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Evaluation of Accuracy and Precision of Manual Size Measurements in Chest Tomosynthesis using Simulated Pulmonary Nodules

Rationale and Objectives

To investigate the accuracy and precision of pulmonary nodule size measurements on chest tomosynthesis images.

Materials and Methods

Artificial ellipsoid-shaped nodules with known sizes were inserted in clinical chest tomosynthesis images. The volume of the nodules corresponded to that of a sphere with a diameter of 4.0, 8.0, or 12.0 mm. Four thoracic radiologists were given the task to determine the longest diameter of the nodules. All nodules were measured twice. Measurement accuracy in terms of the mean measurement error was determined. Intraobserver and interobserver variabilities, as well as variability because of differences between nodules and their locations, were used as measures of precision.

Results

The mean measurement error ranged from −0.3 to 0.1 mm for the nodule size groups and observers. Of the smallest nodules, the observers found 7–17 of total 50 nodules nonmeasurable. The intraobserver and interobserver variabilities were of similar magnitude, indicating relatively small differences between the observers. The internodule variability was in general larger, indicating that the different characteristics of the nodules and their location are sources of variability.

Conclusions

The results suggest a high accuracy and precision for manual measurements of the nodules in chest tomosynthesis images. However, small nodules (<5.0 mm) may be difficult to measure at all because of poor visibility.

Pulmonary nodules are common incidental findings from chest and cardiac computed tomography (CT) examinations . As indicators of malignancy for these lesions, nodule size and growth are important factors . The Fleischner society has proposed a generally accepted management strategy for the follow-up of indeterminate nodules, which is based on repeated CT examinations at certain time intervals, depending on the size of the nodule when it is detected . If a significant size increase in the nodule over time is detected in the images, further diagnostic investigations are initiated. Similar recommendations can be found in the Response Evaluation Criteria In Solid Tumors (RECIST) guidelines concerning the evaluation of treatment response for tumors and metastases . The noninvasive nature of the technique and the high conspicuity of lesions in the images make CT scanning a suitable choice for follow-up. However, repeated CT scans raise concerns regarding the patient radiation dose burden .

Chest tomosynthesis has relatively recently emerged as an interesting alternative modality in lung imaging . The technique allows imaging of the chest in section images at a radiation dose substantially lower than in the case with chest CT . The financial cost for a chest tomosynthesis examination is also, in general, lower than that for a chest CT examination. Additionally, patient throughput is higher for the chest tomosynthesis examinations . Although the depth resolution of chest tomosynthesis is limited compared to CT, previous studies have shown that a relatively large amount of pulmonary nodules visible on CT images are detectable on chest tomosynthesis images . Furthermore, and of even higher importance for the present study, in the study by Vikgren et al. all nodules with a longest diameter larger than 6 mm confirmed on CT were deemed visible in retrospect by tomosynthesis. This indicates the potential of using tomosynthesis for follow-up of already detected nodules.

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Materials and methods

Image Collection

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Nodule Simulation

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Nodule Insertion

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Measurement Study

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Figure 1, Cutouts from reconstructed chest tomosynthesis section images included in the measurement study showing an example of simulated nodules from the three different size groups corresponding to each other in terms of the ratio between the lengths of the major and minor axes, amount of applied rotation, and location in the lung. The longest diameters of the nodules are (a) 4.3 mm, (b) 8.6 mm, and (c) 12.9 mm.

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Data Analysis

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Results

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Table 1

Number of Nodules Judged as Nonmeasurable, Mean Measurement Error, and Mean Relative Measurement Error for Each Observer for the Three Different Size Groups

Parameter Observer 1 Observer 2 Observer 3 Observer 4 4.0 mm N nonmeasurable 15 16 17 7 Mean error (mm) −0.2 (−0.3, 0.0) 0.0 (−0.1, 0.2) −0.2 (−0.3, 0.0) −0.3 (−0.5, −0.2) Mean relative error (%) −3.3 (−6.5, 0.0) 0.5 (−2.7, 3.7) −3.3 (−6.2, −0.5) −7.2 (−10.4, −4.0) 8.0 mm N nonmeasurable 1 3 2 — Mean error (mm) −0.2 (−0.4, 0.0) 0.1 (−0.1, 0.2) −0.2 (−0.4, 0.0) −0.2 (−0.4, 0.0) Mean relative error (%) −1.8 (−3.9, 0.2) 0.6 (−0.8, 2.0) −2.3 (−4.4, −0.1) −2.0 (−3.8, −0.2) 12.0 mm N nonmeasurable — — — — Mean error (mm) −0.1 (−0.2, 0.0) −0.1 (−0.2, 0.1) −0.1 (−0.2, 0.0) 0.1 (0.0, 0.2) Mean relative error (%) −0.5 (−1.2, 0.1) −0.5 (−1.4, 0.5) −0.7 (−1.6, 0.2) 0.6 (−0.2, 1.5)

Data in parentheses are 95% confidence intervals.

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Figure 2, Measurement error for all observers for nodules corresponding in volume to a sphere with a diameter of (a) 4 mm, (b) 8 mm, and (c) 12 mm. Nodules with the same number in the three different nodule size groups were located at identical positions in the images.

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Table 2

Intraobserver Variability Expressed as the Standard Deviation of the Two Measurements on Each Nodule, Both in Absolute Terms and Relative to the Actual Size of the Nodules, Averaged Over all Nodules in Each Size Group for Each Observer

Parameter Observer 1 Observer 2 Observer 3 Observer 4 4.0 mm Intraobserver variability (mm) 0.2 (0.1, 0.2) 0.4 (0.3, 0.5) 0.2 (0.2, 0.3) 0.3 (0.2, 0.4) Intraobserver variability (%) 3.6 (2.3, 5.0) 7.7 (5.4, 9.9) 5.3 (3.5, 7.1) 6.1 (4.4, 7.8) Intraclass correlation coefficient 0.92 (0.83, 0.96) 0.71 (0.32, 0.87) 0.83 (0.57, 0.93) 0.81 (0.62, 0.90) 8.0 mm Intraobserver variability (mm) 0.2 (0.1, 0.3) 0.3 (0.2, 0.3) 0.2 (0.2, 0.3) 0.3 (0.2, 0.4) Intraobserver variability (%) 2.0 (1.4, 2.7) 2.8 (2.1, 3.4) 2.4 (1.7, 3.1) 3.0 (2.3, 3.8) Intraclass correlation coefficient 0.94 (0.89, 0.97) 0.91 (0.84, 0.95) 0.95 (0.90, 0.97) 0.92 (0.86, 0.96) 12.0 mm Intraobserver variability (mm) 0.2 (0.1, 0.2) 0.3 (0.3, 0.4) 0.2 (0.2, 0.3) 0.4 (0.2, 0.5) Intraobserver variability (%) 1.1 (0.9, 1.4) 2.4 (1.9, 2.9) 1.5 (1.1, 1.8) 2.7 (1.7, 3.7) Intraclass correlation coefficient 0.99 (0.98, 0.99) 0.94 (0.89, 0.96) 0.98 (0.96, 0.99) 0.87 (0.78, 0.93)

Data in parentheses are 95% confidence intervals.

Table 3

Interobserver Variability Expressed as the Standard Deviation of the Measurements, Both in Absolute Terms and Relative to the Actual Size of the Nodules, by all Observers on Each Nodule, Averaged Over all Nodules in Each Size Group

Parameter 4 mm 8 mm 12 mm Interobserver variability (mm) 0.2 (0.2, 0.3) 0.3 (0.2, 0.4) 0.3 (0.2, 0.4) Interobserver variability (%) 5.3 (4.1, 6.5) 3.3 (2.4, 4.2) 2.1 (1.7, 2.5) Intraclass correlation coefficient 0.91 (0.82, 0.96) 0.93 (0.88, 0.96) 0.97 (0.96, 0.98)

Data in parentheses are 95% confidence intervals.

Table 4

Internodule Variability, Expressed as the Standard Deviation of the Measurement Error, Both in Absolute Terms and Relative to the Actual Size of the Nodule, for all Nodules in Each Size Group for Each Observer

Parameter Observer 1 Observer 2 Observer 3 Observer 4 4.0 mm Internodule variability (mm) 0.4 (0.3, 0.5) 0.4 (0.3, 0.6) 0.4 (0.3, 0.5) 0.5 (0.4, 0.6) Internodule variability (%) 9.0 (7.2, 11.9) 9.0 (7.2, 11.9) 7.9 (6.3, 10.5) 9.5 (7.8, 12.4) 8.0 mm Internodule variability (mm) 0.7 (0.6, 0.9) 0.4 (0.4, 0.6) 0.7 (0.6, 0.8) 0.6 (0.5, 0.7) Internodule variability (%) 7.2 (6.0, 9.0) 4.8 (4.0, 6.0) 7.2 (6.0, 9.1) 6.2 (5.2, 7.8) 12.0 mm Internodule variability (mm) 0.3 (0.3, 0.4) 0.5 (0.4, 0.6) 0.4 (0.4, 0.5) 0.4 (0.4, 0.5) Internodule variability (%) 2.3 (1.9, 2.9) 3.3 (2.7, 4.1) 3.1 (2.6, 3.9) 3.0 (2.5, 3.7)

Data in parentheses are 95% confidence intervals.

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Discussion

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