Background With the appearance of cadmium-zinc-telluride (CZT) cameras, dynamic myocardial perfusion imaging (MPI) has been introduced, but comparable data to other MPI modalities, such as quantitative coronary angiography (CAG) with fractional flow reserve (FFR) and positron emission tomography (PET), are lacking. This study aimed to evaluate the diagnostic accuracy of dynamic CZT single-photon emission tomography (SPECT) in coronary artery disease compared to quantitative CAG, FFR, and PET as reference. Materials and Methods Different databases were screened for eligible citations performing dynamic CZT-SPECT against CAG, FFR, or PET. PubMed, OvidSP (Medline), Web of Science, the Cochrane Library, and EMBASE were searched on the 5th of July 2020. Studies had to meet the following pre-established inclusion criteria: randomized controlled trials, retrospective trails or observational studies relevant for the diagnosis of coronary artery disease, and performing CZT-SPECT and within half a year the methodological references. Studies which considered coronary stenosis between 50% and 70% as significant based only on CAG were excluded. Data extracted were sensitivity, specificity, likelihood ratios, and diagnostic odds ratios. Quality was assessed with QUADAS-2 and statistical analysis was performed using a bivariate model. Results Based on our criteria, a total of 9 studies containing 421 patients were included. For the assessment of CZT-SPECT, the diagnostic value pooled analysis with a bivariate model was calculated and yielded a sensitivity of 0.79 (% CI 0.73 to 0.85) and a specificity of 0.85 (95% CI 0.74 to 0.92). Diagnostic odds ratio (DOR) was 17.82 (95% CI 8.80 to 36.08, P < 0.001). Positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 3.86 (95% CI 2.76 to 5.38, P < 0.001) and 0.21 (95% CI 0.13 to 0.33, P < 0.001), respectively. Conclusion Based on the results of the current systematic review and meta-analysis, dynamic CZT-SPECT MPI demonstrated a good sensitivity and specificity to diagnose CAD as compared to the gold standards. However, due to the heterogeneity of the methodologies between the CZT-SPECT MPI studies and the relatively small number of included studies, it warrants further well-defined study protocols.

Imaging water pathways in the human body provides an excellent way of measuring accurately the blood flow directed to different organs. This makes it a powerful diagnostic tool for a wide range of diseases that are related to perfusion and oxygenation. Although water PET has a long history, its true potential has not made it into regular clinical practice. The article highlights the potential of water PET in molecular imaging and suggests its prospective role in becoming an essential tool for the 21st century precision medicine in different domains ranging from preclinical to clinical research and practice. The recent technical advances in high-sensitivity PET imaging can play a key accelerating role in empowering this technique, though there are still several challenges to overcome.

Introduction: Establishing the influence of long-term, gender-affirming hormonal treatment (HT) on bone mineral density (BMD) in transgender individuals is important to improve the therapeutic guidelines for these individuals. Aim: To examine the effect of long-term HT and gonadectomy on BMD in transgender individuals. Methods: 68 transwomen and 43 transmen treated with HT who had undergone gonadectomy participated in this study. Dual-energy x-ray absorptiometry (DXA) scans were performed to measure BMD at the lumbar spine and total hip. Laboratory values related to sex hormones were collected within 3 months of performing the DXA scan and analyzed. Main Outcome Measure: BMD and levels of sex hormones in transwomen and transmen. Results: In transwomen, the mean BMD values at the lumbar spine and total hip at the first DXA scan were, respectively, 0.99 ± 0.15 g/cm2 (n = 68) and 0.94 ± 0.28 g/cm2 (n = 65). In transmen, the mean BMD values at the lumbar spine and total hip at the first DXA scan were, respectively, 1.08 ± 0.16 g/cm2 (n = 43) and 1.01 ± 0.18 g/cm2 (n = 43). A significant decrease in total hip BMD was found in both transwomen and transmen after 15 years of HT compared with 10 years of HT (P = .02). Conclusion: In both transwomen and transmen, a decrease was observed in total hip bone mineral density after 15 years of HT compared to the first 10 years of HT.

In computed tomography, coronary artery calcium (CAC) scores are influenced by image reconstruction. The effect of a newly introduced deep learning-based reconstruction (DLR) on CAC scoring in relation to other algorithms is unknown. The aim of this study was to evaluate the effect of four generations of image reconstruction techniques (filtered back projection (FBP), hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), and DLR) on CAC detectability, quantification, and risk classification. First, CAC detectability was assessed with a dedicated static phantom containing 100 small calcifications varying in size and density. Second, CAC quantification was assessed with a dynamic coronary phantom with velocities equivalent to heart rates of 60–75 bpm. Both phantoms were scanned and reconstructed with four techniques. Last, scans of fifty patients were included and the Agatston calcium score was calculated for all four reconstruction techniques. FBP was used as a reference. In the phantom studies, all reconstruction techniques resulted in less detected small calcifications, up to 22%. No clinically relevant quantification changes occurred with different reconstruction techniques (less than 10%). In the patient study, the cardiovascular risk classification resulted, for all reconstruction techniques, in excellent agreement with the reference (κ = 0.96–0.97). However, MBIR resulted in significantly higher Agatston scores (61 (5.5–435.0) vs. 81.5 (9.25–435.0); p < 0.001) and 6% reclassification rate. In conclusion, HIR and DLR reconstructed scans resulted in similar Agatston scores with excellent agreement and low-risk reclassification rate compared with routine reconstructed scans (FBP). However, caution should be taken with low Agatston scores, as based on phantom study, detectability of small calcifications varies with the used reconstruction algorithm, especially with MBIR and DLR.

The study aimed, firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low-dose computed tomography (CT) (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan and, secondly, to assess the added value of CAC scored from LDCT scans acquired during [¹⁵O]-water-positron emission tomography (PET) myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE). Five hundred seventy-two consecutive patients with suspected coronary artery disease, who underwent [¹⁵O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient’s scan was assigned to one out of five cardiovascular risk groups (0, 1–100, 101–400, 401–1000, >1000), and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, and unstable angina. The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 [95% confidence interval (CI): 0.62–0.70] and 0.58 (95% CI: 0.53–0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC > 100 and CAC > 400, respectively, were at increased risk of MACE, independently of ischaemic information from the [¹⁵O]-water-PET scan. There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE.

Background: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans. Methods: In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm³, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CAC_CCTA and CAC_CSCT scoring was measured using Cohen weighted linear κ with 95% CI. Results: For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CAC_CCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CAC_CCTA was not significantly different from CAC_CSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853). Conclusion: In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial. Clinical relevance statement: Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice. Key Points: Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates. Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed. Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.