The basal ganglia matching tools package for striatal uptake semi-quantification: description and validation
ABSTRACT To design a novel algorithm (BasGan) for automatic segmentation of striatal (123)I-FP-CIT SPECT.
The BasGan algorithm is based on a high-definition, three-dimensional (3D) striatal template, derived from Talairach's atlas. A blurred template, obtained by convolving the former with a 3D Gaussian kernel (FWHM = 10 mm), approximates striatal activity distribution. The algorithm performs translations and scale transformation on the bicommissural aligned image to set the striatal templates with standard size in an appropriate initial position. An optimization protocol automatically performs fine adjustments in the positioning of blurred templates to best match the radioactive counts, and locates an occipital ROI for background evaluation. Partial volume effect correction is included in the process of uptake computation of caudate, putamen and background. Experimental validation was carried out by means of six acquisitions of an anthropomorphic striatal phantom. The BasGan software was applied to a first set of patients with Parkinson's disease (PD) versus patients affected by essential tremor.
A highly significant correlation was achieved between true binding potential and measured (123)I activity from the phantom. (123)I-FP-CIT uptake was significantly lower in all basal ganglia in the PD group versus controls with both BasGan and a conventional ROI method used for comparison, but particularly with the former. Correlations with the motor UPDRS score were far more significant with the BasGan.
The novel BasGan algorithm automatically performs the 3D segmentation of striata. Because co-registered MRI is not needed, it can be used by all nuclear medicine departments, since it is freely available on the Web.
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ABSTRACT: Brain single-photon-emission-computerized tomography (SPECT) with I-ioflupane (I-FP-CIT) is useful to diagnose Parkinson disease (PD). To investigate the diagnostic performance of I-FP-CIT brain SPECT with semiquantitative analysis by Basal Ganglia V2 software (BasGan), we evaluated semiquantitative data of patients with suspect of PD by a support vector machine classifier (SVM), a powerful supervised classification algorithm.I-FP-CIT SPECT with BasGan analysis was performed in 90 patients with suspect of PD showing mild symptoms (bradykinesia-rigidity and mild tremor). PD was confirmed in 56 patients, 34 resulted non-PD (essential tremor and drug-induced Parkinsonism). A clinical follow-up of at least 6 months confirmed diagnosis. To investigate BasGan diagnostic performance we trained SVM classification models featuring different descriptors using both a "leave-one-out" and a "five-fold" method. In the first study we used as class descriptors the semiquantitative radiopharmaceutical uptake values in the left (L) and right (R) putamen (P) and in the L and R caudate nucleus (C) for a total of 4 descriptors (CL, CR, PL, PR). In the second study each patient was described only by CL and CR, while in the third by PL and PR descriptors. Age was added as a further descriptor to evaluate its influence in the classification performance.I-FP-CIT SPECT with BasGan analysis reached a classification performance higher than 73.9% in all the models. Considering the "Leave-one-out" method, PL and PR were better predictors (accuracy of 91% for all patients) than CL and CR descriptors; using PL, PR, CL, and CR diagnostic accuracy was similar to that of PL and PR descriptors in the different groups. Adding age as a further descriptor accuracy improved in all the models. The best results were obtained by using all the 5 descriptors both in PD and non-PD subjects (CR and CL + PR and PL + age = 96.4% and 94.1%, respectively). Similar results were observed for the "five-fold" method.I-FP-CIT SPECT with BasGan analysis using SVM classifier was able to diagnose PD. Putamen was the most discriminative descriptor for PD and the patient age influenced the classification accuracy.
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ABSTRACT: Objetivos Describir y validar un nuevo software, totalmente automático, específicamente diseñado para semi-cuantificar la captación estriatal de 123I-FP-CIT usando volúmenes de interés (VOIs). Material y métodos El algoritmo propuesto se basa en una plantilla que remeda la captación estriatal de 123I-FP-CIT en un sujeto sano, obtenida a partir de VOIs anatómicos definidos en WFU PickAtlas. Para la validación experimental de este algoritmo se adquirieron 4 estudios SPECT del maniquí antropomórfico Alderson llenado con concentraciones radioactivas variables. Las imágenes SPECT experimentales se normalizaron espacialmente respecto a la plantilla creada. Los VOIs binarios correspondientes a núcleo caudado y putámen derechos e izquierdos, utilizados para diseñar la plantilla, se proyectaron sobre las imágenes experimentales para obtener las cuentas en estas regiones. Para minimizar los efectos de volumen parcial se utilizó un porcentaje de vóxeles, en vez de utilizar todos los vóxeles contenidos en estos VOIs. Se ha utilizado un VOI binario situado en región occipital para cuantificar la unión no específica. Los potenciales de unión (BPs) experimentales se calcularon a partir de las cuentas obtenidas en estas regiones. Los BPs reales se calcularon a partir de alícuotas tomadas de las soluciones utilizadas para llenar el maniquí. Resultados Hubo diferencias estadísticamente significativas en los BPs experimentales en función del porcentaje de vóxeles utilizados para la cuantificación (p < 0.002). Se alcanzó una alta correlación entre los BPs reales y los experimentales, independientemente del porcentaje de vóxeles utilizados para la cuantificación. Conclusiones Este nuevo programa automático e independiente del observador realiza la semicuantificación de la captación estriatal de 123I-FP-CIT en estudios experimentales.Revista Española de Medicina Nuclear e Imagen Molecular 10/2014; DOI:10.1016/j.remn.2014.08.004 · 0.86 Impact Factor
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ABSTRACT: REM sleep behavior disorder (RBD) can be induced by antidepressants, especially serotonin reuptake inhibitors (SSRI), thus a role of the serotonergic system in the pathogenesis of RBD has been proposed. However, the serotonergic system integrity in idiopathic RBD (iRBD) is still unknown. We aimed to study brain stem serotonergic system integrity, by means of (123)I-FP-CIT-SPECT, in a group of iRBD patients as compared to normal subjects. Single-center, prospective observational study. University hospital. Twenty iRBD outpatients and 23 age-matched normal controls. The diagnosis of RBD was determined clinically and confirmed by means of overnight, laboratory-based video-polysomnography. Both iRBD patients and normal subjects underwent (123)I-FP-CIT-SPECT as a marker of dopamine transporter (DAT) at basal ganglia level and of serotonin transporter (SERT) at brainstem and thalamus levels. (123)I-FP-CIT-SPECT images were analyzed and compared between iRBD patients and controls by means of both region of interest analysis at basal ganglia, midbrain, pons and thalamus levels, and voxel-based analysis, taking into account age and the use of SSRI as confounding factors. No difference in (123)I-FP-CIT-SPECT specific to non-displaceable binding ratios (SBR) values was found between iRBD and normal subjects at brainstem and thalamus levels while iRBD patients showed lower SBR values in all basal ganglia nuclei (P < 0.0001) compared to controls. These results suggest that the serotonergic system is not directly involved in RBD pathogenesis while confirming nigro-striatal dopaminergic deafferentation in iRBD. Copyright © 2015 Associated Professional Sleep Societies, LLC. All rights reserved.Sleep 02/2015; · 5.06 Impact Factor