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MDCT for Computerized Volumetry of Pneumothoraces in Pediatric Patients

Rationale and Objectives

Our purpose in this study was to develop an automated computer-aided volumetry (CAV) scheme for quantifying pneumothorax in multidetector computed tomography (MDCT) images for pediatric patients and to investigate the imaging parameters that may affect its accuracy.

Materials and Methods

Fifty-eight consecutive pediatric patients (mean age 12 ± 6 years) with pneumothorax who underwent MDCT for evaluation were collected retrospectively for this study. All cases were imaged by a 16- or 64-MDCT scanner with weight-based kilovoltage, low-dose tube current, 1.0−1.5 pitch, 0.6−5.0 mm slice thickness, and a B70f (sharp) or B31f (soft) reconstruction kernel. Sixty-three pneumothoraces ≥1 mL were visually identified in the left ( n = 30) and right ( n = 33) lungs. Each identified pneumothorax was contoured manually on an Amira workstation V4.1.1 (Mercury Computer Systems, Chelmsford, MA) by two radiologists in consensus. The computerized volumes of the pneumothoraces were determined by application of our CAV scheme. The accuracy of our automated CAV scheme was evaluated by comparison between computerized volumetry and manual volumetry, for the total volume of pneumothoraces in the left and right lungs.

Results

The mean difference between the computerized volumetry and the manual volumetry for all 63 pneumothoraces ≥1 mL was 8.2%. For pneumothoraces ≥10 mL, ≥50 mL, and ≥200 mL, the mean differences were 7.7% ( n = 57), 7.3% ( n = 33), and 6.4% ( n = 13), respectively. The correlation coefficient was 0.99 between the computerized volume and the manual volume of pneumothoraces. Bland-Altman analysis showed that computerized volumetry has a mean difference of -5.1% compared to manual volumetry. For all pneumothoraces ≥10 mL, the mean differences for slice thickness ≤1.25 mm, = 1.5 mm, and = 5.0 mm were 6.1% ( n = 28), 3.5% ( n = 10), and 12.2% ( n = 19), respectively. For the two reconstruction kernels, B70f and B31f, the mean differences were 6.3% ( n = 42, B70f) and 11.7% ( n = 15, B31f), respectively.

Conclusion

Our automated CAV scheme provides an accurate measurement of pneumothorax volume in MDCT images of pediatric patients. For accurate volumetric quantification of pneumothorax in children in MDCT images by use of the automated CAV scheme, we recommended reconstruction parameters based on a slice thickness ≤1.5 mm and the reconstruction kernel B70f.

Pneumothorax is a potentially life-threatening condition which can occur in up to 20% of pediatric patients who suffer from chest trauma . The early detection and accurate measurement of the size of pneumothorax play an important role in proper management of pediatric patients who have pneumothorax. Failure to identify even a small pneumothorax, which may potentially enlarge rapidly and result in cardiopulmonary compromise, can lead to detrimental consequences, including death.

Although chest radiography has been used as an initial imaging modality for evaluating pneumothorax in children, it has been reported that the false-negative rate of detecting pneumothorax on chest radiographs can be as high as 50% . Studies found that the estimation of pneumothorax size on chest x-ray is inaccurate and inconsistent . Multidetector computed tomography (MDCT), which provides the gold standard for detecting occult traumatic pneumothorax , also provides an imaging modality for more accurate diagnosis and quantification of pneumothorax.

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Material and methods

Institutional Review Board Approval

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Study Patients

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MDCT Imaging

Patient Preparation

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MDCT Imaging Technique

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Computerized Volumetry of Pneumothorax

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Extraction of Pleural Region

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Figure 1, Pleural region geometric modeling (PR-GM) for extraction of the entire pleural region. (a) Rib structures within an axial slab are projected on the medial slice: the ribs on the medial slice are marked in red , whereas green and blue indicate the ribs in the upper half and lower half of the slab, respectively. (b) A ray is shot from the center of the slice for estimating the inner pleural contour by use of the intersection with ribs from the current slice or neighboring slices within the slab. (c) One axial slice with subcutaneous emphysema. (d) Pleural curve built by the intersection points with rib structures successfully excludes these subcutaneous air pockets from the pleural region.

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Detection of Pneumothoraces

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Figure 2, The computer-aided volumetry scheme for pneumothoraces. (a) One axial slice of chest computed tomography scan. (b) Lung region was segmented, and the homogeneous air regions were detected as the pneumothorax candidates. (c) Pneumothorax candidates were segmented by dynamic-threshold level-set method. Pneumothoraces in the right lung region are marked in green, whereas those in the left lung are marked in red. (d) Contours of the segmented pneumothoraces.

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Segmentation of Pneumothoraces

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Figure 3, Pneumothorax segmentation by use of the dynamic-threshold (DT) level-set method. (a) The propagation shell consists of an inner shell, an outer shell, and a medial axis. The medial axis is controlled by a DT speed function that is set based on the histogram in the shell. (b) The resulting contour (medial axis) delineates the boundary of the segmented pneumothorax.

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Volumetry of Pneumothoraces

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Figure 4, An example of the computer-aided volumetry (CAV) scheme for the quantification of pneumothorax on a 12-year-old male patient with metastatic angiosarcomas, who had pneumothorax after pleural biopsy. (a) The pneumothoraces in the right and left lung cavity detected and segmented by our CAV scheme were 741.18 mL and 63.50 mL, respectively. (b) One of the axial images: the resulting pneumothoraces were contoured.

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Figure 5, The user interface of the computer-aided volumetry scheme for quantification of pneumothoraces, which was integrated into a V3D-Explorer platform (Viatronix, Inc., Stony Brook, NY).

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Data Analysis

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Results

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Figure 6, Histogram shows the distributions of volumetric sizes of 63 pneumothoraces ≥1 mL in the study.

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Figure 7, The scatter graph plots the measurements from the manual volumetry and computerized volumetry of pneumothoraces. In total, there were 63 pneumothoraces in the reference standard. (a) The associated regression line demonstrated that the two groups of measurements were highly correlated. (b) Plot shows the difference of volumes against the average volume after log e transformation superimposed with 95% limits of agreement.

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Table 1

Relative Differences for 57 Pneumothoraces ≥10 mL

Category Mean Value 95% CI Pneumothorax size ≥10 mL 7.7% (n = 57) (5.75−9.62%) ≥50 mL 7.3% (n = 33) (5.10−9.53%) ≥200 mL 6.4% (n = 13) (3.29−9.66%) Slice thickness ≤1.25 mm 6.1% (n = 28) (4.24−7.94%) 1.5 mm 3.5% (n = 10) (1.97−5.13%) 5.0 mm 12.2% (n = 19) (7.79−16.65%) Reconstruction kernels B70f 6.3% (n = 42) (4.46−8.08%) B31f 11.7% (n = 15) (6.75−16.58%)

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Table 2

Performance of Visual Assessment Based on the Pneumothorax Volumes

Minimum (mL) Maximum (mL) Mean (mL) Small ( n = 24) 1.01 151.19 31.89 Medium ( n = 16) 1.67 334.92 75.46 Large ( n = 23) 9.17 771.80 264.37

Figure 8, The performance of the three-scaled visual assessment of pneumothoraces. (a) Visual assessment versus volumetric size. (b) Visual assessment vs. pneumothorax percentage of lung region.

Table 3

Performance of Visual Assessment Based on the Percentages of Pneumothoraces Compared to Lung Region

Minimum (%) Maximum (%) Mean (%) Small ( n = 24) 0.07 9.22 1.54 Medium ( n = 16) 0.59 8.04 3.76 Large ( n = 23) 4.26 45.75 14.20

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Discussion

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