Segmentation of lung lobes in volumetric CT images for surgical planning of treating lung cancer

Can preoperative computed tomography of the chest predict completeness of the major pulmonary fissure at surgery?

BACKGROUND

An incomplete major pulmonary fissure can make anatomic lung resection technically more difficult and may increase the risk of complications, such as prolonged postoperative air leak. The objective of this study was to determine if preoperative computed tomography (CT) of the chest could accurately predict the completeness of the major pulmonary fissure observed at the time of surgery.

METHODS

From October 2008 to June 2009, patients at a single university institution were enrolled if they underwent surgery for a pulmonary nodule, mass or known cancer. At the time of surgery, completeness of the major pulmonary fissure was graded 1 if pulmonary lobes were entirely separate, 2 if the visceral cleft was complete with an exposed pulmonary artery at the base with some parenchyma fusion, 3 if the visceral cleft was only evident for part of the fissure without a visible pulmonary artery and 4 if the fissure was absent. The preoperative CT scan of each patient was graded by a single, blinded chest radiologist using the same scale. We used the Pearson χ2 test with 2-tailed significance to test the independence of the operative and radiologic grading.

RESULTS

In 48% (29 of 61) of patients, the radiologic and operative grading were the same. Of those graded differently, 94% (30 of 32) were within 1 grade. Despite this agreement, we observed no statistically significant correlation between the operative and radiologic grading (p = 0.24).

CONCLUSION

The major fissure can often be well-visualized on a preoperative CT scan, but preoperative CT cannot accurately predict the completeness of the major pulmonary fissure discovered at surgery.

Lower-lobe shrinkage relative to total lung volume in collagen vascular diseases

PURPOSE

It has been reported that the prognosis differs between patients who have collagen vascular diseaseassociated interstitial pneumonia (CVD-IP) and those with idiopathic IP (IIP). In this study, chest computed tomography (CT) findings were compared between patients with CVD-IP and IIP.

MATERIALS AND METHODS

A retrospective analysis was performed of 47 consecutive patients (23 with CVD-IP and 24 with IIP). The lower-lobe volume (LLV), total lung volume (TLV), and their ratio (LLV/TLV) were determined by volumetry using three-dimensional computed tomography (CT).

RESULTS

There was no significant difference of the LLV/TLV ratio between the CVD-IP and IIP groups. However, the LLV/TLV ratio was <0.33 in 9/23 patients with CVD-IP versus 2/24 patients with IIP, and there was a significant difference in the percentage of patients with a ratio<0.33 between the CVD-IP and IIP groups (p = 0.01). The LLV/TLV ratio was not influenced by the severity of lung disease.

CONCLUSIONS

Measuring the LLV/TLV ratio by threedimensional CT can help distinguish between CVD-IP and IIP at initial diagnosis, especially in patients with CVD-IP who have pulmonary involvement before other organ diseases and symptoms caused by CVD.

Automatic segmentation of the lungs using robust level sets

This paper presents a method for the automatic segmentation of the lungs in X-ray computed tomography (CT) images. The proposed technique is based on the use of a robust geometric active contour that is initialized around the lungs, automatically splits in two, and performs outlier rejection during the curve evolution. The technique starts by grey-level thresholding of the images followed by edge detection. Then the edge connected points are organized into strokes and classified as valid or invalid. A confidence degree (weight) is assigned to each stroke and updated during the evolution process with the valid strokes receiving a high confidence degree and the confidence degrees of the outlier strokes tending to zero. These weights depend on the distance between the stroke points and the curve and also on the stroke size. Initialization of the curve is fully automatic. Experimental results show the effectiveness of the proposed technique.

Segmentation of lung lobes in isotropic CT images using wavelet transformation

Advanced multi-slice CT scanners produce isotropic CT images, which have pixel dimensions equal to their image thicknesses of 0.6 mm. Comparing to clinical standard CT images with a thickness of 2.5 - 7.0 mm, isotropic CT images have clearly visible lobar fissures. This poses a challenge for developing automatic algorithms to identify the fissure locations and curvatures. This paper presents a wavelet algorithm that allows automatic identification of the left and right oblique fissures, as well semi-automatic identification of the horizontal fissures. This algorithm took a two-stage approach: (a) adaptive fissure sweeping to find fissure regions; and (b) wavelet transform to identify the fissure locations and curvatures within these fissure regions. Tested on 8, 6 and 6 stacks of isotropic CT images for the left oblique, right oblique and horizontal fissures, respectively, the algorithm yielded an accuracy of 77.1 - 93.6% with strict evaluation criteria. This provides promising potential for developing an automatic algorithm to segment lung lobes.