Automated AI-based coronary calcium scoring using retrospective CT data from SCAPIS is accurate and correlates with expert scoring.

OBJECTIVES: Evaluation of the correlation and agreement between AI and semi-automatic evaluations of calcium scoring CT (CSCT) examinations using extensive data from the Swedish CardioPulmonary bio-Image study (SCAPIS). MATERIALS AND METHODS: In total, 5057 CSCT examinations were performed on one CT system at Linköping University Hospital between October 8, 2015, and June 12, 2018. AI evaluations were compared to semi-automatic CSCT results from expert reader evaluations rendered within SCAPIS. Pearson correlation, intraclass correlation coefficients (ICC), and Bland-Altman analysis were applied for Agatston (AS), volume (VS), mass scores (MS), number of lesions and lesion location. Agreement of Agatston score classifications into cardiovascular (CV) risk categories was evaluated with weighted kappa analysis. RESULTS: The evaluation included 4567 subjects, 2229 (48.8%) male, 2338 (51.2%) female, 50-64 years of age (mean 57.3 ± 4.4). The AS ranged from 0 to 2871 in the cohort, with 2846 subjects having an AS of 0. Mean and median AS were 51.4 and 0.0, respectively. Total AS, VS, MS and number of lesions ICCs were 0.994, 0.994, 0.994, 0.960 (p < 0.001), respectively. Bland-Altman analyses rendered mean differences ± 1.96 SD upper and lower limits of agreement for AS -0.04, -52.5 to 52.4, VS -0.44, -46.51 to 45.63, and MS -0.07, -9.62 to 9.48. Weighted kappa analysis for CV risk category classifications was 0.913, and overall accuracy was 91.2%. CONCLUSION: There was excellent correlation and agreement between AI and semi-automatic evaluations for all calcium scores, number of lesions and lesion location. High degrees of agreement and accuracy were found for the CV risk categorization. KEY POINTS: Question Can AI function as a tool for enhancing the efficiency and accuracy of Coronary Artery Calcium Score (CACS) evaluations in clinical radiology practice? Findings This study confirms the robustness of AI-derived CACS results across extensive datasets, though its generalizability is limited by data acquisition from a single CT system. Clinical relevance This study suggests that AI holds significant promise as a tool for enhancing the efficiency and accuracy of CACS evaluations, with implications for improving patient diagnostics and reducing radiologist workload in clinical practice.

Diagnosis of foreign body aspiration with ultralow-dose CT using a tin filter: a comparison study.

PURPOSE: Suspected airway foreign body aspiration (FBA) is a common event in paediatric emergency units, especially in children under 3 years of age. It can be a life-threatening event if not diagnosed promptly and accurately. The purpose of this study is to compare the diagnostic performance of an ultralow-dose CT (DLP of around 1 mGycm) with that of conventional radiographic methods (fluoroscopy and chest radiography of the airways) in the diagnosis of FBA children's airways. METHODS: Retrospective cross-sectional study. Data from 136 children were collected: 75 were examined with conventional radiographic methods and 61 with ultralow-dose CT. Effective doses were compared using independent t tests. The results of bronchoscopy, if performed, were used in creating contingency 2 × 2 tables to assess the diagnostic performance between modalities. An extra triple reading of all images was applied for this purpose. RESULTS: The effective doses used in the ultralow-dose CT examinations were lower compared with those in conventional methods (p < 0.001). The median dose for CT was 0.04 mSv compared with 0.1 mSv for conventional methods. Sensitivity and specificity were higher for ultralow-dose CT than those for conventional methods (100% and 98% versus 33% and 96%) as were the positive and negative predicted values (90% and 100% versus 60% and 91%). CONCLUSION: Ultralow-dose CT can be used as the imaging of choice in the diagnosis of airway FBA in emergency settings, thereby avoiding concerns about radiation doses and negative bronchoscopy outcomes.

Quality control of CT systems by automated monitoring of key performance indicators: a two-year study.

The purpose of this study was to develop a method of performing routine periodical quality controls (QC) of CT systems by automatically analyzing key performance indicators (KPIs), obtainable from images of manufacturers' quality assurance (QA) phantoms. A KPI pertains to a measurable or determinable QC parameter that is influenced by other underlying fundamental QC parameters. The established KPIs are based on relationships between existing QC parameters used in the annual testing program of CT scanners at the Karolinska University Hospital in Stockholm, Sweden. The KPIs include positioning, image noise, uniformity, homogeneity, the CT number of water, and the CT number of air. An application (MonitorCT) was developed to automatically evaluate phantom images in terms of the established KPIs. The developed methodology has been used for two years in clinical routine, where CT technologists perform daily scans of the manufacturer's QA phantom and automatically send the images to MonitorCT for KPI evaluation. In the cases where results were out of tolerance, actions could be initiated in less than 10 min. 900 QC scans from two CT scanners have been collected and analyzed over the two-year period that MonitorCT has been active. Two types of errors have been registered in this period: a ring artifact was discovered with the image noise test, and a calibration error was detected multiple times with the CT number test. In both cases, results were outside the tolerances defined for MonitorCT, as well as by the vendor. Automated monitoring of KPIs is a powerful tool that can be used to supplement established QC methodologies. Medical physicists and other professionals concerned with the performance of a CT system will, using such methods, have access to comprehensive data on the current and historical (trend) status of the system such that swift actions can be taken in order to ensure the quality of the CT examinations, patient safety, and minimal disruption of service.

Ventriculoperitoneal shunt survey in pediatric patients in an emergency setting: a comparison between ultra-low-dose CT using a tin filter and plain radiography.

OBJECTIVE: The aim of this study was to investigate the diagnostic performance, effective radiation dose, and examination time of ventriculoperitoneal shunt evaluation using full-body ultra-low-dose CT (ULD CT) with a tin filter compared with digital plain radiography in a pediatric population. METHODS: A retrospective cross-sectional study was conducted in an emergency setting. Data from 143 children were collected. Sixty were examined with ULD CT with a tin filter and 83 with digital plain radiography methods. Effective doses and times were compared between the two methods. Two observers in pediatric radiology evaluated the patient images. Clinical findings and results from shunt revision, if it was performed, were used to evaluate the diagnostic performance between modalities. An examination-room simulation was performed of the two methods to estimate representative examination times. RESULTS: The mean effective radiation dose for ULD CT with the tin filter was estimated to be 0.29 ± 0.16 mSv compared with 0.16 ± 0.19 mSv for digital plain radiography, with both examinations associated with a very low lifetime attributable risk (< 0.01%). The shunt tip could be more reliably located with ULD CT. ULD CT also allowed assessment of additional findings to explain patient symptoms, such as a cyst at the tip of the shunt catheter and the presence of an obstructing rubber nipple in the duodenum that could not have been observed on a plain radiograph. The examination time with ULD CT of the shunt was estimated to be 20 minutes. The examination time of the shunt with digital plain radiography, including the examination itself time and transfer of the patient between rooms, was estimated to be 60 minutes. CONCLUSIONS: ULD CT using a tin filter allows good visualization of the position or disruption of the shunt catheter that is comparable or superior to plain radiography, at a higher dose, while providing additional findings and reduced patient discomfort.

The synthetic localizer radiograph - A new CT scan planning method.

OBJECTIVE: To investigate if the conventional localizer radiograph (LR) can be replaced by a synthetic LR (SLR), generated from a low-dose spiral CT scan, for CT scan planning with minimal changes to current clinical workflows. METHODS: A dosimetric comparison of SLRs and LRs was made using Monte Carlo methods. Water equivalent diameters (WEDs) of a centered and mis-centered phantom were estimated from low-dose spiral CT scans and LRs acquired at different angles. Body sizes, in the form of two lengths and two diameters obtained from SLRs and LRs, were compared for 10 patients (4 men and 6 women with a mean age of 74.8 and 76.2 years respectively) undergoing CT of thorax and abdomen. The image quality of SLRs for CT scan planning relative to LRs was rated using a 5-grade scale by four radiologists and two CT radiographers. RESULTS: An SLR can be obtained at a comparable effective dose to that of traditionally acquired LRs: 0.14 mSv. WEDs from LRs were more affected by mis-centering than WEDs calculated from low-dose spiral scans. One significant discrepancy of estimated body sizes was observed, the broadest part of the patient that on lateral localizers showed a mean deviation of 17.7 mm (range: 7.3-28.7 mm, p < 0.001). The anteroposterior/posteroanterior SLR image quality was assessed as better compared to an LR while the same could not be shown for lateral localizers. CONCLUSIONS: SLRs based on low-dose spiral scans can replace LRs for CT planning.

Influence of tube potential on CT body composition analysis.

OBJECTIVES: Our purpose was to investigate whether tube potential in contrast-enhanced computed tomography (CT) affects body composition analysis. METHODS: Images from dual-source, dual-energy CT from the abdomen with intravenous contrast media administration were used. A total of 17 patients (11 women, mean age 52) with a mean body mass index of 20.8 kg/cm2 were included. Simultaneously acquired images with a tube voltage of 80 kV and 140 kV were compared. Body composition was analyzed on a single slice at the L3 level. Parameters evaluated included muscle and fat attenuation (Hounsfield units [HU]), skeletal muscle index (cm2/m2), muscle area (cm2), and steatotic muscle area (cm2). Significant differences between 80 kV and 140 kV series were compared using the paired Student's t test. RESULTS: Tube potential affected muscle attenuation with an average difference of 17% between 80 kV and 140 kV series (48 HU versus 41 HU, P < 0.01), fat attenuation (-84 HU versus -69 HU, P < 0.01), skeletal muscle index of 5.2% (40.1 cm2/m2 versus 42.2 cm2/m2, P < 0.01), muscle area of 5.1% (117 cm2 versus 123 cm2, P < 0.01), and steatotic muscle area of 12.9% (31 cm2 versus 35 cm2, P < 0.01). CONCLUSION: Tube potential significantly affects body segmentation in contrast-enhanced CT.

Evaluating the impact of scan settings on automatic tube current modulation in CT using a novel phantom.

OBJECTIVE: The aim of this study was to make a comprehensive evaluation of how variable scan settings can affect the performance of automatic tube current modulation (ATCM) in recent CT scanners from the four major manufacturers. METHODS: A phantom was designed and manufactured for the purpose of evaluating ATCM. The phantom was scanned with four categories of systematically varied settings (scan projection radiograph, technique and reconstruction parameters and phantom miscentring). The performance of ATCM, in terms of applied tube current and noise uniformity, for the scans with varied settings was compared with a reference scan using subjective and quantitative approaches. RESULTS: The ATCM implemented by each manufacturer is based on different principles and any affect to the performance of the ATCM, when varying scan settings, will manifest differently among the vendors. The results are summarized in four tables corresponding to the categories of varied settings. CONCLUSION: The developed phantom proved useful for evaluating the ATCM. It is important to understand how different implementations (vendor specific) of ATCM perform in order to make informed decisions about the selection of scan settings when designing protocols. The resulting tables can serve as a reference for understanding the different implementations of ATCM and highlight settings that should be taken into consideration when adjusting an imaging protocol. Advances in knowledge: The results from this work can serve as a reference for how changes in geometry or scan settings can affect the performance of ATCM, in terms of tube current and noise.

The dosimetric impact of including the patient table in CT dose estimates.

The purpose of this study was to evaluate the dosimetric impact of including the patient table in Monte Carlo CT dose estimates for both spiral scans and scan projection radiographs (SPR). CT scan acquisitions were simulated for a Siemens SOMATOM Force scanner (Siemens Healthineers, Forchheim, Germany) with and without a patient table present. An adult male, an adult female and a pediatric female voxelized phantom were simulated. The simulated scans included tube voltages of 80 and 120 kVp. Spiral scans simulated without a patient table resulted in effective doses that were overestimated by approximately 5% compared to the same simulations performed with the patient table present. Doses in selected individual organs (breast, colon, lung, red bone marrow and stomach) were overestimated by up to 8%. Effective doses from SPR acquired with the x-ray tube stationary at 6 o'clock (posterior-anterior) were overestimated by 14-23% when the patient table was not included, with individual organ dose discrepancies (breast, colon, lung red bone marrow and stomach) all exceeding 13%. The reference entrance skin dose to the back were in this situation overestimated by 6-15%. These results highlight the importance of including the patient table in patient dose estimates for such scan situations.

Upper limits of the photon fluence rate on CT detectors: Case study on a commercial scanner.

PURPOSE: The highest photon fluence rate that a computed tomography (CT) detector must be able to measure is an important parameter. The authors calculate the maximum transmitted fluence rate in a commercial CT scanner as a function of patient size for standard head, chest, and abdomen protocols. METHODS: The authors scanned an anthropomorphic phantom (Kyoto Kagaku PBU-60) with the reference CT protocols provided by AAPM on a GE LightSpeed VCT scanner and noted the tube current applied with the tube current modulation (TCM) system. By rescaling this tube current using published measurements on the tube current modulation of a GE scanner [N. Keat, "CT scanner automatic exposure control systems," MHRA Evaluation Report 05016, ImPACT, London, UK, 2005], the authors could estimate the tube current that these protocols would have resulted in for other patient sizes. An ECG gated chest protocol was also simulated. Using measured dose rate profiles along the bowtie filters, the authors simulated imaging of anonymized patient images with a range of sizes on a GE VCT scanner and calculated the maximum transmitted fluence rate. In addition, the 99th and the 95th percentiles of the transmitted fluence rate distribution behind the patient are calculated and the effect of omitting projection lines passing just below the skin line is investigated. RESULTS: The highest transmitted fluence rates on the detector for the AAPM reference protocols with centered patients are found for head images and for intermediate-sized chest images, both with a maximum of 3.4 ⋅ 10(8) mm(-2) s(-1), at 949 mm distance from the source. Miscentering the head by 50 mm downward increases the maximum transmitted fluence rate to 5.7 ⋅ 10(8) mm(-2) s(-1). The ECG gated chest protocol gives fluence rates up to 2.3 ⋅ 10(8) - 3.6 ⋅ 10(8) mm(-2) s(-1) depending on miscentering. CONCLUSIONS: The fluence rate on a CT detector reaches 3 ⋅ 10(8) - 6 ⋅ 10(8) mm(-2) s(-1) in standard imaging protocols, with the highest rates occurring for ECG gated chest and miscentered head scans. These results will be useful to developers of CT detectors, in particular photon counting detectors.

Technical Note: On the calculation of stopping-power ratio for stoichiometric calibration in proton therapy.

PURPOSE: The quantitative effects of assumptions made in the calculation of stopping-power ratios (SPRs) are investigated, for stoichiometric CT calibration in proton therapy. The assumptions investigated include the use of the Bethe formula without correction terms, Bragg additivity, the choice of I-value for water, and the data source for elemental I-values. METHODS: The predictions of the Bethe formula for SPR (no correction terms) were validated against more sophisticated calculations using the SRIM software package for 72 human tissues. A stoichiometric calibration was then performed at our hospital. SPR was calculated for the human tissues using either the assumption of simple Bragg additivity or the Seltzer-Berger rule (as used in ICRU Reports 37 and 49). In each case, the calculation was performed twice: First, by assuming the I-value of water was an experimentally based value of 78 eV (value proposed in Errata and Addenda for ICRU Report 73) and second, by recalculating the I-value theoretically. The discrepancy between predictions using ICRU elemental I-values and the commonly used tables of Janni was also investigated. RESULTS: Errors due to neglecting the correction terms to the Bethe formula were calculated at less than 0.1% for biological tissues. Discrepancies greater than 1%, however, were estimated due to departures from simple Bragg additivity when a fixed I-value for water was imposed. When the I-value for water was calculated in a consistent manner to that for tissue, this disagreement was substantially reduced. The difference between SPR predictions when using Janni's or ICRU tables for I-values was up to 1.6%. Experimental data used for materials of relevance to proton therapy suggest that the ICRU-derived values provide somewhat more accurate results (root-mean-square-error: 0.8% versus 1.6%). CONCLUSIONS: The conclusions from this study are that (1) the Bethe formula can be safely used for SPR calculations without correction terms; (2) simple Bragg additivity can be reasonably assumed for compound materials; (3) if simple Bragg additivity is assumed, then the I-value for water should be calculated in a consistent manner to that of the tissue of interest (rather than using an experimentally derived value); (4) the ICRU Report 37 I-values may provide a better agreement with experiment than Janni's tables.