open access

Vol 8, No 2 (2005)
Review paper
Submitted: 2012-01-23
Published online: 2005-06-23
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Optimisation of statistical methodologies for a better diagnosis of neurological and psychiatric disorders by means of SPECT

Marco Pagani, Dario Salmaso, Katalin Borbely
Nucl. Med. Rev 2005;8(2):140-149.

open access

Vol 8, No 2 (2005)
Reviews
Submitted: 2012-01-23
Published online: 2005-06-23

Abstract

In the last years there has been a wide consensus on the importance of brain imaging in assessing neurodegenerative and psychiatric disorders. Different techniques for functional and anatomical examination are currently clinically implemented in neurology and psychiatry to improve sensitivity, specificity and accuracy of the diagnosis of various diseases. In addition, the increasing life expectancy in the Western world raises the social importance and the economical impact of age-related neurodegenerative disorders since the incidence of Alzheimer disease and Parkinson disease is higher in the elderly.
An early diagnosis of neuro-psychiatric diseases and the assessment of "natural" changes of regional cerebral blood flow (rCBF) distribution during normal aging are hence of utmost importance.
In the recent past brain disorders have extensively been investigated by means of optimised nuclear medicine techniques, instruments and algorithms. Diagnosis can be better achieved by identifying those structures in which CBF or metabolism deviate from normality resulting in significant changes as compared to a reference database.
In the present paper we present some studies investigating, by means of recently implemented diagnostic tools, patients bearer of various neuro-psychiatric disorders. The improved nuclear medicine techniques and instrumentation, the state-of-the-art software for brain imaging standardisation and the use of sophisticated multivariate data analysis are extensively reviewed.

Abstract

In the last years there has been a wide consensus on the importance of brain imaging in assessing neurodegenerative and psychiatric disorders. Different techniques for functional and anatomical examination are currently clinically implemented in neurology and psychiatry to improve sensitivity, specificity and accuracy of the diagnosis of various diseases. In addition, the increasing life expectancy in the Western world raises the social importance and the economical impact of age-related neurodegenerative disorders since the incidence of Alzheimer disease and Parkinson disease is higher in the elderly.
An early diagnosis of neuro-psychiatric diseases and the assessment of "natural" changes of regional cerebral blood flow (rCBF) distribution during normal aging are hence of utmost importance.
In the recent past brain disorders have extensively been investigated by means of optimised nuclear medicine techniques, instruments and algorithms. Diagnosis can be better achieved by identifying those structures in which CBF or metabolism deviate from normality resulting in significant changes as compared to a reference database.
In the present paper we present some studies investigating, by means of recently implemented diagnostic tools, patients bearer of various neuro-psychiatric disorders. The improved nuclear medicine techniques and instrumentation, the state-of-the-art software for brain imaging standardisation and the use of sophisticated multivariate data analysis are extensively reviewed.
Get Citation

Keywords

SPECT; neuro-psychiatric diseases; standardisation software; multivariate analysis; functional connectivity

About this article
Title

Optimisation of statistical methodologies for a better diagnosis of neurological and psychiatric disorders by means of SPECT

Journal

Nuclear Medicine Review

Issue

Vol 8, No 2 (2005)

Article type

Review paper

Pages

140-149

Published online

2005-06-23

Page views

543

Article views/downloads

1723

Bibliographic record

Nucl. Med. Rev 2005;8(2):140-149.

Keywords

SPECT
neuro-psychiatric diseases
standardisation software
multivariate analysis
functional connectivity

Authors

Marco Pagani
Dario Salmaso
Katalin Borbely

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