TY - JOUR
T1 - A diagnostic strategy for Parkinsonian syndromes using quantitative indices of DAT SPECT and MIBG scintigraphy
T2 - an investigation using the classification and regression tree analysis
AU - Iwabuchi, Yu
AU - Kameyama, Masashi
AU - Matsusaka, Yohji
AU - Narimatsu, Hidetoshi
AU - Hashimoto, Masahiro
AU - Seki, Morinobu
AU - Ito, Daisuke
AU - Tabuchi, Hajime
AU - Yamada, Yoshitake
AU - Jinzaki, Masahiro
N1 - Funding Information:
The authors thank the staff of the Division of Nuclear Medicine at the Department of Radiology for their valuable support. This work was supported by JSPS KAKENHI (Grant Number: JP19K17243).
Funding Information:
The authors thank the staff of the Division of Nuclear Medicine at the Department of Radiology for their valuable support. This work was supported by JSPS KAKENHI (Grant Number: JP19K17243).
Funding Information:
MJ received research grants from Nihon Medi-Physics Co., Ltd.; FUJIFILM Toyama Chemical Co., Ltd.; and GE Healthcare Corp. MK received a research grant from Nihon Medi-Physics Co., Ltd. All other authors declare no conflict of interest.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/6
Y1 - 2021/6
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - CART
KW - Data mining
KW - I-FP-CIT
KW - I-Ioflupane
UR - http://www.scopus.com/inward/record.url?scp=85098593659&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098593659&partnerID=8YFLogxK
U2 - 10.1007/s00259-020-05168-0
DO - 10.1007/s00259-020-05168-0
M3 - Article
C2 - 33392714
AN - SCOPUS:85098593659
SN - 1619-7070
VL - 48
SP - 1833
EP - 1841
JO - European Journal of Nuclear Medicine and Molecular Imaging
JF - European Journal of Nuclear Medicine and Molecular Imaging
IS - 6
ER -