Automated Detection of Polyps from Multi-slice CT Images using 3D Morphologic Matching Algorithm: Phantom Study

Transcription

1 Automated Detection of Polyps from Multi-slice CT Images using 3D Morphologic Matching Algorithm: Phantom Study Yonghum Na, Jin Sung Kim, Bruce R Whiting, K. Ty Bae Electronic Radiology Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, Korea Advanced Institute of Science and Technology, Korea, Daejeon, ABSTRACT A colon polyp phantom, 28 cm long and 5 cm in diameter, was constructed by inflating a latex ultrasound transducer cover. Four round pieces of ham (3, 6, 9, 12 mm diameter) were imbedded in the outer membrane surface of the phantom and then were tied by string at the base to simulate pedunculated polyps. Three more pieces of ham (3, 6, 9 mm) were impressed and taped on the outer surface to simulate sessile polyps. The circumference of the phantom was constricted by string at four evenly spaced locations to simulate haustral folds. The phantom was placed in a water bath and was modified by infusing water into the lumen or by partially deflating the lumen, and then rescanned. CT images were obtained in a multi-slice CT (4x1 mm collimation, 0.5s scan, 120 Kvp, 90 mas, 1 mm slice thickness). CT images were processed with our computer-aided detection program. First, the three-dimensional colonic boundary and inner structure were segmented. From this segmented region, soft-tissue structures were extracted and labeled to generate candidates. Shape features were evaluated along with geometric constraints. Three-dimensional region-growing and morphologic matching processes were applied to refine and classify the candidates. The detected polyps were compared with the true polyps in the phantom or known polyps in clinical cases to calculate the sensitivity and false positives. Keywords: colon, pedunculated polyp, sessile polyp, CAD, 3D region-growing, 3D morphological matching 1. INTRODUCTION Colon cancer is the second leading cause of cancer deaths in the United States 1. Detecting colonic polyps from CT images is a tedious, demanding task. We have developed an automated computer-aided-diagnosis (CAD) program that takes advantage of 3D volumetric data 2, 3. The performance of this program was tested on a colon polyp phantom. We postulated that a realistic colon polyp phantom provide an ideal setting to evaluate the best scenario of the performance of the CAD program. 2. MATERIALS AND METHODS The overall scheme of our 3DMM (Morphological Matching) CAD (Computer Aided Diagnosis/Detection) is shown in Figure 1. CT images were obtained from multi-slice CT with scan parameters (4x1 mm collimation, 0.5s scan, 120 Kvp, 90 mas, 1 mm slice thickness). Air-filled structures, colon, small bowel, and lung were isolated by means of thresholding CT images. The threshold value was determined by taking the average of the air and soft-tissue CT attenuation values. From the segmented air-filled structures, regions representing the colon were segmented by region growing and by applying 3D connectivity, location and volume criteria. The soft-tissue structures along the wall of and within the colon that represent folds and polyps were segmented by means of morphological filtering. These soft-tissue structures were stacked to generate a 3D volumetric database 4. Each connected soft-tissue structure was labeled to Medical Imaging 2003: Image Processing, Milan Sonka, J. Michael Fitzpatrick, Editors, Proceedings of SPIE Vol (2003) 2003 SPIE /03/$

2 represent a polyp candidate. 3D region-growing and morphologic matching processes were applied to refine the candidates. Shape properties such as curvatures, compactness, and elongation factor were calculated for each candidate 5-7. Geometric properties and constraints such as size and locations from the wall and center of the colon were computed. Cost function was calculated from the shape and geometric properties of each candidate. A fuzzy-rule based determinant was applied to classify the polyp candidates. Finally, the detected polyps were compared with the true polyps in the phantom to calculate the sensitivity and false positive. CT images Colon Region Segmentation Generation of a 3D Volumetric Database from the Segmented Softtissue Structures along the Wall of and Within the Colon Region Region Growing and 3D Morphological Matching Filter Shape Features and Geometric Constraints Fuzzy-rule based Determinant and Classification Polyps Detection Figure 1. Overall scheme of automated polyp detection program A colon polyp phantom, 28 cm long and 5 cm in diameter, was constructed by inflating a latex ultrasound transducer cover. Four round pieces of ham (3, 6, 9, 12 mm diameter) were imbedded in the outer membrane surface of the phantom and then were tied by string at the base to simulate pedunculated polyps. Three more pieces of ham (3, 6, 9 mm) were impressed and taped on the outer surface to simulate sessile polyps8. The circumference of the phantom was constricted by string at four evenly spaced locations to simulate haustral folds. The phantom was placed in a water bath. The structure of the phantom was also modified by inflating the phantom partially, by infusion of water into the lumen to simulate air-fluid levels within the lumen, or by infusion of diluted iodinated-contrast medium into the lumen to simulate enteric contrast enhancement. Four different conditions were generated: (1) fully inflated colon; (2) fully inflated colon with water within the lumen; (3) fully inflated colon with diluted contrast media within the lumen; (4) partially inflated colon. The phantom within a water bath was placed on the CT table with the long axis of the phantom aligned parallel or 60º oblique with the direction of the table movement. CT images were obtained using a spiral CT scan protocol (4x1 mm collimation, 0.5s scan, 120 Kvp, 90 mas, 1 mm slice thickness) in a multi-detector row CT scanner (Somatom Plus 4 VolumeZoom, Siemens Medical Systems, Iselin, NJ). The CT images were electronically 878 Proc. of SPIE Vol. 5032

3 transferred to a workstation and processed with our CAD program. The detected structures were reviewed and compared with the truth. (a) (b) (c) Figure 2. (a) Colon phantom with a syringe and extension tubing that were connected to the lumen for inflation of the phantom or infusion of fluid into the lumen. The size of the phantom is compared with that of a dime and nickel. (b) Closed-up view of the phantom showing one of simulated sessile polyps. The size of this polyp is 7mm in diameter. (c) Closed-up view of the phantom showing one of simulated sessile polyps. The size of this polyp is 3 mm in diameter. 3. RESULTS and DISSCUSSION All polyps were detected by our CAD program from the CT images of the fully-inflated colon phantom. One polyp, 6 mm sessile polyp, was not detected in three situations: fully-inflated phantom but containing water, fully-inflated phantom but containing diluted contrast medium, and fully-inflated but obliquely positioned phantom. No false positive was detected in these three situations. Two polyps, 6mm and 9mm sessile polyps, were not detected in partially-inflated phantom CT images. Two false positives were observed. The detection of the simulated polyps by the CAD program was summarized in Table 1. As expected, the performance of our CAD program was best with the fully-inflated, dry phantom, which indicates the importance of adequate inflation and proper cleansing of the colon in polyp detection. Table 1. Detection of simulated colon polyps at different conditions S P S P S P P 3mm 3mm 6mm 6mm 9mm 9mm 12mm FP FN TP Sensitivity Fully-inflated O O O O O O O 7/7 100% Fully-inflated, containing water O O X O O O O 1/7 6/7 85.7% Fully-inflated, containing dilute contrast O O X O O O O 1/7 6/7 85.7% Partially-inflated O O X O X O O 2 2/7 5/7 71.4% Fully-inflated, obliquely placed O O X O O O O 1/7 6/7 85.7% (S: Sessile polyp, P: Pedunculated polyp, FP: False positive, FN: False negative, O: Detected polyp, X: Missed polyp) Proc. of SPIE Vol

4 Figure 3. 3D volumetric and transaxial CT images of phantom colon polyps Figure 3. 3D volumetric and transaxial CT images of phantom colon polyps 4. CONCLUSIONS Evaluation of a CAD program on a phantom is important to test the best scenario performance of the CAD program. A phantom can also be used to compare the performance of different CAD programs. We can easily modify the structure of a phantom to generate different conditions or increase complexity of detection. Highly accurate detection of simulated polyps was achieved by our CAD program in an ideal or close to an ideal situation. Detection rate was affected by the degree of inflation and the presence of fluid. In a limited clinical study, the performance of our CAD program was very promising. We are continuously testing our CAD program on clinical cases. 5. REFERENCES 1. O Brien MJ, Winawer SJ, Zauber AG, et al. The national polyp study: patient and polyp characteristics associated with high-grade dysplasia in colorectal adenomas. Gastroenterology 1990; 98: Proc. of SPIE Vol. 5032

5 2. Yoshida H, Masutani Y, MacEneaney P, Rubin D, Dachman AH. Computerized detection of colonic polyps in CT colonography based on volumetric features: a pilot study. Radiology 2002; 222: Yoshida H, Na ppi J. Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps. IEEE Trans Med Imaging 2001; 20: McFarland EG, Brink JA, Loh J, et al. Visualization of colorectal polyps with spiral CT colonography : evaluation of processing parameters with perspective volume rendering. Radiology 1997; 205: Paik DS, Beaulieu CF, Jeffrey RB, Karadi C, Napel S. Detection of polyps in CT colonography: a comparison of a computer-aided detection algorithm to 3D visualization methods (abstr). Radiology 1999; 213(P): Summers RM, Beaulieu CF, Pusanik LM, et al. Automated polyp detector for CT colonography: feasibility study. Radiology 2000; 216: Summers RM, Hara AK, Luboldt W, Johnson CD. Computed tomographic and magnetic resonance colonography: summary of progress from 1995 to Curr Prob Diagn Radiol 2001; 30: C. D. Jonson and A. H. Dachman, CT colonography: The next colon screening examination? Radiology, vol. 216, pp , Proc. of SPIE Vol