Parkinson Disease: Kung HF

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A digest of articles written 1999 and later, on the topic "Parkinson Disease," originating from Planet Earth —» Kung HF.  Display:  All Citations ·  All Abstracts
1 Review Clinical acceptance of a molecular imaging agent: a long march with [99mTc]TRODAT. 2007

Kung HF, Kung MP, Wey SP, Lin KJ, Yen TC. · Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA. · Nucl Med Biol. · Pubmed #17921030 No free full text.

Abstract: In the past 10 years, significant progress has been made in using a technetium-99m dopamine transporter imaging agent, [99mTc]TRODAT, for routine clinical studies. Developing a molecular imaging agent from bench to the bedside is more than a simple scientific venture. Currently, Taiwan is the only place where [99mTc]TRODAT is approved for routine clinical use in the diagnosis of Parkinson's disease. The trials and tribulations of developing [99mTc]TRODAT for routine clinical use in Taiwan provide an interesting case study in how to (critics may say, how not to) develop a molecular imaging agent.

2 Article Binding of [99mTc]TRODAT-1 to dopamine transporters in patients with Parkinson's disease and in healthy volunteers. free! 2000

Mozley PD, Schneider JS, Acton PD, Plössl K, Stern MB, Siderowf A, Leopold NA, Li PY, Alavi A, Kung HF. · Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, USA. · J Nucl Med. · Pubmed #10768556 links to  free full text

Abstract: [99mTc]TRODAT-1 is a radiolabeled tropane that binds dopamine transporters. The primary goal of this study was to determine whether its regional cerebral distribution could differentiate between patients with Parkinson's disease and healthy human volunteers. METHODS: The sample consisted of 42 patients with Parkinson's disease, 23 age-matched controls, and 38 healthy adults younger than 40 y old. SPECT scans of the brain were acquired on a triple-head gamma camera 3-4 h after the intravenous injection of 740 MBq (20 mCi) [99mTc]TRODAT-1. Mean counts per pixel were measured manually in subregions of the basal ganglia and normalized to the mean background counts to give specific uptake values ([SUVs] approximately k3/k4). Patient and control groups were also compared with automated statistical parametric mapping techniques. Logistic discriminant analyses were performed to determine the optimum uptake values for differentiating patients from age-matched controls. RESULTS: Quantitative image analysis showed that the group mean SUVs in patients were less than the mean values in controls for all regions (all Ps < 0.000001). There was overlap in the caudate as well as in the anterior-most portion of the putamen, but not in the posterior putamen, even when the asymptomatic sides of 5 patients with clinically defined hemi-Parkinson's disease were factored in. CONCLUSION: The findings indicate that Parkinson's disease can be detected with [99mTc]TRODAT by simply inspecting the images for uptake in the posterior putamen. Appropriate asymmetries seem to be visible with quantification in patients with clinically defined hemi-Parkinson's disease, even though changes in the putamen contralateral to the clinically unaffected side in these patients appear to precede the development of symptoms.

3 Article A simplified method to determine [99mTc]TRODAT-1 in human plasma. 1999

Mu M, Kung MP, Plössl K, Acton PD, Mozley PD, Kung HF. · Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA. · Nucl Med Biol. · Pubmed #10628563 No free full text.

Abstract: [99mTc]TRODAT-1 is a useful imaging agent in evaluating changes in presynaptic dopamine transporters (DAT) for Parkinson's disease and other central nervous system (CNS) neurodegenerative diseases, for which a reduction of dopamine neurons is indicated. As part of an effort to establish a quantitative single-photon emission tomography (SPECT) procedure for imaging CNS DAT, measurement of nonmetabolized [99mTc]TRODAT-1 in human plasma was investigated. After an intravenous injection of [99mTc]TRODAT-1, there are three possible radioactive components in human plasma: hydrophilic compounds (pertechnetate, etc.), lipophilic metabolite(s), and unchanged [99mTc]TRODAT-1. Based on the differences in lipophilicity of [99mTc]TRODAT-1 and its lipophilic metabolite [99mTc]BAT, a new quantitative method for measuring [99mTc]TRODAT-1 with a simple solvent extraction method was developed. Various organic solvents or mixtures of solvents were tested, among which cyclohexane gave the best extraction yield for [99mTc]TRODAT-1 (76.06 +/- 3.32%) with a low extraction for [99mTc]BAT (2.43 +/- 0.82%). Extractions of [99mTc]TRODAT-1 and [99mTc]BAT mixtures in different predetermined ratios to simulate the actual human plasma samples with cyclohexane from phosphate buffer (5 mM, pH 8.0) were evaluated. The experimentally obtained ratios were in good agreement with the theoretical ratios. To investigate further the possibility of replacing the previously established high performance liquid chromatography (HPLC) method with the new solvent extraction method for the clinical application, both HPLC and extraction methods were used side by side to determine the unchanged [99mTc]TRODAT-1 in human plasma samples during [99mTc]TRODAT-1/SPECT imaging studies. The results from four human subjects showed that both methods consistently produced similar values for unchanged [99mTc]TRODAT-1 in the plasma samples. This improved solvent extraction method provides an easy and reliable technique to quantify unchanged [99mTc]TRODAT-1 in human plasma, thus making the clinical application of this agent readily available for quantitation of the DAT binding sites in the brain by SPECT imaging.

4 Article Logistic discriminant parametric mapping: a novel method for the pixel-based differential diagnosis of Parkinson's disease. 1999

Acton PD, Mozley PD, Kung HF. · Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA. · Eur J Nucl Med. · Pubmed #10552082 No free full text.

Abstract: Positron emission tomography (PET) and single-photon emission tomography (SPET) imaging of the dopaminergic system is a powerful tool for distinguishing groups of patients with neurodegenerative disorders, such as Parkinson's disease (PD). However, the differential diagnosis of individual subjects presenting early in the progress of the disease is much more difficult, particularly using region-of-interest analysis where small localized differences between subjects are diluted. In this paper we present a novel pixel-based technique using logistic discriminant analysis to distinguish between a group of PD patients and age-matched healthy controls. Simulated images of an anthropomorphic head phantom were used to test the sensitivity of the technique to striatal lesions of known size. The methodology was applied to real clinical SPET images of binding of technetium-99m labelled TRODAT-1 to dopamine transporters in PD patients (n=42) and age-matched controls (n=23). The discriminant model was trained on a subset (n=17) of patients for whom the diagnosis was unequivocal. Logistic discriminant parametric maps were obtained for all subjects, showing the probability distribution of pixels classified as being consistent with PD. The probability maps were corrected for correlated multiple comparisons assuming an isotropic Gaussian point spread function. Simulated lesion sizes measured by logistic discriminant parametric mapping (LDPM) gave strong correlations with the known data (r(2)=0. 985, P<0.001). LDPM correctly classified all PD patients (sensitivity 100%) and only misclassified one control (specificity 95%). All patients who had equivocal clinical symptoms associated with early onset PD (n=4) were correctly assigned to the patient group. Statistical parametric mapping (SPM) had a sensitivity of only 24% on the same patient group. LDPM is a powerful pixel-based tool for the differential diagnosis of patients with PD and healthy controls. The diagnosis of disease even before clinical symptoms become apparent may be possible, and ultimately this technique could be most useful in differentiating between several neurodegenerative disorders, incorporating images of multiple neuroreceptor systems.