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Diagnosis of Regional Cerebral Blood Flow Abnormalities Using Spect: Agreement between Individualized Statistical Parametric Maps and Visual Inspection by Nuclear Medicine Physicians with Different Levels of Expertise in Nuclear Neurology
Authors:Euclides Timóteo da Rocha  Carlos Alberto Buchpiguel  Ricardo Nitrini  Sergio Tazima  Stela Verzinhase Peres  Geraldo Busatto Filho
Affiliation:9. Department of Nuclear Medicine, Hospital de Câncer, Fundação Pio XII - Barretos/SP, Brazil;9. Brazil and Blood Transfusion Center, Medical School, São Paulo State University (UNESP) - Botucatu/SP, Brazil;99. Department of Nuclear Medicine, Hospital do Coração - São Paulo/SP, Brazil and Nuclear Medicine Division, Department of Radiology, Faculdade de Medicina da Universidade de São Paulo - São Paulo/SP, Brazil;999. Department of Neurology, Faculdade de Medicina da Universidade de São Paulo - São Paulo/SP, Brazil;9V. Department of Nuclear Medicine, Hospital Alemão Oswaldo Cruz - São Paulo/SP, Brazil;V. Research Support Group, Hospital de Câncer, Fundação Pio XII - Barretos/SP, Brazil;V9. Institute of Psychiatry, Department of Radiology, Nuclear Medicine Division, Faculdade de Medicina da Universidade de São Paulo - São Paulo/SP, Brazil.
Abstract:

INTRODUCTION:

Visual analysis is widely used to interpret regional cerebral blood flow (rCBF) SPECT images in clinical practice despite its limitations. Automated methods are employed to investigate between-group rCBF differences in research studies but have rarely been explored in individual analyses.

OBJECTIVES:

To compare visual inspection by nuclear physicians with the automated statistical parametric mapping program using a SPECT dataset of patients with neurological disorders and normal control images.

METHODS:

Using statistical parametric mapping, 14 SPECT images from patients with various neurological disorders were compared individually with a databank of 32 normal images using a statistical threshold of p<0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). Statistical parametric mapping results were compared with visual analyses by a nuclear physician highly experienced in neurology (A) as well as a nuclear physician with a general background of experience (B) who independently classified images as normal or altered, and determined the location of changes and the severity.

RESULTS:

Of the 32 images of the normal databank, 4 generated maps showing rCBF abnormalities (p<0.05, corrected). Among the 14 images from patients with neurological disorders, 13 showed rCBF alterations. Statistical parametric mapping and physician A completely agreed on 84.37% and 64.28% of cases from the normal databank and neurological disorders, respectively. The agreement between statistical parametric mapping and ratings of physician B were lower (71.18% and 35.71%, respectively).

CONCLUSION:

Statistical parametric mapping replicated the findings described by the more experienced nuclear physician. This finding suggests that automated methods for individually analyzing rCBF SPECT images may be a valuable resource to complement visual inspection in clinical practice.
Keywords:Brain SPECT   ECD   Statistical parametric mapping   Cerebral blood flow   Dementia
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