Proposal to utilize simplified Swensen protocol in diagnosis of isolated pulmonary nodule

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.

Dynamic contrast-enhanced computed tomography for the diagnosis of solitary pulmonary nodules: a systematic review and meta-analysis

INTRODUCTION

A systematic review and meta-analysis were performed to determine the diagnostic performance of dynamic contrast-enhanced computed tomography (DCE-CT) for the differentiation between malignant and benign pulmonary nodules.

METHODS

Ovid MEDLINE and EMBASE were searched for studies published up to October 2018 on the diagnostic accuracy of DCE-CT for the characterisation of pulmonary nodules. For the index test, studies with a minimum of a pre- and post-contrast computed tomography scan were evaluated. Studies with a reference standard of biopsy for malignancy, and biopsy or 2-year follow-up for benign disease were included. Study bias was assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). The sensitivities, specificities, and diagnostic odds ratios were determined along with 95% confidence intervals (CIs) using a bivariate random effects model.

RESULTS

Twenty-three studies were included, including 2397 study participants with 2514 nodules of which 55.3% were malignant (1389/2514). The pooled accuracy results were sensitivity 94.8% (95% CI 91.5; 96.9), specificity 75.5% (69.4; 80.6), and diagnostic odds ratio 56.6 (24.2-88.9). QUADAS 2 assessment showed intermediate/high risk of bias in a large proportion of the studies (52-78% across the domains). No difference was present in sensitivity or specificity between subgroups when studies were split based on CT technique, sample size, nodule size, or publication date.

CONCLUSION

DCE-CT has a high diagnostic accuracy for the diagnosis of pulmonary nodules although study quality was indeterminate in a large number of cases.

KEY POINTS

• The pooled accuracy results were sensitivity 95.1% and specificity 73.8% although individual studies showed wide ranges of values. • This is comparable to the results of previous meta-analyses of PET/CT (positron emission tomography/computed tomography) diagnostic accuracy for the diagnosis of solitary pulmonary nodules. • Robust direct comparative accuracy and cost-effectiveness studies are warranted to determine the optimal use of DCE-CT and PET/CT in the diagnosis of SPNs.

CT Densitometry and Morphology of Radiofrequency-Ablated Stage IA Non-Small Cell Lung Cancer: Results from the American College of Surgeons Oncology Group Z4033 (Alliance) Trial

PURPOSE

To evaluate tumor and ablation zone morphology and densitometry related to tumor recurrence in participants with Stage IA non-small cell lung cancer undergoing radiofrequency ablation in a prospective, multicenter trial.

MATERIALS AND METHODS

Forty-five participants (median 76 years old; 25 women; 20 men) from 16 sites were followed for 2 years (December 2006 to November 2010) with computed tomography (CT) densitometry. Imaging findings before and after ablation were recorded, including maximum CT attenuation (in Hounsfield units) at precontrast and 45-, 90-, 180-, and 300-s postcontrast.

RESULTS

Every 1-cm increase in the largest axial diameter of the ablation zone at 3-months' follow-up compared to the index tumor reduced the odds of 2-year recurrence by 52% (P = .02). A 1-cm difference performed the best (sensitivity, 0.56; specificity, 0.93; positive likelihood ratio of 8). CT densitometry precontrast and at 45 seconds showed significantly different enhancement patterns in a comparison among pretreated lung cancer (delta = +61.2 HU), tumor recurrence (delta = +57 HU), and treated tumor/ablation zone (delta [change in attenuation] = +16.9 HU), (P < .0001). Densitometry from 45 to 300 s was also different among pretreated tumor (delta = -6.8 HU), recurrence (delta = -11.2 HU), and treated tumor (delta = +12.1 HU; P = .01). Untreated and residual tumor demonstrated washout, whereas treated tumor demonstrated increased attenuation.

CONCLUSIONS

An ablation zone ≥1 cm larger than the initial tumor, based on 3-month follow-up imaging, is recommended to decrease odds of recurrence. CT densitometry can delineate tumor versus treatment zones.