Long-term trends in total administered radiation dose from brain [F]FDG-PET in children with drug-resistant epilepsy.

Purpose: To assess the trends in administered 2-[F]fluoro-2-deoxy-D-glucose ([F]FDG) doses, computed tomography (CT) radiation doses, and image quality over the last 15 years in children with drug-resistant epilepsy (DRE) undergoing hybrid positron emission tomography (PET) brain scans.

Methods: We retrospectively analyzed data from children with DRE who had [F]FDG-PET/CT or magnetic resonance scans for presurgical evaluation between 2005 and 2021. We evaluated changes in injected [F]FDG doses, administered activity per body weight, CT dose index volume (CTDIvol), and dose length product (DLP).

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.

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.

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-[F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[F]-FDG PET/CT) between February and April 2021 were included in this retrospective study. Primary melanoma site, vaccination status, injection site, and 2-[F]-FDG PET/CT were used to classify axillary LNs into normal, inflammatory, and metastatic (combined classification).

A third of the radiotracer dose: two decades of progress in pediatric [F]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 cm volume of interest as an indicator for objective image quality.

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

Objectives: To evaluate the evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[F]fluoro-2-deoxy-D-glucose (2-[F]FDG) PET/CT between 2007 and 2021.

Methods And Materials: Data from all pediatric patients aged 0-18 years who underwent hybrid 2-[F]FDG PET/CT of the body between January 2007 and May 2021 were reviewed. Demographic and imaging parameters were collected.

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: [F]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).

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".

Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT.

Our aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled: 50 patients with Agatston scores ≥ 1000 (high CACS group), 50 patients with Agatston scores < 1000 (negative control group). All patients underwent oncological 18F-FDG-PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months.

Diagnostic Value of Fully Automated Artificial Intelligence Powered Coronary Artery Calcium Scoring from 18F-FDG PET/CT.

Objectives: The objective of this study was to assess the feasibility and accuracy of a fully automated artificial intelligence (AI) powered coronary artery calcium scoring (CACS) method on ungated CT in oncologic patients undergoing 18F-FDG PET/CT.

Methods: A total of 100 oncologic patients examined between 2007 and 2015 were retrospectively included. All patients underwent 18F-FDG PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months.

Assessment of Artificial Intelligence in Echocardiography Diagnostics in Differentiating Takotsubo Syndrome From Myocardial Infarction.

Importance: Machine learning algorithms enable the automatic classification of cardiovascular diseases based on raw cardiac ultrasound imaging data. However, the utility of machine learning in distinguishing between takotsubo syndrome (TTS) and acute myocardial infarction (AMI) has not been studied.

Objectives: To assess the utility of machine learning systems for automatic discrimination of TTS and AMI.

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.

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.

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).

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.

Pneumonia Detection in Chest X-Ray Dose-Equivalent CT: Impact of Dose Reduction on Detectability by Artificial Intelligence.

Rationale And Objectives: There has been a significant increase of immunocompromised patients in recent years due to new treatment modalities for previously fatal diseases. This comes at the cost of an elevated risk for infectious diseases, most notably pathogens affecting the respiratory tract. Because early diagnosis and treatment of pneumonia can help reducing morbidity and mortality, we assessed the performance of a deep neural network in the detection of pulmonary infection in chest X-ray dose-equivalent computed tomography (CT).

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.

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 F-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 F-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.

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.

Association between beta-adrenoceptor antagonist-induced sympathicolysis and severity of coronary artery disease as assessed by coronary computed tomography angiography (CCTA).

Enhanced sympathetic nervous system activity is associated with increased mortality in many cardiac conditions including heart failure and coronary artery disease (CAD). To ensure adequate image quality of coronary CT angiography (CCTA), pre-scan β-adrenergic blockers (BB) are routinely administered. It is currently unknown whether sensitivity to sympathicolytic compounds is associated with severity of CAD.