Cost-Effectiveness Analysis of 68Ga-DOTATATE PET/MRI in Radiotherapy Planning in Patients with Intermediate-Risk Meningioma

BACKGROUND AND PURPOSE

While contrast-enhanced MR imaging is the criterion standard in meningioma diagnosis and treatment response assessment, gallium 68Ga-DOTATATE PET/MR imaging has increasingly demonstrated utility in meningioma diagnosis and management. Integrating 68Ga-DOTATATE PET/MR imaging in postsurgical radiation planning reduces the planning target volume and organ-at-risk dose. However, 68Ga-DOTATATE PET/MR imaging is not widely implemented in clinical practice due to higher perceived costs. Our study analyzes the cost-effectiveness of 68Ga-DOTATATE PET/MR imaging for postresection radiation therapy planning in patients with intermediate-risk meningioma.

MATERIALS AND METHODS

We developed a decision-analytical model based on both recommended guidelines on meningioma management and our institutional experience. Markov models were implemented to estimate quality-adjusted life-years (QALY). Cost-effectiveness analyses with willingness-to-pay thresholds of $50,000/QALY and $100,000/QALY were performed from a societal perspective. Sensitivity analyses were conducted to validate the results. Model input values were based on published literature.

RESULTS

The cost-effectiveness results demonstrated that 68Ga-DOTATATE PET/MR imaging yields higher QALY (5.47 versus 5.05) at a higher cost ($404,260 versus $395,535) compared with MR imaging alone. The incremental cost-effectiveness ratio analysis determined that 68Ga-DOTATATE PET/MR imaging is cost-effective at a willingness to pay of $50,000/QALY and $100,000/QALY. Furthermore, sensitivity analyses showed that 68Ga-DOTATATE PET/MR imaging is cost-effective at $50,000/QALY ($100,000/QALY) for specificity and sensitivity values above 76% (58%) and 53% (44%), respectively.

CONCLUSIONS

68Ga-DOTATATE PET/MR imaging as an adjunct imaging technique is cost-effective in postoperative treatment planning in patients with meningiomas. Most important, the model results show that the sensitivity and specificity cost-effective thresholds of 68Ga-DOTATATE PET/MR imaging could be attained in clinical practice.

Clinical risk factors and CT imaging features of carotid atherosclerotic plaques as predictors of new incident carotid ischemic stroke: a retrospective cohort study

BACKGROUND AND PURPOSE

Parameters other than luminal narrowing are needed to predict the risk of stroke more reliably, particularly in patients with <70% stenosis. The goal of our study was to identify clinical risk factors and CT features of carotid atherosclerotic plaques, in a retrospective cohort of patients free of stroke at baseline, that are independent predictors of incident stroke on follow-up.

MATERIALS AND METHODS

We identified a retrospective cohort of patients admitted to our emergency department with suspected stroke between 2001-2007 who underwent a stroke work-up including a CTA of the carotid arteries that was subsequently negative for acute stroke. All patients also had to receive a follow-up brain study at least 2 weeks later. From a random sample, we reviewed charts and imaging studies of patients with subsequent new stroke on follow-up as well as those who remained stroke-free. All patients were classified either as "new carotid infarct patients" or "no-new carotid infarct patients" based on the Causative Classification for Stroke. Independently, the baseline CTA studies were processed using a custom, CT-based automated computer classifier algorithm that quantitatively assesses a set of carotid CT features (wall thickness, plaque ulcerations, fibrous cap thickness, lipid-rich necrotic core, and calcifications). Univariate and multivariate statistical analyses were used to identify any significant differences in CT features between the patient groups in the sample. Subsequent ROC analysis allowed comparison to the classic NASCET stenosis rule in identifying patients with incident stroke on follow-up.

RESULTS

We identified a total of 315 patients without a new carotid stroke between baseline and follow-up, and 14 with a new carotid stroke between baseline and follow-up, creating the main comparison groups for the study. Statistical analysis showed age and use of antihypertensive drugs to be the most significant clinical variables, and maximal carotid wall thickness was the most relevant imaging variable. The use of age ≥ 75 years, antihypertensive medication use, and a maximal carotid wall thickness of at least 4 mm was able to successfully identify 10 of the 14 patients who developed a new incident infarct on follow-up. ROC analysis showed an area under the ROC curve of 0.706 for prediction of new stroke with this new model.

CONCLUSIONS

Our new paradigm of using age ≥ 75 years, history of hypertension, and carotid maximal wall thickness of >4 mm identified most of the patients with subsequent new carotid stroke in our study. It is simple and may help clinicians choose the patients at greatest risk of developing a carotid infarct, warranting validation with a prospective observational study.