The Utility of the Combined Use of 123I-FP-CIT and 123I-MIBG Myocardial Scintigraphy in Differentiating Parkinson’s Disease from Other Parkinsonian Syndromes

MRI multiparametric scoring system for pial blood supply of intracranial meningiomas

Background

Meningiomas are occasionally fed by pial blood supply (PBS). It is postulated that peritumoral flow void (PTFV), peritumoral brain edema (PTBE), and absence of an arachnoid plane (AP) are useful parameters for evaluating PBS.

Purpose

To determine whether conventional magnetic resonance imaging (MRI) using a multiparametric scoring system (MSS) is a useful way to predict PBS.

Material and Methods

Forty-six patients were included and divided: PBS and non-PBS groups. Differences between the groups in six parameters of MR imaging were analyzed: tumor size, tumor location, PTBE grade, AP grade, PTFV, and MIB1 labeling index (MIB1-LI) grade. Cutoff values were determined using receiver operating characteristic (ROC) curve analysis for the differentiation of both groups based on statistically significant parameters. All cases were scored as 1 (PBS) or 0 (non-PBS) for each parameter according to set thresholds. Individual scores were totaled for each case, yielding a combined score for each case to obtain a cutoff value using ROC curve analysis for the MSS.

Results

Peritumoral brain edema grade, AP grade, PTFV, and MIB-LI grade were statistically associated with PBS. Receiver operating characteristic curve analyses showed that PTBE grade 3 or 4, AP grade 3 or 4, and PTFV positivity had the highest accuracy of 69%, 64%, and 68%, respectively. Regarding the MSS, a cutoff value of 2 had the highest accuracy of 71%; PBS diagnosis was indicated by at least two of the three parameters, namely, PTBE grade, AP grade, and PTFV.

Conclusion

The MSS is a useful way to predict PBS in intracranial meningiomas on MRI.

A diagnostic strategy for Parkinsonian syndromes using quantitative indices of DAT SPECT and MIBG scintigraphy: an investigation using the classification and regression tree analysis

Purpose

We aimed to evaluate the diagnostic performances of quantitative indices obtained from dopamine transporter (DAT) single-photon emission computed tomography (SPECT) and ¹²³I-metaiodobenzylguanidine (MIBG) scintigraphy for Parkinsonian syndromes (PS) using the classification and regression tree (CART) analysis.

Methods

We retrospectively enrolled 216 patients with or without PS, including 80 without PS (NPS) and 136 with PS [90 Parkinson’s disease (PD), 21 dementia with Lewy bodies (DLB), 16 progressive supranuclear palsy (PSP), and 9 multiple system atrophy (MSA). The striatal binding ratio (SBR), putamen-to-caudate ratio (PCR), and asymmetry index (AI) were calculated using DAT SPECT. The heart-to-mediastinum uptake ratio (H/M) based on the early (H/M [Early]) and delayed (H/M [Delay]) images and cardiac washout rate (WR) were calculated from MIBG scintigraphy. The CART analysis was used to establish a diagnostic decision tree model for differentiating PS based on these quantitative indices.

Results

The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 87.5, 96.3, 93.3, 92.9, and 93.1 for NPS; 91.1, 78.6, 75.2, 92.5, and 83.8 for PD; 57.1, 95.9, 60.0, 95.4, and 92.1 for DLB; and 50.0, 98.0, 66.7, 96.1, and 94.4 for PSP, respectively. The PCR, WR, H/M (Delay), and SBR indices played important roles in the optimal decision tree model, and their feature importance was 0.61, 0.22, 0.11, and 0.05, respectively.

Conclusion

The quantitative indices showed high diagnostic performances in differentiating NPS, PD, DLB, and PSP, but not MSA. Our findings provide useful guidance on how to apply these quantitative indices in clinical practice.