Computed tomography colonography: feasibility of computer-aided polyp detection in a "first reader" paradigm

OBJECTIVE:: To determine the feasibility of a computer-aided detection (CAD) algorithm as the "first reader" in computed tomography colonography (CTC). METHODS:: In phase 1 of a 2-part blind trial, we measured the performance of 3 radiologists reading 41 CTC studies without CAD. In phase 2, readers interpreted the same cases using a CAD list of 30 potential polyps. RESULTS:: Unassisted readers detected, on average, 63% of polyps > or =10 mm in diameter. Using CAD, the sensitivity was 74% (not statistically different). Per-patient analysis showed a trend toward increased sensitivity for polyps > or =10 mm in diameter, from 73% to 90% with CAD (not significant) without decreasing specificity. Computer-aided detection significantly decreased interobserver variability (P = 0.017). Average time to detection of the first polyp decreased significantly with CAD, whereas total reading case reading time was unchanged. CONCLUSION:: Computer-aided detection as a first reader in CTC was associated with similar per-polyp and per-patient detection sensitivity to unassisted reading. Computer-aided detection decreased interobserver variability and reduced the time required to detect the first polyp.     

CT colonography: effect of computer-aided detection of colonic polyps as a second and concurrent reader for general radiologists with moderate experience in CT colonography

Objectives

To assess the effectiveness of computer-aided detection (CAD) as a second reader or concurrent reader in helping radiologists who are moderately experienced in computed tomographic colonography (CTC) to detect colorectal polyps.

Methods

Seventy CTC datasets (34 patients: 66 polyps ≥6 mm; 36 patients: no abnormalities) were retrospectively reviewed by seven radiologists with moderate CTC experience. After primary unassisted evaluation, a CAD second read and, after a time interval of ≥4 weeks, a CAD concurrent read were performed. Areas under the receiver operating characteristic (ROC) curve (AUC), along with per-segment, per-polyp and per-patient sensitivities, and also reading times, were calculated for each reader with and without CAD.

Results

Of seven readers, 86 % and 71 % achieved a higher accuracy (segment-level AUC) when using CAD as second and concurrent reader respectively. Average segment-level AUCs with second and concurrent CAD (0.853 and 0.864) were significantly greater (p?<?0.0001) than average AUC in the unaided evaluation (0.781). Per-segment, per-polyp, and per-patient sensitivities for polyps ≥6 mm were significantly higher in both CAD reading paradigms compared with unaided evaluation. Second-read CAD reduced readers’ average segment and patient specificity by 0.007 and 0.036 (p?=?0.005 and 0.011), respectively.

Conclusions

CAD significantly improves the sensitivities of radiologists moderately experienced in CTC for polyp detection, both as second reader and concurrent reader.

Key Points

? CAD helps radiologists with moderate CTC experience to detect polyps ≥6 mm. ? Second and concurrent read CAD increase the radiologist’s sensitivity for detecting polyps ≥6 mm. ? Second read CAD slightly decreases specificity compared with an unassisted read. ? Concurrent read CAD is significantly more time-efficient than second read CAD.     

Computer-assisted detection for CT colonography: external validation

AIM: To externally validate a computer-assisted detection (CAD) system for computed tomography (CT) colonography, using data from a single centre uninvolved with the software development. MATERIALS AND METHODS: Twenty-five multi-detector CT colonography examinations of patients with validated polyps accumulated at a single centre were examined by two readers who used endoscopic and histopathological data to identify polyp coordinates. A CAD system that had been developed using data from elsewhere, and had not previously encountered the present data, was then applied to the data at sphericity filter settings of 0.75 and 0.50 and identified potential polyps. True-positive, false-negative, and false-positive counts were determined by comparison with the known polyp coordinates. RESULTS: Twenty-five patients had 57 polyps, median size 6mm (range 1-15mm). Per-patient sensitivity for the CAD system was 96% (24 of 25). The CAD system detected 44 (77%) polyps at sphericity setting 0.75 and 49 (86%) polyps at sphericity 0.50: the additional five polyps detected all measured 5mm or less. Sphericity of 0.75 resulted in a median of 10 (one to 34) easily dismissed false-positive prompts per patient and a median of 4 (zero to 15) that needed three-dimensional rendering before dismissal. This rose to 32 (16 to 99) and 11 (three to 35), respectively, at sphericity 0.5. CONCLUSIONS: A per-patient sensitivity of 96% was found for the CAD system (in patients with a median polyp diameter of 6mm) using external validation, a more stringent test than either internal cross-validation or temporal validation. Decreasing sphericity increases sensitivity for small polyps at the expense of decreased specificity.     

Does a computer-aided detection algorithm in a second read paradigm enhance the performance of experienced computed tomography colonography readers in a population of increased risk?

We prospectively determined whether computer-aided detection (CAD) could improve the performance characteristics of computed tomography colonography (CTC) in a population of increased risk for colorectal cancer. Therefore, we included 170 consecutive patients that underwent both CTC and colonoscopy. All findings >or=6 mm were evaluated at colonoscopy by segmental unblinding. We determined per-patient sensitivity and specificity for polyps >or=6 mm and >or=10 mm without and with computer-aided detection (CAD). The McNemar test was used for comparison the results without and with CAD. Unblinded colonoscopy detected 50 patients with lesions >or=6 mm and 25 patients with lesions >or=10 mm. Sensitivity of CTC without CAD for these size categories was 80% (40/50, 95% CI: 69-81%) and 64% (16/25, 95% CI: 45-83%), respectively. CTC with CAD detected one additional patient with a lesion >or=6 mm and two with a lesion >or=10 mm, resulting in a sensitivity of 82% (41/50, 95% CI: 71-93%) (p = 0.50) and 72% (18/25, 95% CI: 54-90%) (p = 1.0), respectively. Specificity without CAD for polyps >or=6 mm and >or=10 mm was 84% (101/120, 95% CI: 78-91%) and 94% (136/145, 95% CI: 90-98%), respectively. With CAD, the specificity remained (nearly) unchanged: 83% (99/120, 95% CI: 76-89%) and 94% (136/145, 95% CI: 90-98%), respectively. Thus, although CTC with CAD detected a few more patients than CTC without CAD, it had no statistically significant positive influence on CTC performance.     

Computer-aided detection of colorectal polyps: can it improve sensitivity of less-experienced readers? Preliminary findings

PURPOSE: To determine whether computer-aided detection (CAD) applied to computed tomographic (CT) colonography can help improve sensitivity of polyp detection by less-experienced radiologist readers, with colonoscopy or consensus used as the reference standard. MATERIALS AND METHODS: The release of the CT colonographic studies was approved by the individual institutional review boards of each institution. Institutions from the United States were HIPAA compliant. Written informed consent was waived at all institutions. The CT colonographic studies in 30 patients from six institutions were collected; 24 images depicted at least one confirmed polyp 6 mm or larger (39 total polyps) and six depicted no polyps. By using an investigational software package, seven less-experienced readers from two institutions evaluated the CT colonographic images and marked or scored polyps by using a five-point scale before and after CAD. The time needed to interpret the CT colonographic findings without CAD and then to re-evaluate them with CAD was recorded. For each reader, the McNemar test, adjusted for clustered data, was used to compare sensitivities for readers without and with CAD; a Wilcoxon signed-rank test was used to analyze the number of false-positive results per patient. RESULTS: The average sensitivity of the seven readers for polyp detection was significantly improved with CAD-from 0.810 to 0.908 (P=.0152). The number of false-positive results per patient without and with CAD increased from 0.70 to 0.96 (95% confidence interval for the increase: -0.39, 0.91). The mean total time for the readings was 17 minutes 54 seconds; for interpretation of CT colonographic findings alone, the mean time was 14 minutes 16 seconds; and for review of CAD findings, the mean time was 3 minutes 38 seconds. CONCLUSION: Results of this feasibility study suggest that CAD for CT colonography significantly improves per-polyp detection for less-experienced readers.     

Colonic polyps: complementary role of computer-aided detection in CT colonography

PURPOSE: To apply a computer-aided detection (CAD) algorithm to supine and prone multisection helical computed tomographic (CT) colonographic images to confirm if there is any added benefit provided by CAD over that of standard clinical interpretation. MATERIALS AND METHODS: CT colonography (with patients in both supine and prone positions) was performed with a multisection helical CT scanner in 40 asymptomatic high-risk patients. There were two consecutive series of patients, 20 of whom had at least one polyp 1.0 cm in size or larger and 20 of whom had normal colons at conventional colonoscopy performed the same day. The CT colonographic images were interpreted with an automated CAD algorithm and by two radiologists who were blinded to colonoscopy findings. RESULTS: For 25 polyps at least 1.0 cm in size ("large" polyps), sensitivity for detection by at least one radiologist was 48% (12 of 25). The sensitivity of CAD for detecting large polyps was also 48% (12 of 25), but the CAD algorithm detected four of 13 large polyps that were not detected by either radiologist (31%, 95% two-sided CI: 9, 61), increasing the potential sensitivity to 64% (16 of 25). For polyps identifiable retrospectively, sensitivity of CAD was 67% (12 of 18), and sensitivity of the combination of detection with the CAD algorithm or by at least one radiologist was 89% (16 of 18). There were an average of 11 false-positive detections per patient for CAD. CONCLUSION: In this series of patients in whom radiologists had difficulties detecting polyps (compared with sensitivities of 75%-90% reported in the literature), this CAD algorithm played a complementary role to conventional interpretation of CT colonographic images by detecting a number of large polyps missed by trained observers.     

Computer-aided polyp detection on CT colonography: Comparison of three systems in a high-risk human population

Purpose

To compare the detection performances of two commercial and one academic computer-aided diagnosis (CAD) systems for polyp detection on CT colonography (CTC) in a high-risk human population and to assess their detection characteristics.

Materials and methods

This retrospective study had institutional review board approval, but informed consent was waived. Sixty-eight patients who were suspected of having colonic polyps and scheduled for colonoscopic polyp removal were included. After CTC was performed using a 64-row MDCT, two commercial (PEV, CAR) and one academic (Hessian matrix-based) CAD systems were applied to each CTC dataset. Colonoscopy using the segmental unblinded technique was performed as a standard of reference. Per-polyp and per-patient sensitivities were calculated and compared for each CAD system. The mean number of false-positives (FPs) and false-negatives (FNs) was computed and the causes of all FPs and FNs were analyzed.

Results

A total of 151 polyps in 61 patients were detected (77 polyps <6 mm, 48 6-9.9 mm, 26 ≥ 10 mm). Per-polyp sensitivity for PEV, CAR, and Hessian matrix-based CAD were: 71.6%, 78.4%, and 83.8% for polyps ≥6 mm, and 88.5%, 96.2%, and 96.2% for polyps ≥10 mm. Per-patient sensitivity for polyps ≥6 mm was 80.4%, 89.1%, and 93.5%, and 87%, 95.7%, and 95.7% for polyps ≥10 mm, respectively. Per-polyp and per-patient sensitivities were not significantly different among the three CAD systems regardless of size threshold. Mean number of FPs was 6.9 for PEV, 7.3 for CAR, and 14 for Hessian matrix-based CAD. The most common cause of FPs were feces, followed by extracolonic findings, prominent folds and ileocecal valve, and rectal tube. The distribution of the causes of FPs was significantly different among the three systems.

Conclusion

Sensitivity of the three CAD systems for polyp detection was comparable regardless of the polyp size threshold; however, the number of FPs was higher in the Hessian matrix-based CAD. In addition, the distribution of the causes of FPs was significantly different among the three systems.     

Nonradiologists as second readers for intraluminal findings at CT colonography

RATIONALE AND OBJECTIVES: Multiple trials have documented wide interobserver variability between radiologists interpreting computed tomography colonography (CTC) exams. We sought to determine if nonradiologists could learn to interpret intraluminal findings at CTC with a high degree of sensitivity to determine if they could play a role as second readers in interpreting CTC exams. MATERIALS AND METHODS: Seven nonradiologists (five medical students, two radiologic technologists) undertook self-directed CTC training using a teaching file of 50 cases; thereafter, each reader blindly interpreted 50 cases with colonoscopic correlation (30 positive, 20 negative). Results were compared with a previously studied cohort of radiologists. The two technologists additionally repeated the exam after 6 weeks of clinical experience. RESULTS: The sensitivity of nonradiologists for small (5-9 mm) polyps, large (>9 mm) lesions, and cancers was similar to that of radiologists (0.45 versus 0.63, 0.74 versus 0.71, and 0.80 versus 0.88, respectively). After 6 weeks of clinical experience as second readers, the accuracy of one technologist significantly improved (from 74% to 90%, P = .008), whereas accuracy of the other tended toward improvement (from 74% to 86%%, P = .25). Nonradiologists detected, on average, 6/36 additional polyps (17%) missed by any radiologist, and the sensitivity of 5/7 nonradiologists was significantly greater than at least one of the radiologists (P = .05). CONCLUSION: Nonradiologists can perform similarly to radiologists in interpreting intraluminal findings at CTC, with nonradiologist performance improving even after experience with more than 100 cases. Skilled nonradiologists may play a vital role as a second reader of intraluminal findings or by performing quality control of examinations before patient dismissal.     

Two- versus three-dimensional colon evaluation with recently developed virtual dissection software for CT colonography

This retrospective study was institutional review board approved; the requirement for informed patient consent was waived. The purpose of this study was to retrospectively compare a two-dimensional (2D) data interpretation technique with a three-dimensional (3D) colon dissection technique in terms of interpretation time and sensitivity for colonic polyp detection, with colonoscopy as the reference standard. Ninety-six patients (56 men, 40 women; mean age, 54.8 years) underwent colonoscopy and multidetector computed tomographic (CT) colonography on the same day. Two radiologists independently analyzed the data on a per-polyp and per-patient basis. The sensitivity of both approaches was compared by using the McNemar test. The time required to interpret CT colonographic data with each technique was also assessed. Compared with the conventional 2D colonic polyp detection method, primary 3D interpretation with use of virtual dissection software for CT colonography revealed comparable per-polyp (77% and 69% for two readers) and per-patient (77% and 73% for two readers) sensitivities and comparable per-patient specificity (99% and 89% for two readers) for the detection of polyps 6 mm in diameter or larger and involved a shorter interpretation time.     

计算机辅助检测在结肠低剂量多层螺旋CT成像中的应用

目的 评估计算机辅助检测系统(CAD)设置不同的检测过滤器数值(SFV)时,在低剂量MSCT成像中对结肠病变的检测能力.方法 56例结肠癌和(或)结肠息肉患者行MSCT结肠成像扫描,依据结肠镜和外科手术结果,将病变分为4组:结肠癌、最长径≥10.0mm息肉、最长径5.1～9.9 mm息肉和最长径≤5.0 mm息肉,之后确定病变在CT图像上的部位及大小,作为评估结肠CAD系统检测病变的金标准.将CAD系统的SFV设为0.25、0.50、0.75和1.00共4个等级,分别检测CT结肠成像图像,记录CAD标注出的病灶的部位和大小,根据上述金标准评估CAD系统对结肠病变的检出率,采用x2检验比较不同SFV设置时CAD对各组病变的检出率.结果 56例患者共有159个阳性病灶,其中结肠癌为44个,最长径≥10.0mm息肉45个,最长径5.1～9.9 mm息肉32个,最长径≤5.0 mm息肉38个.将结肠CAD系统SFV分别设置为0.25、0.50、0.75和1.00时,病灶的检出率分别85.5%(136/159)、85.5%(136/159)、79.2%(126/159)和56.0%(89/159).SFV为0.25和0.50时,与SFV为1.00时,CAD对病灶检出率的差异有统计学意义(P＜0.05).随着SFV数值的减低,病灶的检出率增高,假阳性数增加,但91.4%(138/151)～93.9%(31/33)的假阳性病灶很容易识别,仅有6.1%(2/33)～8.6%(13/151)的假阳性病灶,需借助MPR和3D仿真内镜识别.结论 在低剂量MSCT结肠成像中,结肠CAD系统可获得满意的病灶检出率,可调节CAD系统SFV数值,以便满足不同经验阅片者的需求.     

Computer-aided diagnosis in virtual colonography via combination of surface normal and sphere fitting methods

The success of CT colonography (CTC) depends on appropriate tools for quick and accurate diagnostic reading. Current advancements in computer technology have the potential to bring such tools even to personal computer level. In this paper a technique for computed-aided diagnosis (CAD) using CT colonography is described. The method uses a combination of surface normal and sphere fitting methods to label positions in the volume data, which have a strong likelihood of being polyps, and presents them in a user-friendly way. The method was tested on a study group of 18 patients and the detection rate for polyps of 10 mm or larger was 100%, comparable to that of human readers. The price paid for a high detection rate was a large number of approximately eight false-positive findings per case. Our results show that CAD is feasible, and if the number of false positives is further reduced, then this method can be useful for clinical screenings.     

Colorectal polyps: detection with dark-lumen MR colonography versus conventional colonoscopy

PURPOSE: To prospectively compare dark-lumen magnetic resonance (MR) colonography with conventional colonoscopy in the detection of colorectal polyps. MATERIALS AND METHODS: Local ethical committee approval and informed consent were obtained. One hundred consecutive patients (56 men, 44 women; mean age +/- standard deviation, 67.7 years +/- 14.7; range, 25-82 years) who were referred for conventional colonoscopy from January 2003 to January 2004 underwent MR colonography and conventional colonoscopy after standard precolonoscopic bowel cleansing. Colonoscopy was performed immediately after MR colonography. For MR colonography, the colon was filled with approximately 2000 mL of tap water. Imaging was performed with a 1.5-T MR unit with patients in the prone position. A T1-weighted three-dimensional volumetric interpolated breath-hold sequence was performed before and 75 seconds after intravenous administration of 0.2 mmol gadobenate dimeglumine per kilogram of body weight. Results of MR colonography were analyzed on a per-polyp and per-patient basis. Findings at colonoscopy were used as the reference for determining accuracy, sensitivity, specificity, and positive and negative predictive values of MR colonography. RESULTS: Of 100 patients recruited for study, 92 (52 men, 40 women; mean age, 61.5 years +/- 14.5; range, 25-82 years) underwent complete MR and conventional colonoscopy examinations. Forty-three of the 92 patients (47%) had normal findings at conventional colonoscopy. In the other 49 patients (53%), conventional colonoscopy depicted 107 polyps (82 adenomas, 25 hyperplastic polyps) and seven carcinomas. At per-polyp analysis, sensitivity of MR colonography in the detection of adenomatous polyps was 100% for polyps at least 10 mm in diameter and 84.2% for polyps 6-9 mm in diameter. At per-patient analysis, the accuracy of MR colonography was 93.1% (sensitivity, 89%; specificity, 96%) if detection of adenomatous polyps of all sizes was considered. CONCLUSION: Dark-lumen MR colonography is a promising modality with high accuracy for detecting colorectal polyps larger than 5 mm in diameter.     

Diagnostic performance of radiographers as compared to radiologists in magnetic resonance colonography

Purpose

To evaluate the diagnostic performance of radiographers compared to radiologists in the detection of colorectal lesions in MR colonography.

Material and methods

159 patients at increased risk of colorectal cancer were included. Four different experienced observers, one MR radiologist, one radiologist in training and two radiographers evaluated all MR colonography examinations. The protocol included T1-weighted and T2-weighted sequences in prone and supine position. Colonoscopy was used as reference standard. Mean sensitivity rates with 95% confidence intervals (CIs) were determined on a per-patient and per-polyp basis, segmented by size (≥6 mm and ≥10 mm). Specificity was calculated on a per-patient basis. The McNemar and chi-square (χ²) test was used to determine significant differences.

Results

At colonoscopy 74 patients (47%) had normal findings; 23 patients had 40 polyps with a size ≥6 mm. In 10 patients at least 1 polyp ≥10 mm was found (20 polyps in total). Similar sensitivities for patients with lesions ≥10 mm were found for radiologists and radiographers (65% (95%CI: 44-86%) vs. 50% (95%CI: 28-72%)) (p = n.s.). For lesions ≥10 mm combined per-patient specificity for radiologists and radiographers was 96% (95%CI: 94-98%) and 73% (95%CI: 68-79%) (p < 0.0001). Combined per-patient sensitivity for lesions ≥6 mm differed significantly between both groups of observers (57% (95%CI: 42-71%) vs. 33% (95%CI: 19-46%)) (p = 0.03).

Conclusion

Radiographers have comparable sensitivity but lower specificity relative to radiologists in the detection of colorectal lesions ≥10 mm at MR colonography. Adequate training in evaluating MR colonography is necessary, especially for readers with no prior experience with colonography.     

Detection of colorectal lesions: lower-dose multi-detector row helical CT colonography compared with conventional colonoscopy

PURPOSE: To compare the performance of lower-dose multi-detector row helical computed tomographic (CT) colonography with that of conventional colonoscopy in the detection of colorectal lesions. MATERIALS AND METHODS: One hundred fifty-eight patients underwent multi-detector row helical CT colonography (beam collimation, 4 x 2.5 mm; table feed, 17.5 mm/sec; voltage, 140 kV; and effective dose, 10 mAs) followed by conventional colonoscopy. Conventional colonoscopy served as the reference standard. Two radiologists interpreted CT colonographic images to assess the presence of polyps or carcinomas. Sensitivity was calculated on both a per-polyp and a per-patient basis. In the latter, specificity and positive and negative predictive values were also calculated. Weighted CT dose index was calculated on the basis of measurements obtained in a standard body phantom. Effective dose was estimated by using commercially available software. RESULTS: CT colonography correctly depicted all 22 carcinomas (sensitivity, 100%) and 52 of 74 polyps (sensitivity, 70.3%). Sensitivity for detection was 100% in all 13 polyps 10 mm or larger in diameter, 83.3% in 20 of 24 polyps 6-9 mm, and 51.3% in 19 of 37 lesions 5 mm or smaller. With regard to the per-patient analysis, CT colonography had a sensitivity of 96.0%, a specificity of 96.6%, a positive predictive value of 94.1%, and a negative predictive value of 97.7%. The total weighted CT dose index for combined prone and supine acquisitions was 2.74 mGy. The simulated effective doses for complete CT colonography were 1.8 mSv in men and 2.4 mSv in women. CONCLUSION: Lower-dose multi-detector row helical CT colonography ensures substantial dose reduction while maintaining excellent sensitivity for detection of colorectal carcinomas and polyps larger than 6 mm in diameter.     

Effect of computer-aided detection as a second reader in multidetector-row CT colonography

Our purpose was to assess the effect of computer-aided detection (CAD) on lesion detection as a second reader in computed tomographic colonography, and to compare the influence of CAD on the performance of readers with different levels of expertise. Fifty-two CT colonography patient data-sets (37 patients: 55 endoscopically confirmed polyps ≥0.5 cm, seven cancers; 15 patients: no abnormalities) were retrospectively reviewed by four radiologists (two expert, two nonexpert). After primary data evaluation, a second reading augmented with findings of CAD (polyp-enhanced view, Siemens) was performed. Sensitivities and reading time were calculated for each reader without CAD and supported by CAD findings. The sensitivity of expert readers was 91% each, and of nonexpert readers, 76% and 75%, respectively, for polyp detection. CAD increased the sensitivity of expert readers to 96% (P = 0.25) and 93% (P = 1), and that of nonexpert readers to 91% (P = 0.008) and 95% (P = 0.001), respectively. All four readers diagnosed 100% of cancers, but CAD alone only 43%. CAD increased reading time by 2.1 min (mean). CAD as a second reader significantly improves sensitivity for polyp detection in a high disease prevalence population for nonexpert readers. CAD causes a modest increase in reading time. CAD is of limited value in the detection of cancer.     

Electronic cleansing for CT colonography: does it help CAD software performance in a high-risk population for colorectal cancer?

Objective

To compare the performance of computer-aided detection (CAD) for CT colonography (CTC) with and without electronic cleansing (EC) in a high-risk population tagged with a faecal tagging (FT) protocol.

Methods

Thirty-two patients underwent CTC followed by same-day colonoscopy. All patients underwent bowel preparation and FT with barium and gastrografin. Each CTC dataset was processed with colon CAD with and without EC. Per-polyp sensitivity was calculated. The average number of false-positive (FP) results and their causes were also analysed and compared.

Results

Eighty-six polyps were detected in 29 patients. Per-polyp sensitivities of CAD with EC (93.8% and 100%) were higher than those without EC (84.4% and 87.5%) for polyps ≥6 mm and ≥10 mm, respectively. However, the differences were not significant. The average number (6.3) of FPs of CAD with EC was significantly larger than that (3.1) without EC. The distribution of FPs in both CAD settings was also significantly different. The most common cause of FPs was the ileocaecal valve in both datasets. However, untagged faeces was a significantly less common cause of FPs with EC, EC-related artefacts being more common.

Conclusion

Electronic cleansing has the potential to improve per-polyp sensitivity of CTC CAD, although the significantly larger number of FPs with EC remains to be improved.     

Comparative performance of a primary-reader and second-reader paradigm of computer-aided detection for CT colonography in a low-prevalence screening population

Objective

To compare the efficacy of computer-aided detection (CAD) for computed tomographic colonography (CTC) when employed as either primary-reader or second-reader paradigms in a low-prevalence screening population.

Methods

Ninety screening patients underwent same-day CTC and colonoscopy. Four readers prospectively interpreted all CTC data sets using a second-reader paradigm (unassisted interpretation followed immediately by CAD assistance). Three months later, randomized anonymous data sets were re-interpreted by all readers using a primary-reader paradigm (only CAD prompts evaluated).

Results

Compared with the average per-patient sensitivity for unassisted interpretation (0.57), both CAD paradigms significantly increased sensitivity: 0.78 (p < 0.001) for the second-reader paradigm and 0.83 (p < 0.001) for the primary-reader paradigm. There was no significant difference between CAD paradigms (p = 0.25). The average per-patient specificity for polyps ≥6 mm was significantly higher using the primary-reader paradigm than the second-reader paradigm (0.90 vs. 0.83, respectively, p = 0.006), with ROC AUCs of 0.83 and 0.68, respectively. Reading time using CAD as a primary-reader paradigm (median 1.4 min) was significantly shorter than both unassisted (median 4.0 min, p < 0.001) and second-reader paradigms (median 5.5 min, p < 0.001).

Conclusion

CAD improves radiologist sensitivity in screening patients when used as either a second- or primary-reader paradigm, although the latter may improve specificity and efficiency more.     

Computer-assisted reader software versus expert reviewers for polyp detection on CT colonography

OBJECTIVE: The purpose of our study was to assess the sensitivity of computer-assisted reader (CAR) software for polyp detection compared with the performance of expert reviewers. MATERIALS AND METHODS: A library of colonoscopically validated CT colonography cases were collated and separated into training and test sets according to the time of accrual. Training data sets were annotated in consensus by three expert radiologists who were aware of the colonoscopy report. A subset of 45 training cases containing 100 polyps underwent batch analysis using ColonCAR version 1.2 software to determine the optimum polyp enhancement filter settings for polyp detection. Twenty-five consecutive positive test data sets were subsequently interpreted individually by each expert, who was unaware of the endoscopy report, and before generation of the annotated reference via an unblinded consensus interpretation. ColonCAR version 1.2 software was applied to the test cases, at optimized polyp enhancement filter settings, to determine diagnostic performance. False-positive findings were classified according to importance. RESULTS: The 25 test cases contained 32 nondiminutive polyps ranging from 6 to 35 mm in diameter. The ColonCAR version 1.2 software identified 26 (81%) of 32 polyps compared with an average sensitivity of 70% for the expert reviewers. Eleven (92%) of 12 polyps > or = 10 mm were detected by ColonCAR version 1.2. All polyps missed by experts 1 (n = 4) and 2 (n = 3) and 12 (86%) of 14 polyps missed by expert 3 were detected by ColonCAR version 1.2. The median number of false-positive highlights per case was 13, of which 91% were easily dismissed. CONCLUSION: ColonCAR version 1.2 is sensitive for polyp detection, with a clinically acceptable false-positive rate. ColonCAR version 1.2 has a synergistic effect to the reviewer alone, and its standalone performance may exceed even that of experts.     

CAD in CT colonography without and with oral contrast agents: progress and challenges.

Computed tomographic colonography (CTC), also known as virtual colonoscopy, is an emerging alternative technique for screening of colon cancers. CTC uses CT to provide a series of cross-sectional images of the colon for detection of polyps and masses. Fecal tagging is a means of labeling of residual feces by an oral contrast agent for improving the accuracy in the detection of polyps. Computer-aided diagnosis (CAD) for CTC automatically determines the locations of suspicious polyps and masses in CTC and presents them to radiologists, typically as a second opinion. Despite its relatively short history, CAD has become one of the mainstream techniques that could make CTC prime time for screening of colorectal cancer. Rapid technical developments have advanced CAD substantially during the last several years, and a fundamental scheme for the detection of polyps has been established, in which sophisticated 3D image processing, analysis, and display techniques play a pivotal role. The latest CAD systems indicate a clinically acceptable high sensitivity and a low false-positive rate, and observer studies have demonstrated the benefits of these systems in improving radiologists' detection performance. Some technical and clinical challenges, however, remain unresolved before CAD can become a truly useful tool for clinical practice. Also, new challenges are facing CAD as the methods for bowel preparation and image acquisition, such as tagging of fecal residue with oral contrast agents, and interpretation of CTC images evolve. This article reviews the current status and future challenges in CAD for CTC without and with fecal tagging.     

Detection of flat colorectal polyps at screening CT colonography in comparison with conventional polypoid lesions

Background Although the screening of small, flat polyps is clinically important, the role of CT colonography (CTC) screening in their detection has not been thoroughly investigated. Purpose To evaluate the detection capability and usefulness of CTC in the screening of flat and polypoid lesions by comparing CTC with optic colonoscopy findings as the gold standard. Material and Methods We evaluated the CTC detection capability for flat colorectal polyps with a flat surface and a height not exceeding 3 mm (n = 42) by comparing to conventional polypoid lesions (n = 418) according to the polyp diameter. Four types of reconstruction images including multiplanar reconstruction, volume rendering, virtual gross pathology, and virtual endoscopic images were used for visual analysis. We compared the abilities of the four reconstructions for polyp visualization. Results Detection sensitivity for flat polyps was 31.3%, 44.4%, and 87.5% for lesions measuring 2-3 mm, 4-5 mm, and ≥6 mm, respectively; the corresponding sensitivity for polypoid lesions was 47.6%, 79.0%, and 91.7%. The overall sensitivity for flat lesions (47.6%) was significantly lower than polypoid lesions (64.1%). Virtual endoscopic imaging showed best visualization among the four reconstructions. Colon cancers were detected in eight patients by optic colonoscopy, and CTC detected colon cancers in all eight patients. Conclusion CTC using 64-row multidetector CT is useful for colon cancer screening to detect colorectal polyps while the detection of small, flat lesions is still challenging.