Lung: feasibility of a method for changing tube current during low-dose helical CT

Computer-aided diagnosis of lung cancer: definition and detection of ground-glass opacity type of nodules by high-resolution computed tomography

PURPOSE

The ground-glass opacity (GGO) of lung cancer is identified only subjectively on computed tomography (CT) images as no quantitative characteristic has been defined for GGOs. We sought to define GGOs quantitatively and to differentiate between GGOs and solid-type lung cancers semiautomatically with a computer-aided diagnosis (CAD).

METHODS AND MATERIALS

High-resolution CT images of 100 pulmonary nodules (all peripheral lung cancers) were collected from our clinical records. Two radiologists traced the contours of nodules and distinguished GGOs from solid areas. The CT attenuation value of each area was measured. Differentiation between cancer types was assessed by a receiver-operating characteristic (ROC) analysis.

RESULTS

The mean CT attenuation of the GGO areas was -618.4 +/- 212.2 HU, whereas that of solid areas was -68.1 +/- 230.3 HU. CAD differentiated between solidand GGO-type lung cancers with a sensitivity of 86.0% and specificity of 96.5% when the threshold value was -370 HU. Four nodules of mixed GGOs were incorrectly classified as the solid type. CAD detected 96.3% of GGO areas when the threshold between GGO and solid areas was 194 HU.

CONCLUSION

Objective definition of GGO area by CT attenuation is feasible. This method is useful for semiautomatic differentiation between GGOs and solid types of lung cancer.

Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT

We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign (n=55) or malignant (n=52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%.

3-Dimensional Adaptive Raw-Data Filter

OBJECTIVES

To evaluate a 3-dimensional adaptive raw-data filter in reducing streak artifacts in low dose chest computed tomographic (CT) images.

METHODS

Fourteen adult patients who underwent low dose chest CT examination (parameters: 25 or 50 mAs, 120 kV) on 64-detector CTscanner were included in this study. We prepared 2 sets of contiguous 5-mm thick images by reconstruction with and without 3-dimensional adaptive raw-data filter (filter-processed and unprocessed images). Streak artifacts and visualization of peripheral vessels in both filter-processed and unprocessed images were evaluated using a 5-point scale. Upper, middle, and lower thorax were evaluated separately.

RESULTS

The difference in artifact severity was statistically significant in upper and lower thorax (P = 0.002 and 0.03, respectively), whereas it was not significant in middle thorax (P = 0.13). The difference in the visibility of peripheral pulmonary vessels was not statistically significant in all anatomical regions.

CONCLUSIONS

The 3-dimensional adaptive raw-data filter reduced streak artifacts in low dose chest CT in upper and lower thorax.

Pulmonary Nodule Detection with Low-Dose CT of the Lung: Agreement Among Radiologists

OBJECTIVE

The purpose of our study was to assess relative intra- and interobserver agreement in detecting pulmonary nodules when interpreting low-dose chest CT screening examinations.

MATERIALS AND METHODS

Two hundred ninety-three selected low-dose CT examinations of the lung were independently interpreted by three radiologists to detect and classify pulmonary nodules. The data set selected was enriched with examinations depicting pulmonary nodules. A subset of 30 examinations was interpreted twice. All pulmonary nodules greater than 1.0 mm were marked. All nodules greater than 3.0 mm were marked, measured, and scored as to their probability of being benign or malignant. Nodule-based and examination-based relative reviewer agreements were evaluated using percentage of agreement and kappa statistics. Similar assessments were performed on the subset of examinations interpreted twice.

RESULTS

The three radiologists identified a total of 470, 729, and 876 pulmonary nodules of which 395, 641, and 778 were rated as noncalcified with some level of suspicion for being malignant. Nodule-based interobserver agreement among the radiologists was poor (highest kappa value in a paired comparison, 0.120). Examination-based agreement was higher (highest kappa value in a paired comparison, 0.458). Intraobserver agreement was higher than interobserver agreement for examination-based agreement (highest kappa = 0.889) but lower for nodule-based agreement (highest kappa = -0.035). Agreement improved as the suspicion of malignancy increased.

CONCLUSION

Unaided intra- and interobserver agreement in detecting pulmonary nodules in low-dose CT of the lung is relatively low. Computer-assisted detection may provide the consistency that is needed for this purpose.

Computer-aided diagnosis: a shape classification of pulmonary nodules imaged by high-resolution CT

We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. Using a combination of circularity and second moment as quantitative measures we were able to classify pulmonary nodules in each shape group as effectively as could a radiologist. We found that pulmonary nodules with circularity < or =0.75 and second moment < or =0.18 were very likely to reveal lung cancer.

Vascular Virtual Endoluminal Visualization of Invasive Colorectal Cancer on MDCT Colonography

OBJECTIVE

The purpose of this study was to assess the utility of vascular views for visualization of invasive colorectal cancers on contrast-enhanced MDCT colonography.

CONCLUSION

By means of Hounsfield-transparency settings, we obtained virtual endoluminal images that show vascular structures and delineate invasive cancers of the colorectal wall, and we call these images "vascular views." Using this technique for contrast-enhanced MDCT colonography, we found that the increase in flow and pooling of blood related to angiogenesis of cancerous lesions is easy to identify and that this finding is useful in the detection of invasive colorectal cancers.

Dose reduction in multidetector CT using attenuation-based online tube current modulation

OBJECTIVE

This study was designed to quantify the radiation dose saved by attenuation-based online tube current modulation applied to multidetector CT (MDCT) of the adult trunk as a function of effective milliampere-second (mAs) presets, sex, and body habitus. SUBJECTS AND METHODS. One hundred twenty patients underwent MDCT of the trunk (60 thoracic, 60 abdominal) with an attenuation-based online tube current modulation. Consecutive acquisitions at standard and two lower effective mAs presets were obtained in each patient. Mean percentage effective mAs reductions were compared for each effective mAs preset, taking into account sex and body mass index.

RESULTS

Mean effective mAs reduction was 16.9% and 20.0% for the chest and the abdomen, respectively. Mean percentage effective mAs reductions were found to be significantly different for sex (chest, p = 0.003; abdomen, p = 0.002) but not significantly different for the different effective mAs presets or body mass index.

CONCLUSION

Attenuation-based online tube current modulation used with MDCT should be considered as a secondary tool of radiation dose reduction because it saves as much as 20% of the radiation dose on the adult trunk, regardless of initial mAs preset. However, initial decreases of mAs presets by the physician should be considered the primary tool for radiation dose reduction.