Automatic volumetry on MR brain images can support diagnostic decision making.

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Title: Automatic volumetry on MR brain images can support diagnostic decision making.
Author(s): Heckemann, RA
Hammers, A
Rueckert, D
Aviv, RI
Harvey, CJ
Hajnal, JV
Item Type: Journal Article
Abstract: Background: Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing. Methods: A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD) along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence. Results: The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p < 0.02). Conclusion: Volumetric anatomical information extracted from brain images using automatic segmentation and presented as colour overlays can support diagnostic decision making. © 2008 Heckemann et al; licensee BioMed Central Ltd.
Content Version: Published version
Publication Date: 23-May-2008
Citation: BMC Med Imaging Vol.( 8 ) No.( ) pp 9 - 9
URI: http://hdl.handle.net/10044/1/1202
Publisher Link: http://dx.doi.org/10.1186/1471-2342-8-9
DOI: 10.1186/1471-2342-8-9
ISSN: 1471-2342
Start Page: 9
End Page: 9
Copyright Statement: © 2008 Heckemann et al; licensee BioMed Central Ltd.
Volume: 8
Appears in Collections:Clinical Neuroscience
Visual Information Processing
Imaging Sciences



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