Task-based validation and application of a scanner-specific CT simulator using an anthropomorphic phantom.

BACKGROUND: Quantitative analysis of computed tomography (CT) images traditionally utilizes real patient data that can pose challenges with replicability, efficiency, and radiation exposure. Instead, virtual imaging trials (VITs) can overcome these hurdles through computer simulations of models of patients and imaging systems. DukeSim is a scanner-specific CT imaging simulator that has previously been validated with simple cylindrical phantoms, but not with anthropomorphic conditions and clinically relevant measurements. PURPOSE: To validate a scanner-specific CT simulator (DukeSim) for the assessment of lung imaging biomarkers under clinically relevant conditions across multiple scanners using an anthropomorphic chest phantom, and to demonstrate the utility of virtual trials by studying the effects or radiation dose and reconstruction kernels on the lung imaging quantifications. METHODS: An anthropomorphic chest phantom with customized tube inserts was imaged with two commercial scanners (Siemens Force and Siemens Flash) at 28 dose and reconstruction conditions. A computational version of the chest phantom was used with a scanner-specific CT simulator (DukeSim) to simulate virtual images corresponding to the settings of the real acquisitions. Lung imaging biomarkers were computed from both real and simulated CT images and quantitatively compared across all imaging conditions. The VIT framework was further utilized to investigate the effects of radiation dose (20-300 mAs) and reconstruction settings (Qr32f, Qr40f, and Qr69f reconstruction kernels using ADMIRE strength 3) on the accuracy of lung imaging biomarkers, compared against the ground-truth values modeled in the computational chest phantom. RESULTS: The simulated CT images matched closely the real images for both scanners and all imaging conditions qualitatively and quantitatively, with the average biomarker percent error of 3.51% (range 0.002%-18.91%). The VIT study showed that sharper reconstruction kernels had lower accuracy with errors in mean lung HU of 84-94 HU, lung volume of 797-3785 cm3 , and lung mass of -800 to 1751 g. Lower tube currents had the lower accuracy with errors in mean lung HU of 6-84 HU, lung volume of 66-3785 cm3 , and lung mass of 170-1751 g. Other imaging biomarkers were consistent under the studied reconstruction settings and tube currents. CONCLUSION: We comprehensively evaluated the realism of DukeSim in an anthropomorphic setup across a diverse range of imaging conditions. This study paves the way toward utilizing VITs more reliably for conducting medical imaging experiments that are not practical using actual patient images.

The diagnosis and management of ectopic pregnancy presenting to Mater Dei Hospital between June 2019 and June 2020.

The incidence of ectopic pregnancies has steadily increased over recent years and despite advances in treatment it still remains a major cause of maternal morbidity and mortality. The objective of this audit was to assess whether diagnosis and management is occurring as per international suggested guidance and practice. This study is a retrospective one using data collected from June 2019 to June 2020. All data were password protected and kept anonymous. No patient contact occurred. The standard cross referenced was the 'April 2019 NICE Guideline on the Management of Ectopic Pregnancy'. Thirty-one ectopic pregnancies occurred between June 2019 and June 2020. Twenty-nine underwent surgical management and two medical. Six out of the 29 surgically managed patients were managed incorrectly. Twenty-four of the surgical cases were managed laparoscopically. Presence of a foetal heart rate remained undocumented in 21 out of 31 of cases. The results highlight the ease of access to emergency gynaecological services at Malta's national hospital. However, this audit did highlight the discrepancy that can occur in examination in association with ectopic pregnancy. An inconsistency was noted in documentation. Additionally, a number of cases could have been offered and benefitted from different modes of management.Impact StatementWhat is already known on this subject? Ectopic pregnancy (EP) is an important cause of morbidity and mortality in mothers of childbearing age. The diagnostic method and appropriate management for EP has been extensively studied. Concrete- and evidence-based guidelines guide clinical management and improve morbidity and mortality. Local guidelines improve clinical outcome.What do the results of this study add? This study shows the impact of clinical outcome without a national guideline to guide management on a national level. Malta has one national hospital in which the local obstetrics and gynaecology department is run. The results of this study thus comprise of nationwide statistics on EP and its management. Ectopic pregnancies are managed without a local guideline in place. It also reflects the ease of access to health care in smaller countries.What are the implications of these findings for clinical practice and/or further research? The findings of this study have resulted in the production of a local guideline for the management of EP, as well as the introduction of a protocol for obtaining methotrexate for medical management. It has introduced new ultrasound machines and staff training to aid diagnostics. Further re-auditing will be carried out to analyse the impact a local guideline has on clinical practice at a national level.

Hb Valletta [beta87(F3)Thr-->Pro] and Hb Marseille/Long Island [beta2(NA2)His-->Pro; (-1)Met-(+1)Val-(+2)Pro-Leu], in a unique compound heterozygote with a normal hemoglobin phenotype.

This study refers to the quantitative hemoglobin (Hb) phenotype of a 19-year-old female with Hb Valletta [beta87(F3)Thr-->Pro] in association with Hb Marseille/Long Island [beta2(NA2)His-->Pro; (-1)Met-(+1)Val-(+2)Pro-Leu] and a normal Hb electrophoretogram. The data serve to alert investigators to the possibility that relatives with apparently normal Hb phenotypes may be transmitting mutant alleles and suggest methods for identification.