Comparative accuracy and cost-effectiveness of dynamic contrast-enhanced CT and positron emission tomography in the characterisation of solitary pulmonary nodules.

INTRODUCTION: Dynamic contrast-enhanced CT (DCE-CT) and positron emission tomography/CT (PET/CT) have a high reported accuracy for the diagnosis of malignancy in solitary pulmonary nodules (SPNs). The aim of this study was to compare the accuracy and cost-effectiveness of these. METHODS: In this prospective multicentre trial, 380 participants with an SPN (8-30 mm) and no recent history of malignancy underwent DCE-CT and PET/CT. All patients underwent either biopsy with histological diagnosis or completed CT follow-up. Primary outcome measures were sensitivity, specificity and overall diagnostic accuracy for PET/CT and DCE-CT. Costs and cost-effectiveness were estimated from a healthcare provider perspective using a decision-model. RESULTS: 312 participants (47% female, 68.1±9.0 years) completed the study, with 61% rate of malignancy at 2 years. The sensitivity, specificity, positive predictive value and negative predictive values for DCE-CT were 95.3% (95% CI 91.3 to 97.5), 29.8% (95% CI 22.3 to 38.4), 68.2% (95% CI 62.4% to 73.5%) and 80.0% (95% CI 66.2 to 89.1), respectively, and for PET/CT were 79.1% (95% CI 72.7 to 84.2), 81.8% (95% CI 74.0 to 87.7), 87.3% (95% CI 81.5 to 91.5) and 71.2% (95% CI 63.2 to 78.1). The area under the receiver operator characteristic curve (AUROC) for DCE-CT and PET/CT was 0.62 (95% CI 0.58 to 0.67) and 0.80 (95% CI 0.76 to 0.85), respectively (p<0.001). Combined results significantly increased diagnostic accuracy over PET/CT alone (AUROC=0.90 (95% CI 0.86 to 0.93), p<0.001). DCE-CT was preferred when the willingness to pay per incremental cost per correctly treated malignancy was below £9000. Above £15 500 a combined approach was preferred. CONCLUSIONS: PET/CT has a superior diagnostic accuracy to DCE-CT for the diagnosis of SPNs. Combining both techniques improves the diagnostic accuracy over either test alone and could be cost-effective. TRIAL REGISTRATION NUMBER: NCT02013063.

Diagnosis of Pulmonary Hypertension with Cardiac MRI: Derivation and Validation of Regression Models.

Purpose To derive and test multiparametric cardiac MRI models for the diagnosis of pulmonary hypertension (PH). Materials and Methods Images and patient data from consecutive patients suspected of having PH who underwent cardiac MRI and right-sided heart catheterization (RHC) between 2012 and 2016 were retrospectively reviewed. Of 2437 MR images identified, 603 fit the inclusion criteria. The mean patient age was 61 years (range, 18-88 years; mean age of women, 60 years [range, 18-84 years]; mean age of men, 62 years [range, 22-88 years]). In the first 300 patients (derivation cohort), cardiac MRI metrics that showed correlation with mean pulmonary arterial pressure (mPAP) were used to create a regression algorithm. The performance of the model was assessed in the 303-patient validation cohort by using receiver operating characteristic (ROC) and χ2 analysis. Results In the derivation cohort, cardiac MRI mPAP model 1 (right ventricle and black blood) was defined as follows: -179 + loge interventricular septal angle × 42.7 + log10 ventricular mass index (right ventricular mass/left ventricular mass) × 7.57 + black blood slow flow score × 3.39. In the validation cohort, cardiac MRI mPAP model 1 had strong agreement with RHC-measured mPAP, an intraclass coefficient of 0.78, and high diagnostic accuracy (area under the ROC curve = 0.95; 95% confidence interval [CI]: 0.93, 0.98). The threshold of at least 25 mm Hg had a sensitivity of 93% (95% CI: 89%, 96%), specificity of 79% (95% CI: 65%, 89%), positive predictive value of 96% (95% CI: 93%, 98%), and negative predictive value of 67% (95% CI: 53%, 78%) in the validation cohort. A second model, cardiac MRI mPAP model 2 (right ventricle pulmonary artery), which excludes the black blood flow score, had equivalent diagnostic accuracy (ROC difference: P = .24). Conclusion Multiparametric cardiac MRI models have high diagnostic accuracy in patients suspected of having pulmonary hypertension. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Colletti in this issue.

A review of pathologies associated with high T1W signal intensity in the basal ganglia on Magnetic Resonance Imaging.

With several functions and a fundamental influence over cognition and motor functions, the basal ganglia are the cohesive centre of the brain. There are several conditions which affect the basal ganglia and these have various clinical and radiological manifestations. Nevertheless, on magnetic resonance imaging there is a limited differential diagnosis for those conditions presenting with T1 weighted spin echo hyperintensity within the central nervous system in general and the basal ganglia in particular. The aim of our review is to explore some of these basal ganglia pathologies and provide image illustrations.

Fully automatic cardiac four chamber and great vessel segmentation on CT pulmonary angiography using deep learning.

Introduction: Computed tomography pulmonary angiography (CTPA) is an essential test in the work-up of suspected pulmonary vascular disease including pulmonary hypertension and pulmonary embolism. Cardiac and great vessel assessments on CTPA are based on visual assessment and manual measurements which are known to have poor reproducibility. The primary aim of this study was to develop an automated whole heart segmentation (four chamber and great vessels) model for CTPA. Methods: A nine structure semantic segmentation model of the heart and great vessels was developed using 200 patients (80/20/100 training/validation/internal testing) with testing in 20 external patients. Ground truth segmentations were performed by consultant cardiothoracic radiologists. Failure analysis was conducted in 1,333 patients with mixed pulmonary vascular disease. Segmentation was achieved using deep learning via a convolutional neural network. Volumetric imaging biomarkers were correlated with invasive haemodynamics in the test cohort. Results: Dice similarity coefficients (DSC) for segmented structures were in the range 0.58-0.93 for both the internal and external test cohorts. The left and right ventricle myocardium segmentations had lower DSC of 0.83 and 0.58 respectively while all other structures had DSC >0.89 in the internal test cohort and >0.87 in the external test cohort. Interobserver comparison found that the left and right ventricle myocardium segmentations showed the most variation between observers: mean DSC (range) of 0.795 (0.785-0.801) and 0.520 (0.482-0.542) respectively. Right ventricle myocardial volume had strong correlation with mean pulmonary artery pressure (Spearman's correlation coefficient = 0.7). The volume of segmented cardiac structures by deep learning had higher or equivalent correlation with invasive haemodynamics than by manual segmentations. The model demonstrated good generalisability to different vendors and hospitals with similar performance in the external test cohort. The failure rates in mixed pulmonary vascular disease were low (<3.9%) indicating good generalisability of the model to different diseases. Conclusion: Fully automated segmentation of the four cardiac chambers and great vessels has been achieved in CTPA with high accuracy and low rates of failure. DL volumetric biomarkers can potentially improve CTPA cardiac assessment and invasive haemodynamic prediction.

Dynamic contrast-enhanced CT compared with positron emission tomography CT to characterise solitary pulmonary nodules: the SPUtNIk diagnostic accuracy study and economic modelling.

BACKGROUND: Current pathways recommend positron emission tomography-computerised tomography for the characterisation of solitary pulmonary nodules. Dynamic contrast-enhanced computerised tomography may be a more cost-effective approach. OBJECTIVES: To determine the diagnostic performances of dynamic contrast-enhanced computerised tomography and positron emission tomography-computerised tomography in the NHS for solitary pulmonary nodules. Systematic reviews and a health economic evaluation contributed to the decision-analytic modelling to assess the likely costs and health outcomes resulting from incorporation of dynamic contrast-enhanced computerised tomography into management strategies. DESIGN: Multicentre comparative accuracy trial. SETTING: Secondary or tertiary outpatient settings at 16 hospitals in the UK. PARTICIPANTS: Participants with solitary pulmonary nodules of ≥ 8 mm and of ≤ 30 mm in size with no malignancy in the previous 2 years were included. INTERVENTIONS: Baseline positron emission tomography-computerised tomography and dynamic contrast-enhanced computer tomography with 2 years' follow-up. MAIN OUTCOME MEASURES: Primary outcome measures were sensitivity, specificity and diagnostic accuracy for positron emission tomography-computerised tomography and dynamic contrast-enhanced computerised tomography. Incremental cost-effectiveness ratios compared management strategies that used dynamic contrast-enhanced computerised tomography with management strategies that did not use dynamic contrast-enhanced computerised tomography. RESULTS: A total of 380 patients were recruited (median age 69 years). Of 312 patients with matched dynamic contrast-enhanced computer tomography and positron emission tomography-computerised tomography examinations, 191 (61%) were cancer patients. The sensitivity, specificity and diagnostic accuracy for positron emission tomography-computerised tomography and dynamic contrast-enhanced computer tomography were 72.8% (95% confidence interval 66.1% to 78.6%), 81.8% (95% confidence interval 74.0% to 87.7%), 76.3% (95% confidence interval 71.3% to 80.7%) and 95.3% (95% confidence interval 91.3% to 97.5%), 29.8% (95% confidence interval 22.3% to 38.4%) and 69.9% (95% confidence interval 64.6% to 74.7%), respectively. Exploratory modelling showed that maximum standardised uptake values had the best diagnostic accuracy, with an area under the curve of 0.87, which increased to 0.90 if combined with dynamic contrast-enhanced computerised tomography peak enhancement. The economic analysis showed that, over 24 months, dynamic contrast-enhanced computerised tomography was less costly (£3305, 95% confidence interval £2952 to £3746) than positron emission tomography-computerised tomography (£4013, 95% confidence interval £3673 to £4498) or a strategy combining the two tests (£4058, 95% confidence interval £3702 to £4547). Positron emission tomography-computerised tomography led to more patients with malignant nodules being correctly managed, 0.44 on average (95% confidence interval 0.39 to 0.49), compared with 0.40 (95% confidence interval 0.35 to 0.45); using both tests further increased this (0.47, 95% confidence interval 0.42 to 0.51). LIMITATIONS: The high prevalence of malignancy in nodules observed in this trial, compared with that observed in nodules identified within screening programmes, limits the generalisation of the current results to nodules identified by screening. CONCLUSIONS: Findings from this research indicate that positron emission tomography-computerised tomography is more accurate than dynamic contrast-enhanced computerised tomography for the characterisation of solitary pulmonary nodules. A combination of maximum standardised uptake value and peak enhancement had the highest accuracy with a small increase in costs. Findings from this research also indicate that a combined positron emission tomography-dynamic contrast-enhanced computerised tomography approach with a slightly higher willingness to pay to avoid missing small cancers or to avoid a 'watch and wait' policy may be an approach to consider. FUTURE WORK: Integration of the dynamic contrast-enhanced component into the positron emission tomography-computerised tomography examination and the feasibility of dynamic contrast-enhanced computerised tomography at lung screening for the characterisation of solitary pulmonary nodules should be explored, together with a lower radiation dose protocol. STUDY REGISTRATION: This study is registered as PROSPERO CRD42018112215 and CRD42019124299, and the trial is registered as ISRCTN30784948 and ClinicalTrials.gov NCT02013063. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 17. See the NIHR Journals Library website for further project information.

A nodule found on a lung scan can cause concern as it may be a sign of cancer. Finding lung cancer nodules when they are small (i.e. < 3 cm) is very important. Most nodules are not cancerous. Computerised tomography (cross-sectional images created from multiple X-rays) and positron emission tomography­computerised tomography (a technique that uses a radioactive tracer combined with computerised tomography) are used to see whether or not a nodule is cancerous; although they perform well, improvements are required. This study compared dynamic contrast-enhanced computerised tomography with positron emission tomography­computerised tomography scans to find out which test is best. Dynamic contrast-enhanced computerised tomography involves injection of a special dye into the bloodstream, followed by repeated scans of the nodule over several minutes. We assessed the costs to the NHS of undertaking the different scans, relative to their benefits, to judge which option was the best value for money. We recruited 380 patients from 16 hospitals across England and Scotland, of whom 312 had both dynamic contrast-enhanced computerised tomography and positron emission tomography­computerised tomography scans. We found that current positron emission tomography­computerised tomography is more accurate, providing a correct diagnosis in 76% of cases, than the new dynamic contrast-enhanced computerised tomography, which provides a correct diagnosis in 70% of cases. Although dynamic contrast-enhanced computerised tomography cannot replace positron emission tomography­computerised tomography, it may represent good-value use of NHS resources, especially if it is performed before positron emission tomography­computerised tomography and they are used in combination. Although more research is required, it may be possible in the future to perform dynamic contrast-enhanced computerised tomography at the same time as positron emission tomography­computerised tomography in patients with suspected lung cancer or if a lung nodule is found on a lung screening programme at the time of the computerised tomography examination. This may reduce the need for some people to have positron emission tomography­computerised tomography.

IodiNe Subtraction mapping in the diagnosis of Pulmonary chronIc thRomboEmbolic disease (INSPIRE): Rationale and methodology of a cross-sectional observational diagnostic study.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a severe but treatable disease that is commonly underdiagnosed. Computed tomography lung subtraction iodine mapping (CT-LSIM) in addition to standard CT pulmonary angiography (CTPA) may improve the evaluation of suspected chronic pulmonary embolism and improve the diagnostic pick up rate. We aim to recruit 100 patients suspected of having CTEPH and perform CT-LSIM scans in addition to the current gold standard test of nuclear medicine test (lung single photon emission computed tomography (SPECT) imaging) as a pilot study which will contribute to and inform the definitive trial. The diagnostic accuracy of CT-LSIM and lung SPECT will be compared. The primary outcome of the full definitive study is non-inferiority of CT-LSIM versus lung SPECT imaging.

A Systematic Review of Right Ventricular Diastolic Assessment by 4D Flow CMR.

BACKGROUND: Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) is a noninvasive novel imaging technology that can be used to visualise and assess right ventricular function. The aim of this systematic review is to summarise the literature available on 4D flow CMR methods used to determine right ventricular diastolic function. METHODS: A systematic review of current literature was carried out to ascertain what is known about right ventricular assessment by quantification of 4D flow CMR. Structured searches were carried out on Medline and EMBASE in December 2018. PG and NB screened the titles and abstracts for relevance. RESULTS: Of the 20 articles screened, 5 studies met eligibility for systematic review. After a further search on pubmed 1 more relevant article was found and added to the review. CONCLUSIONS: These proposed methods using 4D flow CMR can quantify right ventricular diastolic assessment. The evidence gathered is mainly observational, featuring single-centred studies. Larger, multicentre studies are required to validate the proposed techniques, evaluate reproducibility, and investigate the clinical applicability that 4D flow CMR offers compared to standard practices. PROSPERO registration number is CRD42019121492.