SPECT imaging evaluation in movement disorders: far beyond visual assessment

Area of Science:

• Nuclear medicine neuroimaging
• Medical imaging analysis
• Quantitative diagnostics

Background:

• Single photon emission computed tomography (SPECT) is crucial for differentiating Parkinson's disease (PD) from essential tremor (ET) and Parkinson's
• plus
• syndromes.
• Current diagnosis relies heavily on visual assessment by experienced observers.
• Quantitative methods have been developed to assist neuroimaging diagnosis.

Purpose of the Study:

• To categorize, present, and comment on semi-quantification methods in nuclear medicine neuroimaging.
• To explore the evolution from manual region of interest (ROI) methods to automated procedures.
• To discuss the potential of semi-quantification in improving diagnostic accuracy and patient management.

Main Methods:

• Review and categorization of semi-quantification techniques for SPECT neuroimaging.
• Discussion of classic, advanced automated, and pixel-based statistical analysis methods.
• Exploration of automated image registration, fusion, and segmentation advancements.

Main Results:

• Semi-quantification methods aim to extract numerical data from SPECT images to aid in patient categorization.
• Methods range from manual ROI analysis to sophisticated automated and statistical approaches.
• Despite advancements, visual assessment remains primary, and standardized numerical results for definitive differentiation are not yet established.

Conclusions:

• Semi-quantification methods hold promise for improving sensitivity, strengthening diagnoses, and aiding patient follow-up and therapy response assessment.
• Development of standardized, automated software is crucial for reliable, objective diagnosis.
• Future applications include objective diagnosis, improved marginal case assessment, and standardized multicenter trials.