Effect of investigator experience in CT colonography

Abstract. The aim of this study was to determine the impact of the learning curve on the diagnostic performances of CT colonography. Two blinded teams, each having a radiologist and gastroenterologist, prospectively examined 50 patients using helical CT scan followed by colonoscopy. Intermediate data evaluation was performed after 24 data sets (group 1) and compared with data from 26 subsequent patients (group 2). Parameters evaluated included sensitivity, specificity, false-positive and false-negative findings, time of data acquisition and interpretation. Using colonoscopy as the gold standard, sensitivity for CT colonography was for lesions >5 mm 63% for both teams for group 1 patients; for group 2 patients sensitivity was 45% for team 1 and 64% for team 2. Specificity per patients was for patient group 1 42% for team 1 and 58% for team 2; for patient group 2 it was 79% for both teams (p=0.04 for team 1; p=0.2 for team 2). Comparing group 1 with group 2, the number of false-positive findings decreased significantly (p=0.02). Furthermore, the mean time of data evaluation decreased from 45 to 17 min (p=0.002) and the mean time of data acquisition from 19 to 17 min. With increasing experience, specificity and the time required for data interpretation improved and false positives decreased. There was no significant change of sensitivity, false-negative findings and time of data acquisition. A minimum experience of the readers is required for data interpretation of CT colonography.

[1]  J. Ferrucci,et al.  Virtual colonoscopy: imaging features with colonoscopic correlation. , 1998, AJR. American journal of roentgenology.

[2]  J. Ferrucci,et al.  Virtual colonoscopy: what will the issues be? , 1997, AJR. American journal of roentgenology.

[3]  C H McCollough,et al.  CT colonography: single- versus multi-detector row imaging. , 2001, Radiology.

[4]  P. Wingo,et al.  Cancer statistics, 1995 , 1995, CA: a cancer journal for clinicians.

[5]  E G McFarland,et al.  Helical CT colonography (virtual colonoscopy): the challenge that exists between advancing technology and generalizability. , 1999, AJR. American journal of roentgenology.

[6]  J Cuzick,et al.  Long-term risk of colorectal cancer after excision of rectosigmoid adenomas. , 1992, The New England journal of medicine.

[7]  J. Fleiss Statistical methods for rates and proportions , 1974 .

[8]  A. Hara,et al.  Computed Tomographic Colonography (Virtual Colonoscopy): A New Method for Detecting Colorectal Neoplasms , 1997, Endoscopy.

[9]  D. Ott,et al.  The economic implications of radiologic screening for colonic cancer. , 1991, AJR. American journal of roentgenology.

[10]  G. Dw Colorectal cancer. Screening strategies. , 1997 .

[11]  J. Ferrucci,et al.  A comparison of virtual and conventional colonoscopy for the detection of colorectal polyps. , 1999, The New England journal of medicine.

[12]  A. Zauber,et al.  Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. , 1993 .

[13]  D. Ahlquist,et al.  Patterns of occult bleeding in asymptomatic colorectal cancer , 1990, Cancer.

[14]  A. Hara,et al.  Detection of colorectal polyps with CT colography: initial assessment of sensitivity and specificity. , 1997, Radiology.

[15]  D J Vining,et al.  Virtual endoscopy: is it reality? , 1996, Radiology.

[16]  P Schnyder,et al.  Diagnostic accuracy and interobserver agreement of CT colonography (virtual colonoscopy) , 2000, Gut.

[17]  J G Fletcher,et al.  Optimization of CT colonography technique: prospective trial in 180 patients. , 2000, Radiology.

[18]  D K Rex CT and MR colography (virtual colonoscopy): status report. , 1998, Journal of clinical gastroenterology.

[19]  J G Fletcher,et al.  CT colonography: potential pitfalls and problem-solving techniques. , 1999, AJR. American journal of roentgenology.

[20]  C H McCollough,et al.  Detection of colorectal polyps by computed tomographic colography: feasibility of a novel technique. , 1996, Gastroenterology.