Assessment of the efficacy of early phase parameters by 123I-MIBG dynamic imaging for distinguishing Lewy body-related diseases from Parkinson’s syndrome

Shiiba, Takuro; Nishii, Ryuichi; Sasaki, Masayuki; Kihara, Yasushi; Tsuruta, Kazuhito; Maeda, Masaji; Morishita, Junji

doi:10.1007/s12149-014-0923-9

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…38 Adicionalmente, este método requer muito tempo de análise, embora tenha sido reportado que as imagens da fase inicial de captação de 123 I-MIBG podem ser suficientes para o diagnóstico diferencial entre doenças relacionadas com corpos de Lewy e outras causas de parkinsonismo, e entre DCLewy e DA. 45,49 A suspeita clínica de PCSREM deve ser confirmada por polisssonografia (PSG) de nível I e requer a existência de sono REM sem atonia e a presença de movimentos durante o sono REM, e que os distúrbios do sono não sejam explicáveis por outras condições médicas. 29 A PSG de nível I inclui eletroencefalograma (EEG), eletro-oculograma, ECG, eletromiograma, medição do fluxo oro-nasal e do esforço respiratório, monitorização da posição corporal e oximetria de pulso.…”

Section: Métodos Complementares De Diagnósticounclassified

Consenso Português para o Diagnóstico e Gestão Clínica da Demência com Corpos de Lewy (PORTUCALE)

et al. 2020

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Lewy body dementia is a common cause of dementia leading to the progressive deterioration of cognitive function and motor skills, behavioral changes, and loss of autonomy, impairing the quality of life of patients and their families. Even though it is the second leading cause of neurodegenerative dementia, diagnosis is still challenging, due to its heterogenous clinical presentation, especially in the early stages of the disease. Accordingly, Lewy body dementia is often misdiagnosed and clinically mismanaged. The lack of diagnostic accuracy has important implications for patients, given their increased susceptibility to the adverse effects of certain drugs, such as antipsychotics, which may worsen some symptoms associated with Lewy body dementia. Therefore, a specialist consensus based on the analysis of the most updated and relevant literature, and on clinical experience, is useful to all professionals involved in the care of these patients. This work aims to inform and provide recommendations about the best diagnostic and therapeutic approaches in Lewy body dementia in Portugal. Moreover, we suggest some strategies in order to raise the awareness of physicians, policy makers, and the society at large regarding this disease.

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Section: Métodos Complementares De Diagnósticounclassified

Consenso Português para o Diagnóstico e Gestão Clínica da Demência com Corpos de Lewy (PORTUCALE)

et al. 2020

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“…A dual time-point imaging technique involving myocardial MIBG scintigraphy at 10 – 30 min after injection (early phase) and 3 – 4 h after injection (late phase) is commonly used to diagnose neurodegenerative diseases. Shiiba et al proposed new parameters for detecting LDRD in early-phase dynamic images obtained using myocardial MIBG scintigraphy [4]. The early-phase washout rate and area under the time–activity curve from dynamic images showed a diagnostic performance comparable to that of conventional parameters, the heart-to-mediastinum ratio and washout rate.…”

Section: Neurologymentioning

confidence: 99%

Introduction of nuclear medicine research in Japan

Inubushi

Higashi

Kuji

et al. 2016

Eur J Nucl Med Mol Imaging

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There were many interesting presentations of unique studies at the Annual Meeting of the Japanese Society of Nuclear Medicine, although there were fewer attendees from Europe than expected. These presentations included research on diseases that are more frequent in Japan and Asia than in Europe, synthesis of original radiopharmaceuticals, and development of imaging devices and methods with novel ideas especially by Japanese manufacturers. In this review, we introduce recent nuclear medicine research conducted in Japan in the five categories of Oncology, Neurology, Cardiology, Radiopharmaceuticals and Technology. It is our hope that this article will encourage the participation of researchers from all over the world, in particular from Europe, in scientific meetings on nuclear medicine held in Japan.

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“…Pathologically, PD is characterized by the degeneration of the nigrostriatal dopamine nerve and the appearance of inclusion bodies containing α-synuclein as the main component, i.e. Lewy body [3,4]. The striatum to which dopamine neurons are projected is one of the nerve nuclei constituting the basal ganglia and comprises the caudate nucleus and putamen.…”

Section: Introductionmentioning

confidence: 99%

Improvement of classification performance of Parkinson’s disease using shape features for machine learning on dopamine transporter single photon emission computed tomography

et al. 2020

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Objective To assess the classification performance between Parkinson's disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT) are combined as a feature of machine learning (ML). Methods A total of 100 cases of both PD and normal control (NC) from the Parkinson's Progression Markers Initiative database were evaluated. A summed image was generated and regions of interests were set to the left and right striata. Area, equivalent diameter, major axis length, minor axis length, perimeter and circularity were calculated as shape features. Striatum binding ratios (SBR putamen and SBR caudate) were used as comparison features. The classification performance of the PD and NC groups according to receiver operating characteristic analysis of the shape features was compared in terms of SBRs. Furthermore, we compared the classification performance of ML when shape features or SBRs were used alone and in combination. Results The shape features (except minor axis length) and SBRs indicated significant differences between the NC and PD groups (p < 0.05). The top five areas under the curves (AUC) were as follows: circularity (0.972), SBR putamen (0.972), major axis length (0.945), SBR caudate (0.928) and perimeter (0.896). When classification was done using ML, AUC was as follows: circularity and SBRs (0.995), circularity alone (0.990), and SBRs (0.973). The classification

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Assessment of the efficacy of early phase parameters by 123I-MIBG dynamic imaging for distinguishing Lewy body-related diseases from Parkinson’s syndrome

Cited by 4 publications

References 23 publications

Consenso Português para o Diagnóstico e Gestão Clínica da Demência com Corpos de Lewy (PORTUCALE)

Consenso Português para o Diagnóstico e Gestão Clínica da Demência com Corpos de Lewy (PORTUCALE)

Introduction of nuclear medicine research in Japan

Improvement of classification performance of Parkinson’s disease using shape features for machine learning on dopamine transporter single photon emission computed tomography

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