Coregistration of head CT comparison studies: assessment of clinical utility.
OBJECTIVE
The authors evaluated the clinical utility of image coregistration in the interpretation of follow-up computed tomographic (CT) studies of the head.


METHODS
Fourteen patients with 34 intracranial lesions underwent follow-up head CT. The images were coregistered automatically with proprietary software on a standard personal computer, and all patient demographic data were removed. A neuroradiologist read the coregistered images several days after first reading the nonregistered images. The reading was repeated some months later to assess intraobserver variability, and a second reader was recruited so that interobserver variability also could be assessed. The interpretations of nonregistered images served as controls for the interpretations of coregistered images. Readers were asked to assess changes in lesion size quantitatively and to record the time it took to evaluate each case. Differences in interpretation speed were evaluated with the t test. Univariate analysis was used to measure accuracy; interpretations were compared with those of a nonblinded senior neuroradiologist, which served as the diagnostic standard. Intra- and interindividual variability were assessed with the kappa statistic.


RESULTS
The time needed to read the studies decreased by an average of 65.6% (P < .05), with statistically significant reductions for each reader. Coregistration also changed the interpretation results in 21.9% of cases. Coregistration increased the accuracy of reading, but not significantly. Intraobserver variability improved from 0.3554 to 0.7328 with coregistration, and interobserver variability improved from 0.2670 to 0.3309.


CONCLUSIONS
Image coregistration is technically feasible and accurate. Coregistration of follow-up studies significantly reduces the time needed for comparison and interpretation. It does not detract from the accuracy of interpretation of follow-up studies and tends to decrease intra- and interobserver variability.
Schellingerhout
Dawid
D
Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
Lev
Michael H
MH
Bagga
Ranjit J
RJ
Rincon
Sandra
S
Berdichevsky
Dmitri
D
Thangaraj
Ven
V
Gonzalez
R Gilberto
RG
Alpert
Nathaniel M
NM
D001927:Brain Diseases / Q000000981:diagnostic imaging*; D006801:Humans; D015588:Observer Variation; D011857:Radiographic Image Interpretation, Computer-Assisted; D011873:Radiology Information Systems; D012984:Software; D013997:Time Factors; D014057:Tomography, X-Ray Computed