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

Artificial intelligence stenosis diagnosis in coronary CTA: effect on the performance and consistency of readers with less cardiovascular experience

Background

To investigate the influence of artificial intelligence (AI) based on deep learning on the diagnostic performance and consistency of inexperienced cardiovascular radiologists.

Methods

We enrolled 196 patents who had undergone both coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) within 6 months. Four readers with less cardiovascular experience (Reader 1–Reader 4) and two cardiovascular radiologists (level II, Reader 5 and Reader 6) evaluated all images for ≥ 50% coronary artery stenosis, with ICA as the gold standard. Reader 3 and Reader 4 interpreted with AI system assistance, and the other four readers interpreted without the AI system. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy (area under the receiver operating characteristic curve (AUC)) of the six readers were calculated at the patient and vessel levels. Additionally, we evaluated the interobserver consistency between Reader 1 and Reader 2, Reader 3 and Reader 4, and Reader 5 and Reader 6.

Results

The AI system had 94% and 78% sensitivity at the patient and vessel levels, respectively, which were higher than that of Reader 5 and Reader 6. AI-assisted Reader 3 and Reader 4 had higher sensitivity (range + 7.2–+ 16.6% and + 5.9–+ 16.1%, respectively) and NPVs (range + 3.7–+ 13.4% and + 2.7–+ 4.2%, respectively) than Reader 1 and Reader 2 without AI. Good interobserver consistency was found between Reader 3 and Reader 4 in interpreting ≥ 50% stenosis (Kappa value = 0.75 and 0.80 at the patient and vessel levels, respectively). Only Reader 1 and Reader 2 showed poor interobserver consistency (Kappa value = 0.25 and 0.37). Reader 5 and Reader 6 showed moderate agreement (Kappa value = 0.55 and 0.61).

Conclusions

Our study showed that using AI could effectively increase the sensitivity of inexperienced readers and significantly improve the consistency of coronary stenosis diagnosis via CCTA.

Trial registration Clinical trial registration number: ChiCTR1900021867. Name of registry: Diagnostic performance of artificial intelligence-assisted coronary computed tomography angiography for the assessment of coronary atherosclerotic stenosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00756-y.

Interobserver Variation of Colonic Polyp Measurement at Computed Tomography Colonography

BACKGROUND

The concept of "advanced polyps" is well accepted and is defined as polyps ≥10 mm and/or those having a villous component and/or demonstrating areas of dysplasia. Of these parameters, computed tomography colonography (CTC) can only document size. The accepted management of CTC-detected "advanced polyps" is to recommend excision if feasible, whereas the management of "intermediate" (6-9 mm) polyps is more controversial, and interval surveillance may be acceptable. Therefore, distinction between 6-9 mm and ≥10 mm is important.

METHODS

Datasets containing 26 polyps originally reported as between 8-12 mm in diameter were reviewed independently by 4 CTC-accredited radiologists. Observers tabulated the largest measurement for each polyp on axial, coronal, sagittal, and endoluminal views at lung-window settings. These measurements were also compared to those determined by the computer-aided detection (CAD) software.

RESULTS

The interobserver reliability intra-class correlation coefficient (ICC) for sagittal projection was 0.80 ("excellent" category of Hosmer and Lemeshow [2004]), 0.71 for axial ("acceptable"), 0.69 for coronal, and 0.41 for endoluminal ("unacceptable"). The largest of sagittal/axial/coronal measurement gave the best reliability with the smallest variance (ICC = 0.80; 95% CI 0.67-0.89). For 8 of 26 polyps, at least one radiologist's measurement placed the polyp in a different category compared to a colleague. For the majority of the polyps, the CAD significantly overestimated the readings compared to the largest of the manual measurements with an average difference of 1.6 mm (P < .0001 for sagittal/axial/coronal). This resulted in 33% of polyps falling into a different category-10% were lower and 23% were higher (P < .034).

CONCLUSION

It is apparent that around the cutoff point of 10 mm between "advanced" and "intermediate" polyps, interobserver performance is variable.

Computer-based self-training for CT colonography with and without CAD

OBJECTIVES

To determine whether (1) computer-based self-training for CT colonography (CTC) improves interpretation performance of novice readers; (2) computer-aided detection (CAD) use during training affects learning.

METHODS

Institutional review board approval and patients' informed consent were obtained for all cases included in this study. Twenty readers (17 radiology residents, 3 radiologists) with no experience in CTC interpretation were recruited in three centres. After an introductory course, readers performed a baseline assessment test (37 cases) using CAD as second reader. Then they were randomized (1:1) to perform either a computer-based self-training (150 cases verified at colonoscopy) with CAD as second reader or the same training without CAD. The same assessment test was repeated after completion of the training programs. Main outcome was per lesion sensitivity (≥ 6 mm). A generalized estimating equation model was applied to evaluate readers' performance and the impact of CAD use during training.

RESULTS

After training, there was a significant improvement in average per lesion sensitivity in the unassisted phase, from 74% (356/480) to 83% (396/480) (p < 0.001), and in the CAD-assisted phase, from 83% (399/480) to 87% (417/480) (p = 0.021), but not in average per patient sensitivity, from 93% (390/420) to 94% (395/420) (p = 0.41), and specificity, from 81% (260/320) to 86% (276/320) (p = 0.15). No significant effect of CAD use during training was observed on per patient sensitivity and specificity, nor on per lesion sensitivity.

CONCLUSIONS

A computer-based self-training program for CTC improves readers' per lesion sensitivity. CAD as second reader does not have a significant impact on learning if used during training.

KEY POINTS

• Computer-based self-training for CT colonography improves per lesion sensitivity of novice readers. • Self-training program does not increase per patient specificity of novice readers. • CAD used during training does not have significant impact on learning.

A comparison of computer-assisted detection (CAD) programs for the identification of colorectal polyps: performance and sensitivity analysis, current limitations and practical tips for radiologists

AIM

To directly compare the accuracy and speed of analysis of two commercially available computer-assisted detection (CAD) programs in detecting colorectal polyps.

MATERIALS AND METHOD

In this retrospective single-centre study, patients who had colorectal polyps identified on computed tomography colonography (CTC) and subsequent lower gastrointestinal endoscopy, were analysed using two commercially available CAD programs (CAD1 and CAD2). Results were compared against endoscopy to ascertain sensitivity and positive predictive value (PPV) for colorectal polyps. Time taken for CAD analysis was also calculated.

RESULTS

CAD1 demonstrated a sensitivity of 89.8%, PPV of 17.6% and mean analysis time of 125.8 seconds. CAD2 demonstrated a sensitivity of 75.5%, PPV of 44.0% and mean analysis time of 84.6 seconds.

CONCLUSION

The sensitivity and PPV for colorectal polyps and CAD analysis times can vary widely between current commercially available CAD programs. There is still room for improvement. Generally, there is a trade-off between sensitivity and PPV, and so further developments should aim to optimise both. Information on these factors should be made routinely available, so that an informed choice on their use can be made. This information could also potentially influence the radiologist's use of CAD results.

Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study

PURPOSE

To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on radiologists' diagnostic performance in interpreting three-dimensional brain magnetic resonance (MR) imaging using follow-up imaging and consensus as the reference standard.

MATERIALS AND METHODS

The institutional review board approved this retrospective study. The study cohort consisted of 110 consecutive patients with BM and 30 patients without BM. The training data set included MR images of 80 patients with 450 BM nodules. The test set included MR images of 30 patients with 134 BM nodules and 30 patients without BM. We developed a CAD system for BM detection using template-matching and K-means clustering algorithms for candidate detection and an artificial neural network for false-positive reduction. Four reviewers (two neuroradiologists and two radiology residents) interpreted the test set images before and after the use of CAD in a sequential manner. The sensitivity, false positive (FP) per case, and reading time were analyzed. A jackknife free-response receiver operating characteristic (JAFROC) method was used to determine the improvement in the diagnostic accuracy.

RESULTS

The sensitivity of CAD was 87.3% with an FP per case of 302.4. CAD significantly improved the diagnostic performance of the four reviewers with a figure-of-merit (FOM) of 0.874 (without CAD) vs. 0.898 (with CAD) according to JAFROC analysis (p < 0.01). Statistically significant improvement was noted only for less-experienced reviewers (FOM without vs. with CAD, 0.834 vs. 0.877, p < 0.01). The additional time required to review the CAD results was approximately 72 sec (40% of the total review time).

CONCLUSION

CAD as a second reader helps radiologists improve their diagnostic performance in the detection of BM on MR imaging, particularly for less-experienced reviewers.

A study on the value of computer-assisted assessment for SPECT/CT-scans in sentinel lymph node diagnostics of penile cancer as well as clinical reliability and morbidity of this procedure

BACKGROUND

Because of the increasing importance of computer-assisted post processing of image data in modern medical diagnostic we studied the value of an algorithm for assessment of single photon emission computed tomography/computed tomography (SPECT/CT)-data, which has been used for the first time for lymph node staging in penile cancer with non-palpable inguinal lymph nodes. In the guidelines of the relevant international expert societies, sentinel lymph node-biopsy (SLNB) is recommended as a diagnostic method of choice. The aim of this study is to evaluate the value of the afore-mentioned algorithm and in the clinical context the reliability and the associated morbidity of this procedure.

METHODS

Between 2008 and 2015, 25 patients with invasive penile cancer and inconspicuous inguinal lymph node status underwent SLNB after application of the radiotracer Tc-99m labelled nanocolloid. We recorded in a prospective approach the reliability and the complication rate of the procedure. In addition, we evaluated the results of an algorithm for SPECT/CT-data assessment of these patients.

RESULTS

SLNB was carried out in 44 groins of 25 patients. In three patients, inguinal lymph node metastases were detected via SLNB. In one patient, bilateral lymph node recurrence of the groins occurred after negative SLNB. There was a false-negative rate of 4 % in relation to the number of patients (1/25), resp. 4.5 % in relation to the number of groins (2/44). Morbidity was 4 % in relation to the number of patients (1/25), resp. 2.3 % in relation to the number of groins (1/44). The results of computer-assisted assessment of SPECT/CT data for sentinel lymph node (SLN)-diagnostics demonstrated high sensitivity of 88.8 % and specificity of 86.7 %.

CONCLUSIONS

SLNB is a very reliable method, associated with low morbidity. Computer-assisted assessment of SPECT/CT data of the SLN-diagnostics shows high sensitivity and specificity. While it cannot replace the assessment by medical experts, it can still provide substantial supplement and assistance.

History, evolution, and current status of radiologic imaging tests for colorectal cancer screening

Colorectal cancer screening is thought to be an effective tool with which to reduce the mortality from colorectal cancer through early detection and removal of colonic adenomas and early colon cancers. In this article, we review the history, evolution, and current status of imaging tests of the colon-including single-contrast barium enema, double-contrast barium enema, computed tomographic (CT) colonography, and magnetic resonance (MR) colonography-for colorectal cancer screening. Despite its documented value in the detection of colonic polyps, the double-contrast barium enema has largely disappeared as a screening test because it is widely perceived as a labor-intensive, time-consuming, and technically demanding procedure. In the past decade, the barium enema has been supplanted by CT colonography as the major imaging test in colorectal cancer screening in the United States, with MR colonography emerging as another viable option in Europe. Although MR colonography does not require ionizing radiation, the radiation dose for CT colonography has decreased substantially, and regular screening with this technique has a high benefit-to-risk ratio. In recent years, CT colonography has been validated as an effective tool for use in colorectal cancer screening that is increasingly being disseminated.

Multi-reader multi-case studies using the area under the receiver operator characteristic curve as a measure of diagnostic accuracy: systematic review with a focus on quality of data reporting

INTRODUCTION

We examined the design, analysis and reporting in multi-reader multi-case (MRMC) research studies using the area under the receiver-operating curve (ROC AUC) as a measure of diagnostic performance.

METHODS

We performed a systematic literature review from 2005 to 2013 inclusive to identify a minimum 50 studies. Articles of diagnostic test accuracy in humans were identified via their citation of key methodological articles dealing with MRMC ROC AUC. Two researchers in consensus then extracted information from primary articles relating to study characteristics and design, methods for reporting study outcomes, model fitting, model assumptions, presentation of results, and interpretation of findings. Results were summarized and presented with a descriptive analysis.

RESULTS

Sixty-four full papers were retrieved from 475 identified citations and ultimately 49 articles describing 51 studies were reviewed and extracted. Radiological imaging was the index test in all. Most studies focused on lesion detection vs. characterization and used less than 10 readers. Only 6 (12%) studies trained readers in advance to use the confidence scale used to build the ROC curve. Overall, description of confidence scores, the ROC curve and its analysis was often incomplete. For example, 21 (41%) studies presented no ROC curve and only 3 (6%) described the distribution of confidence scores. Of 30 studies presenting curves, only 4 (13%) presented the data points underlying the curve, thereby allowing assessment of extrapolation. The mean change in AUC was 0.05 (-0.05 to 0.28). Non-significant change in AUC was attributed to underpowering rather than the diagnostic test failing to improve diagnostic accuracy.

CONCLUSIONS

Data reporting in MRMC studies using ROC AUC as an outcome measure is frequently incomplete, hampering understanding of methods and the reliability of results and study conclusions. Authors using this analysis should be encouraged to provide a full description of their methods and results.

Exploration of analysis methods for diagnostic imaging tests: problems with ROC AUC and confidence scores in CT colonography

BACKGROUND

Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection.

METHODS

In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods.

RESULTS

Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC.

CONCLUSIONS

The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests.

Investigation of computer-aided diagnosis system for bone scans: a retrospective analysis in 406 patients

OBJECTIVE

The aim of this study was to investigate the diagnostic ability of a completely automated computer-assisted diagnosis (CAD) system to detect metastases in bone scans by two patterns: one was per region, and the other was per patient.

MATERIALS AND METHODS

This study included 406 patients with suspected metastatic bone tumors who underwent whole-body bone scans that were analyzed by the automated CAD system. The patients were divided into four groups: a group with prostatic cancer (N = 71), breast cancer (N = 109), males with other cancers (N = 153), and females with other cancers (N = 73). We investigated the bone scan index and artificial neural network (ANN), which are parameters that can be used to classify bone scans to determine whether there are metastases. The sensitivities, specificities, positive predictive value (PPV), negative predictive value (NPV), and accuracies for the four groups were compared. Receiver operating characteristic (ROC) analyses of region-based ANN were performed to compare the diagnostic performance of the automated CAD system.

RESULTS

There were no significant differences in the sensitivity, specificity, or NPV between the four groups. The PPVs of the group with prostatic cancer (51.0 %) were significantly higher than those of the other groups (P < 0.01). The accuracy of the group with prostatic cancer (81.5 %) was significantly higher than that of the group with breast cancer (68.6 %) and the females with other cancers (65.9 %) (P < 0.01). For the evaluation of the ROC analysis of region-based ANN, the highest Az values for the groups with prostatic cancer, breast cancer, males with other cancers, and females with other cancers were 0.82 (ANN = 0.4, 0.5, 0.6, 0.7, and 0.8), 0.83 (ANN = 0.7), 0.81 (ANN = 0.5), and 0.81 (ANN = 0.6), respectively.

CONCLUSION

The special CAD system "BONENAVI" trained with a Japanese database appears to have significant potential in assisting physicians in their clinical routine. However, an improved CAD system depending on the primary lesion of the cancer is required to decrease the proportion of false-positive findings.

A retrieval-based computer-aided diagnosis system for the characterization of liver lesions in CT scans

RATIONALE AND OBJECTIVES

To evaluate a computer-aided diagnosis (CADx) system for the characterization of liver lesions in computed tomography (CT) scans. The stand-alone predictive performance of the CADx system was assessed and compared to that of three radiologists who were provided with the same amount of image information to which the CADx system had access.

MATERIALS AND METHODS

The CADx system operates as an image search engine exploiting texture analysis of liver lesion image data for the lesion in question and lesions from a database. A region of interest drawn around an indeterminate liver lesion is used as input query. The CADx system retrieves lesions of similar histology (benign/malignant), density (hypodense/hyperdense), or type (cyst/hemangioma/metastasis). The system's performance was evaluated with leave-one-patient-out receiver operating characteristic area under the curve on 685 CT scans from 372 patients that contained 2325 liver lesions (193 <1 cm(3)). Sensitivity, specificity, and positive and negative predictive values were evaluated separately for subcentimeter lesions. Results were compared to those of three radiologists who rated 83 liver lesions (20 hemangiomas, 20 metastases, 20 cysts, 20 hepatocellular carcinomas, and 3 focal nodular hyperplasias) displaying only the liver.

RESULTS

The CADx system's leave-one-patient-out receiver operating characteristic area under the curve was 97.1% for density, 91.4% for histology, and 95.5% for lesion type. For subcentimeter lesions, input of additional semantic information improved the system's performance. The CADx system has been proved to significantly outperform radiologists in discriminating lesion histology and type, provided the radiologists have no access to information other than the image. The radiologists were most reliable in diagnosing hemangioma given the limited image data.

CONCLUSIONS

The CADx system under study discriminated reliably between various liver lesions, even outperforming radiologists when accessing the same image information and demonstrated promising performance in classifying subcentimeter lesions in particular.

Integrating patient digital photographs with medical imaging examinations

We introduce the concept, benefits, and general architecture for acquiring, storing, and displaying digital photographs along with medical imaging examinations. We also discuss a specific implementation built around an Android-based system for simultaneously acquiring digital photographs along with portable radiographs. By an innovative application of radiofrequency identification technology to radiographic cassettes, the system is able to maintain a tight relationship between these photographs and the radiographs within the picture archiving and communications system (PACS) environment. We provide a cost analysis demonstrating the economic feasibility of this technology. Since our architecture naturally integrates with patient identification methods, we also address patient privacy issues.

Computer-aided diagnosis for detection of lacunar infarcts on MR images: ROC analysis of radiologists' performance

The purpose of this study was to retrospectively evaluate radiologist performance in detection of lacunar infarcts on T1- and T2-weighted images, without and with the use of a computer-aided diagnosis (CAD) scheme. Thirty T1-weighted and 30 T2-weighted MR images obtained from 30 patients were used for assessing observer performance. These images were acquired using the fast spin-echo sequence with a 1.5-T MR imaging scanner. The group included 15 patients (age range, 48-83 years; mean age, 67.2 years; 10 men and five women) with a lacunar infarct and 15 patients (age range, 39-76 years; mean age, 64.0 years; eight men and seven women) without lacunar infarcts. Nine radiologists participated in the study. The radiologists initially interpreted the T1- and T2-weighted images without and then with the use of CAD, which indicated their confidence levels regarding the presence (or absence) of lacunar infarcts and the most likely position of a lesion on each MR scan. The observers' performance without and with the computer output was evaluated by performing receiver operating characteristic analysis. For the nine radiologists, the mean area under the best-fit binormal receiver operating characteristic curve plotted for unit square values of radiologists who interpreted the images without and with the scheme were 0.891 and 0.937, respectively. The performance of the radiologists improved significantly when they used the computer output (p=0.032). The CAD scheme has potential to improve the accuracy of radiologists' performance in detection of lacunar infarcts.

Prostate cancer: computer-aided diagnosis with multiparametric 3-T MR imaging--effect on observer performance

PURPOSE

To determine the effect of computer-aided diagnosis (CAD) on less-experienced and experienced observer performance in differentiation of benign from malignant prostate lesions at 3-T multiparametric magnetic resonance (MR) imaging.

MATERIALS AND METHODS

The institutional review board waived the need for informed consent. Retrospectively, 34 patients were included who had prostate cancer and had undergone multiparametric MR imaging, including T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced MR imaging prior to radical prostatectomy. Six radiologists less experienced in prostate imaging and four radiologists experienced in prostate imaging were asked to characterize different regions suspicious for cancer as benign or malignant on multiparametric MR images first without and subsequently with CAD software. The effect of CAD was analyzed by using a multiple-reader, multicase, receiver operating characteristic analysis and a linear mixed-model analysis.

RESULTS

In 34 patients, 206 preannotated regions, including 67 malignant and 64 benign regions in the peripheral zone (PZ) and 19 malignant and 56 benign regions in the transition zone (TZ), were evaluated. Stand-alone CAD had an overall area under the receiver operating characteristic curve (AUC) of 0.90. For PZ and TZ lesions, the AUCs were 0.92 and 0.87, respectively. Without CAD, less-experienced observers had an overall AUC of 0.81, which significantly increased to 0.91 (P = .001) with CAD. For experienced observers, the AUC without CAD was 0.88, which increased to 0.91 (P = .17) with CAD. For PZ lesions, less-experienced observers increased their AUC from 0.86 to 0.95 (P < .001) with CAD. Experienced observers showed an increase from 0.91 to 0.93 (P = .13). For TZ lesions, less-experienced observers significantly increased their performance from 0.72 to 0.79 (P = .01) with CAD and experienced observers increased their performance from 0.81 to 0.82 (P = .42).

CONCLUSION

Addition of CAD significantly improved the performance of less-experienced observers in distinguishing benign from malignant lesions; when less-experienced observers used CAD, they reached similar performance as experienced observers. The stand-alone performance of CAD was similar to performance of experienced observers.

Efficacy of computer-aided detection as a second reader for 6-9-mm lesions at CT colonography: multicenter prospective trial

PURPOSE

To assess the effect of computer-aided detection (CAD) as a second reader on the sensitivity and specificity of computed tomographic (CT) colonography in detecting 6-9-mm colorectal cancer (CRC) lesions.

MATERIALS AND METHODS

Individuals with clinical indications for colonoscopy--either for symptoms or as part of participating in a surveillance program or CRC screening--were prospectively enrolled at one of 10 academic centers between July 2007 and May 2009. Institutional review board approval was obtained at each clinical site, and all participants provided written informed consent. All participants underwent CT colonography and colonoscopy on the same day. Experienced readers interpreted the CT colonography images unassisted and then reviewed all colorectal lesion-like structures pinpointed by the CAD algorithm. Segmental unblinding of CT colonoscopy findings at colonoscopy was utilized. The sensitivity and specificity of unassisted and CAD-assisted reading in identifying individuals with 6-9-mm lesions were calculated and compared by means of pairwise analysis.

RESULTS

A total of 618 participants (mean age, 57.9 years; 54.5% male) were included in the final analysis. Of these participants, 464 (75.1%) had no lesions 6 mm or larger, and 52 (8.4%) had 6-9-mm lesions. The sensitivity of CT colonography with unassisted reading and that with CAD-assisted reading in identifying individuals with 6-9-mm lesions was 65.4% (95% confidence interval [CI]: 50.9%, 78.0%) and 76.9% (95% CI: 63.2%, 87.5%; P = .016), respectively. No significant change in specificity was observed: The specificity of CT colonography with unassisted and that with CAD-assisted reading was 91.8% (95% CI: 88.9%, 94.1%) and 90.9% (95% CI: 88.0%, 93.4%; P = .063), respectively. Evaluation of CAD candidates required an additional 1.6 minutes (25th-75th percentile: 1.0 minute to 3.4 minutes).

CONCLUSION

The addition of CAD to reading performed by experienced readers resulted in a significant benefit in the detection of 6-9-mm polyps at CT colonography in this cohort.

SUPPLEMENTAL MATERIAL

http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120376/-/DC1.

A computer-aided algorithm to quantitatively predict lymph node status on MRI in rectal cancer

OBJECTIVE

The aim of this study was to demonstrate the principle of supporting radiologists by using a computer algorithm to quantitatively analyse MRI morphological features used by radiologists to predict the presence or absence of metastatic disease in local lymph nodes in rectal cancer.

METHODS

A computer algorithm was developed to extract and quantify the following morphological features from MR images: chemical shift artefact; relative mean signal intensity; signal heterogeneity; and nodal size (volume or maximum diameter). Computed predictions on nodal involvement were generated using quantified features in isolation or in combinations. Accuracies of the predictions were assessed against a set of 43 lymph nodes, determined by radiologists as benign (20 nodes) or malignant (23 nodes).

RESULTS

Predictions using combinations of quantified features were more accurate than predictions using individual features (0.67-0.86 vs 0.58-0.77, respectively). The algorithm was more accurate when three-dimensional images were used (0.58-0.86) than when only middle image slices (two-dimensional) were used (0.47-0.72). Maximum node diameter was more accurate than node volume in representing the nodal size feature; combinations including maximum node diameter gave accuracies up to 0.91.

CONCLUSION

We have developed a computer algorithm that can support radiologists by quantitatively analysing morphological features of lymph nodes on MRI in the context of rectal cancer nodal staging. We have shown that this algorithm can combine these quantitative indices to generate computed predictions of nodal status which closely match radiological assessment. This study provides support for the feasibility of computer-assisted reading in nodal staging, but requires further refinement and validation with larger data sets.

The second ESGAR consensus statement on CT colonography

Objective

To update quality standards for CT colonography based on consensus among opinion leaders within the European Society of Gastrointestinal and Abdominal Radiology (ESGAR).

Material and methods

A multinational European panel of nine members of the ESGAR CT colonography Working Group (representing six EU countries) used a modified Delphi process to rate their level of agreement on a variety of statements pertaining to the acquisition, interpretation and implementation of CT colonography. Four Delphi rounds were conducted, each at 2 months interval.

Results

The panel elaborated 86 statements.

In the final round the panelists achieved complete consensus in 71 of 86 statements (82 %). Categories including the highest proportion of statements with excellent Cronbach's internal reliability were colon distension, scan parameters, use of intravenous contrast agents, general guidelines on patient preparation, role of CAD and lesion measurement.

Lower internal reliability was achieved for the use of a rectal tube, spasmolytics, decubitus positioning and number of CT data acquisitions, faecal tagging, 2D vs. 3D reading, and reporting.

Conclusion

The recommendations of the consensus should be useful for both the radiologist who is starting a CTC service and for those who have already implemented the technique but whose practice may need updating.

Key Points

• Computed tomographic colonography is the optimal radiological method of assessing the colon

• This article reviews ESGAR quality standards for CT colonography

• This article is aimed to provide CT-colonography guidelines for practising radiologists

• The recommendations should help radiologists who are starting/updating their CTC services

Prediction of survival benefit using an automated bone scan index in patients with castration-resistant prostate cancer

What's known on the subject? and What does the study add? A bone scan index (BSI) can quantify the extent of bone involvement and response to treatment, but it has not been widely accepted, because of its time-consuming nature. The study is the first to demonstrate that automated BSI calculated with a computer-assisted diagnosis system is effective in judging the chemotherapeutic response of bone metastatic lesions in patients with castration-resistant prostate cancer.

OBJECTIVE

• To evaluate the value of an automated bone scan index (aBSI), calculated using a computer-assisted diagnosis system, to indicate chemotherapy response and to predict prognosis in patients with castration-resistant prostate cancer (CRPC) with bone metastasis.

PATIENTS AND METHODS

• Forty-two consecutive CRPC patients underwent taxane-based chemotherapy between November 2004 and March 2011 at our institution. • The aBSIs were retrospectively calculated at the diagnosis of CRPC and 16 weeks after starting chemotherapy. • Cox proportional hazards regression models were applied to multivariate analyses with and without aBSI response in addition to the basic model. • Based on the difference in the concordance index (c-index) between each model, the prognostic relevance of adding the aBSI response was determined.

RESULTS

• A decrease in aBSI was found in 28 patients (66.7%), whereas a response was shown by bone scan in only 23.8% of patients. • Patients with a reduction in aBSI had longer overall survival (OS) in comparison with the other patients (P= 0.0157). • Multivariate analysis without aBSI response showed that performance status (P= 0.0182) and PSA response (P= 0.0375) were significant prognosticators. • By adding the aBSI response to this basic model, the prognostic relevance of the model was improved with an increase in the c-index from 0.621 to 0.660.

CONCLUSIONS

• The aBSI reflected the chemotherapy response in bone metastasis. • The index detected small changes of bone metastasis response as quantified values and was a strong prognostic indicator for patients with CRPC.

Computer-aided detection of colorectal polyps in CT colonography with and without fecal tagging: a stand-alone evaluation

PURPOSE

To evaluate the stand-alone performance of a computer-aided detection (CAD) algorithm for colorectal polyps in a large heterogeneous CT colonography (CTC) database that included both tagged and untagged datasets.

METHODS

Written, informed consent was waived for this institutional review board-approved, HIPAA-compliant retrospective study. CTC datasets from 2063 patients were assigned to training (n = 374) and testing (n = 1689). The test set consisted of 836 untagged and 853 tagged examinations not used for CAD training. Examinations were performed at 15 sites in the United States, Asia, and Europe, using 4- to 64-multidetector-row computed tomography and various acquisition parameters. CAD sensitivities were calculated on a per-patient and per-polyp basis for polyps measuring ≥6 mm. The reference standard was colonoscopy in 1588 (94%) and consensus interpretation by expert radiologists in 101 (6%) patients. Statistical testing employed χ, logistic regression, and Mann-Whitney U tests.

RESULTS

In 383 of 1689 individuals, 564 polyps measuring ≥6 mm were identified by the reference standard (347 polyps: 6-9 mm and 217 polyps: ≥10 mm). Overall, CAD per-patient sensitivity was 89.6% (343/383), with 89.0% (187/210) for untagged and 90.2% (156/173) for tagged datasets (P = 0.72). Overall, per-polyp sensitivity was 86.9% (490/564), with 84.4% (270/320) for untagged and 90.2% (220/244) for tagged examinations (P = 068). The mean false-positive rate per patient was 5.14 (median, 4) in untagged and 4.67 (median, 4) in tagged patient datasets (P = 0.353).

CONCLUSION

Stand-alone CAD can be applied to both tagged and untagged CTC studies without significant performance differences. Detection rates are comparable to human readers at a relatively low false-positive rate, making CAD a useful tool in clinical practice.

Colonic polyps: inheritance, susceptibility, risk evaluation, and diagnostic management

Colorectal cancer (CRC) is the third-ranked neoplasm in order of incidence and mortality, worldwide, and the second cause of cancer death in industrialized countries. One of the most important environmental risk factors for CRC is a Western-type diet, which is characterized by a low-fiber and high-fat content. Up to 25% of patients with CRC have a family history for CRC, and a fraction of these patients are affected by hereditary syndromes, such as familial adenomatous polyposis, Gardner or Turcot syndromes, or hereditary nonpolyposis colorectal cancer. The onset of CRC is triggered by a well-defined combination of genetic alterations, which form the bases of the adenoma-carcinoma sequence hypothesis and justify the set-up of CRC screening techniques. Several screening and diagnostic tests for CRC are illustrated, including rectosigmoidoscopy, optical colonoscopy (OC), double contrast barium enema (DCBE), and computed tomography colonography (CTC). The strengths and weaknesses of each technique are discussed. Particular attention is paid to CTC, which has evolved from an experimental technique to an accurate and mature diagnostic approach, and gained wide acceptance and clinical validation for CRC screening. This success of CTC is due mainly to its ability to provide cross-sectional analytical images of the entire colon and secondarily detect extracolonic findings, with minimal invasiveness and lower cost than OC, and with greater detail and diagnostic accuracy than DCBE. Moreover, especially with the advent and widespread availability of modern multidetector CT scanners, excellent quality 2D and 3D reconstructions of the large bowel can be obtained routinely with a relatively low radiation dose. Computer-aided detection systems have also been developed to assist radiologists in reading CTC examinations, improving overall diagnostic accuracy and potentially speeding up the clinical workflow of CTC image interpretation.

Performance improvements of imaging-based screening tests

Endoscopic and radiologic tests appear to be more accurate than stool-tests in detecting advanced neoplasia because of direct visualisation of colorectal mucosa. Further technological advances are expected to improve the performance and acceptability of these tests. Several attempts at increasing the adenoma detection rate of colonoscopy have been tested, and in vivo histologic differentiation between neoplastic and hyperplastic polyps may lead to substantial saving in economic and medical resources. Low-volume and non-cathartic bowel preparations may improve CT colonography acceptability, whilst computer-aided detection and low-dose protocols may result in a higher accuracy and safety of this procedure. Despite the lack of ionising radiation, significant drawbacks will likely to limit the role of MR colonography in screening programs. Colon capsule endoscopy appears to be a safe and technically feasible procedure. The suboptimal accuracy of the first generation seems to be substantially improved by the second generation of this device.

CT colonography computer-aided polyp detection: Effect on radiologist observers of polyp identification by CAD on both the supine and prone scans

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.

Effect of computer-aided detection for CT colonography in a multireader, multicase trial

PURPOSE

To assess the effect of using computer-aided detection (CAD) in second-read mode on readers' accuracy in interpreting computed tomographic (CT) colonographic images.

MATERIALS AND METHODS

The contributing institutions performed the examinations under approval of their local institutional review board, with waiver of informed consent, for this HIPAA-compliant study. A cohort of 100 colonoscopy-proved cases was used: In 52 patients with findings positive for polyps, 74 polyps of 6 mm or larger were observed in 65 colonic segments; in 48 patients with findings negative for polyps, no polyps were found. Nineteen blinded readers interpreted each case at two different times, with and without the assistance of a commercial CAD system. The effect of CAD was assessed in segment-level and patient-level receiver operating characteristic (ROC) curve analyses.

RESULTS

Thirteen (68%) of 19 readers demonstrated higher accuracy with CAD, as measured with the segment-level area under the ROC curve (AUC). The readers' average segment-level AUC with CAD (0.758) was significantly greater (P = .015) than the average AUC in the unassisted read (0.737). Readers' per-segment, per-patient, and per-polyp sensitivity for all polyps of 6 mm or larger was higher (P < .011, .007, .005, respectively) for readings with CAD compared with unassisted readings (0.517 versus 0.465, 0.521 versus 0.466, and 0.477 versus 0.422, respectively). Sensitivity for patients with at least one large polyp of 10 mm or larger was also higher (P < .047) with CAD than without (0.777 versus 0.743). Average reader sensitivity also improved with CAD by more than 0.08 for small adenomas. Use of CAD reduced specificity of readers by 0.025 (P = .05).

CONCLUSION

Use of CAD resulted in a significant improvement in overall reader performance. CAD improves reader sensitivity when measured per segment, per patient, and per polyp for small polyps and adenomas and also reduces specificity by a small amount.

Colorectal polyps: stand-alone performance of computer-aided detection in a large asymptomatic screening population

PURPOSE

To evaluate stand-alone performance of computer-aided detection (CAD) for colorectal polyps of 6 mm or larger at computed tomographic (CT) colonography in a large asymptomatic screening cohort.

MATERIALS AND METHODS

In this retrospective, institutional review board-approved, HIPAA-compliant study, a CAD software system was applied to screening CT colonography in 1638 women and 1408 men (mean age, 56.9 years) evaluated at a single medical center between March 2006 and December 2008. All participants underwent cathartic preparation with stool tagging; electronic cleansing was not used. The reference standard consisted of interpretation by experienced radiologists in all cases. This interpretation was further refined for the subset of cases with positive findings by using subsequent colonoscopic or CT colonographic confirmation, as well as retrospective expert localization of polyps with CT colonography. This test set was not involved in training the CAD system. The Fisher exact test was used to evaluate significance; 95% confidence intervals (CIs) were obtained by using the exact method.

RESULTS

Per-patient CAD sensitivities were 93.8% (350 of 373; 95% CI: 90.9%, 96.1%) and 96.5% (137 of 142; 95% CI: 92.0%, 98.8%) at 6- and 10-mm threshold sizes, respectively. Per-polyp CAD sensitivities for all polyps, regardless of histologic features, were 90.1% (547 of 607; 95% CI: 88.0%, 92.8%) and 96.0% (168 of 175; 95% CI: 91.9%, 98.4%) at 6- and 10-mm threshold sizes, respectively; CAD sensitivities for advanced neoplasia and cancer were 97.0% (128 of 132; 95% CI: 92.4%, 99.2%) and 100% (13 of 13; 95% CI: 79.4%, 100%), respectively. The mean and median false-positive rates were 4.7 and 3 per series, respectively (9.4 and 6 per patient). Among 373 patients with a positive finding at CT colonography, CAD marked an additional 15 polyps of 6 mm or larger, including four large polyps, that were missed at the prospective three-dimensional reading by an expert but were found at subsequent colonoscopy.

CONCLUSION

Stand-alone CAD demonstrated excellent performance for polyp detection in a large screening population, with high sensitivity and an acceptable number of false-positive results.

Nonlaxative PET/CT colonography: feasibility, acceptability, and pilot performance in patients at higher risk of colonic neoplasia

CT colonography without bowel preparation is a safer and better-tolerated alternative to full laxation protocols, but comparative sensitivity and specificity are potentially reduced. Uptake of (18)F-FDG by colonic neoplasia is well described, and combining PET with nonlaxative CT colonography could improve accuracy. The purpose was to prospectively test the technical feasibility and acceptability of combined nonlaxative PET/CT colonography in patients at higher risk of colorectal neoplasia and to provide pilot data on diagnostic performance.

METHODS

Fifty-six patients (median age, 64 y; 30 women) at high risk of colonic neoplasia underwent nonlaxative PET/CT colonography with barium fecal tagging within 2 wk of scheduled colonoscopy. Colonic segmental distension was graded 1 (poor) to 3 (good). A radiologist, experienced in CT colonography, and nuclear medicine physician in consensus analyzed the datasets. The diagnostic performance for standalone CT colonography and combined PET/CT colonography was compared with the reference colonoscopy. Patient experience for 25 items (each scored from 1 to 7) pertaining to satisfaction, worry, and physical discomfort was canvassed after both PET/CT colonography and colonoscopy.

RESULTS

Distension was good in 298 of 334 segments (89%; 95% confidence interval [CI], 85%-92%). Patients experienced more physical discomfort during colonoscopy (median, 4; interquartile range [IQR], 2-7) than during PET/CT colonography (median, 5; IQR, 3-7; P = 0.03) and were more willing to undergo PET/CT colonography again (36/43 [84%; 95% CI, 73%-95%] vs. 31/43 [72%; 95% CI, 59%-86%]; P = 0.001). Twenty-one patients had 54 polyps according to colonoscopy (10 with at least 1 polyp >or=6 mm and 8 with at least 1 polyp >or=10 mm). Of 14 polyps 6 mm or greater, 12 (86%; 95% CI, 67%-100%) were (18)F-FDG-avid, including all those 10 mm or greater (mean standardized uptake value, 10.1). CT colonography sensitivity for polyps 6 mm or larger was 92.9% (95% CI, 79.4%-100%) and was not improved by the addition of PET. However, combined PET/CT colonography review improved per-patient positive predictive value for a polyp 10 mm or greater from 73% (95% CI, 39-92) to 100% (95% CI, 60-100).

CONCLUSION

In this feasibility study, simultaneous PET acquisition during nonlaxative CT colonography is technically feasible, is well tolerated, and potentially improves specificity.

CT colonography: advanced computer-aided detection scheme utilizing MTANNs for detection of "missed" polyps in a multicenter clinical trial

PURPOSE

The purpose of this study was to develop an advanced computer-aided detection (CAD) scheme utilizing massive-training artificial neural networks (MTANNs) to allow detection of "difficult" polyps in CT colonography (CTC) and to evaluate its performance on false-negative (FN) CTC cases that radiologists "missed" in a multicenter clinical trial.

METHODS

The authors developed an advanced CAD scheme consisting of an initial polyp-detection scheme for identification of polyp candidates and a mixture of expert MTANNs for substantial reduction in false positives (FPs) while maintaining sensitivity. The initial polyp-detection scheme consisted of (1) colon segmentation based on anatomy-based extraction and colon-based analysis and (2) detection of polyp candidates based on a morphologic analysis on the segmented colon. The mixture of expert MTANNs consisted of (1) supervised enhancement of polyps and suppression of various types of nonpolyps, (2) a scoring scheme for converting output voxels into a score for each polyp candidate, and (3) combining scores from multiple MTANNs by the use of a mixing artificial neural network. For testing the advanced CAD scheme, they created a database containing 24 FN cases with 23 polyps (range of 6-15 mm; average of 8 mm) and a mass (35 mm), which were "missed" by radiologists in CTC in the original trial in which 15 institutions participated.

RESULTS

The initial polyp-detection scheme detected 63% (15/24) of the missed polyps with 21.0 (505/24) FPs per patient. The MTANNs removed 76% of the FPs with loss of one true positive; thus, the performance of the advanced CAD scheme was improved to a sensitivity of 58% (14/24) with 8.6 (207/24) FPs per patient, whereas a conventional CAD scheme yielded a sensitivity of 25% at the same FP rate (the difference was statistically significant).

CONCLUSIONS

With the advanced MTANN CAD scheme, 58% of the polyps missed by radiologists in the original trial were detected and with a reasonable number of FPs. The results suggest that the use of an advanced MTANN CAD scheme may potentially enhance the detection of "difficult" polyps.

Improving the accuracy of CTC interpretation: computer-aided detection

Computer-aided polyp detection aims to improve the accuracy of the colonography interpretation. The computer searches the colonic wall to look for polyplike protrusions and presents a list of suspicious areas to a physician for further analysis. Computer-aided polyp detection has developed rapidly in the past decade in the laboratory setting and has sensitivities comparable with those of experts. Computer-aided polyp detection tends to help inexperienced readers more than experienced ones and may also lead to small reductions in specificity. In its currently proposed use as an adjunct to standard image interpretation, computer-aided polyp detection serves as a spellchecker rather than an efficiency enhancer.

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 >or=6 mm and >or=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.

CT colonography with decreased purgation: balancing preparation, performance, and patient acceptance

OBJECTIVE

Reduction or elimination of catharsis with fecal tagging enhances the tolerability of CT colonography (CTC) and may increase compliance with colorectal cancer (CRC) screening recommendations. We systematically reviewed studies that prospectively evaluated performance and patient satisfaction with decreased-purgation CTC and with optical colonoscopy.

CONCLUSION

The nine studies reviewed showed moderate-to-good performance for decreased-purgation CTC; however, data are limited, and study design and data presentation are inconsistent. Further study of decreased-purgation CTC and standardization of terminology are needed.

ACR Colon Cancer Committee white paper: status of CT colonography 2009

PURPOSE

To review the current status and rationale of the updated ACR practice guidelines for CT colonography (CTC).

METHODS

Clinical validation trials in both the United States and Europe are reviewed. Key technical aspects of the CTC examination are emphasized, including low-dose protocols, proper insufflation, and bowel preparation. Important issues of implementation are discussed, including training and certification, definition of the target lesion, reporting of colonic and extracolonic findings, quality metrics, reimbursement, and cost-effectiveness.

RESULTS

Successful validation trials in screening cohorts both in the United States with ACRIN and in Germany demonstrated sensitivity > or = 90% for patients with polyps >10 mm. Proper technique is critical, including low-dose techniques in screening cohorts, with an upper limit of the CT dose index by volume of 12.5 mGy per examination. Training new readers includes the requirement of interactive workstation training with 2-D and 3-D image display techniques. The target lesion is defined as a polyp > or = 6 mm, consistent with the American Cancer Society joint guidelines. Five quality metrics have been defined for CTC, with pilot data entered. Although the CMS national noncoverage decision in May 2009 was a disappointment, multiple third-party payers are reimbursing for screening CTC. Cost-effective modeling has shown CTC to be a dominant strategy, including in a Medicare cohort.

CONCLUSION

Supported by third-party payer reimbursement for screening, CTC will continue to further transition into community practice and can provide an important adjunctive examination for colorectal screening.

Performance of computed tomographic colonography for the screening of colorectal polyp in acromegalic patients: a prospective study

CONTEXT

Acromegalic patients have better chances to develop colorectal polyps and cancer and, considered a high-risk group, need to undergo frequent screening examinations. Moreover, in acromegalia, the increased bowel length and the intestinal loop complexity can lead to higher levels of technical difficulties and increase the risks of complications at conventional colonoscopy. Computed tomographic colonography, also known as virtual colonoscopy, is an innovative and secure technology which is revolutionizing the diagnosis of colon and rectum neoplasias.

OBJECTIVE

To analyze computed tomographic colonography performance for the screening of colorectal polyps in acromegalic patients.

METHODS

A prospective study of 21 asymptomatic acromegalic patients, 12 male and 9 female, average age 49, who underwent computed tomographic colonography and conventional colonoscopy. Computed tomographic colonography was performed with a GE Helical Multislice Computed Tomography Apparatus. Conventional colonoscopy was performed in the same day, without previous knowledge of the computed tomographic colonography diagnostics. The study evaluated the capacity of computed tomographic colonography to detect patients with colorectal polyps and identify each colorectal lesion described by the colonoscopy.

RESULTS

In two patients (2/21), conventional colonoscopy was incomplete. However, in all patients computed tomographic colonography was complete. In Phase I ('per patient'), computed tomographic colonography diagnosed eight of the nine patients with colorectal polyps and showed 88% sensitivity, 75% specificity and 81% accuracy. In Phase II ('per polyp'), out of the 21 acromegalic patients included in this study, 12 presented normal findings at conventional colonoscopy. A total of 19 polyps were identified in 9 patients. Ten of the 19 polyps were smaller than 10 mm, and 9 were equal to or larger than 10 mm. Computed tomographic colonography identified 7 of the 9 polyps >10 mm described by conventional colonoscopy and only 6 of the 10 small polyps identified at conventional colonoscopy were detected by computed tomographic colonography. The histological analysis of resected lesions revealed 12 tubular adenomas, 6 hyperplastic polyps and 1 colonic tubulo-villous adenoma with an adenocarcinoma focus.

CONCLUSION

The authors present the first reports of computed tomographic colonography in the screening of colorectal polyps in acromegalic patients. In this study, computed tomographic colonography was performed without complications and a complete and safe colorectal evaluation was possible in all acromegalic patients. Moreover, computed tomographic colonography presented good sensitivity, specificity and accuracy for the identification of acromegalic patients with polyps of any size and better results in the diagnosis of large polyps, when they were compared to small polypoid lesions.

Polyp characteristics correctly annotated by computer-aided detection software but ignored by reporting radiologists during CT colonography

PURPOSE

To retrospectively describe the characteristics of polyps incorrectly dismissed by radiologists despite appropriate computer-aided detection (CAD) prompting during computed tomographic (CT) colonography.

MATERIALS AND METHODS

Ethics committee approval and patient informed consent were obtained from institutions that provided the data sets used in this HIPAA-compliant study. A total of 111 polyps that had a diameter of at least 6 mm and were detected with CAD were collated from three previous studies in which researchers investigated radiologist performance with and without CAD (total, 25 readers). Two new observers graded each polyp with predefined criteria, including polyp size, morphology, and location; data set quality; ease of visualization; tagging use and polyp coating; colonic curvature; CAD mark obscuration; and number of false-positive findings. The 86 polyps that were missed before CAD (those that were unreported by one or more original readers) were divided into those that remained unreported after CAD (no CAD gain, n = 36) and those that were reported correctly by at least one additional reader (CAD gain, n = 50). Logistic-regression analysis and the Fisher exact and Mann-Whitney tests were used to compare the results of both groups with each other and with a control group of 25 polyps, all of which were detected by readers without CAD.

RESULTS

Before CAD, polyps 10 mm in diameter or larger, those that were rated easy to visualize, and those that were uncoated by tagged fluid were less likely to be missed (72%, 76%, and 80% of control polyps vs 43%, 43%, and 59% of missed polyps, respectively; P < .001, P < .01, and P < .03, respectively). After CAD, the odds of CAD gain decreased with increasing polyp size (odds ratio, 0.92; 95% confidence interval: 0.85, 1.00; P = .04) and irregular morphology (odds ratio, 0.28; 95% confidence interval: 0.08, 0.92; P = .04).

CONCLUSION

Larger irregular polyps are a common source of incorrect radiologist dismissal, despite correct CAD prompting.

Computer-aided detection (CAD) as a second reader using perspective filet view at CT colonography: effect on performance of inexperienced readers

AIM

To evaluate whether computer-aided detection (CAD) as a second reader using perspective filet view [three-dimensional (3D) filet] improves the performance of inexperienced readers at computed tomography colonography (CTC) compared with unassisted 3D filet and unassisted two-dimensional (2D) CTC.

MATERIAL AND METHODS

Fifty symptomatic patients underwent CTC and same-day colonoscopy with segmental unblinding. Two inexperienced readers read the CTC studies on 3D filet and 2D several weeks apart. Four months later, readers re-read the cases only evaluating CAD marks using 3D filet. Suspicious CAD marks not previously described on 3D filet were recorded. Jackknife free-response receiver operating characteristic (JAFROC-1) analysis was used to compare the observers' performances in detecting lesions with 3D filet, 2D and 3D filet with CAD.

RESULTS

One hundred and three lesions > or =3mm were detected at colonoscopy with segmental unblinding. CAD alone had a sensitivity of 73% (75/103) at a mean false-positive rate per patient of 12.8 in supine and 11.4 in prone. For inexperienced readers sensitivities with 3D filet with CAD were 58% (60/103) and 48% (50/103) with an improvement of 14-16 percentage points (p<0.05) compared with 2D and of 10-11 percentage points (p<0.05) compared with 3D filet. For inexperienced readers, the false-positive rate was 25-41% and 71-200% higher with 3D filet with CAD compared with 3D filet and 2D, respectively. JAFROC-1 analysis showed no significant differences in per-lesion overall performance among reading modes (p=0.8).

CONCLUSION

CAD applied as a second reader using 3D filet increased both sensitivity and the number of false positives by inexperienced readers compared with 3D filet and 2D, thus not improving overall performance, i.e., the ability to distinguish between lesions and non-lesions.

Automatic polyp detection and measurement with computed tomographic colonography: A phantom study

Purpose

The purpose of this study is to assess the performance of computer-aided detection (CAD) software in detecting and measuring polyps for CT Colonography, based on an in vitro phantom study.

Material and methods

A colon phantom was constructed with a PVC pipe of 3.8 cm diameter. Nine simulated polyps of various sizes (3.2mm-25.4mm) were affixed inside the phantom that was placed in a water bath. The phantom was scanned on a 64-slice CT scanner with tube voltage of 120 kV and current of 205 mAs. Two separate scans were performed, with different slice thickness and reconstruction interval. The first scan (thin) had a slice thickness of 1mm and reconstruction interval 0.5mm. The second scan (thick) had a slice thickness of 2mm and reconstruction interval of 1mm. Images from both scans were processed using CT Colonography software that automatically segments the colon phantom and applies CAD that automatically highlights and provides the size (maximum and minimum diameters, volume) of each polyp. Two readers independently measured each polyp (two orthogonal diameters) using both 2D and 3D views. Readers’ manual measurements (diameters) and automatic measurements from CAD (diameters and volume) were compared to actual polyp sizes as measured by mechanical calipers.

Results

All polyps except the smallest (3.2mm) were detected by CAD. CAD achieved 100% sensitivity in detecting polyps ≥6mm. Mean errors in CAD automated volume measurements for thin and thick slice scans were 8.7% and 6.8%, respectively. Almost all CAD and manual readers’ 3D measurements overestimated the size of polyps to variable extent. Both over- and underestimation of polyp sizes were observed in the readers’ manual 2D measurements. Overall, Reader 1 (expert) had smaller mean error than Reader 2 (non-expert).

Conclusion

CAD provided accurate size measurements for all polyps, and results were comparable to the two readers' manual measurements

Influence of computer-aided detection false-positives on reader performance and diagnostic confidence for CT colonography

OBJECTIVE

The objective of our study was to investigate whether an increasing number of computer-aided detection (CAD) false-positives decreases reader sensitivity, specificity, and confidence for nonexpert readers of CT colonography (CTC).

MATERIALS AND METHODS

Fifty CTC data sets (29 men; mean age, 65 years), 25 of which contained 35 polyps > or = 5 mm, were selected in which CAD had 100% polyp sensitivity at two sphericity settings (0 and 75) but differed in the number of false-positives. The data sets were read by five readers twice: once at each sphericity setting. Sensitivity, specificity, report time, and confidence before and after second-read CAD were compared using the paired exact and Student's t test, respectively. Receiver operating characteristic (ROC) curves were generated using reader confidence (1-100) in correct case classification (normal or abnormal).

RESULTS

CAD generated a mean of 42 (range, 3-118) and 15 (range, 1-36) false-positives at a sphericity of 0 and 75, respectively. CAD at both settings increased per-patient sensitivity from 82% to 87% (p = 0.03) and per-polyp sensitivity by 8% and 10% for a sphericity of 0 and 75, respectively (p < 0.001). Specificity decreased from 84% to 79% (sphericity 0 and 75, p = 0.03 and 0.07). There was no difference in sensitivity, specificity, or reader confidence between sphericity settings (p = 1.0, 1.0, 0.11, respectively). The area under the ROC curve was 0.78 (95% CI, 0.70-0.86) and 0.77 (0.68-0.85) for a sphericity of 0 and 75, respectively. CAD added a median of 4.4 minutes (interquartile range [IQR], 2.7-6.5 minutes) and 2.2 minutes (IQR, 1.2-4.0 minutes) for a sphericity of 0 and 75, respectively (p < 0.001). CONCLUSION. CAD has the potential to increase the sensitivity of readers inexperienced with CTC, although specificity may be reduced. An increased number of CAD-generated false-positives does not negate any beneficial effect but does reduce efficiency.

CT colonography can be an adjunct to optical colonoscopy in CRC screening

CT colonography or virtual colonoscopy is a fairly new modality that has the potential to play a significant role in screening for colon cancer. CT colonography is an attractive option for two specific reasons. First, it is non-invasive and, second, it obviates the need for sedation. It thus overcomes the two major drawbacks of optical colonoscopy. CT colonography cannot be a stand-alone technique for colorectal cancer screening because, unlike conventional colonoscopy, it does not possess a therapeutic option or a definite diagnostic capability. However, CT colonography can be a cost-effective complement to traditional colonoscopy if it is reasonably priced and if appropriate cut-off levels (>6 mm polyp) are used to increase its sensitivity.

Computer-aided assessment of head computed tomography (CT) studies in patients with suspected traumatic brain injury

In this study, we sought to determine the accuracy of a computer algorithm that automatically assesses head computed tomography (CT) studies in patients with suspected traumatic brain injury (TBI) for features of intracranial hemorrhage and mass effect, employing a neuroradiologist's interpretation as the gold standard. To this end, we designed a suite of computer algorithms that evaluates in a fully automated fashion the presence of intracranial blood and/or mass effect based on the following CT findings: (1) presence or absence of a subdural or epidural hematoma, (2) presence or absence of subarachnoid hemorrhage, (3) presence or absence of an intraparenchymal hematoma, (4) presence or absence of clinically significant midline shift (>or=5 mm), and (5) normal, partly effaced, or completely effaced basal cisterns. The algorithm displays abnormal findings as color overlays on the original head CT images, and calculates the volume of each type of blood collection, the midline shift, and the volume of the basal cisterns, based on the above-described features. Thresholds and parameters yielding optimal accuracy of the computer algorithm were determined using a development sample of 33 selected, nonconsecutive patients. The software was then applied to a validation sample of 250 consecutive patients evaluated for suspicion of acute TBI at our institution in 2006-2007. Software detection of the presence of at least one noncontrast CT (NCT) feature of acute TBI demonstrated high sensitivity of 98% and high negative predictive value (NPV) of 99%. There was actually only one false negative case, where a very subtle subdural hematoma, extending exclusively along the falx, was diagnosed by the neuroradiologist, while the case was considered as normal by the computer algorithm. The software was excellent at detecting the presence of mass effect and intracranial hemorrhage, but showed some disagreements with the neuroradiologist in quantifying the degree of mass effect and characterizing the type of intracranial hemorrhage. In summary, we have developed a fully automated computer algorithm that demonstrated excellent sensitivity for acute intracranial hemorrhage and clinically significant midline shift, while maintaining intermediate specificity. Further studies are required to evaluate the potential favorable impact of this software on facilitating workflow and improving diagnostic accuracy when used as a screening aid by physicians with different levels of experience.