetime attributable risks (LARs) of cancer associated with abdominopelvic radiotherapy treatment planning computed tomography (CT) simulations

PURPOSE

The present study attempts to calculate organ-absorbed and effective doses for cancer patients to estimate the possible cancer induction and cancer mortality risks resulting from 64-slice abdominopelvic computed tomography (CT) simulations for radiotherapy treatment planning (RTTP).

MATERIAL AND METHODS

A group of 70 patients, who underwent 64-slice abdominopelvic CT scan for RTTP, voluntarily participated in the present study. To calculate organ and effective doses in a standard phantom of 70 kg, the collected dosimetric parameters were used with the ImPACT CT Patient Dosimetry Calculator. Patient-specific organ dose and effective dose were calculated by applying related correction factors. For the estimation of lifetime attributable risks (LARs) of cancer incidence and cancer-related mortality, doses in radiosensitive organs were converted to risks based on the data published in Biological Effects of Ionizing Radiation VII (BEIR VII).

RESULTS

The mean ± standard deviation (SD) of the effective dose for males and females were 13.87 ± 2.37 mSv (range: 9.25-18.82 mSv) and 13.04 ± 3.42 mSv (range: 6.99-18.37 mSv), respectively. The mean ± SD of LAR of cancer incidence was 35.34 ± 13.82 cases in males and 34.49 ± 9.63 cases in females per 100,000 persons. The LAR of cancer mortality had the mean ± SD value of 15.38 ± 4.25 and 16.72 ± 3.87 cases per 100,000 persons in males and females respectively.

CONCLUSION

Increase in the LAR of cancer occurrence and mortality due to abdominopelvic treatment planning CT simulation is noticeable and should be considered.

Experience With Iterative Reconstruction Techniques for Abdominopelvic Computed Tomography in Morbidly and Super Obese Patients

OBJECTIVE

The aim of this study was to investigate the diagnostic performance of abdominopelvic computed tomography (CT) images reconstructed using filtered back projection (FBP) and iterative reconstruction (IR) algorithms in morbidly and super obese patients.

MATERIALS AND METHODS

One hundred eighty-seven abdominopelvic CT examinations in portal venous phase were performed between February 2015 and February 2016 in 182 patients (mean age = 52 years, mean body mass index = 45.5). One hundred fourteen of 187 examinations were reconstructed using IR and 73 examinations were processed using FBP. Patients were further stratified based on body mass index. Sixty CT scans were reviewed by a single reader for image quality, image noise, and artifacts. Objective noise and attenuation were also determined. Size-specific dose estimate and CT dose index volume were compared and statistically analyzed.

RESULTS

A diagnostic interpretation was rendered for all 187 examinations. A single-reader review of 60 cases showed greater diagnostic acceptability for IR when compared with FBP (image quality = 4.2 and 3.8 [P = 0.035], noise = 1.5 and 1.6 [P = 0.692], artifact = 1.4 and 1.5 [P = 0.759], respectively). For all examinations, the IR group had lower objective image noise (IR = 9.3 and FBP = 14.3; P < 0.001) and higher contrast-to-noise ratio (IR = 17.2 and FBP = 11.7; P < 0.001) without increase in radiation dose (size-specific dose estimate [IR = 15.1, FBP = 16.5 mGy; P = 0.045] and CT dose index volume [IR = 17.6, FBP = 18 mGy; P = 0.62]).

CONCLUSIONS

In morbidly and super obese patients, diagnostic quality images could be reliably generated with minimal artifacts and noise using newer generation scanners integrated with IR without increasing radiation dose.

Effect of automatic exposure technique combined with iterative reconstruction on radiation dose of liver computed tomography

AIM

To observe the effect of automatic exposure technique combined with iterative reconstruction on radiation dose of liver computed tomography (CT).

METHODS

From July 2016 to July 2017, 69 patients who underwent liver enhanced CT examinations were randomly divided into control group, group A, and group B (23 cases in each group), in which reconstruction was performed using filtered back projection, automatic exposure technique, and automatic exposure technique combined with iterative reconstruction (strength 3), respectively. The CT values of different parts in CT images, subjective evaluation, objective evaluation, and radiation dose were comparatively analyzed in the three groups.

RESULTS

There was no significant difference in the CT values of the liver, portal vein, and paraspinal muscles in the three groups (P > 0.05). The subjective evaluation indexes (such as visibility, pixel performance, and overall diagnostic confidence) of CT images in groups A and B were significantly higher than those of the control group (P < 0.05), and the scores of group B were significantly higher than those of group A (P < 0.05). The noise intensity of groups A and B was significantly lower than that of the control group, while the signal to noise ratio and contrast to noise ratio were significantly higher than those in the control group, with group B performing significantly better than group A (P < 0.05). The radiation doses in groups A and B were 8.57 mSv ± 0.86 mSv and 6.92 mSv ± 0.51 mSv, respectively, which were significantly lower than that in the control group.

CONCLUSION

In liver CT examination, using automatic exposure technology combined with iterative reconstruction technology can significantly improve the image quality and reduce radiation dose effectively.

EFFECT OF PATIENT SIZE, ANATOMICAL LOCATION AND MODULATION STRENGTH ON DOSE DELIVERED AND IMAGE-QUALITY ON CT EXAMINATION

To study the effect of patient size, anatomical location and modulation strength (MS) on image-quality and delivered dose of CT scans acquired with automatic-exposure-control system (AEC). Four anthropomorphic phantoms (three paediatric and one thin adult) were studied, and normal and obese adults were simulated by placing bolus plates around the adult phantom. Thorax and abdomen-pelvis CT were performed using an AEC system equipped with five possible MS. Modulated tube current (mAsmod) was compared to Reference mAs and image-noise was assessed. Effective-mAs were lower than Reference-mAs for all but the obese phantom. However, reversal points were estimated for an effective diameter of 27.8 cm in thorax and 26.9 cm in abdomen-pelvis scans, beyond which the patterns of MS were inversed. mAsmod were dependent on attenuation differences among distinct anatomical location. Finally, dose delivered was associated to the mAsmod and patient's size, with both affecting image-quality.

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

BACKGROUND

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment.

METHODS

Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images.

RESULTS

Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result.

CONCLUSION

IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

Diagnosis of acute overt gastrointestinal bleeding with CT-angiography: Comparison of the diagnostic performance of individual acquisition phases

PURPOSE

To compare the respective values of arterial phase, portal venous phase and combination of phases using 64-section multidetector computed tomography (MDCT) for diagnosing acute overt gastrointestinal bleeding (AOGIB).

PATIENTS AND METHODS

Forty-nine patients with AOGIB were included. There were 30 men and 19 women, with a mean age of 65.4±15.6 (SD) years [range, 34-91years]. Two observers reviewed MDCT examinations in consensus for presence of active bleeding, location of bleeding site and nature of causative lesion. The different acquisition phases were reviewed independently.

RESULTS

AOGIB was identified in 28/49 patients (57%) with the multiphasic set, in 26/49 patients (53%) with arterial phase and in 25/49 patients (51%) with portal venous phase. Multiphasic set helped locate the bleeding site in 40/49 patients (82%). The cause was elucidated in 23/49 patients (47%) with multiphasic set. The differences between set performances were not statistically significant. Sensitivity for depicting AOGIB with the multiphasic set was 92% and specificity was 76%.

CONCLUSION

Multiphasic 64-section MDCT has high diagnostic performances in patients with AOGIB. Further studies with a larger population are needed to reach statistical significance and demonstrate better diagnostic performance of multiphasic MDCT in comparison with the arterial or portal phase alone.

Detection of small-bowel tumours with CT enteroclysis using carbon dioxide and virtual enteroscopy: A preliminary study

PURPOSE

The aim of this prospective study was to evaluate the feasibility, tolerance and performance of virtual enteroscopy (VE) using carbon dioxide for small-bowel distension in patients with suspected small-bowel tumours (SBTs).

PATIENTS AND METHODS

After IRB approval, 17 patients with suspected SBTs were prospectively included. Radiation dose was compared to 34 matched patients (2 for 1) for age, gender and body weight, who had undergone CT-enteroclysis with neutral contrast (CTE). Performance of VE was evaluated through comparison with the current standard of reference, including surgery and/or enteroscopy and/or follow-up.

RESULTS

Tolerance was excellent in 16/17 patients (94%). The radiation dose was lower for VE than for CTE (533 ± 282 vs. 974 ± 505 mGy.cm; p = 0.002). With VE, a total of 25 polyps >5 mm in size were depicted in 12/17 patients. On a per-lesion analysis, sensitivity and positive predictive value of VE were 92.0% and 92.0%, respectively. On a per-segment analysis VE had a sensitivity and specificity of 95.0% and 87.0%, respectively.

CONCLUSION

Our preliminary study suggests that VE is a feasible and well-tolerated technique with high sensitivity and specificity for the diagnosis of SBT.

KEY POINTS

• Virtual enteroscopy is feasible and well tolerated. • Virtual enteroscopy appears to be accurate for detection of small-bowel tumours. • Sensitivity and PPV of virtual enteroscopy is 92.0% and 92.0%. • Radiation dose is lower with virtual enteroscopy compared to MDCT-enteroclysis.

Imaging Pancreatic Cysts with CT and MRI

CT and MRI are the imaging modalities of choice to guide the clinical management of incidentally discovered pancreatic cysts. Most of these lesions are mucinous cysts with varying degrees of malignant potential. This article reviews the CT and MRI findings that help differentiate a potentially aggressive lesion that requires EUS or surgery from a lesion of low malignant potential that is appropriate for imaging surveillance. The imaging-based societal guidelines for these cysts are reviewed.

CT imaging of solid renal masses: pitfalls and solutions

Computed tomography (CT) remains the first-line imaging test for the characterisation of renal masses; however, CT has inherent limitations, which if unrecognised, may result in errors. The purpose of this manuscript is to present 10 pitfalls in the CT evaluation of solid renal masses. Thin section non-contrast enhanced CT (NECT) is required to confirm the presence of macroscopic fat and diagnosis of angiomyolipoma (AML). Renal cell carcinoma (RCC) can mimic renal cysts at NECT when measuring <20 HU, but are usually heterogeneous with irregular margins. Haemorrhagic cysts (HC) may simulate solid lesions at NECT; however, a homogeneous lesion measuring >70 HU is essentially diagnostic of HC. Homogeneous lesions measuring 20-70 HU at NECT or >20 HU at contrast-enhanced (CE) CT, are indeterminate, requiring further evaluation. Dual-energy CT (DECT) can accurately characterise these lesions at baseline through virtual NECT, iodine overlay images, or quantitative iodine concentration analysis without recalling the patient. A minority of hypo-enhancing renal masses (most commonly papillary RCC) show indeterminate or absent enhancement at multiphase CT. Follow-up, CE ultrasound or magnetic resonance imaging (MRI) is required to further characterise these lesions. Small (<3 cm) endophytic cysts commonly show pseudo-enhancement, which may simulate RCC; this can be overcome with DECT or MRI. In small (<4 cm) solid renal masses, 20% of lesions are benign, chiefly AML without visible fat or oncocytoma. Low-dose techniques may simulate lesion heterogeneity due to increased image noise, which can be ameliorated through the appropriate use of iterative reconstruction algorithms.

Evaluation of S100B blood level as a biomarker to avoid computed tomography in patients with mild head trauma under antithrombotic medication

PURPOSE

The goal of this prospective study was to analyze the potential of S100B protein as a negative predictive marker for intracranial hemorrhage (ICH) after mild head trauma (MHT) in patient under antithrombotic medication.

METHODS

Patients under antithrombotic medication who had MHT were consecutively included in this study. S100B blood levels were determined from samples drawn within 6hours after injury and were analyzed with the results of head CT performed within the 24hours after injury. Sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) of S100B levels for the detection of ICH, with a cut-off set at 0.105μg/L, were calculated.

RESULTS

A total of 308 patients (151 men and 157 women) with a mean age of 79.1±10.5years (SD) were included in the analysis. CT was positive for the presence of ICH in 33 patients (10.7%; 95% CI: 7.5-14.7%). In the study population, S100B showed a sensitivity of 84.8% (95%CI: 68.1-94.9%), a specificity of 30.2% (95% CI: 24.8-36.0%), a NPV of 94.3% (95% CI: 87.2-98.1%), and a PPV of 12.7% (95% CI: 8.6-17.9%) for the diagnosis of ICH.

CONCLUSION

The results of this study suggest that a S100B serum level<0.105μg/L has a high NPV for ICH after mild head trauma in patients under antithrombotic medication.

The Acceptability of Iterative Reconstruction Algorithms in Head CT: An Assessment of Sinogram Affirmed Iterative Reconstruction (SAFIRE) vs. Filtered Back Projection (FBP) Using Phantoms

BACKGROUND

Computed tomography (CT) is the primary imaging investigation for many neurologic conditions with a proportion of patients incurring cumulative doses. Iterative reconstruction (IR) allows dose optimization, but head CT presents unique image quality complexities and may lead to strong reader preferences.

OBJECTIVES

This study evaluates the relationships between image quality metrics, image texture, and applied radiation dose within the context of IR head CT protocol optimization in the simulated patient setting. A secondary objective was to determine the influence of optimized protocols on diagnostic confidence using a custom phantom.

METHODS AND SETTING

A three-phase phantom study was performed to characterize reconstruction methods at the local reference standard and a range of exposures. CT numbers and pixel noise were quantified supplemented by noise uniformity, noise power spectrum, contrast-to-noise ratio (CNR), high- and low-contrast resolution. Reviewers scored optimized protocol images based on established reporting criteria.

RESULTS

Increasing strengths of IR resulted in lower pixel noise, lower noise variance, and increased CNR. At the reference standard, the image noise was reduced by 1.5 standard deviation and CNR increased by 2.0. Image quality was maintained at ≤24% relative dose reduction. With the exception of image sharpness, there were no significant differences between grading for IR and filtered back projection reconstructions.

CONCLUSIONS

IR has the potential to influence pixel noise, CNR, and noise variance (image texture); however, systematically optimized IR protocols can maintain the image quality of filtered back projection. This work has guided local application and acceptance of lower dose head CT protocols.