Fecal-tagging CT Colonography Research Articles

Dual-energy computed tomography colonography using dual-layer spectral detector computed tomography: Utility of virtual monochromatic imaging for electronic cleansing

ObjectiveTo assess the utility of virtual monochromatic imaging (VMI) using a dual-layer spectral detector CT for electronic cleansing in fecal-tagging CT colonography (CTC). MethodsThis study included 35 patients who underwent fecal-tagging CTC with a dual-layer detector spectral CT scanner. Conventional images at 120 kVp and VMI at 40, 50, and 60 keV were reconstructed. Quantitative image quality parameters, i.e., tagging density and image noise, were compared and the visual image quality was scored on a four-point scale. We recorded the number of the colon segments with appropriate tagging density (≥300 HU) for each patient and used these data to compare the reconstructions. In addition, electronic cleansing performance was semi-quantitatively assessed using a four-point scale. ResultsThe mean tagging density on VMI was significantly higher than that on conventional 120 kVp images. The number of colon segments with appropriate tagging density on VMI were significantly higher than that on conventional 120 kVp images. There was no significant difference among the reconstructed images with respect to image noise. Scores for subjective image quality and electronic cleansing performance on VMI were significantly higher than those on conventional 120 kVp images. ConclusionWith dual-layer spectral detector CT, VMI can yield significantly better fecal-tagged CTC image quality and improve electronic cleansing performance.

Electronic Cleansing in Fecal-Tagging Dual-Energy CT Colonography Based on Material Decomposition and Virtual Colon Tagging

Dual-energy CT provides a promising solution to identify tagged fecal materials in electronic cleansing (EC) for fecal-tagging CT colonography (CTC). In this study, we developed a new EC method based on virtual colon tagging (VCT) for minimizing EC artifacts by use of the material decomposition ability in dual-energy CTC images. In our approach, a localized three-material decomposition model decomposes each voxel into a material mixture vector and the first partial derivatives of three base materials: luminal air, soft tissue, and iodine-tagged fecal material. A Poisson-based derivative smoothing algorithm smoothes the derivatives and implicitly smoothes the associated material mixture fields. VCT is a means for marking the entire colonic lumen by virtually elevating the CT value of luminal air as high as that of the tagged fecal materials to differentiate effectively soft-tissue structures from air-tagging mixtures. A dual-energy EC scheme based on VCT method, denoted as VCT-EC, was developed, in which the colonic lumen was first virtually tagged and then segmented by its high values in VCT images. The performance of the VCT-EC scheme was evaluated in a phantom study and a clinical study. Our results demonstrated that our VCT-EC scheme may provide a significant reduction of EC artifacts.

Fecal-tagging CT colonography with structure-analysis electronic cleansing for detection of colorectal flat lesions

PurposeTo evaluate the feasibility and sensitivity of the 3D-reading of fecal-tagging CT colonography (CTC) with a novel structure-analysis electronic cleansing (SAEC) in detecting colorectal flat lesions in comparison with a cleansed 3D reading with Viatronix V3D Colon system (V3D) and primary uncleansed 2D reading (2D). Materials and methodsForty CTC cases with flat lesions were retrospectively observed. The Subjects from a multicenter clinical trial underwent cathartic bowel preparation with orally administrated barium-based fecal-tagging. Sixty-nine flat lesions were confirmed using colonoscopy and histopathology as a reference standard. The results from SAEC reading were compared with those of prospective V3D and 2D readings. ResultsOverall detection sensitivity with SAEC was 52% (36/69), which was statistically higher than that of 32% (22/69) and 29% (20/69) with V3D and 2D readings, respectively (p<0.05). The sensitivities in detecting not-on-fold flat lesions were 63% (24/38), 45% (17/38), and 42% (16/38) with SAEC, V3D, and 2D readings, respectively; whereas those of on-fold flat lesions were 39% (12/31), 16% (5/31), and 13% (4/31), respectively. None of the eight flat lesions (2-9mm) at cecum was detected by any of the three reading methods. Excluding the flat lesions at cecum, the sensitivity with SAEC for detecting flat lesion ≥4mm increased to 84% (31/37). ConclusionsThe fecal-tagging CTC with structure-analysis electronic cleansing could yield a high sensitivity for detecting flat lesions ≥4mm. The not-on-fold flat lesions were detected with higher sensitivity than on-fold flat lesions.

Full-laxative Versus Minimum-laxative Fecal-tagging CT Colonography Using 64-detector Row CT: Prospective Blinded Comparison of Diagnostic Performance, Tagging Quality, and Patient Acceptance

To compare prospectively 64-detector-row computed tomographic colonography (CTC) after a full-laxative tagging-based preparation (full preparation) with a minimum-laxative tagging-based preparation (minimum preparation) with respect to diagnostic performance in the detection of polyps, tagging quality, and patient acceptance. Consecutive 101 patients at high risk for developing colorectal cancer were alternately assigned to either a full preparation group (n = 51) or a minimum preparation group (n = 50) for fecal-tagging CTC. The full preparation consisted of administration of 2-L polyethylene glycol solution with 20 mL of sodium diatrizoate for fecal tagging. The minimum preparation consisted of ingestion of a total of 45 mL of sodium diatrizoate during the 3 days before and 10 mL of sodium picosulfate solution the night before CT. Colonoscopy was used as the reference standard. We assessed the accuracy of polyp detection and the tagging quality for each preparation. All patients were given questionnaires related to their acceptance. Per-patient sensitivity, specificity, and positive and negative predictive values for polyps > or = 6 mm were as follows: full preparation group, 97%, 92%, 88%, and 98%, respectively; minimum preparation group, 88%, 68%, 56%, and 92%, respectively. Average visual subjective tagging scores for the full and minimum preparation groups were 94.6% and 76.1%, respectively (P < .0001). Minimum preparation was better tolerated than full preparation. Although full-laxative and minimum-laxative fecal-tagging CTC yielded an equally high sensitivity in the detection of polyps > or = 6 mm, the full-laxative fecal-tagging CTC yielded a better specificity than did the minimum-laxative fecal-tagging CTC. Thus, it is desirable to offer patients an option of either full-laxative fecal-tagging CTC for highest diagnostic accuracy and ability to perform a same-day therapeutic colonoscopy without additional bowel preparation, or minimum-laxative fecal-tagging CTC for those unwilling to undergo full preparation but willing to accept moderate decrease in specificity.

Adaptive correction of the pseudo-enhancement of CT attenuation for fecal-tagging CT colonography

In fecal-tagging CT colonography (ftCTC), positive-contrast tagging agents are used for opacifying residual bowel materials to facilitate reliable detection of colorectal lesions. However, tagging agents that have high radiodensity tend to artificially elevate the observed CT attenuation of nearby materials toward that of tagged materials on Hounsfield unit (HU) scale. We developed an image-based adaptive density-correction (ADC) method for minimizing such pseudo-enhancement effect in ftCTC data. After the correction, we can confidently assume that soft-tissue materials and air are represented by their standard CT attenuations, whereas higher CT attenuations indicate tagged materials. The ADC method was optimized by use of an anthropomorphic phantom filled partially with three concentrations of a tagging agent. The effect of ADC on ftCTC was assessed visually and quantitatively by comparison of the accuracy of computer-aided detection (CAD) without and with the use of the ADC method in two different types of clinical ftCTC databases: 20 laxative ftCTC cases with 24 polyps, and 23 reduced-preparation ftCTC cases with 28 polyps. Visual evaluation indicated that ADC minimizes the observed pseudo-enhancement effect. With ADC, the free-response receiver operating characteristic curves indicating CAD performance in polyp detection yielded normalized partial area-under-curve values of 0.91 and 0.80 for the two databases, respectively, with statistically significant improvement over conventional thresholding-based approaches (p<0.05). The results indicate that ADC is a useful method for reducing the pseudo-enhancement effect and for improving CAD performance in CTC.

Fully Automated Three-Dimensional Detection of Polyps in Fecal-Tagging CT Colonography

The presence of opacified materials presents several technical challenges for automated detection of polyps in fecal-tagging computed tomography colonography (ftCTC), such as pseudo-enhancement and the distortion of the density, size, and shape of the observed lesions. We developed a fully automated computer-aided detection (CAD) scheme that addresses these issues in automated detection of polyps in ftCTC. Pseudo-enhancement was minimized by use of an adaptive density correction (ADC) method. The presence of tagging was minimized by use of an adaptive density mapping (ADM) method. We also developed a new method for automated extraction of the colonic wall within air-filled and tagged regions. The ADC and ADM parameters were optimized by use of an anthropomorphic phantom. The CAD scheme was evaluated with 32+32 cases from two types of clinical ftCTC databases. The cases in database I had full cathartic cleansing and 40 polyps > or =6 mm, and the cases in database II had reduced cathartic cleansing and 44 polyps > or =6 mm. The by-polyp detection performance of the CAD scheme was evaluated by use of a leave-one-patient-out method with five features, and the results were compared with those of a conventional CAD scheme by use of free-response receiver operating characteristic curves. The CAD scheme detected 95% and 86% of the polyps > or =6 mm with 3.6 and 4.2 false positives per scan on average in databases I and II, respectively. For polyps > or =10 mm, the detection sensitivity was 94% in database I (with one missed hyperplastic polyp) and 100% in database II at the same false-positive rate. The detection sensitivity of the new CAD scheme was approximately 20% higher than that of the conventional CAD scheme. The results show that the CAD scheme developed in this study resolves the technical challenges introduced by fecal tagging, is applicable to a variety of colon preparation regimens, and provides a performance superior to that of conventional CAD schemes.