CT Colonography Computer-Aided Polyp Detection

Rationale and Objectives

To determine whether the display of computer-aided detection (CAD) marks on individual polyps on both the supine and prone scans leads to improved polyp detection by radiologists compared to the display of CAD marks on individual polyps on either the supine or the prone scan, but not both.

Materials and Methods

The acquisition of patient data for this study was approved by the Institutional Review Board and was Health Insurance Portability and Accountability Act–compliant. Subsequently, the use of the data was declared exempt from further institutional review board review. Four radiologists interpreted 33 computed tomography colonography cases, 21 of which had one adenoma 6–9 mm in size, with the assistance of a CAD system in the first reader mode (ie, the radiologists reviewed only the CAD marks). The radiologists were shown each case twice, with different sets of CAD marks for each of the two readings. In one reading, a true-positive CAD mark for the same polyp was displayed on both the supine and prone scans (a double-mark reading). In the other reading, a true-positive CAD mark was displayed either on the supine or prone scan, but not both (a single-mark reading). True-positive marks were randomized between readings and there was at least a 1-month delay between readings to minimize recall bias. Sensitivity and specificity were determined and receiver operating characteristic (ROC) and multiple-reader multiple-case analyses were performed.

Results

The average per polyp sensitivities were 60% (38%–81%) versus 71% (52%–91%) ( P = .03) for single-mark and double-mark readings, respectively. The areas (95% confidence intervals) under the ROC curves were 0.76 (0.62–0.88) and 0.79 (0.58–0.96), respectively ( P = NS). Specificities were similar for the single-mark compared with the double-mark readings.

Conclusion

The display of CAD marks on a polyp on both the supine and prone scans led to more frequent detection of polyps by radiologists without adversely affecting specificity for detecting 6–9 mm adenomas.

Computed tomography colonography (CTC) computer-aided detection (CAD) of polyps has advanced considerably over the past decade . Several recent studies have found that radiologists’ performance at polyp detection improves significantly with the aid of CAD . There is the prospect that, in the near future, both CTC and CAD will be widely used for colorectal cancer screening.

The successful clinical implementation of CAD depends on a number of factors, both technical and perceptual. The CAD software must locate the polyp and the radiologist must correctly interpret the CAD finding as a polyp. Previous studies have found that radiologists occasionally ignore true-positive CAD findings . Such behavior undermines the potential benefit of CAD. A better understanding of the causes of such errors could lead to improved radiologist performance.

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Materials and methods

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Patient Population

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Bowel Preparation

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Computed Tomography Scanning

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Optical Colonoscopy

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Polyp Identification

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CAD System

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Overview of Study Design

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Selection of Abnormal Patients and Detections

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Selection of False-positive Detections

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Selection of Normal Cases

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Randomization

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Reader Experience

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Training

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Instructions Given to the Radiologist Observers

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Statistical Analysis

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Results

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Table 1

Sensitivity per Polyp for Single-mark and Double-mark Computer-aided Detection True-positive Presentation

Sensitivity ( n = 21) Reader Single-mark Double-mark 1 8

38% 12

57% 2 15

71% 19

91% 3 15

71% 19

91% 4 12

57% 10

48% Average 60% (51%–68%) 71% (63%–80%)

Numbers are polyps (%). Patients had at most one polyp. Note that per-patient and per-polyp sensitivities are not necessarily identical because radiologists could miss the true polyp and instead inappropriately mark a false positive as a polyp, leading to a true-positive patient and false-negative polyp. The differences between single-mark and double-mark reads for individual readers (Fisher exact test) were not statistically significant. The differences between single-mark and double-mark reads for the average reader ( P =.03, three-factor analysis of variance) was statistically significant. 95% confidence intervals are given for the sensitivities for the average reader. There was no statistically significant difference among readers for the single-mark reads, but there was a statistically significant difference among readers for the double-mark reads ( P = .002, Cochran’s Q).

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Table 2

Sensitivity and Specificity per Patient for Single-mark and Double-mark Computer-aided Detection True-positive Presentation

Sensitivity ( n = 21) Specificity ( n = 12) Reader Single-mark Double-mark Single-mark Double-mark 1 9

43% 13

62% 11

92% 8

67% 2 17

81% 19

90% 9

75% 10

83% 3 17

81% 19

90% 10

83% 12

100% 4 13

62% 10

48% 11

92% 10

83% Average 56/84

67%

(44%–86%) 61/84

73%

(48%–94%) 41/48

85%

(65%–100%) 40/48

83%

(63%–98%)

Numbers are patients (%). Patients had at most one polyp. Note that per-patient and per-polyp sensitivities are not necessarily identical because radiologists could miss the true polyp and instead inappropriately mark a false positive as a polyp, leading to a true-positive patient and false-negative polyp. The differences between single-mark and double-mark reads for individual readers and for the average reader were not statistically significant using bootstrap analysis. 95% confidence intervals for the average reader are from the multireader multicase analysis. The data for specificity include three normal cases that were identical on two readings; each reading was arbitrarily assigned to either the single-mark or double-mark groups. For the other nine normal cases, a pair of false positives was either matched (double-mark) or unmatched on the supine and prone scans based on location and computer-aided detection score to mimic the situation for the abnormal cases.

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Table 3

Sensitivity for Polyp Detection by Radiologists on Both Supine and Prone Scans for Single-mark and Double-mark Computer-aided Detection True-positive Presentation

Reader Single-mark ( n = 21) Double-mark ( n = 21)P 1 5

24% 12

57% .06 2 5

24% 14

67% .01 3 14

67% 18

86% .3 4 11

52% 9

43% .8 Average 42% (33%–51%) 63% (54%–72%) .002

Numbers are polyps (%) detected by radiologists on both supine and prone scans. P values are from Fisher exact test for the individual readers and three-factor analysis of variance for the average reader. 95% confidence intervals are given for the sensitivities for the average reader.

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Table 4

Reasons for False-negative Polyps

Reason Given by Radiologist for Not Calling Polyp Single-mark Cases ( n = 34) Double-mark Cases ( n = 61) Stool 15 (44.1%) 20 (32.3%) Normal mucosa 8 (23.5%) 14 (22.6%) Fluid 6 (17.6%) 7 (11.3%) Fold 3 (8.8%) 10 (16.1%) Not viewable 2 (5.9%) 5 (8.1%) Scan artifact 0 (0%) 2 (3.2%) Rectal tube 0 (0%) 1 (1.6%) Air bubble 0 (0%) 1 (1.6%) Other 0 (0%) 1 (1.6%)

Data are numbers of false-negative polyps (%) according to the reasons the radiologists gave for not calling the computer-aided detection (CAD) finding a polyp. These are CAD marks on polyps that were mischaracterized by the radiologists. “Not viewable” means CAD mark was not visible on colonic surface when radiologist clicked on that entry in list of CAD marks.

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Table 5

False-positive Radiologist Findings According to Whether the Computer-aided Detection Marks were Intentionally Spatially Colocated on Supine and Prone Scans

Reader Non-matched FPs Matched FPs 1 12 1 2 28 0 3 14 0 4 10 1 Average 64/1788 ∗

3.6% 2/72

2.8%

Data are numbers (%) of false-positive radiologist diagnoses according to whether the false positive was intentionally matched by the experimenters with a false positive in the same approximate location of the colon on the other scan. Multiple counts for some of the same false positives for readers and readings were included. The 72 matched false positives consist of a pair of false positives in each of 9 normal patients interpreted by each of four readers.

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Discussion

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Acknowledgments

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References

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CT Colonography Computer-Aided Polyp Detection

Rationale and Objectives

Materials and Methods

Results

Conclusion

Materials and methods

Patient Population

Bowel Preparation

Computed Tomography Scanning

Optical Colonoscopy

Polyp Identification

CAD System

Overview of Study Design

Selection of Abnormal Patients and Detections

Selection of False-positive Detections

Selection of Normal Cases

Randomization

Reader Experience

Training

Instructions Given to the Radiologist Observers

Statistical Analysis

Results

Discussion

Acknowledgments

References

Further Reading

CADe Prompts and Observer Performance

Curriculum Development For Medical Education A Six-Step Approach, 2nd Edition

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