PriMa: A low-cost, modular, open hardware, and 3D-printed fMRI manipulandum

Motor actions in fMRI settings require specialized hardware to monitor, record, and control the subjects behavior. Commercially available options for such behavior tracking or control are very restricted and costly. We present a novel grasp manipulandum in a modular design, consisting of MRI-compatible, 3D printable buttons and a chassis for mounting. Button presses are detected by the interruption of an optical fiber path, which is digitized by a photodiode and subsequent signal amplification and thresholding. Two feedback devices (manipulanda) are constructed, one for macaques (Macaca mulatta) and one for human use. Both devices have been tested in their specific experimental setting and possible improvements are reported. Design files are shared under an open hardware license.

Headache and Neuroimaging: Why We Continue to Do It

The appropriate imaging of patients with headache presents a number of important and vexing challenges for clinicians. Despite a number of guidelines and studies demonstrating a lack of cost-effectiveness, clinicians continue to image patients with chronic nonfocal headaches, and the trend toward imaging is increasing. The reasons are complex and include the fear of missing a clinically significant lesion and litigation, habitual and standard of care practices, lack of tort reform, regulatory penalties and potential impact on one's professional reputation, patient pressures, and financial motivation. Regulatory and legislative reforms are needed to encourage best practices without fear of professional sanctions when following the guidelines. The value of negative findings on imaging tests requires better understanding because they appear to provide some measure of societal value. Clinical decision support tools and machine intelligence may offer additional guidance and improve quality and cost-efficient management of this challenging patient population.

Impact of early headache neuroimaging on time to malignant brain tumor diagnosis: A retrospective cohort study

BACKGROUND

Neuroimaging for headaches is both common and costly. While the costs are well quantified, little is known about the benefit in terms of diagnosing pathology. Our objective was to determine the role of early neuroimaging in the identification of malignant brain tumors in individuals presenting to healthcare providers with headaches.

METHODS

This was a retrospective cohort study using administrative claims data (2001-2014) from a US insurer. Individuals were included if they had an outpatient visit for headaches and excluded for prior headache visits, other neurologic conditions, neuroimaging within the previous year, and cancer. The exposure was early neuroimaging, defined as neuroimaging within 30 days of the first headache visit. A propensity score-matched group that did not undergo early neuroimaging was then created. The primary outcome was frequency of malignant brain tumor diagnoses and median time to diagnosis within the first year after the incident headache visit. The secondary outcome was frequency of incidental findings.

RESULTS

22.2% of 180,623 individuals had early neuroimaging. In the following year, malignant brain tumors were found in 0.28% (0.23-0.34%) of the early neuroimaging group and 0.04% (0.02-0.06%) of the referent group (P<0.001). Median time to diagnosis in the early neuroimaging group was 8 (3-19) days versus 72 (39-189) days for the referent group (P<0.001). Likely incidental findings were discovered in 3.17% (3.00-3.34%) of the early neuroimaging group and 0.66% (0.58-0.74%) of the referent group (P<0.001).

CONCLUSIONS

Malignant brain tumors in individuals presenting with an incident headache diagnosis are rare and early neuroimaging leads to a small reduction in the time to diagnosis.

Modeling the Cost Effectiveness of Neuroimaging-Based Treatment of Acute Wake-Up Stroke

BACKGROUND

Thrombolytic treatment (tissue-type plasminogen activator [tPA]) is only recommended for acute ischemic stroke patients with stroke onset time <4.5 hours. tPA is not recommended when stroke onset time is unknown. Diffusion-weighted MRI (DWI) and fluid attenuated inversion recovery (FLAIR) MRI mismatch information has been found to approximate stroke onset time with some accuracy. Therefore, we developed a micro-simulation model to project health outcomes and costs of MRI-based treatment decisions versus no treatment for acute wake-up stroke patients.

METHODS AND FINDINGS

The model assigned simulated patients a true stroke onset time from a specified probability distribution. DWI-FLAIR mismatch estimated stroke onset <4.5 hours with sensitivity and specificity of 0.62 and 0.78, respectively. Modified Rankin Scale (mRS) scores reflected tPA treatment effectiveness accounting for patients' true stroke onset time. Discounted lifetime costs and benefits (quality-adjusted life years [QALYs]) were projected for each strategy. Incremental cost-effectiveness ratios (ICERs) were calculated for the MRI-based strategy in base-case and sensitivity analyses. With no treatment, 45.1% of simulated patients experienced a good stroke outcome (mRS score 0-1). Under the MRI-based strategy, in which 17.0% of all patients received tPA despite stroke onset times >4.5 hours, 46.3% experienced a good stroke outcome. Lifetime discounted QALYs and costs were 5.312 and $88,247 for the no treatment strategy and 5.342 and $90,869 for the MRI-based strategy, resulting in an ICER of $88,000/QALY. Results were sensitive to variations in patient- and provider-specific factors such as sleep duration, hospital travel and door-to-needle times, as well as onset probability distribution, MRI specificity, and mRS utility values.

CONCLUSIONS

Our model-based findings suggest that an MRI-based treatment strategy for this population could be cost-effective and quantifies the impact that patient- and provider-specific factors, such as sleep duration, hospital travel and door-to-needle times, could have on the optimal decision for wake-up stroke patients.

The current impact of incidental findings found during neuroimaging on neurologists' workloads

Objective

Neuroimaging is an important diagnostic tool in the assessment of neurological disease, but often unmasks Incidental Findings (IFs). The negative impacts of IFs, such as ‘patient’ anxiety, present neurologists with management dilemmas, largely due to the limited knowledge base surrounding the medical significance of these IFs. In particular, the lack of evidence-based clinical trials investigating the efficacy of treatments for subclinical IFs makes management protocols challenging. The objective was to determine the impact IFs may have on neurologists’ workloads and healthcare budgets and to examine neurologists’ concerns regarding the clinical management of these ‘patients’.

Methods

Qualitative research based on constructivist grounded theory. Data was collected through semi-structured interviews of purposively sampled neurologists, coded, and concurrent comparative analysis performed. A substantive theory of the ‘IF impacts’ was developed after concept saturation.

Results

Neurologists managed the escalating workload caused by an increased number of referrals of ‘patients’ with IFs found during neuroimaging; however it was unclear whether this was sustainable in the future. Neurologists experienced IF management dilemmas and spent more time with ‘patients’ affected by anxiety. The lack of information provided to those undergoing neuroimaging by the referring clinician regarding the possibility of discovering IFs was highlighted.

Conclusion

The impact of IFs upon the neurologist, ‘patient’ and the health institution appeared considerable. Further research determining the natural history of subclinical IFs and the efficacy of intervention will help to alleviate these issues.

Choosing Wisely: a neurosurgical perspective on neuroimaging for headaches

Multiple national initiatives seek to curb spending to address increasing healthcare costs in the United States. The Choosing Wisely initiative is a popular initiative that focuses on reducing healthcare spending by setting guidelines to limit tests and procedures requested by patients and ordered by physicians. To reduce spending on neuroimaging, the Choosing Wisely initiative and other organizations have offered guidelines to limit neuroimaging for headaches. Although the intentions are laudable, these guidelines are inconsistent with the neurosurgeon's experience with patients with brain tumor. If adopted by governing or funding organizations, these guidelines threaten to negatively affect the care and outcomes of patients with brain tumors, who frequently present with minimal symptoms or isolated headaches syndromes. As physicians grapple with the difficult conflict between evidence-based cost-cutting guidelines and individualized patient-tailored medicine, they must carefully balance the costs and benefits of discretionary services such as neuroimaging for headaches. By participating in the development of validated clinical decision rules on neuroimaging for headaches, neurosurgeons can advocate for their patients and improve their patients' outcomes.

Deep imaging technology needed for NIH BRAIN initiative

This opinion piece discusses potential funding opportunities by the NIH BRAIN initiative to support the development of deep imaging technologies.

The appropriate use of neuroimaging in the diagnostic work-up of dementia: an economic literature review and cost-effectiveness analysis

BACKGROUND

Structural brain imaging is often performed to establish the underlying causes of dementia. However, recommendations differ as to who should receive neuroimaging and whether computed tomography (CT) or magnetic resonance imaging (MRI) should be used.

OBJECTIVES

This study aimed to determine the cost-effectiveness in Ontario of offering structural imaging to all patients with mild to moderate dementia compared with offering it selectively according to guidelines from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCC). We compared the cost-effectiveness of CT and MRI as first-line strategies.

METHODS

We performed a systematic literature search (2000 to 2013) to identify cost-effectiveness studies of clinical prediction rules and structural imaging modalities. Studies were assessed for quality and applicability to Ontario. We also developed a model to evaluate the cost-effectiveness of clinical guidelines (image all versus according to CCC) and modalities (CT versus MRI). Transition probabilities, utilities, and costs were obtained from published literature or expert opinion. Results were expressed in terms of costs and quality adjusted life years (QALYs).

RESULTS

No relevant cost-effectiveness analyses were identified in the published literature. According to the base-case results of our model, the most effective and cost-effective strategy is to image patients who meet CCC criteria with CT and to follow-up with MRI for suspected cases of space-occupying lesions (SOL). However, the results were sensitive to the specificity of MRI for detecting vascular causes of dementia. At a specificity of 64%, the most cost-effective strategy is CCC followed by MRI.

LIMITATIONS

Studies used to estimate diagnostic accuracy were limited by a lack of a gold standard test for establishing the cause of dementia. The model does not include costs to patients and their families, nor does it account for patient preferences about diagnostic information.

CONCLUSIONS

Given the relative prevalence of vascular dementia and SOLs, and the improvement in QALYs associated with treatment, the strategy with the greatest combined sensitivity (CCC with CT followed by MRI for patients with SOLs) results in the greatest number of QALYs and is the least costly. Due to limitations in the clinical data and challenges in the interpretation of this evidence, the model should be considered a framework for assessing uncertainty in the evidence base rather than providing definitive answers to the research questions.

Reducing clinical trial costs by detecting and measuring the placebo effect and treatment effect using brain imaging

Although the placebo effect is known to have a strong impact on the outcomes of clinical trials, methods for measuring it are limited to physiological observations. We propose a method of localizing, identifying and measuring placebo and treatment-induced networks in the brain using functional neuroimaging. Measuring the relative activation of these "placebo" brain networks serves as a proxy for the placebo effect contained within the variable of interest (depression rating, blood pressure, etc). Analogous to the difference between a paired and unpaired t-test, this allows for a sharp gain in power and reduction in the sample sizes needed in clinical trials, potentially leading to a drastically smaller sample sizes for establishing efficacy, a shorter time-to-market for a drug, and a drastic reduction in the cost of bringing new drugs into the market.