Deep learning-based image domain reconstruction enhances image quality and pulmonary nodule detection in ultralow-dose CT with adaptive statistical iterative reconstruction-V

OBJECTIVES

To evaluate the image quality and lung nodule detectability of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) post-processed using a deep learning image reconstruction (DLIR)-based image domain compared to low-dose CT (LDCT) and ULDCT without DLIR.

MATERIALS AND METHODS

A total of 210 patients undergoing lung cancer screening underwent LDCT (mean ± SD, 0.81 ± 0.28 mSv) and ULDCT (0.17 ± 0.03 mSv) scans. ULDCT images were reconstructed with ASiR-V (ULDCT-ASiR-V) and post-processed using DLIR (ULDCT-DLIR). The quality of the three CT images was analyzed. Three radiologists detected and measured pulmonary nodules on all CT images, with LDCT results serving as references. Nodule conspicuity was assessed using a five-point Likert scale, followed by further statistical analyses.

RESULTS

A total of 463 nodules were detected using LDCT. The image noise of ULDCT-DLIR decreased by 60% compared to that of ULDCT-ASiR-V and was lower than that of LDCT (p < 0.001). The subjective image quality scores for ULDCT-DLIR (4.4 [4.1, 4.6]) were also higher than those for ULDCT-ASiR-V (3.6 [3.1, 3.9]) (p < 0.001). The overall nodule detection rates for ULDCT-ASiR-V and ULDCT-DLIR were 82.1% (380/463) and 87.0% (403/463), respectively (p < 0.001). The percentage difference between diameters > 1 mm was 2.9% (ULDCT-ASiR-V vs. LDCT) and 0.5% (ULDCT-DLIR vs. LDCT) (p = 0.009). Scores of nodule imaging sharpness on ULDCT-DLIR (4.0 ± 0.68) were significantly higher than those on ULDCT-ASiR-V (3.2 ± 0.50) (p < 0.001).

CONCLUSION

DLIR-based image domain improves image quality, nodule detection rate, nodule imaging sharpness, and nodule measurement accuracy of ASiR-V on ULDCT.

KEY POINTS

Question Deep learning post-processing is simple and cheap compared with raw data processing, but its performance is not clear on ultralow-dose CT. Findings Deep learning post-processing enhanced image quality and improved the nodule detection rate and accuracy of nodule measurement of ultralow-dose CT. Clinical relevance Deep learning post-processing improves the practicability of ultralow-dose CT and makes it possible for patients with less radiation exposure during lung cancer screening.

Ultra-low dose dual-layer detector spectral CT for pulmonary nodule screening: image quality and diagnostic performance

OBJECTIVES

To investigate the image quality and diagnostic performance with ultra-low dose dual-layer detector spectral CT (DLSCT) by various reconstruction techniques for evaluation of pulmonary nodules.

MATERIALS AND METHODS

Between April 2023 and December 2023, patients with suspected pulmonary nodules were prospectively enrolled and underwent regular-dose chest CT (RDCT; 120 kVp/automatic tube current) and ultra-low dose CT (ULDCT; 100 kVp/10 mAs) on a DLSCT scanner. ULDCT was reconstructed with hybrid iterative reconstruction (HIR), electron density map (EDM), and virtual monoenergetic images at 40 keV and 70 keV. Quantitative and qualitative image analysis, nodule detectability, and Lung-RADS evaluation were compared using repeated one-way analysis of variance, Friedman test, and weighted kappa coefficient.

RESULTS

A total of 249 participants (mean age ± standard deviation, 50.0 years ± 12.9; 126 male) with 637 lung nodules were included. ULDCT resulted in a significantly lower mean radiation dose than RDCT (0.3 mSv ± 0.0 vs. 3.6 mSv ± 0.8; p < 0.001). Compared with RDCT, ULDCT EDM showed significantly higher signal-noise-ratio (44.0 ± 77.2 vs. 4.6 ± 6.6; p < 0.001) and contrast-noise-ratio (26.7 ± 17.7 vs. 5.0 ± 4.4; p < 0.001) with qualitative scores ranked higher or equal to the average. Using the regular-dose images as a reference, ULDCT EDM images had a satisfactory nodule detection rate (84.6%) and good inter-observer agreements compared with RDCT (κw > 0.60).

CONCLUSION

Ultra-low dose dual-layer detector CT with 91.2% radiation dose reduction achieves sufficient image quality and diagnostic performance of pulmonary nodules.

CRITICAL RELEVANCE STATEMENT

Dual-layer detector spectral CT enables substantial radiation dose reduction without impairing image quality for the follow-up of pulmonary nodules or lung cancer screening.

KEY POINTS

Radiation dose is a major concern for patients requiring pulmonary nodules CT screening. Ultra-low dose dual-layer detector spectral CT with 91.2% dose reduction demonstrated satisfactory performance. Dual-layer detector spectral CT has the potential for lung cancer screening and management.

Comparing organ and effective dose of various CT localizer acquisition strategies: A Monte Carlo study

BACKGROUND

CT examinations commonly start with the acquisition of one or two localizer radiographs (2D localizers). Recently, a manufacturer introduced the option to perform a heavily filtrated low-dose helical scan as a localizer acquisition. To compare the dose of one or two 2D localizer acquisitions to the dose of a 3D localizer acquisition, one cannot simply compare the CTDIs of the different acquisition techniques, because of the use of different geometries and spectra.

PURPOSE

To compare the organ and effective dose for various CT localizer acquisition techniques.

METHODS

A Geant4-based Monte Carlo simulation, replicating a clinical wide-area CT scanner was developed and validated. Various localizer acquisition strategies were simulated: Anterior-posterior (AP) alone, PA alone, combined AP+lateral (LAT), and PA+LAT 2D localizers, and an Ag-filtered 3D localizer acquisition. Validation was performed by measuring and simulating CTDI100 in both the periphery and the center of a CTDI phantom. The software was subsequently used to estimate organ and effective doses for localizers for chest, abdomen + pelvis, and the combined chest, abdomen, and pelvis exams. As representations of patients, eight ICRP computational phantoms (adult, 15-, 10-, and 5-year, both male and female) and five female and five male XCAT phantoms with various BMIs were used. The dose of the various strategies was compared to the current clinically-implemented AP+LAT localizers.

RESULTS

CTDI100-measurements and simulations within the CTDI-phantom differs by a maximum of 8.1% and by an average of 0.9%. For chest, the average effective doses for AP, PA, AP+LAT, and the 3D localizer are 0.10, 0.07, 0.32, and 0.22 mSv, respectively. The organ dose to the breast varies the most across the various localizer strategies and is, on average, 0.17, 0.03, 0.44, and 0.33 mGy, in the same order. For abdomen, the average effective doses are 0.11, 0.07, 0.36, and 0.25 mSv for the AP, PA, AP+LAT and the 3D localizer, respectively. The organ dose to the stomach varies the most across the various localizers and is on average 0.14, 0.08, 0.58, and 0.30 mGy, in the same order. The PA-only localizer results in the lowest organ dose to the most radiosensitive organs and the lowest effective dose. For the chest exam, compared to AP+LAT, the PA+LAT results in a 7 ± 2% effective dose reduction (mean ± standard deviation), while the 3D localizer results in a 21 ± 3% effective dose reduction. Using AP or PA only would result in 69 ± 2% and 76 ± 2% reduction, respectively. For the abdomen exam, also compared to AP+LAT, PA+LAT results in 6 ± 2% effective dose reduction, while the 3D localizer results in a 20 ± 5% reduction. Using AP or PA only would result in 69 ± 5% and 76 ± 4% reduction, respectively.

CONCLUSIONS

Using a PA localizer results in a lower or equivalent organ dose in the most radiosensitive organs, and a lower effective dose compared to an AP localizer for both chest and abdomen+pelvis exams. Compared to a two-localizer strategy, the 3D localizer results in a lower effective dose in both the chest and abdomen+pelvis region.

Real-world impact of high-pitch helical CT on radiation exposure and image quality in infants being evaluated for cardiothoracic pathologies

BACKGROUND

Evaluation of cardiothoracic pathologies is a common indication for computed tomography (CT) in infants. However, CT is fraught with challenges specific to the patient population, such as increased sensitivity to radiation and inability to remain stationary during imaging.

OBJECTIVE

This study investigates potential advantages of a high-pitch helical CT protocol for infants with cardiothoracic pathologies. Namely, we evaluate whether a high-pitch helical CT protocol can minimize radiation exposure without compromising image quality.

MATERIALS AND METHODS

This retrospective study included 98 consecutive cardiac protocol CT examinations of infants (56 males, 42 females; mean age 3.3 ± 2.8 months) performed at a tube voltage of 80 kV between 2016 and 2022. Forty-seven examinations were acquired with a non-gated conventional helical protocol on a multi-detector CT scanner (control group) and 51 were acquired with a non-gated high-pitch helical protocol on a dual-source CT scanner (high-pitch (HP) group). Patient characteristics, radiation exposure parameters, and imaging datasets were extracted from the picture archiving and communication system (PACS). Image quality was assessed subjectively by two radiologists who independently assigned ratings, and objectively through attenuation measurements.

RESULTS

Radiation exposure was approximately 75% lower in the HP group (0.54 mSv vs. 2.46 mSv, P < .001). HP examinations demonstrated comparable, or better, image quality across all metrics in both subjective and objective analyses. In the subjective analysis, the HP group achieved superior ratings for visualization of the aorta (P = .04). In the objective analysis, the HP group achieved superior signal-to-noise ratio (SNR) in the left atrium (P < .001), left ventricle (P = .04), and aorta (P = .003), and superior contrast-to-noise ratio (CNR) in the left atrium (P = .003) and aorta (P = .009).

CONCLUSION

Our findings suggest that employing high-pitch helical CT protocols for evaluation of cardiothoracic pathologies in infants decreases radiation exposure while achieving similar to slightly better image quality compared to conventional helical CT protocols.

Comparison of patient radiation exposure and procedure time between CT-fluoroscopy and spiral CT for lumbar epidural steroid injections

OBJECTIVE

To compare patient radiation exposure and procedure time for lumbar epidural steroid injections (ESIs) performed under CT-fluoroscopy (CTF) vs spiral CT-guidance.

MATERIALS AND METHODS

A retrospective cohort study of 767 consecutive lumbar ESIs performed between 2015-2023 using CTF vs spiral CT-guidance was conducted. Patient characteristics (age, sex, weight), procedural characteristics (injection level, type of ESI, trainee participation), and outcomes (patient radiation exposure, procedure time, pain relief, complications) were compared. Student's t and chi-squared tests were performed for statistical analysis.

RESULTS

There were 240 CTF and 527 spiral CT-guided lumbar ESIs. There were no significant differences in patient demographics between groups. Radiation exposure for the CTF group was 37.2 ± 50.5 mGy ∙ cm, compared to 251.1 ± 178.6 mGy ∙ cm in the spiral CT group (p < 0.001). Procedure times were shorter in the CTF group (20.1 ± 6.1 vs 29.6 ± 12.9 min, p < 0.001). There was no significant difference in immediate post-procedure pain reduction in CTF vs spiral CT groups (p = 0.12). There were no intrathecal puncture complications in the CTF group and four in the spiral CT group. Subgroup analysis of attending-only and trainee-performed lumbar ESIs comparing CTF vs spiral-CT groups showed similar results as the primary analysis, with significant reductions in patient radiation (attending: 31.6 ± 40.7 vs 144.4 ± 97.4 mGy ∙ cm; trainee: 40.7 ± 55.5 vs 264.5 ± 182.0 mGy ∙ cm; both p < 0.001) and procedural time (attending: 18.3 ± 4.2 vs 24.4 ± 7.4 min; trainee: 21.2 ± 6.8 vs 30.2 ± 12.4; both p < 0.001).

CONCLUSION

Image-guided lumbar ESIs using CTF were associated with less patient radiation exposure and shorter procedure times without differences in pain relief when compared with spiral CT technique in our practice.

Optimizing Radiation Dose and Image Quality in Stroke CT Protocols: Proposed Diagnostic Reference Levels for Multiphase CT Angiography and Perfusion Imaging

OBJECTIVE

In suspected acute ischemic stroke, it is now reasonable to expand the conventional "stroke protocol" (non-contrast computed tomography (NCCT), arterial CT angiography (CTA), and optionally CT perfusion (CTP)) to early and late venous head scans yielding a multiphase CTA (MP-CTA) to increase diagnostic confidence. Diagnostic reference levels (DRLs) have been defined for neither MP-CTA nor CTP. We therefore present dosimetry data, while also considering image quality, for a large, unselected patient cohort.

METHODS

A retrospective single-center study of 1790 patients undergoing the extended stroke protocol with three scanners (2× dual-source, DSCT; 1× single-source, SSCT) between 07/21 and 12/23 was conducted. For each sequence, we analyzed the radiation dose (volumetric CT dose index (CTDIvol); dose length product; effective dose); objective image quality using manually placed regions of interest (contrast-to-noise ratio (CNR)); and subjective image quality (4-point scale: 1 = non-diagnostic, 4 = excellent). The DRL was defined as the 75% percentile of the CTDIvol distribution. The Kruskal-Wallis test was used initially to test for overall equality of median values in each data group. Single post-test comparisons were performed with Dunn's test, with an overall statistical significance level of 0.05.

RESULTS

Dosimetry values were significantly higher for SSCT (p < 0.001, each). Local DRLs ranged between 37.3 and 49.1 mGy for NCCT, 3.6-5.5 mGy for arterial CTA, 1.2-2.5 mGy each for early/late venous CTA, and 141.1-220.5 mGy for CTP. Protocol adjustment (DSCT-1: CTP) yielded a 28.2% dose reduction. The highest/lowest CNRs (arterial/early venous CTA, respectively) were recorded for SSCT/DSCT-2 (p < 0.001). Subjective image quality was rated excellent except for slightly increased MP-CTA noise at DSCT-2 (median = 3).

CONCLUSIONS

Our data imply that additive MP-CTA scans only yield a minor increase in radiation exposure, particularly when using DSCT. CTP should be limited to selected patients.

Radiological follow-up in patients with resected pulmonary carcinoids: Should we reduce radiation exposure?

INTRODUCTION

After primary resection of pulmonary carcinoids, the recurrence rate is low (approximately 10 %). However, long-term radiological follow-up is generally recommended due to the risk of late recurrence. This must be weighed against risk of radiation-induced cancer, particularly in young patients.

METHODS

The frequency and modality of radiological follow-up according to the ENETS, ESMO, and CommNETs-NANETS guidelines were assessed. Cumulative radiation exposure per guideline and subsequent increased lifetime cancer risk were estimated using sex- and age-dependent risk factors. Data from the Netherlands Cancer Registry (2003-2012) of adults with resected pulmonary carcinoids were used as a reference.

RESULTS

Of 706 reference patients, 32 (4.5 %) were 18-30 years (y). After median follow-up of 127 months, none of the patients aged 18-30y at diagnosis developed recurrence. For these patients, the additional radiation exposure at the age of 40y due to follow-up ranges from 140-308 mSv following ENETS and 35-42 mSv following ESMO guidelines. The additional risk of death due to carcinogenic effects ranged from 0.7 % (male 30y) to 3.1 % (female 18y) following ENETS and 0.2 % (male) to 0.4 % (female) following ESMO guidelines.

CONCLUSIONS

Individualised, less extensive follow-up for young patients with resected carcinoids and a low risk of recurrence are worth exploring to decrease radiation exposure and the corresponding risk of cancer induction. The use of predictive biomarkers to personalise follow-up is warranted.

Comparative effectiveness of digital variance and subtraction angiography in lower limb angiography: A Monte Carlo modelling approach

OBJECTIVE

By modelling patient exposures of interventional procedures, this study compares the reduction of radiation detriment between Digital Variance Angiography (DVA) and Digital Subtraction Angiography (DSA).

METHODS

The paper presents a retrospective risk assessment using an in-house developed tool on 107 patient exposures from a clinical trial of DVA used to diagnose peripheral arterial disease (PAD). DICOM exposure parameters were used to initiate the PENELOPE (PENetration and Energy LOss of Positrons and Electrons) Monte Carlo simulation, radiation quality and quantity, and irradiation geometry. The effective dose and the lifetime attributable risk (LAR) for cancer incidence and mortality are calculated based on the International Commission on Radiation Protection's (ICRP) 103 recommendations and the Committee on the Biological Effects of Ionising Radiations' latest (BEIR VII) report, respectively.

RESULTS

The study found that procedures conducted using DVA significantly reduce the radiation exposure of patients, compared to DSA. The collective effective dose for the DVA group was 58% lower than that for the DSA group. Correspondingly, the LAR of different organs showed a substantial decrease for cancer incidence (25-75%) and mortality (51-84%).

CONCLUSION

DVA demonstrates a considerable reduction in physical dosimetric quantities and consequently effective dose and cancer risk, suggesting its potential as a safer alternative to DSA in interventional radiology. The use of DVA supports the optimisation of patient radiation protection and aligns with the principles of ALARA (as low as reasonably achievable).

Evaluation of ultra-low-dose CT with tin filter for craniosynostosis

INTRODUCTION

CT has replaced skull radiography as the gold standard for assessment of craniosynostosis in children. To minimise the risks of ionising radiation in this radiosensitive population, low-dose CT protocols are increasingly being adopted. This study evaluates the effectiveness of an ultra-low-dose CT protocol with a tin filter in reducing radiation exposure whilst maintaining diagnostic quality for craniosynostosis, and its utility in the evaluation of other findings not appreciable on skull radiography.

METHODS

Twenty-seven patients who underwent ultra-low-dose CT for craniosynostosis were compared with an age-matched control group who received standard-dose CT for indications other than craniosynostosis. Differences in radiation dosimetry and quantitative image quality parameters were analysed using independent two-tailed t-tests. Radiologist reports were also examined for the frequency of other incidental radiological findings.

RESULTS

Mean effective dose for the 27 ultra-low-dose CT scans was 0.14 mSv, a 92% reduction compared with the control group. Image quality, measured by contrast-to-noise ratio, was significantly lower in the ultra-low-dose scans compared with the standard-dose scans; however, all scans were diagnostic for detecting or excluding craniosynostosis. Hydrocephalus was able to be ruled out in all 27 ultra-low-dose scans.

CONCLUSION

Ultra-low-dose CT with a tin filter allows for the diagnosis of craniosynostosis with a 92% dose reduction compared with the standard CT protocol. Despite lower image quality with the ultra-low-dose protocol when compared to standard CT, all 27 scans were adequate for craniosynostosis diagnosis. Additionally, it allowed for the assessment of other relevant findings not appreciable with skull radiography, highlighting its advantages as the new clinical standard for craniosynostosis assessment.

Tube current reduction and iterative image reconstruction for computed tomography myelography

This study aimed to systematically evaluate the impact of a low-dose (LD) protocol using tube current reduction on image quality, the confidence for intervention planning and guidance, and diagnostic yield for computed tomography (CT) myelography. We retrospectively analyzed 68 patients who underwent CT myelography, with 34 investigations performed with a standard-dose (SD) and 34 investigations performed with a LD protocol (using tube current reduction). The different scans were matched considering variables such as sex, age, presence of spinal instrumentation, and body diameter. All images were evaluated by two readers (R1 and R2) using Likert scales. Image noise was measured using attenuation values of paraspinal muscle tissue. Images were reconstructed with model-based iterative reconstruction (post-myelography diagnostic scans) or hybrid reconstruction (planning, periprocedural, and diagnostic scans). Image quality, overall artifacts, image contrast, and confidence for planning or intervention guidance were rated good to perfect for both SD and LD scans according to evaluations of both readers. Inter-reader agreement was good to very good for the images from intervention planning (κ ≥ 0.80) as well as for intervention guidance (κ ≥ 0.77), as well as for diagnostic scans (κ ≥ 0.85). Image noise was similar between SD and LD scans performed for planning of the interventional procedures (model-based iterative reconstruction: SD 45.37 ± 7.29 HU vs. LD 45.17 ± 9.12 HU; hybrid reconstruction: SD 46.05 ± 7.43 HU vs. LD 45.05 ± 8.69 HU; p > 0.05). The volume-weighted CT dose index (CTDIvol) and size-specific dose estimate (SSDE) were significantly lower for the planning scans as well as the periprocedural scans when using the LD protocol as compared to the SD protocol (p < 0.05). In conclusion, implementation of a LD protocol with tube current reduction for CT myelography is a feasible option to reduce radiation exposure, especially when combined with iterative image reconstruction. In our study, LD imaging did not have a relevant negative impact on image quality, confidence for intervention planning or guidance, or diagnostic certainty for CT myelography.

Detection of Pulmonary Nodules on Ultra-low Dose Chest Computed Tomography With Deep-learning Image Reconstruction Algorithm

PURPOSE

To evaluate the accuracy of ultra-low dose (ULD) chest computed tomography (CT), with a radiation exposure equivalent to a 2-view chest x-ray, for pulmonary nodule detection using deep learning image reconstruction (DLIR).

MATERIAL AND METHODS

This prospective cross-sectional study included 60 patients referred to our institution for assessment or follow-up of solid pulmonary nodules. All patients underwent low-dose (LD) and ULD chest CT within the same examination session. LD CT data were reconstructed using Adaptive Statistical Iterative Reconstruction-V (ASIR-V), whereas ULD CT data were reconstructed using DLIR and ASIR-V. ULD CT images were reviewed by 2 readers and LD CT images were reviewed by an experienced thoracic radiologist as the reference standard. Quantitative image quality analysis was performed, and the detectability of pulmonary nodules was assessed according to their size and location.

RESULTS

The effective radiation dose for ULD CT and LD CT were 0.13±0.01 and 1.16±0.6 mSv, respectively. Over the whole population, LD CT revealed 733 nodules. At ULD, DLIR images significantly exhibited better image quality than ASIR-V images. The overall sensitivity of DLIR reconstruction for the detection of solid pulmonary nodules from the ULD CT series was 93% and 82% for the 2 readers, with a good to excellent agreement with LD CT (ICC=0.82 and 0.66, respectively). The best sensitivities were observed in the middle lobe (97% and 85%, respectively).

CONCLUSIONS

At ULD, DLIR reconstructions, with minimal radiation exposure that could facilitate large-scale screening, allow the detection of pulmonary nodules with high sensitivity in an unrestricted BMI population.

Evaluating Lung Changes in Long COVID: Ultra-Low-Dose vs. Standard-Dose CT Chest

Background

Frequent chest CTs within a short period during follow-up of long COVID patients may increase the risk of radiation-related health effects in the exposed individuals. We aimed to assess the image quality and diagnostic accuracy of ultra-low-dose CT (ULDCT) chest compared to standard-dose CT (SDCT) in detecting lung abnormalities associated with long COVID.

Methods

In this prospective study, 100 long COVID patients with respiratory dysfunction underwent SDCT and ULDCT chest that were compared in terms of objective (signal-to-noise ratio, SNR) and subjective image quality (image graininess, sharpness, artifacts, and diagnostic accuracy along with the European guidelines on image quality criteria for CT chest), detection of imaging patterns of long COVID, CT severity score, and effective radiation dose. Additionally, the diagnostic performance of ULDCT was compared among obese (BMI≥30 kg/m2) and non-obese (BMI<30 kg/m2) subjects.

Results

The mean age of study participants was 53 ± 12.9 years, and 68% were male. The mean SNR was 31.4 ± 5.5 and 11.3 ± 4.6 for SDCT and ULDCT respectively (p< 0.0001). Common findings seen on SDCT included ground-glass opacities (GGOs, 77%), septal thickening/reticulations (67%), atelectatic/parenchymal bands (63%) and nodules (26%). ULDCT provided sharp images, with no/minimal graininess, and high diagnostic confidence in 81%, 82% and 80% of the cases respectively. The sensitivity of ULDCT for various patterns of long COVID was 72.7% (GGOs), 71.6% (interlobular septal thickening/reticulations), 100% (consolidation), 81% (atelectatic/parenchymal bands) and 76.9% (nodules). ULDCT scans in non-obese subjects exhibited a significantly higher sensitivity (88% vs. 60.3%, p < 0.0001) and diagnostic accuracy (97.7% vs. 84.9%, p < 0.0001) compared to obese subjects. ULDCT showed very strong correlation with SDCT in terms of CT severity score (r = 0.996, p < 0.0001). The mean effective radiation dose with ULDCT was 0.25 ± 0.02 mSv with net radiation dose reduction of 94.8% ± 1.7% (p < 0.0001) when compared to SDCT (5.5 ± 1.96 mSv).

Conclusion

ULDCT scans achieved comparable diagnostic accuracy to SDCT for detecting long COVID lung abnormalities in non-obese patients, while significantly reducing radiation exposure.

Accuracy of Ultralow-Dose Photon-counting CT in the Detection of Lung Changes after Lung Transplant

Background Data on the diagnostic accuracy of ultralow-dose (ULD) CT protocols for periodic surveillance in recipients of lung transplant are lacking. Purpose To assess the potential for radiation dose reduction using ULD photon-counting CT (PCT) to detect lung abnormalities in recipients of lung transplant during repeat CT follow-up. Materials and Methods Consecutive adult recipients of lung transplant undergoing same-day standard-of-care low-dose (LD) and ULD PCT from March 2023 to May 2023 were prospectively included. The ULD protocols were performed with two target effective doses comprising 20% (hereafter, ULD1) and 10% (hereafter, ULD2) of the standard LD protocol. The 1-mm reconstructions were reviewed by three readers. Subjective image quality, the visibility of certain anatomic structures (using a five-point Likert scale), and the presence of lung abnormalities were independently assessed. The χ2 or t tests were used to evaluate differences between the ULD1 and ULD2 protocols. Results A total of 82 participants (median age, 64 years [IQR, 54-69 years]; 47 male) were included (41 participants for each ULD protocol). The mean effective doses per protocol were 1.41 mSv ± 0.44 (SD) for LD, 0.26 mSv ± 0.08 for ULD1, and 0.17 mSv ± 0.04 for ULD2. According to three readers, the subjective image quality of the ULD images was deemed diagnostic (Likert score ≥3) in 39-40 (ULD1) and 40-41 (ULD2) participants, and anatomic structures could be adequately visualized (Likert score ≥3) in 33-41 (ULD1) and 34-41 (ULD2) participants. The detection accuracy for individual lung anomalies exceeded 70% for both ULD protocols, except for readers 1 and 3 detecting proximal bronchiectasis and reader 3 detecting bronchial wall thickening and air trapping. No evidence of a statistically significant difference in noise (P = .96), signal-to-noise ratio (P = .77), or reader accuracy (all P ≥ .05) was noted between the ULD protocols. Conclusion ULD PCT was feasible for detecting lung abnormalities following lung transplant, with a tenfold radiation dose reduction. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ciet in this issue.

The determination of coefficients for size specific effective dose for adult and pediatric patients undergoing routine computed tomography examinations

The effective dose resulting from computed tomography (CT) scans provides an assessment of the risk associated with stochastic effects but does not account for the patient's size. Advances in Monte Carlo simulations offer the potential to obtain organ dose data from phantoms of varying stature, enabling derivation of a size-specific effective doses (SEDs) representing doses to individual patients. This study aimed to compute size-specific k-conversion factors for SED in routine CT examinations for adult and pediatric patients of different sizes. Radiation interactions were simulated for adult and pediatric phantom models of various sizes using National Cancer Institute CT version 3.0.20211123. Subsequent calculations of SED were performed, and coefficients for SED were derived, considering the variations in body sizes. The results revealed a strong correlation between effective diameter and weight, observed with size-specific k-conversion factors for adult and pediatric phantoms, respectively. While size-specific k-conversion factors for CT brain remained constant in adults, values for pediatric cases varied. When using the tube current modulation (TCM) system, size-specific k-conversion factors increased in larger phantoms and decreased in smaller ones. The extent of this increase or decrease correlated with the set TCM strength. This study provides coefficients for estimating SEDs in routine CT exams. Software utilizing look-up tables of coefficients can be used to provide dose information for CT scanners at local hospitals, offering guidance to practitioners on doses to individual patients and improving radiation risk awareness in clinical practice.

Chest CT at X-Ray Dose Using a Noise-Mitigating Weighted Projection: The Thoracic Tomogram. Diagnostic Performance for Pneumonia Detection in Hemato-Oncology Patients

PURPOSE

To compare the diagnostic performance of a thick-slab reconstruction obtained from an ultra-low-dose CT (termed thoracic tomogram) with standard-of-care low-dose CT (SOC-CT) for rapid interpretation and detection of pneumonia in hemato-oncology patients.

METHODS

Hemato-oncology patients with a working diagnosis of pneumonia underwent an SOC-CT followed by an ultra-low-dose CT, from which the thoracic tomogram (TT) was reconstructed. Three radiologists evaluated the TT and SOC-CT in the following categories: (I) infectious/inflammatory opacities, (II) small airways infectious/inflammatory changes, (III) atelectasis, (IV) pleural effusions, and (V) interstitial abnormalities. The TT interpretation time and radiation dose were recorded. Sensitivity, specificity, diagnostic accuracy, ROC, and AUC were calculated with the corresponding power analyses. The agreement between TT and SOC-CT was calculated by Correlation Coefficient for Repeated Measures (CCRM), and the Shrout-Fleiss intra-class correlations test was used to calculate interrater agreement.

RESULTS

Forty-seven patients (mean age 58.7 ± 14.9 years; 29 male) were prospectively enrolled. Sensitivity, specificity, accuracy, AUC, and Power for categories I/II/III/IV/V were: 94.9/99/97.9/0.971/100, 78/91.2/86.5/0.906/100, 88.6/100/97.2/0.941/100, 100/99.2/99.3/0.995/100, and 47.6/100/92.2/0.746/87.3. CCRM between TT and SOC-CT for the same categories were .97/.81/.92/.96/.62 with an interobserver agreement of .93/.88/.82/.96/.61. Mean interpretation time was 18.6 ± 5.4 seconds. The average effective radiation dose of TT was similar to a frontal and lateral chest X-ray (0.27 ± 0.08 vs 1.46 ± 0.64 mSv for SOC-CT; P < .01).

CONCLUSION

Thoracic tomograms provide comparable diagnostic information to SOC-CT for the detection of pneumonia in immunocompromised patients at one-fifth of the radiation dose with high interobserver agreement.

Redefining CAV surveillance strategies: Benefits of CCTA vs. ICA

BACKGROUND

Cardiac allograft vasculopathy (CAV) assessment post-heart transplantation (HT) typically relies on invasive coronary angiography (ICA). However, cardiac computed tomography angiography (CCTA) is emerging as a promising alternative due to its potential benefits in economic, safety, and logistical aspects. This study aimed to evaluate the impact of a CCTA program on these aspects in CAV surveillance post-HT.

METHODS

A retrospective single-center study was conducted between March 2021 and February 2023, involving HT patients who underwent either CCTA or ICA.

RESULTS

Among 260 patients undergoing CAV surveillance, 115 (44.2%) patients underwent CCTA, and 145 (55.8%) patients underwent ICA. The CCTA group showed incurred lower overall costs (p ​< ​0.0001) and shorter hospitalization times (p ​< ​0.0001) compared to the ICA group. In terms of safety, CCTA surveillance required significantly lower contrast volumes (p ​< ​0.0001) and lower effective doses (p ​= ​0.03).

CONCLUSION

CCTA emerges as a safe and cost-effective non-invasive alternative for CAV surveillance post-HT, outperforming ICA in terms of safety, logistical aspects, and economic burden.

Low-iodine-dose computed tomography coupled with an artificial intelligence-based contrast-boosting technique in children: a retrospective study on comparison with conventional-iodine-dose computed tomography

BACKGROUND

Low-iodine-dose computed tomography (CT) protocols have emerged to mitigate the risks associated with contrast injection, often resulting in decreased image quality.

OBJECTIVE

To evaluate the image quality of low-iodine-dose CT combined with an artificial intelligence (AI)-based contrast-boosting technique in abdominal CT, compared to a standard-iodine-dose protocol in children.

MATERIALS AND METHODS

This single-center retrospective study included 35 pediatric patients (mean age 9.2 years, range 1-17 years) who underwent sequential abdominal CT scans-one with a standard-iodine-dose protocol (standard-dose group, Iobitridol 350 mgI/mL) and another with a low-iodine-dose protocol (low-dose group, Iohexol 240 mgI/mL)-within a 4-month interval from January 2022 to July 2022. The low-iodine CT protocol was reconstructed using an AI-based contrast-boosting technique (contrast-boosted group). Quantitative and qualitative parameters were measured in the three groups. For qualitative parameters, interobserver agreement was assessed using the intraclass correlation coefficient, and mean values were employed for subsequent analyses. For quantitative analysis of the three groups, repeated measures one-way analysis of variance with post hoc pairwise analysis was used. For qualitative analysis, the Friedman test followed by post hoc pairwise analysis was used. Paired t-tests were employed to compare radiation dose and iodine uptake between the standard- and low-dose groups.

RESULTS

The standard-dose group exhibited higher attenuation, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) of organs and vessels compared to the low-dose group (all P-values < 0.05 except for liver SNR, P = 0.12). However, noise levels did not differ between the standard- and low-dose groups (P = 0.86). The contrast-boosted group had increased attenuation, CNR, and SNR of organs and vessels, and reduced noise compared with the low-dose group (all P < 0.05). The contrast-boosted group showed no differences in attenuation, CNR, and SNR of organs and vessels (all P > 0.05), and lower noise (P = 0.002), than the standard-dose group. In qualitative analysis, the contrast-boosted group did not differ regarding vessel enhancement and lesion conspicuity (P > 0.05) but had lower noise (P < 0.05) and higher organ enhancement and artifacts (all P < 0.05) than the standard-dose group. While iodine uptake was significantly reduced in low-iodine-dose CT (P < 0.001), there was no difference in radiation dose between standard- and low-iodine-dose CT (all P > 0.05).

CONCLUSION

Low-iodine-dose abdominal CT, combined with an AI-based contrast-boosting technique exhibited comparable organ and vessel enhancement, as well as lesion conspicuity compared to standard-iodine-dose CT in children. Moreover, image noise decreased in the contrast-boosted group, albeit with an increase in artifacts.

Submillisievert Abdominal Photon-Counting CT versus Energy-integrating Detector CT for Urinary Calculi Detection: Impact on Diagnostic Confidence

Background Contrast-unenhanced abdominal CT is the imaging standard for urinary calculi detection; however, studies comparing photon-counting detector (PCD) CT and energy-integrating detector (EID) CT dose-reduction potentials are lacking. Purpose To compare the radiation dose and image quality of optimized EID CT with those of an experimental PCD CT scan protocol including tin prefiltration in patients suspected of having urinary calculi. Materials and Methods This retrospective single-center study included patients who underwent unenhanced abdominal PCD CT or EID CT for suspected urinary caliculi between February 2022 and March 2023. Signal and noise measurements were performed at three anatomic levels (kidney, psoas, and obturator muscle). Nephrolithiasis and/or urolithiasis presence was independently assessed by three radiologists, and diagnostic confidence was recorded on a five-point scale (1, little to no confidence; 5, complete confidence). Reader agreement was determined by calculating Krippendorff α. Results A total of 507 patients (mean age, 51.7 years ± 17.4 [SD]; 317 male patients) were included (PCD CT group, 229 patients; EID CT group, 278 patients). Readers 1, 2, and 3 detected nephrolithiasis in 129, 127, and 129 patients and 94, 94, and 94 patients, whereas the readers detected urolithiasis in 113, 114, and 114 patients and 152, 153, and 152 patients in the PCD CT and EID CT groups, respectively. Regardless of protocol (PCD CT or EID CT) or calculus localization, near perfect interreader agreement was found (α ≥ 0.99; 95% CI: 0.99, 1). There was no evidence of a difference in reader confidence between PCD CT and EID CT (median confidence, 5; IQR, 5-5; P ≥ .57). The effective doses were 0.79 mSv (IQR, 0.63-0.99 mSv) and 1.39 mSv (IQR, 1.01-1.87 mSv) for PCD CT and EID CT, respectively. Despite the lower radiation exposure, the signal-to-noise ratios at the kidney, psoas, and obturator levels were 30%, 23%, and 17% higher, respectively, in the PCD CT group (P < .001). Conclusion Submillisievert abdominal PCD CT provided high-quality images for the diagnosis of urinary calculi; radiation exposure was reduced by 44% with a higher signal-to-noise ratio than with EID CT and with no evidence of a difference in reader confidence. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Nezami and Malayeri in this issue.

Computed Tomography Effective Dose and Image Quality in Deep Learning Image Reconstruction in Intensive Care Patients Compared to Iterative Algorithms

Deep learning image reconstruction (DLIR) algorithms employ convolutional neural networks (CNNs) for CT image reconstruction to produce CT images with a very low noise level, even at a low radiation dose. The aim of this study was to assess whether the DLIR algorithm reduces the CT effective dose (ED) and improves CT image quality in comparison with filtered back projection (FBP) and iterative reconstruction (IR) algorithms in intensive care unit (ICU) patients. We identified all consecutive patients referred to the ICU of a single hospital who underwent at least two consecutive chest and/or abdominal contrast-enhanced CT scans within a time period of 30 days using DLIR and subsequently the FBP or IR algorithm (Advanced Modeled Iterative Reconstruction [ADMIRE] model-based algorithm or Adaptive Iterative Dose Reduction 3D [AIDR 3D] hybrid algorithm) for CT image reconstruction. The radiation ED, noise level, and signal-to-noise ratio (SNR) were compared between the different CT scanners. The non-parametric Wilcoxon test was used for statistical comparison. Statistical significance was set at p < 0.05. A total of 83 patients (mean age, 59 ± 15 years [standard deviation]; 56 men) were included. DLIR vs. FBP reduced the ED (18.45 ± 13.16 mSv vs. 22.06 ± 9.55 mSv, p < 0.05), while DLIR vs. FBP and vs. ADMIRE and AIDR 3D IR algorithms reduced image noise (8.45 ± 3.24 vs. 14.85 ± 2.73 vs. 14.77 ± 32.77 and 11.17 ± 32.77, p < 0.05) and increased the SNR (11.53 ± 9.28 vs. 3.99 ± 1.23 vs. 5.84 ± 2.74 and 3.58 ± 2.74, p < 0.05). CT scanners employing DLIR improved the SNR compared to CT scanners using FBP or IR algorithms in ICU patients despite maintaining a reduced ED.

Intraoperative navigation increases the projected lifetime cancer risk in patients undergoing surgery for adolescent idiopathic scoliosis

BACKGROUND CONTEXT

Adolescent idiopathic scoliosis (AIS) is a common condition, often requiring surgical correction. Computed tomography (CT) based navigation technologies, which rely on ionizing radiation, are increasingly being utilized for surgical treatment. Although this population is highly vulnerable to radiation, given their age and female predominance, there is little available information elucidating modeled iatrogenic cancer risk.

PURPOSE

To model lifetime cancer risk associated with the use of intraoperative CT-based navigation for surgical treatment of AIS.

STUDY DESIGN/SETTING

This retrospective cross-sectional study took place in a quaternary care academic pediatric hospital in the United States.

PATIENT SAMPLE

Adolescents aged 10-18 who underwent posterior spinal fusion for a diagnosis of AIS between July 2014 and December 2019.

OUTCOMES MEASURES

Effective radiation dose and projected lifetime cancer risk associated with intraoperative doses of ionizing radiation.

METHODS

Clinical and radiographic parameters were abstracted, including total radiation dose during surgery from flat plate radiographs, fluoroscopy, and intraoperative CT scans. Multivariable regression analysis was used to assess differences in radiation exposure between patients treated with conventional radiography versus intraoperative navigation. Radiation exposure was translated into lifetime cancer risk using well-established algorithms.

RESULTS

In total, 245 patients were included, 119 of whom were treated with navigation. The cohort was 82.9% female and 14.4 years of age. The median radiation exposure (in millisieverts, mSv) for fluoroscopy, radiography, and navigation was 0.05, 4.14, and 8.19 mSv, respectively. When accounting for clinical and radiographic differences, patients treated with intraoperative navigation received 8.18 mSv more radiation (95%CI: 7.22-9.15, p<.001). This increase in radiation projects to 0.90 iatrogenic malignancies per 1,000 patients (95%CI 0.79-1.01).

CONCLUSIONS

Ours is the first work to define cancer risk in the setting of radiation exposure for navigated AIS surgery. We project that intraoperative navigation will generate approximately one iatrogenic malignancy for every 1,000 patients treated. Given that spine surgery for AIS is common and occurs in the context of a multitude of other radiation sources, these data highlight the need for radiation budgeting protocols and continued development of lower radiation dose technologies.

LEVEL OF EVIDENCE

Therapeutic, III.

Cumulative radiation exposure from multimodality recurrent imaging of CT, fluoroscopically guided intervention, and nuclear medicine

OBJECTIVES

To assess cumulative effective dose (CED) over a 4-year period in patients undergoing multimodality recurrent imaging at a major hospital in the USA.

METHODS

CED from CT, fluoroscopically guided intervention (FGI), and nuclear medicine was analyzed in consecutive exams in a tertiary care center in 2018-2021. Patients with CED ≥ 100 mSv were classified by age and body habitus (underweight, healthy weight, overweight, obese), as per body mass index percentiles < 5th, 5th to < 85th, 85th to < 95th, and ≥ 95th (age 2-19 years), and its ranges < 18.5, 18.5-24.9, 25-29.9, and ≥ 30 (≥ 20 years), respectively.

RESULTS

Among a total of 205,425 patients, 5.7% received CED ≥ 100 mSv (mean 184 mSv, maximum 1165 mSv) and their ages were mostly 50-64 years (34.1%), followed by 65-74 years (29.8%), ≥ 75 years (19.5%), 20-49 years (16.3%), and ≤ 19 years (0.29%). Body habitus in decreasing occurrence was obese (38.6%), overweight (31.9%), healthy weight (27.5%), and underweight (2.1%). Classification by dose indicated 172 patients (≥ 500 mSv) and 3 (≥ 1000 mSv). In comparison, 5.3% of 189,030 CT patients, 1.6% of 18,963 FGI patients, and 0.19% of 41,401 nuclear-medicine patients received CED ≥ 100 mSv from a single modality.

CONCLUSIONS

The study of total dose from CT, FGI, and nuclear medicine of patients with CED ≥ 100 mSv indicates major (89%) contribution of CT to CED with 70% of cohort being obese and overweight, and 64% of cohort aged 50-74 years.

CLINICAL RELEVANCE STATEMENT

Multimodality recurrent exams are common and there is a lack of information on patient cumulative radiation exposure. This study attempts to address this lacuna and has the potential to motivate actions to improve the justification process for enhancing patient safety.

KEY POINTS

• In total, 5.7% of patients undergoing multimodality recurrent imaging (CT, fluoroscopically guided intervention, nuclear medicine) incurred a dose of ≥ 100 mSv. • Mean dose was 184 mSv, with 15 to 18 times contribution from CT than that from fluoroscopically guided intervention or nuclear medicine. • In total, 70% of those who received ≥ 100mSv were either overweight or obese.

Photon-counting computed tomography for paediatric congenital heart defects yields images of high diagnostic quality with low radiation doses at both 70 kV and 90 kV

BACKGROUND

Photon-counting computed tomography (PCCT) is a new clinical method that may show better diagnostic quality at lower radiation doses than conventional CT.

OBJECTIVE

To investigate the diagnostic quality and radiation dose of paediatric cardiovascular PCCT for diagnosis of congenital heart defects at 70 kV and 90 kV.

MATERIALS AND METHODS

This retrospective assessment included clinical non-gated paediatric PCCT examinations for assessment of congenital heart defects. Radiation doses were recorded, and overall and specific diagnostic quality (1-4) were scored by four paediatric radiologists. Agreement, differences, and trends were assessed by percent rater agreement, intraclass correlation, Mann-Whitney tests, and Jonckheere-Terpstra tests.

RESULTS

Seventy children with congenital heart defects were examined at 70 kV (n = 35; age 2 days-16 years; 63% boys) or 90 kV (n = 35; age 2 days-17 years; 51% boys). All observers gave a median score of 4 (high diagnostic quality) for both 70 kV and 90 kV, with no difference in median values between tube voltages (all P > 0.06). Agreement for overall scores was 66-94% for 70 kV and 60-77% for 90 kV. Agreement for specific scores was 80-97% for 70 kV and 83-89% for 90 kV. Size-dependent dose estimate was 0.68 mGy (0.25-2.02 mGy) for 70 kV and 1.10 mGy (0.58-2.71 mGy; P < 0.001) for 90 kV. Effective dose was 0.30 mSv (0.15-0.82 mSv) for 70 kV and 0.39 mSv (0.22-1.51 mSv; P = 0.01) for 90 kV.

CONCLUSION

Paediatric cardiovascular PCCT yields images for congenital heart defects of high diagnostic quality with low radiation dose at both 70 kV and 90 kV.

Low-dose liver CT: image quality and diagnostic accuracy of deep learning image reconstruction algorithm

OBJECTIVES

To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASiR-V) algorithm.

MATERIALS AND METHODS

Oncologic patients were prospectively enrolled and underwent contrast-enhanced CT. Images were reconstructed with DLIR with three intensity levels of reconstruction (high, medium, and low) and ASiR-V at strength levels from 10 to 100% with a 10% interval. Three radiologists characterized the lesions and two readers assessed diagnostic accuracy and calculated signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), figure of merit (FOM), and subjective image quality, the latter with a 5-point Likert scale.

RESULTS

Fifty patients (mean age: 70 ± 10 years, 23 men) were enrolled and 130 liver lesions (105 benign lesions, 25 metastases) were identified. DLIR_H achieved the highest SNR and CNR, comparable to ASiR-V 100% (p ≥ .051). DLIR_M returned the highest subjective image quality (score: 5; IQR: 4-5; p ≤ .001) and significant median increase (29%) in FOM (p < .001). Differences in detection were identified only for lesions ≤ 0.5 cm: 32/33 lesions were detected with DLIR_M and 26 lesions were detected with ASiR-V 50% (p = .031). Lesion accuracy of was 93.8% (95% CI: 88.1, 97.3; 122 of 130 lesions) for DLIR and 87.7% (95% CI: 80.8, 92.8; 114 of 130 lesions) for ASiR-V 50%.

CONCLUSIONS

DLIR yields superior image quality and provides higher diagnostic accuracy compared to ASiR-V in the assessment of hypovascular liver lesions, in particular for lesions ≤ 0.5 cm.

CLINICAL RELEVANCE STATEMENT

Deep learning image reconstruction algorithm demonstrates higher diagnostic accuracy compared to iterative reconstruction in the identification of hypovascular liver lesions, especially for lesions ≤ 0.5 cm.

KEY POINTS

• Iterative reconstruction algorithm impacts image texture, with negative effects on diagnostic capabilities. • Medium-strength deep learning image reconstruction algorithm outperforms iterative reconstruction in the diagnostic accuracy of ≤ 0.5 cm hypovascular liver lesions (93.9% vs 78.8%), also granting higher objective and subjective image quality. • Deep learning image reconstruction algorithm can be safely implemented in routine abdominal CT protocols in place of iterative reconstruction.

Dose length product to effective dose coefficients in adults

OBJECTIVES

The most accurate method for estimating patient effective dose (a principal metric for tracking patient radiation exposure) from computed tomography (CT) requires time-intensive Monte Carlo simulation. A simpler method multiplies a scalar coefficient by the widely available scanner-reported dose length product (DLP) to estimate effective dose. We developed new adult effective dose coefficients using actual patient scans and assessed their agreement with Monte Carlo simulation.

METHODS

A multicenter sample of 216,906 adult CT scans was prospectively assembled in 2015-2020 from the University of California San Francisco International CT Dose Registry and the University of Florida library of computational phantoms. We generated effective dose coefficients for eight body regions, stratified by patient sex, diameter, and scanner manufacturer. We applied the new coefficients to DLPs to calculate effective doses and assess their correlations with Monte Carlo radiation transport-generated effective dose.

RESULTS

Effective dose coefficients varied by body region and decreased in magnitude with increasing patient diameter. Coefficients were approximately twofold higher for torso scans in smallest compared with largest diameter categories. For example, abdomen and pelvis coefficients decreased from 0.027 to 0.013 mSv/mGy-cm between the 16-20 cm and 41+ cm categories. There were modest but consistent differences by sex and manufacturer. Diameter-based coefficients used to estimate effective dose produced strong correlations with the reference standard (Pearson correlations 0.77-0.86). The reported conversion coefficients differ from previous studies, particularly in neck CT.

CONCLUSIONS

New effective dose coefficients derived from empirical clinical scans can be used to easily estimate effective dose using scanner-reported DLP.

CLINICAL RELEVANCE STATEMENT

Scalar coefficients multiplied by DLP offer a simple approximation to effective dose, a key radiation dose metric. New effective dose coefficients from this study strongly correlate with gold standard, Monte Carlo-generated effective dose, and differ somewhat from previous studies.

KEY POINTS

• Previous effective dose coefficients were derived from theoretical models rather than real patient data. • The new coefficients (from a large registry/phantom library) differ from previous studies. • The new coefficients offer reasonably reliable values for estimating effective dose.

Ultra-low-dose computed tomography and chest X-ray in follow-up of high-grade soft tissue sarcoma-a prospective comparative study

Ultra-low-dose computed tomography (ULD-CT) may combine the high sensitivity of conventional computed tomography (CT) in detecting sarcoma pulmonary metastasis, with a radiation dose in the same magnitude as chest X-ray (CXR). Fifty patients with non-metastatic high-grade soft tissue sarcoma treated with curative intention were recruited. Their follow-up involved both CXR and ULD-CT to evaluate their different sensitivity. Suspected findings were confirmed by conventional CT if necessary. Patients with isolated pulmonary metastases were treated with surgery or stereotactic body radiation therapy (SBRT) with curative intent if possible. The median effective dose from a single ULD-CT study was 0.27 mSv (range 0.12 to 0.89 mSv). Nine patients were diagnosed with asymptomatic lung metastases during the follow-up. Only three of them were visible in CXR and all nine in ULD-CT. CXR had therefore only a 33% sensitivity compared to ULD-CT. Four patients were operated, and one had SBRT to all pulmonary lesions. Eight of them, however, died of the disease. Two patients developed symptomatic metastatic recurrence involving extrapulmonary sites+/-the lungs between two imaging rounds. ULD-CT has higher sensitivity for the detection of sarcoma pulmonary metastasis than CXR, with a radiation dose considerably lower than conventional CT.Clinical trial registration: NCT05813808. 04-14-2023.

PAE planning: Radiation exposure and image quality of CT and CBCT

PURPOSE

To determine accurate organ doses, effective doses, and image quality of computed tomography (CT) compared with cone beam CT (CBCT) for correct identification of prostatic arteries.

METHOD

A dual-energy CT scanner and a flat-panel angiography system were used. Dose measurements (gallbladder (g), intestine (i), bladder (b), prostate (p), testes (t), active bone marrow of pelvis (bmp) and femura (bmf)) were performed using an anthropomorphic phantom with 65 thermoluminescent dosimeters in the pelvis and abdomen region. For the calculation of the contrast-to-noise ratio (CNR) of the pelvic arteries, a patient whose weight and height were almost identical to those of the phantom was selected for each examination type.

RESULTS

The effective dose of CT was 2.7 mSv and that of CBCT was 21.8 mSv. Phantom organ doses were lower for CT than for CBCT in all organs except the testes (g: 1.2 mGy vs. 3.3 mGy, i: 5.8 mGy vs. 23.9 mGy, b: 6.9 mGy vs. 19.4 mGy, p: 6.4 mGy vs. 13.2 mGy, t: 4.7 mGy vs. 2.4 mGy, bmp: 5.1 mGy vs. 18.2 mGy, bmf: 3.3 mGy vs. 6.6 mGy). For human pelvic arteries, the CNR of CT was better than that of CBCT, with the exception of one prostate artery that showed stenosis on CT. Evaluation by experienced radiologists also confirmed the better detectability of prostate arteries on CT examination.

CONCLUSIONS

In our study preprocedural CT had lower organ doses and better image quality comparedd with CBCT and should be considered for the correct identification of prostatic arteries.

Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT

PURPOSE

To prospectively evaluate whether Lung-RADS classification and volumetric nodule assessment were feasible with ultralow-dose (ULD) chest CT scans with deep learning image reconstruction (DLIR).

METHODS

The institutional review board approved this prospective study. This study included 40 patients (mean age, 66±12 years; 21 women). Participants sequentially underwent LDCT and ULDCT (CTDIvol, 0.96±0.15 mGy and 0.12±0.01 mGy) scans reconstructed with the adaptive statistical iterative reconstruction-V 50% (ASIR-V50) and DLIR. CT image quality was compared subjectively and objectively. The pulmonary nodules were assessed visually by two readers using the Lung-RADS 1.1 and automatically using a computerized assisted tool.

RESULTS

DLIR provided a significantly higher signal-to-noise ratio for LDCT and ULDCT images than ASIR-V50 (all P < .001). In general, DLIR showed superior subjective image quality for ULDCT images (P < .001) and comparable quality for LDCT images compared to ASIR-V50 (P = .01-1). The per-nodule sensitivities of observers for Lung-RADS category 3-4 nodules were 70.6-88.2% and 64.7-82.4% for DLIR-LDCT and DLIR-ULDCT images (P = 1) and categories were mostly concordant within observers. The per-nodule sensitivities of the computer-assisted detection for nodules ≥4 mm were 72.1% and 67.4% on DLIR-LDCT and ULDCT images (P = .50). The 95% limits of agreement for nodule volume differences between DLIR-LDCT and ULDCT images (-85.6 to 78.7 mm3) was similar to the within-scan nodule volume differences between DLIR- and ASIR-V50-LDCT images (-63.9 to 78.5 mm3), with volume differences smaller than 25% in 88.5% and 92.3% of nodules, respectively (P = .65).

CONCLUSION

DLIR enabled comparable Lung-RADS and volumetric nodule assessments on ULDCT images to LDCT images.

Feasibility of Low-Dose and Low-Contrast Media Volume Approach in Computed Tomography Cardiovascular Imaging Reconstructed with Model-Based Algorithm

Aim: To evaluate the dose reduction and image quality of low-dose, low-contrast media volume in computed tomography (CT) examinations reconstructed with the model-based iterative reconstruction (MBIR) algorithm in comparison with the hybrid iterative (HIR) one. Methods: We prospectively enrolled a total of 401 patients referred for cardiovascular CT, evaluated with a 256-MDCT scan with a low kVp (80 kVp) reconstructed with an MBIR (study group) or a standard HIR protocol (100 kVp-control group) after injection of a fixed dose of contrast medium volume. Vessel contrast enhancement and image noise were measured by placing the region of interest (ROI) in the left ventricle, ascending aorta; left, right and circumflex coronary arteries; main, right and left pulmonary arteries; aortic arch; and abdominal aorta. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Subjective image quality obtained by consensus was assessed by using a 4-point Likert scale. Radiation dose exposure was recorded. Results: HU values of the proximal tract of all coronary arteries; main, right and left pulmonary arteries; and of the aorta were significantly higher in the study group than in the control group (p < 0.05), while the noise was significantly lower (p < 0.05). SNR and CNR values in all anatomic districts were significantly higher in the study group (p < 0.05). MBIR subjective image quality was significantly higher than HIR in CCTA and CTPA protocols (p < 0.05). Radiation dose was significantly lower in the study group (p < 0.05). Conclusions: The MBIR algorithm combined with low-kVp can help reduce radiation dose exposure, reduce noise, and increase objective and subjective image quality.

Customised weight-based volume contrast media protocol for multiphase abdominal computed tomography

INTRODUCTION

Multiphase computed tomography (CT) using fixed volume contrast media may lead to high radiation exposure and toxicity in patients with low body weight. We evaluated a customised weight-based protocol for multiphase CT in terms of radiation exposure, image quality and cost savings.

METHODS

A total of 224 patients were recruited. An optimised CT protocol was applied using 100 kV and 1 mL/kg of contrast media dosing. The image quality and radiation dose exposure of this CT protocol were compared to those of a standard 120 kV, 80 mL fixed volume protocol. The radiation dose information and CT Hounsfield units were recorded. The signal-to-noise ratio, contrast-to-noise ratio (CNR) and figure of merit (FOM) were used as comparison metrics. The images were assessed for contrast opacification and visual quality by two radiologists. The renal function, contrast media volume and cost were also evaluated.

RESULTS

The median effective dose was lowered by 16% in the optimised protocol, while the arterial phase images achieved significantly higher CNR and FOM. The radiologists' evaluation showed more than 97% absolute agreement with no significant differences in image quality. No significant differences were found in the pre- and post-CT estimated glomerular filtration rate. However, contrast media usage was significantly reduced by 1,680 mL, with an overall cost savings of USD 421 in the optimised protocol.

CONCLUSION

The optimised weight-based protocol is cost-efficient and lowers radiation dose while maintaining overall contrast enhancement and image quality.

Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window

OBJECTIVES

To explore the performance of low-dose computed tomography (LDCT) with deep learning reconstruction (DLR) for the improvement of image quality and assessment of lung parenchyma.

METHODS

Sixty patients underwent chest regular-dose CT (RDCT) followed by LDCT during the same examination. RDCT images were reconstructed with hybrid iterative reconstruction (HIR) and LDCT images were reconstructed with HIR and DLR, both using lung algorithm. Radiation exposure was recorded. Image noise, signal-to-noise ratio, and subjective image quality of normal and abnormal CT features were evaluated and compared using the Kruskal-Wallis test with Bonferroni correction.

RESULTS

The effective radiation dose of LDCT was significantly lower than that of RDCT (0.29 ± 0.03 vs 2.05 ± 0.65 mSv, p < 0.001). The mean image noise ± standard deviation was 33.9 ± 4.7, 39.6 ± 4.3, and 31.1 ± 3.2 HU in RDCT, LDCT HIR-Strong, and LDCT DLR-Strong, respectively (p < 0.001). The overall image quality of LDCT DLR-Strong was significantly better than that of LDCT HIR-Strong (p < 0.001) and comparable to that of RDCT (p > 0.05). LDCT DLR-Strong was comparable to RDCT in evaluating solid nodules, increased attenuation, linear opacity, and airway lesions (all p > 0.05). The visualization of subsolid nodules and decreased attenuation was better with DLR than with HIR in LDCT but inferior to RDCT (all p < 0.05).

CONCLUSION

LDCT DLR can effectively reduce image noise and improve image quality. LDCT DLR provides good performance for evaluating pulmonary lesions, except for subsolid nodules and decreased lung attenuation, compared to RDCT-HIR.

CLINICAL RELEVANCE STATEMENT

The study prospectively evaluated the contribution of DLR applied to chest low-dose CT for image quality improvement and lung parenchyma assessment. DLR can be used to reduce radiation dose and keep image quality for several indications.

KEY POINTS

• DLR enables LDCT maintaining image quality even with very low radiation doses. • Chest LDCT with DLR can be used to evaluate lung parenchymal lesions except for subsolid nodules and decreased lung attenuation. • Diagnosis of pulmonary emphysema or subsolid nodules may require higher radiation doses.

Image quality, contrast enhancement and radiation dose of electrocardiograph- versus non-electrocardiograph-triggered computed tomography angiography of the aorta

INTRODUCTION

Computed tomography angiography of the aorta (CTAA) is the modality of choice for investigating aortic disease. Our aim was to evaluate the image quality, contrast enhancement and radiation dose of electrocardiograph (ECG)-triggered and non-ECG-triggered CTAA on a 256-slice single-source CT scanner. This allows the requesting clinician and the radiologist to balance radiation risk and image quality.

METHODS

We retrospectively assessed the data of 126 patients who had undergone CTAA on a single-source CT scanner using ECG-triggered (group 1, n = 77) or non-ECG-triggered (group 2, n = 49) protocols. Radiation doses were compared. Qualitative (4-point scale) and quantitative image quality assessments were performed.

RESULTS

The mean volume CT dose index, dose length product and effective dose in group 1 were 12.4 ± 1.9 mGy, 765.8 ± 112.4 mGy cm and 13.0 ± 1.9 mSv, respectively. These were significantly higher compared to group 2 values (9.1 ± 2.6 mGy, 624.1 ± 174.8 mGy cm and 10.6 ± 3.0 mSv, respectively) ( P < 0.001). Qualitative assessment showed the image quality at the aortic root-proximal ascending aorta was significantly higher in group 1 (median 3) than in group 2 (median 2, P < 0.001). Quantitative assessment showed significantly better mean arterial attenuation, signal-to-noise ratio and contrast-to-noise ratio in ECG-triggered CTAA compared to non-ECG-triggered CTAA.

CONCLUSION

ECG-triggered CTAA in a single-source scanner has superior image quality and vessel attenuation of aortic root/ascending aorta, but a higher radiation dose of approximately 23%. Its use should be considered specifically when assessing aortic root/ascending aorta pathology.

Radiation Exposure from GEP NET Surveillance

BACKGROUND

Neuroendocrine tumors (NET) are neoplasms that secrete peptides and neuroamines. For gastroenteropancreatic (GEP) NET, surgical resection represents the only curative option. Ten-year imaging surveillance programs are recommended due to long time-to-recurrence following resection. We performed retrospective chart review evaluating radiation exposure and practice patterns from surveillance of completely resected GEP NET.

METHODS

We performed a retrospective cohort study of cases with well-differentiated GEP NET from January 2005 to July 2020. Location of primary, modality of imaging, and duration of follow-up were collected. Dosimetry data was collected to calculate effective dose.

RESULTS

62 cases were included with 422 surveillance scans performed. Cross-sectional imaging was used in 82% and functional imaging was used in 18% of scans. Mean number of scans per year was 1.25 (0.42-3). Mean total effective dose was 56.05 mSv (SD 45.56; 0 to 198 mSv) while mean total effective dose per year was 10.62 mSv (SD 9.35; 0 to 45 mSv). Over the recommended ten years of surveillance the estimated total effective dose was 106 mSv.

CONCLUSIONS

Surveillance of completely resected GEP NET results in cumulative radiation doses in the range associated with secondary malignancy development. Strategies to minimize radiation exposure in surveillance should be considered in future guideline development.

The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation

OBJECTIVE

The purpose of this study is to evaluate the efficacy of deep learning reconstruction (DLR) on low-tube-voltage computed tomographic angiography (CTA) for transcatheter aortic valve implantation (TAVI).

METHODS

We enrolled 30 patients who underwent TAVI-CT on a 320-row CT scanner. Electrocardiogram-gated coronary CTA (CCTA) was performed at 100 kV, followed by nongated aortoiliac CTA at 80 kV using a single bolus of contrast material. We used hybrid-iterative reconstruction (HIR), model-based IR (MBIR), and DLR to reconstruct these images. The contrast-to-noise ratios (CNRs) were calculated. Five-point scales were used for the overall image quality analysis. The diameter of the aortic annulus was measured in each reconstructed image, and we compared the interobserver and intraobserver agreements.

RESULTS

In the CCTA, the CNR and image quality score for DLR were significantly higher than those for HIR and MBIR ( P < 0.01). In the aortoiliac CTA, the CNR for DLR was significantly higher than that for HIR ( P < 0.01) and significantly lower than that for MBIR ( P ≤ 0.02). The image quality score for DLR was significantly higher than that for HIR ( P < 0.01). No significant differences were observed between the image quality scores for DLR and MBIR. The measured aortic annulus diameter had high interobserver and intraobserver agreement regardless of the reconstruction method (all intraclass correlation coefficients, >0.89).

CONCLUSIONS

In low tube voltage TAVI-CT, DLR provides higher image quality than HIR, and DLR provides higher image quality than MBIR in CCTA and is visually comparable to MBIR in aortoiliac CTA.

A fully automated machine learning-based methodology for personalized radiation dose assessment in thoracic and abdomen CT

PURPOSE

To develop a machine learning-based methodology for patient-specific radiation dosimetry in thoracic and abdomen CT.

METHODS

Three hundred and thirty-one thoracoabdominal radiotherapy-planning CT examinations with the respective organ/patient contours were collected retrospectively for the development and validation of segmentation 3D-UNets. Moreover, 97 diagnostic thoracic and 89 diagnostic abdomen CT examinations were collected retrospectively. For each of the diagnostic CT examinations, personalized MC dosimetry was performed. The data derived from MC simulations along with the respective CT data were used for the training and validation of a dose prediction deep neural network (DNN). An algorithm was developed to utilize the trained models and perform patient-specific organ dose estimates for thoracic and abdomen CT examinations. The doses estimated with the DNN were compared with the respective doses derived from MC simulations. A paired t-test was conducted between the DNN and MC results. Furthermore, the time efficiency of the proposed methodology was assessed.

RESULTS

The mean percentage differences (range) between DNN and MC dose estimates for the lungs, liver, spleen, stomach, and kidneys were 7.2 % (0.2-24.1 %), 5.5 % (0.4-23.0 %), 7.9 % (0.6-22.3 %), 6.9 % (0.0-23.0 %) and 6.7 % (0.3-22.6 %) respectively. The differences between DNN and MC dose estimates were not significant (p-value = 0.12). Moreover, the mean processing time of the proposed workflow was 99 % lower than the respective time needed for MC-based dosimetry.

CONCLUSIONS

The proposed methodology can be used for rapid and accurate patient-specific dosimetry in chest and abdomen CT.

Pediatric Cardiovascular Computed Tomography: Clinical Indications, Technique, and Standardized Reporting. Recommendations From the Cardiothoracic Taskforce of the European Society of Pediatric Radiology

Congenital heart diseases affect 1% of all live births in the general population. The prognosis of these children is increasingly improving due to advances in medical care and surgical treatment. Imaging is also evolving rapidly to assess accurately complex cardiac anomalies prenatally and postnatally. Transthoracic echocardiography is the gold-standard imaging technique to diagnose and follow-up children with congenital heart disease. Cardiac computed tomography imaging plays a key role in the diagnosis of children with congenital heart defects that require intervention, due to its high temporal and spatial resolution, with low radiation doses. It is challenging for radiologists, not primarily specialized in this field, to perform and interpret these studies due to the difficult anatomy, physiology, and postsurgical changes. Technical challenges consist of necessary electrocardiogram gating and contrast bolus timing to obtain an optimal examination. This article aims to define indications for pediatric cardiac computed tomography, to explain how to perform and report these studies, and to discuss future applications of this technique.

Deep learning-based scan range optimization can reduce radiation exposure in coronary CT angiography

OBJECTIVES

Cardiac computed tomography (CT) is essential in diagnosing coronary heart disease. However, a disadvantage is the associated radiation exposure to the patient which depends in part on the scan range. This study aimed to develop a deep neural network to optimize the delimitation of scan ranges in CT localizers to reduce the radiation dose.

METHODS

On a retrospective training cohort of 1507 CT localizers randomly selected from calcium scoring and angiography scans and acquired between 2010 and 2017, optimized scan ranges were delimited by two radiologists in consensus. A neural network was trained to reproduce the scan ranges and was tested on two randomly selected and independent validation cohorts: an internal cohort of 233 CT localizers (January 2018-June 2020) and an external cohort from a nearby hospital of 298 CT localizers (July 2020-December 2020). Localizers where a bypass surgery was visible were excluded. The effective radiation dose to the patient was simulated using a Monte Carlo simulation. Scan ranges of radiographers, radiologists, and the network were compared using an equivalence test; likewise, the reduction in effective dose was tested using a superior test.

RESULTS

The network replicated the radiologists' scan ranges with a Dice score of 96.5 ± 0.02 (p < 0.001, indicating equivalence). The generated scan ranges resulted in an effective dose reduction of 10.0% (p = 0.002) in the internal cohort and 12.6% (p < 0.001) in the external cohort compared to the scan ranges delimited by radiographers in clinical routine.

CONCLUSIONS

Automatic delimitation of the scan range can result in a radiation dose reduction to the patient.

CLINICAL RELEVANCE STATEMENT

Fully automated delimitation of the scan range using a deep neural network enables a significant reduction in radiation exposure during CT coronary angiography compared to manual examination planning. It can also reduce the workload of the radiographers.

KEY POINTS

• Scan range delimitation for coronary computed tomography angiography could be performed with high accuracy by a deep neural network. • Automated scan ranges showed a high agreement of 96.5% with the scan ranges of radiologists. • Using a Monte Carlo simulation, automated scan ranges reduced the effective dose to the patient by up to 12.6% (0.9 mSv) compared to the scan ranges of radiographers in clinical routine.

Iodine contrast volume reduction in preoperative transcatheter aortic valve implantation computed tomography: Comparison with 64- and 256-multidetector row computed tomography

INTRODUCTION

This study aimed to compare the vascular enhancement and radiation dose in preoperative transcatheter aortic valve implantation (TAVI) computed tomography (CT) with a reduced contrast medium (CM) using volume scans in 256-multidetector row CT (MDCT) with a standard CM using 64-MDCT.

METHODS

This study included 78 patients with preoperative TAVI CT with either 64- or 256-MDCT. The CM was injected at 1.5 mL/kg in the 64-MDCT group and 1.0 mL/kg in the 256-MDCT group. We compared vascular enhancement of the aortic root and access routes, image quality (IQ) scores, and radiation dose in both groups.

RESULTS

Despite the reduced CM (by 33 %) in the 256-MDCT group, the mean vascular enhancement of the right and left subclavian arteries was significantly higher than that in the 64-MDCT group [284 and 267 Hounsfield units (HU) vs. 376 and 359 HU; p < 0.05]; however, no significant differences in the mean vascular enhancement in the ascending aorta, abdominal aorta at the celiac level, and bilateral common femoral arteries were observed between the two groups (p > 0.05 for all). The median IQ scores at the aortic root were higher in the 256-MDCT group than in the 64-MDCT group (3 vs. 4; p < 0.05), and those at the femoral access routes were comparable (4 vs. 4; p = 0.33). The mean effective dose was significantly reduced by 30 % in the 256-MDCT group (23.6 vs. 16.3 mSv; p < 0.05).

CONCLUSION

In preoperative TAVI CT, volume scans using 256-MDCT provide comparable or better vascular enhancement and IQ with a 30 % reduction in CM and radiation dose than those using 64-MDCT.

IMPLICATIONS FOR PRACTICE

Volume scan using 256-MDCT for preoperative TAVI CT may reduce CM and radiation dose in TAVI patients with renal dysfunction.

A multi-institutional assessment of low-dose protocols in chest computed tomography: Dose and image quality

Background

Low-dose CT (LDCT) chest protocols have widespread clinical applications for many indications; as a result, there is a need for protocol assessment prior to standardization. Dalhousie University and Oslo Metropolitan University have a formally established cooperative relationship.

Purpose

The purpose is to assess radiation dose and image quality for LDCT chest protocols in seven different hospital locations in Norway and Canada.

Material and methods

Retrospective dosimetry data, volumetric CT dose index (CTDIvol), and dose length product (DLP) from 240 average-sized patients as well as CT protocol parameters were included in the survey. Effective dose (ED) and size-specific dose estimate (SSDE) were calculated for each examination. For a quantitative image quality analysis, noise, CT number, and signal-to-noise ratio (SNR) were determined for three regions in the chest. The contrast-to-noise ratio (CNR) was calculated for lung parenchyma in comparison to the subcutaneous fat. Differences in dose and image quality were evaluated by a single-factor ANOVA test. A two-sample t-test was performed to determine differences in means between individual scanners.

Results

The ANOVA test revealed significant differences (p < .05) in dose values for all scanners, including identical scanner models. Statistically significant differences (p < .05) were determined in mean values of the SNR distributions between the scanners in all three measured regions in the chest, as well as the CNR values.

Conclusion

The observed variations in dose and image quality measurements, even within the same hospitals and between identical scanner models, indicate a potential for protocol optimization in the involved hospitals in both countries.

Tomosynthesis performance compared to radiography and computed tomography for sacroiliac joint structural damage detection in patients with suspected axial spondyloarthritis

Purpose

To compare tomosynthesis performance to radiography for the differentiation of sacroiliitis versus normal or degenerative changes in sacroiliac joints in patients with suspected axial spondyloarthritis (SpA).

Materials and methods

Radiography, tomosynthesis and CT of sacroiliac joints (29 patients) were performed on the same day in consecutive patients with suspected SpA. The examinations were retrospectively read independently, blinded by two radiologists (one junior and one senior, and twice by one junior). Interobserver and intraobserver agreement was evaluated using the kappa coefficient. Effective doses for each imaging sensitivity, specificity and accuracy were assessed and compared with CT as gold standard.

Results

CT detected 15/58 joints with sacroiliitis. The imaging sensitivity, specificity and accuracy were 60%, 84% and 44%, respectively, for radiography and 87%, 91% and 77% for tomosynthesis. The mean effective dose for tomosynthesis was significantly lower than that of CT (5-fold less) and significantly higher than that of radiography (8-fold more).

Conclusion

Tomosynthesis is superior to radiography for sacroiliitis detection in patients with suspected SpA, with 5-fold less radiation exposure than CT.

Comparison of diagnostic accuracy of ultra low-dose computed tomography and X-ray of the kidneys, ureters and bladder for urolithiasis in the follow-up setting

INTRODUCTION

Urolithiasis is frequently followed up with a low-dose computed tomography of the kidneys ureters and bladder (LD-CTKUB) with doses typically less than 3 millisieverts. Although X-ray is a lower dose (0.5-1.1 mSv) alternative for follow up, it has lower diagnostic accuracy and is limited to radiopaque calculi. This study aims to compare the diagnostic accuracy of sub-millisievert ultra-low dose CT (ULD-CTKUB) against X-ray KUB for the follow up of urolithiasis when both are compared against the standard of care of a low-dose CT KUB (LD-CTKUB).

METHODS

This prospective study included patients with a known diagnosis of urolithiasis on prior CTKUB presenting for follow up. Each patient underwent a repeat reference LD-CTKUB, ULD-CTKUB and X-ray KUB. All imaging studies were interpreted by three readers. The radiation dose and quantitative noise was calculated for each CT. Both CT and X-ray were assessed for the presence, number and size of all calculi ≥2 mm.

RESULTS

A total of 58 patients were included in this study. LD-CTKUB identified 197 calculi. ULD-CTKUB in our study had a mean effective dose of 0.5 mSv compared to X-ray KUB where doses range in the literature from 0.5 to 1.1 mSv. Per-patient pooled analysis for intrarenal calculi when comparing ULD-CTKUB versus X-ray KUB against a reference LD-CTKUB found a sensitivity of 90% versus 67% (P < 0.01) and specificity of 93% versus 98% (P = 0.18) respectively. For ureteric calculi, the sensitivity was 67% versus 33% (P < 0.01) and specificity 94% versus 94% (P = 1.00) respectively. Per-stone pooled analysis detection rate was 79% for ULD-CTKUB versus 48% for X-ray (P < 0.01) when each was compared to the reference LD-CTKUB. Interobserver agreement was high for intrarenal calculi and moderate for ureteric calculi.

CONCLUSION

Sub-millisievert ULD-CTKUB had lower doses and higher sensitivity than X-ray in patients requiring follow up of known urolithiasis.

Image Characteristics of Virtual Non-Contrast Series Derived from Photon-Counting Detector Coronary CT Angiography-Prerequisites for and Feasibility of Calcium Quantification

In photon-counting detector CT (PCD-CT), coronary artery calcium scoring (CACS) can be performed using virtual non-contrast (VNC) series derived from coronary CT angiography (CCTA) datasets. Our study analyzed image characteristics of VNC series in terms of the efficacy of virtual iodine "removal" and image noise to determine whether the prerequisites for calcium quantification were satisfied. We analyzed 38 patients who had undergone non-enhanced CT followed by CCTA on a PCD-CT. VNC reconstructions were performed at different settings and algorithms (conventional VNCConv; PureCalcium VNCPC). Virtual iodine "removal" was investigated by comparing histograms of heart volumes. Noise was assessed within the left ventricular cavity. Calcium was quantified on the true non-contrast (TNC) and all VNC series. The histograms were comparable for TNC and all VNC. Image noise between TNC and all VNC differed slightly but significantly. VNCConv CACS showed a significant underestimation regardless of the reconstruction setting, while VNCPC CACS were comparable to TNC. Correlations between TNC and VNC were excellent, with a higher predictive accuracy for VNCPC. In conclusion, the iodine contrast can be effectively subtracted from CCTA datasets. The remaining VNC series satisfy the requirements for CACS, yielding results with excellent correlation compared to TNC-based CACS and high predicting accuracy.

Simulation study on the conversion between CT and CBCT dose quantities via the effective dose

In recent years, cone-beam computed tomography (CBCT) has been used in many imaging tasks traditionally performed by computed tomography (CT). This has created challenges for dosimetry, as the dose quantities in CBCT and CT, i.e. the dose-area product (DAP) and dose-length product (DLP), are not mutually convertible. Convertibility would be desirable to compare doses in similar clinical studies performed using CT or CBCT and ultimately for the application of diagnostic reference levels (DRLs). In this work, the conversion of the DAP into the DLP and vice versa via the effective doseEis investigated with the aim of finding common diagnostic reference levels. The dose calculation was performed using Monte Carlo simulations for scan regions with imaging tasks, which can be carried out either with CT or CBCT scanners. Four regions in the head and four in the trunk were chosen. The calculations resulted in conversion coefficientsk=DAPDLPof 30(4) cm for the cranium, 22(4) cm for the facial bones, 24(2) cm for the paranasal sinuses, 18(2) cm for the cervical spine, 78(12) cm for the thorax, 85(13) cm for the upper abdomen, 57(6) cm for the lumbar spine and 70(12) cm for the pelvis.

Imaging evaluation of a proposed 3D generative model for MRI to CT translation in the lumbar spine

BACKGROUND CONTEXT

A computed tomography (CT) and magnetic resonance imaging (MRI) are used routinely in the radiologic evaluation and surgical planning of patients with lumbar spine pathology, with the modalities being complimentary. We have developed a deep learning algorithm which can produce 3D lumbar spine CT images from MRI data alone. This has the potential to reduce radiation to the patient as well as burden on the health care system.

PURPOSE

The purpose of this study is to evaluate the accuracy of the synthetic lumbar spine CT images produced using our deep learning model.

STUDY DESIGN

A training set of 400 unpaired CTs and 400 unpaired MRI scans of the lumbar spine was used to train a supervised 3D cycle-Gan model. Evaluators performed a set of clinically relevant measurements on 20 matched synthetic CTs and true CTs. These measurements were then compared to assess the accuracy of the synthetic CTs.

PATIENT SAMPLE

The evaluation data set consisted of 20 patients who had CT and MRI scans performed within a 30-day period of each other. All patient data was deidentified. Notable exclusions included artefact from patient motion, metallic implants or any intervention performed in the 30 day intervening period.

OUTCOME MEASURES

The outcome measured was the mean difference in measurements performed by the group of evaluators between real CT and synthetic CTs in terms of absolute and relative error.

METHODS

Data from the 20 MRI scans was supplied to our deep learning model which produced 20 "synthetic CT" scans. This formed the evaluation data set. Four clinical evaluators consisting of neurosurgeons and radiologists performed a set of 24 clinically relevant measurements on matched synthetic CT and true CTs in 20 patients. A test set of measurements were performed prior to commencing data collection to identify any significant interobserver variation in measurement technique.

RESULTS

The measurements performed in the sagittal plane were all within 10% relative error with the majority within 5% relative error. The pedicle measurements performed in the axial plane were considerably less accurate with a relative error of up to 34%.

CONCLUSIONS

The computer generated synthetic CTs demonstrated a high level of accuracy for the measurements performed in-plane to the original MRIs used for synthesis. The measurements performed on the axial reconstructed images were less accurate, attributable to the images being synthesized from nonvolumetric routine sagittal T1-weighted MRI sequences. It is hypothesized that if axial sequences or volumetric data were input into the algorithm these measurements would have improved accuracy.

Factors contributing to uncertainty in paediatric abdominal ultrasound reports in the paediatric emergency department

BACKGROUND

Abdominal pain, which is a common cause of children presenting to the paediatric emergency department (PED), is often evaluated by ultrasonography (US). However, uncertainty in US reports may necessitate additional imaging.

OBJECTIVE

In this study, we evaluated factors contributing to uncertainty in paediatric abdominal US reports in the PED.

MATERIALS AND METHODS

This retrospective cohort study included children younger than 18 years of age who underwent abdominal US in the PED of the study hospital between January 2017 and December 2019. After exclusion, the researchers manually reviewed and classified all US reports as 'certain' or 'uncertain'. Univariate and multivariate logistic regression analyses were performed to identify the factors contributing to uncertain reports.

RESULTS

In total, 1006 patients were included in the final analysis., 796 patients were tagged as having certain reports, and 210 as having uncertain reports. Children with uncertain reports had a significantly higher rate of undergoing an additional computed tomography (CT) scan (31.0% vs. 2.5%, p < 0.001) and a longer PED median length of stay (321.0 (Interquartile range (IQR); 211.3-441.5) minutes vs. 284.5 (IQR; 191.8-439.5) minutes, p = 0.042). After logistic regression, US performed by a radiology resident (odds ratio, 5.01; 95% confidence interval, 3.63-7.15) was the most significant factor contributing to uncertainty in paediatric abdominal US reports followed by obesity and age.

CONCLUSION

Several factors contribute to uncertainty in paediatric abdominal US reports. Uncertain radiological reports increase the likelihood of additional CT scans. Measures to improve the clarity of radiological reports must be considered to improve the quality of care for children visiting the PED.

Ultra-low-dose computed tomography with deep learning reconstruction for craniosynostosis at radiation doses comparable to skull radiographs: a pilot study

BACKGROUND

Craniofacial computed tomography (CT) is the diagnostic investigation of choice for craniosynostosis, but high radiation dose remains a concern.

OBJECTIVE

To evaluate the image quality and diagnostic performance of an ultra-low-dose craniofacial CT protocol with deep learning reconstruction for diagnosis of craniosynostosis.

MATERIALS AND METHODS

All children who underwent initial craniofacial CT for suspected craniosynostosis between September 2021 and September 2022 were included in the study. The ultra-low-dose craniofacial CT protocol using 70 kVp, model-based iterative reconstruction and deep learning reconstruction techniques was compared with a routine-dose craniofacial CT protocol. Quantitative analysis of the signal-to-noise ratio and noise was performed. The 3-dimensional (D) volume-rendered images were independently evaluated by two radiologists with regard to surface coarseness, step-off artifacts and overall image quality on a 5-point scale. Sutural patency was assessed for each of six sutures. Radiation dose was compared between the two protocols.

RESULTS

Among 29 patients (15 routine-dose CT and 14 ultra-low-dose CT), 23 patients had craniosynostosis. The 3-D volume-rendered images of ultra-low-dose CT without deep learning showed decreased image quality compared to routine-dose CT. The 3-D volume-rendered images of ultra-low-dose CT with deep learning reconstruction showed higher noise level, higher surface coarseness but decreased step-off artifacts, comparable signal-to-noise ratio and overall similar image quality compared to the routine-dose CT images. Diagnostic performance for detecting craniosynostosis at the suture level showed no significant difference between ultra-low-dose CT without deep learning reconstruction, ultra-low-dose CT with deep learning reconstruction and routine-dose CT. The estimated effective radiation dose for the ultra-low-dose CT was 0.05 mSv (range, 0.03-0.06 mSv), a 95% reduction in dose over the routine-dose CT at 1.15 mSv (range, 0.54-1.74 mSv). This radiation dose is comparable to 4-view skull radiography (0.05-0.1 mSv) and lower than previously reported effective dose for craniosynostosis protocols (0.08-3.36 mSv).

CONCLUSION

In this pilot study, an ultra-low-dose CT protocol using radiation doses at a level similar to skull radiographs showed preserved diagnostic performance for craniosynostosis, but decreased image quality compared to the routine-dose CT protocol. However, by combining the ultra-low-dose CT protocol with deep learning reconstruction, image quality was improved to a level comparable to the routine-dose CT protocol, without sacrificing diagnostic performance for craniosynostosis.

Reconsidering pregnancy screening policies for minors: patient-specific estimate of fetus and effective dose for potentially pregnant minors undergoing optimized dose CT of the pelvis

BACKGROUND

Only verbal pregnancy screening is recommended for post-menarcheal females undergoing pelvic radiographs. In contrast, usually, a urine/serum pregnancy test for pelvic computed tomographic (CT) exams is required out of concern for higher radiation exposure.

OBJECTIVE

To estimate patient-specific fetus absorbed dose to a potentially pregnant minor from an optimized dose CT of the pelvis for femoral version and surgical planning and provide evidence that such examinations of the pelvis can be performed with only verbal pregnancy screening.

METHODS AND METHODS

A retrospective study was performed on 102 female patients between 12-18 years of age (15.4 ± 2.1 years) who underwent optimized dose CT of the pelvis for orthopedic evaluation of femoral version and surgical planning. Optimized CT exams were performed with weight-adjusted kVp and tube current modulation. Patient-specific dose from the optimized dose CT was calculated using the National Cancer Institute Dosimetry System for CT (NCICT) database by matching each patient to a phantom from the NCI non-reference phantom library based on patient sex, weight, and height. The calculated absorbed uterus dose was used as a surrogate for the fetus dose. Furthermore, patient-specific organ doses were used to estimate the effective dose. The strengths of the linear relationships between the dose metrics and patient characteristics were assessed using Pearson correlation coefficients through linear regression.

RESULTS

The mean patient-specific effective dose for an optimized dose CT of the pelvis was 0.54 ± 0.20 mSv (range: 0.15-1.22 mSv). The mean estimated absorbed uterine dose was 1.57 ± 0.67 mGy (range: 0.42-4.81 mGy). Both effective dose and estimated uterine dose correlated poorly with patient physical characteristics (R = -0.26; 95% CI: [-0.43, -0.007] for age, R = 0.03; 95% CI: [-0.17, 0.22] for weight) but correlated strongly (R = 0.79, 95% CI: [0.7, 0.85]) with CTDIvol.

CONCLUSION

The estimated fetus dose in case of pregnancy was significantly lower than 20 mGy for urine/serum pregnancy screening, suggesting that the pregnancy screening protocols in minors undergoing optimized dose CT require reassessment and may be safely performed by verbal attestation only.

Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.