P1.22 Progression of thermal sweating dysfunction and findings on [123I]metaiodobenzylguanidine myocardial scintigraphy in Parkinson's disease patients

2009 ◽  
Vol 149 (1-2) ◽  
pp. 68
Author(s):  
M. Kunimoto ◽  
Y. Fujita ◽  
A. Kuga ◽  
M. Ubano ◽  
Y. Uesaka
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Myocardial Scintigraphy ◽  
Thermal Sweating

Comparison of the progress in thermal sweating dysfunction and findings of MIBG myocardial scintigraphy in Parkinson's disease

2010 ◽  
Vol 158 (1-2) ◽  
pp. 132
Author(s):  
Yoshiyuki Fujita ◽  
Atsushi Kuga ◽  
Megumi Ubano ◽  
Yoshikazu Uesaka ◽  
Masanari Kunimoto
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Myocardial Scintigraphy ◽  
Thermal Sweating

Chronological changes of123I-MIBG myocardial scintigraphy and clinical features of Parkinson's disease

2015 ◽  
Vol 86 (9) ◽  
pp. 945-951 ◽  
Author(s):  
Koyo Tsujikawa ◽  
Yasuhiro Hasegawa ◽  
Satoshi Yokoi ◽  
Keizo Yasui ◽  
Ichiro Nanbu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Features ◽  
Myocardial Scintigraphy

scholarly journals [123I]-Ioflupane SPECT in combination with MIBG myocardial scintigraphy in Parkinson’s disease: a case series study

2016 ◽  
Vol 56 (6) ◽  
pp. 400-406 ◽  
Author(s):  
Akane Yamada ◽  
Takenobu Murakami ◽  
Yongjin Kang ◽  
Yoichiro Iikuni ◽  
Akeshi Morimatsu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Case Series ◽  
Myocardial Scintigraphy ◽  
Case Series Study ◽  
Series Study

scholarly journals [123I] Meta-iodobenzylguanidine Myocardial Scintigraphy Differentiates Corticohasal Degeneration from Parkinson's Disease.

2003 ◽  
Vol 42 (1) ◽  
pp. 127-128 ◽  
Author(s):  
Satoshi ORIMO ◽  
Eisuke OZAWA ◽  
Soju NAKADE ◽  
Hideyuki HATTORI ◽  
Kuniaki TSUCHIYA ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Myocardial Scintigraphy

scholarly journals Artificial intelligence techniques support nuclear medicine modalities to improve the diagnosis of Parkinson’s disease and Parkinsonian syndromes

2020 ◽  
Author(s):  
Barbara Palumbo ◽  
Francesco Bianconi ◽  
Susanna Nuvoli ◽  
Angela Spanu ◽  
Mario Luca Fravolini
Keyword(s):  
Artificial Intelligence ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Nuclear Medicine ◽  
Movement Disorders ◽  
Myocardial Scintigraphy ◽  
Machine Learning Techniques ◽  
Parkinsonian Syndromes ◽  
Learning Techniques ◽  
Using Data

Abstract Purpose The aim of this review is to discuss the most significant contributions about the role of Artificial Intelligence (AI) techniques to support the diagnosis of movement disorders through nuclear medicine modalities. Methods The work is based on a selection of papers available on PubMed, Scopus and Web of Sciences. Articles not written in English were not considered in this study. Results Many papers are available concerning the increasing contribution of machine learning techniques to classify Parkinson’s disease (PD), Parkinsonian syndromes and Essential Tremor (ET) using data derived from brain SPECT with dopamine transporter radiopharmaceuticals. Other papers investigate by AI techniques data obtained by 123I-MIBG myocardial scintigraphy to differentially diagnose PD and other Parkinsonian syndromes. Conclusion The recent literature provides strong evidence that AI techniques can play a fundamental role in the diagnosis of movement disorders by means of nuclear medicine modalities, therefore paving the way towards personalized medicine.

Evaluation of DAT-SPECT and 123I-MIBG myocardial scintigraphy in the diagnosis and staging of Parkinson’s disease

2017 ◽  
Vol 381 ◽  
pp. 956
Author(s):  
T. Shigekiyo ◽  
K. Unoda ◽  
S. Ishida ◽  
H. Nakajima ◽  
H. Kimura ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Myocardial Scintigraphy ◽  
Dat Spect
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