Coregistration of Head CT Comparison Studies

Original Investigations

Coregistration of Head CT Comparison Studies: Assessment of Clinical Utility1 Dawid Schellingerhout, MD, Michael H. Lev, MD, Ranjit J. Bagga, MD, Sandra Rincon, MD, Dmitri Berdichevsky, MD Ven Thangaraj, MD, R. Gilberto Gonzalez, MD, Nathaniel M. Alpert, MD

Rationale and Objectives. The authors evaluated the clinical utility of image coregistration in the interpretation of follow-up computed tomographic (CT) studies of the head. Materials and 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 ␬ 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. Conclusion. 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. Key Words. Computed tomography (CT), image processing; diagnostic radiology, observer performance; head, CT. ©

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The management of a disease or condition often depends on changes in disease as assessed by a radiologist comparing imaging studies over time. Whether an abnormality has increased, decreased, or remains unchanged may determine changes in therapy. Under ideal circumstances,

Acad Radiol 2003; 10:242–248 1 From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 (D.S., M.H.L., R.J.B., S.R., D.B., R.G.G., N.M.A.); and Integrated Medical Imaging Systems, Waltham, Mass (V.T.). Received December 9, 2002; accepted December 10. Address correspondence to D.S.

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this judgment is easy to make and only the disease process evaluated influences the assessment. Unfortunately, many technical factors can cloud our view of the change in disease, including differences in patient positioning (eg, in angle and rotation), exposure factors chosen, the field of view employed, and the level and window settings chosen. These technical differences between initial and follow-up studies can impede the evaluation of change and may obscure progression or improvement in the underlying disease process (Fig 1). Follow-up imaging of the most critically ill patients often presents the greatest technical difficulty, and the resulting images can be most difficult to interpret.

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Automated image coregistration is designed to minimize this technical variability between scans. The goal of coregistration is to standardize all aspects of the images for the comparison of follow-up studies, allowing radiologists to focus their attention on the disease entity and thus improving the accuracy and ease of interpretation with regard to change in disease. Multiple methods of coregistration have been described by authors including Pelizzari et al (1), Alpert et al (2), Woods et al (3), Ardekani et al (4), Wells et al (5), and Ashburner and Friston (6). However, these methods have not yet had an important clinical effect, probably because of the labor and the cost of the necessary hardware and software. We use an automated method that requires a minimum of labor and supervision and runs on relatively inexpensive equipment. This method is not user dependent, does not involve input from the interpreting radiologist, and is eminently suited to CT of the head and to other digital modalities. The technique is currently limited to head CT but should be widely applicable to all forms of digital imaging. In this initial evaluation, we investigated the clinical utility of this method for image coregistration and assessed its clinical effect on the speed and accuracy of image interpretation. MATERIALS AND METHODS Registration Software The software system we used for CT registration is a prototype developed by Integrated Medical Imaging Systems of Waltham, Mass, and it has been described previously in the literature (7). It runs on a standard Pentium II– based personal computer with 512 MB of memory, in the Linux operating system. A brief description follows. Data input and operation.—A Digital Imaging and Communications in Medicine (DICOM) receiver with associated software runs continuously in the background as a daemon, waiting for DICOM data to be pushed from a DICOM-compliant picture archiving system or directly from a DICOM-compliant CT scanner. DICOM data are automatically stored in a local tree-structured database with fields for patient study, examination series, and image. A point-and-click X Windows interface allows the operator to navigate through the database and select data for registration. The operator designates one series as the “initial study” and the other as the “follow-up study” and then clicks the “register” button. The data are validated in the DICOM database to ensure that the images being reg-

COREGISTRATION OF HEAD CT COMPARISON STUDIES

istered are logically consistent. The software system automatically determines the transformation (translation plus rotation) needed to produce a one-to-one correspondence of section positions and voxels within the initial and follow-up studies by calculating a new image volume for the older study. Registration.—Computing the registration parameters involves a number of steps. Gantry tilt and nonuniform section separation corrections are applied. The optimal dynamic range is determined, relative to brain intensity, and the voxel values are transformed to a representation that preserves the Hounsfield scale, without compression. Since extracranial tissues may differ between scanning sessions (eg, mouth opened or closed, or endotracheal tubes inserted or withdrawn), a fully automated segmentation process removes extracranial structures, including scalp, skull, and meninges, before registration (8). Registration is performed as a two-step process beginning with surface registration as a first approximation. In surface registration, a chamfer-matching algorithm is applied to the brain surfaces determined from the segmentation step discussed above. The registration parameters determined by means of surface fitting initialize an extension of the intensity-matching algorithm, as described elsewhere (8). The final registration parameters are used to produce a new follow-up volume that exactly matches the orientation and section locations of the reference volume. Output and display.—A custom-designed viewing system was developed to allow for analysis of subtraction images. The features of the visualization include (a) simultaneous or separate display of three sections: the initial image, the follow-up image, and the subtraction image; (b) simultaneous measurement of location and intensity at corresponding voxels in the three image sections; (c) separate control of the section, window, and level for each individual section; (d) common control of section, window, and level for all three sections, as an alternative; and (e) the ability to store settings of window and level as named presets to facilitate setup of individual preferences. For the purpose of this evaluation the system included a software switch (for blinded readings) to hide patient demographic information. Evaluation of Registration Speed and Accuracy Registration accuracy and speed were evaluated as described previously (7). Briefly, CT data were selected that were representative of typical clinical cases. Quantitative assessment of registration accuracy was based on manual

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Figure 1. Image coregistration in a pediatric patient with a complex cystic intracranial mass. The clinical question was whether the lesion had changed in size. Differences in scan plane make a one-to-one comparison of (a) selected current images from head computed tomography (CT) and (b) images of the same area obtained 1 month previously nearly impossible and make it very difficult to identify subtle size differences (Fig 1 continues).

measurement of anatomic landmarks observed in the registered image pairs. A series of 12 internal landmarks were located and measured. Registration error was defined as the root mean square of differences in the coordinates of landmarks. Clinical Evaluation Initial and follow-up head CT studies of 14 patients were reviewed. These patients had 34 lesions, including intracranial bleeding (n ⫽ 12), hydrocephalus (n ⫽ 10), stroke (n ⫽ 5), edema (n ⫽ 5), tumor (n ⫽ 1), and an extraaxial collection (n ⫽ 1). A neuroradiologist reviewed the CT study pairs during two readout sessions separated by several days. The images read during the first session were nonregistered, and those read during the second session were coregistered. The reader rated the change in each lesion on a five-point scale (with points 1–5 indicating ⬎ 25% smaller, ⬎ 10% smaller, no change, ⬎ 10% larger, and ⬎ 25% larger, respectively) and recorded the time required to review each case. A few months later, the entire reading (of images with and images without coregistration) was repeated, with an enlarged image data set from 25 patients, including the original 14. This second reading allowed an assessment of intraobserver variability. Each case served its own control through comparison of the nonregistered and coregistered

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results; statistical analysis was performed with the t test. The effects of coregistration on the interpretations were assessed in terms of the time required to read a case and changes in interpretation due to coregistration. An additional reader was then recruited to evaluate the cases blindly and independently, as the first reader had done initially. The ␬ values were determined to assess intraand interobserver variability. Univariate analysis was performed by measuring the reader’s interpretations against benchmark readings by the senior neuroradiologist who compiled and collected the test cases; these interpretations served as the diagnostic standard. RESULTS Evaluation of Registration Speed and Accuracy Registration speed.—The technical performance of the coregistration software has been evaluated previously by Alpert et al (7). After all cases were pooled, the mean registration speed was 109 seconds ⫾ 38. The difference in registration times was due primarily to the number of sections in the volume. Careful visual examination of the registration data indicated that the registration was subjectively excellent in all cases. Subtraction postprocessing performance.—The mean registration accuracy for all in-plane landmarks was 0.87

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Figure 1 (continued). Image coregistration in a pediatric patient with a complex cystic intracranial mass. The clinical question was whether the lesion had changed in size. (c, d) Selected images of the lesion after coregistration show that a one-to-one comparison is now possible, and interpretation is greatly eased. The image quality in d is slightly inferior to that in c, because of manipulation of the older set of images—a small price to pay for the ability to compare the studies easily. We concluded that there was no notable interval change in the size of the cystic lesion. (e) Subtraction images obtained by subtracting images in d from the corresponding images in c. Subtraction would not have been possible in this case without image coregistration.

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Table 1 Effect of Coregistration on the Time Required to Interpret Head CT Studies Time (sec) Reader

Nonregistered Images

Coregistered Images

Difference in Means (%)

P Value

1 2

208.9 ⫾ 79.3 246.4 ⫾ 81.5

147.9 ⫾ 51.2 132.1 ⫾ 55.2

70.8 53.6

.0056 .0015

Note.—Nonregistered studies took significantly longer to interpret in every case.

mm. The three-dimensional error in locating landmarks was about 2.0 mm (7). The larger three-dimensional error is the inevitable consequence of anisotropic imaging, with thicker imaging sections causing a loss of spatial accuracy compared with the higher in-plane resolution. Clinical Interpretation Speed of interpretation.—There were highly significant reductions in the amount of time needed to interpret a case—70.8% for reader 1 and 53.6% for reader 2 (Table 1), with an average time saving of 65.6% per case. The mean time per case, which ranged from 209 to 153 seconds without coregistration, was reduced to 148 –107 seconds with coregistration. The difference was statistically significant for each reader at each reading session. This effect was noted both during the initial readout session and months later, during the second readout session. The time required to interpret each case was slightly less during the second readout session, probably due to greater reader experience with the computer user interface. Accuracy of interpretation.—Coregistration changed the results of the interpretation of a lesion in 37.5% of cases for reader 1 and in 6.3% of cases for reader 2, for an average changed reading of 21.9% at the first reading for both readers (Fig 2). Reader 1 changed 28.1% of readings by one point and 9.4% by two points; reader 2 changed 6.3% of interpretations by one point. At the second pair of readout sessions (of nonregistered images and of coregistered images) for reader 1, coregistration changed the results of the interpretation of a lesion in 44.8% of cases. Most of the changed interpretations differed by one point on the five-point scale used (one-point difference, 34.5%; two-point difference, 8.6%; three-point difference, 1.7%) (Fig 3). Statistical analysis with the simple ␬ statistic showed that reader 1 had an intraobserver variability of 0.2227

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Figure 2. The magnitude of the difference in interpretation of lesion size as a result of image coregistration. Changed and unchanged readings are shown with the difference between nonregistered and coregistered images as a percentage of total readings. ⽧ ⫽ reader 1, ▫ ⫽ reader 2.

Figure 3. The magnitude of the difference in interpretation of lesion size, as a result of image coregistration, by reader 1 at the time of the second pair of readout sessions. These data are directly comparable to those in Figure 2; note the similar slopes to the curve for reader 1.

for nonregistered images. For coregistered images, intraobserver variability was 0.5474 (Table 2). The interobserver variability was 0.2670 for nonregistered images and 0.3309 for coregistered images (Table 2). A comparison of weighted ␬ statistics for reader 1’s performance consistency between the two paired readout sessions shows that the reader’s interpretation was most consistent with the coregistered images. The ␬ values were 0.3554 for nonregistered images and 0.7328 for coregistered images, indicating a decrease in intraobserver variability with coregistration. When reader 1’s interpretations of nonregistered images and of coregistered images within the consecutive readout sessions were compared

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Table 2 Simple ␬ Statistic Values for Inter- and Intraobserver Comparisons

␬ Statistic

Comparison Reader 1 Reading 1 (non- vs coregistered) Reading 2 (non- vs coregistered) Reading 1 vs reading 2 Nonregistered Coregistered Reader 2 (non- vs coregistered) Reader 1 vs reader 2 Nonregistered Coregistered

0.4431 0.3251 0.2227 0.5474 0.9150 0.2670 0.3309

Table 3 Univariate Analysis of Readers’ Divergence from the Reference Reading with and without Coregistration Mean Divergence* Reader

Nonregistered Images

Coregistered Images

1 (reading 1) 1 (reading 2) 2

⫺0.16129 (.2824) 0.16129 (.2016) ⫺0.1935484 (.2059)

0 (1.0) 0.064516 (.67997) ⫺0.1935484 (.2059)

*P values for difference from 0 are given in parentheses.

for consistency, the ␬ values were 0.5896 and 0.4480. These intermediate values are not directly comparable to each other but also point to the effects of coregistration in improving intraobserver consistency. Univariate analysis was performed to compare the readers’ interpretations with a reference reading (Table 3). The mean agreement with the reference reading either improved or, in one case, remained unchanged. While these differences did not achieve statistical significance, they nonetheless point to an enhanced uniformity of interpretation with coregistration. DISCUSSION Image coregistration is technically easy to implement, given the ready availability of the required computer equipment, the near universality of the DICOM standard, and the growing popularity of digital images over film images. The user interface places relatively low demands on personnel, and registration of images should be well within the capabilities of technologists and other support personnel. Our results indicate that about a minute of computer

time is required to coregister a head CT image acquired without contrast material and a comparison image (7)—little enough to allow routine use in day-to-day practice. With near-continuous advances in computer technology, the time required to register images should become even shorter. The performance of the postprocessing algorithms is robust, with a three-dimensional inaccuracy of only 2 mm with standard clinical data sets (7). This error is an unavoidable consequence of image manipulation and stems from the uncertainties introduced when nonidentical source images are manipulated into alignment. Theoretically, thinner sections would increase the amount of information in the source images, allowing more precise registration, but this improvement would be at the expense of increased radiation dose to the patient. The effects of registration were appreciable on the manipulated images but were never perceived as a diagnostic hindrance. In our implementation, the older image was always manipulated to conform with the current study, which was left in its original form. This served to minimize the effects on interpretation. In a clinical system, one could anticipate having free access to both the registered images and the raw data set, should questions arise. The amount of time spent assessing images with coregistration is less by an average of 65.6% than that for traditional methods of comparison. The differences were statistically significant in every instance. Readers reported subjectively finding coregistered images faster and easier to interpret with increased confidence. This finding alone should make image coregistration a valuable tool in dayto-day practice. Coregistration changed the reader’s interpretation in about a quarter of cases on average. This is likely a higher proportion than would be expected for a regular mix of cases, because of selection bias for the difficult cases in our sample. Our data indicate improvement in intra- and interobserver variability with coregistration and improved correlation with a reference reading. Image coregistration may also lead to interesting new future applications, such as image subtraction (Fig 1e), which is not possible without the use of coregistration technology. In conclusion, image coregistration is technically feasible and robust, with little introduction of error. The technique could be incorporated into an electronic radiologic practice with little modification of existing equipment or workflow. We found that coregistration of follow-up head CT studies significantly reduced the amount of time needed for comparison and interpretation.

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Coregistration does not detract from the accuracy of interpretation of follow-up studies but instead serves to reduce intra- and interobserver variability. A nonsignificant trend toward improved accuracy was demonstrated. Our experience indicates that image coregistration could be welcome in clinical use even for experienced radiologists. The benefits to less experienced radiologists or nonradiologists might be even greater than those demonstrated in our research. REFERENCES 1. Pelizzari CA, Chen GT, Spelbring DR, Weichselbaum RR, Chen CT. Accurate three-dimensional registration of CT, PET, and/or MR images of the brain. J Comput Assist Tomogr 1989; 13:20 –26.

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2. Alpert NM, Bradshaw JF, Kennedy D, Correia JA. The principal axes transformation: a method for image registration. J Nucl Med 1990; 31: 1717–1722. 3. Woods RP, Mazziotta JC, Cherry SR. MRI-PET registration with automated algorithm. J Comput Assist Tomogr 1993; 17:536 –546. 4. Ardekani BA, Braun M, Hutton BF, Kanno I, Iida H. A fully automatic multimodality image registration algorithm. J Comput Assist Tomogr 1995; 19:615– 623. 5. Wells WM III, Viola P, Atsumi H, Nakajima S, Kikinis R. Multi-modal volume registration by maximization of mutual information. Med Image Anal 1996; 1:35–51. 6. Ashburner J, Friston K. Multimodal image coregistration and partitioning: a unified framework. Neuroimage 1997; 6:209 –217. 7. Alpert NM, Berdichevsky D, Levin Z, Thangaraj V, Gonzalez G, Lev MH. Performance evaluation of an automated system for registration and postprocessing of CT scans. J Comput Assist Tomogr 2001; 25:747– 752. 8. Alpert NM, Berdichevsky D, Levin Z, Morris ED, Fischman AJ. Improved methods for image registration. Neuroimage 1996; 3:10 –18.