TY - JOUR
T1 - Standardized Uptake Value Ratio-Independent Evaluation of Brain Amyloidosis
AU - Alzheimer's Disease Neuroimaging Initiative
AU - Chincarini, Andrea
AU - Sensi, Francesco
AU - Rei, Luca
AU - Bossert, Irene
AU - Morbelli, Silvia
AU - Guerra, Ugo Paolo
AU - Frisoni, Giovanni
AU - Padovani, Alessandro
AU - Nobili, Flavio
PY - 2016/10/18
Y1 - 2016/10/18
N2 - The assessment of in vivo 18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based on standardized uptake value ratio (SUVr) measurements. We target the difficulties of image reading and possible shortcomings of the SUVr methods by validating a new semi-quantitative approach named ELBA. ELBA involves a minimal image preprocessing and does not rely on small, specific regions of interest (ROIs). It evaluates the whole brain and delivers a geometrical/intensity score to be used for ranking and dichotomic assessment. The method was applied to adniimages 18F-florbetapir images from the ADNI database. Five expert readers provided visual assessment in blind and open sessions. The longitudinal trend and the comparison to SUVr measurements were also evaluated. ELBA performed with area under the roc curve (AUC) = 0.997 versus the visual assessment. The score was significantly correlated to the SUVr values (r = 0.86, p < 10-4). The longitudinal analysis estimated a test/retest error of ≃2.3. Cohort and longitudinal analysis suggests that the ELBA method accurately ranks the brain amyloid burden. The expert readers confirmed its relevance in aiding the visual assessment in a significant number (85) of difficult cases. Despite the good performance, poor and uneven image quality constitutes the major limitation.
AB - The assessment of in vivo 18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based on standardized uptake value ratio (SUVr) measurements. We target the difficulties of image reading and possible shortcomings of the SUVr methods by validating a new semi-quantitative approach named ELBA. ELBA involves a minimal image preprocessing and does not rely on small, specific regions of interest (ROIs). It evaluates the whole brain and delivers a geometrical/intensity score to be used for ranking and dichotomic assessment. The method was applied to adniimages 18F-florbetapir images from the ADNI database. Five expert readers provided visual assessment in blind and open sessions. The longitudinal trend and the comparison to SUVr measurements were also evaluated. ELBA performed with area under the roc curve (AUC) = 0.997 versus the visual assessment. The score was significantly correlated to the SUVr values (r = 0.86, p < 10-4). The longitudinal analysis estimated a test/retest error of ≃2.3. Cohort and longitudinal analysis suggests that the ELBA method accurately ranks the brain amyloid burden. The expert readers confirmed its relevance in aiding the visual assessment in a significant number (85) of difficult cases. Despite the good performance, poor and uneven image quality constitutes the major limitation.
KW - Alzheimer's disease
KW - amyloid
KW - image analysis
KW - mild cognitive impairment
KW - PET
KW - standardized uptake value ratio
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U2 - 10.3233/JAD-160232
DO - 10.3233/JAD-160232
M3 - Article
C2 - 27662288
AN - SCOPUS:84992135207
VL - 54
SP - 1437
EP - 1457
JO - Journal of Alzheimer's Disease
JF - Journal of Alzheimer's Disease
SN - 1387-2877
IS - 4
ER -