Potential diagnostic value of 131I-MIBG myocardial scintigraphy in discrimination between Alzheimer disease and dementia with Lewy bodies

The role of 123-I-MIBG cardiac scintigraphy in the differential diagnosis between dementia with Lewy bodies and Alzheimer's disease

Although detailed diagnostic guidelines are available, differentiating dementia with Lewy bodies from Alzheimer's disease is often difficult. 123-I-MIBG cardiac scintigraphy is one of the tools which have been proposed for the diagnostic procedure. The present review is aimed at evaluating the available literature about this topic. Studies assessing the use of this technique to differentiate between the two diseases have been examined and reported. Overall, despite a certain study-to-study variability, the available literature suggests that 123-I-MIBG cardiac scintigraphy is an effective tool in differentiating between the two diseases, with high sensitivity and specificity values. Although the large-scale application of this technique is limited by possible interactions with specific medications and comorbidities, the reported studies are supportive for the usefulness of this technique in clinical practice.

The potential role of the cardiac MIBG scan in differentiating the drug-induced Parkinsonism from Parkinson’s disease

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MIBG scan is more positive in the PD group than the DIP.

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There is a significant difference in MIBG uptake between the PD and DIP groups.

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MIBG scan can be used to determine the prognosis of DIP.

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MIBG scan is 84.4% sensitive and 86.36% specific in diagnosing PD.

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MIBG scan is useful in better referring the patients to related centers.

Introduction

Methods

Results

Conclusion

Diagnostic accuracy of DAT-SPECT and MIBG scintigraphy for dementia with Lewy bodies: an updated systematic review and Bayesian latent class model meta-analysis

PURPOSE

Imperfect clinical reference standards can preclude accurately estimating the diagnostic accuracy of DAT-SPECT and MIBG myocardial scintigraphy for diagnosing DLB. To investigate the validity of unadjusted accuracy, we updated our previous meta-analysis.

METHODS

Literature search was updated to March 18, 2018. We also examined published systematic review reports. Two investigators extracted data and rated study validity using the QUADAS-2 tool. We performed a Bayesian latent class model meta-analysis accounting for imperfect reference standards.

RESULTS

We evaluated 27 studies including 2236 patients. With the exception of two DAT-SPECT studies that involved postmortem neuropathological verification, studies were susceptible to bias from imperfect reference standards. Compared with the unadjusted accuracy estimates, the adjusted sensitivity values were similar, whereas the adjusted specificity values were generally lower for detecting α-synuclein pathology in the brain. The adjusted summary sensitivity and specificity were 0.86 (95% credible interval [CrI], 0.76-0.95) and 0.81 (CrI, 0.70-0.92), and 0.93 (CrI, 0.74-1.00) and 0.75 (CI, 0.47-0.94) for visual and semi-quantitative assessments of DAT-SPECT, respectively; 0.92 (CrI, 0.81-0.99) and 0.80 (CrI, 0.67-0.93), and 0.87 (CrI, 0.74-0.98) and 0.80 (CrI, 0.69-0.93), for delayed- and early-phase scans of MIBG scintigraphy, respectively. When diagnosing the typical clinical syndrome, the adjusted accuracy values were similar to the unadjusted estimates. The adjusted sensitivity and specificity were 0.89 (CrI, 0.75-0.98) and 0.87 (CrI, 0.72-0.97), and 0.97 (CrI, 0.78-1.0) and 0.70 (CrI, 0.43-0.92) for visual and semi-quantitative assessments of DAT-SPECT, respectively; and 0.93 (CrI, 0.81-0.98) and 0.90 (CrI, 0.73-0.97), and 0.85 (CrI, 0.66-0.96) and 0.96 (95% CI, 0.83-1.0) for delayed- and early-phase scans of MIBG scintigraphy, respectively.

CONCLUSIONS

In our adjusted analyses, both imaging biomarkers had high diagnostic accuracy for detecting the hallmark pathology in the brain and for diagnosing the typical clinical syndrome.

Improved diagnostic accuracy for myocardial perfusion imaging using artificial neural networks on different input variables including clinical and quantification data

OBJECTIVE

Diagnostic accuracy of myocardial perfusion imaging (MPI) is not optimal to predict the result of angiography. The current study aimed at investigating the application of artificial neural network (ANN) to integrate the clinical data with the result and quantification of MPI.

METHODS

Out of 923 patients with MPI, 93 who underwent angiography were recruited. The clinical data including the cardiac risk factors were collected and the results of MPI and coronary angiography were recorded. The quantification of MPI polar plots (i.e. the counts of 20 segments of each stress and rest polar plots) and the Gensini score of angiographies were calculated. Feed-forward ANN was designed integrating clinical and quantification data to predict the result of angiography (normal vs. abnormal), non-obstructive or obstructive coronary artery disease (CAD), and Gensini score (≥10 and <10). The ANNs were designed to predict the results of angiography using different combinations of data as follows: reports of MPI, the counts of 40 segments of stress and rest polar plots, and the count of these 40 segments in addition to age, gender, and the number of risk factors. The diagnostic performance of MPI with different ANNs was compared.

RESULTS

The accuracy of MPI to predict the result of angiography, obstructive CAD, and Gensini score increased from 81.7% to 92.9%, 65.0% to 85.7%, and 50.5% to 92.9%, respectively by ANN using counts and clinical risk factors.

CONCLUSION

The diagnostic accuracy of MPI could be improved by ANN, using clinical and quantification data.

Roles of cardiac sympathetic neuroimaging in autonomic medicine

Sympathetic neuroimaging is based on the injection of compounds that either radiolabel sites of the cell membrane norepinephrine transporter (NET) or that are taken up into sympathetic nerves via the NET and radiolabel intra-neuronal catecholamine storage sites. Detection of the radioactivity is by planar or tomographic radionuclide imaging. The heart stands out among body organs in terms of the intensity of radiolabeling of sympathetic nerves, and virtually all of sympathetic neuroimaging focuses on the left ventricular myocardium. The most common cardiac sympathetic neuroimaging method worldwide is ¹²³I-metaiodobenzylguanidine (¹²³I-MIBG) scanning. ¹²³I-MIBG scanning is used routinely in Europe and East Asia in the diagnostic evaluation of neurogenic orthostatic hypotension (nOH), to distinguish Lewy body diseases (e.g., Parkinson disease with orthostatic hypotension (OH), pure autonomic failure) from non-Lewy body diseases (e.g., multiple system atrophy) and to distinguish dementia with Lewy bodies from Alzheimer's disease. In the USA, ¹²³I-MIBG scanning has been approved by the Food and Drug Administration for the evaluation of pheochromocytoma and some forms of heart failure-but not for the above-mentioned differential diagnoses. Positron emission tomographic methods based on imaging agents such as ¹⁸F-dopamine are categorized as research tools, despite more than a quarter century of clinical experience with these modalities. Considering that ¹²³I-MIBG scanning is available at most academic medical centers in the USA, cardiac sympathetic neuroimaging by this methodology merits consideration as an autonomic test, especially in patients with nOH.