Fully automated computational measurement of noise in positron emission tomography.

OBJECTIVES: To introduce an automated computational algorithm that estimates the global noise level across the whole imaging volume of PET datasets. METHODS: [18F]FDG PET images of 38 patients were reconstructed with simulated decreasing acquisition times (15-120 s) resulting in increasing noise levels, and with block sequential regularized expectation maximization with beta values of 450 and 600 (Q.Clear 450 and 600). One reader performed manual volume-of-interest (VOI) based noise measurements in liver and lung parenchyma and two readers graded subjective image quality as sufficient or insufficient. An automated computational noise measurement algorithm was developed and deployed on the whole imaging volume of each reconstruction, delivering a single value representing the global image noise (Global Noise Index, GNI). Manual noise measurement values and subjective image quality gradings were compared with the GNI. RESULTS: Irrespective of the absolute noise values, there was no significant difference between the GNI and manual liver measurements in terms of the distribution of noise values (p = 0.84 for Q.Clear 450, and p = 0.51 for Q.Clear 600). The GNI showed a fair to moderately strong correlation with manual noise measurements in liver parenchyma (r = 0.6 in Q.Clear 450, r = 0.54 in Q.Clear 600, all p < 0.001), and a fair correlation with manual noise measurements in lung parenchyma (r = 0.52 in Q.Clear 450, r = 0.33 in Q.Clear 600, all p < 0.001). Classification performance of the GNI for subjective image quality was AUC 0.898 for Q.Clear 450 and 0.919 for Q.Clear 600. CONCLUSION: An algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. CLINICAL RELEVANCE STATEMENT: An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking of clinical PET imaging within and across institutions. KEY POINTS: • Noise is an important quantitative marker that strongly impacts image quality of PET images. • An automated computational noise measurement algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. • An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking as well as protocol harmonization.

PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI.

PURPOSE: High PSMA expression might be correlated with structural characteristics such as growth patterns on histopathology, not recognized by the human eye on MRI images. Deep structural image analysis might be able to detect such differences and therefore predict if a lesion would be PSMA positive. Therefore, we aimed to train a neural network based on PSMA PET/MRI scans to predict increased prostatic PSMA uptake based on the axial T2-weighted sequence alone. MATERIAL AND METHODS: All patients undergoing simultaneous PSMA PET/MRI for PCa staging or biopsy guidance between April 2016 and December 2020 at our institution were selected. To increase the specificity of our model, the prostatic beds on PSMA PET scans were dichotomized in positive and negative regions using an SUV threshold greater than 4 to generate a PSMA PET map. Then, a C-ENet was trained on the T2 images of the training cohort to generate a predictive prostatic PSMA PET map. RESULTS: One hundred and fifty-four PSMA PET/MRI scans were available (133 [68Ga]Ga-PSMA-11 and 21 [18F]PSMA-1007). Significant cancer was present in 127 of them. The whole dataset was divided into a training cohort (n = 124) and a test cohort (n = 30). The C-ENet was able to predict the PSMA PET map with a dice similarity coefficient of 69.5 ± 15.6%. CONCLUSION: Increased prostatic PSMA uptake on PET might be estimated based on T2 MRI alone. Further investigation with larger cohorts and external validation is needed to assess whether PSMA uptake can be predicted accurately enough to help in the interpretation of mpMRI.

A third of the radiotracer dose: two decades of progress in pediatric [18F]fluorodeoxyglucose PET/CT and PET/MR imaging.

OBJECTIVES: To assess the evolution of administered radiotracer activity for F-18-fluorodeoxyglucose (18F-FDG) PET/CT or PET/MR in pediatric patients (0-16 years) between years 2000 and 2021. METHODS: Pediatric patients (≤ 16 years) referred for 18F-FDG PET/CT or PET/MR imaging of the body during 2000 and 2021 were retrospectively included. The amount of administered radiotracer activity in megabecquerel (MBq) was recorded, and signal-to-noise ratio (SNR) was measured in the right liver lobe with a 4 cm3 volume of interest as an indicator for objective image quality. Descriptive statistics were computed. RESULTS: Two hundred forty-three children and adolescents underwent a total of 466 examinations. The median injected 18F-FDG activity in MBq decreased significantly from 296 MBq in 2000-2005 to 100 MBq in 2016-2021 (p < 0.001), equaling approximately one-third of the initial amount. The median SNR ratio was stable during all years with 11.7 (interquartile range [IQR] 10.7-12.9, p = 0.133). CONCLUSIONS: Children have benefited from a massive reduction in the administered 18F-FDG dose over the past 20 years without compromising objective image quality. CLINICAL RELEVANCE STATEMENT: Radiotracer dose was reduced considerably over the past two decades of pediatric F-18-fluorodeoxyglucose PET/CT and PET/MR imaging highlighting the success of technical innovations in pediatric PET imaging. KEY POINTS: • The evolution of administered radiotracer activity for F-18-fluorodeoxyglucose (18F-FDG) PET/CT or PET/MR in pediatric patients (0-16 years) between 2000 and 2021 was assessed. • The injected tracer activity decreased by 66% during the study period from 296 megabecquerel (MBq) to 100 MBq (p < 0.001). • The continuous implementation of technical innovations in pediatric hybrid 18F-FDG PET has led to a steady decrease in the amount of applied radiotracer, which is particularly beneficial for children who are more sensitive to radiation.

Comparison of detection of trauma-related injuries using combined "all-in-one" fused images and conventionally reconstructed images in acute trauma CT.

OBJECTIVES: To compare the accuracy of lesion detection of trauma-related injuries using combined "all-in-one" fused (AIO) and conventionally reconstructed images (CR) in acute trauma CT. METHODS: In this retrospective study, trauma CT of 66 patients (median age 47 years, range 18-96 years; 20 female (30.3%)) were read using AIO and CR. Images were independently reviewed by 4 blinded radiologists (two residents and two consultants) for trauma-related injuries in 22 regions. Sub-analyses were performed to analyze the influence of experience (residents vs. consultants) and body region (chest, abdomen, skeletal structures) on lesion detection. Paired t-test was used to compare the accuracy of lesion detection. The effect size was calculated (Cohen's d). Linear mixed-effects model with patients as the fixed effect and random forest models were used to investigate the effect of experience, reconstruction/image processing, and body region on lesion detection. RESULTS: Reading time of residents was significantly faster using AIO (AIO: 266 ± 72 s, CR: 318 ± 113 s; p < 0.001; d = 0.46) while no significant difference was observed in the accuracy of lesion detection (AIO: 93.5 ± 6.0%, CR: 94.6 ± 6.0% p = 0.092; d = - 0.21). Reading time of consultants showed no significant difference (AIO: 283 ± 82 s, CR: 274 ± 95 s; p = 0.067; d = 0.16). Accuracy was significantly higher using CR; however, the difference and effect size were very small (AIO 95.1 ± 4.9%, CR: 97.3 ± 3.7%, p = 0.002; d = - 0.39). The linear mixed-effects model showed only minor effect of image processing/reconstruction for lesion detection. CONCLUSIONS: Residents at the emergency department might benefit from faster reading time without sacrificing lesion detection rate using AIO for trauma CT. KEY POINTS: • Image fusion techniques decrease the reading time of acute trauma CT without sacrificing diagnostic accuracy.

Splenic switch-off as a predictor for coronary adenosine response: validation against 13N-ammonia during co-injection myocardial perfusion imaging on a hybrid PET/CMR scanner.

BACKGROUND: Inadequate coronary adenosine response is a potential cause for false negative ischemia testing. Recently, the splenic switch-off (SSO) sign has been identified as a promising tool to ascertain the efficacy of adenosine during vasodilator stress cardiovascular magnetic resonance imaging (CMR). We assessed the value of SSO to predict adenosine response, defined as an increase in myocardial blood flow (MBF) during quantitative stress myocardial perfusion 13 N-ammonia positron emission tomography (PET). METHODS: We prospectively enrolled 64 patients who underwent simultaneous CMR and PET myocardial perfusion imaging on a hybrid PET/CMR scanner with co-injection of gadolinium based contrast agent (GBCA) and 13N-ammonia during rest and adenosine-induced stress. A myocardial flow reserve (MFR) of  > 1.5 or ischemia as assessed by PET were defined as markers for adequate coronary adenosine response. The presence or absence of SSO was visually assessed. The stress-to-rest intensity ratio (SIR) was calculated as the ratio of stress over rest peak signal intensity for splenic tissue. Additionally, the spleen-to-myocardium ratio, defined as the relative change of spleen to myocardial signal, was calculated for stress (SMRstress) and rest. RESULTS: Sixty-one (95%) patients were coronary adenosine responders, but SSO was absent in 18 (28%) patients. SIR and SMRstress were significantly lower in patients with SSO (SIR: 0.56 ± 0.13 vs. 0.93 ± 0.23; p < 0.001 and SMRstress: 1.09 ± 0.47 vs. 1.68 ± 0.62; p < 0.001). Mean hyperemic and rest MBF were 2.12 ± 0.68 ml/min/g and 0.78 ± 0.26 ml/min/g, respectively. MFR was significantly higher in patients with vs. patients without presence of SSO (3.07 ± 1.03 vs. 2.48 ± 0.96; p = 0.038), but there was only a weak inverse correlation between SMRstress and MFR (R = -0.378; p = 0.02) as well as between SIR and MFR (R = -0.356; p = 0.004). CONCLUSIONS: The presence of SSO implies adequate coronary adenosine-induced MBF response. Its absence, however, is not a reliable indicator for failed adenosine-induced coronary vasodilatation.

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.

OBJECTIVES: To evaluate the diagnostic performance of a deep learning algorithm for automated detection of small 18F-FDG-avid pulmonary nodules in PET scans, and to assess whether novel block sequential regularized expectation maximization (BSREM) reconstruction affects detection accuracy as compared to ordered subset expectation maximization (OSEM) reconstruction. METHODS: Fifty-seven patients with 92 18F-FDG-avid pulmonary nodules (all ≤ 2 cm) undergoing PET/CT for oncological (re-)staging were retrospectively included and a total of 8824 PET images of the lungs were extracted using OSEM and BSREM reconstruction. Per-slice and per-nodule sensitivity of a deep learning algorithm was assessed, with an expert readout by a radiologist/nuclear medicine physician serving as standard of reference. Receiver-operator characteristic (ROC) curve of OSEM and BSREM were assessed and the areas under the ROC curve (AUC) were compared. A maximum standardized uptake value (SUVmax)-based sensitivity analysis and a size-based sensitivity analysis with subgroups defined by nodule size was performed. RESULTS: The AUC of the deep learning algorithm for nodule detection using OSEM reconstruction was 0.796 (CI 95%; 0.772-0.869), and 0.848 (CI 95%; 0.828-0.869) using BSREM reconstruction. The AUC was significantly higher for BSREM compared to OSEM (p = 0.001). On a per-slice analysis, sensitivity and specificity were 66.7% and 79.0% for OSEM, and 69.2% and 84.5% for BSREM. On a per-nodule analysis, the overall sensitivity of OSEM was 81.5% compared to 87.0% for BSREM. CONCLUSIONS: Our results suggest that machine learning algorithms may aid detection of small 18F-FDG-avid pulmonary nodules in clinical PET/CT. AI performed significantly better on images with BSREM than OSEM. KEY POINTS: • The diagnostic value of deep learning for detecting small lung nodules (≤ 2 cm) in PET images using BSREM and OSEM reconstruction was assessed. • BSREM yields higher SUVmaxof small pulmonary nodules as compared to OSEM reconstruction. • The use of BSREM translates into a higher detectability of small pulmonary nodules in PET images as assessed with artificial intelligence.

"Apical thinning": Relations between myocardial wall thickness and apical left ventricular tracer uptake as assessed with positron emission tomography myocardial perfusion imaging.

BACKGROUND: A reduction in left ventricular apical tracer uptake (apical thinning) is frequently observed in myocardial perfusion imaging (MPI), yet its cause remains a matter of debate, particularly in perfusion emission tomography (PET). This analysis sought to determine whether apical thinning in PET-MPI is attributable to true anatomical thinning of the left ventricular apical myocardium. METHODS AND RESULTS: We retrospectively analyzed 57 patients without any history or signs of apical myocardial infarction who underwent rest PET-MPI with 13N-ammonia and contrast-enhanced cardiac computed tomography (CT). Semi-quantitative normalized percent apical 13N-ammonia uptake at rest, myocardial blood flow (MBF), and k2 wash-out rate constants were compared to apical myocardial wall thickness measurements derived from CT and base-to-apex gradients were calculated. Apical thinning was found in 93% of patients and in 74% when analysis of normalized apical tracer uptake was confined to end-systole. No significant correlation was found between apical myocardial thickness and apical tracer uptake (r = - 0.080, P = .553), MBF (r = - 0.211, P = .115), or k2 wash-out rate (r = - 0.023, P = .872), nor between apical myocardial thickness and any gradients. A statistically significant but small difference in apical myocardial thickness was observed in patients with moderately to severely reduced apical tracer uptake vs patients with normal to mildly reduced uptake (4.3 ± 0.7 mm vs 4.7 ± 0.7 mm; P = .043). CONCLUSIONS: Apical thinning is a highly prevalent finding during 13N-ammonia PET-MPI that is not solely attributable to true anatomical apical wall thickness or the partial volume effect. Other factors that yet need to be identified seem to have a more prominent impact.

Ultra-low-dose computed tomography for attenuation correction of cadmium-zinc-telluride single photon emission computed tomography myocardial perfusion imaging.

BACKGROUND: The applicability of ultra-low-dose computed tomography (CT) for attenuation correction (AC) of single-photon-emission computed tomography myocardial perfusion imaging (SPECT-MPI) remains elusive. METHODS AND RESULTS: One-hundred patients underwent one-day 99mTc-tetrofosmin stress-rest MPI and non-contrast enhanced cardiac CT with 120, 80, and 70 kilovolt peak (kVp) tube voltage and tube current of 200 milliamperes for creation of AC maps. Normalized percent myocardial uptake from SPECT-MPI using 80 kVp scans for AC showed excellent correlation vs AC from 120 kVp scans for stress [intraclass correlation (ICC) = 0.988, 95% CI = 0.986-0.989, P < .001] and rest (ICC = 0.985, 95% CI = 0.983-0.987, P < .001) with narrow Bland-Altman limits of agreement (BA-LA) (- 5.3% to 4.5% and - 5.4% to 4.4%, respectively) and minimal bias (- 0.4% and - 0.5%, respectively). Correlation of AC SPECT-MPI based on 70 vs 120 kVp scans was excellent for stress (ICC = 0.988, 95% CI = 0.986-0.989, P < .001) and rest (ICC = 0.986, 95% CI = 0.984-0.987, P < .001) with narrow BA-LA (- 5.3% to 4.4% and - 5.2% to 4.5%, respectively) and small bias (- 0.4% and - 0.3%, respectively). Mean effective radiation dose for the 120, 80 and 70 kVp scans were 0.58 ± 0.07, 0.19 ± 0.02, and 0.12 ± 0.01 mSv, respectively. CONCLUSIONS: Attenuation maps for MPI obtained from ultra-low radiation dose CT scans are interchangeable with attenuation maps from standard-dose CT while offering a substantial reduction in radiation dose exposure.

Sex and age differences in the association of heart rate responses to adenosine and myocardial ischemia in patients undergoing myocardial perfusion imaging.

BACKGROUND: In light of growing cardiovascular mortality rates observed in young women, sexual dimorphism in cardiac autonomic nervous control is gaining increasing attention. Heart rate responses to adenosine mirror autonomic activity and may carry important prognostic information. METHODS AND RESULTS: Hemodynamic changes during adenosine stress were retrospectively analysed in a propensity-matched cohort of 1932 consecutive patients undergoing myocardial perfusion single-photon-emission computed tomography (MPI-SPECT). Heart rate (HR) and systolic blood pressure (SBP) increased during adenosine infusion (P < 0.001). The increase in SBP and HR (heart rate reserve, HRR), was significantly more pronounced in women compared with men (P < 0.05). Patients ≤ 55 years had a higher HRR compared with patients > 55 years (46.8% vs 37.5%, P = 0.015). Women ≤ 55 years with a reversible perfusion defect on MPI-SPECT exhibited the highest HRR (89.2%), while age-matched men showed a blunted HR response to adenosine (26.4%, P = 0.01). Accordingly, age and an interaction term of female sex and increased HRR were identified as significant predictors of myocardial ischemia in a multiple regression analysis (OR 1.4, 95% CI 1.02-1.9, P = 0.038). CONCLUSION: HRR during adenosine infusion is influenced by age and sex. Our data suggest a stronger, sympathetic-driven, hemodynamic response to adenosine in younger women with myocardial ischemia.

Potential of Radiation Dose Reduction by Optimizing Z-Axis Coverage in Coronary Computed Tomography Angiography on a Latest-Generation 256-Slice Scanner.

OBJECTIVE: The purpose of this study was to quantify the reduction in radiation dose achievable by using the optimal z-axis coverage in coronary computed tomography (CT) angiography (CCTA) on a latest-generation 256-slice scanner. METHODS: A total of 408 scans were reviewed that were performed on a wide-range detector scanner allowing up to 16-cm z-axis coverage (adjustable in 2-cm increments). For each CCTA study, we assessed the radiation dose (ie, dose-length product and volume CT dose index) and measured the minimum z-axis coverage necessary to cover the complete cardiac anatomy. We calculated the potential radiation dose savings achievable through reduction of the z-axis coverage to the minimum necessary. RESULTS: The majority of the CCTA scans were performed with a z-axis coverage of 16 cm (n = 285, 69.9%), followed by 14 cm (n = 121, 29.7%) and 12 cm (n = 2, 0.5%). In the group that was scanned with a collimation of 16 cm, radiation dose could have been reduced by 12.5% in 55 patients, 25% in 195 patients, and 37.5% in 33 patients when using optimal z-axis coverage for CCTA. In the group that was scanned with a collimation of 14 cm, radiation dose could have been reduced by 14.3% in 90 patients, and 28.6% in 30 patients, whereas in the group that was scanned with a collimation of 12 cm, dose could have been reduced by 16.7% in 2 patients. CONCLUSIONS: Using correct z-axis coverage in CCTA on a latest-generation 256-slice scanner yields average dose reductions of 22.0% but may be as high as 37.5%.

Enhanced radiation exposure associated with anterior-posterior x-ray tube position in young women undergoing cardiac computed tomography.

Given the current increase in the incidence of coronary artery disease in younger women as well as the high lifetime risk of developing an x-ray-induced malignancy in this population, we aimed at assessing chest radiation in 206 women ≤55 years old undergoing coronary calcium scoring (CACS) by using a Monte Carlo simulation tool. Our data indicate that the simulated radiation dose of the female breast during CACS depends substantially on the starting position of the x-ray tube, with an almost 2 times excess of breast radiation exposure being measured during anterior-posterior tube positioning. Thus, an additional technical feature taking into account the position of the x-ray tube when acquisition is triggered might be an important tool to reduce radiation exposure of the female breast during CACS.

Heart rate reserve during pharmacological stress is a significant negative predictor of impaired coronary flow reserve in women.

PURPOSE: Evidence to date has failed to adequately explore determinants of cardiovascular risk in women with coronary microvascular dysfunction (CMVD). Heart rate responses to adenosine mirror autonomic activity and may carry important prognostic information for the diagnosis of CMVD. METHODS: Hemodynamic changes during adenosine stress were analyzed in a propensity-matched cohort of 404 patients (202 women, mean age 65.9 ± 11.0) who underwent clinically indicated myocardial perfusion 13N-ammonia Positron-Emission-Tomography (PET) at our institution between September 2013 and May 2017. RESULTS: Baseline heart rate (HR) was significantly higher in patients with abnormal coronary flow reserve (CFR, p < 0.001 vs normal CFR). Accordingly, a blunted HR response to adenosine (=reduced heart rate reserve, %HRR) was seen in patients with abnormal CFR, with a most pronounced effect being observed in female patients free of myocardial ischemia (45.9 ± 34.9 vs 26.5 ± 18.0, p < 0.001 in women and 29.1 ± 16.9 vs 24.3 ± 21.7, p = 0.15 in men). Hence, a fully-adjusted multivariate logistic regression model identified HRR as the strongest negative predictor of reduced CFR in women free of myocardial ischemia, but not in men. Accordingly, receiver operating characteristics (ROC) curves for the presence of reduced CFR revealed that a %HRR <35 was a powerful predictor for abnormal CFR with a sensitivity of 81% and a specificity of 60% in women. CONCLUSION: A blunted HRR <35% is associated with abnormal CFR in women. Taking into account HR responses during stress test in women may help to risk stratify the heterogeneous female population of patients with non-obstructive coronary artery disease (CAD).

Clinical Features and Outcomes of Takotsubo (Stress) Cardiomyopathy.

BACKGROUND: The natural history, management, and outcome of takotsubo (stress) cardiomyopathy are incompletely understood. METHODS: The International Takotsubo Registry, a consortium of 26 centers in Europe and the United States, was established to investigate clinical features, prognostic predictors, and outcome of takotsubo cardiomyopathy. Patients were compared with age- and sex-matched patients who had an acute coronary syndrome. RESULTS: Of 1750 patients with takotsubo cardiomyopathy, 89.8% were women (mean age, 66.8 years). Emotional triggers were not as common as physical triggers (27.7% vs. 36.0%), and 28.5% of patients had no evident trigger. Among patients with takotsubo cardiomyopathy, as compared with an acute coronary syndrome, rates of neurologic or psychiatric disorders were higher (55.8% vs. 25.7%) and the mean left ventricular ejection fraction was markedly lower (40.7±11.2% vs. 51.5±12.3%) (P<0.001 for both comparisons). Rates of severe in-hospital complications including shock and death were similar in the two groups (P=0.93). Physical triggers, acute neurologic or psychiatric diseases, high troponin levels, and a low ejection fraction on admission were independent predictors for in-hospital complications. During long-term follow-up, the rate of major adverse cardiac and cerebrovascular events was 9.9% per patient-year, and the rate of death was 5.6% per patient-year. CONCLUSIONS: Patients with takotsubo cardiomyopathy had a higher prevalence of neurologic or psychiatric disorders than did those with an acute coronary syndrome. This condition represents an acute heart failure syndrome with substantial morbidity and mortality. (Funded by the Mach-Gaensslen Foundation and others; ClinicalTrials.gov number, NCT01947621.).

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.

Evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[18F]FDG PET/CT between 2007 and 2021.

OBJECTIVES: To evaluate the evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[18F]fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET/CT between 2007 and 2021. METHODS AND MATERIALS: Data from all pediatric patients aged 0-18 years who underwent hybrid 2-[18F]FDG PET/CT of the body between January 2007 and May 2021 were reviewed. Demographic and imaging parameters were collected. A board-certified radiologist reviewed all CT scans and measured image noise in the brain, liver, and adductor muscles. RESULTS: 294 scans from 167 children (72 females (43%); median age: 14 (IQR 10-15) years; BMI: median 17.5 (IQR 15-20.4) kg/m2) were included. CT dose index-volume (CTDIvol) and dose length product (DLP) both decreased significantly from 2007 to 2021 (both p < 0.001, Spearman's rho coefficients -0.46 and -0.35, respectively). Specifically, from 2007 to 2009 to 2019-2021 CTDIvol and DLP decreased from 2.94 (2.14-2.99) mGy and 309 (230-371) mGy*cm, respectively, to 0.855 (0.568-1.11) mGy and 108 (65.6-207) mGy*cm, respectively. From 2007 to 2021, image noise in the brain and liver remained constant (p = 0.26 and p = 0.06), while it decreased in the adductor muscles (p = 0.007). Peak tube voltage selection (in kilovolt, kV) of CT scans shifted from high kV imaging (140 or 120kVp) to low kV imaging (100 or 80kVp) (p < 0.001) from 2007 to 2021. CONCLUSION: CT radiation dose in pediatric patients undergoing hybrid 2-[18F]FDG PET/CT has decreased in recent years equaling approximately one-third of the initial amount. ADVANCES IN KNOWLEDGE: Over the past 15 years, CT radiation dose decreased considerably in pediatric patients undergoing hybrid imaging, while objective image quality may not have been compromised.

Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system.

To evaluate whether a machine learning classifier can evaluate image quality of maximum intensity projection (MIP) images from F18-FDG-PET scans. A total of 400 MIP images from F18-FDG-PET with simulated decreasing acquisition time (120 s, 90 s, 60 s, 30 s and 15 s per bed-position) using block sequential regularized expectation maximization (BSREM) with a beta-value of 450 and 600 were created. A machine learning classifier was fed with 283 images rated "sufficient image quality" and 117 images rated "insufficient image quality". The classification performance of the machine learning classifier was assessed by calculating sensitivity, specificity, and area under the receiver operating characteristics curve (AUC) using reader-based classification as the target. Classification performance of the machine learning classifier was AUC 0.978 for BSREM beta 450 and 0.967 for BSREM beta 600. The algorithm showed a sensitivity of 89% and 94% and a specificity of 94% and 94% for the reconstruction BSREM 450 and 600, respectively. Automated assessment of image quality from F18-FDG-PET images using a machine learning classifier provides equivalent performance to manual assessment by experienced radiologists.

Characterization of hypermetabolic lymph nodes after SARS-CoV-2 vaccination using PET-CT derived node-RADS, in patients with melanoma.

This study aimed to evaluate the diagnostic accuracy of Node Reporting and Data System (Node-RADS) in discriminating between normal, reactive, and metastatic axillary LNs in patients with melanoma who underwent SARS-CoV-2 vaccination. Patients with proven melanoma who underwent a 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[18F]-FDG PET/CT) between February and April 2021 were included in this retrospective study. Primary melanoma site, vaccination status, injection site, and 2-[18F]-FDG PET/CT were used to classify axillary LNs into normal, inflammatory, and metastatic (combined classification). An adapted Node-RADS classification (A-Node-RADS) was generated based on LN anatomical characteristics on low-dose CT images and compared to the combined classification. 108 patients were included in the study (54 vaccinated). HALNs were detected in 42 patients (32.8%), of whom 97.6% were vaccinated. 172 LNs were classified as normal, 30 as inflammatory, and 14 as metastatic using the combined classification. 152, 22, 29, 12, and 1 LNs were classified A-Node-RADS 1, 2, 3, 4, and 5, respectively. Hence, 174, 29, and 13 LNs were deemed benign, equivocal, and metastatic. The concordance between the classifications was very good (Cohen's k: 0.91, CI 0.86-0.95; p-value < 0.0001). A-Node-RADS can assist the classification of axillary LNs in melanoma patients who underwent 2-[18F]-FDG PET/CT and SARS-CoV-2 vaccination.

Impact of dose reduction and iterative reconstruction algorithm on the detectability of pulmonary nodules by artificial intelligence.

PURPOSE: The purpose of this study was to assess whether the performances of an automated software for lung nodule detection with computed tomography (CT) are affected by radiation dose and the use of iterative reconstruction algorithm. MATERIALS AND METHODS: A chest phantom (Multipurpose Chest Phantom N1; Kyoto Kagaku Co. Ltd, Kyoto, Japan) with 15 pulmonary nodules was scanned with a total of five CT protocol settings with up to 20-fold dose reduction. All CT examinations were reconstructed with iterative reconstruction algorithms ADMIRE 3 and ADMIRE 5 and were then analyzed for the presence of pulmonary nodules with a fully automated computer aided detection software system (InferReadTM CT Lung, Infervision), which is based on deep neural networks. RESULTS: The sensitivity of fully automated pulmonary nodule detection for ground-glass nodules at standard dose CT was greater (70.0%; 14/20; 95% CI: 51.6-88.4%) than at 10-fold and 20-fold dose reduction (30.0%; 6/20; 95% CI: 0.0%-62.5%). There were less false positive findings when ADMIRE 5 reconstruction was used (4.0 ± 2.8 [SD]; range: 2-6) instead of ADMIRE 3 reconstruction (25.0 ± 15.6 [SD]; range: 14-36). There was no difference in the sensitivity of detection of solid and subsolid nodules between standard dose (100%; 95% CI: 100-100%) and 10- and 20-fold reduced dose CT (92.5%; 95% CI: 83.8-100.0%). Image noise was significantly greater with ADMIRE 3 (81 ± 2 [SD] [range: 79-84]; 104 ± 3 [SD] [range: 101-107]; 114 ± 5 [SD] [range: 110-119]; 193 ± 10 [SD] [range: 183-203]; 220 ± 16 [SD] [range: 210-238]) compared to ADMIRE 5 (44 ± 2 [SD] [range: 42-46]; 60 ± 2 [SD] [range: 57-61]; 66 ± 1 [SD] [range: 65-67]; 103 ± 4 [SD] [range: 98-106]; 110 ± 1 [SD] [range: 109-111]), respectively in each of the five CT protocols. CONCLUSION: This phantom study suggests that dose reduction and iterative reconstruction settings have an impact on detectability of pulmonary nodules by artificial intelligence software and we therefore encourage adaption of dose levels and reconstruction methods prior to widespread implementation of fully automatic nodule detection software for lung cancer screening purposes.

Impact of Adaptive Statistical Iterative Reconstruction-V on Coronary Artery Calcium Scores Obtained From Low-Tube-Voltage Computed Tomography - A Patient Study.

OBJECTIVE: To evaluate the impact of adaptive statistical iterative reconstruction-V (ASIR-V) on the accuracy of ultra-low-dose coronary artery calcium (CAC) scoring. MATERIALS AND METHOD: One-hundred-and-three patients who underwent computed tomography (CT) for CAC scoring were prospectively included. All underwent standard scanning with 120-kilovolt-peak (kVp) and with 80- and 70-kVp tube voltage. ASiR-V was applied to the 80- and 70-kVp scans at different levels. The 120-kVp scans reconstructed with filtered back projection served as the standard of reference. Recently published novel kVp-adapted thresholds were used for calculation of CAC scores from 80- and 70-kVp scans and the resulting CAC scores were compared against the standard of reference. Patients were stratified into six CAC score risk categories: 0, 1-10, 11-100, 101-400, 401-1000, and >1000. RESULTS: Increasing levels of ASIR-V led to an increasing underestimation of CAC scores with bias ranging from -128 to -118 and from -205 to -198 for the 80- and 70-kVp scans, respectively, when compared with the standard of reference. Reconstruction with 20% and 40% ASIR-V for the 80- and 70-kVp scans, respectively, yielded noise levels comparable to the standard of reference. Nevertheless, a change in risk-class was observed in 29 (28.6%) and 46 (44.7%) patients, exclusively to a lower risk-class, when CAC scores were derived from these reconstructions. CONCLUSION: ASIR-V leads to noise reduction in CT scans acquired with low tube-voltages. However, ASIR-V introduces substantial inaccuracies and marked underestimation of ultra-low-dose CAC scoring as compared with standard-dose CAC scoring despite normalization of noise.